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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.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
Pichia pastoris (syn. Komagataella phaffi) is a distinguished expression system widely used in industrial production processes. Recent molecular research has focused on numerous approaches to increase recombinant protein yield in P. pastoris. For example, the design of expression vectors and synthetic genetic elements, gene copy number optimization, or co-expression of helper proteins
(transcription factors, chaperones, etc.). However, high clonal variability of transformants and low screening throughput have hampered significant success.
To enhance screening capacities, display-based methodologies inherit the potential for efficient isolation of producer clones via fluorescence-activated cell sorting (FACS). Therefore, this study focused on developing a novel clone selection method that is based on the non-covalent attachment of Fab fragments on the P. pastoris cell surface to be applicable for FACS.
Initially, a P. pastoris display system was developed, which is a prerequisite for the surface capture of secreted Fabs. A Design of Experiments approach was applied to analyze the influence of various genetic elements on antibody fragment display. The combined P. pastoris formaldehyde dehydrogenase promoter (PFLD1), Saccharomyces cerevisiae invertase 2 signal peptide (ScSUC2), - agglutinin (ScSAG1) anchor protein, and the ARS of Kluyveromyces lactis (panARS) conferred highest display levels.
Subsequently, eight single-chain variable fragments (scFv) specific for the constant part of the Fab heavy or light chain were individually displayed in P. pastoris. Among the tested scFvs, the anti-human CH1 IgG domain scFv allowed the most efficient Fab capture detected by flow cytometry.
Irrespective of the Fab sequence, exogenously added as well as simultaneously secreted Fabs were successfully captured on the cell surface. Furthermore, Fab secretion capacities were shown to correlate to the level of surface-bound Fabs as demonstrated for characterized producer clones.
Flow-sorted clones presenting high amounts of Fabs showed an increase in median Fab titers (factor of 21 to 49) compared to unsorted clones when screened in deep-well plates. For selected candidates, improved functional Fab yields of sorted cells vs. unsorted cells were confirmed in an upscaled shake flask production. Since the scFv capture matrix was encoded on an episomal plasmid with inherently unstable autonomously replicating sequences (ARS), efficient plasmid curing was observed after removing the selective pressure. Hence, sorted clones could be immediately used for production without the need to modify the expression host or vector. The resulting switchable display/secretion system provides a streamlined approach for the isolation of Fab producers and subsequent Fab production.
As a result of CMOS scaling, radiation-induced Single-Event Effects (SEEs) in electronic circuits became a critical reliability issue for modern Integrated Circuits (ICs) operating under harsh radiation conditions. SEEs can be triggered in combinational or sequential logic by the impact of high-energy particles, leading to destructive or non-destructive faults, resulting in data corruption or even system failure. Typically, the SEE mitigation methods are deployed statically in processing architectures based on the worst-case radiation conditions, which is most of the time unnecessary and results in a resource overhead. Moreover, the space radiation conditions are dynamically changing, especially during Solar Particle Events (SPEs). The intensity of space radiation can differ over five orders of magnitude within a few hours or days, resulting in several orders of magnitude fault probability variation in ICs during SPEs. This thesis introduces a comprehensive approach for designing a self-adaptive fault resilient multiprocessing system to overcome the static mitigation overhead issue. This work mainly addresses the following topics: (1) Design of on-chip radiation particle monitor for real-time radiation environment detection, (2) Investigation of space environment predictor, as support for solar particle events forecast, (3) Dynamic mode configuration in the resilient multiprocessing system. Therefore, according to detected and predicted in-flight space radiation conditions, the target system can be configured to use no mitigation or low-overhead mitigation during non-critical periods of time. The redundant resources can be used to improve system performance or save power. On the other hand, during increased radiation activity periods, such as SPEs, the mitigation methods can be dynamically configured appropriately depending on the real-time space radiation environment, resulting in higher system reliability. Thus, a dynamic trade-off in the target system between reliability, performance and power consumption in real-time can be achieved. All results of this work are evaluated in a highly reliable quad-core multiprocessing system that allows the self-adaptive setting of optimal radiation mitigation mechanisms during run-time. Proposed methods can serve as a basis for establishing a comprehensive self-adaptive resilient system design process. Successful implementation of the proposed design in the quad-core multiprocessor shows its application perspective also in the other designs.
Many complex systems that we encounter in the world can be formalized using networks. Consequently, they have been in the focus of computer science for decades, where algorithms are developed to understand and utilize these systems.
Surprisingly, our theoretical understanding of these algorithms and their behavior in practice often diverge significantly. In fact, they tend to perform much better on real-world networks than one would expect when considering the theoretical worst-case bounds. One way of capturing this discrepancy is the average-case analysis, where the idea is to acknowledge the differences between practical and worst-case instances by focusing on networks whose properties match those of real graphs. Recent observations indicate that good representations of real-world networks are obtained by assuming that a network has an underlying hyperbolic geometry.
In this thesis, we demonstrate that the connection between networks and hyperbolic space can be utilized as a powerful tool for average-case analysis. To this end, we first introduce strongly hyperbolic unit disk graphs and identify the famous hyperbolic random graph model as a special case of them. We then consider four problems where recent empirical results highlight a gap between theory and practice and use hyperbolic graph models to explain these phenomena theoretically. First, we develop a routing scheme, used to forward information in a network, and analyze its efficiency on strongly hyperbolic unit disk graphs. For the special case of hyperbolic random graphs, our algorithm beats existing performance lower bounds. Afterwards, we use the hyperbolic random graph model to theoretically explain empirical observations about the performance of the bidirectional breadth-first search. Finally, we develop algorithms for computing optimal and nearly optimal vertex covers (problems known to be NP-hard) and show that, on hyperbolic random graphs, they run in polynomial and quasi-linear time, respectively.
Our theoretical analyses reveal interesting properties of hyperbolic random graphs and our empirical studies present evidence that these properties, as well as our algorithmic improvements translate back into practice.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
Background and aims:
To succeed in competition, elite team and individual athletes often seek the development of both, high levels of muscle strength and power as well as cardiorespiratory endurance. In this context, concurrent training (CT) is a commonly applied and effective training approach. While being exposed to high training loads, youth athletes (≤ 18 years) are yet underrepresented in the scientific literature. Besides, immunological responses to CT have received little attention. Therefore, the aims of this work were to examine the acute (< 15min) and delayed (≥ 6 hours) effects of dif-ferent exercise order in CT on immunological stress responses, muscular fitness, metabolic response, and rating of perceived exertion (RPE) in highly trained youth male and female judo athletes.
Methods:
A total of twenty male and thirteen female participants, with an average age of 16 ± 1.8 years and 14.4 ± 2.1 years, respectively, were included in the study. They were randomly assigned to two CT sessions; power-endurance versus endurance-power (i.e., study 1), or strength-endurance versus endurance-strength (i.e., study 2). Markers of immune response (i.e., white-blood-cells, granulocytes, lymphocytes, mon-ocytes, and lymphocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index), muscular fitness (i.e., counter-movement jump [CMJ]), metabolic responses (i.e., blood lactate, glucose), and RPE were collected at different time points (i.e., PRE12H, PRE, MID, POST, POST6H, POST22H).
Results (study 1):
There were significant time*order interactions for white-blood-cells, lymphocytes, granulocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The power-endurance order resulted in significantly larger PRE-to-POST increases in white-blood-cells, monocytes, and lymphocytes while the endur-ance-power order resulted in significantly larger PRE-to-POST increases in the granu-locyte-lymphocyte-ratio and systemic-inflammation-index. Likewise, significantly larger increases from PRE-to-POST6H in white-blood-cells and granulocytes were observed following the power-endurance order compared to endurance-power. All markers of immune response returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. Following the endur-ance-power order, blood lactate and glucose increased from PRE-to-MID but not from PRE-to-POST. Meanwhile, in the power-endurance order blood lactate and glucose increased from PRE-to-POST but not from PRE-to-MID. A significant time*order inter-action was observed for CMJ-force with larger PRE-to-POST decreases in the endur-ance-power order compared to power-endurance order. Further, CMJ-power showed larger PRE-to-MID performance decreases following the power-endurance order, com-pared to the endurance-power order. Regarding RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endurance-power order and larger PRE-to-POST values following the power-endurance order.
Results (study 2):
There were significant time*order interactions for lymphocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The strength-endurance order resulted in significantly larger PRE-to-POST increases in lymphocytes while the endurance-strength order resulted in significantly larger PRE-to-POST increases in the granulocyte-lymphocyte-ratio and systemic-inflammation-index. All markers of the immune system returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. From PRE-to-MID, there was a significantly greater increase in blood lactate and glu-cose following the endurance-strength order compared to strength-endurance order. Meanwhile, from PRE-to-POST there was a significantly higher increase in blood glu-cose following the strength-endurance order compared to endurance-strength order. Regarding physical fitness, a significant time*order interaction was observed for CMJ-force and CMJ-power with larger PRE-to-MID increases following the endurance-strength order compared to the strength-endurance order. For RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endur-ance-power order and larger PRE-to-POST values following the power-endurance or-der.
Conclusions:
The primary findings from both studies revealed order-dependent effects on immune responses. In male youth judo athletes, the results demonstrated greater immunological stress responses, both immediately (≤ 15 min) and delayed (≥ 6 hours), following the power-endurance order compared to the endurance-power order. For female youth judo athletes, the results indicated higher acute, but not delayed, order-dependent changes in immune responses following the strength-endurance order compared to the endurance-strength order. It is worth noting that in both studies, all markers of immune system response returned to baseline levels within 22 hours. This suggests that successful recovery from the exercise-induced immune stress response was achieved within 22 hours. Regarding metabolic responses, physical fitness, and perceived exertion, the findings from both studies indicated acute (≤ 15 minutes) alterations that were dependent on the exercise order. These alterations were primarily influ-enced by the endurance exercise component. Moreover, study 1 provided substantial evidence suggesting that internal load measures, such as immune markers, may differ from external load measures. This indicates a disparity between immunological, perceived, and physical responses following both concurrent training orders. Therefore, it is crucial for practitioners to acknowledge these differences and take them into consideration when designing training programs.
The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries.
In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.
