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This dissertation examines the integration of incongruent visual-scene and morphological-case information (“cues”) in building thematic-role representations of spoken relative clauses in German.
Addressing the mutual influence of visual and linguistic processing, the Coordinated Interplay Account (CIA) describes a mechanism in two steps supporting visuo-linguistic integration (Knoeferle & Crocker, 2006, Cog Sci). However, the outcomes and dynamics of integrating incongruent thematic-role representations from distinct sources have been investigated scarcely. Further, there is evidence that both second-language (L2) and older speakers may rely on non-syntactic cues relatively more than first-language (L1)/young speakers. Yet, the role of visual information for thematic-role comprehension has not been measured in L2 speakers, and only limitedly across the adult lifespan.
Thematically unambiguous canonically ordered (subject-extracted) and noncanonically ordered (object-extracted) spoken relative clauses in German (see 1a-b) were presented in isolation and alongside visual scenes conveying either the same (congruent) or the opposite (incongruent) thematic relations as the sentence did.
1 a Das ist der Koch, der die Braut verfolgt.
This is the.NOM cook who.NOM the.ACC bride follows
This is the cook who is following the bride.
b Das ist der Koch, den die Braut verfolgt.
This is the.NOM cook whom.ACC the.NOM bride follows
This is the cook whom the bride is following.
The relative contribution of each cue to thematic-role representations was assessed with agent identification. Accuracy and latency data were collected post-sentence from a sample of L1 and L2 speakers (Zona & Felser, 2023), and from a sample of L1 speakers from across the adult lifespan (Zona & Reifegerste, under review). In addition, the moment-by-moment dynamics of thematic-role assignment were investigated with mouse tracking in a young L1 sample (Zona, under review).
The following questions were addressed: (1) How do visual scenes influence thematic-role representations of canonical and noncanonical sentences? (2) How does reliance on visual-scene, case, and word-order cues vary in L1 and L2 speakers? (3) How does reliance on visual-scene, case, and word-order cues change across the lifespan?
The results showed reliable effects of incongruence of visually and linguistically conveyed thematic relations on thematic-role representations. Incongruent (vs. congruent) scenes yielded slower and less accurate responses to agent-identification probes presented post-sentence. The recently inspected agent was considered as the most likely agent ~300ms after trial onset, and the convergence of visual scenes and word order enabled comprehenders to assign thematic roles predictively.
L2 (vs. L1) participants relied more on word order overall. In response to noncanonical clauses presented with incongruent visual scenes, sensitivity to case predicted the size of incongruence effects better than L1-L2 grouping. These results suggest that the individual’s ability to exploit specific cues might predict their weighting.
Sensitivity to case was stable throughout the lifespan, while visual effects increased with increasing age and were modulated by individual interference-inhibition levels. Thus, age-related changes in comprehension may stem from stronger reliance on visually (vs. linguistically) conveyed meaning.
These patterns represent evidence for a recent-role preference – i.e., a tendency to re-assign visually conveyed thematic roles to the same referents in temporally coordinated utterances. The findings (i) extend the generalizability of CIA predictions across stimuli, tasks, populations, and measures of interest, (ii) contribute to specifying the outcomes and mechanisms of detecting and indexing incongruent representations within the CIA, and (iii) speak to current efforts to understand the sources of variability in sentence comprehension.
Concepts and techniques for 3D-embedded treemaps and their application to software visualization
(2024)
This thesis addresses concepts and techniques for interactive visualization of hierarchical data using treemaps. It explores (1) how treemaps can be embedded in 3D space to improve their information content and expressiveness, (2) how the readability of treemaps can be improved using level-of-detail and degree-of-interest techniques, and (3) how to design and implement a software framework for the real-time web-based rendering of treemaps embedded in 3D. With a particular emphasis on their application, use cases from software analytics are taken to test and evaluate the presented concepts and techniques.
Concerning the first challenge, this thesis shows that a 3D attribute space offers enhanced possibilities for the visual mapping of data compared to classical 2D treemaps. In particular, embedding in 3D allows for improved implementation of visual variables (e.g., by sketchiness and color weaving), provision of new visual variables (e.g., by physically based materials and in situ templates), and integration of visual metaphors (e.g., by reference surfaces and renderings of natural phenomena) into the three-dimensional representation of treemaps.
For the second challenge—the readability of an information visualization—the work shows that the generally higher visual clutter and increased cognitive load typically associated with three-dimensional information representations can be kept low in treemap-based representations of both small and large hierarchical datasets. By introducing an adaptive level-of-detail technique, we cannot only declutter the visualization results, thereby reducing cognitive load and mitigating occlusion problems, but also summarize and highlight relevant data. Furthermore, this approach facilitates automatic labeling, supports the emphasis on data outliers, and allows visual variables to be adjusted via degree-of-interest measures.
The third challenge is addressed by developing a real-time rendering framework with WebGL and accumulative multi-frame rendering. The framework removes hardware constraints and graphics API requirements, reduces interaction response times, and simplifies high-quality rendering. At the same time, the implementation effort for a web-based deployment of treemaps is kept reasonable.
The presented visualization concepts and techniques are applied and evaluated for use cases in software analysis. In this domain, data about software systems, especially about the state and evolution of the source code, does not have a descriptive appearance or natural geometric mapping, making information visualization a key technology here. In particular, software source code can be visualized with treemap-based approaches because of its inherently hierarchical structure. With treemaps embedded in 3D, we can create interactive software maps that visually map, software metrics, software developer activities, or information about the evolution of software systems alongside their hierarchical module structure.
Discussions on remaining challenges and opportunities for future research for 3D-embedded treemaps and their applications conclude the thesis.
With the many challenges facing the agricultural system, such as water scarcity, loss of arable land due to climate change, population growth, urbanization or trade disruptions, new agri-food systems are needed to ensure food security in the future. In addition, healthy diets are needed to combat non-communicable diseases. Therefore, plant-based diets rich in health-promoting plant secondary metabolites are desirable. A saline indoor farming system is representing a sustainable and resilient new agrifood system and can preserve valuable fresh water. Since indoor farming relies on artificial lighting, assessment of lighting conditions is essential. In this thesis, the cultivation of halophytes in a saline indoor farming system was evaluated and the influence of cultivation conditions were assessed in favor of improving the nutritional quality of halophytes for human consumption. Therefore, five selected edible halophyte species (Brassica oleracea var. palmifolia, Cochlearia officinalis, Atriplex hortensis, Chenopodium quinoa, and Salicornia europaea) were cultivated in saline indoor farming. The halophyte species were selected for to their salt tolerance levels and mechanisms. First, the suitability of halophytes for saline indoor farming and the influence of salinity on their nutritional properties, e.g. plant secondary metabolites and minerals, were investigated. Changes in plant performance and nutritional properties were observed as a function of salinity. The response to salinity was found to be species-specific and related to the salt tolerance mechanism of the halophytes. At their optimal salinity levels, the halophytes showed improved carotenoid content. In addition, a negative correlation was found between the nitrate and chloride content of halophytes as a function of salinity. Since chloride and nitrate can be antinutrient compounds, depending on their content, monitoring is essential, especially in halophytes. Second, regional brine water was introduced as an alternative saline water resource in the saline indoor farming system. Brine water was shown to be feasible for saline indoor farming
of halophytes, as there was no adverse effect on growth or nutritional properties, e.g. carotenoids. Carotenoids were shown to be less affected by salt composition than by salt concentration. In addition, the interaction between the salinity and the light regime in indoor farming and greenhouse cultivation has been studied. There it was shown that interacting light regime and salinity alters the content of carotenoids and chlorophylls. Further, glucosinolate and nitrate content were also shown to be influenced by light regime. Finally, the influence of UVB light on halophytes was investigated using supplemental narrow-band UVB LEDs. It was shown that UVB light affects the growth, phenotype and metabolite profile of halophytes and that the UVB response is species specific. Furthermore, a modulation of carotenoid content in S. europaea could be achieved to enhance health-promoting properties and thus improve nutritional quality. This was shown to be dose-dependent and the underlying mechanisms of carotenoid accumulation were also investigated. Here it was revealed that carotenoid accumulation is related to oxidative stress.
In conclusion, this work demonstrated the potential of halophytes as alternative vegetables produced in a saline indoor farming system for future diets that could contribute to ensuring food security in the future. To improve the sustainability of the saline indoor farming system, LED lamps and regional brine water could be integrated into the system. Since the nutritional properties have been shown to be influenced by salt, light regime and UVB light, these abiotic stressors must be taken into account when considering halophytes as alternative vegetables for human nutrition.
Cross-sectional associations of dietary biomarker patterns with health and nutritional status
(2024)
The African weakly electric fishes (Mormyridae) exhibit a remarkable adaptive radiation possibly due to their species-specific electric organ discharges (EODs). It is produced by a muscle-derived electric organ that is located in the caudal peduncle. Divergence in EODs acts as a pre-zygotic isolation mechanism to drive species radiations. However, the mechanism behind the EOD diversification are only partially understood.
The aim of this study is to explore the genetic basis of EOD diversification from the gene expression level across Campylomormyrus species/hybrids and ontogeny. I firstly produced a high quality genome of the species C. compressirostris as a valuable resource to understand the electric fish evolution.
The next study compared the gene expression pattern between electric organs and skeletal muscles in Campylomormyrus species/hybrids with different types of EOD duration. I identified several candidate genes with an electric organ-specific expression, e.g. KCNA7a, KLF5, KCNJ2, SCN4aa, NDRG3, MEF2. The overall genes expression pattern exhibited a significant association with EOD duration in all analyzed species/hybrids. The expression of several candidate genes, e.g. KCNJ2, KLF5, KCNK6 and KCNQ5, possibly contribute to the regulation of EOD duration in Campylomormyrus due to their increasing or decreasing expression. Several potassium channel genes showed differential expression during ontogeny in species and hybrid with EOD alteration, e.g. KCNJ2.
I next explored allele specific expression of intragenus hybrids by crossing the duration EOD species C. compressirostris with the medium duration EOD species C. tshokwe and the elongated duration EOD species C. rhynchophorus. The hybrids exhibited global expression dominance of the C. compressirostris allele in the adult skeletal muscle and electric organ, as well as in the juvenile electric organ. Only the gene KCNJ2 showed dominant expression of the allele from C. rhynchophorus, and this was increasingly dominant during ontogeny. It hence supported our hypothesis that KCNJ2 is a key gene of regulating EOD duration. Our results help us to understand, from a genetic perspective, how gene expression effect the EOD diversification in the African weakly electric fish.
Protected cultivation in greenhouses or polytunnels offers the potential for sustainable production of high-yield, high-quality vegetables. This is related to the ability to produce more on less land and to use resources responsibly and efficiently. Crop yield has long been considered the most important factor. However, as plant-based diets have been proposed for a sustainable food system, the targeted enrichment of health-promoting plant secondary metabolites should be addressed. These metabolites include carotenoids and flavonoids, which are associated with several health benefits, such as cardiovascular health and cancer protection.
Cover materials generally have an influence on the climatic conditions, which in turn can affect the levels of secondary metabolites in vegetables grown underneath. Plastic materials are cost-effective and their properties can be modified by incorporating additives, making them the first choice. However, these additives can migrate and leach from the material, resulting in reduced service life, increased waste and possible environmental release. Antifogging additives are used in agricultural films to prevent the formation of droplets on the film surface, thereby increasing light transmission and preventing microbiological contamination.
This thesis focuses on LDPE/EVA covers and incorporated antifogging additives for sustainable protected cultivation, following two different approaches. The first addressed the direct effects of leached antifogging additives using simulation studies on lettuce leaves (Lactuca sativa var capitata L). The second determined the effect of antifog polytunnel covers on lettuce quality. Lettuce is usually grown under protective cover and can provide high nutritional value due to its carotenoid and flavonoid content, depending on the cultivar.
To study the influence of simulated leached antifogging additives on lettuce leaves, a GC-MS method was first developed to analyze these additives based on their fatty acid moieties. Three structurally different antifogging additives (reference material) were characterized outside of a polymer matrix for the first time. All of them contained more than the main fatty acid specified by the manufacturer. Furthermore, they were found to adhere to the leaf surface and could not be removed by water or partially by hexane.
The incorporation of these additives into polytunnel covers affects carotenoid levels in lettuce, but not flavonoids, caffeic acid derivatives and chlorophylls. Specifically, carotenoids were higher in lettuce grown under polytunnels without antifog than with antifog. This has been linked to their effect on the light regime and was suggested to be related to carotenoid function in photosynthesis.
In terms of protected cultivation, the use of LDPE/EVA polytunnels affected light and temperature, and both are closely related. The carotenoid and flavonoid contents of lettuce grown under polytunnels was reversed, with higher carotenoid and lower flavonoid levels. At the individual level, the flavonoids detected in lettuce did not differ however, lettuce carotenoids adapted specifically depending on the time of cultivation. Flavonoid reduction was shown to be transcriptionally regulated (CHS) in response to UV light (UVR8). In contrast, carotenoids are thought to be regulated post-transcriptionally, as indicated by the lack of correlation between carotenoid levels and transcripts of the first enzyme in carotenoid biosynthesis (PSY) and a carotenoid degrading enzyme (CCD4), as well as the increased carotenoid metabolic flux. Understanding the regulatory mechanisms and metabolite adaptation strategies could further advance the strategic development and selection of cover materials.
Relativistic pair beams produced in the cosmic voids by TeV gamma rays from blazars are expected to produce a detectable GeV-scale cascade emission missing in the observations. The suppression of this secondary cascade implies either the deflection of the pair beam by intergalactic magnetic fields (IGMFs) or an energy loss of the beam due to the electrostatic beam-plasma instability. IGMF of femto-Gauss strength is sufficient to significantly deflect the pair beams reducing the flux of secondary cascade below the observational limits. A similar flux reduction may result in the absence of the IGMF from the beam energy loss by the instability before the inverse Compton cooling. This dissertation consists of two studies about the instability role in the evolution of blazar-induced beams.
Firstly, we investigated the effect of sub-fG level IGMF on the beam energy loss by the instability. Considering IGMF with correlation lengths smaller than a few kpc, we found that such fields increase the transverse momentum of the pair beam particles, dramatically reducing the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. Our results show that the IGMF eliminates beam plasma instability as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission and hence can be excluded.
Secondly, we probed how the beam-plasma instability feeds back on the beam, using a realistic two-dimensional beam distribution. We found that the instability broadens the beam opening angles significantly without any significant energy loss, thus confirming a recent feedback study on a simplified one-dimensional beam distribution. However, narrowing diffusion feedback of the beam particles with Lorentz factors less than 1e6 might become relevant even though initially it is negligible. Finally, when considering the continuous creation of TeV pairs, we found that the beam distribution and the wave spectrum reach a new quasi-steady state, in which the scattering of beam particles persists and the beam opening angle may increase by a factor of hundreds. This new intrinsic scattering of the cascade can result in time delays of around ten years, thus potentially mimicking the IGMF deflection. Understanding the implications on the GeV cascade emission requires accounting for inverse Compton cooling and simulating the beam-plasma system at different points in the IGM.
The present dissertation investigates changes in lingual coarticulation across childhood in German-speaking children from three to nine years of age and adults. Coarticulation refers to the mismatch between the abstract phonological units and their seemingly commingled realization in continuous speech. Being a process at the intersection of phonology and phonetics, addressing its changes across childhood allows for insights in speech motor as well as phonological developments. Because specific predictions for changes in coarticulation across childhood can be derived from existing speech production models, investigating children’s coarticulatory patterns can help us model human speech production.
While coarticulatory changes may shed light on some of the central questions of speech production development, previous studies on the topic were sparse and presented a puzzling picture of conflicting findings. One of the reasons for this lack is the difficulty in articulatory data acquisition in a young population. Within the research program this dissertation is embedded in, we accepted this challenge and successfully set up the hitherto largest corpus of articulatory data from children using ultrasound tongue imaging. In contrast to earlier studies, a high number of participants in tight age cohorts across a wide age range and a thoroughly controlled set of pseudowords allowed for statistically powerful investigations of a process known as variable and complicated to track.
The specific focus of my studies is on lingual vocalic coarticulation as measured in the horizontal position of the highest point of the tongue dorsum. Based on three studies on a) anticipatory coarticulation towards the left, b) carryover coarticulation towards the right side of the utterance, and c) anticipatory coarticulatory extent in repeated versus read aloud speech, I deduct the following main theses:
1. Maturing speech motor control is responsible for some developmental changes in coarticulation.
2. Coarticulation can be modeled as the coproduction of articulatory gestures.
3. The developmental change in coarticulation results from a decrease of vocalic activation width.
Èto-clefts are Russian focus constructions with the demonstrative pronoun èto ‘this’ at the beginning: “Èto Mark vyigral gonku” (“It was Mark who won the race”). They are often being compared with English it-clefts, German es-clefts, as well as the corresponding focus-background structures in other languages.
In terms of semantics, èto-clefts have two important properties which are cross-linguistically typical for clefts: existence presupposition (“Someone won the race”) and exhaustivity (“Nobody except Mark won the race”). However, the exhaustivity effects are not as strong as exhaustivity effects in structures with the exclusive only and require more research.
At the same time, the question if the syntactic structure of èto-clefts matches the biclausal structure of English and German clefts, remains open. There are arguments in favor of biclausality, as well as monoclausality. Besides, there is no consistency regarding the status of èto itself.
Finally, the information structure of èto-clefts has remained underexplored in the existing literature.
This research investigates the information-structural, syntactic, and semantic properties of Russian clefts, both theoretically (supported by examples from Russian text corpora and judgments from native speakers) and experimentally. It is determined which desired changes in the information structure motivate native speakers to choose an èto-cleft and not the canonical structure or other focus realization tools. Novel syntactic tests are conducted to find evidence for bi-/monoclausality of èto-clefts, as well as for base-generation or movement of the cleft pivot. It is hypothesized that èto has a certain important function in clefts, and its status is investigated. Finally, new experiments on the nature of exhaustivity in èto-clefts are conducted. They allow for direct cross-linguistic comparison, using an incremental-information paradigm with truth-value judgments.
In terms of information structure, this research makes a new proposal that presents èto-clefts as structures with an inherent focus-background bipartitioning. Even though èto-clefts are used in typical focus contexts, evidence was found that èto-clefts (as well as Russian thetic clefts) allow for both new information focus and contrastive focus. Èto-clefts are pragmatically acceptable when a singleton answer to the implied question is expected (e.g. “It was Mark who won the race” but not “It was Mark who came to the party”). Importantly, èto in Russian clefts is neither dummy, nor redundant, but is a topic expression; conveys familiarity which triggers existence presupposition; refers to an instantiated event, or a known/perceivable situation; finally, èto plays an important role in the spoken language as a tool for speech coherency and a focus marker.
In terms of syntax, this research makes a new monoclausal proposal and shows evidence that the cleft pivot undergoes movement to the left peripheral position. Èto is proposed to be TopP.
Finally, in terms of semantics, a novel cross-linguistic evaluation of Russian clefts is made. Experiments show that the exhaustivity inference in èto-clefts is not robust. Participants used different strategies in resolving exhaustivity, falling into 2 groups: one group considered èto-clefts exhaustive, while another group considered them non-exhaustive. Hence, there is evidence for the pragmatic nature of exhaustivity in èto-clefts. The experimental results for èto-clefts are similar to the experimental results for clefts in German, French and Akan. It is concluded that speakers use different tools available in their languages to produce structures with similar interpretive properties.
Development of a CRISPR/Cas gene editing technique for the coccolithophore Chrysotila carterae
(2024)
Optimizing power analysis for randomized experiments: Design parameters for student achievement
(2024)
Randomized trials (RTs) are promising methodological tools to inform evidence-based reform to enhance schooling. Establishing a robust knowledge base on how to promote student achievement requires sensitive RT designs demonstrating sufficient statistical power and precision to draw conclusive and correct inferences on the effectiveness of educational programs and innovations. Proper power analysis is therefore an integral component of any informative RT on student achievement. This venture critically hinges on the availability of reasonable input variance design parameters (and their inherent uncertainties) that optimally reflect the realities around the prospective RT—precisely, its target population and outcome, possibly applied covariates, the concrete design as well as the planned analysis. However, existing compilations in this vein show far-reaching shortcomings.
The overarching endeavor of the present doctoral thesis was to substantively expand available resources devoted to tweak the planning of RTs evaluating educational interventions. At the core of this thesis is a systematic analysis of design parameters for student achievement, generating reliable and versatile compendia and developing thorough guidance to support apt power analysis to design strong RTs. To this end, the thesis at hand bundles two complementary studies which capitalize on rich data of several national probability samples from major German longitudinal large-scale assessments.
