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Aptamers are single-stranded DNA (ssDNA) or RNA molecules that can bind specifically and with high affinity to target molecules due to their unique three-dimensional structure. For this reason, they are often compared to antibodies and sometimes even referred to as “chemical antibodies”. They are simple and inexpensive to synthesize, easy to modify, and smaller than conventional antibodies. Enzymes, especially hydrolases, are interesting targets in this context. This class of enzymes is capable of hydrolytically cleaving various macromolecules such as proteins, as well as smaller molecules such as antibiotics. Hence, they play an important role in many biological processes including diseases and their treatment. Hydrolase detection as well as the understanding of their function is therefore of great importance for diagnostics and therapy. Due to their various desirable features compared to antibodies, aptamers are being discussed as alternative agents for analytical and diagnostic use in various applications. The use of aptamers in therapy is also frequently investigated, as the binding of aptamers can have effects on the catalytic activity, protein-protein interactions, or proteolytic cascades. Aptamers are generated by an in vitro selection process. Potential aptamer candidates are selected from a pool of enriched nucleic acid sequences with affinity to the target, and their binding affinity and specificity is investigated. This is one of the most important steps in aptamer generation to obtain specific aptamers with high affinity for use in analytical and diagnostic applications. The binding properties or binding domains and their effects on enzyme functions form the basis for therapeutic applications.
In this work, the binding properties of DNA aptamers against two different hydrolases were investigated. In view of their potential utility for analytical methods, aptamers against human urokinase (uPA) and New Delhi metallo-β-lactamase-1 (NDM-1) were evaluated for their binding affinity and specificity using different methods. Using the uPA aptamers, a protocol for measuring the binding kinetics of an aptamer-protein-interaction by surface plasmon resonance spectroscopy (SPR) was developed. Based on the increased expression of uPA in different types of cancer, uPA is discussed as a prognostic and diagnostic tumor marker. As uPA aptamers showed different binding sites on the protein, microtiter plate-based aptamer sandwich assay systems for the detection of uPA were developed. Because of the function of urokinase in cancer cell proliferation and metastasis, uPA is also discussed as a therapeutic target. In this regard, the different binding sites of aptamers showed different effects on uPA function. In vitro experiments demonstrated both inhibition of uPA binding to its receptor as well as the inhibition of uPA catalytic activity for different aptamers. Thus, in addition to their specificity and affinity for their targets, the utility of the aptamers for potential diagnostic and therapeutic applications was demonstrated. First, as an alternative inhibitor of human urokinase for therapeutic purposes, and second, as valuable recognition molecules for the detection of urokinase, as a prognostic and diagnostic marker for cancer, and for NDM-1 to detect resistance to carbapenem antibiotics.
Search for light primordial black holes with VERITAS using gamma γ-ray and optical observations
(2023)
The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four imaging atmospheric Cherenkov telescopes (IACTs). VERITAS is sensitive to very-high-energy gamma-rays in the range of 100 GeV to >30 TeV. Hypothesized primordial black holes (PBHs) are attractive targets for IACTs. If they exist, their potential cosmological impact reaches beyond the candidacy for constituents of dark matter. The sublunar mass window is the largest unconstrained range of PBH masses. This thesis aims to develop novel concepts searching for light PBHs with VERITAS. PBHs below the sublunar window lose mass due to Hawking radiation. They would evaporate at the end of their lifetime, leading to a short burst of gamma-rays. If PBHs formed at about 10^15 g, the evaporation would occur nowadays. Detecting these signals might not only confirm the existence of PBHs but also prove the theory of Hawking radiation. This thesis probes archival VERITAS data recorded between 2012 and 2021 for possible PBH signals. This work presents a new automatic approach to assess the quality of the VERITAS data. The array-trigger rate and far infrared temperature are well suited to identify periods with poor data quality. These are masked by time cuts to obtain a consistent and clean dataset which contains about 4222 hours. The PBH evaporations could occur at any location in the field of view or time within this data. Only a blind search can be performed to identify these short signals. This thesis implements a data-driven deep learning based method to search for short transient signals with VERITAS. It does not depend on the modelling of the effective area and radial acceptance. This work presents the first application of this method to actual observational IACT data. This thesis develops new concepts dealing with the specifics of the data and the transient detection method. These are reflected in the developed data preparation pipeline and search strategies. After correction for trial factors, no candidate PBH evaporation is found in the data. Thus, new constraints of the local rate of PBH evaporations are derived. At the 99% confidence limit it is below <1.07 * 10^5 pc^-3 yr^-1. This constraint with the new, independent analysis approach is in the range of existing limits for the evaporation rate.
This thesis also investigates an alternative novel approach to searching for PBHs with IACTs. Above the sublunar window, the PBH abundance is constrained by optical microlensing studies. The sampling speed, which is of order of minutes to hours for traditional optical telescopes, is a limiting factor in expanding the limits to lower masses. IACTs are also powerful instruments for fast transient optical astronomy with up to O(ns) sampling. This thesis investigates whether IACTs might constrain the sublunar window with optical microlensing observations. This study confirms that, in principle, the fast sampling speed might allow extending microlensing searches into the sublunar mass window. However, the limiting factor for IACTs is the modest sensitivity to detect changes in optical fluxes. This thesis presents the expected rate of detectable events for VERITAS as well as prospects of possible future next-generation IACTs. For VERITAS, the rate of detectable microlensing events in the sublunar range is ~10^-6 per year of observation time. The future prospects for a 100 times more sensitive instrument are at ~0.05 events per year.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
In the last century, several astronomical measurements have supported that a significant percentage (about 22%) of the total mass of the Universe, on galactic and extragalactic scales, is composed of a mysterious ”dark” matter (DM). DM does not interact with the electromagnetic force; in other words it does not reflect, absorb or emit light. It is possible that DM particles are weakly interacting massive particles (WIMPs) that can annihilate (or decay) into Standard Model (SM) particles, and modern very- high-energy (VHE; > 100 GeV) instruments such as imaging atmospheric Cherenkov telescopes (IACTs) can play an important role in constraining the main properties of such DM particles, by detecting these products. One of the most privileged targets where to look for DM signal are dwarf spheroidal galaxies (dSphs), as they are expected to be high DM-dominated objects with a clean, gas-free environment. Some dSphs could be considered as extended sources, considering the angular resolution of IACTs; their angu- lar resolution is adequate to detect extended emission from dSphs. For this reason, we performed an extended-source analysis, by taking into account in the unbinned maximum likelihood estimation both the energy and the angular extension dependency of observed events. The goal was to set more constrained upper limits on the velocity-averaged cross-section annihilation of WIMPs with VERITAS data. VERITAS is an array of four IACTs, able to detect γ-ray photons ranging between 100 GeV and 30 TeV. The results of this extended analysis were compared against the traditional spectral analysis. We found that a 2D analysis may lead to more constrained results, depending on the DM mass, channel, and source. Moreover, in this thesis, the results of a multi-instrument project are presented too. Its goal was to combine already published 20 dSphs data from five different experiments, such as Fermi-LAT, MAGIC, H.E.S.S., VERITAS and HAWC, in order to set upper limits on the WIMP annihilation cross-section in the widest mass range ever reported.
The first part of the thesis studies the properties of fast mode in magneto hydro-dynamic (MHD) turbulence. 1D and 3D numerical simulations are carried out to generate decaying fast mode MHD turbulence. The injection of waves are carried out in a collinear and isotropic fashion to generate fast mode turbulence. The properties of fast mode turbulence are analyzed by studying their energy spectral density, 2D structure functions and energy decay/cascade time. The injection wave vector is varied to study the dependence of the above properties on the injection wave vectors. The 1D energy spectrum obtained for the velocity and magnetic fields has 𝐸 (𝑘) ∝ 𝑘−2. The 2D energy spectrum and 2D structure functions in parallel and perpendicular directions shows that fast mode turbulence generated is isotropic in nature. The cascade/decay rate of fast mode MHD turbulence is proportional to 𝑘−0.5 for different kinds of wave vector injection. Simulations are also carried out in 1D and 3D to compare balanced and imbalanced turbulence. The results obtained shows that while 1D imbalanced turbulence decays faster than 1D balanced turbulence, there is no difference in the decay of 3D balanced and imbalanced turbulence for the current resolution of 512 grid points.
"The second part of the thesis studies cosmic ray (CR) transport in driven MHD turbulence and is strongly dependent on it’s properties. Test particle simulations are carried out to study CR interaction with both total MHD turbulence and decomposed MHD modes. The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence. The results confirms that the fast modes dominate the CR propagation, whereas Alfvén, slow modes are much less efficient with similar pitch angle scattering rates. The cross field transport on large and small scales are investigated next. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by 𝑀𝜁𝐴 compared to the parallel diffusion coefficients, with 𝜁 closer to 4 in Alfvén modes than that in total turbulence as theoretically expected. For the CR transport on scales smaller than the turbulence injection scale 𝐿, both the local and global magnetic reference frames are adopted. Super diffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfvén modes show clear Richardson diffusion in the local reference frame. The diffusion transition smoothly from the Richardson’s one with index 1.5 to normal diffusion as particle’s mean free path decreases from 𝜆∥ ≫ 𝐿 to 𝜆∥ ≪ 𝐿. These results have broad applications to CRs in various astrophysical environments".
Aging is a complex process characterized by several factors, including loss of genetic and epigenetic information, accumulation of chronic oxidative stress, protein damage and aggregates and it is becoming an emergent drug target. Therefore, it is the utmost importance to study aging and agerelated diseases, to provide treatments to develop a healthy aging process. Skeletal muscle is one of the earliest tissues affected by age-related changes with progressive loss of muscle mass and function from 30 years old, effect known as sarcopenia. Several studies have shown the accumulation of protein aggregates in different animal models, as well as in humans, suggesting impaired proteostasis, a hallmark of aging, especially regarding degradation systems. Thus, different publications have explored the role of the main proteolytic systems in skeletal muscle from rodents and humans, like ubiquitin proteasomal system (UPS) and autophagy lysosomal system (ALS), however with contradictory results. Yet, most of the published studies are performed in muscles that comprise more than one fiber type, that means, muscles composed by slow and fast fibers. These fiber types, exhibit different metabolism and contraction speed; the slow fibers or type I display an oxidative metabolism, while fast fibers function towards a glycolytic metabolism ranging from fast oxidative to fast glycolytic fibers. To this extent, the aim of this thesis sought to understand on how aging impacts both fiber types not only regarding proteostasis but also at a metabolome and transcriptome network levels. Therefore, the first part of this thesis, presents the differences between slow oxidative (from Soleus muscle) and fast glycolytic fibers (Extensor digitorum longus, EDL) in terms of degradation systems and how they cope with oxidative stress during aging, while the second part explores the differences between young and old EDL muscle transcriptome and metabolome, unraveling molecular features. More specifically, the results from the present work show that slow oxidative muscle performs better at maintaining the function of UPS and ALS during aging than EDL muscle, which is clearly affected, accounting for the decline in the catalytic activity rates and accumulation of autophagy-related proteins. Strinkingly, transcriptome and metabolome analyses reveal that fast glycolytic muscle evidences significant downregulation of mitochondrial related processes and damaged mitochondria morphology during aging, despite of having a lower oxidative metabolism compared to oxidative fibers. Moreover, predictive analyses reveal a negative association between aged EDL gene signature and lifespan extending interventions such as caloric restriction (CR). Although, CR intervention does not alter the levels of mitochondrial markers in aged EDL muscle, it can reverse the higher mRNA levels of muscle damage markers. Together, the results from this thesis give new insights about how different metabolic muscle fibers cope with age-related changes and why fast glycolytic fibers are more susceptible to aging than slow oxidative fibers.
A biological trade-off situation denotes the dependence between traits whereby an increase in the value of one of the traits leads to a decrease in the value of at least one of the others. Understanding trade-offs in cellular systems is relevant to understanding the limits and constraints to tuning desired phenotypes. Therefore, it is mainly the case for rates (i.e. fluxes) of biochemical reactions that shape not only molecular traits, like metabolite concentrations but also determine physiological traits, like growth. Intracellular fluxes are the final phenotype from transcriptional and (post)translational regulation. Quantifying intracellular fluxes provides insights into cellular physiology under particular growth conditions and can be used to characterize the metabolic activity of different pathways. However, estimating fluxes from labelling experiments is labour-intensive; therefore, developing approaches to accurately and precisely predict intracellular fluxes is essential. This thesis addresses two main problems: (i) identifying flux trade-offs and (ii) predicting accurate and precise reaction flux at a genome-scale level. To this end, the concept of an absolute flux trade-off is defined, and a constraint-based approach, termed FluTO, was developed to identify absolute flux trade-offs. FluTO is cast as a mixed integer programming approach applied to genome-scale metabolic models of E. coli, S. cerevisiae, and A. thaliana, imposing realistic constraints on growth and nutrient uptake.. The findings showed that trade-offs are not only species-specific but also specific to carbon sources. In addition, we found that different models of a single species have a different number of reactions in trade-offs. We also showed that absolute flux trade-offs depend on the biomass reaction used to model the growth of A. thaliana under different carbon and nitrogen conditions. Findings reflect the strong relation between nitrogen, carbon, and sulphur metabolisms in the leaves of C3 plants. The concept of relative trade-offs was introduced to further study trade-offs in metabolic networks. A constraint-based approach, FluTOr, was proposed to identify reactions whose fluxes are in relative trade-off concerning an optimized fitness-related cellular task, like growth. FluTOr was employed to find the relative flux trade-offsin the genome-scale metabolic networks of E. coli, S. cerevisiae, and A. thaliana. The results showed that in contrast to the A. thaliana model, the relative trade-offs in the two microorganisms depend on the carbon source, reflecting the differences in the underlying metabolic network. Furthermore, applying FluTOr also showed that reactions that participated in relative trade-offs were implicated in cofactor biosynthesis in the two microorganisms. Prediction of reaction fluxes in the constraint-based metabolic framework is usually performed by parsimonious flux balance analysis (pFBA), employing the principle of efficient usage of protein resources. However, we argued that principles related to the coordination of flux values, neglected in previous studies, provide other means to predict intracellular fluxes. To this end, we designed a constraint-based approach, termed complex-balanced FBA (cbFBA), to predict steady-state flux distributions that maximize the number of balanced complexes in a flux distribution, whereby multi-reaction dependencies are maximized. The comparative analysis showed a better agreement of the flux distributions resulting from cbFBA compared to pFBA with experimentally measured fluxes from 17 E. coli strains and 26 S. cerevisiae knock-out mutants. The results also showed that the predictions from cbFBA are more precise than those from pFBA since cbFBA results in a smaller space of alternative solutions than pFBA.
The emerging threat of antibiotic-resistant bacteria has become a global challenge in the last decades, leading to a rising demand for alternative treatments for bacterial infections. One approach is to target the bacterial cell envelope, making understanding its biophysical properties crucial. Specifically, bacteriophages use the bacterial envelope as an entry point to initiate infection, and they are considered important building blocks of new antibiotic strategies against drug-resistant bacteria.. Depending on the structure of the cell wall, bacteria are classified as Gram-negative and Gram-positive. Gram-negative bacteria are equipped with a complex cell envelope composed of two lipid membranes enclosing a rigid peptidoglycan layer. The synthesis machinery of the Gram-negative cell envelope is the target of antimicrobial agents, including new physical sanitizing procedures addressing the outer membrane (OM). It is therefore very important to study the biophysical properties of the Gram-negative bacterial cell envelope. The high complexity of the Gram-negative OM sets the demand for a model system in which the contribution of individual components can be evaluated separately. In this respect, giant unilamellar vesicles (GUVs) are promising membrane systems to study membrane properties while controlling parameters such as membrane composition and surrounding medium conditions.
The aim of this work was to develop methods and approaches for the preparation and characterization of a GUV-based membrane model that mimics the OM of the Gram-negative cell envelope. A major component of the OM is the lipopolysaccharide (LPS) on the outside of the OM heterobilayer. The vesicle model was designed to contain LPS in the outer leaflet and lipids in the inner leaflet. Furthermore, the interaction of the prepared LPS-GUVs with bacteriophages was tested. LPS containing GUVs were prepared by adapting the inverted emulsion technique to meet the challenging properties of LPS, namely their high self-aggregation rate in aqueous solutions. Notably, an additional emulsification step together with the adaption of solution conditions was employed to asymmetrically incorporate LPS containing long polysaccharide chains into the artificial membranes. GUV membrane asymmetry was verified with a fluorescence quenching assay. Since the necessary precautions for handling the quenching agent sodium dithionite are often underestimated and poorly described, important parameters were tested and identified to obtain a stable and reproducible assay. In the context of varied LPS incorporation, a microscopy-based technique was introduced to determine the LPS content on individual GUVs and to directly compare vesicle properties and LPS coverage. Diffusion coefficient measurements in the obtained GUVs showed that increasing LPS concentrations in the membranes resulted in decreased diffusivity.
Employing LPS-GUVs we could demonstrate that a Salmonella bacteriophage bound with high specificity to its LPS receptor when presented at the GUV surface, and that the number of bound bacteriophages scaled with the amount of presented LPS receptor. In addition to binding, the bacteriophages were able to eject their DNA into the vesicle lumen. LPS-GUVs thus provide a starting platform for bottom-up approaches for the generation of more complex membranes, in which the effects of individual components on the membrane properties and the interaction with antimicrobial agents such as bacteriophages could be explored.
Solar photocatalysis is the one of leading concepts of research in the current paradigm of sustainable chemical industry. For actual practical implementation of sunlight-driven catalytic processes in organic synthesis, a cheap, efficient, versatile and robust heterogeneous catalyst is necessary. Carbon nitrides are a class of organic semiconductors who are known to fulfill these requirements.
First, current state of solar photocatalysis in economy, industry and lab research is overviewed, outlining EU project funding, prospective synthetic and reforming bulk processes, small scale solar organic chemistry, and existing reactor designs and prototypes, concluding feasibility of the approach.
Then, the photocatalytic aerobic cleavage of oximes to corresponding aldehydes and ketones by anionic poly(heptazine imide) carbon nitride is discussed. The reaction provides a feasible method of deprotection and formation of carbonyl compounds from nitrosation products and serves as a convenient model to study chromoselectivity and photophysics of energy transfer in heterogeneous photocatalysis.
Afterwards, the ability of mesoporous graphitic carbon nitride to conduct proton-coupled electron transfer was utilized for the direct oxygenation of 1,3-oxazolidin-2-ones to corresponding 1,3-oxazlidine-2,4-diones. This reaction provides an easier access to a key scaffold of diverse types of drugs and agrochemicals.
Finally, a series of novel carbon nitrides based on poly(triazine imide) and poly(heptazine imide) structure was synthesized from cyanamide and potassium rhodizonate. These catalysts demonstrated a good performance in a set of photocatalytic benchmark reactions, including aerobic oxidation, dual nickel photoredox catalysis, hydrogen peroxide evolution and chromoselective transformation of organosulfur precursors.
Concluding, the scope of carbon nitride utilization for net-oxidative and net-neutral photocatalytic processes was expanded, and a new tunable platform for catalyst synthesis was discovered.
Biogeochemical analyses of lacustrine environments are well-established methods that allow exploring and understanding complex systems in the lake ecosystem. However, most were conducted in temperate lakes controlled by entirely different physical conditions than in tropical climates. The most important difference between the temperate and tropical lakes is lacking seasonal temperature fluctuations in the latter, which leads to a stable temperature gradient in the water column. Thus, the water column in tropical latitudes generally is void of perturbations that can be seen in their temperate counterparts. Permanent stratification in the water column provides optimal conditions for intact sedimentation. The geochemical processes in the water column and the weathering process in the distinct lithology in the catchment leads to the different biogeochemical characteristic in the sediment. Conducting a biogeochemical study in this lake sediment, especially in the Sediment Water Interface (SWI) helps reveal the sedimentation and diagenetic process records influenced by the internal or external loading. Lake Sentani, the study area, is one of the thousands of lakes in Indonesia and located in the Papua province. This tropical lake has a unique feature, as it consists of four interconnected sub-basins with different water depths. More importantly, its catchment is comprised of various different lithologies. Hence, its lithological characteristics are highly diverse, and range from mafic and ultramafic rocks to clastic sediment and carbonates. Each sub-basin receives a distinct sediment input. Equally important, besides the natural loading, Lake Sentani is also influenced by anthropogenic input. Previous studies have elaborated that there is an increase in population growth rate around the lake which has direct consequences on eutrophication. Considering these factors, the government of The Republic of Indonesia put Lake Sentani on the list of national priority lakes for restoration. This thesis aims to develop a fundamental understanding of Lake Sentani's sedimentary geochemistry and geomicrobiology with a special focus on the effects of different lithologies and anthropogenic pressures in the catchment area. We conducted geochemical and geomicrobiology research on Lake Sentani to meet this objective. We investigated geochemical characteristics in the water column, porewater, and sediment core of the four sub-basins. Additional to direct investigations of the lake itself, we also studied the sediments in the tributary rivers, of which some are ephemeral, as well as the river mouths, as connections between riverine and the lacustrine habitat. The thesis is composed of three main publications about Lake Sentani and supported by several publications that focus on other tropical lakes in Indonesia. The first main publication investigates the geochemical characterization of the water column, porewater, and surface sediment (upper 40-50 cm) from the center of the four sub-basins. It reveals that besides catchment lithology, the water column heavily influences the geochemical characteristics in the lake sediments and their porewater. The findings indicate that water column stratification has a strong influence on overall chemistry. The four sub-basins are very different with regard to their water column chemistry. Based on the physicochemical profiles, especially dissolved oxygen, one sub-basin is oxygenated, one intermediate i.e. just reaches oxygen depletion at the sediment-water interface, and two sub-basins are fully meromictic. However, all four sub-basins share the same surface water chemistry. The structure of the water column creates differences on the patterns of anions and cations in the porewater. Likewise, the distinct differences in geochemical composition between the sub-basins show that the lithology in the catchment affects the geochemical characteristic in the sediment. Overall, water column stratification and particularly bottom water oxygenation strongly influence the overall elemental composition of the sediment and porewater composition. The second publication reveals differences in surface sediment composition between habitats, influenced by lithological variations in the catchment area. The macro-element distribution shows that the geochemical characteristics between habitats are different. Furthermore, the geochemical composition also indicates a distinct distribution between the sub-basins. The geochemical composition of the eastern sub-basin suggests that lithogenic elements are more dominant than authigenic elements. This is also supported by sulfide speciation, particle distribution, and smear slide data. The third publication is a geomicrobiological study of the surface sediment. We compare the geochemical composition of the surface sediment and its microbiological composition and compare the different signals. Next Generation Sequencing (NGS) of the 16S rRNA gene was applied to determine the microbial community composition of the surface sediment from a great number of locations. We use a large number of sampling sites in all four sub-basins as well as in the rivers and river mouths to illustrate the links between the river, the river mouth, and the lake. Rigorous assessment of microbial communities across the diverse Lake Sentani habitats allowed us to study some of these links and report novel findings on microbial patterns in such ecosystems. The main result of the Principal Coordinates Analysis (PCoA) based on microbial community composition highlighted some commonalities but also differences between the microbial community analysis and the geochemical data. The microbial community in rivers, river mouths and sub-basins is strongly influenced by anthropogenic input from the catchment area. Generally, Bacteroidetes and Firmicutes could be an indicator for river sediments. The microbial community in the river is directly influenced by anthropogenic pressure and is markedly different from the lake sediment. Meanwhile, the microbial community in the lake sediment reflects the anoxic environment, which is prevalent across the lake in all sediments below a few mm burial depth. The lake sediments harbour abundant sulfate reducers and methanogens. The microbial communities in sediments from river mouths are influenced by both rivers and lake ecosystems. This study provides valuable information to understand the basic processes that control biogeochemical cycling in Lake Sentani. Our findings are critical for lake managers to accurately assess the uncertainties of the changing environmental conditions related to the anthropogenic pressure in the catchment area. Lake Sentani is a unique study site directly influenced by the different geology across the watershed and morphometry of the four studied basins. As a result of these factors, there are distinct geochemical differences between the habitats (river, river mouth, lake) and the four sub-basins. In addition to geochemistry, microbial community composition also shows differences between habitats, although there are no obvious differences between the four sub-basins. However, unlike sediment geochemistry, microbial community composition is impacted by human activities. Therefore, this thesis will provide crucial baseline data for future lake management.