The African weakly electric fish genus Campylomormyrus includes 15 described species mostly native to the Congo River and its tributaries. They are considered sympatric species, because their distribution area overlaps. These species generate species-specific electric organ discharges (EODs) varying in waveform characteristics, including duration, polarity, and phase number. They exhibit also pronounced divergence in their snout, i.e. the length, thickness, and curvature. The diversifications in these two phenotypical traits (EOD and snout) have been proposed as key factors promoting adaptive radiation in Campylomormyrus. The role of EODs as a pre-zygotic isolation mechanism driving sympatric speciation by promoting assortative mating has been examined using behavioral, genetical, and histological approaches. However, the evolutionary effects of the snout morphology and its link to species divergence have not been closely examined. Hence, the main objective of this study is to investigate the effect of snout morphology diversification and its correlated EOD to better understand their sympatric speciation and evolutionary drivers. Moreover, I aim to utilize the intragenus and intergenus hybrids of Campylomormyrus to better understand trait divergence as well as underlying molecular/genetic mechanisms involved in the radiation scenario. To this end, I utilized three different approaches: feeding behavior analysis, diet assessment, and geometric morphometrics analysis. I performed feeding behavior experiments to evaluate the concept of the phenotype-environment correlation by testing whether Campylomormyrus species show substrate preferences. The behavioral experiments showed that the short snout species exhibits preference to sandy substrate, the long snout species prefers a stone substrate, and the species with intermediate snout size does not exhibit any substrate preference. The experiments suggest that the diverse feeding apparatus in the genus Campylomormyrus may have evolved in adaptation to their microhabitats. I also performed diet assessments of sympatric Campylomormyrus species and a sister genus species (Gnathonemus petersii) with markedly different snout morphologies and EOD using NGS-based DNA metabarcoding of their stomach contents. The diet of each species was documented showing that aquatic insects such as dipterans, coleopterans and trichopterans represent the major diet component. The results showed also that all species are able to exploit diverse food niches in their habitats. However, comparing the diet overlap indices showed that different snout morphologies and the associated divergence in the EOD translated into different prey spectra. These results further support the idea that the EOD could be a ‘magic trait’ triggering both adaptation and reproductive isolation. Geometric morphometrics method was also used to compare the phenotypical shape traits of the F1 intragenus (Campylomormyrus) and intergenus (Campylomormyrus species and Gnathonemus petersii) hybrids relative to their parents. The hybrids of these species were well separated based on the morphological traits, however the hybrid phenotypic traits were closer to the short-snouted species. In addition, the likelihood that the short snout expressed in the hybrids increases with increasing the genetic distance of the parental species. The results confirmed that additive effects produce intermediate phenotypes in F1-hybrids. It seems, therefore, that morphological shape traits in hybrids, unlike the physiological traits, were not expressed straightforward.
Nowadays, innovative and entrepreneurial activities and their actors are embedded in interdependent systems to drive joint value creation. Innovation ecosystems and entrepreneurial ecosystems have become established system-level concepts in management research to explain how value transpires between different actors and institutions in distinct contexts. Despite the popularity of the concepts, researchers have critiqued their theoretical depth, conceptual distinctiveness, as well as operationalization and measurement (Autio & Thomas, 2022; Klimas & Czakon, 2022). Furthermore, in light of current-day challenges, research has yet to address how context impacts innovation and entrepreneurial ecosystems and their actors and elements (Wurth et al., 2022).
The aim of this cumulative thesis is to provide a deeper understanding of the conceptualization, operationalization, and measurement of innovation and entrepreneurial ecosystems and investigate how contextual factors can influence the overall ecosystem and its key actors. To this end, bibliometric and empirical-qualitative methods, as well as narrative and systematic literature reviews, are employed. After introducing the research scope and key concepts in Chapter 1, a systematic literature review to operationalize and measure the concept of innovation ecosystems is conducted, and an integrative framework of its composition is introduced in Chapter 2. In Chapter 3, the innovation journal network is outlined by means of science mapping to determine current and emerging research areas characterizing innovation studies. In Chapters 4 and 5, the interplay between the temporal context of the Covid-19 pandemic and the spatial context of entrepreneurial ecosystems is assessed by focusing on the role of organizational resilience and affordances. The findings shed new light on the dynamics and boundaries of entrepreneurial ecosystems as they move between the spatial and digital realm. Building on this, an integrative framework of digital entrepreneurial ecosystems is presented in Chapter 6. The concluding Chapter 7 summarizes my thesis’s conceptual, theoretical, and empirical insights, highlighting implications, limitations, and promising future research avenues.
The findings of this cumulative thesis contribute to the theoretical and conceptual advancement of ecosystems in innovation and entrepreneurship by providing insights into the measurement and operationalization of its elements. Furthermore, the results show that contextual factors, such as crisis events or institutional circumstances, influence innovation and entrepreneurial ecosystems and their actors, calling for a more nuanced consideration of ecosystem configurations and dynamics. By drawing from the theory of affordances, the elements that actually afford value to the actors and how they shift between the physical and digital realm are portrayed. Based on these findings, this thesis introduces novel frameworks and conceptual advancements of the configurations and boundaries of innovation and (digital) entrepreneurial ecosystems, laying the foundation for a renewed understanding of how to design, orchestrate, and evaluate ecosystems today and in the future.
Advances in hydrogravimetry
(2023)
The interest of the hydrological community in the gravimetric method has steadily increased within the last decade. This is reflected by numerous studies from many different groups with a broad range of approaches and foci. Many of those are traditionally rather hydrology-oriented groups who recognized gravimetry as a potential added value for their hydrological investigations. While this resulted in a variety of interesting and useful findings, contributing to extend the respective knowledge and confirming the methodological potential, on the other hand, many interesting and unresolved questions emerged.
This thesis manifests efforts, analyses and solutions carried out in this regard. Addressing and evaluating many of those unresolved questions, the research contributes to advancing hydrogravimetry, the combination of gravimetric and hydrological methods, in showing how gravimeters are a highly useful tool for applied hydrological field research.
In the first part of the thesis, traditional setups of stationary terrestrial superconducting gravimeters are addressed. They are commonly installed within a dedicated building, the impermeable structure of which shields the underlying soil from natural exchange of water masses (infiltration, evapotranspiration, groundwater recharge). As gravimeters are most sensitive to mass changes directly beneath the meter, this could impede their suitability for local hydrological process investigations, especially for near-surface water storage changes (WSC). By studying temporal local hydrological dynamics at a dedicated site equipped with traditional hydrological measurement devices, both below and next to the building, the impact of these absent natural dynamics on the gravity observations were quantified. A comprehensive analysis with both a data-based and model-based approach led to the development of an alternative method for dealing with this limitation. Based on determinable parameters, this approach can be transferred to a broad range of measurement sites where gravimeters are deployed in similar structures. Furthermore, the extensive considerations on this topic enabled a more profound understanding of this so called umbrella effect.
The second part of the thesis is a pilot study about the field deployment of a superconducting gravimeter. A newly developed field enclosure for this gravimeter was tested in an outdoor installation adjacent to the building used to investigate the umbrella effect. Analyzing and comparing the gravity observations from both indoor and outdoor gravimeters showed performance with respect to noise and stable environmental conditions was equivalent while the sensitivity to near-surface WSC was highly increased for the field deployed instrument. Furthermore it was demonstrated that the latter setup showed gravity changes independent of the depth where mass changes occurred, given their sufficiently wide horizontal extent. As a consequence, the field setup suits monitoring of WSC for both short and longer time periods much better. Based on a coupled data-modeling approach, its gravity time series was successfully used to infer and quantify local water budget components (evapotranspiration, lateral subsurface discharge) on the daily to annual time scale.
The third part of the thesis applies data from a gravimeter field deployment for applied hydrological process investigations. To this end, again at the same site, a sprinkling experiment was conducted in a 15 x 15 m area around the gravimeter. A simple hydro-gravimetric model was developed for calculating the gravity response resulting from water redistribution in the subsurface. It was found that, from a theoretical point of view, different subsurface water distribution processes (macro pore flow, preferential flow, wetting front advancement, bypass flow and perched water table rise) lead to a characteristic shape of their resulting gravity response curve. Although by using this approach it was possible to identify a dominating subsurface water distribution process for this site, some clear limitations stood out. Despite the advantage for field installations that gravimetry is a non-invasive and integral method, the problem of non-uniqueness could only be overcome by additional measurements (soil moisture, electric resistivity tomography) within a joint evaluation. Furthermore, the simple hydrological model was efficient for theoretical considerations but lacked the capability to resolve some heterogeneous spatial structures of water distribution up to a needed scale. Nevertheless, this unique setup for plot to small scale hydrological process research underlines the high potential of gravimetery and the benefit of a field deployment.
The fourth and last part is dedicated to the evaluation of potential uncertainties arising from the processing of gravity observations. The gravimeter senses all mass variations in an integral way, with the gravitational attraction being directly proportional to the magnitude of the change and inversely proportional to the square of the distance of the change. Consequently, all gravity effects (for example, tides, atmosphere, non-tidal ocean loading, polar motion, global hydrology and local hydrology) are included in an aggregated manner. To isolate the signal components of interest for a particular investigation, all non-desired effects have to be removed from the observations. This process is called reduction. The large-scale effects (tides, atmosphere, non-tidal ocean loading and global hydrology) cannot be measured directly and global model data is used to describe and quantify each effect. Within the reduction process, model errors and uncertainties propagate into the residual, the result of the reduction. The focus of this part of the thesis is quantifying the resulting, propagated uncertainty for each individual correction. Different superconducting gravimeter installations were evaluated with respect to their topography, distance to the ocean and the climate regime. Furthermore, different time periods of aggregated gravity observation data were assessed, ranging from 1 hour up to 12 months. It was found that uncertainties were highest for a frequency of 6 months and smallest for hourly frequencies. Distance to the ocean influences the uncertainty of the non-tidal ocean loading component, while geographical latitude affects uncertainties of the global hydrological component. It is important to highlight that the resulting correction-induced uncertainties in the residual have the potential to mask the signal of interest, depending on the signal magnitude and its frequency. These findings can be used to assess the value of gravity data across a range of applications and geographic settings.
In an overarching synthesis all results and findings are discussed with a general focus on their added value for bringing hydrogravimetric field research to a new level. The conceptual and applied methodological benefits for hydrological studies are highlighted. Within an outlook for future setups and study designs, it was once again shown what enormous potential is offered by gravimeters as hydrological field tools.
The field of exercise psychology has established robust evidence on the health benefits of physical activity. However, interventions to promote sustained exercise behavior have often proven ineffective. This dissertation addresses challenges in the field, particularly the neglect of situated and affective processes in understanding and changing exercise behavior. Dual process models, considering both rational and affective processes, have gained recognition. The Affective Reflective Theory of Physical Inactivity and Exercise (ART) is a notable model in this context, positing that situated processes in-the-moment of choice influence exercise decisions and subsequent exercise behavior.
The dissertation identifies current challenges within exercise psychology and proposes methodological and theoretical advancements. It emphasizes the importance of momentary affective states and situated processes, offering alternatives to self-reported measures and advocating for a more comprehensive modeling of individual variability. The focus is on the affective processes during exercise, theorized to reappear in momentary decision-making, shaping overall exercise behavior.
The first publication introduces a new method by using automated facial action analysis to measure variable affective responses during exercise. It explores how these behavioral indicators covary with self-reported measures of affective valence and perceived exertion. The second publication delves into situated processes at the moment of choice between exercise and non-exercise options, revealing that intraindividual factors play a crucial role in explaining exercise-related choices. The third publication presents an open-source research tool, the Decisional Preferences in Exercising Test (DPEX), designed to capture repeated situated decisions and predict exercise behavior based on past experiences.