Study I applied two- and three-level latent (covariate) modeling to analyze design parameters for a wide spectrum of mathematical-scientific, verbal, and domain-general achievement outcomes. Three vital covariate sets were covered comprising (a) pretests, (b) sociodemographic characteristics, and (c) their combination. The accumulated estimates were additionally summarized in terms of normative distributions.
Study II specified (manifest) single-, two-, and three-level models and referred to influential psychometric heuristics to analyze design parameters and develop concise selection guidelines for covariate (a) types of varying bandwidth-fidelity (domain-identical, cross-domain, fluid intelligence pretests; sociodemographic characteristics), (b) combinations quantifying incremental validities, and (c) time lags of 1- to 7-year-lagged pretests scrutinizing validity degradation. The estimates for various mathematical-scientific and verbal achievement outcomes were meta-analytically integrated and employed in precision simulations.
In doing so, Studies I and II addressed essential gaps identified in previous repertoires in six major dimensions: Taken together, this thesis accumulated novel design parameters and deliberate guidance for RT power analysis (1) tailored to four German student (sub)populations across the entire school career from Grade 1 to 12, (2) matched to 21 achievement (sub)domains, (3) adjusted for 11 covariate sets enriched by empirically supported guidelines, (4) adapted to six RT designs, (5) suitable for latent and manifest analysis models, (6) which were cataloged along with quantifications of their associated uncertainties. These resources are complemented by a plethora of illustrative application examples to gently direct psychological and educational researchers through pivotal steps in the process of RT design.
The striking heterogeneity of the design parameter estimates across all these dimensions constitutes the overall, joint key result of Studies I and II. Hence, this work convincingly reinforces calls for a close match between design parameters and the specific peculiarities of the target RT’s research context.
All in all, the present doctoral thesis offers a—so far unique—nuanced and extensive toolkit to optimize power analysis for sound RTs on student achievement in the German (and similar) school context. It is of utmost importance that research does not tire to spawn robust evidence on what actually works to improve schooling. With this in mind, I hope that the emerging compendia and guidance contribute to the quality and rigor of our randomized experiments in psychology and education.
It is a common finding that preschoolers have difficulties in identifying who is doing what to whom in non-canonical sentences, such as (object-verb-subject) OVS and passive sentences in German. This dissertation investigates how German monolingual and German-Italian simultaneous bilingual children process German OVS sentences in Study 1 and German passives in Study 2. Offline data (i.e., accuracy data) and online data (i.e., eye-gaze and pupillometry data) were analyzed to explore whether children can assign thematic roles during sentence comprehension and processing. Executive functions, language-internal and -external factors were investigated as potential predictors for children’s sentence comprehension and processing.
Throughout the literature, there are contradicting findings on the relation between language and executive functions. While some results show a bilingual cognitive advantage over monolingual speakers, others suggest there is no relationship between bilingualism and executive functions. If bilingual children possess more advanced executive function abilities than monolingual children, then this might also be reflected in a better performance on linguistic tasks. In the current studies monolingual and bilingual children were tested by means of two executive function tasks: the Flanker task and the task-switching paradigm. However, these findings showed no bilingual cognitive advantages and no better performance by bilingual children in the linguistic tasks. The performance was rather comparable between bilingual and monolingual children, or even better for the monolingual group. This may be due to cross-linguistic influences and language experience (i.e., language input and output). Italian was used because it does not syntactically overlap with the structure of German OVS sentences, and it only overlapped with one of the two types of sentence condition used for the passive study - considering the subject-(finite)verb alignment. The findings showed a better performance of bilingual children in the passive sentence structure that syntactically overlapped in the two languages, providing evidence for cross-linguistic influences.
Further factors for children’s sentence comprehension were considered. The parents’ education, the number of older siblings and language experience variables were derived from a language background questionnaire completed by parents. Scores of receptive vocabulary and grammar, visual and short-term memory and reasoning ability were measured by means of standardized tests. It was shown that higher German language experience by bilinguals correlates with better accuracy in German OVS sentences but not in passive sentences. Memory capacity had a positive effect on the comprehension of OVS and passive sentences in the bilingual group. Additionally, a role was played by executive function abilities in the comprehension of OVS sentences and not of passive sentences. It is suggested that executive function abilities might help children in the sentence comprehension task when the linguistic structures are not yet fully mastered.
Altogether, these findings show that bilinguals’ poorer performance in the comprehension and processing of German OVS is mainly due to reduced language experience in German, and that the different performance of bilingual children with the two types of passives is mainly due to cross-linguistic influences.
Actin is one of the most highly conserved proteins in eukaryotes and distinct actin-related proteins with filament-forming properties are even found in prokaryotes. Due to these commonalities, actin-modulating proteins of many species share similar structural properties and proposed functions. The polymerization and depolymerization of actin are critical processes for a cell as they can contribute to shape changes to adapt to its environment and to move and distribute nutrients and cellular components within the cell. However, to what extent functions of actin-binding proteins are conserved between distantly related species, has only been addressed in a few cases. In this work, functions of Coronin-A (CorA) and Actin-interacting protein 1 (Aip1), two proteins involved in actin dynamics, were characterized. In addition, the interchangeability and function of Aip1 were investigated in two phylogenetically distant model organisms. The flowering plant Arabidopsis thaliana (encoding two homologs, AIP1-1 and AIP1-2) and in the amoeba Dictyostelium discoideum (encoding one homolog, DdAip1) were chosen because the functions of their actin cytoskeletons may differ in many aspects. Functional analyses between species were conducted for AIP1 homologs as flowering plants do not harbor a CorA gene.
In the first part of the study, the effect of four different mutation methods on the function of Coronin-A protein and the resulting phenotype in D. discoideum was revealed in two genetic knockouts, one RNAi knockdown and a sudden loss-of-function mutant created by chemical-induced dislocation (CID). The advantages and disadvantages of the different mutation methods on the motility, appearance and development of the amoebae were investigated, and the results showed that not all observed properties were affected with the same intensity. Remarkably, a new combination of Selection-Linked Integration and CID could be established.
In the second and third parts of the thesis, the exchange of Aip1 between plant and amoeba was carried out. For A. thaliana, the two homologs (AIP1-1 and AIP1-2) were analyzed for functionality as well as in D. discoideum. In the Aip1-deficient amoeba, rescue with AIP1-1 was more effective than with AIP1-2. The main results in the plant showed that in the aip1-2 mutant background, reintroduced AIP1-2 displayed the most efficient rescue and A. thaliana AIP1-1 rescued better than DdAip1. The choice of the tagging site was important for the function of Aip1 as steric hindrance is a problem. The DdAip1 was less effective when tagged at the C-terminus, while the plant AIP1s showed mixed results depending on the tag position. In conclusion, the foreign proteins partially rescued phenotypes of mutant plants and mutant amoebae, despite the organisms only being very distantly related in evolutionary terms.
The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data.
The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient.
The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.
This study focuses on William Faulkner, whose works explore the demise of the slavery-based Old South during the Civil War in a highly experimental narrative style. Central to this investigation is the analysis of the temporal dimensions of both individual and collective guilt, thus offering a new approach to the often-discussed problem of Faulkner’s portrayal of social decay. The thesis examines how Faulkner re-narrates the legacy of the Old South as a guilt narrative and argues that Faulkner uses guilt in order to corroborate his concept of time and the idea of the continuity of the past. The focus of the analysis is on three of Faulkner’s arguably most important novels: The Sound and the Fury, Absalom, Absalom!, and Go Down, Moses. Each of these novels features a main character deeply overwhelmed by the crimes of the past, whether private, familial, or societal. As a result, guilt is explored both from a domestic as well as a social perspective. In order to show how Faulkner blends past and present by means of guilt, this work examines several methods and motifs borrowed from different fields and genres with which Faulkner narratively negotiates guilt. These include religious notions of original sin, the motif of the ancestral curse prevalent in the Southern Gothic genre, and the psychological concept of trauma. Each of these motifs emphasizes the temporal dimensions of guilt, which are the core of this study, and makes clear that guilt in Faulkner’s work is primarily to be understood as a temporal rather than a moral problem.
Assessing the impact of global change on hydrological systems is one of the greatest hydrological challenges of our time. Changes in land cover, land use, and climate have an impact on water quantity, quality, and temporal availability. There is a widespread consensus that, given the far-reaching effects of global change, hydrological systems can no longer be viewed as static in their structure; instead, they must be regarded as entire ecosystems, wherein hydrological processes interact and coevolve with biological, geomorphological, and pedological processes. To accurately predict the hydrological response under the impact of global change, it is essential to understand this complex coevolution. The knowledge of how hydrological processes, in particular the formation of subsurface (preferential) flow paths, evolve within this coevolution and how they feed back to the other processes is still very limited due to a lack of observational data.
At the hillslope scale, this intertwined system of interactions is known as the hillslope feedback cycle. This thesis aims to enhance our understanding of the hillslope feedback cycle by studying the coevolution of hillslope structure and hillslope hydrological response. Using chronosequences of moraines in two glacial forefields developed from siliceous and calcareous glacial till, the four studies shed light on the complex coevolution of hydrological, biological, and structural hillslope properties, as well as subsurface hydrological flow paths over an evolutionary period of 10 millennia in these two contrasting geologies. The findings indicate that the contrasting properties of siliceous and calcareous parent materials lead
to variations in soil structure, permeability, and water storage. As a result, different plant species and vegetation types are favored on siliceous versus calcareous parent material, leading to diverse ecosystems with distinct hydrological dynamics. The siliceous parent material was found to show a higher activity level in driving the coevolution. The soil pH resulting from parent material weathering emerges as a crucial factor, influencing vegetation development, soil formation, and consequently, hydrology. The acidic weathering of the siliceous parent material favored the accumulation of organic matter, increasing the soils’ water storage capacity and attracting acid-loving shrubs, which further promoted organic matter accumulation and ultimately led to podsolization after 10 000 years. Tracer experiments revealed that the subsurface flow path evolution was influenced by soil and vegetation development, and vice versa. Subsurface flow paths changed from vertical, heterogeneous matrix flow to finger-like flow paths over a few hundred years, evolving into macropore flow, water storage, and lateral subsurface flow after several thousand years. The changes in flow paths among younger age classes were driven by weathering processes altering soil structure, as well as by vegetation development and root activity. In the older age
class, the transition to more water storage and lateral flow was attributed to substantial organic matter accumulation and ongoing podsolization. The rapid vertical water transport in the finger-like flow paths, along with the conductive sandy material, contributed to podsolization and thus to the shift in the hillslope hydrological response.
In contrast, the calcareous site possesses a high pH buffering capacity, creating a neutral to basic environment with relatively low accumulation of dead organic matter, resulting in a lower water storage capacity and the establishment of predominantly grass vegetation. The coevolution was found to be less dynamic over the millennia. Similar to the siliceous site, significant changes in subsurface flow paths occurred between the young age classes. However, unlike the siliceous site, the subsurface flow paths at the calcareous site only altered in shape and not in direction. Tracer experiments showed that flow paths changed from vertical, heterogeneous matrix flow to vertical, finger-like flow paths after a few hundred to thousands of years, which was driven by root activities and weathering processes. Despite having a finer soil texture, water storage at the calcareous site was significantly lower than at the siliceous site, and water transport remained primarily rapid and vertical, contributing to the flourishing of grass vegetation.
The studies elucidated that changes in flow paths are predominantly shaped by the characteristics of the parent material and its weathering products, along with their complex interactions with initial water flow paths and vegetation development. Time, on the other hand, was not found to be a primary factor in describing the evolution of the hydrological response. This thesis makes a valuable contribution to closing the gap in the observations of the coevolution of hydrological processes within the hillslope feedback cycle, which is important to improve predictions of hydrological processes in changing landscapes. Furthermore, it emphasizes the importance of interdisciplinary studies in addressing the hydrological challenges arising from global change.
The increasing number of known exoplanets raises questions about their demographics and the mechanisms that shape planets into how we observe them today. Young planets in close-in orbits are exposed to harsh environments due to the host star being magnetically highly active, which results in high X-ray and extreme UV fluxes impinging on the planet. Prolonged exposure to this intense photoionizing radiation can cause planetary atmospheres to heat up, expand and escape into space via a hydrodynamic escape process known as photoevaporation. For super-Earth and sub-Neptune-type planets, this can even lead to the complete erosion of their primordial gaseous atmospheres. A factor of interest for this particular mass-loss process is the activity evolution of the host star. Stellar rotation, which drives the dynamo and with it the magnetic activity of a star, changes significantly over the stellar lifetime. This strongly affects the amount of high-energy radiation received by a planet as stars age. At a young age, planets still host warm and extended envelopes, making them particularly susceptible to atmospheric evaporation. Especially in the first gigayear, when X-ray and UV levels can be 100 - 10,000 times higher than for the present-day sun, the characteristics of the host star and the detailed evolution of its high-energy emission are of importance.
In this thesis, I study the impact of stellar activity evolution on the high-energy-induced atmospheric mass loss of young exoplanets. The PLATYPOS code was developed as part of this thesis to calculate photoevaporative mass-loss rates over time. The code, which couples parameterized planetary mass-radius relations with an analytical hydrodynamic escape model, was used, together with Chandra and eROSITA X-ray observations, to investigate the future mass loss of the two young multiplanet systems V1298 Tau and K2-198. Further, in a numerical ensemble study, the effect of a realistic spread of activity tracks on the small-planet radius gap was investigated for the first time. The works in this thesis show that for individual systems, in particular if planetary masses are unconstrained, the difference between a young host star following a low-activity track vs. a high-activity one can have major implications: the exact shape of the activity evolution can determine whether a planet can hold on to some of its atmosphere, or completely loses its envelope, leaving only the bare rocky core behind. For an ensemble of simulated planets, an observationally-motivated distribution of activity tracks does not substantially change the final radius distribution at ages of several gigayears. My simulations indicate that the overall shape and slope of the resulting small-planet radius gap is not significantly affected by the spread in stellar activity tracks. However, it can account for a certain scattering or fuzziness observed in and around the radius gap of the observed exoplanet population.
Watershed management requires an understanding of key hydrochemical processes. The Pra Basin is one of the five major river basins in Ghana with a population of over 4.2 million people. Currently, water resources management faces challenges due to surface water pollution caused by the unregulated release of untreated household and industrial waste into aquatic ecosystems and illegal mining activities. This has increased the need for groundwater as the most reliable water supply. Our understanding of groundwater recharge mechanisms and chemical evolution in the basin has been inadequate, making effective management difficult. Therefore, the main objective of this work is to gain insight into the processes that determine the hydrogeochemical evolution of groundwater quality in the Pra Basin. The combined use of stable isotope, hydrochemistry, and water level data provides the basis for conceptualizing the chemical evolution of groundwater in the Pra Basin. For this purpose, the origin and evaporation rates of water infiltrating into the unsaturated zone were evaluated. In addition, Chloride Mass Balance (CMB) and Water Table Fluctuations (WTF) were considered to quantify groundwater recharge for the basin. Indices such as water quality index (WQI), sodium adsorption ratio (SAR), Wilcox diagram, and salinity (USSL) were used in this study to determine the quality of the resource for use as drinking water and for irrigation purposes. Due to the heterogeneity of the hydrochemical data, the statistical techniques of hierarchical cluster and factor analysis were applied to subdivide the data according to their spatial correlation. A conceptual hydrogeochemical model was developed and subsequently validated by applying combinatorial inverse and reaction pathway-based geochemical models to determine plausible mineral assemblages that control the chemical composition of the groundwater. The interactions between water and rock determine the groundwater quality in the Pra Basin. The results underline that the groundwater is of good quality and can be used for drinking water and irrigation purposes. It was demonstrated that there is a large groundwater potential to meet the entire Pra Basin’s current and future water demands. The main recharge area was identified as the northern zone, while the southern zone is the discharge area. The predominant influence of weathering of silicate minerals plays a key role in the chemical evolution of the groundwater. The work presented here provides fundamental insights into the hydrochemistry of the Pra Basin and provides data important to water managers for informed decision-making in planning and allocating water resources for various purposes. A novel inverse modelling approach was used in this study to identify different mineral compositions that determine the chemical evolution of groundwater in the Pra Basin. This modelling technique has the potential to simulate the composition of groundwater at the basin scale with large hydrochemical heterogeneity, using average water composition to represent established spatial groupings of water chemistry.
Advancing digitalization is changing society and has far-reaching effects on people and companies. Fundamental to these changes are the new technological possibilities for processing data on an ever-increasing scale and for various purposes. The availability of large and high-quality data sets, especially those based on personal data, is crucial. They are used either to improve the productivity, quality, and individuality of products and services or to develop new types of services. Today, user behavior is tracked more actively and comprehensively than ever despite increasing legal requirements for protecting personal data worldwide. That increasingly raises ethical, moral, and social questions, which have moved to the forefront of the political debate, not least due to popular cases of data misuse. Given this discourse and the legal requirements, today's data management must fulfill three conditions: Legality or legal conformity of use and ethical legitimacy. Thirdly, the use of data should add value from a business perspective. Within the framework of these conditions, this cumulative dissertation pursues four research objectives with a focus on gaining a better understanding of
(1) the challenges of implementing privacy laws,
(2) the factors that influence customers' willingness to share personal data,
(3) the role of data protection for digital entrepreneurship, and
(4) the interdisciplinary scientific significance, its development, and its interrelationships.
Electricity production contributes to a significant share of greenhouse gas emissions in Europe and is thus an important driver of climate change. To fulfil the Paris Agreement, the European Union (EU) needs a rapid transition to a fully decarbonised power production system. Presumably, such a system will be largely based on renewables. So far, many EU countries have supported a shift towards renewables such as solar and wind power using support schemes, but the economic and political context is changing. Renewables are now cheaper than ever before and have become cost-competitive with conventional technologies. Therefore, European policymakers are striving to better integrate renewables into a competitive market and to increase the cost-effectiveness of the expansion of renewables. The first step was to replace previous fixed-price schemes with competitive auctions. In a second step, these auctions have become more technology-open. Finally, some governments may phase out any support for renewables and fully expose them to the competitive power market.
However, such policy changes may be at odds with the need to rapidly expand renewables and meet national targets due to market characteristics and investors’ risk perception. Without support, price risks are higher, and it may be difficult to meet an investor’s income expectations. Furthermore, policy changes across different countries could have unexpected effects if power markets are interconnected and investors able to shift their investments. Finally, in multi-technology auctions, technologies may dominate, which can be a risk for long-term power system reliability. Therefore, in my thesis, I explore the effects of phasing out support policies for renewables, of coordinating these phase-outs across countries, and of using multi-technology designs. I expand the public policy literature about investment behaviour and policy design as well as policy change and coordination, and I further develop an agent-based model.
The main questions of my thesis are what the cost and deployment effects of gradually exposing renewables to market forces would be and how coordination between countries affects investors’ decisions and market prices.. In my three contributions to the academic literature, I use different methods and come to the following results. In the first contribution, I use a conjoint analysis and market simulation to evaluate the effects of phasing out support or reintroducing feed-in tariffs from the perspective of investors. I find that a phase-out leads to investment shifts, either to other still-supported technologies or to other countries that continue to offer support. I conclude that the coordination of policy changes avoids such shifts.. In the second contribution, I integrate the empirically-derived preferences from the first contribution in to an agent-based power system model of two countries to simulate the effects of ending auctions for renewables. I find that this slows the energy transition, and that cross-border effects are relevant. Consequently, continued support is necessary to meet the national renewables targets. In the third contribution, I analyse the outcome of past multi-technology auctions using descriptive statistics, regression analysis as well as case study comparisons. I find that the outcomes are skewed towards single technologies. This cannot be explained by individual design elements of the auctions, but rather results from context-specific and country-specific characteristics. Based on this, I discuss potential implications for long-term power system reliability.
The main conclusions of my thesis are that a complete phase-out of renewables support would slow down the energy transition and thus jeopardize climate targets, and that multi-technology auctions may pose a risk for some countries, especially those that cannot regulate an unbalanced power plant portfolio in the long term. If policymakers decide to continue supporting renewables, they may consider adopting technology-specific auctions to better steer their portfolio. In contrast, if policymakers still want to phase out support, they should coordinate these policy changes with other countries. Otherwise, overall transition costs can be higher, because investment decisions shift to still-supported but more expensive technologies.