The shallow Earth’s layers are at the interplay of many physical processes: some being driven by atmospheric forcing (precipitation, temperature...) whereas others take their origins at depth, for instance ground shaking due to seismic activity. These forcings cause the subsurface to continuously change its mechanical properties, therefore modulating the strength of the surface geomaterials and hydrological fluxes. Because our societies settle and rely on the layers hosting these time-dependent properties, constraining the hydro-mechanical dynamics of the shallow subsurface is crucial for our future geographical development. One way to investigate the ever-changing physical changes occurring under our feet is through the inference of seismic velocity changes from ambient noise, a technique called seismic interferometry. In this dissertation, I use this method to monitor the evolution of groundwater storage and damage induced by earthquakes. Two research lines are investigated that comprise the key controls of groundwater recharge in steep landscapes and the predictability and duration of the transient physical properties due to earthquake ground shaking. These two types of dynamics modulate each other and influence the velocity changes in ways that are challenging to disentangle. A part of my doctoral research also addresses this interaction. Seismic data from a range of field settings spanning several climatic conditions (wet to arid climate) in various seismic-prone areas are considered. I constrain the obtained seismic velocity time-series using simple physical models, independent dataset, geophysical tools and nonlinear analysis. Additionally, a methodological development is proposed to improve the time-resolution of passive seismic monitoring.
Reactive eutectic media based on ammonium formate for the valorization of bio-sourced materials
(2023)
In the last several decades eutectic mixtures of different compositions were successfully used as solvents for vast amount of chemical processes, and only relatively recently they were discovered to be widely spread in nature. As such they are discussed as a third liquid media of the living cell, that is composed of common cell metabolites. Such media may also incorporate water as a eutectic component in order to regulate properties such as enzyme activity or viscosity. Taking inspiration form such sophisticated use of eutectic mixtures, this thesis will explore the use of reactive eutectic media (REM) for organic synthesis. Such unconventional media are characterized by the reactivity of their components, which means that mixture may assume the role of the solvent as well as the reactant itself.
The thesis focuses on novel REM based on ammonium formate and investigates their potential for the valorization of bio-sourced materials. The use of REM allows the performance of a number of solvent-free reactions, which entails the benefits of a superior atom and energy economy, higher yields and faster rates compared to reactions in solution. This is evident for the Maillard reaction between ammonium formate and various monosaccharides for the synthesis of substituted pyrazines as well as for a Leuckart type reaction between ammonium formate and levulinic acid for the synthesis of 5-methyl-2-pyrrolidone. Furthermore, reaction of ammonium formate with citric acid for the synthesis of yet undiscovered fluorophores, shows that synthesis in REM can open up unexpected reaction pathways.
Another focus of the thesis is the study of water as a third component in the REM. As a result, the concept of two different dilution regimes (tertiary REM and in REM in solvent) appears useful for understanding the influence of water. It is shown that small amounts of water can be of great benefit for the reaction, by reducing viscosity and at the same time increasing reaction yields.
REM based on ammonium formate and organic acids are employed for lignocellulosic biomass treatment. The thesis thereby introduces an alternative approach towards lignocellulosic biomass fractionation that promises a considerable process intensification by the simultaneous generation of cellulose and lignin as well as the production of value-added chemicals from REM components. The thesis investigates the generated cellulose and the pathway to nanocellulose generation and also includes the structural analysis of extracted lignin.
Finally, the thesis investigates the potential of microwave heating to run chemical reactions in REM and describes the synergy between these two approaches. Microwave heating for chemical reactions and the use of eutectic mixtures as alternative reaction media are two research fields that are often described in the scope of green chemistry. The thesis will therefore also contain a closer inspection of this terminology and its greater goal of sustainability.
Depressive disorders are associated with reduced life satisfaction and ability to work. The waiting time for psychotherapy in Germany is currently between three and six months. Accordingly, there is a need for alternative, evidence-based treatment options that are made accessible to patients at a low threshold. A large number of empirical studies prove the effectiveness of exercise in mild and moderate depression. For further conceptualization and quality assurance of exercise as a treatment option, it is necessary to understand the concrete mechanisms of action. In addition to physiological factors, psychological factors also play a role in the effect. As a meta-theory of human experience and behavior, Self-Determination Theory (SDT) provides a useful frame for understanding psychological mechanisms of action with concrete implications for treatment practice. The conceptual extension of SDT to include the frustration of basic psychological needs in addition to need satisfaction is proving useful in the study of mental illness. The first part of this dissertation consists of two publications that validate relevant measurement instruments in this context. The first questionnaire measures the extent of generally experienced satisfaction and frustration of the basic psychological needs for autonomy, competence, and relatedness. The second questionnaire measures the experienced satisfaction of needs by the instructor (here: exercise therapist). The second part of the dissertation includes two publications that examine and classify the satisfaction and frustration of basic psychological needs in depressive symptoms. Differences in the extent of need satisfaction and need frustration between a sample with depression and a sample without depressive symptoms are examined. Further, the relationship between need frustration and depressive symptoms is placed in the context of established pathological processes (emotional dysregulation, rumination). The main findings of this work show that by adding the dimension of need frustration to Basic Psychological Needs Theory, SDT now covers a broader spectrum on the health-disease continuum. In doing so, SDT focuses on the psychological impact of social environments. In addition to the nonfulfillment of basic psychological needs, it is primarily experienced need frustration that is a general vulnerability factor for the occurrence of psychological illness. Moreover, the unbalanced satisfaction of basic psychological needs possibly indicates a conflicting experience between the needs. For the treatment practice it can be deduced that an autonomy-supporting atmosphere, which enables the balanced satisfaction of all three needs, is central for the treatment success.
This thesis explores the variation in coreference patterns across language modes (i.e., spoken and written) and text genres. The significance of research on variation in language use has been emphasized in a number of linguistic studies. For instance, Biber and Conrad [2009] state that “register/genre variation is a fundamental aspect of human language” and “Given the ubiquity of register/genre variation, an understanding of how linguistic features are used in patterned ways across text varieties is of central importance for both the description of particular languages and the development of cross-linguistic theories of language use.”[p.23]
We examine the variation across genres with the primary goal of contributing to the body of knowledge on the description of language use in English. On the computational side, we believe that incorporating linguistic knowledge into learning-based systems can boost the performance of automatic natural language processing systems, particularly for non-standard texts. Therefore, in addition to their descriptive value, the linguistic findings we provide in this study may prove to be helpful for improving the performance of automatic coreference resolution, which is essential for a good text understanding and beneficial for several downstream NLP applications, including machine translation and text summarization.
In particular, we study a genre of texts that is formed of conversational interactions on the well-known social media platform Twitter. Two factors motivate us: First, Twitter conversations are realized in written form but resemble spoken communication [Scheffler, 2017], and therefore they form an atypical genre for the written mode. Second, while Twitter texts are a complicated genre for automatic coreference resolution, due to their widespread use in the digital sphere, at the same time they are highly relevant for applications that seek to extract information or sentiments from users’ messages. Thus, we are interested in discovering more about the linguistic and computational aspects of coreference in Twitter conversations. We first created a corpus of such conversations for this purpose and annotated it for coreference. We are interested in not only the coreference patterns but the overall discourse behavior of Twitter conversations. To address this, in addition to the coreference relations, we also annotated the coherence relations on the corpus we compiled. The corpus is available online in a newly developed form that allows for separating the tweets from their annotations.
This study consists of three empirical analyses where we independently apply corpus-based, psycholinguistic and computational approaches for the investigation of variation in coreference patterns in a complementary manner. (1) We first make a descriptive analysis of variation across genres through a corpus-based study. We investigate the linguistic aspects of nominal coreference in Twitter conversations and we determine how this genre relates to other text genres in spoken and written modes. In addition to the variation across genres, studying the differences in spoken-written modes is also in focus of linguistic research since from Woolbert [1922]. (2) In order to investigate whether the language mode alone has any effect on coreference patterns, we carry out a crowdsourced experiment and analyze the patterns in the same genre for both spoken and written modes. (3) Finally, we explore the potentials of domain adaptation of automatic coreference resolution (ACR) for the conversational Twitter data. In order to answer the question of how the genre of Twitter conversations relates to other genres in spoken and written modes with respect to coreference patterns, we employ a state-of-the-art neural ACR model [Lee et al., 2018] to examine whether ACR on Twitter conversations will benefit from mode-based separation in out-of-domain training data.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Childhood compared to adolescence and adulthood is characterized by high neuroplasticity represented by accelerated cognitive maturation and rapid cognitive developmental trajectories. Natural growth, biological maturation and permanent interaction with the physical and social environment fosters motor and cognitive development in children. Of note, the promotion of physical activity, physical fitness, and motor skill learning at an early age is mandatory first, as these aspects are essential for a healthy development and an efficient functioning in everyday life across the life span and second, physical activity behaviors and lifestyle habits tend to track from childhood into adulthood.
The main objective of the present thesis was to optimize and deepen the knowledge of motor and cognitive performance in young children and to develop an effective and age-appropriate exercise program feasible for the implementation in kindergarten and preschool settings. A systematic review with meta-analysis was conducted to examine the effectiveness of fundamental movement skill and exercise interventions in healthy preschool-aged children. Further, the relation between measures of physical fitness (i.e., static balance, muscle strength, power, and coordination) and attention as one domain of cognitive performance in preschool-aged children was analyzed. Subsequently, effects of a strength-dominated kindergarten-based exercise program on physical fitness components (i.e., static balance, muscle strength, power, and coordination) and cognitive performance (i.e., attention) compared to a usual kindergarten curriculum was examined.
The systematic review included trials focusing on healthy young children in kindergarten or preschool settings that applied fundamental movement skill-enhancing intervention programs of at least 4 weeks and further reported standardized motor skill outcome measures for the intervention and the control group. Children aged 4-6 years from three kindergartens participated in the cross-sectional and the longitudinal study. Product-orientated measures were conducted for the assessment of muscle strength (i.e., handgrip strength), muscle power (i.e., standing long jump), balance (i.e., timed single-leg stand), coordination (hopping on right/left leg), and attentional span (i.e., “Konzentrations-Handlungsverfahren für Vorschulkinder” [concentration-action procedure for preschoolers]).
With regards to the scientific literature, exercise and fundamental movement skill interventions are an effective method to promote overall proficiency in motor skills (i.e., object control and locomotor skills) in preschool children particularly when conducted by external experts with a duration of 4 weeks to 5 months. Moreover, significant medium associations were found between the composite score of physical fitness and attention as well as between coordination separately and attention in children aged 4-6 years. A 10-weeks strength-dominated exercise program implemented in kindergarten and preschool settings by educated and trained kindergarten teachers revealed significant improvements for the standing long jump test and the Konzentrations-Handlungsverfahren of intervention children compared to children of the control group.
The findings of the present thesis imply that fundamental movement skill and exercise interventions improve motor skills (i.e., locomotor and object control skills). Nonetheless, more high-quality research is needed. Additionally, physical fitness, particularly high performance in complex fitness components (i.e., coordination measured with the hopping on one leg test), tend to predict attention in preschool age. Furthermore, an exercise program including strength-dominated exercises, fundamental movement skills and elements of gymnastics has a beneficial effect on jumping performance with a concomitant trend toward improvements in attentional capacity in healthy preschool children. Finally, it is recommended to start early with the integration of muscular fitness (i.e., muscle strength, muscle power, muscular endurance) next to coordination, agility, balance, and fundamental movement skill exercises into regular physical activity curriculums in kindergarten settings.
The relevance of physical fitness for children’s and adolescents’ health is indisputable and it is crucial to regularly assess and evaluate children’s and adolescents’ individual physical fitness development to detect potential negative health consequences in time. Physical fitness tests are easy-to-administer, reliable, and valid which is why they should be widely used to provide information on performance development and health status of children and adolescents. When talking about development of physical fitness, two perspectives can be distinguished. One perspective is how the physical fitness status of children and adolescents changed / developed over the past decades (i.e., secular trends). The other perspective covers the analyses how physical fitness develops with increasing age due to growth and maturation processes. Although, the development of children’s and adolescents’ physical fitness has been extensively described and analyzed in the literature, still some questions remain to be uncovered that will be addressed in the present doctoral thesis.
Previous systematic reviews and meta-analyses have examined secular trends in children’s and adolescents’ physical fitness. However, considering that those analyses are by now 15 years old and that updates are available only to limited components of physical fitness, it is time to re-analyze the literature and examine secular trends for selected components of physical fitness (i.e., cardiorespiratory endurance, muscle strength, proxies of muscle power, and speed). Fur-thermore, the available studies on children’s development of physical fitness as well as the ef-fects of moderating variables such as age and sex have been investigated within a long-term ontogenetic perspective. However, the effects of age and sex in the transition from pre-puberty to puberty in the ninth year of life using a short-term ontogenetic perspective and the effect of timing of school enrollment on children’s development of physical fitness have not been clearly identified. Therefore, the present doctoral thesis seeks to complement the knowledge of children’s and adolescents’ physical fitness development by updating secular trend analysis in selected components of physical fitness, by examining short-term ontogenetic cross-sectional developmental differences in children`s physical fitness, and by comparing physical fitness of older- and younger-than-keyage children versus keyage-children. These findings provide valuable information about children’s and adolescents’ physical fitness development to help prevent potential deficits in physical fitness as early as possible and consequently ensure a holistic development and a lifelong healthy life.
Initially, a systematic review to provide an ‘update’ on secular trends in selected components of physical fitness (i.e., cardiorespiratory endurance, relative muscle strength, proxies of muscle power, speed) in children and adolescents aged 6 to 18 years was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guidelines. To examine short-term ontogenetic cross-sectional developmental differences and to compare physical fitness of older- and younger-than-keyage children versus keyage-children physical fitness data of 108,295 keyage-children (i.e., aged 8.00 to 8.99 years), 2,586 younger-than-keyage children (i.e., aged 7.00 to 7.99 years), and 26,540 older-than-keyage children (i.e., aged 9.00 to 9.99 years) from the third grade were analyzed. Physical fitness was assessed through the EMOTIKON test battery measuring cardiorespiratory endurance (i.e., 6-min-run test), coordina-tion (i.e., star-run test), speed (i.e., 20-m linear sprint test), and proxies of lower (i.e., standing long jump test) and upper limbs (i.e., ball-push test) muscle power. Statistical inference was based on Linear Mixed Models.
Findings from the systematic review revealed a large initial improvement and an equally large subsequent decline between 1986 and 2010 as well as a stabilization between 2010 and 2015 in cardiorespiratory endurance, a general trend towards a small improvement in relative muscle strength from 1972 to 2015, an overall small negative quadratic trend for proxies of muscle power from 1972 to 2015, and a small-to-medium improvement in speed from 2002 to 2015. Findings from the cross-sectional studies showed that even in a single prepubertal year of life (i.e., ninth year) physical fitness performance develops linearly with increasing chronological age, boys showed better performances than girls in all physical fitness components, and the components varied in the size of sex and age effects. Furthermore, findings revealed that older-than-keyage children showed poorer performance in physical fitness compared to keyage-children, older-than-keyage girls showed better performances than older-than-keyage boys, and younger-than-keyage children outperformed keyage-children.
Due to the varying secular trends in physical fitness, it is recommended to promote initiatives for physical activity and physical fitness for children and adolescents to prevent adverse effects on health and well-being. More precisely, public health initiatives should specifically consider exercising cardiorespiratory endurance and muscle strength because both components showed strong positive associations with markers of health. Furthermore, the findings implied that physical education teachers, coaches, or researchers can utilize a proportional adjustment to individually interpret physical fitness of prepubertal school-aged children. Special attention should be given to the promotion of physical fitness of older-than-keyage children because they showed poorer performance in physical fitness than keyage-children. Therefore, it is necessary to specifically consider this group and provide additional health and fitness programs to reduce their deficits in physical fitness experienced during prior years to guarantee a holistic development.
Climate change of anthropogenic origin is affecting Earth’s biodiversity and therefore ecosystems and their services. High latitude ecosystems are even more impacted than the rest of Northern Hemisphere because of the amplified polar warming. Still, it is challenging to predict the dynamics of high latitude ecosystems because of complex interaction between abiotic and biotic components. As the past is the key to the future, the interpretation of past ecological changes to better understand ongoing processes is possible. In the Quaternary, the Pleistocene experienced several glacial and interglacial stages that affected past ecosystems. During the last Glacial, the Pleistocene steppe-tundra was covering most of unglaciated northern hemisphere and disappeared in parallel to the megafauna’s extinction at the transition to the Holocene (~11,700 years ago). The origin of the steppe-tundra decline is not well understood and knowledge on the mechanisms, which caused shifts in past communities and ecosystems, is of high priority as they are likely comparable to those affecting modern ecosystems. Lake or permafrost core sediments can be retrieved to investigate past biodiversity at transitions between glacial and interglacial stages. Siberia and Beringia were the origin of dispersal of the steppe-tundra, which make investigation this area of high priority. Until recently, macrofossils and pollen were the most common approaches. They are designed to reconstruct past composition changes but have limit and biases. Since the end of the 20th century, sedimentary ancient DNA (sedaDNA) can also be investigated. My main objectives were, by using sedaDNA approaches to provide scientific evidence of compositional and diversity changes in the Northern Hemisphere ecosystems at the transition between Quaternary glacial and interglacial stages.
In this thesis, I provide snapshots of entire ancient ecosystems and describe compositional changes between Quaternary glacial and interglacial stages, and confirm the vegetation composition and the spatial and temporal boundaries of the Pleistocene steppe-tundra. I identify a general loss of plant diversity with extinction events happening in parallel of megafauna’ extinction. I demonstrate how loss of biotic resilience led to the collapse of a previously well-established system and discuss my results in regards to the ongoing climate change. With further work to constrain biases and limits, sedaDNA can be used in parallel or even replace the more established macrofossils and pollen approaches as my results support the robustness and potential of sedaDNA to answer new palaeoecological questions such as plant diversity changes, loss and provide snapshots of entire ancient biota.
Additive manufacturing (AM) processes enable the production of metal structures with exceptional design freedom, of which laser powder bed fusion (PBF-LB) is one of the most common. In this process, a laser melts a bed of loose feedstock powder particles layer-by-layer to build a structure with the desired geometry. During fabrication, the repeated melting and rapid, directional solidification create large temperature gradients that generate large thermal stress. This thermal stress can itself lead to cracking or delamination during fabrication. More often, large residual stresses remain in the final part as a footprint of the thermal stress. This residual stress can cause premature distortion or even failure of the part in service. Hence, knowledge of the residual stress field is critical for both process optimization and structural integrity.
Diffraction-based techniques allow the non-destructive characterization of the residual stress fields. However, such methods require a good knowledge of the material of interest, as certain assumptions must be made to accurately determine residual stress. First, the measured lattice plane spacings must be converted to lattice strains with the knowledge of a strain-free material state. Second, the measured lattice strains must be related to the macroscopic stress using Hooke's law, which requires knowledge of the stiffness of the material. Since most crystal structures exhibit anisotropic material behavior, the elastic behavior is specific to each lattice plane of the single crystal. Thus, the use of individual lattice planes in monochromatic diffraction residual stress analysis requires knowledge of the lattice plane-specific elastic properties. In addition, knowledge of the microstructure of the material is required for a reliable assessment of residual stress.
This work presents a toolbox for reliable diffraction-based residual stress analysis. This is presented for a nickel-based superalloy produced by PBF-LB. First, this work reviews the existing literature in the field of residual stress analysis of laser-based AM using diffraction-based techniques. Second, the elastic and plastic anisotropy of the nickel-based superalloy Inconel 718 produced by PBF-LB is studied using in situ energy dispersive synchrotron X-ray and neutron diffraction techniques. These experiments are complemented by ex situ material characterization techniques. These methods establish the relationship between the microstructure and texture of the material and its elastic and plastic anisotropy. Finally, surface, sub-surface, and bulk residual stress are determined using a texture-based approach. Uncertainties of different methods for obtaining stress-free reference values are discussed.
The tensile behavior in the as-built condition is shown to be controlled by texture and cellular sub-grain structure, while in the heat-treated condition the precipitation of strengthening phases and grain morphology dictate the behavior. In fact, the results of this thesis show that the diffraction elastic constants depend on the underlying microstructure, including texture and grain morphology. For columnar microstructures in both as-built and heat-treated conditions, the diffraction elastic constants are best described by the Reuss iso-stress model. Furthermore, the low accumulation of intergranular strains during deformation demonstrates the robustness of using the 311 reflection for the diffraction-based residual stress analysis with columnar textured microstructures. The differences between texture-based and quasi-isotropic approaches for the residual stress analysis are shown to be insignificant in the observed case. However, the analysis of the sub-surface residual stress distributions show, that different scanning strategies result in a change in the orientation of the residual stress tensor. Furthermore, the location of the critical sub-surface tensile residual stress is related to the surface roughness and the microstructure. Finally, recommendations are given for the diffraction-based determination and evaluation of residual stress in textured additively manufactured alloys.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties.
Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult – if not impossible – to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates (‘higher export in warmer years’) that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes.
Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine Ötztal valley in Tyrol, Austria, over decadal timescales in the past and future – i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest.
The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper Ötztal, Vent, Sölden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 % of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors.
The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.
The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed – unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology.
This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves – especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.
Large parts of the Earth’s interior are inaccessible to direct observation, yet global geodynamic processes are governed by the physical material properties under extreme pressure and temperature conditions. It is therefore essential to investigate the deep Earth’s physical properties through in-situ laboratory experiments. With this goal in mind, the optical properties of mantle minerals at high pressure offer a unique way to determine a variety of physical properties, in a straight-forward, reproducible, and time-effective manner, thus providing valuable insights into the physical processes of the deep Earth. This thesis focusses on the system Mg-Fe-O, specifically on the optical properties of periclase (MgO) and its iron-bearing variant ferropericlase ((Mg,Fe)O), forming a major planetary building block. The primary objective is to establish links between physical material properties and optical properties. In particular the spin transition in ferropericlase, the second-most abundant phase of the lower mantle, is known to change the physical material properties. Although the spin transition region likely extends down to the core-mantle boundary, the ef-fects of the mixed-spin state, where both high- and low-spin state are present, remains poorly constrained.