The findings challenge previous assumptions and provide insights into the complex interplay of affective responses, situated processes, and exercise choices. The dissertation underscores the need for individualized interventions that manipulate affective responses during exercise and calls for systematic testing to establish causal links to automatic affective processes and subsequent exercise behavior. This dissertation highlights the necessity for methodological and conceptual refinements in understanding and promoting exercise behavior, ultimately contributing to the broader goal of combating increasing inactivity trends.
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
An exploration of activity and therapist preferences and their predictors in German-speaking samples
(2023)
According to current definitions of evidence-based practice, patients’ preferences play an important role for the psychotherapeutic process and outcomes. However, whereas a significant body of research investigated preferences regarding specific treatments, research on preferred activities or therapist characteristics is rare, investigated heterogeneous aspects with inconclusive results, lacked validated assessment tools, and neglected relevant preferences, their predictors as well as the perspective of mental health professionals. Therefore, the three studies of this dissertation aimed to address the most fundamental drawbacks in current preference research by providing a validated questionnaire, focus efforts on activity and therapist preferences and add preferences of psychotherapy trainees. To this end, Paper I reports the translation and validation of the 18-item Cooper-Norcross Inventory of Preference (C-NIP) in a broad, heterogeneous sample of N = 969 laypeople, resulting in good to acceptable reliabilities and first evidence of validity. However, the original factor structure was not replicated. Paper II assesses activity preferences of psychotherapists in training using the C-NIP and compares them with the initial laypeople sample. There were significant differences between both samples, with trainees preferring a more patient-directed, emotionally intense and confrontational approach than laypeople. CBT trainees preferred a more therapist-directed, present-focused, challenging and less emotional intense approach than psychodynamic or -analytic trainees. Paper III explores therapist preferences and tests predictors for specific preference choices. For most characteristics, more than half of the participants did not have specific preferences. Results pointed towards congruency effects (i.e., preference for similar characteristics), especially for members of marginalized groups. The dissertation provides both researchers and practitioners with a validated questionnaire, shows potentially obstructive differences between patients and therapists and underlines the importance of therapist characteristics for marginalized groups, thereby laying the foundation for future applications and implementations in research and practice.
Starch is an essential biopolymer produced by plants. Starch can be made inside source tissue (such as leaves) and sink tissue (such as fruits and tubers). Nevertheless, understanding how starch metabolism is regulated in source and sink tissues is fundamental for improving crop production.
Despite recent advances in the understanding of starch and its metabolism, there is still a knowledge gap in the source and sink metabolism. Therefore, this study aimed to summarize the state of the art regarding starch structure and metabolism inside plants. In addition, this study aimed to elucidate the regulation of starch metabolism in the source tissue using the leaves of a model organism, Arabidopsis thaliana, and the sink tissue of oil palm (Elaeis guineensis) fruit as a commercial crop.
The research regarding the source tissue will focus on the effect of the blockage of starch degradation on the starch parameter in leaves, especially in those of A. thaliana, which lack both disproportionating enzyme 2 (DPE2) and plastidial glucan phosphorylase 1 (PHS1) (dpe2/phs1). The additional elimination of phosphoglucan water dikinase (PWD), starch excess 4 (SEX4), isoamylase 3 (ISA3), and disproportionating enzyme 1 (DPE1) in the dpe2/phs1 mutant background demonstrates the alteration of starch granule number per chloroplast. This study provides insights into the control mechanism of granule number regulation in the chloroplast.
The research regarding the sink tissue will emphasize the relationship between starch metabolism and the lipid metabolism pathway in oil palm fruits. This study was conducted to observe the alteration of starch parameters, metabolite abundance, and gene expression during oil palm fruit development with different oil yields. This study shows that starch and sucrose can be used as biomarkers for oil yield in oil palms. In addition, it is revealed that the enzyme isoforms related to starch metabolism influence the oil production in oil palm fruit.
Overall, this thesis presents novel information regarding starch metabolism in the source tissue of A.thaliana and the sink tissue of E.guineensis. The results shown in this thesis can be applied to many applications, such as modifying the starch parameter in other plants for specific needs.
In nature, plants often encounter biotic and abiotic stresses, which can cause reduced crop yield and quality, and threaten the nutrition of a growing human population. As heat stress (HS) is one of the main abiotic stresses, and is projected to increase due to global warming, it is necessary to better understand how plants respond and survive under HS. In Arabidopsis thaliana, plants can survive under severe HS if primed by a non-lethal HS, a process called acquisition of thermotolerance. This primed stated can be maintained for several days, and the ability of plants to maintain the primed state is called maintenance of acquired thermotolerance (mATT) or HS memory. According to current research, two Heat shock factors (HSFs) HSFA2 and HSFA3 are known to account for the majority of mATT capability, and there are other HSFs e.g. HSFA1b and HSFA6b in HSF complexes containing HSFA2 and/or HSFA3, however, the roles of these HSFs in HS memory is not clearly understood. Moreover, the mechanism of these HSFs in regulating HS memory is unclear, whether transcriptional machinery e.g. the Mediator complex contributes to transcriptional memory. This work investigates the role of HSFs and Mediator subunits in HS memory in A. thaliana. For the role of HSFs, the interaction between HSFA1b and HSFA2 during HS memory phase was confirmed by in vivo co- immunoprecipitation (Co-IP). HSFA1b, HSFA2, HSFA3 and HSFA6b targeted HS memory-related genes according to DNA affinity purification sequencing (DAP-seq) data, and targets of HSFA1b were confirmed in vivo by chromatin immunoprecipitation qPCR (ChIP-qPCR). The mutant of hsfa6b showed an HS memory deficiency phenotype in mATT survival assay. These data confirmed the role for HSFA2 and HSFA3 in HS memory, and suggest that HSFA1b and HSFA6b also function in HS memory. The Mediator complex functions as an RNA Polymerase II (RNA Pol II) co-regulator, and includes Head, Middle, Tail and Kinase modules. Both MED23 and MED32 belong to the Tail module, and they have a positive role in HS memory. MED23 interacted with HSFA3, as determined by yeast two hybrid (Y2H) and in vivo Co-IP assays. The med23 mutant showed a decreased HS memory phenotype, reduced expression of Type I (sustained expression) memory genes following HS, and reduced accumulation of the memory-associated Tri-methylation of histone H3 lysine 4 (H3K4me3)histone modification at HS memory-related gene loci after HS. MED23 was recruited to HS-inducible memory and non-memory genes after HS, as determined by ChIP-qPCR. The med32
mutant showed a reduced HS memory phenotype, decreased expression of Type I and Type II (hyper-induction) memory genes, and lower accumulation of H3K4me3 at memory gene lociafter HS. However, MED32 did not show interaction with any tested HSF in Y2H or in vivo Co-IP. MED32 regulated the recruitment of RNA Pol II at HS-inducible genes after HS, but was not itself recruited to HS memory genes after HS. These results provided more evidence
that the Mediator subunits MED23 and MED32 regulate HS memory on transcriptional and epigenetic levels. In general, this work provides a better insight into the molecular mechanism of how HSFs and Mediator subunits regulate HS memory in plants and will provide new perspectives to breed crops with improved thermotolerance.
The light reactions of photosynthesis are carried out by a series of multiprotein complexes embedded in thylakoid membranes. Among them, photosystem I (PSI), acting as plastocyanin-ferderoxin oxidoreductase, catalyzes the final reaction. Together with light-harvesting antenna I, PSI forms a high-molecular-weight supercomplex of ~600 kDa, consisting of eighteen subunits and nearly two hundred co-factors. Assembly of the various components into a functional thylakoid membrane complex requires precise coordination, which is provided by the assembly machinery. Although this includes a small number of proteins (PSI assembly factors) that have been shown to play a role in the formation of PSI, the process as a whole, as well as the intricacy of its members, remains largely unexplored.
In the present work, two approaches were used to find candidate PSI assembly factors. First, EnsembleNet was used to select proteins thought to be functionally related to known PSI assembly factors in Arabidopsis thaliana (approach I), and second, co-immunoprecipitation (Co-IP) of tagged PSI assembly factors in Nicotiana tabacum was performed (approach II).
Here, the novel PSI assembly factors designated CO-EXPRESSED WITH PSI ASSEMBLY 1 (CEPA1) and Ycf4-INTERACTING PROTEIN 1 (Y4IP1) were identified. A. thaliana null mutants for CEPA1 and Y4IP1 showed a growth phenotype and pale leaves compared with the wild type. Biophysical experiments using pulse amplitude modulation (PAM) revealed insufficient electron transport on the PSII acceptor side. Biochemical analyses revealed that both CEPA1 and Y4IP1 are specifically involved in PSI accumulation in A. thaliana at the post-translational level but are not essential. Consistent with their roles as factors in the assembly of a thylakoid membrane protein complex, the two proteins localize to thylakoid membranes. Remarkably, cepa1 y4ip1 double mutants exhibited lethal phenotypes in early developmental stages under photoautotrophic growth. Finally, co-IP and native gel experiments supported a possible role for CEPA1 and Y4IP1 in mediating PSI assembly in conjunction with other PSI assembly factors (e.g., PPD1- and PSA3-CEPA1 and Ycf4-Y4IP1). The fact that CEPA1 and Y4IP1 are found exclusively in green algae and higher plants suggests eukaryote-specific functions. Although the specific mechanisms need further investigation, CEPA1 and Y4IP1 are two novel assembly factors that contribute to PSI formation.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.
This research investigated the relationship between frequent engagement in industrial action (also known as ‘employee strikes’) and the internal attractiveness of government employment. It focused on a special group of public employees: public university lecturers and public-school teachers in Uganda who frequently engaged in industrial action. At the very basic level, the research explored whether public employees frequently engaged in industrial action because they considered public service employment to be unattractive or whether frequent engagement in industrial action was in fact part of the attractiveness of government employment. Beyond exploring these relationships, it also explained why (or why not) such relationships existed.
Methodologically, the research was conducted using an exploratory sequential design – a mixed methods study design that starts with a qualitative followed by a quantitative phase. It is the results of the initial qualitative phase that determined the direction of the subsequent quantitative phase. The qualitative phase started with an exploration of the relationship between industrial action and internal public service attractiveness, resulting into two specific research questions:
1) Why do public employees engage in industrial action and what role does frequent engagement in industrial action play in their perception of public service attractiveness?
2) Why and how is organizational justice related to public employees’ perception of public service attractiveness?
The above questions were answered both qualitatively and quantitatively. The theoretical postulations of the Social Movements Theories, Social Exchange Theory, and the Signaling Theory were used to structure the research assumptions and hypotheses.
The results showed that public employees engaged in industrial action mostly because of relative, rather than absolute deprivation. An established culture of workplace militancy was also found to be key in actualizing industrial action as was the (perceived) absence of alternatives to achieve workplace justice. Importantly, there was a clear dichotomy between absolute working conditions and frequent engagement in industrial action. Frequent engagement in industrial action was itself found to have both positive and negative effects on internal public service attractiveness. It was also found that public service attractiveness from the perspective of current public employees might be different from what it is from the perspective of prospective employees. This is because current public employees do not assume what it feels like to work for government, but mostly use their day-to-day lived experiences to judge the attractiveness of their employer. The existing literature is particularly deficient on analyzing public service attractiveness from an internal perspective, which is surprising given the public sector’s high reliance on internal recruitment.