Volcanic hydrothermal systems are an integral part of most volcanoes and typically involve a heat source, adequate fluid supply, and fracture or pore systems through which the fluids can circulate within the volcanic edifice. Associated with this are subtle but powerful processes that can significantly influence the evolution of volcanic activity or the stability of the near-surface volcanic system through mechanical weakening, permeability reduction, and sealing of the affected volcanic rock. These processes are well constrained for rock samples by laboratory analyses but are still difficult to extrapolate and evaluate at the scale of an entire volcano. Advances in unmanned aircraft systems (UAS), sensor technology, and photogrammetric processing routines now allow us to image volcanic surfaces at the centimeter scale and thus study volcanic hydrothermal systems in great detail. This thesis aims to explore the potential of UAS approaches for studying the structures, processes, and dynamics of volcanic hydrothermal systems but also to develop methodological approaches to uncover secondary information hidden in the data, capable of indicating spatiotemporal dynamics or potentially critical developments associated with hydrothermal alteration. To accomplish this, the thesis describes the investigation of two near-surface volcanic hydrothermal systems, the El Tatio geyser field in Chile and the fumarole field of La Fossa di Vulcano (Italy), both of which are among the best-studied sites of their kind. Through image analysis, statistical, and spatial analyses we have been able to provide the most detailed structural images of both study sites to date, with new insights into the driving forces of such systems but also revealing new potential controls, which are summarized in conceptual site-specific models. Furthermore, the thesis explores methodological remote sensing approaches to detect, classify and constrain hydrothermal alteration and surface degassing from UAS-derived data, evaluated them by mineralogical and chemical ground-truthing, and compares the alteration pattern with the present-day degassing activity. A significant contribution of the often neglected diffuse degassing activity to the total amount of degassing is revealed and constrains secondary processes and dynamics associated with hydrothermal alteration that lead to potentially critical developments like surface sealing. The results and methods used provide new approaches for alteration research, for the monitoring of degassing and alteration effects, and for thermal monitoring of fumarole fields, with the potential to be incorporated into volcano monitoring routines.
The remarkable antifouling properties of zwitterionic polymers in controlled environments are often counteracted by their delicate mechanical stability. In order to improve the mechanical stabilities of zwitterionic hydrogels, the effect of increased crosslinker densities was thus explored. In a first approach, terpolymers of zwitterionic monomer 3-[N -2(methacryloyloxy)ethyl-N,N-dimethyl]ammonio propane-1-sulfonate (SPE), hydrophobic monomer butyl methacrylate (BMA), and photo-crosslinker 2-(4-benzoylphenoxy)ethyl methacrylate (BPEMA) were synthesized. Thin hydrogel coatings of the copolymers were then produced and photo-crosslinked. Studies of the swollen hydrogel films showed that not only the mechanical stability but also, unexpectedly, the antifouling properties were improved by the presence of hydrophobic BMA units in the terpolymers.
Based on the positive results shown by the amphiphilic terpolymers and in order to further test the impact that hydrophobicity has on both the antifouling properties of zwitterionic hydrogels and on their mechanical stability, a new amphiphilic zwitterionic methacrylic monomer, 3-((2-(methacryloyloxy)hexyl)dimethylammonio)propane-1-sulfonate (M1), was synthesized in good yields in a multistep synthesis. Homopolymers of M1 were obtained by free-radical polymerization. Similarly, terpolymers of M1, zwitterionic monomer SPE, and photo-crosslinker BPEMA were synthesized by free-radical copolymerization and thoroughly characterized, including its solubilities in selected solvents.
Also, a new family of vinyl amide zwitterionic monomomers, namely 3-(dimethyl(2-(N -vinylacetamido)ethyl)ammonio)propane-1-sulfonate (M2), 4-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)butane-1-sulfonate (M3), and 3-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)propyl sulfate (M4), together with the new photo-crosslinker 4-benzoyl-N-vinylbenzamide (M5) that is well-suited for copolymerization with vinylamides, are introduced within the scope of the present work. The monomers are synthesized with good yields developing a multistep synthesis. Homopolymers of the new vinyl amide zwitterionic monomers are obtained by free-radical polymerization and thoroughly characterized. From the solubility tests, it is remarkable that the homopolymers produced are fully soluble in water, evidence of their high hydrophilicity. Copolymerization of the vinyl amide zwitterionic monomers, M2, M3, and M4 with the vinyl amide photo-crosslinker M5 proved to require very specific polymerization conditions. Nevertheless, copolymers were successfully obtained by free-radical copolymerization under appropriate conditions.
Moreover, in an attempt to mitigate the intrinsic hydrophobicity introduced in the copolymers by the photo-crosslinkers, and based on the proven affinity of quaternized diallylamines to copolymerize with vinyl amides, a new quaternized diallylamine sulfobetaine photo-crosslinker 3-(diallyl(2-(4-benzoylphenoxy)ethyl)ammonio)propane-1-sulfonate (M6) is synthesized. However, despite a priori promising copolymerization suitability, copolymerization with the vinyl amide zwitterionic monomers could not be achieved.
Light is the essential energy source for plants to drive photosynthesis. In nature, light availability is highly variable and often fluctuates on very short time scales. As a result, plants developed mechanisms to cope with these fluctuations. Understanding how to improve light use efficiency in natural fluctuating light (FL) conditions is a major target for agronomy.
In the first project, we identified an Arabidopsis thaliana plant that showed reduced levels of rapidly inducible non-photochemical quenching (NPQ). This plant was devoid of any T-DNA insertion. Using a mapping-by-sequencing approach, we successfully located the causal genomic region near the end of chromosome 4. Through variant investigations in that region, we identified a deletion of about 20 kb encompassing 9 genes. By complementation analysis, we confirmed that one of the deleted genes, VTC2, is the causal gene responsible for the low NPQ. Loss of VTC2 decreased NPQ particularly in old leaves, with young leaves being only slightly affected. Additionally, ascorbate levels were almost abolished in old leaves, likely causing the NPQ decrease by reducing the activity of the xanthophyll cycle. Although ascorbate levels in younger leaves were reduced compared to wild-type plants, they remained at a comparably higher level. This difference may be due to the VTC2 paralog VTC5, which is expressed at a higher level in young leaves than in old ones.
Plants require the PROTON GRADIENT REGULATION 5 (PGR5) protein for survival in FL. pgr5 mutants die because they fail to increase the luminal proton concentration in response to high light (HL) phases. A rapid elevation in ∆pH is needed to slow down electron transport through the Cytochrome b6 f complex (photosynthetic control). In FL, such lack of control in the pgr5 mutants results in photosystem I (PSI) overreduction, reactive oxygen species (ROS) production, and cell death. Decreases in photosystem II (PSII) activity introduced by crossing pgr5 with PSII deficient mutants
rescued the lethality of pgr5 in FL. PGR5 was suggested to act as part of the ferredoxin-plastoquinone reductase (FQR), involved in cyclic electron transfer around PSI. However, the proposed molecular role of PGR5 remains highly debated. To learn more about PGR5 function, we performed a forward genetic screen in Arabidopsis thaliana to identify EMS-induced suppressor mutants surviving longer when grown in FL compared to pgr5 mutants (referred to as ”suppressor of pgr5 lethality in fluctuating light”, splf ). 11 different candidate genes were identified in a total of 22 splf plants.
Mutants of seven of these genes in the pgr5 background showed low Fv/Fm values when grown in non-fluctuating low light (LL). Five of these 4genes were previously reported to have a role in PSII biogenesis or function. Two others, RPH1 and a DEAD/DEAH box helicase (AT3G02060), have not been linked to PSII function before. Three of splf candidate genes link to primary metabolism, fructose-2,6-bisphosphatase (F2KP ), udp-glucose pyrophosphorylase 1 (UGP1 ) and ferredoxin-dependent glutamate synthase (Fd-GOGAT ). They are characterized by the fact that they survive longer in FL than pgr5 mutants but do not procede beyond the early vegetative
phase and then die.
Classification, prediction and evaluation of graph neural networks on online social media platforms
(2024)
The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks.
This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes.
Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN.
Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
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.
With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind’s fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation – the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere.
By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
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.
This dissertation examines the lack of clarity in the scientific literature regarding gender and negotiation performance. It is often claimed that men negotiate better than women, yet it is simultaneously emphasized that results strongly depend on context. Through the use of qualitative methods such as content analysis and critical mixed-methods review, the research question: "Are women truly inferior negotiators compared to men?" is addressed. The study comprises a descriptive and an interpretive part. The descriptive section illuminates various interpretations of gender-specific negotiation theory among citing authors, with 67% arguing for a general superiority of men. However, given the high variance in gender-specific differences, the focus should instead be on the context-dependency of negotiation performance. Generalized statements can be made within contexts, but not across them. In the interpretive section, several factors contributing to this misinterpretation are highlighted, including discrepancies in the definition of negotiation performance and distortions in research communication.. From a scientific perspective, this study underscores the need for a nuanced sociological analysis and warns against the one-sided acceptance of inaccurate scientific interpretations. From a practical standpoint, it amplifies the voices of women affected by biased research paradigms. Overall, the dissertation clarifies the theory of gender-specific negotiation performance and advocates for the elimination of biases in scientific discourse.
Efficiently managing large state is a key challenge for data management systems. Traditionally, state is split into fast but volatile state in memory for processing and persistent but slow state on secondary storage for durability. Persistent memory (PMem), as a new technology in the storage hierarchy, blurs the lines between these states by offering both byte-addressability and low latency like DRAM as well persistence like secondary storage. These characteristics have the potential to cause a major performance shift in database systems.
Driven by the potential impact that PMem has on data management systems, in this thesis we explore their use of PMem. We first evaluate the performance of real PMem hardware in the form of Intel Optane in a wide range of setups. To this end, we propose PerMA-Bench, a configurable benchmark framework that allows users to evaluate the performance of customizable database-related PMem access. Based on experimental results obtained with PerMA-Bench, we discuss findings and identify general and implementation-specific aspects that influence PMem performance and should be considered in future work to improve PMem-aware designs. We then propose Viper, a hybrid PMem-DRAM key-value store. Based on PMem-aware access patterns, we show how to leverage PMem and DRAM efficiently to design a key database component. Our evaluation shows that Viper outperforms existing key-value stores by 4–18x for inserts while offering full data persistence and achieving similar or better lookup performance. Next, we show which changes must be made to integrate PMem components into larger systems. By the example of stream processing engines, we highlight limitations of current designs and propose a prototype engine that overcomes these limitations. This allows our prototype to fully leverage PMem's performance for its internal state management. Finally, in light of Optane's discontinuation, we discuss how insights from PMem research can be transferred to future multi-tier memory setups by the example of Compute Express Link (CXL).
Overall, we show that PMem offers high performance for state management, bridging the gap between fast but volatile DRAM and persistent but slow secondary storage. Although Optane was discontinued, new memory technologies are continuously emerging in various forms and we outline how novel designs for them can build on insights from existing PMem research.
The biosecurity individual
(2024)
Discoveries in biomedicine and biotechnology, especially in diagnostics, have made prevention and (self)surveillance increasingly important in the context of health practices. Frederike Offizier offers a cultural critique of the intersection between health, security and identity, and explores how the focus on risk and security changes our understanding of health and transforms our relationship to our bodies. Analyzing a wide variety of texts, from life writing to fiction, she offers a critical intervention on how this shift in the medical gaze produces new paradigms of difference and new biomedically facilitated identities: biosecurity individuals.
The landscape of software self-adaptation is shaped in accordance with the need to cost-effectively achieve and maintain (software) quality at runtime and in the face of dynamic operation conditions. Optimization-based solutions perform an exhaustive search in the adaptation space, thus they may provide quality guarantees. However, these solutions render the attainment of optimal adaptation plans time-intensive, thereby hindering scalability. Conversely, deterministic rule-based solutions yield only sub-optimal adaptation decisions, as they are typically bound by design-time assumptions, yet they offer efficient processing and implementation, readability, expressivity of individual rules supporting early verification. Addressing the quality-cost trade-of requires solutions that simultaneously exhibit the scalability and cost-efficiency of rulebased policy formalism and the optimality of optimization-based policy formalism as explicit artifacts for adaptation. Utility functions, i.e., high-level specifications that capture system objectives, support the explicit treatment of quality-cost trade-off. Nevertheless, non-linearities, complex dynamic architectures, black-box models, and runtime uncertainty that makes the prior knowledge obsolete are a few of the sources of uncertainty and subjectivity that render the elicitation of utility non-trivial.
This thesis proposes a twofold solution for incremental self-adaptation of dynamic architectures. First, we introduce Venus, a solution that combines in its design a ruleand an optimization-based formalism enabling optimal and scalable adaptation of dynamic architectures. Venus incorporates rule-like constructs and relies on utility theory for decision-making. Using a graph-based representation of the architecture, Venus captures rules as graph patterns that represent architectural fragments, thus enabling runtime extensibility and, in turn, support for dynamic architectures; the architecture is evaluated by assigning utility values to fragments; pattern-based definition of rules and utility enables incremental computation of changes on the utility that result from rule executions, rather than evaluating the complete architecture, which supports scalability. Second, we introduce HypeZon, a hybrid solution for runtime coordination of multiple off-the-shelf adaptation policies, which typically offer only partial satisfaction of the quality and cost requirements. Realized based on meta-self-aware architectures, HypeZon complements Venus by re-using existing policies at runtime for balancing the quality-cost trade-off.
The twofold solution of this thesis is integrated in an adaptation engine that leverages state- and event-based principles for incremental execution, therefore, is scalable for large and dynamic software architectures with growing size and complexity. The utility elicitation challenge is resolved by defining a methodology to train utility-change prediction models. The thesis addresses the quality-cost trade-off in adaptation of dynamic software architectures via design-time combination (Venus) and runtime coordination (HypeZon) of rule- and optimization-based policy formalisms, while offering supporting mechanisms for optimal, cost-effective, scalable, and robust adaptation. The solutions are evaluated according to a methodology that is obtained based on our systematic literature review of evaluation in self-healing systems; the applicability and effectiveness of the contributions are demonstrated to go beyond the state-of-the-art in coverage of a wide spectrum of the problem space for software self-adaptation.
To manage tabular data files and leverage their content in a given downstream task, practitioners often design and execute complex transformation pipelines to prepare them. The complexity of such pipelines stems from different factors, including the nature of the preparation tasks, often exploratory or ad-hoc to specific datasets; the large repertory of tools, algorithms, and frameworks that practitioners need to master; and the volume, variety, and velocity of the files to be prepared. Metadata plays a fundamental role in reducing this complexity: characterizing a file assists end users in the design of data preprocessing pipelines, and furthermore paves the way for suggestion, automation, and optimization of data preparation tasks.
Previous research in the areas of data profiling, data integration, and data cleaning, has focused on extracting and characterizing metadata regarding the content of tabular data files, i.e., about the records and attributes of tables. Content metadata are useful for the latter stages of a preprocessing pipeline, e.g., error correction, duplicate detection, or value normalization, but they require a properly formed tabular input. Therefore, these metadata are not relevant for the early stages of a preparation pipeline, i.e., to correctly parse tables out of files. In this dissertation, we turn our focus to what we call the structure of a tabular data file, i.e., the set of characters within a file that do not represent data values but are required to parse and understand the content of the file. We provide three different approaches to represent file structure, an explicit representation based on context-free grammars; an implicit representation based on file-wise similarity; and a learned representation based on machine learning.
In our first contribution, we use the grammar-based representation to characterize a set of over 3000 real-world csv files and identify multiple structural issues that let files deviate from the csv standard, e.g., by having inconsistent delimiters or containing multiple tables. We leverage our learnings about real-world files and propose Pollock, a benchmark to test how well systems parse csv files that have a non-standard structure, without any previous preparation. We report on our experiments on using Pollock to evaluate the performance of 16 real-world data management systems.
Following, we characterize the structure of files implicitly, by defining a measure of structural similarity for file pairs. We design a novel algorithm to compute this measure, which is based on a graph representation of the files' content. We leverage this algorithm and propose Mondrian, a graphical system to assist users in identifying layout templates in a dataset, classes of files that have the same structure, and therefore can be prepared by applying the same preparation pipeline.
Finally, we introduce MaGRiTTE, a novel architecture that uses self-supervised learning to automatically learn structural representations of files in the form of vectorial embeddings at three different levels: cell level, row level, and file level. We experiment with the application of structural embeddings for several tasks, namely dialect detection, row classification, and data preparation efforts estimation.
Our experimental results show that structural metadata, either identified explicitly on parsing grammars, derived implicitly as file-wise similarity, or learned with the help of machine learning architectures, is fundamental to automate several tasks, to scale up preparation to large quantities of files, and to provide repeatable preparation pipelines.
Additive manufacturing (AM) processes enable the production of metal structures with exceptional design freedom, of which laser powder bed fusion (PBF-LB) is one of the most common. In this process, a laser melts a bed of loose feedstock powder particles layer-by-layer to build a structure with the desired geometry. During fabrication, the repeated melting and rapid, directional solidification create large temperature gradients that generate large thermal stress. This thermal stress can itself lead to cracking or delamination during fabrication. More often, large residual stresses remain in the final part as a footprint of the thermal stress. This residual stress can cause premature distortion or even failure of the part in service. Hence, knowledge of the residual stress field is critical for both process optimization and structural integrity.
Diffraction-based techniques allow the non-destructive characterization of the residual stress fields. However, such methods require a good knowledge of the material of interest, as certain assumptions must be made to accurately determine residual stress. First, the measured lattice plane spacings must be converted to lattice strains with the knowledge of a strain-free material state. Second, the measured lattice strains must be related to the macroscopic stress using Hooke's law, which requires knowledge of the stiffness of the material. Since most crystal structures exhibit anisotropic material behavior, the elastic behavior is specific to each lattice plane of the single crystal. Thus, the use of individual lattice planes in monochromatic diffraction residual stress analysis requires knowledge of the lattice plane-specific elastic properties. In addition, knowledge of the microstructure of the material is required for a reliable assessment of residual stress.
This work presents a toolbox for reliable diffraction-based residual stress analysis. This is presented for a nickel-based superalloy produced by PBF-LB. First, this work reviews the existing literature in the field of residual stress analysis of laser-based AM using diffraction-based techniques. Second, the elastic and plastic anisotropy of the nickel-based superalloy Inconel 718 produced by PBF-LB is studied using in situ energy dispersive synchrotron X-ray and neutron diffraction techniques. These experiments are complemented by ex situ material characterization techniques. These methods establish the relationship between the microstructure and texture of the material and its elastic and plastic anisotropy. Finally, surface, sub-surface, and bulk residual stress are determined using a texture-based approach. Uncertainties of different methods for obtaining stress-free reference values are discussed.
The tensile behavior in the as-built condition is shown to be controlled by texture and cellular sub-grain structure, while in the heat-treated condition the precipitation of strengthening phases and grain morphology dictate the behavior. In fact, the results of this thesis show that the diffraction elastic constants depend on the underlying microstructure, including texture and grain morphology. For columnar microstructures in both as-built and heat-treated conditions, the diffraction elastic constants are best described by the Reuss iso-stress model. Furthermore, the low accumulation of intergranular strains during deformation demonstrates the robustness of using the 311 reflection for the diffraction-based residual stress analysis with columnar textured microstructures. The differences between texture-based and quasi-isotropic approaches for the residual stress analysis are shown to be insignificant in the observed case. However, the analysis of the sub-surface residual stress distributions show, that different scanning strategies result in a change in the orientation of the residual stress tensor. Furthermore, the location of the critical sub-surface tensile residual stress is related to the surface roughness and the microstructure. Finally, recommendations are given for the diffraction-based determination and evaluation of residual stress in textured additively manufactured alloys.
We live in an era driven by fossil fuels. The prevailing climate change suggests that we have to significantly reduce greenhouse gas emissions. The only way forward is to use renewable energy sources. Among those, solar energy is a clean, affordable, and sustainable source of energy. It has the potential to satisfy the world’s energy demand in the future. However, there is a need to develop new materials that can make solar energy usable. Photovoltaics (PV) are devices that convert photon energy into electrical energy. The most commonly used solar cells are based on crystalline silicon. However, the fabrication process for silicon solar cells is technologically difficult and costly. Solar cells based on lead halide perovskites (PSCs) have emerged as a new candidate for PV applications since 2009. To date, PSCs have achieved 26% power-conversion-efficiency (PCE) for its single junction, and 33.7% PCE for tandem junction devices. However, there is still room for improvement in overall performance. The main challenge for the commercialization of this technology is the stability of the solar cells under operational conditions. Inorganic perovskite CsPbI3 has attracted researchers’ interest due to its stability at elevated temperatures, however, inorganic perovskites also have associated challenges, e.g. phase stability, larger voltage loss compared to their organic-inorganic hybrid counterparts, and interface energy misalignment. The most efficient inorganic perovskite solar cell is stable for up to a few hundred hours while the most stable device in the field of inorganic PSCs reported so far is at 17% PCE. This suggests the need for improvement of the interfaces for enhanced open circuit voltage (VOC), and optimization of the energy alignment at the interfaces. This dissertation presents the study on interfaces between the perovskite layer and hole transport layer (HTL) for stable CsPbI3 solar cells.