In the studies presented herein, we show how optical properties are linked to physical properties such as electrical conductivity, radiative thermal conductivity and viscosity. We also show how the optical properties reveal changes in the chemical bonding. Furthermore, we unveil how the chemical bonding, the optical and other physical properties are affected by the iron spin transition. We find opposing trends in the pres-sure dependence of the refractive index of MgO and (Mg,Fe)O. From 1 atm to ~140 GPa, the refractive index of MgO decreases by ~2.4% from 1.737 to 1.696 (±0.017). In contrast, the refractive index of (Mg0.87Fe0.13)O (Fp13) and (Mg0.76Fe0.24)O (Fp24) ferropericlase increases with pressure, likely because Fe Fe interactions between adjacent iron sites hinder a strong decrease of polarizability, as it is observed with increasing density in the case of pure MgO. An analysis of the index dispersion in MgO (decreasing by ~23% from 1 atm to ~103 GPa) reflects a widening of the band gap from ~7.4 eV at 1 atm to ~8.5 (±0.6) eV at ~103 GPa. The index dispersion (between 550 and 870 nm) of Fp13 reveals a decrease by a factor of ~3 over the spin transition range (~44–100 GPa). We show that the electrical band gap of ferropericlase significantly widens up to ~4.7 eV in the mixed spin region, equivalent to an increase by a factor of ~1.7. We propose that this is due to a lower electron mobility between adjacent Fe2+ sites of opposite spin, explaining the previously observed low electrical conductivity in the mixed spin region. From the study of absorbance spectra in Fp13, we show an increasing covalency of the Fe-O bond with pressure for high-spin ferropericlase, whereas in the low-spin state a trend to a more ionic nature of the Fe-O bond is observed, indicating a bond weakening effect of the spin transition. We found that the spin transition is ultimately caused by both an increase of the ligand field-splitting energy and a decreasing spin-pairing energy of high-spin Fe2+.
The evaluation of process-oriented cognitive theories through time-ordered observations is crucial for the advancement of cognitive science. The findings presented herein integrate insights from research on eye-movement control and sentence comprehension during reading, addressing challenges in modeling time-ordered data, statistical inference, and interindividual variability. Using kernel density estimation and a pseudo-marginal likelihood for fixation durations and locations, a likelihood implementation of the SWIFT model of eye-movement control during reading (Engbert et al., Psychological Review, 112, 2005, pp. 777–813) is proposed. Within the broader framework of data assimilation, Bayesian parameter inference with adaptive Markov Chain Monte Carlo techniques is facilitated for reliable model fitting. Across the different studies, this framework has shown to enable reliable parameter recovery from simulated data and prediction of experimental summary statistics. Despite its complexity, SWIFT can be fitted within a principled Bayesian workflow, capturing interindividual differences and modeling experimental effects on reading across different geometrical alterations of text. Based on these advancements, the integrated dynamical model SEAM is proposed, which combines eye-movement control, a traditionally psychological research area, and post-lexical language processing in the form of cue-based memory retrieval (Lewis & Vasishth, Cognitive Science, 29, 2005, pp. 375–419), typically the purview of psycholinguistics. This proof-of-concept integration marks a significant step forward in natural language comprehension during reading and suggests that the presented methodology can be useful to develop complex cognitive dynamical models that integrate processes at levels of perception, higher cognition, and (oculo-)motor control. These findings collectively advance process-oriented cognitive modeling and highlight the importance of Bayesian inference, individual differences, and interdisciplinary integration for a holistic understanding of reading processes. Implications for theory and methodology, including proposals for model comparison and hierarchical parameter inference, are briefly discussed.
It is a well-attested finding in head-initial languages that individuals with aphasia (IWA) have greater difficulties in comprehending object-extracted relative clauses (ORCs) as compared to subject-extracted relative clauses (SRCs). Adopting the linguistically based approach of Relativized Minimality (RM; Rizzi, 1990, 2004), the subject-object asymmetry is attributed to the occurrence of a Minimality effect in ORCs due to reduced processing capacities in IWA (Garraffa & Grillo, 2008; Grillo, 2008, 2009). For ORCs, it is claimed that the embedded subject intervenes in the syntactic dependency between the moved object and its trace, resulting in greater processing demands. In contrast, no such intervener is present in SRCs. Based on the theoretical framework of RM and findings from language acquisition (Belletti et al., 2012; Friedmann et al., 2009), it is assumed that Minimality effects are alleviated when the moved object and the intervening subject differ in terms of relevant syntactic features. For German, the language under investigation, the RM approach predicts that number (i.e., singular vs. plural) and the lexical restriction [+NP] feature (i.e., lexically restricted determiner phrases vs. lexically unrestricted pronouns) are considered relevant in the computation of Minimality. Greater degrees of featural distinctiveness are predicted to result in more facilitated processing of ORCs, because IWA can more easily distinguish between the moved object and the intervener.
This cumulative dissertation aims to provide empirical evidence on the validity of the RM approach in accounting for comprehension patterns during relative clause (RC) processing in German-speaking IWA. For that purpose, I conducted two studies including visual-world eye-tracking experiments embedded within an auditory referent-identification task to study the offline and online processing of German RCs. More specifically, target sentences were created to evaluate (a) whether IWA demonstrate a subject-object asymmetry, (b) whether dissimilarity in the number and/or the [+NP] features facilitates ORC processing, and (c) whether sentence processing in IWA benefits from greater degrees of featural distinctiveness. Furthermore, by comparing RCs disambiguated through case marking (at the relative pronoun or the following noun phrase) and number marking (inflection of the sentence-final verb), it was possible to consider the role of the relative position of the disambiguation point. The RM approach predicts that dissimilarity in case should not affect the occurrence of Minimality effects. However, the case cue to sentence interpretation appears earlier within RCs than the number cue, which may result in lower processing costs in case-disambiguated RCs compared to number-disambiguated RCs.
In study I, target sentences varied with respect to word order (SRC vs. ORC) and dissimilarity in the [+NP] feature (lexically restricted determiner phrase vs. pronouns as embedded element). Moreover, by comparing the impact of these manipulations in case- and number-disambiguated RCs, the effect of dissimilarity in the number feature was explored. IWA demonstrated a subject-object asymmetry, indicating the occurrence of a Minimality effect in ORCs. However, dissimilarity neither in the number feature nor in the [+NP] feature alone facilitated ORC processing. Instead, only ORCs involving distinct specifications of both the number and the [+NP] features were well comprehended by IWA. In study II, only temporarily ambiguous ORCs disambiguated through case or number marking were investigated, while controlling for varying points of disambiguation. There was a slight processing advantage of case marking as cue to sentence interpretation as compared to number marking.
Taken together, these findings suggest that the RM approach can only partially capture empirical data from German IWA. In processing complex syntactic structures, IWA are susceptible to the occurrence of the intervening subject in ORCs. The new findings reported in the thesis show that structural dissimilarity can modulate sentence comprehension in aphasia. Interestingly, IWA can override Minimality effects in ORCs and derive correct sentence meaning if the featural specifications of the constituents are maximally different, because they can more easily distinguish the moved object and the intervening subject given their reduced processing capacities. This dissertation presents new scientific knowledge that highlights how the syntactic theory of RM helps to uncover selective effects of morpho-syntactic features on sentence comprehension in aphasia, emphasizing the close link between assumptions from theoretical syntax and empirical research.
The biosecurity individual
(2024)
Discoveries in biomedicine and biotechnology, especially in diagnostics, have made prevention and (self)surveillance increasingly important in the context of health practices. Frederike Offizier offers a cultural critique of the intersection between health, security and identity, and explores how the focus on risk and security changes our understanding of health and transforms our relationship to our bodies. Analyzing a wide variety of texts, from life writing to fiction, she offers a critical intervention on how this shift in the medical gaze produces new paradigms of difference and new biomedically facilitated identities: biosecurity individuals.
To manage tabular data files and leverage their content in a given downstream task, practitioners often design and execute complex transformation pipelines to prepare them. The complexity of such pipelines stems from different factors, including the nature of the preparation tasks, often exploratory or ad-hoc to specific datasets; the large repertory of tools, algorithms, and frameworks that practitioners need to master; and the volume, variety, and velocity of the files to be prepared. Metadata plays a fundamental role in reducing this complexity: characterizing a file assists end users in the design of data preprocessing pipelines, and furthermore paves the way for suggestion, automation, and optimization of data preparation tasks.
Previous research in the areas of data profiling, data integration, and data cleaning, has focused on extracting and characterizing metadata regarding the content of tabular data files, i.e., about the records and attributes of tables. Content metadata are useful for the latter stages of a preprocessing pipeline, e.g., error correction, duplicate detection, or value normalization, but they require a properly formed tabular input. Therefore, these metadata are not relevant for the early stages of a preparation pipeline, i.e., to correctly parse tables out of files. In this dissertation, we turn our focus to what we call the structure of a tabular data file, i.e., the set of characters within a file that do not represent data values but are required to parse and understand the content of the file. We provide three different approaches to represent file structure, an explicit representation based on context-free grammars; an implicit representation based on file-wise similarity; and a learned representation based on machine learning.
In our first contribution, we use the grammar-based representation to characterize a set of over 3000 real-world csv files and identify multiple structural issues that let files deviate from the csv standard, e.g., by having inconsistent delimiters or containing multiple tables. We leverage our learnings about real-world files and propose Pollock, a benchmark to test how well systems parse csv files that have a non-standard structure, without any previous preparation. We report on our experiments on using Pollock to evaluate the performance of 16 real-world data management systems.
Following, we characterize the structure of files implicitly, by defining a measure of structural similarity for file pairs. We design a novel algorithm to compute this measure, which is based on a graph representation of the files' content. We leverage this algorithm and propose Mondrian, a graphical system to assist users in identifying layout templates in a dataset, classes of files that have the same structure, and therefore can be prepared by applying the same preparation pipeline.
Finally, we introduce MaGRiTTE, a novel architecture that uses self-supervised learning to automatically learn structural representations of files in the form of vectorial embeddings at three different levels: cell level, row level, and file level. We experiment with the application of structural embeddings for several tasks, namely dialect detection, row classification, and data preparation efforts estimation.
Our experimental results show that structural metadata, either identified explicitly on parsing grammars, derived implicitly as file-wise similarity, or learned with the help of machine learning architectures, is fundamental to automate several tasks, to scale up preparation to large quantities of files, and to provide repeatable preparation pipelines.
The landscape of software self-adaptation is shaped in accordance with the need to cost-effectively achieve and maintain (software) quality at runtime and in the face of dynamic operation conditions. Optimization-based solutions perform an exhaustive search in the adaptation space, thus they may provide quality guarantees. However, these solutions render the attainment of optimal adaptation plans time-intensive, thereby hindering scalability. Conversely, deterministic rule-based solutions yield only sub-optimal adaptation decisions, as they are typically bound by design-time assumptions, yet they offer efficient processing and implementation, readability, expressivity of individual rules supporting early verification. Addressing the quality-cost trade-of requires solutions that simultaneously exhibit the scalability and cost-efficiency of rulebased policy formalism and the optimality of optimization-based policy formalism as explicit artifacts for adaptation. Utility functions, i.e., high-level specifications that capture system objectives, support the explicit treatment of quality-cost trade-off. Nevertheless, non-linearities, complex dynamic architectures, black-box models, and runtime uncertainty that makes the prior knowledge obsolete are a few of the sources of uncertainty and subjectivity that render the elicitation of utility non-trivial.
This thesis proposes a twofold solution for incremental self-adaptation of dynamic architectures. First, we introduce Venus, a solution that combines in its design a ruleand an optimization-based formalism enabling optimal and scalable adaptation of dynamic architectures. Venus incorporates rule-like constructs and relies on utility theory for decision-making. Using a graph-based representation of the architecture, Venus captures rules as graph patterns that represent architectural fragments, thus enabling runtime extensibility and, in turn, support for dynamic architectures; the architecture is evaluated by assigning utility values to fragments; pattern-based definition of rules and utility enables incremental computation of changes on the utility that result from rule executions, rather than evaluating the complete architecture, which supports scalability. Second, we introduce HypeZon, a hybrid solution for runtime coordination of multiple off-the-shelf adaptation policies, which typically offer only partial satisfaction of the quality and cost requirements. Realized based on meta-self-aware architectures, HypeZon complements Venus by re-using existing policies at runtime for balancing the quality-cost trade-off.
The twofold solution of this thesis is integrated in an adaptation engine that leverages state- and event-based principles for incremental execution, therefore, is scalable for large and dynamic software architectures with growing size and complexity. The utility elicitation challenge is resolved by defining a methodology to train utility-change prediction models. The thesis addresses the quality-cost trade-off in adaptation of dynamic software architectures via design-time combination (Venus) and runtime coordination (HypeZon) of rule- and optimization-based policy formalisms, while offering supporting mechanisms for optimal, cost-effective, scalable, and robust adaptation. The solutions are evaluated according to a methodology that is obtained based on our systematic literature review of evaluation in self-healing systems; the applicability and effectiveness of the contributions are demonstrated to go beyond the state-of-the-art in coverage of a wide spectrum of the problem space for software self-adaptation.
Sigmund Freud, the founder of psychoanalysis, began his intellectual life with the Jewish Bible and also ended it with it. He began by reading the Philippson Bible together, especially with his father Jacob Freud, and ended by studying the figure of Moses. This study systematically traces this preoccupation and shows that the Jewish Bible was a constant reference for Freud and determined his Jewish identity. This is shown by analysing family documents, religious instruction and references to the Bible in Freud's writings and correspondence.
Concepts and techniques for 3D-embedded treemaps and their application to software visualization
(2024)
This thesis addresses concepts and techniques for interactive visualization of hierarchical data using treemaps. It explores (1) how treemaps can be embedded in 3D space to improve their information content and expressiveness, (2) how the readability of treemaps can be improved using level-of-detail and degree-of-interest techniques, and (3) how to design and implement a software framework for the real-time web-based rendering of treemaps embedded in 3D. With a particular emphasis on their application, use cases from software analytics are taken to test and evaluate the presented concepts and techniques.
Concerning the first challenge, this thesis shows that a 3D attribute space offers enhanced possibilities for the visual mapping of data compared to classical 2D treemaps. In particular, embedding in 3D allows for improved implementation of visual variables (e.g., by sketchiness and color weaving), provision of new visual variables (e.g., by physically based materials and in situ templates), and integration of visual metaphors (e.g., by reference surfaces and renderings of natural phenomena) into the three-dimensional representation of treemaps.
For the second challenge—the readability of an information visualization—the work shows that the generally higher visual clutter and increased cognitive load typically associated with three-dimensional information representations can be kept low in treemap-based representations of both small and large hierarchical datasets. By introducing an adaptive level-of-detail technique, we cannot only declutter the visualization results, thereby reducing cognitive load and mitigating occlusion problems, but also summarize and highlight relevant data. Furthermore, this approach facilitates automatic labeling, supports the emphasis on data outliers, and allows visual variables to be adjusted via degree-of-interest measures.
The third challenge is addressed by developing a real-time rendering framework with WebGL and accumulative multi-frame rendering. The framework removes hardware constraints and graphics API requirements, reduces interaction response times, and simplifies high-quality rendering. At the same time, the implementation effort for a web-based deployment of treemaps is kept reasonable.
The presented visualization concepts and techniques are applied and evaluated for use cases in software analysis. In this domain, data about software systems, especially about the state and evolution of the source code, does not have a descriptive appearance or natural geometric mapping, making information visualization a key technology here. In particular, software source code can be visualized with treemap-based approaches because of its inherently hierarchical structure. With treemaps embedded in 3D, we can create interactive software maps that visually map, software metrics, software developer activities, or information about the evolution of software systems alongside their hierarchical module structure.
Discussions on remaining challenges and opportunities for future research for 3D-embedded treemaps and their applications conclude the thesis.
The increasing number of known exoplanets raises questions about their demographics and the mechanisms that shape planets into how we observe them today. Young planets in close-in orbits are exposed to harsh environments due to the host star being magnetically highly active, which results in high X-ray and extreme UV fluxes impinging on the planet. Prolonged exposure to this intense photoionizing radiation can cause planetary atmospheres to heat up, expand and escape into space via a hydrodynamic escape process known as photoevaporation. For super-Earth and sub-Neptune-type planets, this can even lead to the complete erosion of their primordial gaseous atmospheres. A factor of interest for this particular mass-loss process is the activity evolution of the host star. Stellar rotation, which drives the dynamo and with it the magnetic activity of a star, changes significantly over the stellar lifetime. This strongly affects the amount of high-energy radiation received by a planet as stars age. At a young age, planets still host warm and extended envelopes, making them particularly susceptible to atmospheric evaporation. Especially in the first gigayear, when X-ray and UV levels can be 100 - 10,000 times higher than for the present-day sun, the characteristics of the host star and the detailed evolution of its high-energy emission are of importance.
In this thesis, I study the impact of stellar activity evolution on the high-energy-induced atmospheric mass loss of young exoplanets. The PLATYPOS code was developed as part of this thesis to calculate photoevaporative mass-loss rates over time. The code, which couples parameterized planetary mass-radius relations with an analytical hydrodynamic escape model, was used, together with Chandra and eROSITA X-ray observations, to investigate the future mass loss of the two young multiplanet systems V1298 Tau and K2-198. Further, in a numerical ensemble study, the effect of a realistic spread of activity tracks on the small-planet radius gap was investigated for the first time. The works in this thesis show that for individual systems, in particular if planetary masses are unconstrained, the difference between a young host star following a low-activity track vs. a high-activity one can have major implications: the exact shape of the activity evolution can determine whether a planet can hold on to some of its atmosphere, or completely loses its envelope, leaving only the bare rocky core behind. For an ensemble of simulated planets, an observationally-motivated distribution of activity tracks does not substantially change the final radius distribution at ages of several gigayears. My simulations indicate that the overall shape and slope of the resulting small-planet radius gap is not significantly affected by the spread in stellar activity tracks. However, it can account for a certain scattering or fuzziness observed in and around the radius gap of the observed exoplanet population.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
It is a common finding that preschoolers have difficulties in identifying who is doing what to whom in non-canonical sentences, such as (object-verb-subject) OVS and passive sentences in German. This dissertation investigates how German monolingual and German-Italian simultaneous bilingual children process German OVS sentences in Study 1 and German passives in Study 2. Offline data (i.e., accuracy data) and online data (i.e., eye-gaze and pupillometry data) were analyzed to explore whether children can assign thematic roles during sentence comprehension and processing. Executive functions, language-internal and -external factors were investigated as potential predictors for children’s sentence comprehension and processing.
Throughout the literature, there are contradicting findings on the relation between language and executive functions. While some results show a bilingual cognitive advantage over monolingual speakers, others suggest there is no relationship between bilingualism and executive functions. If bilingual children possess more advanced executive function abilities than monolingual children, then this might also be reflected in a better performance on linguistic tasks. In the current studies monolingual and bilingual children were tested by means of two executive function tasks: the Flanker task and the task-switching paradigm. However, these findings showed no bilingual cognitive advantages and no better performance by bilingual children in the linguistic tasks. The performance was rather comparable between bilingual and monolingual children, or even better for the monolingual group. This may be due to cross-linguistic influences and language experience (i.e., language input and output). Italian was used because it does not syntactically overlap with the structure of German OVS sentences, and it only overlapped with one of the two types of sentence condition used for the passive study - considering the subject-(finite)verb alignment. The findings showed a better performance of bilingual children in the passive sentence structure that syntactically overlapped in the two languages, providing evidence for cross-linguistic influences.
Further factors for children’s sentence comprehension were considered. The parents’ education, the number of older siblings and language experience variables were derived from a language background questionnaire completed by parents. Scores of receptive vocabulary and grammar, visual and short-term memory and reasoning ability were measured by means of standardized tests. It was shown that higher German language experience by bilinguals correlates with better accuracy in German OVS sentences but not in passive sentences. Memory capacity had a positive effect on the comprehension of OVS and passive sentences in the bilingual group. Additionally, a role was played by executive function abilities in the comprehension of OVS sentences and not of passive sentences. It is suggested that executive function abilities might help children in the sentence comprehension task when the linguistic structures are not yet fully mastered.
Altogether, these findings show that bilinguals’ poorer performance in the comprehension and processing of German OVS is mainly due to reduced language experience in German, and that the different performance of bilingual children with the two types of passives is mainly due to cross-linguistic influences.
Protected cultivation in greenhouses or polytunnels offers the potential for sustainable production of high-yield, high-quality vegetables. This is related to the ability to produce more on less land and to use resources responsibly and efficiently. Crop yield has long been considered the most important factor. However, as plant-based diets have been proposed for a sustainable food system, the targeted enrichment of health-promoting plant secondary metabolites should be addressed. These metabolites include carotenoids and flavonoids, which are associated with several health benefits, such as cardiovascular health and cancer protection.
Cover materials generally have an influence on the climatic conditions, which in turn can affect the levels of secondary metabolites in vegetables grown underneath. Plastic materials are cost-effective and their properties can be modified by incorporating additives, making them the first choice. However, these additives can migrate and leach from the material, resulting in reduced service life, increased waste and possible environmental release. Antifogging additives are used in agricultural films to prevent the formation of droplets on the film surface, thereby increasing light transmission and preventing microbiological contamination.
This thesis focuses on LDPE/EVA covers and incorporated antifogging additives for sustainable protected cultivation, following two different approaches. The first addressed the direct effects of leached antifogging additives using simulation studies on lettuce leaves (Lactuca sativa var capitata L). The second determined the effect of antifog polytunnel covers on lettuce quality. Lettuce is usually grown under protective cover and can provide high nutritional value due to its carotenoid and flavonoid content, depending on the cultivar.
To study the influence of simulated leached antifogging additives on lettuce leaves, a GC-MS method was first developed to analyze these additives based on their fatty acid moieties. Three structurally different antifogging additives (reference material) were characterized outside of a polymer matrix for the first time. All of them contained more than the main fatty acid specified by the manufacturer. Furthermore, they were found to adhere to the leaf surface and could not be removed by water or partially by hexane.
The incorporation of these additives into polytunnel covers affects carotenoid levels in lettuce, but not flavonoids, caffeic acid derivatives and chlorophylls. Specifically, carotenoids were higher in lettuce grown under polytunnels without antifog than with antifog. This has been linked to their effect on the light regime and was suggested to be related to carotenoid function in photosynthesis.
In terms of protected cultivation, the use of LDPE/EVA polytunnels affected light and temperature, and both are closely related. The carotenoid and flavonoid contents of lettuce grown under polytunnels was reversed, with higher carotenoid and lower flavonoid levels. At the individual level, the flavonoids detected in lettuce did not differ however, lettuce carotenoids adapted specifically depending on the time of cultivation. Flavonoid reduction was shown to be transcriptionally regulated (CHS) in response to UV light (UVR8). In contrast, carotenoids are thought to be regulated post-transcriptionally, as indicated by the lack of correlation between carotenoid levels and transcripts of the first enzyme in carotenoid biosynthesis (PSY) and a carotenoid degrading enzyme (CCD4), as well as the increased carotenoid metabolic flux. Understanding the regulatory mechanisms and metabolite adaptation strategies could further advance the strategic development and selection of cover materials.