The research results underlined key implications for theory, practice, and research. At theory level, the results suggested that public employee ratings of internal public service attractiveness were heavily affected by halo effects and should therefore not be taken at face value. The complex workplace social exchanges which are deeply rooted in organizational justice and the ‘personification metaphor’ were also emphasized. From an empirical perspective, the results underlined the need to prioritize internal public service attractiveness as recent research has confirmed the value of family socialization and internal recommendations in making public sector employment attractive, even to external applicants. This research argues that the centrality of organizational justice in public sector employee relations requires public sector organizations to be intentional in their bid to create fair, just, and attractive workplaces. Beyond assessing the fairness of personnel policies, procedures, and interactional relationships, it is also important to prepare and equip public managers with the right skills to promote and practice justice in their day-to-day interactions with public employees, and to encourage, improve, and facilitate alternative public employee feedback mechanisms.
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.
Point processes are a common methodology to model sets of events. From earthquakes to social media posts, from the arrival times of neuronal spikes to the timing of crimes, from stock prices to disease spreading -- these phenomena can be reduced to the occurrences of events concentrated in points. Often, these events happen one after the other defining a time--series.
Models of point processes can be used to deepen our understanding of such events and for classification and prediction. Such models include an underlying random process that generates the events. This work uses Bayesian methodology to infer the underlying generative process from observed data. Our contribution is twofold -- we develop new models and new inference methods for these processes.
We propose a model that extends the family of point processes where the occurrence of an event depends on the previous events. This family is known as Hawkes processes. Whereas in most existing models of such processes, past events are assumed to have only an excitatory effect on future events, we focus on the newly developed nonlinear Hawkes process, where past events could have excitatory and inhibitory effects. After defining the model, we present its inference method and apply it to data from different fields, among others, to neuronal activity.
The second model described in the thesis concerns a specific instance of point processes --- the decision process underlying human gaze control. This process results in a series of fixated locations in an image. We developed a new model to describe this process, motivated by the known Exploration--Exploitation dilemma. Alongside the model, we present a Bayesian inference algorithm to infer the model parameters.
Remaining in the realm of human scene viewing, we identify the lack of best practices for Bayesian inference in this field. We survey four popular algorithms and compare their performances for parameter inference in two scan path models.
The novel models and inference algorithms presented in this dissertation enrich the understanding of point process data and allow us to uncover meaningful insights.
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.
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.
Biostimulant SuperFifty based molecular priming to increase plant strength and stress tolerance
(2023)
Establishment of final leaf size in plants represents a complex mechanism that relies on the precise regulation of two interconnected cellular processes, cell division and cell expansion. In previous work, the barley protein BROAD LEAF1 (BLF1) was identified as a novel negative regulator of cell proliferation, that mainly limits leaf growth in the width direction. Here I identified a novel RING/U-box protein that interacts with BLF1 through a yeast two hybrid screen. Using BiFC, Co-IP and FRET I confirmed the interaction of the two proteins in planta. Enrichment of the BLF1-mEGFP fusion protein and the increase of the FRET signal upon MG132 treatment of tobacco plants, together with an in vivo ubiquitylation assay in bacteria, confirmed that the RING/U-box E3 interacts with BLF1 to mediate its ubiquitylation and degradation by the 26S proteasome system. Consistent with regulation of endogenous BLF1 in barley by proteasomal degradation, inhibition of the proteasome by bortezomib treatment on BLF1-vYFP transgenic barley plants also resulted in an enrichment of the BLF1 protein. I thus demonstrated that RING/U-box E3 is colocalized with BLF1 in nuclei and negatively regulates BLF1 protein levels. Analysis of ring-e3_1 knock-out mutants suggested the involvement of the RING/U-box E3 gene in leaf growth control, although the effect was mainly on leaf length. Together, my results suggest that proteasomal degradation, possibly mediated by RING/U-box E3, contributes to fine-tuning BLF1 protein-level in barley.
The urge of light utilization in fabrication of materials is as encouraging as challenging. Steadily increasing energy consumption in accordance with rapid population growth, is requiring a corresponding solution within the same rate of occurrence speed. Therefore, creating, designing and manufacturing materials that can interact with light and in further be applicable as well as disposable in photo-based applications are very much under attention of researchers. In the era of sustainability for renewable energy systems, semiconductor-based photoactive materials have received great attention not only based on solar and/or hydrocarbon fuels generation from solar energy, but also successful stimulation of photocatalytic reactions such as water splitting, pollutant degradation and organic molecule synthesisThe turning point had been reached for water splitting with an electrochemical cell consisting of TiO2-Pt electrode illuminated by UV light as energy source rather than an external voltage, that successfully pursued water photolysis by Fujishima and Honda in 1972. Ever since, there has been a great deal of interest in research of semiconductors (e.g. metal oxide, metal-free organic, noble-metal complex) exhibiting effective band gap for photochemical reactions. In the case of environmental friendliness, toxicity of metal-based semiconductors brings some restrictions in possible applications. Regarding this, very robust and ‘earth-abundant’ organic semiconductor, graphitic carbon nitride has been synthesized and successfully applied in photoinduced applications as novel photocatalyst. Properties such as suitable band gap, low charge carrier recombination and feasibility for scaling up, pave the way of advance combination with other catalysts to gather higher photoactivity based on compatible heterojunction.
This dissertation aims to demonstrate a series of combinations between organic semiconductor g-CN and polymer materials that are forged through photochemistry, either in synthesis or in application. Fabrication and design processes as well as applications performed in accordance to the scope of thesis will be elucidated in detail. In addition to UV light, more attention is placed on visible light as energy source with a vision of more sustainability and better scalability in creation of novel materials and solar energy based applications.
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.
Continental rifts are key geodynamic regions where the complex interplay of magmatism and faulting activity can be studied to understand the driving forces of extension and the formation of new divergent plate boundaries. Well-preserved rift morphology can provide a wealth of information on the growth, interaction, and linkage of normal-fault systems through time. If rift basins are preserved over longer geologic time periods, sedimentary archives generated during extensional processes may mirror tectonic and climatic influences on erosional and sedimentary processes that have varied over time. Rift basins are furthermore strategic areas for hydrocarbon and geothermal energy exploration, and they play a central role in species dispersal and evolution as well as providing or inhibiting hydrologic connectivity along basins at emerging plate boundaries.
The Cenozoic East African rift system (EARS) is one of the most important continental extension zones, reflecting a range of evolutionary stages from an early rift stage with isolated basins in Malawi to an advanced stage of continental extension in southern Afar. Consequently, the EARS is an ideal natural laboratory that lends itself to the study of different stages in the breakup of a continent. The volcanically and seismically active eastern branch of the EARS is characterized by multiple, laterally offset tectonic and magmatic segments where adjacent extensional basins facilitate crustal extension either across a broad deformation zone or via major transfer faulting. The Broadly Rifted Zone (BRZ) in southern Ethiopia is an integral part of the eastern branch of the EARS; in this region, rift segments of the southern Ethiopian Rift (sMER) and northern Kenyan Rift (nKR) propagate in opposite directions in a region with one of the earliest manifestations of volcanism and extensional tectonism in East Africa. The basin margins of the Chew-Bahir Basin and the Gofa Province, characterized by a semi-arid climate and largely uniform lithology, provide ideal conditions for studying the tectonic and geomorphologic features of this complex kinematic transfer zone, but more importantly, this area is suitable for characterizing and quantifying the overlap between the propagating structures of the sMER and nKR and the resulting deformation patterns of the BRZ transfer zones.
In this study, I have combined data from thermochronology, thermal modeling, morphometry, paleomagnetic analysis, geochronology, and geomorphological field observations with information from published studies to reconstruct the spatiotemporal relationship between volcanism and fault activity in the BRZ and quantify the deformation patterns of the overlapping rift segments. I present the following results: (1) new thermochronological data from the en-échelon basin margins and footwall blocks of the rift flanks and morphometric results verified in the field to link different phases of magmatism and faulting during extension and infer geomorphological landscape features related to the current tectonic interaction between the nKR and the sMER; (2) temporally constrained paleomagnetic data from the BRZ overlap zone between the Ethiopian and Kenyan rifts to quantitatively determine block rotation between the two segments. Combining the collected data, time-temperature histories of thermal modeling results from representative samples show well-defined deformation phases between 25–20 Ma, 15–9Ma, and ~5 Ma to the present. Each deformation phase is characterized by the onset of rapid cooling (>2°C/Ma) of the crust associated with uplift or exhumation of the rift shoulder. After an initial, spatially very diffuse phase of extension, the rift has gradually evolved into a system of connected structures formed in an increasingly focused rift zone during the last 5 Ma. Regarding the morphometric analysis of the rift structures, it can be shown that normalized slope indices of the river courses, spatial arrangement of knickpoints in the river longitudinal profiles of the footwall blocks, local relief values, and the average maximum values of the slope of the river profiles indicate a gradual increase in the extension rate from north (Sawula basin: mature) to south (Chew Bahir: young). The complexity of the structural evolution of the BRZ overlap zone between nKR and sMER is further emphasized by the documentation of crustal blocks around a vertical axis. A comparison of the mean directions obtained for the Eo-Oligocene (Ds=352.6°, Is=-17.0°, N=18, α95=5.5°) and Miocene (Ds=2.9°, Is=0.9°, N=9, α95=12.4°) volcanics relative to the pole for stable South Africa and with respect to the corresponding ages of the analyzed units record a significant counterclockwise rotation of ~11.1°± 6.4° and insignificant CCW rotation of ~3.2° ± 11.5°, respectively.
In this work, binding interactions between biomolecules were analyzed by a technique that is based on electrically controllable DNA nanolevers. The technique was applied to virus-receptor interactions for the first time. As receptors, primarily peptides on DNA nanostructures and antibodies were utilized. The DNA nanostructures were integrated into the measurement technique and enabled the presentation of the peptides in a controllable geometrical order. The number of peptides could be varied to be compatible to the binding sites of the viral surface proteins.
Influenza A virus served as a model system, on which the general measurability was demonstrated. Variations of the receptor peptide, the surface ligand density, the measurement temperature and the virus subtypes showed the sensitivity and applicability of the technology. Additionally, the immobilization of virus particles enabled the measurement of differences in oligovalent binding of DNA-peptide nanostructures to the viral proteins in their native environment.
When the coronavirus pandemic broke out in 2020, work on binding interactions of a peptide from the hACE2 receptor and the spike protein of the SARS-CoV-2 virus revealed that oligovalent binding can be quantified in the switchSENSE technology. It could also be shown that small changes in the amino acid sequence of the spike protein resulted in complete loss of binding. Interactions of the peptide and inactivated virus material as well as pseudo virus particles could be measured. Additionally, the switchSENSE technology was utilized to rank six antibodies for their binding affinity towards the nucleocapsid protein of SARS-CoV-2 for the development of a rapid antigen test device.