The first part of the thesis presents an investigation of the CsPbI3 film annealing environment and its subsequent effects on the perovskite/HTL interface dynamics. Thin films annealed in dry air were compared with thin films annealed in ambient air. Synchrotron-based hard X-ray spectroscopy (HAXPES) measurements reveal that annealing in ambient air does not have an adverse effect; instead, those samples undergo surface band bending. This surface band modification induces changes in interface charge dynamics and, consequently, an improvement in charge extraction at the interfaces. Further, transient surface photovoltage (tr-SPV) simulations show that air-annealed samples exhibit fewer trap states compared to samples annealed in dry air. Finally, by annealing the CsPbI3 films in ambient air, a PCE of 19.8% and Voc of 1.23 V were achieved for an n-i-p structured device.
Interface engineering has emerged as a strategy to extract the charge and optimize the energy alignment in perovskite solar cells (PSCs). An interface with fewer trap states and energy band levels closer to the selective contact helps to attain improved efficiencies in PSCs. The second part of the thesis presents a design for the CsPbI3/HTM interface. In this work, an interface between CsPbI3 perovskite and its hole selective contact N2,N2,N2′,N2′,N7,N7,N7′,N7′-octakis(4-methoxyphenyl)-9,9′-spirobi[9H-fluorene]-2,2′,7,7′-tetramine(Spiro-OMeTAD), realized by trioctylphosphine oxide (TOPO), a dipole molecule is introduced. On top of a perovskite film well-passivated by n-octyl ammonium Iodide (OAI), it created an upward surface band-bending at the interface byTOPO that optimizes energy level alignment and enhances the extraction of holes from the perovskite layer to the hole transport material. Consequently, a Voc of 1.2 V and high-power conversion efficiency (PCE) of over 19% were achieved for inorganic CsPbI3 perovskite solar cells. In addition, the work also sheds light on the interfacial charge-selectivity and the long-term stability of CsPbI3 perovskite solar cells.
The third part of the thesis extends the previous studies to polymeric poly(3-hexylthiophene-2,5-diyl) (P3HT) as HTL. The CsPbI3/P3HT interface is critical due to high non-radiative recombination. This work presents a CsPbI3/P3HT interface modified with a long-chain alkyl halide molecule, n-hexyl trimethyl ammonium bromide (HTAB). This molecule largely passivates the CsPbI3 perovskite surface and improves the charge extraction across the interface. Consequently, a Voc of over 1.00 V and 14.2% PCE were achieved for CsPbI3 with P3HT as HTM.
Overall the results presented in this dissertation introduce and discuss methods to design and study the interfaces in CsPbI3-based solar cells. This study can pave the way for novel interface designs between CsPbI3 and HTM for charge extraction, efficiency and stability.
Large parts of the Earth’s interior are inaccessible to direct observation, yet global geodynamic processes are governed by the physical material properties under extreme pressure and temperature conditions. It is therefore essential to investigate the deep Earth’s physical properties through in-situ laboratory experiments. With this goal in mind, the optical properties of mantle minerals at high pressure offer a unique way to determine a variety of physical properties, in a straight-forward, reproducible, and time-effective manner, thus providing valuable insights into the physical processes of the deep Earth. This thesis focusses on the system Mg-Fe-O, specifically on the optical properties of periclase (MgO) and its iron-bearing variant ferropericlase ((Mg,Fe)O), forming a major planetary building block. The primary objective is to establish links between physical material properties and optical properties. In particular the spin transition in ferropericlase, the second-most abundant phase of the lower mantle, is known to change the physical material properties. Although the spin transition region likely extends down to the core-mantle boundary, the ef-fects of the mixed-spin state, where both high- and low-spin state are present, remains poorly constrained.
In the studies presented herein, we show how optical properties are linked to physical properties such as electrical conductivity, radiative thermal conductivity and viscosity. We also show how the optical properties reveal changes in the chemical bonding. Furthermore, we unveil how the chemical bonding, the optical and other physical properties are affected by the iron spin transition. We find opposing trends in the pres-sure dependence of the refractive index of MgO and (Mg,Fe)O. From 1 atm to ~140 GPa, the refractive index of MgO decreases by ~2.4% from 1.737 to 1.696 (±0.017). In contrast, the refractive index of (Mg0.87Fe0.13)O (Fp13) and (Mg0.76Fe0.24)O (Fp24) ferropericlase increases with pressure, likely because Fe Fe interactions between adjacent iron sites hinder a strong decrease of polarizability, as it is observed with increasing density in the case of pure MgO. An analysis of the index dispersion in MgO (decreasing by ~23% from 1 atm to ~103 GPa) reflects a widening of the band gap from ~7.4 eV at 1 atm to ~8.5 (±0.6) eV at ~103 GPa. The index dispersion (between 550 and 870 nm) of Fp13 reveals a decrease by a factor of ~3 over the spin transition range (~44–100 GPa). We show that the electrical band gap of ferropericlase significantly widens up to ~4.7 eV in the mixed spin region, equivalent to an increase by a factor of ~1.7. We propose that this is due to a lower electron mobility between adjacent Fe2+ sites of opposite spin, explaining the previously observed low electrical conductivity in the mixed spin region. From the study of absorbance spectra in Fp13, we show an increasing covalency of the Fe-O bond with pressure for high-spin ferropericlase, whereas in the low-spin state a trend to a more ionic nature of the Fe-O bond is observed, indicating a bond weakening effect of the spin transition. We found that the spin transition is ultimately caused by both an increase of the ligand field-splitting energy and a decreasing spin-pairing energy of high-spin Fe2+.
Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties.
Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult – if not impossible – to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates (‘higher export in warmer years’) that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes.
Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine Ötztal valley in Tyrol, Austria, over decadal timescales in the past and future – i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest.
The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper Ötztal, Vent, Sölden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 % of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors.
The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.
The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed – unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology.
This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves – especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.
It is a well-attested finding in head-initial languages that individuals with aphasia (IWA) have greater difficulties in comprehending object-extracted relative clauses (ORCs) as compared to subject-extracted relative clauses (SRCs). Adopting the linguistically based approach of Relativized Minimality (RM; Rizzi, 1990, 2004), the subject-object asymmetry is attributed to the occurrence of a Minimality effect in ORCs due to reduced processing capacities in IWA (Garraffa & Grillo, 2008; Grillo, 2008, 2009). For ORCs, it is claimed that the embedded subject intervenes in the syntactic dependency between the moved object and its trace, resulting in greater processing demands. In contrast, no such intervener is present in SRCs. Based on the theoretical framework of RM and findings from language acquisition (Belletti et al., 2012; Friedmann et al., 2009), it is assumed that Minimality effects are alleviated when the moved object and the intervening subject differ in terms of relevant syntactic features. For German, the language under investigation, the RM approach predicts that number (i.e., singular vs. plural) and the lexical restriction [+NP] feature (i.e., lexically restricted determiner phrases vs. lexically unrestricted pronouns) are considered relevant in the computation of Minimality. Greater degrees of featural distinctiveness are predicted to result in more facilitated processing of ORCs, because IWA can more easily distinguish between the moved object and the intervener.
This cumulative dissertation aims to provide empirical evidence on the validity of the RM approach in accounting for comprehension patterns during relative clause (RC) processing in German-speaking IWA. For that purpose, I conducted two studies including visual-world eye-tracking experiments embedded within an auditory referent-identification task to study the offline and online processing of German RCs. More specifically, target sentences were created to evaluate (a) whether IWA demonstrate a subject-object asymmetry, (b) whether dissimilarity in the number and/or the [+NP] features facilitates ORC processing, and (c) whether sentence processing in IWA benefits from greater degrees of featural distinctiveness. Furthermore, by comparing RCs disambiguated through case marking (at the relative pronoun or the following noun phrase) and number marking (inflection of the sentence-final verb), it was possible to consider the role of the relative position of the disambiguation point. The RM approach predicts that dissimilarity in case should not affect the occurrence of Minimality effects. However, the case cue to sentence interpretation appears earlier within RCs than the number cue, which may result in lower processing costs in case-disambiguated RCs compared to number-disambiguated RCs.
In study I, target sentences varied with respect to word order (SRC vs. ORC) and dissimilarity in the [+NP] feature (lexically restricted determiner phrase vs. pronouns as embedded element). Moreover, by comparing the impact of these manipulations in case- and number-disambiguated RCs, the effect of dissimilarity in the number feature was explored. IWA demonstrated a subject-object asymmetry, indicating the occurrence of a Minimality effect in ORCs. However, dissimilarity neither in the number feature nor in the [+NP] feature alone facilitated ORC processing. Instead, only ORCs involving distinct specifications of both the number and the [+NP] features were well comprehended by IWA. In study II, only temporarily ambiguous ORCs disambiguated through case or number marking were investigated, while controlling for varying points of disambiguation. There was a slight processing advantage of case marking as cue to sentence interpretation as compared to number marking.
Taken together, these findings suggest that the RM approach can only partially capture empirical data from German IWA. In processing complex syntactic structures, IWA are susceptible to the occurrence of the intervening subject in ORCs. The new findings reported in the thesis show that structural dissimilarity can modulate sentence comprehension in aphasia. Interestingly, IWA can override Minimality effects in ORCs and derive correct sentence meaning if the featural specifications of the constituents are maximally different, because they can more easily distinguish the moved object and the intervening subject given their reduced processing capacities. This dissertation presents new scientific knowledge that highlights how the syntactic theory of RM helps to uncover selective effects of morpho-syntactic features on sentence comprehension in aphasia, emphasizing the close link between assumptions from theoretical syntax and empirical research.
Within the context of United Nations (UN) environmental institutions, it has become apparent that intergovernmental responses alone have been insufficient for dealing with pressing transboundary environmental problems. Diverging economic and political interests, as well as broader changes in power dynamics and norms within global (environmental) governance, have resulted in negotiation and implementation efforts by UN member states becoming stuck in institutional gridlock and inertia. These developments have sparked a renewed debate among scholars and practitioners about an imminent crisis of multilateralism, accompanied by calls for reforming UN environmental institutions. However, with the rise of transnational actors and institutions, states are not the only relevant actors in global environmental governance. In fact, the fragmented architectures of different policy domains are populated by a hybrid mix of state and non-state actors, as well as intergovernmental and transnational institutions. Therefore, coping with the complex challenges posed by severe and ecologically interdependent transboundary environmental problems requires global cooperation and careful management from actors beyond national governments.
This thesis investigates the interactions of three intergovernmental UN treaty secretariats in global environmental governance. These are the secretariats of the United Nations Framework Convention on Climate Change, the Convention on Biological Diversity, and the United Nations Convention to Combat Desertification. While previous research has acknowledged the increasing autonomy and influence of treaty secretariats in global policy-making, little attention has been paid to their strategic interactions with non-state actors, such as non-governmental organizations, civil society actors, businesses, and transnational institutions and networks, or their coordination with other UN agencies. Through qualitative case-study research, this thesis explores the means and mechanisms of these interactions and investigates their consequences for enhancing the effectiveness and coherence of institutional responses to underlying and interdependent environmental issues.
Following a new institutionalist ontology, the conceptual and theoretical framework of this study draws on global governance research, regime theory, and scholarship on international bureaucracies. From an actor-centered perspective on institutional interplay, the thesis employs concepts such as orchestration and interplay management to assess the interactions of and among treaty secretariats. The research methodology involves structured, focused comparison, and process-tracing techniques to analyze empirical data from diverse sources, including official documents, various secondary materials, semi-structured interviews with secretariat staff and policymakers, and observations at intergovernmental conferences.
The main findings of this research demonstrate that secretariats employ tailored orchestration styles to manage or bypass national governments, thereby raising global ambition levels for addressing transboundary environmental problems. Additionally, they engage in joint interplay management to facilitate information sharing, strategize activities, and mobilize relevant actors, thereby improving coherence across UN environmental institutions. Treaty secretariats play a substantial role in influencing discourses and knowledge exchange with a wide range of actors. However, they face barriers, such as limited resources, mandates, varying leadership priorities, and degrees of politicization within institutional processes, which may hinder their impact. Nevertheless, the secretariats, together with non-state actors, have made progress in advancing norm-building processes, integrated policy-making, capacity building, and implementation efforts within and across framework conventions. Moreover, they utilize innovative means of coordination with actors beyond national governments, such as data-driven governance, to provide policy-relevant information for achieving overarching governance targets.
Importantly, this research highlights the growing interactions between treaty secretariats and non-state actors, which not only shape policy outcomes but also have broader implications for the polity and politics of international institutions. The findings offer opportunities for rethinking collective agency and actor dynamics within UN entities, addressing gaps in institutionalist theory concerning the interaction of actors in inter-institutional spaces. Furthermore, the study addresses emerging challenges and trends in global environmental governance that are pertinent to future policy-making. These include reflections for the debate on reforming international institutions, the role of emerging powers in a changing international world order, and the convergence of public and private authority through new alliance-building and a division of labor between international bureaucracies and non-state actors in global environmental governance.
Animal movement is a crucial aspect of life, influencing ecological and evolutionary processes. It plays an important role in shaping biodiversity patterns, connecting habitats and ecosystems. Anthropogenic landscape changes, such as in agricultural environments, can impede the movement of animals by affecting their ability to locate resources during recurring movements within home ranges and, on a larger scale, disrupt migration or dispersal. Inevitably, these changes in movement behavior have far-reaching consequences on the mobile link functions provided by species inhabiting such extensively altered matrix areas. In this thesis, I investigate the movement characteristics and activity patterns of the European hare (Lepus europaeus), aiming to understand their significance as a pivotal species in fragmented agricultural landscapes. I reveal intriguing results that shed light on the importance of hares for seed dispersal, the influence of personality traits on behavior and space use, the sensitivity of hares to extreme weather conditions, and the impacts of GPS collaring on mammals' activity patterns and movement behavior.
In Chapter I, I conducted a controlled feeding experiment to investigate the potential impact of hares on seed dispersal. By additionally utilizing GPS data of hares in two contrasting landscapes, I demonstrated that hares play a vital role, acting as effective mobile linkers for many plant species in small and isolated habitat patches. The analysis of seed intake and germination success revealed that distinct seed traits, such as density, surface area, and shape, profoundly affect hares' ability to disperse seeds through endozoochory. These findings highlight the interplay between hares and plant communities and thus provide valuable insights into seed dispersal mechanisms in fragmented landscapes.
By employing standardized behavioral tests in Chapter II, I revealed consistent behavioral responses among captive hares while simultaneously examining the intricate connection between personality traits and spatial patterns within wild hare populations. This analysis provides insights into the ecological interactions and dynamics within hare populations in agricultural habitats. Examining the concept of animal personality, I established a link between personality traits and hare behavior. I showed that boldness, measured through standardized tests, influences individual exploration styles, with shy and bold hares exhibiting distinct space use patterns. In addition to providing valuable insights into the role of animal personality in heterogeneous environments, my research introduced a novel approach demonstrating the feasibility of remotely assessing personality types using animal-borne sensors without additional disturbance of the focal individual.
While climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe, in Chapter III, I uncovered the sensitivity of hares to temperature, humidity, and wind speed during their peak reproduction period. I found a strong response in activity to high temperatures above 25°C, with a particularly pronounced effect during temperature extremes of over 35°C. The non-linear relationship between temperature and activity was characterized by contrasting responses observed for day and night. These findings emphasize the vulnerability of hares to climate change and the potential consequences for their fitness and population dynamics with the ongoing rise of temperature.
Since such insights can only be obtained through capturing and tagging free-ranging animals, I assessed potential impacts and the recovery process post-collar attachment in Chapter IV. For this purpose, I examined the daily distances moved and the temporal-associated activity of 1451 terrestrial mammals out of 42 species during their initial tracking period. The disturbance intensity and the speed of recovery varied across species, with herbivores, females, and individuals captured and collared in relatively secluded study areas experiencing more pronounced disturbances due to limited anthropogenic influences.
Mobile linkers are essential for maintaining biodiversity as they influence the dynamics and resilience of ecosystems. Furthermore, their ability to move through fragmented landscapes makes them a key component for restoring disturbed sites. Individual movement decisions determine the scale of mobile links, and understanding variations in space use among individuals is crucial for interpreting their functions. Climate change poses further challenges, with wildlife species expected to adjust their behavior, especially in response to high-temperature extremes, and comprehending the anthropogenic influence on animal movements will remain paramount to effective land use planning and the development of successful conservation strategies.
This thesis provides a comprehensive ecological understanding of hares in agricultural landscapes. My research findings underscore the importance of hares as mobile linkers, the influence of personality traits on behavior and spatial patterns, the vulnerability of hares to extreme weather conditions, and the immediate consequences of collar attachment on mammalian movements. Thus, I contribute valuable insights to wildlife conservation and management efforts, aiding in developing strategies to mitigate the impact of environmental changes on hare populations. Moreover, these findings enable the development of methodologies aimed at minimizing the impacts of collaring while also identifying potential biases in the data, thereby benefiting both animal welfare and the scientific integrity of localization studies.
The evaluation of process-oriented cognitive theories through time-ordered observations is crucial for the advancement of cognitive science. The findings presented herein integrate insights from research on eye-movement control and sentence comprehension during reading, addressing challenges in modeling time-ordered data, statistical inference, and interindividual variability. Using kernel density estimation and a pseudo-marginal likelihood for fixation durations and locations, a likelihood implementation of the SWIFT model of eye-movement control during reading (Engbert et al., Psychological Review, 112, 2005, pp. 777–813) is proposed. Within the broader framework of data assimilation, Bayesian parameter inference with adaptive Markov Chain Monte Carlo techniques is facilitated for reliable model fitting. Across the different studies, this framework has shown to enable reliable parameter recovery from simulated data and prediction of experimental summary statistics. Despite its complexity, SWIFT can be fitted within a principled Bayesian workflow, capturing interindividual differences and modeling experimental effects on reading across different geometrical alterations of text. Based on these advancements, the integrated dynamical model SEAM is proposed, which combines eye-movement control, a traditionally psychological research area, and post-lexical language processing in the form of cue-based memory retrieval (Lewis & Vasishth, Cognitive Science, 29, 2005, pp. 375–419), typically the purview of psycholinguistics. This proof-of-concept integration marks a significant step forward in natural language comprehension during reading and suggests that the presented methodology can be useful to develop complex cognitive dynamical models that integrate processes at levels of perception, higher cognition, and (oculo-)motor control. These findings collectively advance process-oriented cognitive modeling and highlight the importance of Bayesian inference, individual differences, and interdisciplinary integration for a holistic understanding of reading processes. Implications for theory and methodology, including proposals for model comparison and hierarchical parameter inference, are briefly discussed.
The development of speaking competence is widely regarded as a central aspect of second language (L2) learning. It may be questioned, however, if the currently predominant ways of conceptualising the term fully satisfy the complexity of the construct: Although there is growing recognition that language primarily constitutes a tool for communication and participation in social life, as yet it is rare for conceptualisations of speaking competence to incorporate the ability to inter-act and co-construct meaning with co-participants. Accordingly, skills allowing for the successful accomplishment of interactional tasks (such as orderly speaker change, and resolving hearing and understanding trouble) also remain largely unrepresented in language teaching and assessment. As fostering the ability to successfully use the L2 within social interaction should arguably be a main objective of language teaching, it appears pertinent to broaden the construct of speaking competence by incorporating interactional competence (IC). Despite there being a growing research interest in the conceptualisation and development of (L2) IC, much of the materials and instruments required for its teaching and assessment, and thus for fostering a broader understanding of speaking competence in the L2 classroom, still await development. This book introduces an approach to the identification of candidate criterial features for the assessment of EFL learners’ L2 repair skills. Based on a corpus of video-recorded interaction between EFL learners, and following conversation-analytic and interactional-linguistic methodology as well as drawing on basic premises of research in the framework of Conversation Analysis for Second Language Acquisition, differences between (groups of) learners in terms of their L2 repair conduct are investigated through qualitative and inductive analyses. Candidate criterial features are derived from the analysis results. This book does not only contribute to the operationalisation of L2 IC (and of L2 repair skills in particular), but also lays groundwork for the construction of assessment scales and rubrics geared towards the evaluation of EFL learners’ L2 interactional skills.
Background: Physical fitness is a key aspect of children’s ability to perform activities of daily living, engage in leisure activities, and is associated with important health characteristics. As such, it shows multi-directional associations with weight status as well as executive functions, and varies according to a variety of moderating factors, such as the child’s gender, age, geographical location, and socioeconomic conditions and context. The assessment and monitoring of children’s physical fitness has gained attention in recent decades, as has the question of how to promote physical fitness through the implementation of a variety of programs and interventions. However, these programs and interventions rarely focus on children with deficits in their physical fitness. Due to their deficits, these children are at the highest risk of suffering health impairments compared to their more average fit peers. In efforts to promote physical fitness, schools could offer promising and viable approaches to interventions, as they provide access to large youth populations while providing useful infrastructure. Evidence suggests that school-based physical fitness interventions, particularly those that include supplementary physical education, are useful for promoting and improving physical fitness in children with normal fitness. However, there is little evidence on whether these interventions have similar or even greater effects on children with deficits in their physical fitness. Furthermore, the question arises whether these measures help to sustainably improve the development/trajectories of physical fitness in these children.