The African weakly electric fishes (Mormyridae) exhibit a remarkable adaptive radiation possibly due to their species-specific electric organ discharges (EODs). It is produced by a muscle-derived electric organ that is located in the caudal peduncle. Divergence in EODs acts as a pre-zygotic isolation mechanism to drive species radiations. However, the mechanism behind the EOD diversification are only partially understood.
The aim of this study is to explore the genetic basis of EOD diversification from the gene expression level across Campylomormyrus species/hybrids and ontogeny. I firstly produced a high quality genome of the species C. compressirostris as a valuable resource to understand the electric fish evolution.
The next study compared the gene expression pattern between electric organs and skeletal muscles in Campylomormyrus species/hybrids with different types of EOD duration. I identified several candidate genes with an electric organ-specific expression, e.g. KCNA7a, KLF5, KCNJ2, SCN4aa, NDRG3, MEF2. The overall genes expression pattern exhibited a significant association with EOD duration in all analyzed species/hybrids. The expression of several candidate genes, e.g. KCNJ2, KLF5, KCNK6 and KCNQ5, possibly contribute to the regulation of EOD duration in Campylomormyrus due to their increasing or decreasing expression. Several potassium channel genes showed differential expression during ontogeny in species and hybrid with EOD alteration, e.g. KCNJ2.
I next explored allele specific expression of intragenus hybrids by crossing the duration EOD species C. compressirostris with the medium duration EOD species C. tshokwe and the elongated duration EOD species C. rhynchophorus. The hybrids exhibited global expression dominance of the C. compressirostris allele in the adult skeletal muscle and electric organ, as well as in the juvenile electric organ. Only the gene KCNJ2 showed dominant expression of the allele from C. rhynchophorus, and this was increasingly dominant during ontogeny. It hence supported our hypothesis that KCNJ2 is a key gene of regulating EOD duration. Our results help us to understand, from a genetic perspective, how gene expression effect the EOD diversification in the African weakly electric fish.
Optimizing power analysis for randomized experiments: Design parameters for student achievement
(2024)
Randomized trials (RTs) are promising methodological tools to inform evidence-based reform to enhance schooling. Establishing a robust knowledge base on how to promote student achievement requires sensitive RT designs demonstrating sufficient statistical power and precision to draw conclusive and correct inferences on the effectiveness of educational programs and innovations. Proper power analysis is therefore an integral component of any informative RT on student achievement. This venture critically hinges on the availability of reasonable input variance design parameters (and their inherent uncertainties) that optimally reflect the realities around the prospective RT—precisely, its target population and outcome, possibly applied covariates, the concrete design as well as the planned analysis. However, existing compilations in this vein show far-reaching shortcomings.
The overarching endeavor of the present doctoral thesis was to substantively expand available resources devoted to tweak the planning of RTs evaluating educational interventions. At the core of this thesis is a systematic analysis of design parameters for student achievement, generating reliable and versatile compendia and developing thorough guidance to support apt power analysis to design strong RTs. To this end, the thesis at hand bundles two complementary studies which capitalize on rich data of several national probability samples from major German longitudinal large-scale assessments.
Study I applied two- and three-level latent (covariate) modeling to analyze design parameters for a wide spectrum of mathematical-scientific, verbal, and domain-general achievement outcomes. Three vital covariate sets were covered comprising (a) pretests, (b) sociodemographic characteristics, and (c) their combination. The accumulated estimates were additionally summarized in terms of normative distributions.
Study II specified (manifest) single-, two-, and three-level models and referred to influential psychometric heuristics to analyze design parameters and develop concise selection guidelines for covariate (a) types of varying bandwidth-fidelity (domain-identical, cross-domain, fluid intelligence pretests; sociodemographic characteristics), (b) combinations quantifying incremental validities, and (c) time lags of 1- to 7-year-lagged pretests scrutinizing validity degradation. The estimates for various mathematical-scientific and verbal achievement outcomes were meta-analytically integrated and employed in precision simulations.
In doing so, Studies I and II addressed essential gaps identified in previous repertoires in six major dimensions: Taken together, this thesis accumulated novel design parameters and deliberate guidance for RT power analysis (1) tailored to four German student (sub)populations across the entire school career from Grade 1 to 12, (2) matched to 21 achievement (sub)domains, (3) adjusted for 11 covariate sets enriched by empirically supported guidelines, (4) adapted to six RT designs, (5) suitable for latent and manifest analysis models, (6) which were cataloged along with quantifications of their associated uncertainties. These resources are complemented by a plethora of illustrative application examples to gently direct psychological and educational researchers through pivotal steps in the process of RT design.
The striking heterogeneity of the design parameter estimates across all these dimensions constitutes the overall, joint key result of Studies I and II. Hence, this work convincingly reinforces calls for a close match between design parameters and the specific peculiarities of the target RT’s research context.
All in all, the present doctoral thesis offers a—so far unique—nuanced and extensive toolkit to optimize power analysis for sound RTs on student achievement in the German (and similar) school context. It is of utmost importance that research does not tire to spawn robust evidence on what actually works to improve schooling. With this in mind, I hope that the emerging compendia and guidance contribute to the quality and rigor of our randomized experiments in psychology and education.
Development of a CRISPR/Cas gene editing technique for the coccolithophore Chrysotila carterae
(2024)
This study focuses on William Faulkner, whose works explore the demise of the slavery-based Old South during the Civil War in a highly experimental narrative style. Central to this investigation is the analysis of the temporal dimensions of both individual and collective guilt, thus offering a new approach to the often-discussed problem of Faulkner’s portrayal of social decay. The thesis examines how Faulkner re-narrates the legacy of the Old South as a guilt narrative and argues that Faulkner uses guilt in order to corroborate his concept of time and the idea of the continuity of the past. The focus of the analysis is on three of Faulkner’s arguably most important novels: The Sound and the Fury, Absalom, Absalom!, and Go Down, Moses. Each of these novels features a main character deeply overwhelmed by the crimes of the past, whether private, familial, or societal. As a result, guilt is explored both from a domestic as well as a social perspective. In order to show how Faulkner blends past and present by means of guilt, this work examines several methods and motifs borrowed from different fields and genres with which Faulkner narratively negotiates guilt. These include religious notions of original sin, the motif of the ancestral curse prevalent in the Southern Gothic genre, and the psychological concept of trauma. Each of these motifs emphasizes the temporal dimensions of guilt, which are the core of this study, and makes clear that guilt in Faulkner’s work is primarily to be understood as a temporal rather than a moral problem.
Advancing digitalization is changing society and has far-reaching effects on people and companies. Fundamental to these changes are the new technological possibilities for processing data on an ever-increasing scale and for various purposes. The availability of large and high-quality data sets, especially those based on personal data, is crucial. They are used either to improve the productivity, quality, and individuality of products and services or to develop new types of services. Today, user behavior is tracked more actively and comprehensively than ever despite increasing legal requirements for protecting personal data worldwide. That increasingly raises ethical, moral, and social questions, which have moved to the forefront of the political debate, not least due to popular cases of data misuse. Given this discourse and the legal requirements, today's data management must fulfill three conditions: Legality or legal conformity of use and ethical legitimacy. Thirdly, the use of data should add value from a business perspective. Within the framework of these conditions, this cumulative dissertation pursues four research objectives with a focus on gaining a better understanding of
(1) the challenges of implementing privacy laws,
(2) the factors that influence customers' willingness to share personal data,
(3) the role of data protection for digital entrepreneurship, and
(4) the interdisciplinary scientific significance, its development, and its interrelationships.
Èto-clefts are Russian focus constructions with the demonstrative pronoun èto ‘this’ at the beginning: “Èto Mark vyigral gonku” (“It was Mark who won the race”). They are often being compared with English it-clefts, German es-clefts, as well as the corresponding focus-background structures in other languages.
In terms of semantics, èto-clefts have two important properties which are cross-linguistically typical for clefts: existence presupposition (“Someone won the race”) and exhaustivity (“Nobody except Mark won the race”). However, the exhaustivity effects are not as strong as exhaustivity effects in structures with the exclusive only and require more research.
At the same time, the question if the syntactic structure of èto-clefts matches the biclausal structure of English and German clefts, remains open. There are arguments in favor of biclausality, as well as monoclausality. Besides, there is no consistency regarding the status of èto itself.
Finally, the information structure of èto-clefts has remained underexplored in the existing literature.
This research investigates the information-structural, syntactic, and semantic properties of Russian clefts, both theoretically (supported by examples from Russian text corpora and judgments from native speakers) and experimentally. It is determined which desired changes in the information structure motivate native speakers to choose an èto-cleft and not the canonical structure or other focus realization tools. Novel syntactic tests are conducted to find evidence for bi-/monoclausality of èto-clefts, as well as for base-generation or movement of the cleft pivot. It is hypothesized that èto has a certain important function in clefts, and its status is investigated. Finally, new experiments on the nature of exhaustivity in èto-clefts are conducted. They allow for direct cross-linguistic comparison, using an incremental-information paradigm with truth-value judgments.
In terms of information structure, this research makes a new proposal that presents èto-clefts as structures with an inherent focus-background bipartitioning. Even though èto-clefts are used in typical focus contexts, evidence was found that èto-clefts (as well as Russian thetic clefts) allow for both new information focus and contrastive focus. Èto-clefts are pragmatically acceptable when a singleton answer to the implied question is expected (e.g. “It was Mark who won the race” but not “It was Mark who came to the party”). Importantly, èto in Russian clefts is neither dummy, nor redundant, but is a topic expression; conveys familiarity which triggers existence presupposition; refers to an instantiated event, or a known/perceivable situation; finally, èto plays an important role in the spoken language as a tool for speech coherency and a focus marker.
In terms of syntax, this research makes a new monoclausal proposal and shows evidence that the cleft pivot undergoes movement to the left peripheral position. Èto is proposed to be TopP.
Finally, in terms of semantics, a novel cross-linguistic evaluation of Russian clefts is made. Experiments show that the exhaustivity inference in èto-clefts is not robust. Participants used different strategies in resolving exhaustivity, falling into 2 groups: one group considered èto-clefts exhaustive, while another group considered them non-exhaustive. Hence, there is evidence for the pragmatic nature of exhaustivity in èto-clefts. The experimental results for èto-clefts are similar to the experimental results for clefts in German, French and Akan. It is concluded that speakers use different tools available in their languages to produce structures with similar interpretive properties.
The present dissertation investigates changes in lingual coarticulation across childhood in German-speaking children from three to nine years of age and adults. Coarticulation refers to the mismatch between the abstract phonological units and their seemingly commingled realization in continuous speech. Being a process at the intersection of phonology and phonetics, addressing its changes across childhood allows for insights in speech motor as well as phonological developments. Because specific predictions for changes in coarticulation across childhood can be derived from existing speech production models, investigating children’s coarticulatory patterns can help us model human speech production.
While coarticulatory changes may shed light on some of the central questions of speech production development, previous studies on the topic were sparse and presented a puzzling picture of conflicting findings. One of the reasons for this lack is the difficulty in articulatory data acquisition in a young population. Within the research program this dissertation is embedded in, we accepted this challenge and successfully set up the hitherto largest corpus of articulatory data from children using ultrasound tongue imaging. In contrast to earlier studies, a high number of participants in tight age cohorts across a wide age range and a thoroughly controlled set of pseudowords allowed for statistically powerful investigations of a process known as variable and complicated to track.
The specific focus of my studies is on lingual vocalic coarticulation as measured in the horizontal position of the highest point of the tongue dorsum. Based on three studies on a) anticipatory coarticulation towards the left, b) carryover coarticulation towards the right side of the utterance, and c) anticipatory coarticulatory extent in repeated versus read aloud speech, I deduct the following main theses:
1. Maturing speech motor control is responsible for some developmental changes in coarticulation.
2. Coarticulation can be modeled as the coproduction of articulatory gestures.
3. The developmental change in coarticulation results from a decrease of vocalic activation width.
With the many challenges facing the agricultural system, such as water scarcity, loss of arable land due to climate change, population growth, urbanization or trade disruptions, new agri-food systems are needed to ensure food security in the future. In addition, healthy diets are needed to combat non-communicable diseases. Therefore, plant-based diets rich in health-promoting plant secondary metabolites are desirable. A saline indoor farming system is representing a sustainable and resilient new agrifood system and can preserve valuable fresh water. Since indoor farming relies on artificial lighting, assessment of lighting conditions is essential. In this thesis, the cultivation of halophytes in a saline indoor farming system was evaluated and the influence of cultivation conditions were assessed in favor of improving the nutritional quality of halophytes for human consumption. Therefore, five selected edible halophyte species (Brassica oleracea var. palmifolia, Cochlearia officinalis, Atriplex hortensis, Chenopodium quinoa, and Salicornia europaea) were cultivated in saline indoor farming. The halophyte species were selected for to their salt tolerance levels and mechanisms. First, the suitability of halophytes for saline indoor farming and the influence of salinity on their nutritional properties, e.g. plant secondary metabolites and minerals, were investigated. Changes in plant performance and nutritional properties were observed as a function of salinity. The response to salinity was found to be species-specific and related to the salt tolerance mechanism of the halophytes. At their optimal salinity levels, the halophytes showed improved carotenoid content. In addition, a negative correlation was found between the nitrate and chloride content of halophytes as a function of salinity. Since chloride and nitrate can be antinutrient compounds, depending on their content, monitoring is essential, especially in halophytes. Second, regional brine water was introduced as an alternative saline water resource in the saline indoor farming system. Brine water was shown to be feasible for saline indoor farming
of halophytes, as there was no adverse effect on growth or nutritional properties, e.g. carotenoids. Carotenoids were shown to be less affected by salt composition than by salt concentration. In addition, the interaction between the salinity and the light regime in indoor farming and greenhouse cultivation has been studied. There it was shown that interacting light regime and salinity alters the content of carotenoids and chlorophylls. Further, glucosinolate and nitrate content were also shown to be influenced by light regime. Finally, the influence of UVB light on halophytes was investigated using supplemental narrow-band UVB LEDs. It was shown that UVB light affects the growth, phenotype and metabolite profile of halophytes and that the UVB response is species specific. Furthermore, a modulation of carotenoid content in S. europaea could be achieved to enhance health-promoting properties and thus improve nutritional quality. This was shown to be dose-dependent and the underlying mechanisms of carotenoid accumulation were also investigated. Here it was revealed that carotenoid accumulation is related to oxidative stress.
In conclusion, this work demonstrated the potential of halophytes as alternative vegetables produced in a saline indoor farming system for future diets that could contribute to ensuring food security in the future. To improve the sustainability of the saline indoor farming system, LED lamps and regional brine water could be integrated into the system. Since the nutritional properties have been shown to be influenced by salt, light regime and UVB light, these abiotic stressors must be taken into account when considering halophytes as alternative vegetables for human nutrition.
The urban heat island (UHI) effect, describing an elevated temperature of urban areas compared with their natural surroundings, can expose urban dwellers to additional heat stress, especially during hot summer days. A comprehensive understanding of the UHI dynamics along with urbanization is of great importance to efficient heat stress mitigation strategies towards sustainable urban development. This is, however, still challenging due to the difficulties of isolating the influences of various contributing factors that interact with each other. In this work, I present a systematical and quantitative analysis of how urban intrinsic properties (e.g., urban size, density, and morphology) influence UHI intensity.
To this end, we innovatively combine urban growth modelling and urban climate simulation to separate the influence of urban intrinsic factors from that of background climate, so as to focus on the impact of urbanization on the UHI effect. The urban climate model can create a laboratory environment which makes it possible to conduct controlled experiments to separate the influences from different driving factors, while the urban growth model provides detailed 3D structures that can be then parameterized into different urban development scenarios tailored for these experiments. The novelty in the methodology and experiment design leads to the following achievements of our work.
First, we develop a stochastic gravitational urban growth model that can generate 3D structures varying in size, morphology, compactness, and density gradient. We compare various characteristics, like fractal dimensions (box-counting, area-perimeter scaling, area-population scaling, etc.), and radial gradient profiles of land use share and population density, against those of real-world cities from empirical studies. The model shows the capability of creating 3D structures resembling real-world cities. This model can generate 3D structure samples for controlled experiments to assess the influence of some urban intrinsic properties in question. [Chapter 2]
With the generated 3D structures, we run several series of simulations with urban structures varying in properties like size, density and morphology, under the same weather conditions. Analyzing how the 2m air temperature based canopy layer urban heat island (CUHI) intensity varies in response to the changes of the considered urban factors, we find the CUHI intensity of a city is directly related to the built-up density and an amplifying effect that urban sites have on each other. We propose a Gravitational Urban Morphology (GUM) indicator to capture the neighbourhood warming effect. We build a regression model to estimate the CUHI intensity based on urban size, urban gross building volume, and the GUM indicator. Taking the Berlin area as an example, we show the regression model capable of predicting the CUHI intensity under various urban development scenarios. [Chapter 3]
Based on the multi-annual average summer surface urban heat island (SUHI) intensity derived from Land surface temperature, we further study how urban intrinsic factors influence the SUHI effect of the 5,000 largest urban clusters in Europe. We find a similar 3D GUM indicator to be an effective predictor of the SUHI intensity of these European cities. Together with other urban factors (vegetation condition, elevation, water coverage), we build different multivariate linear regression models and a climate space based Geographically Weighted Regression (GWR) model that can better predict SUHI intensity. By investigating the roles background climate factors play in modulating the coefficients of the GWR model, we extend the multivariate linear model to a nonlinear one by integrating some climate parameters, such as the average of daily maximal temperature and latitude. This makes it applicable across a range of background climates. The nonlinear model outperforms linear models in SUHI assessment as it captures the interaction of urban factors and the background climate. [Chapter 4]
Our work reiterates the essential roles of urban density and morphology in shaping the urban thermal environment. In contrast to many previous studies that link bigger cities with higher UHI intensity, we show that cities larger in the area do not necessarily experience a stronger UHI effect. In addition, the results extend our knowledge by demonstrating the influence of urban 3D morphology on the UHI effect. This underlines the importance of inspecting cities as a whole from the 3D perspective. While urban 3D morphology is an aggregated feature of small-scale urban elements, the influence it has on the city-scale UHI intensity cannot simply be scaled up from that of its neighbourhood-scale components. The spatial composition and configuration of urban elements both need to be captured when quantifying urban 3D morphology as nearby neighbourhoods also cast influences on each other. Our model serves as a useful UHI assessment tool for the quantitative comparison of urban intervention/development scenarios. It can support harnessing the capacity of UHI mitigation through optimizing urban morphology, with the potential of integrating climate change into heat mitigation strategies.
Nils-Hendrik Grohmann beschäftigt sich mit dem noch andauernden Stärkungsprozess der UN-Menschenrechtsvertragsorgane. Er analysiert, welche rechtlichen Befugnisse die Ausschüsse haben, ob sie von sich aus Vorschläge einbringen können und inwieweit sie ihre Verfahrensweisen bisher aufeinander abgestimmt haben. Ein weiterer Schwerpunkt liegt auf der Zusammenarbeit zwischen den verschiedenen Ausschüssen und der Frage, welche Rolle das Treffen der Vorsitzenden bei der Stärkung spielen kann.
Classification, prediction and evaluation of graph neural networks on online social media platforms
(2024)
The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks.
This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes.
Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN.
Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse.
The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data.
The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient.
The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.
The remarkable antifouling properties of zwitterionic polymers in controlled environments are often counteracted by their delicate mechanical stability. In order to improve the mechanical stabilities of zwitterionic hydrogels, the effect of increased crosslinker densities was thus explored. In a first approach, terpolymers of zwitterionic monomer 3-[N -2(methacryloyloxy)ethyl-N,N-dimethyl]ammonio propane-1-sulfonate (SPE), hydrophobic monomer butyl methacrylate (BMA), and photo-crosslinker 2-(4-benzoylphenoxy)ethyl methacrylate (BPEMA) were synthesized. Thin hydrogel coatings of the copolymers were then produced and photo-crosslinked. Studies of the swollen hydrogel films showed that not only the mechanical stability but also, unexpectedly, the antifouling properties were improved by the presence of hydrophobic BMA units in the terpolymers.
Based on the positive results shown by the amphiphilic terpolymers and in order to further test the impact that hydrophobicity has on both the antifouling properties of zwitterionic hydrogels and on their mechanical stability, a new amphiphilic zwitterionic methacrylic monomer, 3-((2-(methacryloyloxy)hexyl)dimethylammonio)propane-1-sulfonate (M1), was synthesized in good yields in a multistep synthesis. Homopolymers of M1 were obtained by free-radical polymerization. Similarly, terpolymers of M1, zwitterionic monomer SPE, and photo-crosslinker BPEMA were synthesized by free-radical copolymerization and thoroughly characterized, including its solubilities in selected solvents.
Also, a new family of vinyl amide zwitterionic monomomers, namely 3-(dimethyl(2-(N -vinylacetamido)ethyl)ammonio)propane-1-sulfonate (M2), 4-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)butane-1-sulfonate (M3), and 3-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)propyl sulfate (M4), together with the new photo-crosslinker 4-benzoyl-N-vinylbenzamide (M5) that is well-suited for copolymerization with vinylamides, are introduced within the scope of the present work. The monomers are synthesized with good yields developing a multistep synthesis. Homopolymers of the new vinyl amide zwitterionic monomers are obtained by free-radical polymerization and thoroughly characterized. From the solubility tests, it is remarkable that the homopolymers produced are fully soluble in water, evidence of their high hydrophilicity. Copolymerization of the vinyl amide zwitterionic monomers, M2, M3, and M4 with the vinyl amide photo-crosslinker M5 proved to require very specific polymerization conditions. Nevertheless, copolymers were successfully obtained by free-radical copolymerization under appropriate conditions.
Moreover, in an attempt to mitigate the intrinsic hydrophobicity introduced in the copolymers by the photo-crosslinkers, and based on the proven affinity of quaternized diallylamines to copolymerize with vinyl amides, a new quaternized diallylamine sulfobetaine photo-crosslinker 3-(diallyl(2-(4-benzoylphenoxy)ethyl)ammonio)propane-1-sulfonate (M6) is synthesized. However, despite a priori promising copolymerization suitability, copolymerization with the vinyl amide zwitterionic monomers could not be achieved.
Efficiently managing large state is a key challenge for data management systems. Traditionally, state is split into fast but volatile state in memory for processing and persistent but slow state on secondary storage for durability. Persistent memory (PMem), as a new technology in the storage hierarchy, blurs the lines between these states by offering both byte-addressability and low latency like DRAM as well persistence like secondary storage. These characteristics have the potential to cause a major performance shift in database systems.