The technique was furthermore employed to show binding of a non-enveloped virus (adenovirus) and a virus-like particle (norovirus-like particle) to antibodies. Apart from binding interactions, the use of DNA origami levers with a length of around 50 nm enabled the switching of virus material. This proved that the technology is also able to size objects with a hydrodynamic diameter larger than 14 nm.
A theoretical work on diffusion and reaction-limited binding interactions revealed that the technique and the chosen parameters enable the determination of binding rate constants in the reaction-limited regime.
Overall, the applicability of the switchSENSE technique to virus-receptor binding interactions could be demonstrated on multiple examples. While there are challenges that remain, the setup enables the determination of affinities between viruses and receptors in their native environment. Especially the possibilities regarding the quantification of oligo- and multivalent binding interactions could be presented.
The trace elements, selenium (Se) and copper (Cu) play an important role in maintaining normal brain function. Since they have essential functions as cofactors of enzymes or structural components of proteins, an optimal supply as well as a well-defined homeostatic regulation are crucial. Disturbances in trace element homeostasis affect the health status and contribute to the incidence and severity of various diseases. The brain in particular is vulnerable to oxidative stress due to its extensive oxygen consumption and high energy turnover, among other factors. As components of a number of antioxidant enzymes, both elements are involved in redox homeostasis. However, high concentrations are also associated with the occurrence of oxidative stress, which can induce cellular damage. Especially high Cu concentrations in some brain areas are associated with the development and progression of neurodegenerative diseases such as Alzheimer's disease (AD). In contrast, reduced Se levels were measured in brains of AD patients. The opposing behavior of Cu and Se renders the study of these two trace elements as well as the interactions between them being particularly relevant and addressed in this work.
Heat stress (HS) is one of the major abiotic stresses which adversely affects the survival and growth of plants due to their sessile nature. To combat the detrimental effects of HS and develop thermotolerance, plants have evolved several defense mechanisms. Thermomemory is one such molecular mechanism whereby plants that have been acclimated (or primed/P) by a moderate HS can respond more efficiently and continue their growth after exposure to a severe or lethal HS (called triggering/T), while unprimed plants cannot survive. Thermomemory is known to be regulated by several transcription factors (TFs), epigenetic changes, chromatin remodellers, post-transcriptional changes and it also involves protein stability control and primary metabolism adjustment. Recent research has suggested that the shoot apical meristem (SAM) in Arabidopsis thaliana has a distinct transcriptional thermomemory which is possibly regulated by eight TFs called HEAT SHOCK FACTORS (HSFs). The main objective of this PhD thesis is to investigate the role of HSFA7b (one of the eight HSFs), in regulating thermomemory at the SAM by identifying the molecular networks it regulates. HSFA7a, a close homolog of HSFA7b, is also one of the eight HSFs that are involved in regulating thermomemory at the SAM. Thermomemory was found to be defective in the hsfa7b and hsfa7a hsfa7b mutants; the percentage survival of these seedlings was significantly lower than in wild-type (WT) seedlings after the priming and triggering (PT) treatment. Transcriptome and ChIP analyses were performed to identify the molecular networks controlled by HSFA7b and its close homolog HSFA7a, in regulating thermomemory at the SAM. The chromatin regulator SPLAYED (SYD) was found to be regulated by both HSFA7a and HSFA7b at the SAM during thermomemory. SYD is directly involved in SAM maintenance by directly regulating WUSCHEL (WUS), a master regulator of stem cell maintenance. WUS expression was down-regulated at the SAM of PT treated hsfa7a/b mutants compared to WT-Col-0 seedlings. HSFA7a and HSFA7b also jointly regulate the expression of orphan gene QUA QUINE STARCH (QQS) during thermomemory. Starch accumulation negatively correlates with QQS expression and this trend was observed in WT plants in response to thermopriming. The remobilization of starch was affected in the hsfa7a/b mutants compared to WT plants during the recovery period after T treatment. These findings indicate that defects in SAM maintenance and starch remobilization could possibly contribute to the reduced thermomemory in the hsfa7a/b mutants. Moreover, transcriptome and ChIP analysis indicate that ethylene signaling genes are directly regulated by HSFA7b during thermomemory. Transcriptome analysis of the HSFA7b-IOE line indicates that HSFA7b positively regulates the expression of HEAT STRESS ASSOCIATED 32 (HSA32), an important thermomemory gene, and HSFA7b strongly suppresses the expression of the reactive oxygen species (ROS) responsive REDOX RESPONSIVE TRANSCRIPTION FACTOR 1 (RRTF1) gene, which is also a repressed target of SYD. In Arabidopsis, the HSFA7b transcript undergoes alternative splicing at high temperatures to form two splice variants: one correctly/constitutively spliced variant which is functional and codes for the HSFA7b protein and one intron retained splice variant. Higher accumulation of the functional HSFA7b splice variant was found at the SAM compared to other tissues. Moreover, accumulation of the functional splice variant was higher in P and PT plants compared to control plants, whereas higher levels of the intron retained splice variant is found in plants subjected directly to the T treatment. The intron retained HSFA7b splice variant is degraded by the non-sense mediated decay (NMD) pathway as a means of regulating transcript level essential for protein synthesis at high temperatures. Importantly, HSFA7b protein accumulation was observed in plants subjected to PT treatment that survive and continue growth, but not in plants subjected directly to T treatment that do not survive, indicating that constitutive/ correct splicing of the HSFA7b transcript is a component of thermomemory. Taken together, these findings suggest that HSFA7a and HSFA7b jointly regulate SAM maintenance via the chromatin remodeller SYD and starch remobilization via QQS. In addition to them, HSFA7b also regulates the expression of ethylene signaling genes, heat responsive genes and the ROS responsive RRTF1. Furthermore, constitutive/correct splicing in the HSFA7b transcript is also an essential component of thermomemory.
This thesis discusses heat and charge transport phenomena in single-crystalline Silicon penetrated by nanometer-sized pores, known as mesoporous Silicon (pSi). Despite the extensive attention given to it as a thermoelectric material of interest, studies on microscopic thermal and electronic transport beyond its macroscopic characterizations are rarely reported. In contrast, this work reports the interplay of both.
PSi samples synthesized by electrochemical anodization display a temperature dependence of specific heat 𝐶𝑝 that deviates from the characteristic 𝑇^3 behaviour (at 𝑇<50𝐾). A thorough analysis reveals that both 3D and 2D Einstein and Debye modes contribute to this specific heat. Additional 2D Einstein modes (~3 𝑚𝑒𝑉) agree reasonably well with the boson peak of SiO2 in pSi pore walls. 2D Debye modes are proposed to account for surface acoustic modes causing a significant deviation from the well-known 𝑇^3 dependence of 𝐶𝑝 at 𝑇<50𝐾.
A novel theoretical model gives insights into the thermal conductivity of pSi in terms of porosity and phonon scattering on the nanoscale. The thermal conductivity analysis utilizes the peculiarities of the pSi phonon dispersion probed by the inelastic neutron scattering experiments. A phonon mean-free path of around 10 𝑛𝑚 extracted from the presented model is proposed to cause the reduced thermal conductivity of pSi by two orders of magnitude compared to p-doped bulk Silicon. Detailed analysis indicates that compound averaging may cause a further 10-50% reduction. The percolation threshold of 65% for thermal conductivity of pSi samples is subsequently determined by employing theoretical effective medium models.
Temperature-dependent electrical conductivity measurements reveal a thermally activated transport process. A detailed analysis of the activation energy 𝐸𝐴𝜎 in the thermally activated transport exhibits a Meyer Neldel compensation rule between different samples that originates in multi-phonon absorption upon carrier transport. Activation energies 𝐸𝐴𝑆 obtained from temperature-dependent thermopower measurements provide further evidence for multi-phonon assisted hopping between localized states as a dominant charge transport mechanism in pSi, as they systematically differ from the determined 𝐸𝐴𝜎 values.
Planets outside our solar system, so-called "exoplanets", can be detected with different methods, and currently more than 5000 exoplanets have been confirmed, according to NASA Exoplanet Archive. One major highlight of the studies on exoplanets in the past twenty years is the characterization of their atmospheres usingtransmission spectroscopy as the exoplanet transits. However, this characterization is a challenging process and sometimes there are reported discrepancies in the literature regarding the atmosphere of the same exoplanet. One potential reason for the observed atmospheric inconsistencies is called impact parameter degeneracy, and it is highly driven by the limb darkening effect of the host star. A brief introductionto those topics in presented in chapter 1, while the motivation and objectives of thiswork are described in chapter 2.The first goal is to clarify the origin of the transmission spectrum, which is anindicator of an exoplanet’s atmosphere; whether it is real or influenced by the impactparameter degeneracy. A second goal is to determine whether photometry from space using the Transiting Exoplanet Survey Satellite (TESS), could improve on the major parameters, which are responsible for the aforementioned degeneracy, of known exoplanetary systems. Three individual projects were conducted in order toaddress those goals. The three manuscripts are presented, in short, in the manuscriptoverview in chapter 3.More specifically, in chapter 4, the first manuscript is presented, which is an ex-tended investigation on the impact parameter degeneracy and its application onsynthetic transmission spectra. Evidently, the limb darkening of the host star isan important driver for this effect. It keeps the degeneracy persisting through different groups of exoplanets, based on the uncertainty of their impact parameter and on the type of their host star. The second goal, was addressed in the second and third manuscripts (chapter 5 and chapter 6 respectively). Using observationsfrom the TESS mission, two samples of exoplanets were studied; 10 transiting inflated hot-Jupiters and 43 transiting grazing systems. Potentially, the refinement or confirmation of their major system parameters’ measurements can assist in solving current or future discrepancies regarding their atmospheric characterization.In chapter 7 the conclusions of this work are discussed, while in chapter 8 itis proposed how TESS’s measurements can be able to discern between erroneousinterpretations of transmission spectra, especially on systems where the impact parameter degeneracy is likely not applicable.
The work is designed to investigate the impacts and sensitivity of climate change on water resources, droughts and hydropower production in Malawi, the South-Eastern region which is highly vulnerable to climate change. It is observed that rainfall is decreasing and temperature is increasing which calls for the understanding of what these changes may impact the water resources, drought occurrences and hydropower generation in the region. The study is conducted in the Greater Lake Malawi Basin (Lake Malawi and Shire River Basins) and is divided into three projects. The first study is assessing the variability and trends of both meteorological and hydrological droughts from 1970-2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation Index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. And later the relationship of the meteorological and hydrological droughts is established.
While the second study extends the drought analysis into the future by examining the potential future meteorological water balance and associated drought characteristics such as the drought intensity (DI), drought months (DM), and drought events (DE) in the Greater Lake Malawi Basin. The sensitivity of drought to changes of rainfall and temperature is also assessed using the scenario-neutral approach. The climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021–2050 and 2071–2100 are used. The study also investigates the effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble in reproducing observed drought characteristics as compared to raw climate projections.