The present thesis aims to elucidate the following four objectives: (1) to evaluate the effects of a 14 week intervention with 2 x 45 minutes per week additional remedial physical education on physical fitness and executive function in children with deficits in their physical fitness; (2) to assess moderating effects of body height and body mass on physical fitness components in children with physical fitness deficits; (3) to assess moderating effects of age and skeletal growth on physical fitness in children with physical fitness deficits; and (4) to analyse moderating effects of different physical fitness components on executive function in children with physical fitness deficits.
Methods: Using physical fitness data from the EMOTIKON study, 76 third graders with physical fitness deficits were identified in 11 schools in Brandenburg state that met the requirements for implementing a remedial physical education intervention (i.e., employing specially trained physical education teachers). The fitness intervention was implemented in a cross-over design and schools were randomly assigned to either an intervention-control or control-intervention group. The remedial physical education intervention consisted of a 14 week, 2 x 45 minutes per week remedial physical education curriculum supplemented by a physical exercise homework program. Assessments were conducted at the beginning and end of each intervention and control period, and further assessments were conducted at the beginning and end of each school year until the end of sixth grade. Physical fitness as the primary outcome was assessed using fitness tests implemented in the EMOTIKON study (i.e., lower body muscular strength (standing long jump), speed (20 m sprint), cardiorespiratory fitness (6 min run), agility (star run), upper body muscular strength (ball push test), and balance (one leg balance)). Executive functions as a secondary outcome were assessed using attention and psychomotor processing speed (digit symbol substitution test), mental flexibility and fine motor skills (trail making test), and inhibitory control (Simon task). Anthropometric measures such as body height, body mass, maturity offset, and body composition parameters, as well as socioeconomic information were recorded as potential moderators.
Results: (1) The evaluation of possible effects of the remedial physical education intervention on physical fitness and executive functions of children with deficits in their physical fitness did not reveal any detectable intervention-related improvements in physical fitness or executive functions. The implemented analysis strategies also showed moderating effects of body mass index (BMI) on performance in 6 min run, star run, and standing long jump, with children with a lower BMI performing better, moderating effects of proximity to Berlin on performance in the 6 min run and standing long jump, better performances being found in children living closer to Berlin, and overall gendered differences in executive function test performance, with boys performing better compared to girls. (2) Analysing moderating effects of body height and body mass on physical fitness performance, better overall physical fitness performance was found for taller children. For body mass, a negative effect was found on performance in the 6 min run (linear), standing long jump (linear), and 20 m sprint (quadratic), with better performance associated with lighter children, and a positive effect of body mass on performance in the ball push test, with heavier children performing better. In addition, the analysis revealed significant interactions between body height and body mass on performance in 6 min run and 20 m sprint, with higher body mass being associated with performance improvements in larger children, while higher body mass was associated with performance declines in smaller children. In addition, the analysis revealed overall age-related improvements in physical fitness and was able to show that children with better overall physical fitness also elicit greater age-related improvements. (3) In the analysis of moderating effects of age and maturity offset on physical fitness performances, two unrotated principal components of z-transformed age and maturity offset values were calculated (i.e., relative growth = (age + maturity offset)/2; growth delay = (age - maturity offset)) to avoid colinearity. Analysing these constructs revealed positive effects of relative growth on performances in star run, 20 m sprint, and standing long jump, with children of higher relative growth performing better. For growth delay, positive effects were found on performances in 6 min run and 20 m sprint, with children having larger growth delays showing better performances. Further, the model revealed gendered differences in 6 min run and 20 m sprint performances with girls performing better than boys. (4) Analysing the effects of physical fitness tests on executive function revealed a positive effect of star run and one leg balance performance and a negative effect of 6 min run performance on reaction speed in the Simon task. However, these effects were not detectable when individual differences were accounted for. Then these effects showed overall positive effects, with better performances being associated with faster reaction speeds. In addition, the analysis revealed a positive correlation between overall reaction speed and effects of the 6 min run, suggesting that children with greater effects of 6 min run had faster overall reaction speeds. Negative correlations were found between star run effects and age effects on Simon task reaction speed, meaning that children with larger star run effects had smaller age effects, and between 6 min run effects and star run effects on Simon task reaction speed, meaning that children with larger 6 min run effects tended to have smaller star run effects on Simon task reaction speed and vice versa.
Conclusions: (1) The lack of detectable intervention-related effects could have been caused by an insufficient intervention period, by the implementation of comprehensive and thus non- specific exercises, or by both. Accordingly, longer intervention periods and/or more specific exercises may have been more beneficial and could have led to detectable improvements in physical fitness and/or executive function. However, it remains unclear whether these interventions can benefit children with deficits in physical fitness, as it is possible that their deficits are not caused by a mere lack of exercise, but rather depend on the socioeconomic conditions of the children and their families and areas. Therefore, further research is needed to assess the moderation of physical fitness in children with physical fitness deficits and, in particular, the links between children’s environment and their physical fitness trajectories. (2) Findings from this work suggest that using BMI as a composite of body height and body mass may not be able to capture the variation associated with these parameters and their interactions. In particular, because of their multidirectional associations, further research would help elucidate how BMI and its subcomponents influence physical fitness and how they vary between children with and without physical fitness deficits. (3) The assessment of growth- related changes indicated negative effects associated with the growth spurt approaching age of peak height velocity, and furthermore showed significant differences in these effects between children. Thus, these effects and possible interindividual differences should be considered in the assessment of the development of physical fitness in children. (4) Furthermore, this work has shown that the associations between physical fitness and executive functions vary between children and may be moderated by children’s socioeconomic conditions and the structure of their daily activities. Further research is needed to explore these associations using approaches that account for individual variance.
The reliance on fossil fuels has resulted in an abnormal increase in the concentration of greenhouse gases, contributing to the global climate crisis. In response, a rapid transition to renewable energy sources has begun, particularly lithium-ion batteries, playing a crucial role in the green energy transformation. However, concerns regarding the availability and geopolitical implications of lithium have prompted the exploration of alternative rechargeable battery systems, such as sodium-ion batteries. Sodium is significantly abundant and more homogeneously distributed in the crust and seawater, making it easier and less expensive to extract than lithium. However, because of the mysterious nature of its components, sodium-ion batteries are not yet sufficiently advanced to take the place of lithium-ion batteries. Specifically, sodium exhibits a more metallic character and a larger ionic radius, resulting in a different ion storage mechanism utilized in lithium-ion batteries. Innovations in synthetic methods, post-treatments, and interface engineering clearly demonstrate the significance of developing high-performance carbonaceous anode materials for sodium-ion batteries. The objective of this dissertation is to present a systematic approach for fabricating efficient, high-performance, and sustainable carbonaceous anode materials for sodium-ion batteries. This will involve a comprehensive investigation of different chemical environments and post-modification techniques as well.
This dissertation focuses on three main objectives. Firstly, it explores the significance of post-synthetic methods in designing interfaces. A conformal carbon nitride coating is deposited through chemical vapor deposition on a carbon electrode as an artificial solid-electrolyte interface layer, resulting in improved electrochemical performance. The interaction between the carbon nitride artificial interface and the carbon electrode enhances initial Coulombic efficiency, rate performance, and total capacity. Secondly, a novel process for preparing sulfur-rich carbon as a high-performing anode material for sodium-ion batteries is presented. The method involves using an oligo-3,4-ethylenedioxythiophene precursor for high sulfur content hard carbon anode to investigate the sulfur heteroatom effect on the electrochemical sodium storage mechanism. By optimizing the condensation temperature, a significant transformation in the materials’ nanostructure is achieved, leading to improved electrochemical performance. The use of in-operando small-angle X-ray scattering provides valuable insights into the interaction between micropores and sodium ions during the electrochemical processes. Lastly, the development of high-capacity hard carbon, derived from 5-hydroxymethyl furfural, is examined. This carbon material exhibits exceptional performance at both low and high current densities. Extensive electrochemical and physicochemical characterizations shed light on the sodium storage mechanism concerning the chemical environment, establishing the material’s stability and potential applications in sodium-ion batteries.
Sigmund Freud, the founder of psychoanalysis, began his intellectual life with the Jewish Bible and also ended it with it. He began by reading the Philippson Bible together, especially with his father Jacob Freud, and ended by studying the figure of Moses. This study systematically traces this preoccupation and shows that the Jewish Bible was a constant reference for Freud and determined his Jewish identity. This is shown by analysing family documents, religious instruction and references to the Bible in Freud's writings and correspondence.
The origin and structure of magnetic fields in the Galaxy are largely unknown. What is known is that they are essential for several astrophysical processes, in particular the propagation of cosmic rays. Our ability to describe the propagation of cosmic rays through the Galaxy is severely limited by the lack of observational data needed to probe the structure of the Galactic magnetic field on many different length scales. This is particularly true for modelling the propagation of cosmic rays into the Galactic halo, where our knowledge of the magnetic field is particularly poor.
In the last decade, observations of the Galactic halo in different frequency regimes have revealed the existence of out-of-plane bubble emission in the Galactic halo. In gamma rays these bubbles have been termed Fermi bubbles with a radial extent of ≈ 3 kpc and an azimuthal height of ≈ 6 kpc. The radio counterparts of the Fermi bubbles were seen by both the S-PASS telescopes and the Planck satellite, and showed a clear spatial overlap. The X-ray counterparts of the Fermi bubbles were named eROSITA bubbles after the eROSITA satellite, with a radial width of ≈ 7 kpc and an azimuthal height of ≈ 14 kpc. Taken together, these observations suggest the presence of large extended Galactic Halo Bubbles (GHB) and have stimulated interest in exploring the less explored Galactic halo.
In this thesis, a new toy model (GHB model) for the magnetic field and non-thermal electron distribution in the Galactic halo has been proposed. The new toy model has been used to produce polarised synchrotron emission sky maps. Chi-square analysis was used to compare the synthetic skymaps with the Planck 30 GHz polarised skymaps. The obtained constraints on the strength and azimuthal height were found to be in agreement with the S-PASS radio observations.
The upper, lower and best-fit values obtained from the above chi-squared analysis were used to generate three separate toy models. These three models were used to propagate ultra-high energy cosmic rays. This study was carried out for two potential sources, Centaurus A and NGC 253, to produce magnification maps and arrival direction skymaps. The simulated arrival direction skymaps were found to be consistent with the hotspots of Centaurus A and NGC 253 as seen in the observed arrival direction skymaps provided by the Pierre Auger Observatory (PAO).
The turbulent magnetic field component of the GHB model was also used to investigate the extragalactic dipole suppression seen by PAO. UHECRs with an extragalactic dipole were forward-tracked through the turbulent GHB model at different field strengths. The suppression in the dipole due to the varying diffusion coefficient from the simulations was noted. The results could also be compared with an analytical analogy of electrostatics. The simulations of the extragalactic dipole suppression were in agreement with similar studies carried out for galactic cosmic rays.
Organic solar cells (OSCs) represent a new generation of solar cells with a range of captivating attributes including low-cost, light-weight, aesthetically pleasing appearance, and flexibility. Different from traditional silicon solar cells, the photon-electron conversion in OSCs is usually accomplished in an active layer formed by blending two kinds of organic molecules (donor and acceptor) with different energy levels together.
The first part of this thesis focuses on a better understanding of the role of the energetic offset and each recombination channel on the performance of these low-offset OSCs. By combining advanced experimental techniques with optical and electrical simulation, the energetic offsets between CT and excitons, several important insights were achieved: 1. The short circuit current density and fill-factor of low-offset systems are largely determined by field-dependent charge generation in such low-offset OSCs. Interestingly, it is strongly evident that such field-dependent charge generation originates from a field-dependent exciton dissociation yield. 2. The reduced energetic offset was found to be accompanied by strongly enhanced bimolecular recombination coefficient, which cannot be explained solely by exciton repopulation from CT states. This implies the existence of another dark decay channel apart from CT.
The second focus of the thesis was on the technical perspective. In this thesis, the influence of optical artifacts in differential absorption spectroscopy upon the change of sample configuration and active layer thickness was studied. It is exemplified and discussed thoroughly and systematically in terms of optical simulations and experiments, how optical artifacts originated from non-uniform carrier profile and interference can manipulate not only the measured spectra, but also the decay dynamics in various measurement conditions. In the end of this study, a generalized methodology based on an inverse optical transfer matrix formalism was provided to correct the spectra and decay dynamics manipulated by optical artifacts.
Overall, this thesis paves the way for a deeper understanding of the keys toward higher PCEs in low-offset OSC devices, from the perspectives of both device physics and characterization techniques.
In this work, the role of the TusA protein was investigated for the cell functionality and FtsZ ring assembly in Escherichia coli. TusA is the tRNA-2-thiouridine synthase that acts as a sulfur transferase in tRNA thiolation for the formation of 2-thiouridine at the position 34 (wobble base) of tRNALys, tRNAGlu and tRNAGln. It binds the persulfide form of sulfur and transfers it to further proteins during mnm5s2U tRNA modification at wobble position and for Moco biosynthesis. With this thiomodification of tRNA, the ribosome binding is more efficient and frameshifting is averted during the protein translation. Previous studies have revealed an essential role of TusA in bacterial cell physiology since deletion of the tusA gene resulted in retarded growth and filamentous cells during the exponential growth phase in a rich medium which suddenly disappeared during the stationary phase. This indicates a problem in the cell division process. Therefore the focus of this work was to investigate the role of TusA for cell functionality and FtsZ ring formation and thus the cell separation.
The reason behind the filamentous growth of the tusA mutant strain was investigated by growth and morphological analyses. ΔtusA cells showed a retarded growth during the exponential phase compared to the WT strain. Also, morphological analysis of ΔtusA cells confirmed the filamentous cell shape. The growth and cell division defects in ΔtusA indicated a defect in FtsZ protein as a key player of cell division. The microscopic investigation revealed that filamentous ΔtusA cells possessed multiple DNA parts arranged next to each other. This suggested that although the DNA replication occurred correctly, there was a defect in the step where FtsZ should act; probably FtsZ is unable to assemble to the ring structure or the assembled ring is not able to constrict. All tested mutant strains (ΔtusD, ΔtusE and ΔmnmA) involved in the mnm5s2U34 tRNA modification pathway shared the similar retarded growth and filamentous cell shape like ΔtusA strain. Thus, the cell division defect arises from a defect in mnm5s2U34 tRNA thiolation.
Since the FtsZ ring formation was supposed to be defective in filaments, a possible intracellular interaction of TusA and FtsZ was examined by fluorescent (EGFP and mCherry) fusion proteins expression and FRET. FtsZ expressing tusA mutant (DE3) cells showed a red mCherry signal at the cell poles, indicating that FtsZ is still in the assembling phase. Interestingly, the cellular region of EGFP-TusA fusion protein expressed in ΔtusA (DE3) was conspicuous; the EGFP signal was spread throughout the whole cell and, in addition, a slight accumulation of the EGFP-TusA fluorescence was detectable at the cell poles, the same part of the cell as for mCherry-FtsZ. Thus, this strongly suggested an interaction of TusA and FtsZ.
Furthermore, the cellular FtsZ and Fis concentrations, and their change during different growth phases were determined via immunoblotting. All tested deletion strains of mnm5s2U34 tRNA modification show high cellular FtsZ and Fis levels in the exponential phase, shifting to the later growth phases. This shift reflects the retarded growth, whereby the deletion strains reach later the exponential phase. Conclusively, the growth and cell division defect, and thus the formation of filaments, is most likely caused by changes in the cellular FtsZ and Fis concentrations.
Finally, the translation efficiencies of certain proteins (RpoS, Fur, Fis and mFis) in tusA mutant and in additional gene deletion strains were studied whether they were affected by using unmodified U34 tRNAs of Lys, Glu and Gln. The translation efficiency is decreased in mnm5s2U34 tRNA modification-impaired strains in addition to their existing growth and cell division defect due to the elimination of these three amino acids. Finally, these results confirm and reinforce the importance of Lys, Glu and Gln and the mnm5s2U34 tRNA thiolation for efficient protein translation. Thus, these findings verify that the translation of fur, fis and rpoS is regulated by mnm5s2U34 tRNA modifications, which is growth phase-dependent.
In total, this work showed the importance of the role of TusA for bacterial cell functionality and physiology. The deletion of the tusA gene disrupted a complex regulatory network within the cell, that most influenced by the decreased translation of Fis and RpoS, caused by the absence of mnm5s2U34 tRNA modifications. The disruption of RpoS and Fis cellular network influences in turn the cellular FtsZ level in the early exponential phase. Finally, the reduced FtsZ concentration leads to elongated, filamentous E. coli cells, which are unable to divide.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
The urban heat island (UHI) effect, describing an elevated temperature of urban areas compared with their natural surroundings, can expose urban dwellers to additional heat stress, especially during hot summer days. A comprehensive understanding of the UHI dynamics along with urbanization is of great importance to efficient heat stress mitigation strategies towards sustainable urban development. This is, however, still challenging due to the difficulties of isolating the influences of various contributing factors that interact with each other. In this work, I present a systematical and quantitative analysis of how urban intrinsic properties (e.g., urban size, density, and morphology) influence UHI intensity.
To this end, we innovatively combine urban growth modelling and urban climate simulation to separate the influence of urban intrinsic factors from that of background climate, so as to focus on the impact of urbanization on the UHI effect. The urban climate model can create a laboratory environment which makes it possible to conduct controlled experiments to separate the influences from different driving factors, while the urban growth model provides detailed 3D structures that can be then parameterized into different urban development scenarios tailored for these experiments. The novelty in the methodology and experiment design leads to the following achievements of our work.
First, we develop a stochastic gravitational urban growth model that can generate 3D structures varying in size, morphology, compactness, and density gradient. We compare various characteristics, like fractal dimensions (box-counting, area-perimeter scaling, area-population scaling, etc.), and radial gradient profiles of land use share and population density, against those of real-world cities from empirical studies. The model shows the capability of creating 3D structures resembling real-world cities. This model can generate 3D structure samples for controlled experiments to assess the influence of some urban intrinsic properties in question. [Chapter 2]
With the generated 3D structures, we run several series of simulations with urban structures varying in properties like size, density and morphology, under the same weather conditions. Analyzing how the 2m air temperature based canopy layer urban heat island (CUHI) intensity varies in response to the changes of the considered urban factors, we find the CUHI intensity of a city is directly related to the built-up density and an amplifying effect that urban sites have on each other. We propose a Gravitational Urban Morphology (GUM) indicator to capture the neighbourhood warming effect. We build a regression model to estimate the CUHI intensity based on urban size, urban gross building volume, and the GUM indicator. Taking the Berlin area as an example, we show the regression model capable of predicting the CUHI intensity under various urban development scenarios. [Chapter 3]
Based on the multi-annual average summer surface urban heat island (SUHI) intensity derived from Land surface temperature, we further study how urban intrinsic factors influence the SUHI effect of the 5,000 largest urban clusters in Europe. We find a similar 3D GUM indicator to be an effective predictor of the SUHI intensity of these European cities. Together with other urban factors (vegetation condition, elevation, water coverage), we build different multivariate linear regression models and a climate space based Geographically Weighted Regression (GWR) model that can better predict SUHI intensity. By investigating the roles background climate factors play in modulating the coefficients of the GWR model, we extend the multivariate linear model to a nonlinear one by integrating some climate parameters, such as the average of daily maximal temperature and latitude. This makes it applicable across a range of background climates. The nonlinear model outperforms linear models in SUHI assessment as it captures the interaction of urban factors and the background climate. [Chapter 4]
Our work reiterates the essential roles of urban density and morphology in shaping the urban thermal environment. In contrast to many previous studies that link bigger cities with higher UHI intensity, we show that cities larger in the area do not necessarily experience a stronger UHI effect. In addition, the results extend our knowledge by demonstrating the influence of urban 3D morphology on the UHI effect. This underlines the importance of inspecting cities as a whole from the 3D perspective. While urban 3D morphology is an aggregated feature of small-scale urban elements, the influence it has on the city-scale UHI intensity cannot simply be scaled up from that of its neighbourhood-scale components. The spatial composition and configuration of urban elements both need to be captured when quantifying urban 3D morphology as nearby neighbourhoods also cast influences on each other. Our model serves as a useful UHI assessment tool for the quantitative comparison of urban intervention/development scenarios. It can support harnessing the capacity of UHI mitigation through optimizing urban morphology, with the potential of integrating climate change into heat mitigation strategies.
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.