Driven by the potential impact that PMem has on data management systems, in this thesis we explore their use of PMem. We first evaluate the performance of real PMem hardware in the form of Intel Optane in a wide range of setups. To this end, we propose PerMA-Bench, a configurable benchmark framework that allows users to evaluate the performance of customizable database-related PMem access. Based on experimental results obtained with PerMA-Bench, we discuss findings and identify general and implementation-specific aspects that influence PMem performance and should be considered in future work to improve PMem-aware designs. We then propose Viper, a hybrid PMem-DRAM key-value store. Based on PMem-aware access patterns, we show how to leverage PMem and DRAM efficiently to design a key database component. Our evaluation shows that Viper outperforms existing key-value stores by 4–18x for inserts while offering full data persistence and achieving similar or better lookup performance. Next, we show which changes must be made to integrate PMem components into larger systems. By the example of stream processing engines, we highlight limitations of current designs and propose a prototype engine that overcomes these limitations. This allows our prototype to fully leverage PMem's performance for its internal state management. Finally, in light of Optane's discontinuation, we discuss how insights from PMem research can be transferred to future multi-tier memory setups by the example of Compute Express Link (CXL).
Overall, we show that PMem offers high performance for state management, bridging the gap between fast but volatile DRAM and persistent but slow secondary storage. Although Optane was discontinued, new memory technologies are continuously emerging in various forms and we outline how novel designs for them can build on insights from existing PMem research.
Actin is one of the most highly conserved proteins in eukaryotes and distinct actin-related proteins with filament-forming properties are even found in prokaryotes. Due to these commonalities, actin-modulating proteins of many species share similar structural properties and proposed functions. The polymerization and depolymerization of actin are critical processes for a cell as they can contribute to shape changes to adapt to its environment and to move and distribute nutrients and cellular components within the cell. However, to what extent functions of actin-binding proteins are conserved between distantly related species, has only been addressed in a few cases. In this work, functions of Coronin-A (CorA) and Actin-interacting protein 1 (Aip1), two proteins involved in actin dynamics, were characterized. In addition, the interchangeability and function of Aip1 were investigated in two phylogenetically distant model organisms. The flowering plant Arabidopsis thaliana (encoding two homologs, AIP1-1 and AIP1-2) and in the amoeba Dictyostelium discoideum (encoding one homolog, DdAip1) were chosen because the functions of their actin cytoskeletons may differ in many aspects. Functional analyses between species were conducted for AIP1 homologs as flowering plants do not harbor a CorA gene.
In the first part of the study, the effect of four different mutation methods on the function of Coronin-A protein and the resulting phenotype in D. discoideum was revealed in two genetic knockouts, one RNAi knockdown and a sudden loss-of-function mutant created by chemical-induced dislocation (CID). The advantages and disadvantages of the different mutation methods on the motility, appearance and development of the amoebae were investigated, and the results showed that not all observed properties were affected with the same intensity. Remarkably, a new combination of Selection-Linked Integration and CID could be established.
In the second and third parts of the thesis, the exchange of Aip1 between plant and amoeba was carried out. For A. thaliana, the two homologs (AIP1-1 and AIP1-2) were analyzed for functionality as well as in D. discoideum. In the Aip1-deficient amoeba, rescue with AIP1-1 was more effective than with AIP1-2. The main results in the plant showed that in the aip1-2 mutant background, reintroduced AIP1-2 displayed the most efficient rescue and A. thaliana AIP1-1 rescued better than DdAip1. The choice of the tagging site was important for the function of Aip1 as steric hindrance is a problem. The DdAip1 was less effective when tagged at the C-terminus, while the plant AIP1s showed mixed results depending on the tag position. In conclusion, the foreign proteins partially rescued phenotypes of mutant plants and mutant amoebae, despite the organisms only being very distantly related in evolutionary terms.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
This dissertation examines the lack of clarity in the scientific literature regarding gender and negotiation performance. It is often claimed that men negotiate better than women, yet it is simultaneously emphasized that results strongly depend on context. Through the use of qualitative methods such as content analysis and critical mixed-methods review, the research question: "Are women truly inferior negotiators compared to men?" is addressed. The study comprises a descriptive and an interpretive part. The descriptive section illuminates various interpretations of gender-specific negotiation theory among citing authors, with 67% arguing for a general superiority of men. However, given the high variance in gender-specific differences, the focus should instead be on the context-dependency of negotiation performance. Generalized statements can be made within contexts, but not across them. In the interpretive section, several factors contributing to this misinterpretation are highlighted, including discrepancies in the definition of negotiation performance and distortions in research communication.. From a scientific perspective, this study underscores the need for a nuanced sociological analysis and warns against the one-sided acceptance of inaccurate scientific interpretations. From a practical standpoint, it amplifies the voices of women affected by biased research paradigms. Overall, the dissertation clarifies the theory of gender-specific negotiation performance and advocates for the elimination of biases in scientific discourse.
With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind’s fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation – the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere.
By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.
Volcanic hydrothermal systems are an integral part of most volcanoes and typically involve a heat source, adequate fluid supply, and fracture or pore systems through which the fluids can circulate within the volcanic edifice. Associated with this are subtle but powerful processes that can significantly influence the evolution of volcanic activity or the stability of the near-surface volcanic system through mechanical weakening, permeability reduction, and sealing of the affected volcanic rock. These processes are well constrained for rock samples by laboratory analyses but are still difficult to extrapolate and evaluate at the scale of an entire volcano. Advances in unmanned aircraft systems (UAS), sensor technology, and photogrammetric processing routines now allow us to image volcanic surfaces at the centimeter scale and thus study volcanic hydrothermal systems in great detail. This thesis aims to explore the potential of UAS approaches for studying the structures, processes, and dynamics of volcanic hydrothermal systems but also to develop methodological approaches to uncover secondary information hidden in the data, capable of indicating spatiotemporal dynamics or potentially critical developments associated with hydrothermal alteration. To accomplish this, the thesis describes the investigation of two near-surface volcanic hydrothermal systems, the El Tatio geyser field in Chile and the fumarole field of La Fossa di Vulcano (Italy), both of which are among the best-studied sites of their kind. Through image analysis, statistical, and spatial analyses we have been able to provide the most detailed structural images of both study sites to date, with new insights into the driving forces of such systems but also revealing new potential controls, which are summarized in conceptual site-specific models. Furthermore, the thesis explores methodological remote sensing approaches to detect, classify and constrain hydrothermal alteration and surface degassing from UAS-derived data, evaluated them by mineralogical and chemical ground-truthing, and compares the alteration pattern with the present-day degassing activity. A significant contribution of the often neglected diffuse degassing activity to the total amount of degassing is revealed and constrains secondary processes and dynamics associated with hydrothermal alteration that lead to potentially critical developments like surface sealing. The results and methods used provide new approaches for alteration research, for the monitoring of degassing and alteration effects, and for thermal monitoring of fumarole fields, with the potential to be incorporated into volcano monitoring routines.
Electricity production contributes to a significant share of greenhouse gas emissions in Europe and is thus an important driver of climate change. To fulfil the Paris Agreement, the European Union (EU) needs a rapid transition to a fully decarbonised power production system. Presumably, such a system will be largely based on renewables. So far, many EU countries have supported a shift towards renewables such as solar and wind power using support schemes, but the economic and political context is changing. Renewables are now cheaper than ever before and have become cost-competitive with conventional technologies. Therefore, European policymakers are striving to better integrate renewables into a competitive market and to increase the cost-effectiveness of the expansion of renewables. The first step was to replace previous fixed-price schemes with competitive auctions. In a second step, these auctions have become more technology-open. Finally, some governments may phase out any support for renewables and fully expose them to the competitive power market.
However, such policy changes may be at odds with the need to rapidly expand renewables and meet national targets due to market characteristics and investors’ risk perception. Without support, price risks are higher, and it may be difficult to meet an investor’s income expectations. Furthermore, policy changes across different countries could have unexpected effects if power markets are interconnected and investors able to shift their investments. Finally, in multi-technology auctions, technologies may dominate, which can be a risk for long-term power system reliability. Therefore, in my thesis, I explore the effects of phasing out support policies for renewables, of coordinating these phase-outs across countries, and of using multi-technology designs. I expand the public policy literature about investment behaviour and policy design as well as policy change and coordination, and I further develop an agent-based model.
The main questions of my thesis are what the cost and deployment effects of gradually exposing renewables to market forces would be and how coordination between countries affects investors’ decisions and market prices.. In my three contributions to the academic literature, I use different methods and come to the following results. In the first contribution, I use a conjoint analysis and market simulation to evaluate the effects of phasing out support or reintroducing feed-in tariffs from the perspective of investors. I find that a phase-out leads to investment shifts, either to other still-supported technologies or to other countries that continue to offer support. I conclude that the coordination of policy changes avoids such shifts.. In the second contribution, I integrate the empirically-derived preferences from the first contribution in to an agent-based power system model of two countries to simulate the effects of ending auctions for renewables. I find that this slows the energy transition, and that cross-border effects are relevant. Consequently, continued support is necessary to meet the national renewables targets. In the third contribution, I analyse the outcome of past multi-technology auctions using descriptive statistics, regression analysis as well as case study comparisons. I find that the outcomes are skewed towards single technologies. This cannot be explained by individual design elements of the auctions, but rather results from context-specific and country-specific characteristics. Based on this, I discuss potential implications for long-term power system reliability.
The main conclusions of my thesis are that a complete phase-out of renewables support would slow down the energy transition and thus jeopardize climate targets, and that multi-technology auctions may pose a risk for some countries, especially those that cannot regulate an unbalanced power plant portfolio in the long term. If policymakers decide to continue supporting renewables, they may consider adopting technology-specific auctions to better steer their portfolio. In contrast, if policymakers still want to phase out support, they should coordinate these policy changes with other countries. Otherwise, overall transition costs can be higher, because investment decisions shift to still-supported but more expensive technologies.
This dissertation examines the integration of incongruent visual-scene and morphological-case information (“cues”) in building thematic-role representations of spoken relative clauses in German.
Addressing the mutual influence of visual and linguistic processing, the Coordinated Interplay Account (CIA) describes a mechanism in two steps supporting visuo-linguistic integration (Knoeferle & Crocker, 2006, Cog Sci). However, the outcomes and dynamics of integrating incongruent thematic-role representations from distinct sources have been investigated scarcely. Further, there is evidence that both second-language (L2) and older speakers may rely on non-syntactic cues relatively more than first-language (L1)/young speakers. Yet, the role of visual information for thematic-role comprehension has not been measured in L2 speakers, and only limitedly across the adult lifespan.
Thematically unambiguous canonically ordered (subject-extracted) and noncanonically ordered (object-extracted) spoken relative clauses in German (see 1a-b) were presented in isolation and alongside visual scenes conveying either the same (congruent) or the opposite (incongruent) thematic relations as the sentence did.
1 a Das ist der Koch, der die Braut verfolgt.
This is the.NOM cook who.NOM the.ACC bride follows
This is the cook who is following the bride.
b Das ist der Koch, den die Braut verfolgt.
This is the.NOM cook whom.ACC the.NOM bride follows
This is the cook whom the bride is following.
The relative contribution of each cue to thematic-role representations was assessed with agent identification. Accuracy and latency data were collected post-sentence from a sample of L1 and L2 speakers (Zona & Felser, 2023), and from a sample of L1 speakers from across the adult lifespan (Zona & Reifegerste, under review). In addition, the moment-by-moment dynamics of thematic-role assignment were investigated with mouse tracking in a young L1 sample (Zona, under review).
The following questions were addressed: (1) How do visual scenes influence thematic-role representations of canonical and noncanonical sentences? (2) How does reliance on visual-scene, case, and word-order cues vary in L1 and L2 speakers? (3) How does reliance on visual-scene, case, and word-order cues change across the lifespan?
The results showed reliable effects of incongruence of visually and linguistically conveyed thematic relations on thematic-role representations. Incongruent (vs. congruent) scenes yielded slower and less accurate responses to agent-identification probes presented post-sentence. The recently inspected agent was considered as the most likely agent ~300ms after trial onset, and the convergence of visual scenes and word order enabled comprehenders to assign thematic roles predictively.
L2 (vs. L1) participants relied more on word order overall. In response to noncanonical clauses presented with incongruent visual scenes, sensitivity to case predicted the size of incongruence effects better than L1-L2 grouping. These results suggest that the individual’s ability to exploit specific cues might predict their weighting.
Sensitivity to case was stable throughout the lifespan, while visual effects increased with increasing age and were modulated by individual interference-inhibition levels. Thus, age-related changes in comprehension may stem from stronger reliance on visually (vs. linguistically) conveyed meaning.
These patterns represent evidence for a recent-role preference – i.e., a tendency to re-assign visually conveyed thematic roles to the same referents in temporally coordinated utterances. The findings (i) extend the generalizability of CIA predictions across stimuli, tasks, populations, and measures of interest, (ii) contribute to specifying the outcomes and mechanisms of detecting and indexing incongruent representations within the CIA, and (iii) speak to current efforts to understand the sources of variability in sentence comprehension.
Column-oriented database systems can efficiently process transactional and analytical queries on a single node. However, increasing or peak analytical loads can quickly saturate single-node database systems. Then, a common scale-out option is using a database cluster with a single primary node for transaction processing and read-only replicas. Using (the naive) full replication, queries are distributed among nodes independently of the accessed data. This approach is relatively expensive because all nodes must store all data and apply all data modifications caused by inserts, deletes, or updates.
In contrast to full replication, partial replication is a more cost-efficient implementation: Instead of duplicating all data to all replica nodes, partial replicas store only a subset of the data while being able to process a large workload share. Besides lower storage costs, partial replicas enable (i) better scaling because replicas must potentially synchronize only subsets of the data modifications and thus have more capacity for read-only queries and (ii) better elasticity because replicas have to load less data and can be set up faster. However, splitting the overall workload evenly among the replica nodes while optimizing the data allocation is a challenging assignment problem.
The calculation of optimized data allocations in a partially replicated database cluster can be modeled using integer linear programming (ILP). ILP is a common approach for solving assignment problems, also in the context of database systems. Because ILP is not scalable, existing approaches (also for calculating partial allocations) often fall back to simple (e.g., greedy) heuristics for larger problem instances. Simple heuristics may work well but can lose optimization potential.
In this thesis, we present optimal and ILP-based heuristic programming models for calculating data fragment allocations for partially replicated database clusters. Using ILP, we are flexible to extend our models to (i) consider data modifications and reallocations and (ii) increase the robustness of allocations to compensate for node failures and workload uncertainty. We evaluate our approaches for TPC-H, TPC-DS, and a real-world accounting workload and compare the results to state-of-the-art allocation approaches. Our evaluations show significant improvements for varied allocation’s properties: Compared to existing approaches, we can, for example, (i) almost halve the amount of allocated data, (ii) improve the throughput in case of node failures and workload uncertainty while using even less memory, (iii) halve the costs of data modifications, and (iv) reallocate less than 90% of data when adding a node to the cluster. Importantly, we can calculate the corresponding ILP-based heuristic solutions within a few seconds. Finally, we demonstrate that the ideas of our ILP-based heuristics are also applicable to the index selection problem.
Volatile supply and sales markets, coupled with increasing product individualization and complex production processes, present significant challenges for manufacturing companies. These must navigate and adapt to ever-shifting external and internal factors while ensuring robustness against process variabilities and unforeseen events. This has a pronounced impact on production control, which serves as the operational intersection between production planning and the shop- floor resources, and necessitates the capability to manage intricate process interdependencies effectively. Considering the increasing dynamics and product diversification, alongside the need to maintain constant production performances, the implementation of innovative control strategies becomes crucial.
In recent years, the integration of Industry 4.0 technologies and machine learning methods has gained prominence in addressing emerging challenges in production applications. Within this context, this cumulative thesis analyzes deep learning based production systems based on five publications. Particular attention is paid to the applications of deep reinforcement learning, aiming to explore its potential in dynamic control contexts. Analysis reveal that deep reinforcement learning excels in various applications, especially in dynamic production control tasks. Its efficacy can be attributed to its interactive learning and real-time operational model. However, despite its evident utility, there are notable structural, organizational, and algorithmic gaps in the prevailing research. A predominant portion of deep reinforcement learning based approaches is limited to specific job shop scenarios and often overlooks the potential synergies in combined resources. Furthermore, it highlights the rare implementation of multi-agent systems and semi-heterarchical systems in practical settings. A notable gap remains in the integration of deep reinforcement learning into a hyper-heuristic.
To bridge these research gaps, this thesis introduces a deep reinforcement learning based hyper- heuristic for the control of modular production systems, developed in accordance with the design science research methodology. Implemented within a semi-heterarchical multi-agent framework, this approach achieves a threefold reduction in control and optimisation complexity while ensuring high scalability, adaptability, and robustness of the system. In comparative benchmarks, this control methodology outperforms rule-based heuristics, reducing throughput times and tardiness, and effectively incorporates customer and order-centric metrics. The control artifact facilitates a rapid scenario generation, motivating for further research efforts and bridging the gap to real-world applications. The overarching goal is to foster a synergy between theoretical insights and practical solutions, thereby enriching scientific discourse and addressing current industrial challenges.
Aging is associated with bone loss, which can lead to osteoporosis and high fracture risk. This coincides with the enhanced formation of bone marrow adipose tissue (BMAT), suggesting a negative effect of bone marrow adipocytes on skeletal health. Increased BMAT formation is also observed in pathologies such as obesity, type 2 diabetes and osteoporosis. However, a subset of bone marrow adipocytes forming the constitutive BMAT (cBMAT), arise early in life in the distal skeleton, contain high levels of unsaturated fatty acids and are thought to provide a physiological function. Regulated BMAT (rBMAT) forms during aging and obesity in proximal regions of the bone and contain a large proportion of saturated fatty acids. Paradoxically, BMAT accumulation is also enhanced during caloric restriction (CR), a life-span extending dietary intervention. This indicates, that different types of BMAT can form in response to opposing nutritional stimuli with potentially different functions.
To this end, two types of nutritional interventions, CR and high fat diet (HFD), that are both described to induce BMAT accumulation were carried out. CR markedly increased BMAT formation in the proximal tibia and led to a higher proportion of unsaturated fatty acids, making it similar to the physiological cBMAT. Additionally, proximal and diaphyseal tibia regions displayed higher adiponectin expression. In aged mice, CR was associated with an improved trabecular bone structure. Taken together, these findings demonstrate, that the type of BMAT that forms during CR might provide beneficial effects for local bone stem/progenitor cells and metabolic health. The HFD intervention performed in this thesis showed no effect on BMAT accumulation and bone microstructure. RNA Seq analysis revealed alterations in the composition of the collagen-containing extracellular matrix (ECM).
In order to investigate the effects of glucose homeostasis on osteogenesis, differentiation capacity of immortalized multipotent mesenchymal stromal cells (MSCs) and osteochondrogenic progenitor cells (OPCs) was analyzed. Insulin improved differentiation in both cell types, however, combination of with a high glucose concentration led to an impaired mineralization of the ECM. In the MSCs, this was accompanied by the formation of adipocytes, indicating negative effects of the adipocytes formed during hyperglycemic conditions on mineralization processes. However, the altered mineralization pattern and structure of the ECM was also observed in OPCs, which did not form any adipocytes, suggesting further negative effects of a hyperglycemic environment on osteogenic differentiation.
In summary, the work provided in this thesis demonstrated that differentiation commitment of bone-resident stem cells can be altered through nutrient availability, specifically glucose. Surprisingly, both high nutrient supply, e.g. the hyperglycemic cell culture conditions, and low nutrient supply, e.g. CR, can induce adipogenic differentiation. However, while CR-induced adipocyte formation was associated with improved trabecular bone structure, adipocyte formation in a hyperglycemic cell-culture environment hampered mineralization. This thesis provides further evidence for the existence of different types of BMAT with specific functions.
Microalgae have been recognized as a promising green production platform for recombinant proteins. The majority of studies on recombinant protein expression have been conducted in the green microalga C. reinhardtii. While promising improvement regarding nuclear transgene expression in this alga has been made, it is still inefficient due to epigenetic silencing, often resulting in low yields that are not competitive with other expressor organisms. Other microalgal species might be better suited for high-level protein expression, but are limited in their availability of molecular tools.
The red microalga Porphyridium purpureum recently emerged as candidate for the production of recombinant proteins. It is promising in that transformation vectors are episomally maintained as autonomously replicating plasmids in the nucleus at a high copy number, thus leading to high expression values in this red alga.
In this work, we expand the genetic tools for P. purpureum and investigate parameters that govern efficient transgene expression. We provide an improved transformation protocol to streamline the generation of transgenic lines in this organism. After being able to efficiently generate transgenic lines, we showed that codon usage is a main determinant of high-level transgene expression, not only at the protein level but also at the level of mRNA accumulation. The optimized expression constructs resulted in YFP accumulation up to an unprecedented 5% of the total soluble protein. Furthermore, we designed new constructs conferring efficient transgene expression into the culture medium, simplifying purification and harvests of recombinant proteins. To further improve transgene expression, we tested endogenous promoters driving the most highly transcribed genes in P. purpureum and found minor increase of YFP accumulation.
We employed the previous findings to express complex viral antigens from the hepatitis B virus and the hepatitis C virus in P. purpureum to demonstrate its feasibility as producer of biopharmaceuticals. The viral glycoproteins were successfully produced to high levels and could reach their native confirmation, indicating a functional glycosylation machinery and an appropriate folding environment in this red alga. We could successfully upscale the biomass production of transgenic lines and with that provide enough material for immunization trials in mice that were performed in collaboration. These trials showed no toxicity of neither the biomass nor the purified antigens, and, additionally, the algal-produced antigens were able to elicit a strong and specific immune response.
The results presented in this work pave the way for P. purpureum as a new promising producer organism for biopharmaceuticals in the microalgal field.
The origin and structure of magnetic fields in the Galaxy are largely unknown. What is known is that they are essential for several astrophysical processes, in particular the propagation of cosmic rays. Our ability to describe the propagation of cosmic rays through the Galaxy is severely limited by the lack of observational data needed to probe the structure of the Galactic magnetic field on many different length scales. This is particularly true for modelling the propagation of cosmic rays into the Galactic halo, where our knowledge of the magnetic field is particularly poor.
In the last decade, observations of the Galactic halo in different frequency regimes have revealed the existence of out-of-plane bubble emission in the Galactic halo. In gamma rays these bubbles have been termed Fermi bubbles with a radial extent of ≈ 3 kpc and an azimuthal height of ≈ 6 kpc. The radio counterparts of the Fermi bubbles were seen by both the S-PASS telescopes and the Planck satellite, and showed a clear spatial overlap. The X-ray counterparts of the Fermi bubbles were named eROSITA bubbles after the eROSITA satellite, with a radial width of ≈ 7 kpc and an azimuthal height of ≈ 14 kpc. Taken together, these observations suggest the presence of large extended Galactic Halo Bubbles (GHB) and have stimulated interest in exploring the less explored Galactic halo.
In this thesis, a new toy model (GHB model) for the magnetic field and non-thermal electron distribution in the Galactic halo has been proposed. The new toy model has been used to produce polarised synchrotron emission sky maps. Chi-square analysis was used to compare the synthetic skymaps with the Planck 30 GHz polarised skymaps. The obtained constraints on the strength and azimuthal height were found to be in agreement with the S-PASS radio observations.