The sensitivity of key hydrologic variables and hydropower generation to climate change in Lake Malawi and Shire River basins is assessed in third study. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Similar to second study, the scenario-neutral approach is also applied to determine the sensitivity of climate change on water resources more particularly Lake Malawi level and Shire River flow which later helps to estimate the hydropower production susceptibility.
Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions since the 36-months SPEI can predict hydrological droughts ten-months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m.a.s.l.
Despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher DI and longer events (DM). DI is projected to increase between +25% and +50% during 2021-2050 and between +131% and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, DE is decreasing. Projected droughts based on RCP8.5 are 1.7 times more severe than droughts based on RCP4.5.
It is also found that an annual temperature increase of 1°C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi’s water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows on Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5°C (3.5°C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021–2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071–2100.
The findings are later linked to global policies more particularly the United Nations Framework Convention on Climate Change (UNFCCC)’s Paris Agreement and the United Nations (UN)’s Sustainable Development Goals (SDGs), and how the failure to adhere the restriction of temperature increase below the global limit of 1.5°C will affect drought and the water resources in Malawi consequently impact the hydropower production. As a result, the achievement of most of the SDGs will be compromised.
The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change. The information generation is important for decision making more especially supporting the climate action required to fight against climate change. The frequency of extreme climate events due to climate change has reached the climate emergency as saving lives and livelihoods require urgent action.
Soil is today considered a non-renewable resource on societal time scale, as the rate of soil loss is higher than the one of soil formation.
Soil formation is complex, can take several thousands of years and is influenced by a variety of factors, one of them is time. Oftentimes, there is the assumption of constant and progressive conditions for soil and/or profile development (i.e., steady-state). In reality, for most of the soils, their (co-)evolution leads to a complex and irregular soil development in time and space characterised by “progressive” and “regressive” phases.
Lateral transport of soil material (i.e., soil erosion) is one of the principal processes shaping the land surface and soil profile during “regressive” phases and one of the major environmental problems the world faces.
Anthropogenic activities like agriculture can exacerbate soil erosion. Thus, it is of vital importance to distinguish short-term soil redistribution rates (i.e., within decades) influenced by human activities differ from long-term natural rates. To do so, soil erosion (and denudation) rates can be determined by using a set of isotope methods that cover different time scales at landscape level.
With the aim to unravel the co-evolution of weathering, soil profile development and lateral redistribution on a landscape level, we used Pluthonium-239+240 (239+240Pu), Beryllium-10 (10Be, in situ and meteoric) and Radiocarbon (14C) to calculate short- and long-term erosion rates in two settings, i.e., a natural and an anthropogenic environment in the hummocky ground moraine landscape of the Uckermark, North-eastern Germany. The main research questions were:
1. How do long-term and short-term rates of soil redistributing processes differ?
2. Are rates calculated from in situ 10Be comparable to those of using meteoric 10Be?
3. How do soil redistribution rates (short- and long-term) in an agricultural and in a natural landscape compare to each other?
4. Are the soil patterns observed in northern Germany purely a result of past events (natural and/or anthropogenic) or are they imbedded in ongoing processes?
Erosion and deposition are reflected in a catena of soil profiles with no or almost no erosion on flat positions (hilltop), strong erosion on the mid-slope and accumulation of soil material at the toeslope position. These three characteristic process domains were chosen within the CarboZALF-D experimental site, characterised by intense anthropogenic activities. Likewise, a hydrosequence in an ancient forest was chosen for this study and being regarded as a catena strongly influenced by natural soil transport.
The following main results were obtained using the above-mentioned range of isotope methods available to measure soil redistribution rates depending on the time scale needed (e.g., 239+240Pu, 10Be, 14C):
1. Short-term erosion rates are one order of magnitude higher than long-term rates in agricultural settings.
2. Both meteoric and in situ 10Be are suitable soil tracers to measure the long-term soil redistribution rates giving similar results in an anthropogenic environment for different landscape positions (e.g., hilltop, mid-slope, toeslope)
3. Short-term rates were extremely low/negligible in a natural landscape and very high in an agricultural landscape – -0.01 t ha-1 yr-1 (average value) and -25 t ha-1 yr-1 respectively. On the contrary, long-term rates in the forested landscape are comparable to those calculated in the agricultural area investigated with average values of -1.00 t ha-1 yr-1 and -0.79 t ha-1 yr-1.
4. Soil patterns observed in the forest might be due to human impact and activities started after the first settlements in the region, earlier than previously postulated, between 4.5 and 6.8 kyr BP, and not a result of recent soil erosion.
5. Furthermore, long-term soil redistribution rates are similar independently from the settings, meaning past natural soil mass redistribution processes still overshadow the present anthropogenic erosion processes.
Overall, this study could make important contributions to the deciphering of the co-evolution of weathering, soil profile development and lateral redistribution in North-eastern Germany. The multi-methodological approach used can be challenged by the application in a wider range of landscapes and geographic regions.
Modern datasets often exhibit diverse, feature-rich, unstructured data, and they are massive in size. This is the case of social networks, human genome, and e-commerce databases. As Artificial Intelligence (AI) systems are increasingly used to detect pattern in data and predict future outcome, there are growing concerns on their ability to process large amounts of data. Motivated by these concerns, we study the problem of designing AI systems that are scalable to very large and heterogeneous data-sets.
Many AI systems require to solve combinatorial optimization problems in their course of action. These optimization problems are typically NP-hard, and they may exhibit additional side constraints. However, the underlying objective functions often exhibit additional properties. These properties can be exploited to design suitable optimization algorithms. One of these properties is the well-studied notion of submodularity, which captures diminishing returns. Submodularity is often found in real-world applications. Furthermore, many relevant applications exhibit generalizations of this property.
In this thesis, we propose new scalable optimization algorithms for combinatorial problems with diminishing returns. Specifically, we focus on three problems, the Maximum Entropy Sampling problem, Video Summarization, and Feature Selection. For each problem, we propose new algorithms that work at scale. These algorithms are based on a variety of techniques, such as forward step-wise selection and adaptive sampling. Our proposed algorithms yield strong approximation guarantees, and the perform well experimentally.
We first study the Maximum Entropy Sampling problem. This problem consists of selecting a subset of random variables from a larger set, that maximize the entropy. By using diminishing return properties, we develop a simple forward step-wise selection optimization algorithm for this problem. Then, we study the problem of selecting a subset of frames, that represent a given video. Again, this problem corresponds to a submodular maximization problem. We provide a new adaptive sampling algorithm for this problem, suitable to handle the complex side constraints imposed by the application. We conclude by studying Feature Selection. In this case, the underlying objective functions generalize the notion of submodularity. We provide a new adaptive sequencing algorithm for this problem, based on the Orthogonal Matching Pursuit paradigm.
Overall, we study practically relevant combinatorial problems, and we propose new algorithms to solve them. We demonstrate that these algorithms are suitable to handle massive datasets. However, our analysis is not problem-specific, and our results can be applied to other domains, if diminishing return properties hold. We hope that the flexibility of our framework inspires further research into scalability in AI.
The global climate crisis is significantly contributing to changing ecosystems, loss of biodiversity and is putting numerous species on the verge of extinction. In principle, many species are able to adapt to changing conditions or shift their habitats to more suitable regions. However, change is progressing faster than some species can adjust, or potential adaptation is blocked and disrupted by direct and indirect human action. Unsustainable anthropogenic land use in particular is one of the driving factors, besides global heating, for these ecologically critical developments. Precisely because land use is anthropogenic, it is also a factor that could be quickly and immediately corrected by human action.
In this thesis, I therefore assess the impact of three climate change scenarios of increasing intensity in combination with differently scheduled mowing regimes on the long-term development and dispersal success of insects in Northwest German grasslands. The large marsh grasshopper (LMG, Stethophyma grossum, Linné 1758) is used as a species of reference for the analyses. It inhabits wet meadows and marshes and has a limited, yet fairly good ability to disperse. Mowing and climate conditions affect the development and mortality of the LMG differently depending on its life stage.
The specifically developed simulation model HiLEG (High-resolution Large Environmental
Gradient) serves as a tool for investigating and projecting viability and dispersal success under different climate conditions and land use scenarios. It is a spatially explicit, stage- and cohort-based model that can be individually configured to represent the life cycle and characteristics of terrestrial insect species, as well as high-resolution environmental data and the occurrence of external disturbances. HiLEG is a freely available and adjustable software that can be used to support conservation planning in cultivated grasslands.
In the three case studies of this thesis, I explore various aspects related to the structure of simulation models per se, their importance in conservation planning in general, and insights regarding the LMG in particular. It became apparent that the detailed resolution of model processes and components is crucial to project the long-term effect of spatially and temporally confined events. Taking into account conservation measures at the regional level has further proven relevant, especially in light of the climate crisis. I found that the LMG is benefiting from global warming in principle, but continues to be constrained by harmful mowing regimes. Land use measures could, however, be adapted in such a way that they allow the expansion and establishment of the LMG without overly affecting agricultural yields.
Overall, simulation models like HiLEG can make an important contribution and add value
to conservation planning and policy-making. Properly used, simulation results shed light
on aspects that might be overlooked by subjective judgment and the experience of individual stakeholders. Even though it is in the nature of models that they are subject to limitations and only represent fragments of reality, this should not keep stakeholders from using them, as long as these limitations are clearly communicated. Similar to HiLEG, models could further be designed in such a way that not only the parameterization can be adjusted as required, but also the implementation itself can be improved and changed as desired. This openness and flexibility should become more widespread in the development of simulation models.
Housing in metabolic cages can induce a pronounced stress response. Metabolic cage systems imply housing mice on metal wire mesh for the collection of urine and feces in addition to monitoring food and water intake. Moreover, mice are single-housed, and no nesting, bedding, or enrichment material is provided, which is often argued to have a not negligible impact on animal welfare due to cold stress. We therefore attempted to reduce stress during metabolic cage housing for mice by comparing an innovative metabolic cage (IMC) with a commercially available metabolic cage from Tecniplast GmbH (TMC) and a control cage. Substantial refinement measures were incorporated into the IMC cage design. In the frame of a multifactorial approach for severity assessment, parameters such as body weight, body composition, food intake, cage and body surface temperature (thermal imaging), mRNA expression of uncoupling protein 1 (Ucp1) in brown adipose tissue (BAT), fur score, and fecal corticosterone metabolites (CMs) were included. Female and male C57BL/6J mice were single-housed for 24 h in either conventional Macrolon cages (control), IMC, or TMC for two sessions. Body weight decreased less in the IMC (females—1st restraint: 6.94%; 2nd restraint: 6.89%; males—1st restraint: 8.08%; 2nd restraint: 5.82%) compared to the TMC (females—1st restraint: 13.2%; 2nd restraint: 15.0%; males—1st restraint: 13.1%; 2nd restraint: 14.9%) and the IMC possessed a higher cage temperature (females—1st restraint: 23.7°C; 2nd restraint: 23.5 °C; males—1st restraint: 23.3 °C; 2nd restraint: 23.5 °C) compared with the TMC (females—1st restraint: 22.4 °C; 2nd restraint: 22.5 °C; males—1st restraint: 22.6 °C; 2nd restraint: 22.4 °C). The concentration of fecal corticosterone metabolites in the TMC (females—1st restraint: 1376 ng/g dry weight (DW); 2nd restraint: 2098 ng/g DW; males—1st restraint: 1030 ng/g DW; 2nd restraint: 1163 ng/g DW) was higher compared to control cage housing (females—1st restraint:
640 ng/g DW; 2nd restraint: 941 ng/g DW; males—1st restraint: 504 ng/g DW; 2nd restraint: 537 ng/g DW). Our results show the stress potential induced by metabolic cage restraint that is markedly influenced by the lower housing temperature. The IMC represents a first attempt to target cold stress reduction during metabolic cage application thereby producing more animal welfare friendly data.