The development of seeds in angiosperms starts with a complex process of double fertilization, involving the fusion of the maternal egg cell and central cell with two paternal sperm cells. This gives rise to the embryo and the nourishing endosperm, which are then enclosed by the seed coat, derived from the maternal integuments. The growth of the seed coat in Arabidopsis thaliana (Arabidopsis) is actively inhibited before fertilization by epigenetic regulators known as Polycomb Group (PcG) proteins. These proteins deposit a repressive histone mark called H3K27me3, which must be removed to enable seed coat formation. In this thesis, I explored the mechanism of removal of H3K27me3 marks from the integument cells following fertilization, which allows for seed coat formation. We hypothesized that this removal should be primarily facilitated by histone demethylases from the JMJ family and potentially influenced by the plant hormones Brassinosteroids (BRs). This hypothesis was supported by the expression patterns of the JMJ protein REF6 and of BR related genes, which are specifically expressed in the integuments and in the seed coat. Moreover, mutations in both these pathways lead to developmental defects, such as reduced ovule viability and delayed seed coat growth. Our research provides evidence suggesting that BR signalling is likely involved in recruiting JMJ-type histone demethylases to target loci responsible for seed coat growth. Moreover, we have discovered an additional pathway through which BRs regulate seed coat development, independent of their influence on H3K27me3 marks. This finding emphasizes the diverse roles of BRs in coordinating seed development, extending beyond their well-known involvement in plant growth and development. Furthermore, I explored the role of another epigenetic mark, DNA methylation, in fertilization-independent (or autonomous) seed formation in Arabidopsis. For this, we utilized epigenetic Recombinant Inbred Lines (epiRILs) and thus identified an epigenetic Quantitative Trait Locus (epiQTL) on chromosome II, potentially responsible for the larger autonomous seed size observed in DNA methylation mutants. Overall, this thesis significantly enhances our comprehension of the intricate relationship between epigenetic modifications, hormonal signaling, and plant reproductive processes. It offers valuable insights into the genetic mechanisms governing both sexual and asexual seed formation, while also presenting potential avenues for the engineer of advantageous traits in agricultural crops.
Mountain ranges can fundamentally influence the physical and and chemical processes that shape Earths’ surface. With elevations of up to several kilometers they create climatic enclaves by interacting with atmospheric circulation and hydrologic systems, thus leading to a specific distribution of flora and fauna. As a result, the interiors of many Cenozoic mountain ranges are characterized by an arid climate, internally drained and sediment-filled basins, as well as unique ecosystems that are isolated from the adjacent humid, low-elevation regions along their flanks and forelands. These high-altitude interiors of orogens are often characterized by low relief and coalesced sedimentary basins, commonly referred to as plateaus, tectono-geomorphic entities that result from the complex interactions between mantle-driven geological and tectonic conditions and superposed atmospheric and hydrological processes. The efficiency of these processes and the fate of orogenic plateaus is therefore closely tied to the balance of constructive and destructive processes – tectonic uplift and erosion, respectively. In numerous geological studies it has been shown that mountain ranges are delicate systems that can be obliterated by an imbalance of these underlying forces. As such, Cenozoic mountain ranges might not persist on long geological timescales and will be destroyed by erosion or tectonic collapse. Advancing headward erosion of river systems that drain the flanks of the orogen may ultimately sever the internal drainage conditions and the maintenance of storage of sediments within the plateau, leading to destruction of plateau morphology and connectivity with the foreland. Orogenic collapse may be associated with the changeover from a compressional stress field with regional shortening and topographic growth, to a tensional stress field with regional extensional deformation and ensuing incision of the plateau. While the latter case is well-expressed by active extensional faults in the interior parts of the Tibetan Plateau and the Himalaya, for example, the former has been attributed to have breached the internally drained areas of the high-elevation sectors of the Iranian Plateau.
In the case of the Andes of South America and their internally drained Altiplano-Puna Plateau, signs of both processes have been previously described. However, in the orogenic collapse scenario the nature of the extensional structures had been primarily investigated in the northern and southern terminations of the plateau; in some cases, the extensional faults were even regarded to be inactive. After a shallow earthquake in 2020 within the Eastern Cordillera of Argentina that was associated with extensional deformation, the state of active deformation and the character of the stress field in the central parts of the plateau received renewed interest to explain a series of extensional structures in the northernmost sectors of the plateau in north-western Argentina. This study addresses (1) the issue of tectonic orogenic collapse of the Andes and the destruction of plateau morphology by studying the fill and erosion history of the central eastern Andean Plateau using sedimentological and geochronological data and (2) the kinematics, timing and magnitude of extensional structures that form well-expressed fault scarps in sediments of the regional San Juan del Oro surface, which is an integral part of the Andean Plateau and adjacent morphotectonic provinces to the east.
Importantly, sediment properties and depositional ages document that the San Juan del Oro Surface was not part of the internally-drained Andean Plateau, but rather associated with a foreland-directed drainage system, which was modified by the Andean orogeny and that became successively incorporated into the orogen by the eastward-migration of the Andean deformation front during late Miocene – Pliocene time. Structural and geomorphic observations within the plateau indicate that extensional processes must have been repeatedly active between the late Miocene and Holocene supporting the notion of plateau-wide extensional processes, potentially associated with Mw ~ 7 earthquakes. The close relationship between extensional joints and fault orientations underscores that 3 was oriented horizontally in NW-SE direction and 1 was vertical. This unambiguously documents that the observed deformation is related to gravitational forces that drive the orogenic collapse of the plateau. Applied geochronological analyses suggest that normal faulting in the northern Puna was active at about 3 Ma, based on paired cosmogenic nuclide dating of sediment fill units. Possibly due to regional normal faulting the drainage system within the plateau was modified, promoting fluvial incision.
Advancements in computer vision techniques driven by machine learning have facilitated robust and efficient estimation of attributes such as depth, optical flow, albedo, and shading. To encapsulate all such underlying properties associated with images and videos, we evolve the concept of intrinsic images towards intrinsic attributes. Further, rapid hardware growth in the form of high-quality smartphone cameras, readily available depth sensors, mobile GPUs, or dedicated neural processing units have made image and video processing pervasive. In this thesis, we explore the synergies between the above two advancements and propose novel image and video processing techniques and systems based on them. To begin with, we investigate intrinsic image decomposition approaches and analyze how they can be implemented on mobile devices. We propose an approach that considers not only diffuse reflection but also specular reflection; it allows us to decompose an image into specularity, albedo, and shading on a resource constrained system (e.g., smartphones or tablets) using the depth data provided by the built-in depth sensors. In addition, we explore how on-device depth data can further be used to add an immersive dimension to 2D photos, e.g., showcasing parallax effects via 3D photography. In this regard, we develop a novel system for interactive 3D photo generation and stylization on mobile devices. Further, we investigate how adaptive manipulation of baseline-albedo (i.e., chromaticity) can be used for efficient visual enhancement under low-lighting conditions. The proposed technique allows for interactive editing of enhancement settings while achieving improved quality and performance. We analyze the inherent optical flow and temporal noise as intrinsic properties of a video. We further propose two new techniques for applying the above intrinsic attributes for the purpose of consistent video filtering. To this end, we investigate how to remove temporal inconsistencies perceived as flickering artifacts. One of the techniques does not require costly optical flow estimation, while both provide interactive consistency control. Using intrinsic attributes for image and video processing enables new solutions for mobile devices – a pervasive visual computing device – and will facilitate novel applications for Augmented Reality (AR), 3D photography, and video stylization. The proposed low-light enhancement techniques can also improve the accuracy of high-level computer vision tasks (e.g., face detection) under low-light conditions. Finally, our approach for consistent video filtering can extend a wide range of image-based processing for videos.
Lanthanide based ceria nanomaterials are important practical materials due to their redox properties that are useful in technology and life sciences. This PhD thesis examined various properties and potential for catalytic and bio-applications of Ln3+-doped ceria nanomaterials. Ce1-xGdxO2-y: Eu3+, gadolinium doped ceria (GDC) (0 ≤ x ≤ 0.4) nanoparticles were synthesized by flame spray pyrolysis (FSP) and studied, followed by 15 % CexZr1-xO2-y: Eu3+|YSZ (0 ≤ x ≤ 1) nanocomposites. Furthermore, Ce1-xYb xO2-y (0.004 ≤ x ≤ 0.22) nanoparticles were synthesized by thermal decomposition and characterized. Finally, CeO2-y: Eu3+ nanoparticles were synthesized by a microemulsion method, biofunctionalized and characterized. The studies undertaken presents a novel approach to structurally elucidate ceria-based nanomaterials by way of Eu3+ and Yb3+ spectroscopy and processing the spectroscopic data with the multi-way decomposition method PARAFAC. Data sets of the three variables: excitation wavelength, emission wavelength and time were used to perform the deconvolution of spectra.
GDC nanoparticles from FSP are nano-sized and of roughly cubic shape and crystal structure (Fm3̅m). Raman data revealed four vibrational modes exhibited by Gd3+ containing samples whereas CeO2-y: Eu3+ displays only two. The room temperature, time-resolved emission spectra recorded at λexcitation = 464 nm show that Gd3+ doping results in significantly altered emission spectra compared to pure ceria. The PARAFAC analysis for the pure ceria samples reveals two species; a high-symmetry species and a low-symmetry species. The GDC samples yield two low-symmetry spectra in the same experiment. High-resolution emission spectra recorded at 4 K after probing the 5D0-7F0 transition revealed additional variation in the low symmetry Eu3+ sites in pure ceria and GDC. The data of the Gd3+-containing samples indicates that the average charge density around the Eu3+ ions in the lattice is inversely related to Gd3+ and oxygen vacancy concentration.
The particle crystallites of the 773 K and 1273 K annealed Yb3+ -ceria nanostructure materials are nano-sized and have a cubic fluorite structure with four Raman vibrational modes. Elemental maps clearly show that cluster formation occurs for 773 K annealed with high Yb3+ ion concentration from 15 mol % in the ceria lattice. These clusters are destroyed with annealing to 1273 K. The emission spectra observed from room temperature and 4 K measurements for the Ce1-xYb xO2-y samples have a manifold that corresponds to the 2F5/2-2F7/2 transition of Yb3+ ions. Some small shifts are observed in the Stark splitting pattern and are induced by the variations of the crystal field influenced by where the Yb3+ ions are located in the crystal lattices in the samples. Upon mixing ceria with high Yb3+ concentrations, the 2F5/2-2F7/2 transition is also observed in the Stark splitting pattern, but the spectra consist of two broad high background dominated peaks. Annealing the nanomaterials at 1273 K for 2 h changes the spectral signature as new peaks emerge. The deconvolution yielded luminescence decay kinetics as well as the accompanying luminescence spectra of three species for each of the low Yb3+ doped ceria samples annealed at 773 K and one species for the 1273 K annealed samples. However, the ceria samples with high Yb3+ concentration annealed at the two temperatures yielded one species with lower decay times as compared to the Yb3+ doped ceria samples after PARAFAC analysis.
Through the calcination of the nanocomposites at two high temperatures, the evolution of the emission patterns from specific Eu3+ lattice sites to indicate structural changes for the nanocomposites was followed. The spectroscopy results effectively complemented the data obtained from the conventional techniques. Annealing the samples at 773 K, resulted in amorphous, unordered domains whereas the TLS of the 1273 K nanocomposites reveal two distinct sites, with most red shifted Eu3+ species coming from pure Eu3+ doped ZrO2 on the YSZ support.
Finally, for Eu3+ doped ceria, successful transfer from hydrophobic to water phase and subsequent biocompatibility was achieved using ssDNA. PARAFAC analysis for the Eu3+ in nanoparticles dispersed in toluene and water revealed one Eu3+ species, with slightly differing surface properties for the nanoparticles as far as the luminescence kinetics and solvent environments were concerned. Several functionalized nanoparticles conjugated onto origami triangles after hybridization were visualized by atomic force microscopy (AFM). Putting all into consideration, Eu3+ and Yb3+ spectroscopy was used to monitor the structural changes and determining the feasibility of the nanoparticle transfer into water. PARAFAC proves to be a powerful tool to analyze lanthanide spectra in crystalline solid materials and in solutions, which are characterized by numerous Stark transitions and where measurements usually yield a superposition of different emission contributions to any given spectrum.
Earthquake modeling is the key to a profound understanding of a rupture. Its kinematics or dynamics are derived from advanced rupture models that allow, for example, to reconstruct the direction and velocity of the rupture front or the evolving slip distribution behind the rupture front. Such models are often parameterized by a lattice of interacting sub-faults with many degrees of freedom, where, for example, the time history of the slip and rake on each sub-fault are inverted. To avoid overfitting or other numerical instabilities during a finite-fault estimation, most models are stabilized by geometric rather than physical constraints such as smoothing.
As a basis for the inversion approach of this study, we build on a new pseudo-dynamic rupture model (PDR) with only a few free parameters and a simple geometry as a physics-based solution of an earthquake rupture. The PDR derives the instantaneous slip from a given stress drop on the fault plane, with boundary conditions on the developing crack surface guaranteed at all times via a boundary element approach. As a side product, the source time function on each point on the rupture plane is not constraint and develops by itself without additional parametrization. The code was made publicly available as part of the Pyrocko and Grond Python packages. The approach was compared with conventional modeling for different earthquakes. For example, for the Mw 7.1 2016 Kumamoto, Japan, earthquake, the effects of geometric changes in the rupture surface on the slip and slip rate distributions could be reproduced by simply projecting stress vectors. For the Mw 7.5 2018 Palu, Indonesia, strike-slip earthquake, we also modelled rupture propagation using the 2D Eikonal equation and assuming a linear relationship between rupture and shear wave velocity. This allowed us to give a deeper and faster propagating rupture front and the resulting upward refraction as a new possible explanation for the apparent supershear observed at the Earth's surface.
The thesis investigates three aspects of earthquake inversion using PDR: (1) to test whether implementing a simplified rupture model with few parameters into a probabilistic Bayesian scheme without constraining geometric parameters is feasible, and whether this leads to fast and robust results that can be used for subsequent fast information systems (e.g., ground motion predictions). (2) To investigate whether combining broadband and strong-motion seismic records together with near-field ground deformation data improves the reliability of estimated rupture models in a Bayesian inversion. (3) To investigate whether a complex rupture can be represented by the inversion of multiple PDR sources and for what type of earthquakes this is recommended.
I developed the PDR inversion approach and applied the joint data inversions to two seismic sequences in different tectonic settings. Using multiple frequency bands and a multiple source inversion approach, I captured the multi-modal behaviour of the Mw 8.2 2021 South Sandwich subduction earthquake with a large, curved and slow rupturing shallow earthquake bounded by two faster and deeper smaller events. I could cross-validate the results with other methods, i.e., P-wave energy back-projection, a clustering analysis of aftershocks and a simple tsunami forward model.
The joint analysis of ground deformation and seismic data within a multiple source inversion also shed light on an earthquake triplet, which occurred in July 2022 in SE Iran. From the inversion and aftershock relocalization, I found indications for a vertical separation between the shallower mainshocks within the sedimentary cover and deeper aftershocks at the sediment-basement interface. The vertical offset could be caused by the ductile response of the evident salt layer to stress perturbations from the mainshocks.
The applications highlight the versatility of the simple PDR in probabilistic seismic source inversion capturing features of rather different, complex earthquakes. Limitations, as the evident focus on the major slip patches of the rupture are discussed as well as differences to other finite fault modeling methods.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
Conservation of the jaguar relies on holistic and transdisciplinary conservation strategies that integratively safeguard essential, connected habitats, sustain viable populations and their genetic exchange, and foster peaceful human-jaguar coexistence. These strategies define four research priorities to advance jaguar conservation throughout the species’ range. In this thesis I provide several relevant ecological and sociological insights into these research priorities, each addressed in a separate chapter. I focus on the effects of anthropogenic landscapes on jaguar habitat use and population gene flow, spatial patterns of jaguar habitat suitability and functional population connectivity, and on innovative governance approaches which can work synergistically to help achieve human-wildlife conviviality. Furthermore, I translate these insights into recommendations for conservation practice by providing tools and suggestions that conservation managers and stakeholders can use to implement local actions but also make broad scale conservation decisions in Central America. In Chapter 2, I model regional habitat use of jaguars, producing spatially-explicit maps for management of key areas of habitat suitability. Using an occupancy model of 13-year-camera-trap occurrence data, I show that human influence has the strongest impact on jaguar habitat use, and that Jaguar Conservation Units are the most important reservoirs of high quality habitat in this region. I build upon these results by zooming in to an area of high habitat suitability loss in Chapter 3, northern Central America. Here I study the drivers of jaguar gene flow and I produce spatially-explicit maps for management of key areas of functional population connectivity in this region. I use microsatellite data and pseudo-optimized multiscale, multivariate resistance surfaces of gene flow to show that jaguar gene flow is influenced by environmental, and even more strongly, by human influence variables; and that the areas of lowest gene flow resistance largely coincide with the location of the Jaguar Conservation Units. Given that human activities significantly impact jaguar habitat use and gene flow, securing viable jaguar populations in anthropogenic landscapes also requires fostering peaceful human-wildlife coexistence. This is a complex challenge that cannot be met without transdisciplinary academic research and cross-sectoral, collaborative governance structures that effectively respond to the multiple challenges of such coexistence. With this in mind, I focus in Chapter 4 on carnivore conservation initiatives that apply transformative governance approaches to enact transformative change towards human-carnivore coexistence. Using the frameworks of transformative biodiversity governance and convivial conservation, I highlight in this chapter concrete pathways, supported by more inclusive, democratic forms of conservation decision-making and participation that promote truly transformative changes towards human-jaguar conviviality.
Feminist Solidarities after Modulation produces an intersectional analysis of transnational feminist movements and their contemporary digital frameworks of identity and solidarity. Engaging media theory, critical race theory, and Black feminist theory, as well as contemporary feminist movements, this book argues that digital feminist interventions map themselves onto and make use of the multiplicity and ambiguity of digital spaces to question presentist and fixed notions of the internet as a white space and technologies in general as objective or universal. Understanding these frameworks as colonial constructions of the human, identity is traced to a socio-material condition that emerges with the modernity/colonialism binary. In the colonial moment, race and gender become the reasons for, as well as the effects of, technologies of identification, and thus need to be understood as and through technologies. What Deleuze has called modulation is not a present modality of control, but is placed into a longer genealogy of imperial division, which stands in opposition to feminist, queer, and anti-racist activism that insists on non-modular solidarities across seeming difference. At its heart, Feminist Solidarities after Modulation provides an analysis of contemporary digital feminist solidarities, which not only work at revealing the material histories and affective ""leakages"" of modular governance, but also challenges them to concentrate on forms of political togetherness that exceed a reductive or essentialist understanding of identity, solidarity, and difference.
Strings of words can correspond to more than one interpretation or underlying structure, which makes them ambiguous. Prosody can be used to resolve this structural ambiguity. This dissertation investigates the use of prosodic cues in the domains of fundamental frequency (f0) and duration to disambiguate between two interpretations of ambiguous structures when speakers addressed different interlocutors. The dissertation comprises of three production studies and one comprehension study.
Prosodic disambiguation was studied with a focus on German name sequences of three names (coordinates) in two conditions: without (Name1 and Name2 and Name3) and with internal grouping of the first two names ([Name1 and Name2] and Name3). The study of coordinates was complemented with production data of locally ambiguous sentences with a case-ambiguous first noun phrase.
Variability was studied in a controlled setting: Productions were elicited with a within-subject manipulation of context in a referential communication task in order to evoke prosodic adaptations to different conversational contexts. Context had five levels and involved interlocutors in three age groups (child, young adult, elderly adult) with German as L1 in the absence of background white noise, the young adult with background white noise, and a young adult without German as L1. Variability was explored at different levels: within a group of young individuals (intra-group level), within and between young individuals (intra-individual level and inter-individual level, respectively), and comparing between the group of young and a group of older speakers (inter-group level).
Our data replicate the use of the three prosodic cues (f0-movement, final lengthening, and pause) in productions of young adult speakers and extend their use to productions of older adult speakers. Both age groups distinguished consistently between the two coordinate conditions. Prosodic grouping in production was evident not only on the group-final Name2 but also at earlier stages in the utterance, on the group-internal Name1 (early cues). For some speakers, some listeners were able to decode these early cues effectively as they were able to reliably predict the upcoming structure after listening to Name1 only. Thus, prosodic grouping appears as a globally marked phenomenon building up along the utterance. The internal structure of coordinates was disambiguated irrespective of the conversational context. In our data, speakers only slightly modified the prosodic cues marking the disambiguation in the different contexts. Listeners were unable to identify to which interlocutor the sequence had been produced. We interpret this intra-individual consistency in the production of disambiguating prosodic cues as support for a strong link between prosody and syntax. The findings support models in favour of situational independence of disambiguating prosody. All speakers reliably marked the distinction between the grouping conditions with at least one of the three prosodic cues investigated and most of the speakers used at least two of these cues. Further, individual differences in prosodic grouping did not lead to difficulties in recovering the grouping in comprehension. Taken together, these findings support the existence of a phonological category of prosodic grouping.