The upper, lower and best-fit values obtained from the above chi-squared analysis were used to generate three separate toy models. These three models were used to propagate ultra-high energy cosmic rays. This study was carried out for two potential sources, Centaurus A and NGC 253, to produce magnification maps and arrival direction skymaps. The simulated arrival direction skymaps were found to be consistent with the hotspots of Centaurus A and NGC 253 as seen in the observed arrival direction skymaps provided by the Pierre Auger Observatory (PAO).
The turbulent magnetic field component of the GHB model was also used to investigate the extragalactic dipole suppression seen by PAO. UHECRs with an extragalactic dipole were forward-tracked through the turbulent GHB model at different field strengths. The suppression in the dipole due to the varying diffusion coefficient from the simulations was noted. The results could also be compared with an analytical analogy of electrostatics. The simulations of the extragalactic dipole suppression were in agreement with similar studies carried out for galactic cosmic rays.
Relativistic pair beams produced in the cosmic voids by TeV gamma rays from blazars are expected to produce a detectable GeV-scale cascade emission missing in the observations. The suppression of this secondary cascade implies either the deflection of the pair beam by intergalactic magnetic fields (IGMFs) or an energy loss of the beam due to the electrostatic beam-plasma instability. IGMF of femto-Gauss strength is sufficient to significantly deflect the pair beams reducing the flux of secondary cascade below the observational limits. A similar flux reduction may result in the absence of the IGMF from the beam energy loss by the instability before the inverse Compton cooling. This dissertation consists of two studies about the instability role in the evolution of blazar-induced beams.
Firstly, we investigated the effect of sub-fG level IGMF on the beam energy loss by the instability. Considering IGMF with correlation lengths smaller than a few kpc, we found that such fields increase the transverse momentum of the pair beam particles, dramatically reducing the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. Our results show that the IGMF eliminates beam plasma instability as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission and hence can be excluded.
Secondly, we probed how the beam-plasma instability feeds back on the beam, using a realistic two-dimensional beam distribution. We found that the instability broadens the beam opening angles significantly without any significant energy loss, thus confirming a recent feedback study on a simplified one-dimensional beam distribution. However, narrowing diffusion feedback of the beam particles with Lorentz factors less than 1e6 might become relevant even though initially it is negligible. Finally, when considering the continuous creation of TeV pairs, we found that the beam distribution and the wave spectrum reach a new quasi-steady state, in which the scattering of beam particles persists and the beam opening angle may increase by a factor of hundreds. This new intrinsic scattering of the cascade can result in time delays of around ten years, thus potentially mimicking the IGMF deflection. Understanding the implications on the GeV cascade emission requires accounting for inverse Compton cooling and simulating the beam-plasma system at different points in the IGM.
Mindful Eating
(2024)
Maladaptive eating behaviors such as emotional eating, external eating, and loss-of-control eating are widespread in the general population. Moreover, they are associated to adverse health outcomes and well-known for their role in the development and maintenance of eating disorders and obesity (i.e., eating and weight disorders). Eating and weight disorders are associated with crucial burden for individuals as well as high costs for society in general. At the same time, corresponding treatments yield poor outcomes. Thus, innovative concepts are needed to improve prevention and treatment of these conditions.
The Buddhist concept of mindfulness (i.e., paying attention to the present moment without judgement) and its delivery via mindfulness-based intervention programs (MBPs) has gained wide popularity in the area of maladaptive eating behaviors and associated eating and weight disorders over the last two decades. Though previous findings on their effects seem promising, the current assessment of mindfulness and its mere application via multi-component MBPs hampers to draw conclusions on the extent to which mindfulness-immanent qualities actually account for the effects (e.g., the modification of maladaptive eating behaviors). However, this knowledge is pivotal for interpreting previous effects correctly and for avoiding to cause harm in particularly vulnerable groups such as those with eating and weight disorders.
To address these shortcomings, recent research has focused on the context-specific approach of mindful eating (ME) to investigate underlying mechanisms of action. ME can be considered a subdomain of generic mindfulness describing it specifically in relation to the process of eating and associated feelings, thoughts, and motives, thus including a variety of different attitudes and behaviors. However, there is no universal operationalization and the current assessment of ME suffers from different limitations. Specifically, current measurement instruments are not suited for a comprehensive assessment of the multiple facets of the construct that are currently discussed as important in the literature. This in turn hampers comparisons of different ME facets which would allow to evaluate their particular effect on maladaptive eating behaviors. This knowledge is needed to tailor prevention and treatment of associated eating and weight disorders properly and to explore potential underlying mechanisms of action which have so far been proposed mainly on theoretical grounds.
The dissertation at hand aims to provide evidence-based fundamental research that contributes to our understanding of how mindfulness, more specifically its context-specific form of ME, impacts maladaptive eating behaviors and, consequently, how it could be used appropriately to enrich the current prevention and treatment approaches for eating and weight disorders in the future.
Specifically, in this thesis, three scientific manuscripts applying several qualitative and quantitative techniques in four sequential studies are presented. These manuscripts were published in or submitted to three scientific peer-reviewed journals to shed light on the following questions:
I. How can ME be measured comprehensively and in a reliable and valid way to advance the understanding of how mindfulness works in the context of eating?
II. Does the context-specific construct of ME have an advantage over the generic concept in advancing the understanding of how mindfulness is related to maladaptive eating behaviors?
III. Which ME facets are particularly useful in explaining maladaptive eating behaviors?
IV. Does training a particular ME facet result in changes in maladaptive eating behaviors?
To answer the first research question (Paper 1), a multi-method approach using three subsequent studies was applied to develop and validate a comprehensive self-report instrument to assess the multidimensional construct of ME - the Mindful Eating Inventory (MEI). Study 1 aimed to create an initial version of the MEI by following a three-step approach: First, a comprehensive item pool was compiled by including selected and adapted items of the existing ME questionnaires and supplementing them with items derived from an extensive literature review. Second, the preliminary item pool was complemented and checked for content validity by experts in the field of eating behavior and/or mindfulness (N = 15). Third, the item pool was further refined through qualitative methods: Three focus groups comprising laypersons (N = 16) were used as a check for applicability. Subsequently, think-aloud protocols (N = 10) served as a last check of comprehensibility and elimination of ambiguities.
The resulting initial MEI version was tested in Study 2 in an online convenience sample (N = 828) to explore its factor structure using exploratory factor analysis (EFA). Results were used to shorten the questionnaire in accordance with qualitative and quantitative criteria yielding the final MEI version which encompasses 30 items. These items were assigned to seven ME facets: (1) ‘Accepting and Non-attached Attitude towards one’s own eating experience’ (ANA), (2) ‘Awareness of Senses while Eating’ (ASE), (3) ‘Eating in Response to awareness of Fullness‘ (ERF), (4) ‘Awareness of eating Triggers and Motives’ (ATM), (5) ‘Interconnectedness’ (CON), (6) ‘Non-Reactive Stance’ (NRS) and (7) Focused Attention on Eating’ (FAE).
Study 3 sought to confirm the found facets and the corresponding factor structure in an independent online convenience sample (N = 612) using confirmatory factor analysis (CFA). The study served as further indication of the assumed multidimensionality of ME (the correlational seven-factor model was shown to be superior to a single-factor model). Psychometric properties of the MEI, regarding factorial validity, internal consistency, retest-reliability, and observed criterion validity using a wide range of eating-specific and general health-related outcomes, showed the inventory to be suitable for a comprehensive, reliable and valid assessment of ME. These findings were complemented by demonstrating measurement invariance of the MEI regarding gender. In accordance with the factor structure of the MEI, Paper 1 offers an empirically-derived definition of ME, succeeding in overcoming ambiguities and problems of previous attempts at defining the construct.
To answer the second and third research questions (Paper 2) a subsample of Study 2 from the MEI validation studies (N = 292) was analyzed. Incremental validity of ME beyond generic mindfulness was shown using hierarchical regression models concerning the outcome variables of maladaptive eating behaviors (emotional eating and uncontrolled eating) and nutrition behaviors (consumption of energy-dense food). Multiple regression analyses were applied to investigate the impact of the seven different ME facets (identified in Paper 1) on the same outcome variables. The following ME facets significantly contributed to explaining variance in maladaptive eating and nutrition behaviors: Accepting and Non-attached Attitude towards one`s own eating experience (ANA), Eating in Response to awareness of Fullness (ERF), the Awareness of eating Triggers and Motives (ATM), and a Non-Reactive Stance (NRS, i.e., an observing, non-impulsive attitude towards eating triggers). Results suggest that these ME facets are promising variables to consider when a) investigating potential underlying mechanisms of mindfulness and MBPs in the context of eating and b) addressing maladaptive eating behaviors in general as well as in the prevention and treatment of eating and weight disorders.
To answer the fourth research question (Paper 3), a training on an isolated exercise (‘9 Hunger’) based on the previously identified ME facet ATM was designed to explore its particular association with changes in maladaptive eating behaviors and thus to preliminary explore one possible mechanism of action. The online study was realized using a randomized controlled trial (RCT) design. Latent Change Scores (LCS) across three measurement points (before the training, directly after the training and three months later) were compared between the intervention group (n = 211) and a waitlist control group (n = 188). Short- and longer-term effects of the training could be shown on maladaptive eating behaviors (emotional eating, external eating, loss-of-control eating) and associated outcomes (intuitive eating, ME, self-compassion, well-being). Findings serve as preliminary empirical evidence that MBPs might influence maladaptive eating behaviors through an enhanced non-judgmental awareness of and distinguishment between eating motives and triggers (i.e., ATM). This mechanism of action had previously only been hypothesized from a theoretical perspective. Since maladaptive eating behaviors are associated with eating and weight disorders, the findings can enhance our understanding of the general effects of MBPs on these conditions.
The integration of the different findings leads to several suggestions of how ME might enrich different kinds of future interventions on maladaptive eating behaviors to improve health in general or the prevention and treatment of eating and weight disorders in particular. Strengths of the thesis (e.g., deliberate specific methodology, variety of designs and methods, high number of participants) are emphasized. The main limitations particularly regarding sample characteristics (e.g., higher level of formal education, fewer males, self-selected) are discussed to arrive at an outline for future studies (e.g., including multi-modal-multi-method approaches, clinical eating disorder samples and youth samples) to improve upcoming research on ME and underlying mechanisms of action of MBPs for maladaptive eating behaviors and associated eating and weight disorders.
This thesis enriches current research on mindfulness in the context of eating by providing fundamental research on the core of the ME construct. Thereby it delivers a reliable and valid instrument to comprehensively assess ME in future studies as well as an operational definition of the construct. Findings on ME facet level might inform upcoming research and practice on how to address maladaptive eating behaviors appropriately in interventions. The ME skill ‘Awareness of eating Triggers and Motives (ATM)’ as one particular mechanism of action should be further investigated in representative community and specific clinical samples to examine the validity of the results in these groups and to justify an application of the concept to the general population as well as to subgroups with eating and weight disorders in particular.
In conclusion, findings of the current thesis can be used to set future research on mindfulness, more specifically ME, and its underlying mechanism in the context of eating on a more evidence-based footing. This knowledge can inform upcoming prevention and treatment to tailor MBPs on maladaptive eating behaviors and associated eating and weight disorders appropriately.
Cross-sectional associations of dietary biomarker patterns with health and nutritional status
(2024)
Diglossic translanguaging
(2024)
This book examines how German-speaking Jews living in Berlin make sense and make use of their multilingual repertoire. With a focus on lexical variation, the book demonstrates how speakers integrate Yiddish and Hebrew elements into German for indexing belonging and for positioning themselves within the Jewish community. Linguistic choices are shaped by language ideologies (e.g., authenticity, prescriptivism, nostalgia). Speakers translanguage when using their multilingual repertoire, but do so in a diglossic way, using elements from different languages for specific domains
Assessing the impact of global change on hydrological systems is one of the greatest hydrological challenges of our time. Changes in land cover, land use, and climate have an impact on water quantity, quality, and temporal availability. There is a widespread consensus that, given the far-reaching effects of global change, hydrological systems can no longer be viewed as static in their structure; instead, they must be regarded as entire ecosystems, wherein hydrological processes interact and coevolve with biological, geomorphological, and pedological processes. To accurately predict the hydrological response under the impact of global change, it is essential to understand this complex coevolution. The knowledge of how hydrological processes, in particular the formation of subsurface (preferential) flow paths, evolve within this coevolution and how they feed back to the other processes is still very limited due to a lack of observational data.
At the hillslope scale, this intertwined system of interactions is known as the hillslope feedback cycle. This thesis aims to enhance our understanding of the hillslope feedback cycle by studying the coevolution of hillslope structure and hillslope hydrological response. Using chronosequences of moraines in two glacial forefields developed from siliceous and calcareous glacial till, the four studies shed light on the complex coevolution of hydrological, biological, and structural hillslope properties, as well as subsurface hydrological flow paths over an evolutionary period of 10 millennia in these two contrasting geologies. The findings indicate that the contrasting properties of siliceous and calcareous parent materials lead
to variations in soil structure, permeability, and water storage. As a result, different plant species and vegetation types are favored on siliceous versus calcareous parent material, leading to diverse ecosystems with distinct hydrological dynamics. The siliceous parent material was found to show a higher activity level in driving the coevolution. The soil pH resulting from parent material weathering emerges as a crucial factor, influencing vegetation development, soil formation, and consequently, hydrology. The acidic weathering of the siliceous parent material favored the accumulation of organic matter, increasing the soils’ water storage capacity and attracting acid-loving shrubs, which further promoted organic matter accumulation and ultimately led to podsolization after 10 000 years. Tracer experiments revealed that the subsurface flow path evolution was influenced by soil and vegetation development, and vice versa. Subsurface flow paths changed from vertical, heterogeneous matrix flow to finger-like flow paths over a few hundred years, evolving into macropore flow, water storage, and lateral subsurface flow after several thousand years. The changes in flow paths among younger age classes were driven by weathering processes altering soil structure, as well as by vegetation development and root activity. In the older age
class, the transition to more water storage and lateral flow was attributed to substantial organic matter accumulation and ongoing podsolization. The rapid vertical water transport in the finger-like flow paths, along with the conductive sandy material, contributed to podsolization and thus to the shift in the hillslope hydrological response.
In contrast, the calcareous site possesses a high pH buffering capacity, creating a neutral to basic environment with relatively low accumulation of dead organic matter, resulting in a lower water storage capacity and the establishment of predominantly grass vegetation. The coevolution was found to be less dynamic over the millennia. Similar to the siliceous site, significant changes in subsurface flow paths occurred between the young age classes. However, unlike the siliceous site, the subsurface flow paths at the calcareous site only altered in shape and not in direction. Tracer experiments showed that flow paths changed from vertical, heterogeneous matrix flow to vertical, finger-like flow paths after a few hundred to thousands of years, which was driven by root activities and weathering processes. Despite having a finer soil texture, water storage at the calcareous site was significantly lower than at the siliceous site, and water transport remained primarily rapid and vertical, contributing to the flourishing of grass vegetation.
The studies elucidated that changes in flow paths are predominantly shaped by the characteristics of the parent material and its weathering products, along with their complex interactions with initial water flow paths and vegetation development. Time, on the other hand, was not found to be a primary factor in describing the evolution of the hydrological response. This thesis makes a valuable contribution to closing the gap in the observations of the coevolution of hydrological processes within the hillslope feedback cycle, which is important to improve predictions of hydrological processes in changing landscapes. Furthermore, it emphasizes the importance of interdisciplinary studies in addressing the hydrological challenges arising from global change.
Rapidly growing seismic and macroseismic databases and simplified access to advanced machine learning methods have in recent years opened up vast opportunities to address challenges in engineering and strong motion seismology from novel, datacentric perspectives. In this thesis, I explore the opportunities of such perspectives for the tasks of ground motion modeling and rapid earthquake impact assessment, tasks with major implications for long-term earthquake disaster mitigation.
In my first study, I utilize the rich strong motion database from the Kanto basin, Japan, and apply the U-Net artificial neural network architecture to develop a deep learning based ground motion model. The operational prototype provides statistical estimates of expected ground shaking, given descriptions of a specific earthquake source, wave propagation paths, and geophysical site conditions. The U-Net interprets ground motion data in its spatial context, potentially taking into account, for example, the geological properties in the vicinity of observation sites. Predictions of ground motion intensity are thereby calibrated to individual observation sites and earthquake locations.
The second study addresses the explicit incorporation of rupture forward directivity into ground motion modeling. Incorporation of this phenomenon, causing strong, pulse like ground shaking in the vicinity of earthquake sources, is usually associated with an intolerable increase in computational demand during probabilistic seismic hazard analysis (PSHA) calculations. I suggest an approach in which I utilize an artificial neural network to efficiently approximate the average, directivity-related adjustment to ground motion predictions for earthquake ruptures from the 2022 New Zealand National Seismic Hazard Model. The practical implementation in an actual PSHA calculation demonstrates the efficiency and operational readiness of my model. In a follow-up study, I present a proof of concept for an alternative strategy in which I target the generalizing applicability to ruptures other than those from the New Zealand National Seismic Hazard Model.
In the third study, I address the usability of pseudo-intensity reports obtained from macroseismic observations by non-expert citizens for rapid impact assessment. I demonstrate that the statistical properties of pseudo-intensity collections describing the intensity of shaking are correlated with the societal impact of earthquakes. In a second step, I develop a probabilistic model that, within minutes of an event, quantifies the probability of an earthquake to cause considerable societal impact. Under certain conditions, such a quick and preliminary method might be useful to support decision makers in their efforts to organize auxiliary measures for earthquake disaster response while results from more elaborate impact assessment frameworks are not yet available.
The application of machine learning methods to datasets that only partially reveal characteristics of Big Data, qualify the majority of results obtained in this thesis as explorative insights rather than ready-to-use solutions to real world problems. The practical usefulness of this work will be better assessed in the future by applying the approaches developed to growing and increasingly complex data sets.
Heat stress (HS) is a major abiotic stress that negatively affects plant growth and productivity. However, plants have developed various adaptive mechanisms to cope with HS, including the acquisition and maintenance of thermotolerance, which allows them to respond more effectively to subsequent stress episodes. HS memory includes type II transcriptional memory which is characterized by enhanced re-induction of a subset of HS memory genes upon recurrent HS. In this study, new regulators of HS memory in A. thaliana were identified through the characterization of rein mutants.
The rein1 mutant carries a premature stop in CYCLIN-DEPENDENT-KINASE 8 (CDK8) which is part of the cyclin kinase module of the Mediator complex. Rein1 seedlings show impaired type II transcriptional memory in multiple heat-responsive genes upon re-exposure to HS. Additionally, the mutants exhibit a significant deficiency in HS memory at the physiological level. Interaction studies conducted in this work indicate that CDK8 associates with the memory HEAT SHOCK FACTORs HSAF2 and HSFA3. The results suggest that CDK8 plays a crucial role in HS memory in plants together with other memory HSFs, which may be potential targets of the CDK8 kinase function. Understanding the role and interaction network of the Mediator complex during HS-induced transcriptional memory will be an exciting aspect of future HS memory research.
The second characterized mutant, rein2, was selected based on its strongly impaired pAPX2::LUC re-induction phenotype. In gene expression analysis, the mutant revealed additional defects in the initial induction of HS memory genes. Along with this observation, basal thermotolerance was impaired similarly as HS memory at the physiological level in rein2. Sequencing of backcrossed bulk segregants with subsequent fine mapping narrowed the location of REIN2 to a 1 Mb region on chromosome 1. This interval contains the At1g65440 gene, which encodes the histone chaperone SPT6L. SPT6L interacts with chromatin remodelers and bridges them to the transcription machinery to regulate nucleosome and Pol II occupancy around the transcriptional start site. The EMS-induced missense mutation in SPT6L may cause altered HS-induced gene expression in rein2, possibly triggered by changes in the chromatin environment resulting from altered histone chaperone function.
Expanding research on screen-derived factors that modify type II transcriptional memory has the potential to enhance our understanding of HS memory in plants. Discovering connections between previously identified memory factors will help to elucidate the underlying network of HS memory. This knowledge can initiate new approaches to improve heat resilience in crops.
The reliance on fossil fuels has resulted in an abnormal increase in the concentration of greenhouse gases, contributing to the global climate crisis. In response, a rapid transition to renewable energy sources has begun, particularly lithium-ion batteries, playing a crucial role in the green energy transformation. However, concerns regarding the availability and geopolitical implications of lithium have prompted the exploration of alternative rechargeable battery systems, such as sodium-ion batteries. Sodium is significantly abundant and more homogeneously distributed in the crust and seawater, making it easier and less expensive to extract than lithium. However, because of the mysterious nature of its components, sodium-ion batteries are not yet sufficiently advanced to take the place of lithium-ion batteries. Specifically, sodium exhibits a more metallic character and a larger ionic radius, resulting in a different ion storage mechanism utilized in lithium-ion batteries. Innovations in synthetic methods, post-treatments, and interface engineering clearly demonstrate the significance of developing high-performance carbonaceous anode materials for sodium-ion batteries. The objective of this dissertation is to present a systematic approach for fabricating efficient, high-performance, and sustainable carbonaceous anode materials for sodium-ion batteries. This will involve a comprehensive investigation of different chemical environments and post-modification techniques as well.
This dissertation focuses on three main objectives. Firstly, it explores the significance of post-synthetic methods in designing interfaces. A conformal carbon nitride coating is deposited through chemical vapor deposition on a carbon electrode as an artificial solid-electrolyte interface layer, resulting in improved electrochemical performance. The interaction between the carbon nitride artificial interface and the carbon electrode enhances initial Coulombic efficiency, rate performance, and total capacity. Secondly, a novel process for preparing sulfur-rich carbon as a high-performing anode material for sodium-ion batteries is presented. The method involves using an oligo-3,4-ethylenedioxythiophene precursor for high sulfur content hard carbon anode to investigate the sulfur heteroatom effect on the electrochemical sodium storage mechanism. By optimizing the condensation temperature, a significant transformation in the materials’ nanostructure is achieved, leading to improved electrochemical performance. The use of in-operando small-angle X-ray scattering provides valuable insights into the interaction between micropores and sodium ions during the electrochemical processes. Lastly, the development of high-capacity hard carbon, derived from 5-hydroxymethyl furfural, is examined. This carbon material exhibits exceptional performance at both low and high current densities. Extensive electrochemical and physicochemical characterizations shed light on the sodium storage mechanism concerning the chemical environment, establishing the material’s stability and potential applications in sodium-ion batteries.
This work analyzed functional and regulatory aspects of the so far little characterized EPSIN N-terminal Homology (ENTH) domain-containing protein EPSINOID2 in Arabidopsis thaliana. ENTH domain proteins play accessory roles in the formation of clathrin-coated vesicles (CCVs) (Zouhar and Sauer 2014). Their ENTH domain interacts with membranes and their typically long, unstructured C-terminus contains binding motifs for adaptor protein complexes and clathrin itself. There are seven ENTH domain proteins in Arabidopsis. Four of them possess the canonical long C-terminus and participate in various, presumably CCV-related intracellular transport processes (Song et al. 2006; Lee et al. 2007; Sauer et al. 2013; Collins et al. 2020; Heinze et al. 2020; Mason et al. 2023). The remaining three ENTH domain proteins, however, have severely truncated C-termini and were termed EPSINOIDs (Zouhar and Sauer 2014; Freimuth 2015). Their functions are currently unclear. Preceding studies focusing on EPSINOID2 indicated a role in root hair formation: epsinoid2 T DNA mutants exhibited an increased root hair density and EPSINOID2-GFP was specifically located in non-hair cell files in the Arabidopsis root epidermis (Freimuth 2015, 2019).