Answer Set Programming (ASP) allows us to address knowledge-intensive search and optimization problems in a declarative way due to its integrated modeling, grounding, and solving workflow. A problem is modeled using a rule based language and then grounded and solved. Solving results in a set of stable models that correspond to solutions of the modeled problem. In this thesis, we present the design and implementation of the clingo system---perhaps, the most
widely used ASP system. It features a rich modeling language originating from the field of knowledge representation and reasoning, efficient grounding algorithms based on database evaluation techniques, and high performance solving algorithms based on Boolean satisfiability (SAT) solving technology.
The contributions of this thesis lie in the design of the modeling language, the design and implementation of the grounding algorithms, and the design and implementation of an Application Programmable Interface (API) facilitating the use of ASP in real world applications and the implementation of complex forms of reasoning beyond the traditional ASP workflow.
The musculoskeletal system provides support and enables movement to the body, and its deterioration is a crucial aspect of age-related functional decline. Mesenchymal stromal cells (MSCs) play an important role in musculoskeletal homeostasis due to their broad differentiation potentials and their ability to support osteogenic and myogenic tissue maintenance and regeneration. In the bone, MSCs differentiate either into osteochondrogenic progenitors to form osteocytes and chondrocytes, or increasingly with age into adipogenic progenitors which give rise to bone-resident adipocytes. In skeletal muscle, during healthy regeneration MSCs provide regulatory signals that activate local, tissue-specific stem cells, known as satellite cells, which regenerate contractile myofibres. This process involves a significant cross-talk to immune cells stemming from both lymphoid and myeloid lineages. During ageing, muscle-resident MSCs undergo increased adipogenic lineage commitment, causing niche changes that contribute to fatty infiltration in muscles. These shifts in cell populations in bone lead to the loss of osteogenic cells and subsequently osteoporosis, or in muscle to impaired regeneration and to the development of sarcopenia. However, the signals that drive transition of MSCs into their respective cellular fates remain elusive.
This thesis aims to elucidate the transcriptional shifts modulating cell states and cell types in musculoskeletal MSC fate determination. Single-cell RNA-sequencing (scRNA-seq) was used to characterise cell type-specific transcript regulation. State-of-the-art bioinformatics tools were combined with different analytical platforms that include both droplet-based scRNA-seq for large heterogeneous populations, and microfluidics-based scRNA-seq to assess small, rare subpopulations. For each platform, distinct computational pipelines were established including filtering steps to exclude low-quality cells, and data visualisation was performed by dimensionality reduction. Downstream analysis included clustering, cell type annotation, and differential gene expression to investigate transcriptional states in defined cell types during ageing and injury in the muscle and bone. Finally, a novel tool to assess publication activities in defined areas of research for the identified marker genes was developed.
The results in the bone indicate that ageing MSCs increasingly commit towards an adipogenic fate at the expense of osteogenic specialisation. The data also suggests that significant cell population shifts of MSC-type fibro-adipogenic progenitors during muscle ageing underlie the pathologies observed in homeostatic and post-injury regenerative conditions. High-throughput visualisation of publication activity for candidate genes enabled more effective biological evaluation of scRNA-seq data. These results expose critical age-related changes in the stem cell niches of skeletal muscle and bone, highlight their respective sensitivity to nutrition and pathology, and elucidate novel factors that modulate stem cell-based regeneration. Targeting these processes might improve musculoskeletal health in the context of ageing and prevent the negative effects of pathological lineage determination.
Following the extinction of dinosaurs, the great adaptive radiation of mammals occurred, giving rise to an astonishing ecological and phenotypic diversity of mammalian species. Even closely related species often inhabit vastly different habitats, where they encounter diverse environmental challenges and are exposed to different evolutionary pressures. As a response, mammals evolved various adaptive phenotypes over time, such as morphological, physiological and behavioural ones. Mammalian genomes vary in their content and structure and this variation represents the molecular mechanism for the long-term evolution of phenotypic variation. However, understanding this molecular basis of adaptive phenotypic variation is usually not straightforward.
The recent development of sequencing technologies and bioinformatics tools has enabled a better insight into mammalian genomes. Through these advances, it was acknowledged that mammalian genomes differ more, both within and between species, as a consequence of structural variation compared to single-nucleotide differences. Structural variant types investigated in this thesis - such as deletion, duplication, inversion and insertion, represent a change in the structure of the genome, impacting the size, copy number, orientation and content of DNA sequences. Unlike short variants, structural variants can span multiple genes. They can alter gene dosage, and cause notable gene expression differences and subsequently phenotypic differences. Thus, they can lead to a more dramatic effect on the fitness (reproductive success) of individuals, local adaptation of populations and speciation.
In this thesis, I investigated and evaluated the potential functional effect of structural variations on the genomes of mustelid species. To detect the genomic regions associated with phenotypic variation I assembled the first reference genome of the tayra (Eira barbara) relying on linked-read sequencing technology to achieve a high level of genome completeness important for reliable structural variant discovery. I then set up a bioinformatics pipeline to conduct a comparative genomic analysis and explore variation between mustelid species living in different environments. I found numerous genes associated with species-specific phenotypes related to diet, body condition and reproduction among others, to be impacted by structural variants.
Furthermore, I investigated the effects of artificial selection on structural variants in mice selected for high fertility, increased body mass and high endurance. Through selective breeding of each mouse line, the desired phenotypes have spread within these populations, while maintaining structural variants specific to each line. In comparison to the control line, the litter size has doubled in the fertility lines, individuals in the high body mass lines have become considerably larger, and mice selected for treadmill performance covered substantially more distance. Structural variants were found in higher numbers in these trait-selected lines than in the control line when compared to the mouse reference genome. Moreover, we have found twice as many structural variants spanning protein-coding genes (specific to each line) in trait-selected lines. Several of these variants affect genes associated with selected phenotypic traits. These results imply that structural variation does indeed contribute to the evolution of the selected phenotypes and is heritable.
Finally, I suggest a set of critical metrics of genomic data that should be considered for a stringent structural variation analysis as comparative genomic studies strongly rely on the contiguity and completeness of genome assemblies. Because most of the available data used to represent reference genomes of mammalian species is generated using short-read sequencing technologies, we may have incomplete knowledge of genomic features. Therefore, a cautious structural variation analysis is required to minimize the effect of technical constraints.
The impact of structural variants on the adaptive evolution of mammalian genomes is slowly gaining more focus but it is still incorporated in only a small number of population studies. In my thesis, I advocate the inclusion of structural variants in studies of genomic diversity for a more comprehensive insight into genomic variation within and between species, and its effect on adaptive evolution.
Control over spin and electronic structure of MoS₂ monolayer via interactions with substrates
(2023)
The molybdenum disulfide (MoS2) monolayer is a semiconductor with a direct bandgap while it is a robust and affordable material.
It is a candidate for applications in optoelectronics and field-effect transistors.
MoS2 features a strong spin-orbit coupling which makes its spin structure promising for acquiring the Kane-Mele topological concept with corresponding applications in spintronics and valleytronics.
From the optical point of view, the MoS2 monolayer features two valleys in the regions of K and K' points. These valleys are differentiated by opposite spins and a related valley-selective circular dichroism.
In this study we aim to manipulate the MoS2 monolayer spin structure in the vicinity of the K and K' points to explore the possibility of getting control over the optical and electronic properties.
We focus on two different substrates to demonstrate two distinct routes: a gold substrate to introduce a Rashba effect and a graphene/cobalt substrate to introduce a magnetic proximity effect in MoS2.
The Rashba effect is proportional to the out-of-plane projection of the electric field gradient. Such a strong change of the electric field occurs at the surfaces of a high atomic number materials and effectively influence conduction electrons as an in-plane magnetic field. A molybdenum and a sulfur are relatively light atoms, thus, similar to many other 2D materials, intrinsic Rashba effect in MoS2 monolayer is vanishing small. However, proximity of a high atomic number substrate may enhance Rashba effect in a 2D material as it was demonstrated for graphene previously.
Another way to modify the spin structure is to apply an external magnetic field of high magnitude (several Tesla), and cause a Zeeman splitting, the conduction electrons.
However, a similar effect can be reached via magnetic proximity which allows us to reduce external magnetic fields significantly or even to zero. The graphene on cobalt interface is ferromagnetic and stable for MoS2 monolayer synthesis. Cobalt is not the strongest magnet; therefore, stronger magnets may lead to more significant results.
Nowadays most experimental studies on the dichalcogenides (MoS2 included) are performed on encapsulated heterostructures that are produced by mechanical exfoliation.
While mechanical exfoliation (or scotch-tape method) allows to produce a huge variety of structures, the shape and the size of the samples as well as distance between layers in heterostructures are impossible to control reproducibly.
In our study we used molecular beam epitaxy (MBE) methods to synthesise both MoS2/Au(111) and MoS2/graphene/Co systems.
We chose to use MBE, as it is a scalable and reproducible approach, so later industry may adapt it and take over.
We used graphene/cobalt instead of just a cobalt substrate because direct contact of MoS2\ monolayer and a metallic substrate may lead to photoluminescence (PL) quenching in the metallic substrate. Graphene and hexagonal boron nitride monolayer are considered building blocks of a new generation of electronics also commonly used as encapsulating materials for PL studies. Moreover graphene is proved to be a suitable substrate for the MBE growth of transitional metal dichalcogenides (TMDCs).
In chapter 1,
we start with an introduction to TMDCs. Then we focus on MoS2 monolayer state of the art research in the fields of application scenario; synthesis approaches; electronic, spin, and optical properties; and interactions with magnetic fields and magnetic materials.
We briefly touch the basics of magnetism in solids and move on to discuss various magnetic exchange interactions and magnetic proximity effect.
Then we describe MoS2 optical properties in more detail. We start from basic exciton physics and its manifestation in the MoS2 monolayer. We consider optical selection rules in the MoS2 monolayer and such properties as chirality, spin-valley locking, and coexistence of bright and dark excitons.