Characterization of the role of stress - responsive NAC transcription factors ANAC055 and ATAF1
(2022)
Starch is a biopolymer for which, despite its simple composition, understanding the precise mechanism behind its formation and regulation has been challenging. Several approaches and bioanalytical tools can be used to expand the knowledge on the different parts involved in the starch metabolism. In this sense, a comprehensive analysis targeting two of the main groups of molecules involved in this process: proteins, as effectors/regulators of the starch metabolism, and maltodextrins as starch components and degradation products, was conducted in this research work using potato plants (Solanum tuberosum L. cv. Desiree) as model of study. On one side, proteins physically interacting to potato starch were isolated and analyzed through mass spectrometry and western blot for their identification. Alternatively, starch interacting proteins were explored in potato tubers from transgenic plants having antisense inhibition of starch-related enzymes and on tubers stored under variable environmental conditions. Most of the proteins recovered from the starch granules corresponded to previously described proteins having a specific role in the starch metabolic pathway. Another set of proteins could be grouped as protease inhibitors, which were found weakly interacting to starch. Variations in the protein profile obtained after electrophoresis separation became clear when tubers were stored under different temperatures, indicating a differential expression of proteins in response to changing environmental conditions.
On the other side, since maltodextrin metabolism is thought to be involved in both starch initiation and degradation, soluble maltooligosaccharide content in potato tubers was analyzed in this work under diverse experimental variables. For this, tuber disc samples from wild type and transgenic lines strongly repressing either the plastidial or cytosolic form of the -glucan phosphorylase and phosphoglucomutase were incubated with glucose, glucose-6-phosphate, and glucose-1-phosphate solutions to evaluate the influence of such enzymes on the conversion of the carbon sources into soluble maltodextrins, in comparison to wild-type samples. Relative maltodextrin amounts analyzed through capillary electrophoresis equipped with laser-induced fluorescence (CE-LIF) revealed that tuber discs could immediately uptake glucose-1-phosphate and use it to produce maltooligosaccharides with a degree of polymerization of up to 30 (DP30), in contrast to transgenic tubers with strong repression of the plastidial glucan phosphorylase. The results obtained from the maltodextrin analysis support previous indications that a specific transporter for glucose-1-phosphate may exist in both the plant cells and the plastidial membranes, thereby allowing a glucose-6-phosphate independent transport. Furthermore, it confirms that the plastidial glucan phosphorylase is responsible for producing longer maltooligosaccharides in the plastids by catalyzing a glucan polymerization reaction when glucose-1-phosphate is available. All these findings contribute to a better understanding of the role of the plastidial glucan phosphorylase as a key enzyme directly involved in the synthesis and degradation of glucans and their implication on starch metabolism.
The deformation style of mountain belts is greatly influenced by the upper plate architecture created during preceding deformation phases. The Mesozoic Salta Rift extensional phase has created a dominant structural and lithological framework that controls Cenozoic deformation and exhumation patterns in the Central Andes. Studying the nature of these pre-existing anisotropies is a key to understanding the spatiotemporal distribution of exhumation and its controlling factors. The Eastern Cordillera in particular, has a structural grain that is in part controlled by Salta Rift structures and their orientation relative to Andean shortening. As a result, there are areas in which Andean deformation prevails and areas where the influence of the Salta Rift is the main control on deformation patterns.
Between 23 and 24°S, lithological and structural heterogeneities imposed by the Lomas de Olmedo sub-basin (Salta Rift basin) affect the development of the Eastern Cordillera fold-and-thrust belt. The inverted northern margin of the sub-basin now forms the southern boundary of the intermontane Cianzo basin. The former western margin of the sub-basin is located at the confluence of the Subandean Zone, the Santa Barbara System and the Eastern Cordillera. Here, the Salta Rift basin architecture is responsible for the distribution of these morphotectonic provinces. In this study we use a multi-method approach consisting of low-temperature (U-Th-Sm)/He and apatite fission track thermochronology, detrital geochronology, structural and sedimentological analyses to investigate the Mesozoic structural inheritance of the Lomas de Olmedo sub-basin and Cenozoic exhumation patterns.
Characterization of the extension-related Tacurú Group as an intermediate succession between Paleozoic basement and the syn-rift infill of the Lomas de Olmedo sub-basin reveals a Jurassic maximum depositional age. Zircon (U-Th-Sm)/He cooling ages record a pre-Cretaceous onset of exhumation for the rift shoulders in the northern part of the sub-basin, whereas the western shoulder shows a more recent onset (140–115 Ma). Variations in the sedimentary thickness of syn- and post-rift strata document the evolution of accommodation space in the sub-basin. While the thickness of syn-rift strata increases rapidly toward the northern basin margin, the post-rift strata thickness decreases toward the margin and forms a condensed section on the rift shoulder.
Inversion of Salta Rift structures commenced between the late Oligocene and Miocene (24–15 Ma) in the ranges surrounding the Cianzo basin. The eastern and western limbs of the Cianzo syncline, located in the hanging wall of the basin-bounding Hornocal fault, show diachronous exhumation. At the same time, western fault blocks of Tilcara Range, south of the Cianzo basin, began exhuming in the late Oligocene to early Miocene (26–16 Ma). Eastward propagation to the frontal thrust and to the Paleozoic strata east of the Tilcara Range occurred in the middle Miocene (22–10 Ma) and the late Miocene–early Pliocene (10–4 Ma), respectively.
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 present work focuses on the preparation and characterisation of various nanoplastic reference material candidates. Nanoplastics are plastic particles in a size range of 1 − 1000 nm. The term has emerged in recent years as a distinction from the larger microplastic (1 − 1000 μm). Since the properties of the two plastic particles differ significantly due to their size, it is important to have nanoplastic reference material. This was produced for the polymer types polypropylene (PP) and polyethylene (PE) as well as poly(lactic acid) (PLA).
A top-down method was used to produce the nanoplastic for the polyolefins PP and PE (Section 3.1). The material was crushed in acetone using an Ultra-Turrax disperser and then transferred to water. This process produces reproducible results when repeated, making it suitable for the production of a reference material candidate. The resulting dispersions were investigated using dynamic and electrophoretic light scattering. The dispersion of PP particles gave a mean hydrodynamic diameter Dh = 180.5±5.8 nm with a PDI = 0.08±0.02 and a zeta potential ζ = −43.0 ± 2.0 mV. For the PE particles, a diameter Dh = 344.5 ± 34.6 nm, with a PDI = 0.39 ± 0.04 and a zeta potential of ζ = −40.0 ± 4.2 mV was measured. This means that both dispersions are nanoplastics, as the particles are < 1000 nm. Furthermore, the starting material of these polyolefin particles was mixed with a gold salt and thereby the nanoplastic production was repeated in order to obtain nanoplastic particles doped with gold, which should simplify the detection of the particles.
In addition to the top-down approach, a bottom-up method was chosen for the PLA (Section 3.2). Here, the polymer was first dissolved in THF and stabilised with a surfactant. Then water was added and THF evaporated, leaving an aqueous PLA dispersion. This experiment was also investigated using dynamic light scattering and, when repeated, yielded reproducible results, i. e. an average hydrodynamic diameter of Dh = 89.2 ± 3.0 nm. Since the mass concentration of PLA in the dispersion is known due to the production method, a Python notebook was tested for these samples to calculate the number and mass concentration of nano(plastic) particles using the MALS results. Similar to the plastic produced in Section 3.1, gold was also incorporated into the particle, which was achieved by adding a dispersion of gold clusters with a diameter of D = 1.15 nm in an ionic liquid (IL) in the production process. Here, the preparation of the gold clusters in the ionic liquid 1-ethyl-3-methylimidazolium dicyanamide ([Emim][DCA]) represented the first use of an IL both as a reducing agent for gold and as a solvent for the gold clusters. Two volumes of gold cluster dispersion were added during the PLA particle synthesis. The addition of the gold clusters leads to much larger particles. The nanoPLA with 0.8% Au has a diameter of Dh = 198.0 ± 10.8 nm and the nanoPLA with 4.9% Au has a diameter of Dh = 259.1 ± 23.7 nm. First investigations by TEM imaging show that the nanoPLA particles form hollow spheres when gold clusters are added. However, the mechanism leading to these structures remains unclear.
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.
Stars under influence: evidence of tidal interactions between stars and substellar companions
(2023)
Tidal interactions occur between gravitationally bound astrophysical bodies. If their spatial separation is sufficiently small, the bodies can induce tides on each other, leading to angular momentum transfer and altering of evolutionary path the bodies would have followed if they were single objects. The tidal processes are well established in the Solar planet-moon systems and close stellar binary systems. However, how do stars behave if they are orbited by a substellar companion (e.g. a planet or a brown dwarf) on a tight orbit?
Typically, a substellar companion inside the corotation radius of a star will migrate toward the star as it loses orbital angular momentum. On the other hand, the star will gain angular momentum which has the potential to increase its rotation rate. The effect should be more pronounced if the substellar companion is more massive. As the stellar rotation rate and the magnetic activity level are coupled, the star should appear more magnetically active under the tidal influence of the orbiting substellar companion. However, the difficulty in proving that a star has a higher magnetic activity level due to tidal interactions lies in the fact that (I) substellar companions around active stars are easier to detect if they are more massive, leading to a bias toward massive companions around active stars and mimicking the tidal interaction effect, and that (II) the age of a main-sequence star cannot be easily determined, leaving the possibility that a star is more active due to its young age.
In our work, we overcome these issues by employing wide stellar binary systems where one star hosts a substellar companion, and where the other star provides the magnetic activity baseline for the host star, assuming they have coevolved, and thereby provides the host's activity level if tidal interactions have no effect on it. Firstly, we find that extrasolar planets can noticeably increase the host star's X-ray luminosity and that the effect is more pronounced if the exoplanet is at least Jupiter-like in mass and close to the star. Further, we find that a brown dwarf will have an even stronger effect, as expected, and that the X-ray surface flux difference between the host star and the wide stellar companion is a significant outlier when compared to a large sample of similar wide binary systems without any known substellar companions. This result proves that substellar hosting wide binary systems can be good tools to reveal the tidal effect on host stars, and also show that the typical stellar age indicators as activity or rotation cannot be used for these stars. Finally, knowing that the activity difference is a good tracer of the substellar companion's tidal impact, we develop an analytical method to calculate the modified tidal quality factor Q' of individual host stars, which defines the tidal dissipation efficiency in the convective envelope of a given main-sequence star.
This dissertation focuses on the understanding of the optical manipulation of microgels dispersed in aqueous solution of azobenzene containing surfactant. The work consists of three parts where each part is a systematic investigation of the (1) photo-isomerization kinetics of the surfactant in complex with the microgel polymer matrix, (2) light driven diffusiosmosis (LDDO) in microgels and (3) photo-responsivity of microgel on complexation with spiropyran.
The first part comprises three publications where the first one [P1] investigates the photo-isomerization kinetics and corresponding isomer composition at a photo-stationary state of the photo-sensitive surfactant conjugated with charged polymers or micro sized polymer networks to understand the structural response of such photo-sensitive complexes. We report that the photo-isomerization of the azobenzene-containing cationic surfactant is slower in a polymer complex compared to being purely dissolved in an aqueous solution. The surfactant aggregates near the polyelectrolyte chains at concentrations much lower than the bulk critical micelle concentration. This, along with the inhibition of the photo-isomerization kinetics due to steric hindrance within the densely packed aggregates, pushes the isomer-ratio to a higher trans-isomer concentration for all irradiation wavelengths.
The second publication [P2] combines experimental results and non-adiabatic dynamic simulations for the same surfactant molecules embedded in the micelles with absorption spectroscopy measurements of micellar solutions to uncover the reasons responsible for the slowdown in photo induced trans → cis azobenzene isomerization at concentrations higher than the critical micelle concentration (CMC). The simulations reveal a decrease of isomerization quantum yields for molecules inside the micelles and observes a reduction of extinction coefficients upon micellization. These findings explain the deceleration of the trans → cis switching in micelles of the azobenzene-containing surfactants.
Finally, the third publication [P3] focusses on the kinetics of adsorption and desorption of the same surfactant within anionic microgels in the dark and under continuous irradiation. Experimental data demonstrate, that microgels can serve as a selective absorber of the trans isomers. The interaction of the isomers with the gel matrix induces a remotely controllable collapse or swelling on appropriate irradiation wavelengths. Measuring the kinetics of the microgel size response and knowing the exact isomer composition under light exposure, we calculate the adsorption rate of the trans-isomers.
The second part comprises two publications. The first publication [P4] reports on the phenomenon of light-driven diffusioosmotic (DO) long-range attractive and repulsive interactions between micro-sized objects, whose range extends several times the size of microparticles and can be adjusted to point towards or away from the particle by varying irradiation parameters such as intensity or wavelength of light. The phenomenon is fueled by the aforementioned photosensitive surfactant. The complex interaction of dynamic exchange of isomers and photo-isomerization rate yields to relative concentrations gradients of the isomers in the vicinity of micro-sized object inducing a local diffusioosmotic (DO) flow thereby making a surface act as a micropump.
The second publication [P5] exclusively aims the visualization and investigation of the DO flows generated from microgels by using small tracer particles. Similar to micro sized objects, the flow is able to push adjacent tracers over distances several times larger than microgel size. Here we report that the direction and the strength of the l-LDDO depends on the intensity, irradiation wavelength and the amount of surfactant adsorbed by the microgel. For example, the flow pattern around a microgel is directed radially outward and can be maintained quasi-indefinitely under exposure at 455 nm when the trans:cis ratio is 2:1, whereas irradiation at 365 nm, generates a radially transient flow pattern, which inverts at lower intensities.
Lastly, the third part consists of one publication [P6] which, unlike the previous works, reports on the study of the kinetics of photo- and thermo-switching of a new surfactant namely, spiropyran, upon exposure with light of different wavelengths and its interaction with p(NIPAM-AA) microgels. The surfactant being an amphiphile, switches between its ring closed spiropyran (SP) form and ring open merocyanine (MC) form which results in a change in the hydrophilic–hydrophobic balance of the surfactant as MC being a zwitterionic form along with the charged head group, generates three charges on the molecule. Therefore, the MC form of the surfactant is more hydrophilic than in the case of the neutral SP state. Here, we investigate the initial shrinkage of the gel particles via charge compensation on first exposure to SP molecules which results from the complex formation of the molecules with the gel matrix, triggering them to become photo responsive. The size and VPTT of the microgels during irradiation is shown to be a combination of heating up of the solution during light absorption by the surfactant (more pronounced in the case of UV irradiation) and the change in the hydrophobicity of the surfactant.
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.
Traditionally, mental disorders have been identified based on specific symptoms and standardized diagnostic systems such as the DSM-5 and ICD-10. However, these symptom-based definitions may only partially represent neurobiological and behavioral research findings, which could impede the development of targeted treatments. A transdiagnostic approach to mental health research, such as the Research Domain Criteria (RDoC) approach, maps resilience and broader aspects of mental health to associated components. By investigating mental disorders in a transnosological way, we can better understand disease patterns and their distinguishing and common factors, leading to more precise prevention and treatment options.
Therefore, this dissertation focuses on (1) the latent domain structure of the RDoC approach in a transnosological sample including healthy controls, (2) its domain associations to disease severity in patients with anxiety and depressive disorders, and (3) an overview of the scientific results found regarding Positive (PVS) and Negative Valence Systems (NVS) associated with mood and anxiety disorders.
The following main results were found: First, the latent RDoC domain structure for PVS and NVS, Cognitive Systems (CS), and Social Processes (SP) could be validated using self-report and behavioral measures in a transnosological sample. Second, we found transdiagnostic and disease-specific associations between those four domains and disease severity in patients with depressive and anxiety disorders. Third, the scoping review showed a sizable amount of RDoC research conducted on PVS and NVS in mood and anxiety disorders, with research gaps for both domains and specific conditions.
In conclusion, the research presented in this dissertation highlights the potential of the transnosological RDoC framework approach in improving our understanding of mental disorders. By exploring the latent RDoC structure and associations with disease severity and disease-specific and transnosological associations for anxiety and depressive disorders, this research provides valuable insights into the full spectrum of psychological functioning. Additionally, this dissertation highlights the need for further research in this area, identifying both RDoC indicators and research gaps. Overall, this dissertation represents an important contribution to the ongoing efforts to improve our understanding and the treatment of mental disorders, particularly within the commonly comorbid disease spectrum of mood and anxiety disorders.
Digitalisation in industry – also called “Industry 4.0” – is seen by numerous actors as an opportunity to reduce the environmental impact of the industrial sector. The scientific assessments of the effects of digitalisation in industry on environmental sustainability, however, are ambivalent. This cumulative dissertation uses three empirical studies to examine the expected and observed effects of digitalisation in industry on environmental sustainability. The aim of this dissertation is to identify opportunities and risks of digitalisation at different system levels and to derive options for action in politics and industry for a more sustainable design of digitalisation in industry. I use an interdisciplinary, socio-technical approach and look at selected countries of the Global South (Study 1) and the example of China (all studies). In the first study (section 2, joint work with Marcel Matthess), I use qualitative content analysis to examine digital and industrial policies from seven different countries in Africa and Asia for expectations regarding the impact of digitalisation on sustainability and compare these with the potentials of digitalisation for sustainability in the respective country contexts. The analysis reveals that the documents express a wide range of vague expectations that relate more to positive indirect impacts of information and communication technology (ICT) use, such as improved energy efficiency and resource management, and less to negative direct impacts of ICT, such as electricity consumption through ICT. In the second study (section 3, joint work with Marcel Matthess, Grischa Beier and Bing Xue), I conduct and analyse interviews with 18 industry representatives of the electronics industry from Europe, Japan and China on digitalisation measures in supply chains using qualitative content analysis. I find that while there are positive expectations regarding the effects of digital technologies on supply chain sustainability, their actual use and observable effects are still limited. Interview partners can only provide few examples from their own companies which show that sustainability goals have already been pursued through digitalisation of the supply chain or where sustainability effects, such as resource savings, have been demonstrably achieved. In the third study (section 4, joint work with Peter Neuhäusler, Melissa Dachrodt and Marcel Matthess), I conduct an econometric panel data analysis. I examine the relationship between the degree of Industry 4.0, energy consumption and energy intensity in ten manufacturing sectors in China between 2006 and 2019. The results suggest that overall, there is no significant relationship between the degree of Industry 4.0 and energy consumption or energy intensity in manufacturing sectors in China. However, differences can be found in subgroups of sectors. I find a negative correlation of Industry 4.0 and energy intensity in highly digitalised sectors, indicating an efficiency-enhancing effect of Industry 4.0 in these sectors. On the other hand, there is a positive correlation of Industry 4.0 and energy consumption for sectors with low energy consumption, which could be explained by the fact that digitalisation, such as the automation of previously mainly labour-intensive sectors, requires energy and also induces growth effects. In the discussion section (section 6) of this dissertation, I use the classification scheme of the three levels macro, meso and micro, as well as of direct and indirect environmental effects to classify the empirical observations into opportunities and risks, for example, with regard to the probability of rebound effects of digitalisation at the three levels. I link the investigated actor perspectives (policy makers, industry representatives), statistical data and additional literature across the system levels and consider political economy aspects to suggest fields of action for more sustainable (digitalised) industries. The dissertation thus makes two overarching contributions to the academic and societal discourse. First, my three empirical studies expand the limited state of research at the interface between digitalisation in industry and sustainability, especially by considering selected countries in the Global South and the example of China. Secondly, exploring the topic through data and methods from different disciplinary contexts and taking a socio-technical point of view, enables an analysis of (path) dependencies, uncertainties, and interactions in the socio-technical system across different system levels, which have often not been sufficiently considered in previous studies. The dissertation thus aims to create a scientifically and practically relevant knowledge basis for a value-guided, sustainability-oriented design of digitalisation in industry.
Functional characterization of ROS-responsive genes, ANAC085 and ATR7, in Arabidopsis thaliana
(2023)
Individuals with aphasia vary in the speed and accuracy they perform sentence comprehension tasks. Previous results indicate that the performance patterns of individuals with aphasia vary between tasks (e.g., Caplan, DeDe, & Michaud, 2006; Caplan, Michaud, & Hufford, 2013a). Similarly, it has been found that the comprehension performance of individuals with aphasia varies between homogeneous test sentences within and between sessions (e.g., McNeil, Hageman, & Matthews, 2005). These studies ascribed the variability in the performance of individuals with aphasia to random noise. This conclusion would be in line with an influential theory on sentence comprehension in aphasia, the resource reduction hypothesis (Caplan, 2012). However, previous studies did not directly compare variability in language-impaired and language-unimpaired adults. Thus, it is still unclear how the variability in sentence comprehension differs between individuals with and without aphasia. Furthermore, the previous studies were exclusively carried out in English. Therefore, the findings on variability in sentence processing in English still need to be replicated in a different language.