In this work, it was clearly shown that loss of EPSINOID2 leads to an increase in root hair density through analyses of three independent mutant alleles, including a newly generated CRISPR/Cas9 full deletion mutant. The ectopic root hairs emerging from non-hair positions in all epsinoid2 mutant alleles are most likely not a consequence of altered cell fate, because extensive genetic analyses placed EPSINOID2 downstream of the established epidermal patterning network. Thus, EPSINOID2 seems to act as a cell autonomous inhibitor of root hair formation. Attempts to confirm this hypothesis by ectopically overexpressing EPSINOID2 led to the discovery of post-transcriptional and -translational regulation through different mechanisms. One involves the little characterized miRNA844-3p. Interference with this pathway resulted in ectopic EPSINOID2 overexpression and decreased root hair density, confirming it as negative factor in root hair formation. A second mechanism likely involves proteasomal degradation. Treatment with proteasomal inhibitor MG132 led to EPSINOID2-GFP accumulation, and a KEN box degron motif was identified in the EPSINOID2 sequence associated with degradation through a ubiquitin/proteasome-dependent pathway. In line with a tight dose regulation, genetic analyses of all three mutant alleles indicate that EPSINOID2 is haploinsufficient. Lastly, it was revealed that, although EPSINOID2 promoter activity was found in all epidermal cells, protein accumulation was observed in N-cells only, hinting at yet another layer of regulation.
Organic solar cells (OSCs) represent a new generation of solar cells with a range of captivating attributes including low-cost, light-weight, aesthetically pleasing appearance, and flexibility. Different from traditional silicon solar cells, the photon-electron conversion in OSCs is usually accomplished in an active layer formed by blending two kinds of organic molecules (donor and acceptor) with different energy levels together.
The first part of this thesis focuses on a better understanding of the role of the energetic offset and each recombination channel on the performance of these low-offset OSCs. By combining advanced experimental techniques with optical and electrical simulation, the energetic offsets between CT and excitons, several important insights were achieved: 1. The short circuit current density and fill-factor of low-offset systems are largely determined by field-dependent charge generation in such low-offset OSCs. Interestingly, it is strongly evident that such field-dependent charge generation originates from a field-dependent exciton dissociation yield. 2. The reduced energetic offset was found to be accompanied by strongly enhanced bimolecular recombination coefficient, which cannot be explained solely by exciton repopulation from CT states. This implies the existence of another dark decay channel apart from CT.
The second focus of the thesis was on the technical perspective. In this thesis, the influence of optical artifacts in differential absorption spectroscopy upon the change of sample configuration and active layer thickness was studied. It is exemplified and discussed thoroughly and systematically in terms of optical simulations and experiments, how optical artifacts originated from non-uniform carrier profile and interference can manipulate not only the measured spectra, but also the decay dynamics in various measurement conditions. In the end of this study, a generalized methodology based on an inverse optical transfer matrix formalism was provided to correct the spectra and decay dynamics manipulated by optical artifacts.
Overall, this thesis paves the way for a deeper understanding of the keys toward higher PCEs in low-offset OSC devices, from the perspectives of both device physics and characterization techniques.
Global warming, driven primarily by the excessive emission of greenhouse gases such as carbon dioxide into the atmosphere, has led to severe and detrimental environmental impacts. Rising global temperatures have triggered a cascade of adverse effects, including melting glaciers and polar ice caps, more frequent and intense heat waves disrupted weather patterns, and the acidification of oceans. These changes adversely affect ecosystems, biodiversity, and human societies, threatening food security, water availability, and livelihoods. One promising solution to mitigate the harmful effects of global warming is the widespread adoption of solar cells, also known as photovoltaic cells. Solar cells harness sunlight to generate electricity without emitting greenhouse gases or other pollutants. By replacing fossil fuel-based energy sources, solar cells can significantly reduce CO2 emissions, a significant contributor to global warming. This transition to clean, renewable energy can help curb the increasing concentration of greenhouse gases in the atmosphere, thereby slowing down the rate of global temperature rise.
Solar energy’s positive impact extends beyond emission reduction. As solar panels become more efficient and affordable, they empower individuals, communities, and even entire nations to generate electricity and become less dependent on fossil fuels. This decentralized energy generation can enhance resilience in the face of climate-related challenges. Moreover, implementing solar cells creates green jobs and stimulates technological innovation, further promoting sustainable economic growth. As solar technology advances, its integration with energy storage systems and smart grids can ensure a stable and reliable energy supply, reducing the need for backup fossil fuel power plants that exacerbate environmental degradation.
The market-dominant solar cell technology is silicon-based, highly matured technology with a highly systematic production procedure. However, it suffers from several drawbacks, such as: 1) Cost: still relatively high due to high energy consumption due to the need to melt and purify silicon, and the use of silver as an electrode, which hinders their widespread availability, especially in low-income countries. 2) Efficiency: theoretically, it should deliver around 29%; however, the efficiency of most of the commercially available silicon-based solar cells ranges from 18 – 22%. 3) Temperature sensitivity: The efficiency decreases with the increase in the temperature, affecting their output. 4) Resource constraints: silicon as a raw material is unavailable in all countries, creating supply chain challenges.
Perovskite solar cells arose in 2011 and matured very rapidly in the last decade as a highly efficient and versatile solar cell technology. With an efficiency of 26%, high absorption coefficients, solution processability, and tunable band gap, it attracted the attention of the solar cells community. It represented a hope for cheap, efficient, and easily processable next-generation solar cells. However, lead toxicity might be the block stone hindering perovskite solar cells’ market reach. Lead is a heavy and bioavailable element that makes perovskite solar cells environmentally unfriendly technology. As a result, scientists try to replace lead with a more environmentally friendly element. Among several possible alternatives, tin was the most suitable element due to its electronic and atomic structure similarity to lead.
Tin perovskites were developed to alleviate the challenge of lead toxicity. Theoretically, it shows very high absorption coefficients, an optimum band gap of 1.35 eV for FASnI3, and a very high short circuit current, which nominates it to deliver the highest possible efficiency of a single junction solar cell, which is around 30.1% according to Schockly-Quisser limit. However, tin perovskites’ efficiency still lags below 15% and is irreproducible, especially from lab to lab. This humble performance could be attributed to three reasons: 1) Tin (II) oxidation to tin (IV), which would happen due to oxygen, water, or even by the effect of the solvent, as was discovered recently. 2) fast crystallization dynamics, which occurs due to the lateral exposure of the P-orbitals of the tin atom, which enhances its reactivity and increases the crystallization pace. 3) Energy band misalignment: The energy bands at the interfaces between the perovskite absorber material and the charge selective layers are not aligned, leading to high interfacial charge recombination, which devastates the photovoltaic performance. To solve these issues, we implemented several techniques and approaches that enhanced the efficiency of tin halide perovskites, providing new chemically safe solvents and antisolvents. In addition, we studied the energy band alignment between the charge transport layers and the tin perovskite absorber.
Recent research has shown that the principal source of tin oxidation is the solvent known as dimethylsulfoxide, which also happens to be one of the most effective solvents for processing perovskite. The search for a stable solvent might prove to be the factor that makes all the difference in the stability of tin-based perovskites. We started with a database of over 2,000 solvents and narrowed it down to a series of 12 new solvents that are suitable for processing FASnI3 experimentally. This was accomplished by looking into 1) the solubility of the precursor chemicals FAI and SnI2, 2) the thermal stability of the precursor solution, and 3) the potential to form perovskite. Finally, we show that it is possible to manufacture solar cells using a novel solvent system that outperforms those produced using DMSO. The results of our research give some suggestions that may be used in the search for novel solvents or mixes of solvents that can be used to manufacture stable tin-based perovskites.
Due to the quick crystallization of tin, it is more difficult to deposit tin-based perovskite films from a solution than manufacturing lead-based perovskite films since lead perovskite is more often utilized. The most efficient way to get high efficiencies is to deposit perovskite from dimethyl sulfoxide (DMSO), which slows down the quick construction of the tin-iodine network that is responsible for perovskite synthesis. This is the most successful approach for achieving high efficiencies. Dimethyl sulfoxide, which is used in the processing, is responsible for the oxidation of tin, which is a disadvantage of this method. This research presents a potentially fruitful alternative in which 4-(tert-butyl) pyridine can substitute dimethyl sulfoxide in the process of regulating crystallization without causing tin oxidation to take place. Perovskite films that have been formed from pyridine have been shown to have a much-reduced defect density. This has resulted in increased charge mobility and better photovoltaic performance, making pyridine a desirable alternative for use in the deposition of tin perovskite films.
The precise control of perovskite precursor crystallization inside a thin film is of utmost importance for optimizing the efficiency and manufacturing of solar cells. The deposition process of tin-based perovskite films from a solution presents difficulties due to the quick crystallization of tin compared to the more often employed lead perovskite. The optimal approach for attaining elevated efficiencies entails using dimethyl sulfoxide (DMSO) as a medium for depositing perovskite. This choice of solvent impedes the tin-iodine network’s fast aggregation, which plays a crucial role in the production of perovskite. Nevertheless, this methodology is limited since the utilization of dimethyl sulfoxide leads to the oxidation of tin throughout the processing stage. In this thesis, we present a potentially advantageous alternative approach wherein 4-(tert-butyl) pyridine is proposed as a substitute for dimethyl sulfoxide in regulating crystallization processes while avoiding the undesired consequence of tin oxidation. Films of perovskite formed using pyridine as a solvent have a notably reduced density of defects, resulting in higher mobility of charges and improved performance in solar applications. Consequently, the utilization of pyridine for the deposition of tin perovskite films is considered advantageous.
Tin perovskites are suffering from an apparent energy band misalignment. However, the band diagrams published in the current body of research display contradictions, resulting in a dearth of unanimity. Moreover, comprehensive information about the dynamics connected with charge extraction is lacking. This thesis aims to ascertain the energy band locations of tin perovskites by employing the kelvin probe and Photoelectron yield spectroscopy methods. This thesis aims to construct a precise band diagram for the often-utilized device stack. Moreover, a comprehensive analysis is performed to assess the energy deficits inherent in the current energetic structure of tin halide perovskites. In addition, we investigate the influence of BCP on the improvement of electron extraction in C60/BCP systems, with a specific emphasis on the energy factors involved. Furthermore, transient surface photovoltage was utilized to investigate the charge extraction kinetics of frequently studied charge transport layers, such as NiOx and PEDOT as hole transport layers and C60, ICBA, and PCBM as electron transport layers. The Hall effect, KP, and TRPL approaches accurately ascertain the p-doping concentration in FASnI3. The results consistently demonstrated a value of 1.5 * 1017 cm-3. Our research findings highlight the imperative nature of autonomously constructing the charge extraction layers for tin halide perovskites, apart from those used for lead perovskites.
The crystallization of perovskite precursors relies mainly on the utilization of two solvents. The first one dissolves the perovskite powder to form the precursor solution, usually called the solvent. The second one precipitates the perovskite precursor, forming the wet film, which is a supersaturated solution of perovskite precursor and in the remains of the solvent and the antisolvent. Later, this wet film crystallizes upon annealing into a full perovskite crystallized film. In our research context, we proposed new solvents to dissolve FASnI3, but when we tried to form a film, most of them did not crystallize. This is attributed to the high coordination strength between the metal halide and the solvent molecules, which is unbreakable by the traditionally used antisolvents such as Toluene and Chlorobenzene. To solve this issue, we introduce a high-throughput antisolvent screening in which we screened around 73 selected antisolvents against 15 solvents that can form a 1M FASnI3 solution. We used for the first time in tin perovskites machine learning algorithm to understand and predict the effect of an antisolvent on the crystallization of a precursor solution in a particular solvent. We relied on film darkness as a primary criterion to judge the efficacy of a solvent-antisolvent pair. We found that the relative polarity between solvent and antisolvent is the primary factor that affects the solvent-antisolvent interaction. Based on our findings, we prepared several high-quality tin perovskite films free from DMSO and achieved an efficiency of 9%, which is the highest DMSO tin perovskite device so far.
Knowledge about causal structures is crucial for decision support in various domains. For example, in discrete manufacturing, identifying the root causes of failures and quality deviations that interrupt the highly automated production process requires causal structural knowledge. However, in practice, root cause analysis is usually built upon individual expert knowledge about associative relationships. But, "correlation does not imply causation", and misinterpreting associations often leads to incorrect conclusions. Recent developments in methods for causal discovery from observational data have opened the opportunity for a data-driven examination. Despite its potential for data-driven decision support, omnipresent challenges impede causal discovery in real-world scenarios. In this thesis, we make a threefold contribution to improving causal discovery in practice.
(1) The growing interest in causal discovery has led to a broad spectrum of methods with specific assumptions on the data and various implementations. Hence, application in practice requires careful consideration of existing methods, which becomes laborious when dealing with various parameters, assumptions, and implementations in different programming languages. Additionally, evaluation is challenging due to the lack of ground truth in practice and limited benchmark data that reflect real-world data characteristics.
To address these issues, we present a platform-independent modular pipeline for causal discovery and a ground truth framework for synthetic data generation that provides comprehensive evaluation opportunities, e.g., to examine the accuracy of causal discovery methods in case of inappropriate assumptions.
(2) Applying constraint-based methods for causal discovery requires selecting a conditional independence (CI) test, which is particularly challenging in mixed discrete-continuous data omnipresent in many real-world scenarios. In this context, inappropriate assumptions on the data or the commonly applied discretization of continuous variables reduce the accuracy of CI decisions, leading to incorrect causal structures.
Therefore, we contribute a non-parametric CI test leveraging k-nearest neighbors methods and prove its statistical validity and power in mixed discrete-continuous data, as well as the asymptotic consistency when used in constraint-based causal discovery. An extensive evaluation of synthetic and real-world data shows that the proposed CI test outperforms state-of-the-art approaches in the accuracy of CI testing and causal discovery, particularly in settings with low sample sizes.
(3) To show the applicability and opportunities of causal discovery in practice, we examine our contributions in real-world discrete manufacturing use cases. For example, we showcase how causal structural knowledge helps to understand unforeseen production downtimes or adds decision support in case of failures and quality deviations in automotive body shop assembly lines.
The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.
A comprehensive study on seismic hazard and earthquake triggering is crucial for effective mitigation of earthquake risks. The destructive nature of earthquakes motivates researchers to work on forecasting despite the apparent randomness of the earthquake occurrences. Understanding their underlying mechanisms and patterns is vital, given their potential for widespread devastation and loss of life. This thesis combines methodologies, including Coulomb stress calculations and aftershock analysis, to shed light on earthquake complexities, ultimately enhancing seismic hazard assessment.
The Coulomb failure stress (CFS) criterion is widely used to predict the spatial distributions of aftershocks following large earthquakes. However, uncertainties associated with CFS calculations arise from non-unique slip inversions and unknown fault networks, particularly due to the choice of the assumed aftershocks (receiver) mechanisms. Recent studies have proposed alternative stress quantities and deep neural network approaches as superior to CFS with predefined receiver mechanisms. To challenge these propositions, I utilized 289 slip inversions from the SRCMOD database to calculate more realistic CFS values for a layered-half space and variable receiver mechanisms. The analysis also investigates the impact of magnitude cutoff, grid size variation, and aftershock duration on the ranking of stress metrics using receiver operating characteristic (ROC) analysis. Results reveal the performance of stress metrics significantly improves after accounting for receiver variability and for larger aftershocks and shorter time periods, without altering the relative ranking of the different stress metrics.
To corroborate Coulomb stress calculations with the findings of earthquake source studies in more detail, I studied the source properties of the 2005 Kashmir earthquake and its aftershocks, aiming to unravel the seismotectonics of the NW Himalayan syntaxis. I simultaneously relocated the mainshock and its largest aftershocks using phase data, followed by a comprehensive analysis of Coulomb stress changes on the aftershock planes. By computing the Coulomb failure stress changes on the aftershock faults, I found that all large aftershocks lie in regions of positive stress change, indicating triggering by either co-seismic or post-seismic slip on the mainshock fault.
Finally, I investigated the relationship between mainshock-induced stress changes and associated seismicity parameters, in particular those of the frequency-magnitude (Gutenberg-Richter) distribution and the temporal aftershock decay (Omori-Utsu law). For that purpose, I used my global data set of 127 mainshock-aftershock sequences with the calculated Coulomb Stress (ΔCFS) and the alternative receiver-independent stress metrics in the vicinity of the mainshocks and analyzed the aftershocks properties depend on the stress values. Surprisingly, the results show a clear positive correlation between the Gutenberg-Richter b-value and induced stress, contrary to expectations from laboratory experiments. This observation highlights the significance of structural heterogeneity and strength variations in seismicity patterns. Furthermore, the study demonstrates that aftershock productivity increases nonlinearly with stress, while the Omori-Utsu parameters c and p systematically decrease with increasing stress changes. These partly unexpected findings have significant implications for future estimations of aftershock hazard.
The findings in this thesis provides valuable insights into earthquake triggering mechanisms by examining the relationship between stress changes and aftershock occurrence. The results contribute to improved understanding of earthquake behavior and can aid in the development of more accurate probabilistic-seismic hazard forecasts and risk reduction strategies.
This thesis presents a comprehensive exploration of the application of DNA origami nanofork antennas (DONAs) in the field of spectroscopy, with a particular focus on the structural analysis of Cytochrome C (CytC) at the single-molecule level. The research encapsulates the design, optimization, and application of DONAs in enhancing the sensitivity and specificity of Raman spectroscopy, thereby offering new insights into protein structures and interactions.
The initial phase of the study involved the meticulous optimization of DNA origami structures. This process was pivotal in developing nanoscale tools that could significantly enhance the capabilities of Raman spectroscopy. The optimized DNA origami nanoforks, in both dimer and aggregate forms, demonstrated an enhanced ability to detect and analyze molecular vibrations, contributing to a more nuanced understanding of protein dynamics.
A key aspect of this research was the comparative analysis between the dimer and aggregate forms of DONAs. This comparison revealed that while both configurations effectively identified oxidation and spin states of CytC, the aggregate form offered a broader range of detectable molecular states due to its prolonged signal emission and increased number of molecules. This extended duration of signal emission in the aggregates was attributed to the collective hotspot area, enhancing overall signal stability and sensitivity.
Furthermore, the study delved into the analysis of the Amide III band using the DONA system. Observations included a transient shift in the Amide III band's frequency, suggesting dynamic alterations in the secondary structure of CytC. These shifts, indicative of transitions between different protein structures, were crucial in understanding the protein’s functional mechanisms and interactions.
The research presented in this thesis not only contributes significantly to the field of spectroscopy but also illustrates the potential of interdisciplinary approaches in biosensing. The use of DNA origami-based systems in spectroscopy has opened new avenues for research, offering a detailed and comprehensive understanding of protein structures and interactions. The insights gained from this research are expected to have lasting implications in scientific fields ranging from drug development to the study of complex biochemical pathways. This thesis thus stands as a testament to the power of integrating nanotechnology, biochemistry, and spectroscopic techniques in addressing complex scientific questions.
The mobile-immobile model (MIM) has been established in geoscience in the context of contaminant transport in groundwater. Here the tracer particles effectively immobilise, e.g., due to diffusion into dead-end pores or sorption. The main idea of the MIM is to split the total particle density into a mobile and an immobile density. Individual tracers switch between the mobile and immobile state following a two-state telegraph process, i.e., the residence times in each state are distributed exponentially. In geoscience the focus lies on the breakthrough curve (BTC), which is the concentration at a fixed location over time. We apply the MIM to biological experiments with a special focus on anomalous scaling regimes of the mean squared displacement (MSD) and non-Gaussian displacement distributions. As an exemplary system, we have analysed the motion of tau proteins, that diffuse freely inside axons of neurons. Their free diffusion thereby corresponds to the mobile state of the MIM. Tau proteins stochastically bind to microtubules, which effectively immobilises the tau proteins until they unbind and continue diffusing. Long immobilisation durations compared to the mobile durations give rise to distinct non-Gaussian Laplace shaped distributions. It is accompanied by a plateau in the MSD for initially mobile tracer particles at relevant intermediate timescales. An equilibrium fraction of initially mobile tracers gives rise to non-Gaussian displacements at intermediate timescales, while the MSD remains linear at all times. In another setting bio molecules diffuse in a biosensor and transiently bind to specific receptors, where advection becomes relevant in the mobile state. The plateau in the MSD observed for the advection-free setting and long immobilisation durations persists also for the case with advection. We find a new clear regime of anomalous diffusion with non-Gaussian distributions and a cubic scaling of the MSD. This regime emerges for initially mobile and for initially immobile tracers. For an equilibrium fraction of initially mobile tracers we observe an intermittent ballistic scaling of the MSD. The long-time effective diffusion coefficient is enhanced by advection, which we physically explain with the variance of mobile durations. Finally, we generalize the MIM to incorporate arbitrary immobilisation time distributions and focus on a Mittag-Leffler immobilisation time distribution with power-law tail ~ t^(-1-mu) with 0<mu<1 and diverging mean immobilisation durations. A fit of our model to the BTC of experimental data from tracer particles in aquifers matches the BTC including the power-law tail. We use the fit parameters for plotting the displacement distributions and the MSD. We find Gaussian normal diffusion at short times and long-time power-law decay of mobile mass accompanied by anomalous diffusion at long times. The long-time diffusion is subdiffusive in the advection-free setting, while it is either subdiffusive for 0<mu<1/2 or superdiffusive for 1/2<mu<1 when advection is present. In the long-time limit we show equivalence of our model to a bi-fractional diffusion equation.
Long-term bacteria-fungi-plant associations in permafrost soils inferred from palaeometagenomics
(2024)
The arctic is warming 2 – 4 times faster than the global average, resulting in a strong feedback on northern ecosystems such as boreal forests, which cover a vast area of the high northern latitudes. With ongoing global warming, the treeline subsequently migrates northwards into tundra areas. The consequences of turning ecosystems are complex: on the one hand, boreal forests are storing large amounts of global terrestrial carbon and act as a carbon sink, dragging carbon dioxide out of the global carbon cycle, suggesting an enhanced carbon uptake with increased tree cover. On the other hand, with the establishment of trees, the albedo effect of tundra decreases, leading to enhanced soil warming. Meanwhile, permafrost thaws, releasing large amounts of previously stored carbon into the atmosphere. So far, mainly vegetation dynamics have been assessed when studying the impact of warming onto ecosystems. Most land plants are living in close symbiosis with bacterial and fungal communities, sustaining their growth in nutrient poor habitats. However, the impact of climate change on these subsoil communities alongside changing vegetation cover remains poorly understood. Therefore, a better understanding of soil community dynamics on multi millennial timescales is inevitable when addressing the development of entire ecosystems. Unravelling long-term cross-kingdom dependencies between plant, fungi, and bacteria is not only a milestone for the assessment of warming on boreal ecosystems. On top, it also is the basis for agriculture strategies to sustain society with sufficient food in a future warming world.