Chapter 2 contains an overview of the employed surface science methods: angle-integrated, angle-resolved, and spin-resolved photoemission; low energy electron diffraction and scanning tunneling microscopy.
In chapter 3, we describe MoS2 monolayer synthesis details for two substrates: gold monocrystal with (111) surface and graphene on cobalt thin film with Co(111) surface orientation.
The synthesis descriptions are followed by a detailed characterisation of the obtained structures: fingerprints of MoS2 monolayer formation; MoS2 monolayer symmetry and its relation to the substrate below; characterisation of MoS2 monolayer coverage, domain distribution, sizes and shapes, and moire structures.
In chapter~4, we start our discussion with MoS2/Au(111) electronic and spin structure. Combining density functional theory computations (DFT) and spin-resolved photoemission studies, we demonstrate that the MoS2 monolayer band structure features an in-plane Rashba spin splitting. This confirms the possibility of MoS2 monolayer spin structure manipulation via a substrate.
Then we investigate the influence of a magnetic proximity in the MoS2/graphene/Co system on the MoS2 monolayer spin structure.
We focus our investigation on MoS2 high symmetry points: G and K.
First, using spin-resolved measurements, we confirm that electronic states are spin-split at the G point via a magnetic proximity effect. Second, combining spin-resolved measurements and DFT computations for MoS2 monolayer in the K point region, we demonstrate the appearance of a small in-plane spin polarisation in the valence band top and predict a full in-plane spin polarisation for the conduction band bottom.
We move forward discussing how these findings are related to the MoS2 monolayer optical properties, in particular the possibility of dark exciton observation. Additionally, we speculate on the control of the MoS2 valley energy via magnetic proximity from cobalt.
As graphene is spatially buffering the MoS2 monolayer from the Co thin film, we speculate on the role of graphene in the magnetic proximity transfer by replacing graphene with vacuum and other 2D materials in our computations.
We finish our discussion by investigating the K-doped MoS2/graphene/Co system and the influence of this doping on the electronic and spin structure as well as on the magnetic proximity effect.
In summary, using a scalable MBE approach we synthesised
MoS2/Au(111) and MoS2/graphene/Co systems. We found a Rashba effect taking place in MoS2/Au(111) which proves that the MoS2 monolayer in-plane spin structure can be modified. In MoS2/graphene/Co the in-plane magnetic proximity effect indeed takes place which rises the possibility of fine tuning the MoS2 optical properties via manipulation of the the substrate magnetisation.
Creative intensive processes
(2023)
Creativity – developing something new and useful – is a constant challenge in the working world. Work processes, services, or products must be sensibly adapted to changing times. To be able to analyze and, if necessary, adapt creativity in work processes, a precise understanding of these creative activities is necessary. Process modeling techniques are often used to capture business processes, represent them graphically and analyze them for adaptation possibilities. This has been very limited for creative work. An accurate understanding of creative work is subject to the challenge that, on the one hand, it is usually very complex and iterative. On the other hand, it is at least partially unpredictable as new things emerge. How can the complexity of creative business processes be adequately addressed and simultaneously manageable? This dissertation attempts to answer this question by first developing a precise process understanding of creative work. In an interdisciplinary approach, the literature on the process description of creativity-intensive work is analyzed from the perspective of psychology, organizational studies, and business informatics. In addition, a digital ethnographic study in the context of software development is used to analyze creative work. A model is developed based on which four elementary process components can be analyzed: Intention of the creative activity, Creation to develop the new, Evaluation to assess its meaningfulness, and Planning of the activities arising in the process – in short, the ICEP model. These four process elements are then translated into the Knockledge Modeling Description Language (KMDL), which was developed to capture and represent knowledge-intensive business processes. The modeling extension based on the ICEP model enables creative business processes to be identified and specified without the need for extensive modeling of all process details. The modeling extension proposed here was developed using ethnographic data and then applied to other organizational process contexts. The modeling method was applied to other business contexts and evaluated by external parties as part of two expert studies. The developed ICEP model provides an analytical framework for complex creative work processes. It can be comprehensively integrated into process models by transforming it into a modeling method, thus expanding the understanding of existing creative work in as-is process analyses.
The collaboration-based professional development approach Lesson Study (LS), which has its roots in the Japanese education system, has gained international recognition over the past three decades and spread quickly throughout the world. LS is a collaborative method to professional development (PD) that incorporates multiple characteristics that have been identified in the research literature as key to effective PD. Specifically, LS is a long-term process that consists of subsequent inquiry cycles, it is site-based and integrated in teachers’ practice, it encourages collaboration and reflection, places a strong emphasis on student learning, and it typically involves external experts that support the process or offer additional insights.
As LS integrates all these characteristics, it has rapidly gained international popularity since the turn of the 21st century and is currently being practiced in over 40 countries around the world. This international borrowing of the idea of LS to new national contexts has given rise to a research field that aims to investigate the effectiveness of LS on teacher learning as well as the circumstances and mechanisms that make LS effective in various settings around the world. Such research is important, as borrowing educational innovations and adapting them to new contexts can be a challenging process. Educational innovations that fail to deliver the expected outcomes tend to be abandoned prematurely and before they have been completely understood or a substantial research base has been established.
In order to prevent LS from early abandonment, Lewis and colleagues outlined three critical research needs in 2006, not long after LS was initially introduced to the United States. These research needs included (1) developing a descriptive knowledge base on LS, (2) examining the mechanisms by which teachers learn through LS, and (3) using design-based research cycles to analyze and improve LS.
This dissertation set out to take stock of the progress that has been made on these research needs over the past 20 years. The scoping review conducted for the framework of this dissertation indicates that, while a large and international knowledge base has been developed, the field has not yet produced reliable evidence of the effectiveness of LS. Based on the scoping review, this dissertation makes the case that Lewis et al.’s (2006) critical research needs should be updated. In order to do so, a number of limitations to the current knowledge base on LS need to be addressed. These limitations include (1) the frequent lack of comparable and replicable descriptions of the LS intervention in publications, (2) the incoherent use or lack of use of theoretical frameworks to explain teacher learning through LS, (3) the inconsistent use of terminology and concepts, and (4) the lack of scientific rigor in research studies and of established ways or tools to measure the effectiveness of LS.
This dissertation aims to advance the critical research needs in the field by examining the extent and nature of these limitations in three research studies. The focus of these studies lies on the LS stages of observation and reflection, as these stages have a high potential to facilitate teacher learning. The first study uses a mixed-method design to examine how teachers at German primary schools reflect critically together. The study derives a theory-based definition of critical and collaborative reflection in order to re-frame the reflection element in LS.
The second study, a systematic review of 129 articles on LS, assess how transparent research articles are in reporting how teachers observed and reflected together. In addition, it is investigated whether these articles provide any kind of theorization for the stages of observation and reflection.
The third study proposes a conceptual model for the field of LS that is based on existing models of continuous professional development and research findings on team effectiveness and collaboration. The model describes the dimensions of input, mediating mechanisms, and outcomes in order to provide a conceptual grid to teachers’ continuous professional development through LS.
Visual perception is a complex and dynamic process that plays a crucial role in how we perceive and interact with the world. The eyes move in a sequence of saccades and fixations, actively modulating perception by moving different parts of the visual world into focus. Eye movement behavior can therefore offer rich insights into the underlying cognitive mechanisms and decision processes. Computational models in combination with a rigorous statistical framework are critical for advancing our understanding in this field, facilitating the testing of theory-driven predictions and accounting for observed data. In this thesis, I investigate eye movement behavior through the development of two mechanistic, generative, and theory-driven models. The first model is based on experimental research regarding the distribution of attention, particularly around the time of a saccade, and explains statistical characteristics of scan paths. The second model implements a self-avoiding random walk within a confining potential to represent the microscopic fixational drift, which is present even while the eye is at rest, and investigates the relationship to microsaccades. Both models are implemented in a likelihood-based framework, which supports the use of data assimilation methods to perform Bayesian parameter inference at the level of individual participants, analyses of the marginal posteriors of the interpretable parameters, model comparisons, and posterior predictive checks. The application of these methods enables a thorough investigation of individual variability in the space of parameters. Results show that dynamical modeling and the data assimilation framework are highly suitable for eye movement research and, more generally, for cognitive modeling.
The Andes reflect Cenozoic deformation and uplift along the South American margin in the context of regional shortening associated with the interaction between the subducting Nazca plate and the overriding continental South American plate. Simultaneously, multiple levels of uplifted marine terraces constitute laterally continuous geomorphic features related to the accumulation of permanent forearc deformation in the coastal realm. However, the mechanisms responsible for permanent coastal uplift and the persistency of current/decadal deformation patterns over millennial timescales are still not fully understood. This dissertation presents a continental-scale database of last interglacial terrace elevations and uplift rates along the South American coast that provides the basis for an analysis of a variety of mechanisms that are possibly responsible for the accumulation of permanent coastal uplift. Regional-scale mapping and analysis of multiple, late Pleistocene terrace levels in central Chile furthermore provide valuable insights regarding the persistency of current seismic asperities, the role of upper-plate faulting, and the impact of bathymetric ridges on permanent forearc deformation.
The database of last interglacial terrace elevations reveals an almost continuous signal of background-uplift rates along the South American coast at ~0.22 mm/yr that is modified by various short- to long-wavelength changes. Spatial correlations with crustal faults and subducted bathymetric ridges suggest long-term deformation to be affected by these features, while the latitudinal variability of climate forcing factors has a profound impact on the generation and preservation of marine terraces. Systematic wavelength analyses and comparisons of the terrace-uplift rate signal with different tectonic parameters reveal short-wavelength deformation to result from crustal faulting, while intermediate- to long-wavelength deformation might indicate various extents of long-term seismotectonic segments on the megathrust, which are at least partially controlled by the subduction of bathymetric anomalies. The observed signal of background-uplift rate is likely accumulated by moderate earthquakes near the Moho, suggesting multiple, spatiotemporally distinct phases of uplift that manifest as a continuous uplift signal over millennial timescales.
Various levels of late Pleistocene marine terraces in the 2015 M8.3 Illapel-earthquake area reveal a range of uplift rates between 0.1 and 0.6 mm/yr and indicate decreasing uplift rates since ~400 ka. These glacial-cycle uplift rates do not correlate with current or decadal estimates of coastal deformation suggesting seismic asperities not to be persistent features on the megathrust that control the accumulation of permanent forearc deformation over long timescales of 105 years. Trench-parallel, crustal normal faults modulate the characteristics of permanent forearc-deformation; upper-plate extension likely represents a second-order phenomenon resulting from subduction erosion and subsequent underplating that lead to regional tectonic uplift and local gravitational collapse of the forearc. In addition, variable activity with respect to the subduction of the Juan Fernández Ridge can be detected in the upper plate over the course of multiple interglacial periods, emphasizing the role of bathymetric anomalies in causing local increases in terrace-uplift rate. This thesis therefore provides new insights into the current understanding of subduction-zone processes and the dynamics of coastal forearc deformation, whose different interacting forcing factors impact the topographic and geomorphic evolution of the western South American coast.