The first objective of this thesis was to assess ancient DNA as a proxy for reconstructing the soil microbiome (Manuscripts I, II, III, IV). Research findings across these projects enable a comprehensive new insight into the relationships of soil microorganisms to the surrounding vegetation. First, this was achieved by establishing (Manuscript I) and applying (Manuscript II) a primer pair for the selective amplification of ancient fungal DNA from lake sediment samples with the metabarcoding approach. To assess fungal and plant co-variation, the selected primer combination (ITS67, 5.8S) amplifying the ITS1 region was applied on samples from five boreal and arctic lakes. The obtained data showed that the establishment of fungal communities is impacted by warming as the functional ecological groups are shifting. Yeast and saprotroph dominance during the Late Glacial declined with warming, while the abundance of mycorrhizae and parasites increased with warming. The overall species richness was also alternating. The results were compared to shotgun sequencing data reconstructing fungi and bacteria (Manuscripts III, IV), yielding overall comparable results to the metabarcoding approach. Nonetheless, the comparison also pointed out a bias in the metabarcoding, potentially due to varying ITS lengths or copy numbers per genome.
The second objective was to trace fungus-plant interaction changes over time (Manuscripts II, III). To address this, metabarcoding targeting the ITS1 region for fungi and the chloroplast P6 loop for plants for the selective DNA amplification was applied (Manuscript II). Further, shotgun sequencing data was compared to the metabarcoding results (Manuscript III). Overall, the results between the metabarcoding and the shotgun approaches were comparable, though a bias in the metabarcoding was assumed. We demonstrated that fungal shifts were coinciding with changes in the vegetation. Yeast and lichen were mainly dominant during the Late Glacial with tundra vegetation, while warming in the Holocene lead to the expansion of boreal forests with increasing mycorrhizae and parasite abundance. Aside, we highlighted that Pinaceae establishment is dependent on mycorrhizal fungi such as Suillineae, Inocybaceae, or Hyaloscypha species also on long-term scales.
The third objective of the thesis was to assess soil community development on a temporal gradient (Manuscripts III, IV). Shotgun sequencing was applied on sediment samples from the northern Siberian lake Lama and the soil microbial community dynamics compared to ecosystem turnover. Alongside, podzolization processes from basaltic bedrock were recovered (Manuscript III). Additionally, the recovered soil microbiome was compared to shotgun data from granite and sandstone catchments (Manuscript IV, Appendix). We assessed if the establishment of the soil microbiome is dependent on the plant taxon and as such comparable between multiple geographic locations or if the community establishment is driven by abiotic soil properties and as such the bedrock area. We showed that the development of soil communities is to a great extent driven by the vegetation changes and temperature variation, while time only plays a minor role. The analyses showed general ecological similarities especially between the granite and basalt locations, while the microbiome on species-level was rather site-specific. A greater number of correlated soil taxa was detected for deep-rooting boreal taxa in comparison to grasses with shallower roots. Additionally, differences between herbaceous taxa of the late Glacial compared to taxa of the Holocene were revealed.
With this thesis, I demonstrate the necessity to investigate subsoil community dynamics on millennial time scales as it enables further understanding of long-term ecosystem as well as soil development processes and such plant establishment. Further, I trace long-term processes leading to podzolization which supports the development of applied carbon capture strategies under future global warming.
Moss-microbe associations are often characterised by syntrophic interactions between the microorganisms and their hosts, but the structure of the microbial consortia and their role in peatland development remain unknown.
In order to study microbial communities of dominant peatland mosses, Sphagnum and brown mosses, and the respective environmental drivers, four study sites representing different successional stages of natural northern peatlands were chosen on a large geographical scale: two brown moss-dominated, circumneutral peatlands from the Arctic and two Sphagnum-dominated, acidic peat bogs from subarctic and temperate zones.
The family Acetobacteraceae represented the dominant bacterial taxon of Sphagnum mosses from various geographical origins and displayed an integral part of the moss core community. This core community was shared among all investigated bryophytes and consisted of few but highly abundant prokaryotes, of which many appear as endophytes of Sphagnum mosses. Moreover, brown mosses and Sphagnum mosses represent habitats for archaea which were not studied in association with peatland mosses so far. Euryarchaeota that are capable of methane production (methanogens) displayed the majority of the moss-associated archaeal communities. Moss-associated methanogenesis was detected for the first time, but it was mostly negligible under laboratory conditions. Contrarily, substantial moss-associated methane oxidation was measured on both, brown mosses and Sphagnum mosses, supporting that methanotrophic bacteria as part of the moss microbiome may contribute to the reduction of methane emissions from pristine and rewetted peatlands of the northern hemisphere.
Among the investigated abiotic and biotic environmental parameters, the peatland type and the host moss taxon were identified to have a major impact on the structure of moss-associated bacterial communities, contrarily to archaeal communities whose structures were similar among the investigated bryophytes. For the first time it was shown that different bog development stages harbour distinct bacterial communities, while at the same time a small core community is shared among all investigated bryophytes independent of geography and peatland type.
The present thesis displays the first large-scale, systematic assessment of bacterial and archaeal communities associated both with brown mosses and Sphagnum mosses. It suggests that some host-specific moss taxa have the potential to play a key role in host moss establishment and peatland development.
Nanoparticles of magnetite (Fe3O4) are envisioned to find used in diverse applications, ranging from magnetic data storage, inks, ferrofluids as well as in magnetic resonance imaging, drug delivery, and hyperthermia cancer treatment. Their magnetic properties strongly depend on their size and morphology, two properties that can be synthetically controlled. Achieving appropriate control under soft chemical conditions has so far remained a challenging endeavor. One proven way of exerting this desired control has been using a biomimetic approach that emulates the proteome of magnetotactic bacteria by adding poly-L-arginine in the co- precipitation of ferrous and ferric chloride. The objective of the work presented here is to understand the impact of this polycation on the formation mechanism of magnetite and, through rational design, to enhance the control we can exert on magnetite nanoparticle size and morphology. We developed a SAXS setup to temporally and structurally resolve the formation of magnetite in the presence of poly-L-arginine in situ. Using analytical scattering models, we were able to separate the scattering contribution of a low-density 5 nm iron structure from the contribution of the growing nanoparticles. We identified that the low-density iron structure is a metastable precursor to the magnetite particles and that it is electrostatically stabilized by poly-L-arginine. In a process analogous to biomineralization, the presence of the charged macromolecule thus shifts the reaction mechanism from a thermodynamically controlled one to a kinetically controlled one. We identify this shift in reactions mechanism as the cornerstone of the proposed mechanism and as the crucial step in the paradigm of this extraordinary nanoparticle morphology and size control. Based on SAXS data, theoretical considerations suggest that an observed morphological transition between spherical, solid, and sub-structured mesocrystalline magnetite nanoparticles is induced through a pH-driven change in the wettability of the nanoparticle surface. With these results, we further demonstrate that SAXS can be an invaluable tool for investigating nanoparticle formation. We were able to change particle morphology from spherically solid particles to sub-structured mesocrystals merely by changing the precipitation pH. Improving the synthesis sustainability by substituting poly-L-arginine with renewable, polysaccharide-based polycations produced at the metric ton scale, we demonstrated that the ability to alter the reaction mechanism of magnetite can be generically attributed to the presence of polycations. Through meticulous analysis and the understanding of the formation mechanism, we were able to exert precise control over particle size and morphology, by adapting crucial synthesis parameters. We were thus able to grow mesocrystals up to 200 nm and solid nanocrystals of 100 nm by adding virtually any strong polycation. We further found a way to produce stable single domain magnetite at only slightly increased alkalinity, as magnetotactic bacteria do it. Thus through the understanding of the biological system, the consecutive biomimetic synthesis of magnetite and the following understanding of the mechanism involved in the in vitro synthesis, we managed to improve the synthetic control over the co-precipitation of magnetite, coming close biomineralization of magnetite in magnetotactic bacteria. Polyanions, in both natural as well as in synthetic systems, have been in the spotlight of recent research, yet our work shows the pivotal influence polycations have on the nucleation of magnetite. This work will contribute significantly to our ability to tailor magnetite nanoparticle size and morphology; in addition, we presume it will provide us with a model system for studying biomineralization of magnetite in vitro, putting the spotlight on the important influence of polycations, which have not had the scientific attention they deserve.
Recently crops encounter an increased number of individual and combined abiotic and biotic stress, which severely affect their growth and yield. Plants are associated with a large number of microorganisms including beneficial as well as pathogenic microorganisms. The interaction of plants with beneficial microorganisms can exert a substantial impact on plant growth and health and their potential can be utilized in sustainable plant production systems. Currently, climate change will increase the impact of stress on crops which will more likely be exposed to combined abiotic and biotic stress. At present, knowledge on how abiotic and biotic stress and the combination of both stresses affect the plant performance and the microbiome is limited. Soil-borne pathogens are responsible for relevant economic losses and are difficult to control. The root bacterial endophytes have shown potential in alleviating stress on plants and improving crop yield and quality. This raises the question how individual abiotic stress like salinity (ionic) and drought (osmotic) and the combination with biotic stress (Verticillium dahliae or Fusarium oxysporum) affects the root microbiota and thus the performance of the plant. Therefore, the goal of this thesis was to improve the understanding of the impact of individual and combined biotic and abiotic stress especially the endophytic root microbiota and thus plant performance. The work is focused on the economically important horticultural crop tomato. The bacterial rootendophytes of tomato plants exposed to individual and combined abiotic and biotic stress was studied with culture-independent and culture-dependent methods. Bacterial root endophytes obtained from tomato roots exposed to individual and combined stress were characterized for their traits that are beneficial to plant growth and health in in vitro and in vivo assays. Finally, the efficacy of selected endophytes in alleviating individual and combined abiotic and biotic stress in tomato plants was assessed. Furthermore, stress conditions can alter the composition of root exudates and volatiles, which may in turn affect the root microbiota assembly. Therefore, the volatile profiles of healthy and pathogen (F. oxysporum) infected tomato roots grown in soil was investigated. A soil olfactometer was established to study the impact of root volatiles of healthy and infected tomato on migration of applied beneficial bacteria. The results of tomato characteristics (plant growth, photosynthesis rate) confirmed the negative effect of individual abiotic and biotic stress reported in other studies. However, the response of combined abiotic stress with biotic stress on plant growth varied depending on the type of combined stress.. For instance, a significant higher negative impact on plant growth was observed when tomato plants were cultivated under ionic stress and infected with F. oxysporum. No additional negative effect on plant growth was observed when tomato was infected with V. dahliae. Both culture-dependent and cultureindependent analyses of the root microbiota revealed that individual and combined abiotic and biotic stress alter the root microbiota structure and diversity of tomato. A significantly lower number of cultivable root endophytes was obtained from roots exposed to ionic stress. 16S rRNA amplicon analysis revealed a stronger impact on the diversity of root-associated bacteria in comparison to biotic stress. The endophytes were characterized as member of the phyla Proteobacteria, Actinobacteria and Firmicutes, and members of Bacteriodetes were only detected by culture-independent approach. A total of 683 cultivable bacterial endophytes were characterized using various in vitro and in vivo plant growth-promoting (PGP) assays. As expected, the highest number of root endophytes with tolerance to ionic stress were obtained from tomato roots exposed to ionic stress. Comparably, a high percentage of root endophytes isolated from roots exposed to osmotic were tolerant to osmotic stress showing that the environment affects the selection of microorganisms by the plant. Interestingly, endopyhtes obtained from roots exposed to abiotic stress showed no traits related to plant growth promotion. Based on in vivo and in vitro traits, five selected endophytes were able to alleviate abiotic and biotic stress on plants. These endophytes were obtained from tomato roots infected with V. dahliae. The blend of root emitted volatiles also differed between healthy and F. oxysporum infected tomato plants. The olfactometer setup results highlighted that root volatiles were involved in attraction of bacteria to the plant roots and beneficial bacteria were observed to migrate towards both, diseased and healthy plants in comparable density. It is proposed that root volatiles from healthy and pathogen infected plants not only work as signals but are also used as an energy source for the rhizosphere bacteria. Concluding, the results of this study indicate that abiotic and biotic stress altered the bacterial rootendophytes and thus affects plant performance. The treatment of plants with beneficial microorganisms reduced the negative impact of stress conditions on plant performance. However, more studies using the selected isolates must be performed in the field for drawing inferences on the efficacy of the selected bacterial isolates in ameliorating the effect of abiotic and biotic stress in plants. The extensive isolate collection will serve as a basis for conducting investigations of root-associated bacteria on plant performance. This is important for the development of new plant protection strategies.
Solar cells based on hybrid perovskites materials have become significantly important among the third generation photovoltaics over the last few years. The first solid state solar cell was reported in 2012. Over the years, the power conversion efficiencies of these devices have increased at a tremendous pace and this has made the perovskite solar cell devices a serious competitor in the well-established market of thin-film and wafer technologies. Over time, a large number of articles on this topic has been published in peer-reviewed journals. The presence of lead in the most efficient hybrid perovskite materials have raised questions about the possible toxicity of these devices and the extent of their environmental impact. Therefore, a lot of research has been devoted to finding alternative perovskite materials with similar or even better opto-electronic properties. An alternative strategy to improve the efficiency of thin film solar cells is to build efficient tandem cells by combining two or more perovskite materials with specifically tailored band gaps. The first step towards the development of perovskite-only tandem solar cells is to identify complementary hybrid perovskite materials with specific band gaps that maximize the efficiency of tandem solar cells. The optimal set of optical gaps for a tandem structure made of two materials is 1.9 eV and 1.0 eV. Since the electronic properties of hybrid perovskites are known to be strongly dependent on the composition and distortion of the crystal lattice, strong focus has been made towards the structure optimisation as well as the calculation of the energy band gaps of the materials using density functional theory (DFT). In an attempt to study the structure-property relationship of these perovskite materials and to find novel perovskite materials for future applications, researchers have employed computational screening procedures to study a large range of these materials by systematic replacement of the cations and anions from the prototypical perovskite. Density functional theory in particular is used as a theoretical tool, because of it’s precision to determine the properties of materials and also it’s computational viability in dealing with complex systems. In this thesis, the main focus is to do a systematic screening of the perovskite materials, of the composition ABX3 again by replacing the A-site, B-site and the X-site elements to find novel materials with band gaps suitable for application in tandem solar cells. As a first step towards contributing to this vibrant field of research, a high-throughput computational screening has been performed by replacing the metal and the halogen in the conventional CH3NH3PbI3 perovskites with homovalent metals and halogens to find materials in the desired range of band gaps that has already been mentioned earlier. This is achieved by performing a geometry optimisation on all the simulated structures followed by calculating their energy band gaps at the semilocal and the hybrid levels of theory. However, it is well known that the rotation of the organic cation CH3NH3 hinders the stability of these devices by the formation of hydrogen bonds between the hydrogen atoms of the cation and the halogens. This causes the materials to degrade under normal temperature and pressure conditions. As an attempt to prevent these devices from being unstable, a next step has been taken where the CH3NH3 cation has been replaced by inorganic cations of similar ionic radius. This is followed by another thorough screening, similar to the previous step. The stability of the materials has been determined by using the empirical Goldschmidt tolerance factor. As a last part of the thesis, a small proportion of the inorganic cation is mixed with CH3NH3 in order to form mixed-halide perovskites. These structures are optimised and their band gaps are calculated using density functional theory in order to predict materials suitable for single junction as well as tandem solar cell devices. It is expected that the contribution made through this thesis will be helpful for the progress of perovskite solar cells in terms of efficiencies and will also allow the community to explore the different properties these materials for further progress and development.
The European fire-bellied toad (Bombina bombina) is regarded as one of the most threatened species of amphibians in central Europe and is particularly affected by environmental perturbations. During the last decades population numbers in Germany have declined drastically due to pollution, eutrophication and habitat fragmentation. Illegal translocations resulted in an introgression from southern genotypes (probably Austrian) into three local Bombina populations (Northern Germany and Southern Sweden) belonging to the northern lineage of the species. Interestingly, these populations show high frequencies of allochthonous (non-local) alleles at multiple loci and outperform the autochthonous populations in terms of their body condition. Over a time period of ten years, I could show that the Southern lineage haplo- and genotypes are still present in the North and that frequencies of introgressed haplotypes in allochthonous populations did not increase over time. However, the introgression itself expanded towards adjacent populations while the overall haplotype diversity has decreased. In contrast, southern lineage genotypes for two candidate genes under selection, the (immunity) MHC class II gene, as well as the (temperature) stress response HSP70 kDa gene, either do not occur at all or only at low frequencies in northern populations. Furthermore, these alleles do not seem to follow the introgression pattern, as they are also present in non-introgressed populations. This thesis tested two possible outcomes of introgressive hybridization in Northern B. bombina populations: (1) local populations (autochthonous) of Bombina bombina are highly adapted to their environments so that introgression of alien genes causes outbreeding depression or (2) local populations of Bombina bombina potentially lack adaptive variation so that introgression of alien genes causes genetic rescue and promotes adaptive change. I found that this unintentional experiment, as a result of illegal translocations imitating introgression of alien genes coming from a southern population (potentially adapted to warmer climate) into a northern lineage (potentially adapted to local pathogens), has increased the genetic diversity and improved fitness in introgressed northern populations, without disrupting local adaptation in the threatened amphibian species B. bombina, favouring the genetic rescue hypothesis. These results and conclusions represent relevant information for future conservation plans, including supportive breeding programmes for fire-bellied toads in Northern Germany and Southern Sweden.
Bioelectrochemical investigation of E. coli TMAO reductase and R. capsulatus formate dehydrogenase
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Each year, donor countries spend billions of Euros on development cooperation. Not surprisingly, a large strand of research has emerged which examines the impact of development cooperation. A sub-discipline within this strand of the literature deals with the question of whether the impact or effectiveness of development cooperation depends on the quality of the recipient country's policy and institutional environment. Over hundreds of studies have assessed this question at the macro level. In so doing, most of these studies test whether a potential effect of aid on the growth of a recipient country’s gross domestic product (GDP) is conditional on the country's policy and institutional environment. However, even after decades of research and hundreds of studies, no conclusive result has been found. One of the main reasons for the inconclusive state of the literature is that most macro-level studies have to deal with a high risk of endogeneity, treat aid as nothing but a pure income transfer, and rely on low-quality GDP data. To solve these three methodical issues, some authors have started to change the analytical focus from the macro to the micro level. Thus, these authors assess the determinants for the performance of individual development projects instead of the determinants for an effect of aid on GDP. Yet, even though the number of studies focusing on the micro level has increased steadily over the last few years, the state of the literature on the determinants for the performance of development projects still contains multiple highly relevant research gaps. The present thesis seeks to address three of these research gaps. The first research gap addressed by this thesis is related to the specific type of development cooperation. So far, nearly all existing studies focus on projects by Multilateral Development Banks. Research on the determinants for the performance of bilateral development projects is still rare. Thus, even though donors pledge to implement effective development projects, there are hardly any micro-level studies on bilateral projects. So far, only three studies use a sample which includes bilateral projects. Yet, none of the three studies assess the determinants for the performance of bilateral technical development projects. The first paper in the present thesis (GIZ paper) seeks to address this research gap by assessing the determinants for the performance of projects by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), a bilateral state-owned aid agency active in the area of technical cooperation. The results of the paper indicate that some but not all of the existing theoretical arguments can be extended to bilateral technical projects as well.. For example, the level of market interventions in the recipient county only affects the performance of financial development projects, while the recipient country’s government capacity affects both technical and financial development projects. The paper also indicates that effects of determinants may vary among project sectors. The paper also highlights a dilemma of technical development cooperation. The countries with low government capacity are usually the ones most in need of technical cooperation projects. But, at the same time, they are also the countries in which these projects have the poorest performance The second research gap addressed by this thesis is related to one specific factor in the policy and institutional environment of recipient countries, namely corruption. This determinant is often cited as essential for project performance but has gained surprisingly little coverage in empirical studies. The few existing studies on the effect of corruption on project performance are inconclusive. Some find a statistically significant correlation, while others do not. Furthermore, so far, all existing studies use corruption perception indices as a measurement for corruption, despite the fact that these indices have well-known deficits when it comes to this research topic. One of these deficits is that such indices do not distinguish between different forms of corruption, even though it is likely that the effect of corruption will vary depending on the type of development project and form of corruption. The second paper in this thesis (Corruption paper) seeks to address this inconclusive state of the research while focusing on one specific form of corruption, namely bribery between private firms and public officials. The paper finds a small but statistically significant correlation between the corruption level and the performance of World Bank projects. The systematic effect of corruption on project performance confirms the need to consider the risk of corruption in the design and during the implementation of projects. Nonetheless, the relatively small effect of corruption and the low pseudo R-squareds advise not to overestimate the relevance of corruption for project performance. At least for the project level, the paper finds no indication that corruption is a primary obstacle to aid effectiveness. The third research gap addressed by this thesis is related to one specific sample, namely recipient countries of the International Development Association (IDA). The question of whether the policy and institutional environment affects project performance is of particular relevance for these countries, given that the World Bank's ratings on a country's policy and institutional environment decide how much IDA resources it receives. One core justification of such an allocation system is that it helps to steer more resources to places where they are most effective. However, so far, there is no conclusive empirical evidence for this statement. The only study specifically focusing on this topic, a study by the Independent Evaluation Group of the World Bank from 2010, has essential methodological limitations. The third paper of this thesis (CPR paper) seeks to address this research gap by testing whether a more refined analysis confirms the assumption of previous studies that the policy and institutional environment of IDA-recipient countries, measured by the Country Policy and Institutional Assessment ratings, has an effect on the performance of World Bank projects. Overall, neither the main regression models nor any of the robustness tests indicate a substantial correlation between the policy and institutional environment and project performance. Only for Investments Loans is the coefficient large enough to assume some effect. The overall results not only contradict the results of previous studies, but also raise strong doubts around one of the core justifications for the allocation system of the IDA. All three papers rely on a statistical large-N analysis of the performance ratings of individual development projects. These ratings are usually assigned based on the final evaluation of a project and indicate the merit or worth of an activity. The merit or worth of an activity itself is measured by criteria like relevance, effectiveness, and efficiency. In the case of the two papers on World Bank projects, the needed data stem from different databases of the World Bank. The relevant data for the GIZ paper are gathered from internal evaluation reports of the GIZ. Logistic regressions are applied as the main analytical tool. Overall, the three papers show that the policy and institutional environment of recipient countries matters for project performance, but only to a small degree and under certain circumstances. This result highlights that many researchers and practitioners tend to overestimate the role that the policy and institutional environment of recipient countries plays in project performance. Furthermore, the thesis shows that authors of future studies should consider possible interactions between project- and country-level determinants whenever possible, both in their theoretical arguments and statistical models. Otherwise, the debate on the determinants for project performance is at risk of degenerating into a statistics tournament without any connection to reality.