This dissertation aims to give a systematic overview of the patterns of variability in sentence comprehension performance in aphasia in German and, based on this overview, to put the resource reduction hypothesis to the test. In order to reach the first aim, variability was considered on three different dimensions (persons, measures, and occasions) following the classification by Hultsch, Strauss, Hunter, and MacDonald (2011). At the dimension of persons, the thesis compared the performance of individuals with aphasia and language-unimpaired adults. At the dimension of measures, this work explored the performance across different sentence comprehension tasks (object manipulation, sentence-picture matching). Finally, at the dimension of occasions, this work compared the performance in each task between two test sessions. Several methods were combined to study variability to gain a large and diverse database. In addition to the offline comprehension tasks, the self-paced-listening paradigm and the visual world eye-tracking paradigm were used in this work.
The findings are in line with the previous results. As in the previous studies, variability in sentence comprehension in individuals with aphasia emerged between test sessions and between tasks. Additionally, it was possible to characterize the variability further using hierarchical Bayesian models. For individuals with aphasia, it was shown that both between-task and between-session variability are unsystematic. In contrast to that, language-unimpaired individuals exhibited systematic differences between measures and between sessions. However, these systematic differences occurred only in the offline tasks. Hence, variability in sentence comprehension differed between language-impaired and language-unimpaired adults, and this difference could be narrowed down to the offline measures.
Based on this overview of the patterns of variability, the resource reduction hypothesis was evaluated. According to the hypothesis, the variability in the performance of individuals with aphasia can be ascribed to random fluctuations in the resources available for sentence processing. Given that the performance of the individuals with aphasia varied unsystematically, the results support the resource reduction hypothesis. Furthermore, the thesis proposes that the differences in variability between language-impaired and language-unimpaired adults can also be explained by the resource reduction hypothesis. More specifically, it is suggested that the systematic changes in the performance of language-unimpaired adults are due to decreasing fluctuations in available processing resources. In parallel, the unsystematic variability in the performance of individuals with aphasia could be due to constant fluctuations in available processing resources. In conclusion, the systematic investigation of variability contributes to a better understanding of language processing in aphasia and thus enriches aphasia research.
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.
Aptamers are single-stranded DNA (ssDNA) or RNA molecules that can bind specifically and with high affinity to target molecules due to their unique three-dimensional structure. For this reason, they are often compared to antibodies and sometimes even referred to as “chemical antibodies”. They are simple and inexpensive to synthesize, easy to modify, and smaller than conventional antibodies. Enzymes, especially hydrolases, are interesting targets in this context. This class of enzymes is capable of hydrolytically cleaving various macromolecules such as proteins, as well as smaller molecules such as antibiotics. Hence, they play an important role in many biological processes including diseases and their treatment. Hydrolase detection as well as the understanding of their function is therefore of great importance for diagnostics and therapy. Due to their various desirable features compared to antibodies, aptamers are being discussed as alternative agents for analytical and diagnostic use in various applications. The use of aptamers in therapy is also frequently investigated, as the binding of aptamers can have effects on the catalytic activity, protein-protein interactions, or proteolytic cascades. Aptamers are generated by an in vitro selection process. Potential aptamer candidates are selected from a pool of enriched nucleic acid sequences with affinity to the target, and their binding affinity and specificity is investigated. This is one of the most important steps in aptamer generation to obtain specific aptamers with high affinity for use in analytical and diagnostic applications. The binding properties or binding domains and their effects on enzyme functions form the basis for therapeutic applications.
In this work, the binding properties of DNA aptamers against two different hydrolases were investigated. In view of their potential utility for analytical methods, aptamers against human urokinase (uPA) and New Delhi metallo-β-lactamase-1 (NDM-1) were evaluated for their binding affinity and specificity using different methods. Using the uPA aptamers, a protocol for measuring the binding kinetics of an aptamer-protein-interaction by surface plasmon resonance spectroscopy (SPR) was developed. Based on the increased expression of uPA in different types of cancer, uPA is discussed as a prognostic and diagnostic tumor marker. As uPA aptamers showed different binding sites on the protein, microtiter plate-based aptamer sandwich assay systems for the detection of uPA were developed. Because of the function of urokinase in cancer cell proliferation and metastasis, uPA is also discussed as a therapeutic target. In this regard, the different binding sites of aptamers showed different effects on uPA function. In vitro experiments demonstrated both inhibition of uPA binding to its receptor as well as the inhibition of uPA catalytic activity for different aptamers. Thus, in addition to their specificity and affinity for their targets, the utility of the aptamers for potential diagnostic and therapeutic applications was demonstrated. First, as an alternative inhibitor of human urokinase for therapeutic purposes, and second, as valuable recognition molecules for the detection of urokinase, as a prognostic and diagnostic marker for cancer, and for NDM-1 to detect resistance to carbapenem antibiotics.
Late-type stars are by far the most frequent stars in the universe and of fundamental interest to various fields of astronomy – most notably to Galactic archaeology and exoplanet research. However, such stars barely change during their main sequence lifetime; their temperature, luminosity, or chemical composition evolve only very slowly over the course of billions of years. As such, it is difficult to obtain the age of such a star, especially when it is isolated and no other indications (like cluster association) can be used. Gyrochronology offers a way to overcome this problem.
Stars, just like all other objects in the universe, rotate and the rate at which stars rotate impacts many aspects of their appearance and evolution. Gyrochronology leverages the observed rotation rate of a late-type main sequence star and its systematic evolution to estimate their ages. Unlike the above-mentioned parameters, the rotation rate of a main sequence star changes drastically throughout its main sequence lifetime; stars spin down. The youngest stars rotate every few hours, whereas much older stars rotate only about once a month, or – in the case of some late M-stars – once in a hundred days. Given that this spindown is systematic (with an additional mass dependence), it gave rise to the idea of using the observed rotation rate of a star (and its mass or a suitable proxy thereof) to estimate a star’s age. This has been explored widely in young stellar open clusters but remains essentially unconstrained for stars older than the sun, and K and M stars older than 1 Gyr.
This thesis focuses on the continued exploration of the spindown behavior to assess, whether gyrochronology remains applicable for stars of old ages, whether it is universal for late-type main sequence stars (including field stars), and to provide calibration mileposts for spindown models. To accomplish this, I have analyzed data from Kepler space telescope for the open clusters Ruprecht 147 (2.7 Gyr old) and M 67 (4 Gyr). Time series photometry data (light curves)
were obtained for both clusters during Kepler’s K2 mission. However, due to technical limitations and telescope malfunctions, extracting usable data from the K2 mission to identify (especially long) rotation periods requires extensive data preparation.
For Ruprecht 147, I have compiled a list of about 300 cluster members from the literature and adopted preprocessed light curves from the Kepler archive where available. They have been cleaned of the gravest of data artifacts but still contained systematics. After correcting them for said artifacts, I was able to identify rotation periods in 31 of them.
For M 67 more effort was taken. My work on Ruprecht 147 has shown the limitations imposed by the preselection of Kepler targets. Therefore, I adopted the time series full frame image directly and performed photometry on a much higher spatial resolution to be able to obtain data for as many stars as possible. This also means that I had to deal with the ubiquitous artifacts in Kepler data. For that, I devised a method that correlates the artificial flux variations with the ongoing drift of the telescope pointing in order to remove it. This process was a large success and I was able to create light curves whose quality match and even exceede those that were created by the Kepler mission – all while operating on higher spatial resolution and processing fainter stars. Ultimately, I was able to identify signs of periodic variability in the (created) light curves for 31 and 47 stars in Ruprecht 147 and M 67, respectively. My data connect well to bluer stars of cluster of the same age and extend for the first time to stars redder than early-K and older than 1 Gyr. The cluster data show a clear flattening in the distribution of Ruprecht 147 and even a downturn for M 67, resulting in a somewhat sinusoidal shape. With that, I have shown that the systematic spindown of stars continues at least until 4 Gyr and stars continue to live on a single surface in age-rotation periods-mass space which allows gyrochronology to be used at least up to that age. However, the shape of the spindown – as exemplified by the newly discovered sinusoidal shape of the cluster sequence – deviates strongly from the expectations.
I then compiled an extensive sample of rotation data in open clusters – very much including my own work – and used the resulting cluster skeleton (with each cluster forming a rip in color-rotation period-mass space) to investigate if field stars follow the same spindown as cluster stars. For the field stars, I used wide binaries, which – with their shared origin and coevality – are in a sense the smallest possible open clusters. I devised an empirical method to evaluate the consistency between the rotation rates of the wide binary components and found that the vast majority of them are in fact consistent with what is observed in open clusters. This leads me to conclude that gyrochronology – calibrated on open clusters – can be applied to determine the ages of field stars.
Amoeboid cell motility takes place in a variety of biomedical processes such as cancer metastasis, embryonic morphogenesis, and wound healing. In contrast to other forms of cell motility, it is mainly driven by substantial cell shape changes. Based on the interplay of explorative membrane protrusions at the front and a slower-acting membrane retraction at the rear, the cell moves in a crawling kind of way. Underlying these protrusions and retractions are multiple physiological processes resulting in changes of the cytoskeleton, a meshwork of different multi-functional proteins. The complexity and versatility of amoeboid cell motility raise the need for novel computational models based on a profound theoretical framework to analyze and simulate the dynamics of the cell shape.
The objective of this thesis is the development of (i) a mathematical framework to describe contour dynamics in time and space, (ii) a computational model to infer expansion and retraction characteristics of individual cell tracks and to produce realistic contour dynamics, (iii) and a complementing Open Science approach to make the above methods fully accessible and easy to use.
In this work, we mainly used single-cell recordings of the model organism Dictyostelium discoideum. Based on stacks of segmented microscopy images, we apply a Bayesian approach to obtain smooth representations of the cell membrane, so-called cell contours. We introduce a one-parameter family of regularized contour flows to track reference points on the contour (virtual markers) in time and space. This way, we define a coordinate system to visualize local geometric and dynamic quantities of individual contour dynamics in so-called kymograph plots. In particular, we introduce the local marker dispersion as a measure to identify membrane protrusions and retractions in a fully automated way.
This mathematical framework is the basis of a novel contour dynamics model, which consists of three biophysiologically motivated components: one stochastic term, accounting for membrane protrusions, and two deterministic terms to control the shape and area of the contour, which account for membrane retractions. Our model provides a fully automated approach to infer protrusion and retraction characteristics from experimental cell tracks while being also capable of simulating realistic and qualitatively different contour dynamics. Furthermore, the model is used to classify two different locomotion types: the amoeboid and a so-called fan-shaped type.
With the complementing Open Science approach, we ensure a high standard regarding the usability of our methods and the reproducibility of our research. In this context, we introduce our software publication named AmoePy, an open-source Python package to segment, analyze, and simulate amoeboid cell motility. Furthermore, we describe measures to improve its usability and extensibility, e.g., by detailed run instructions and an automatically generated source code documentation, and to ensure its functionality and stability, e.g., by automatic software tests, data validation, and a hierarchical package structure.
The mathematical approaches of this work provide substantial improvements regarding the modeling and analysis of amoeboid cell motility. We deem the above methods, due to their generalized nature, to be of greater value for other scientific applications, e.g., varying organisms and experimental setups or the transition from unicellular to multicellular movement. Furthermore, we enable other researchers from different fields, i.e., mathematics, biophysics, and medicine, to apply our mathematical methods. By following Open Science standards, this work is of greater value for the cell migration community and a potential role model for other Open Science contributions.
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.
This thesis is concerned with the phenomenon of quantifier scope ambiguities. This phenomenon has been researched extensively, both from a theoretical and from an empirical point of view. Nevertheless, there are still a number of under-researched topics in the field of quantifier scope, which will be the main focus of this thesis. I will take a closer look at three languages, English, German, and the Asante Twi dialect of Akan (Kwa, Niger-Kongo). The goal is a better understanding of the phenomenon of quantifier scope both within each language, as well as from a cross-linguistic perspective. First, this thesis will provide a series of experiments that allow a direct cross-linguistic comparison between English and German – two languages about which specific claims have been made in the literature. I will also provide exploratory research in the case of Asante Twi, where so far, no work has been dedicated specifically to the study of quantifier scope. The work on Asante Twi will go beyond quantifier scope and also target the quantifier and determiner system in general. The question is not only if particular scope readings are possible or not, but also which factors contribute to an increase or decrease of scope availability, and if there are factors that block certain scope readings altogether. While some of the results confirm and thereby strengthen previous claims, other results contradict general assumptions in the literature. This is particularly the case for inverse readings in German and inverse readings across clause-boundaries.
Volcanic hazard assessment relies on physics-based models of hazards, such as lava flows and pyroclastic density currents, whose outcomes are very sensitive to the location where future eruptions will occur. On the contrary, forecast of vent opening locations in volcanic areas typically relies on purely data-driven approaches, where the spatial density of past eruptive vents informs the probability maps of future vent opening. Such techniques may be suboptimal in volcanic systems with missing or scarce data, and where the controls on magma pathways may change over time. An alternative approach was recently proposed, relying on a model of stress-driven pathways of magmatic dikes. In that approach, the crustal stress was optimized so that dike trajectories linked consistently the location of the magma chamber to that of past vents. The retrieved information on the stress state was then used to forecast future dike trajectories. The validation of such an approach requires extensive application to nature. Before doing so, however, several important limitations need to be removed, most importantly the two-dimensional (2D) character of the models and theoretical concepts. In this thesis, I develop methods and tools so that a physics-based strategy of stress inversion and eruptive vent forecast in volcanoes can be applied to three dimensional (3D) problems. In the first part, I test the stress inversion and vent forecast strategy on analog models, still within a 2D framework, but improving on the efficiency of the stress optimization. In the second part, I discuss how to correctly account for gravitational loading/unloading due to complex 3D topography with a Boundary-Element numerical model. Then, I develop a new, simplified but fast model of dike pathways in 3D, designed for running large numbers of simulations at minimal computational cost, and able to backtrack dike trajectories from vents on the surface. Finally, I combine the stress and dike models to simulate dike pathways in synthetic calderas. In the third part, I describe a framework of stress inversion and vent forecast strategy in 3D for calderas. The stress inversion relies on, first, describing the magma storage below a caldera in terms of a probability density function. Next, dike trajectories are backtracked from the known locations of past vents down through the crust, and the optimization algorithm seeks for the stress models which lead trajectories through the regions of highest probability. I apply the new strategy to the synthetic scenarios presented in the second part, and I exploit the results from the stress inversions to produce probability maps of future vent locations for some of those scenarios. In the fourth part, I present the inversion of different deformation source models applied to the ongoing ground deformation observed across the Rhenish Massif in Central Europe. The region includes the Eifel Volcanic Fields in Germany, a potential application case for the vent forecast strategy. The results show how the observed deformation may be due to melt accumulation in sub-horizontal structures in the lower crust or upper mantle. The thesis concludes with a discussion of the stress inversion and vent forecast strategy, its limitations and applicability to real volcanoes. Potential developments of the modeling tools and concepts presented here are also discussed, as well as possible applications to other geophysical problems.
Reactive eutectic media based on ammonium formate for the valorization of bio-sourced materials
(2023)
In the last several decades eutectic mixtures of different compositions were successfully used as solvents for vast amount of chemical processes, and only relatively recently they were discovered to be widely spread in nature. As such they are discussed as a third liquid media of the living cell, that is composed of common cell metabolites. Such media may also incorporate water as a eutectic component in order to regulate properties such as enzyme activity or viscosity. Taking inspiration form such sophisticated use of eutectic mixtures, this thesis will explore the use of reactive eutectic media (REM) for organic synthesis. Such unconventional media are characterized by the reactivity of their components, which means that mixture may assume the role of the solvent as well as the reactant itself.
The thesis focuses on novel REM based on ammonium formate and investigates their potential for the valorization of bio-sourced materials. The use of REM allows the performance of a number of solvent-free reactions, which entails the benefits of a superior atom and energy economy, higher yields and faster rates compared to reactions in solution. This is evident for the Maillard reaction between ammonium formate and various monosaccharides for the synthesis of substituted pyrazines as well as for a Leuckart type reaction between ammonium formate and levulinic acid for the synthesis of 5-methyl-2-pyrrolidone. Furthermore, reaction of ammonium formate with citric acid for the synthesis of yet undiscovered fluorophores, shows that synthesis in REM can open up unexpected reaction pathways.
Another focus of the thesis is the study of water as a third component in the REM. As a result, the concept of two different dilution regimes (tertiary REM and in REM in solvent) appears useful for understanding the influence of water. It is shown that small amounts of water can be of great benefit for the reaction, by reducing viscosity and at the same time increasing reaction yields.
REM based on ammonium formate and organic acids are employed for lignocellulosic biomass treatment. The thesis thereby introduces an alternative approach towards lignocellulosic biomass fractionation that promises a considerable process intensification by the simultaneous generation of cellulose and lignin as well as the production of value-added chemicals from REM components. The thesis investigates the generated cellulose and the pathway to nanocellulose generation and also includes the structural analysis of extracted lignin.
Finally, the thesis investigates the potential of microwave heating to run chemical reactions in REM and describes the synergy between these two approaches. Microwave heating for chemical reactions and the use of eutectic mixtures as alternative reaction media are two research fields that are often described in the scope of green chemistry. The thesis will therefore also contain a closer inspection of this terminology and its greater goal of sustainability.
The Lyman-𝛼 (Ly𝛼) line commonly assists in the detection of high-redshift galaxies, the so-called Lyman-alpha emitters (LAEs). LAEs are useful tools to study the baryonic matter distribution of the high-redshift universe. Exploring their spatial distribution not only reveals the large-scale structure of the universe at early epochs, but it also provides an insight into the early formation and evolution of the galaxies we observe today. Because dark matter halos (DMHs) serve as sites of galaxy formation, the LAE distribution also traces that of the underlying dark matter. However, the details of this relation and their co-evolution over time remain unclear. Moreover, theoretical studies predict that the spatial distribution of LAEs also impacts their own circumgalactic medium (CGM) by influencing their extended Ly𝛼 gaseous halos (LAHs), whose origin is still under investigation. In this thesis, I make several contributions to improve the knowledge on these fields using samples of LAEs observed with the Multi Unit Spectroscopic Explorer (MUSE) at redshifts of 3 < 𝑧 < 6.
Soft-template strategy enables the fabrication of composite nanomaterials with desired functionalities and structures. In this thesis, soft templates, including poly(ionic liquid) nanovesicles (PIL NVs), self-assembled polystyrene-b-poly(2-vinylpyridine) (PS-b-P2VP) particles, and glycopeptide (GP) biomolecules have been applied for the synthesis of versatile composite particles of PILs/Cu, molybdenum disulfide/carbon (MoS2/C), and GP-carbon nanotubes-metal (GP-CNTs-metal) composites, respectively. Subsequently, their possible applications as efficient catalysts in two representative reactions, i.e. CO2 electroreduction (CO2ER) and reduction of 4-nitrophenol (4-NP), have been studied, respectively.
In the first work, PIL NVs with a tunable particle size of 50 to 120 nm and a shell thickness of 15 to 60 nm have been prepared via one-step free radical polymerization. By increasing monomer concentration for polymerization, their nanoscopic morphology can evolve from hollow NVs to dense spheres, and finally to directional worms, in which a multi-lamellar packing of PIL chains occurred in all samples. The obtained PIL NVs with varied shell thickness have been in situ functionalized with ultra-small Cu nanoparticles (Cu NPs, 1-3 nm) and subsequently employed as the electrocatalysts for CO2ER. The hollow PILs/Cu composite catalysts exhibit a 2.5-fold enhancement in selectivity towards C1 products compared to the pristine Cu NPs. This enhancement is primarily attributed to the strong electronic interactions between the Cu NPs and the surface functionalities of PIL NVs. This study casts new aspects on using nanostructured PILs as novel electrocatalyst supports in efficient CO2 conversion.
In the second work, a novel approach towards fast degradation of 4-NP has been developed using porous MoS2/C particles as catalysts, which integrate the intrinsically catalytic property of MoS2 with its photothermal conversion capability. Various MoS2/C composite particles have been prepared using assembled PS-b-P2VP block copolymer particles as sacrificed soft templates. Intriguingly, the MoS2/C particles exhibit tailored morphologies including pomegranate-like, hollow, and open porous structures. Subsequently, the photothermal conversion performance of these featured particles has been compared under near infrared (NIR) light irradiation. When employing the open porous MoS2/C particles as the catalyst for the reduction of 4-NP, the reaction rate constant has increased by 1.5-fold under light illumination. This catalytic enhancement mainly results from the open porous architecture and photothermal conversion performance of the MoS2 particles. This proposed strategy offers new opportunities for efficient photothermal-assisted catalysis.
In the third work, a facile and green approach towards the fabrication of GP-CNTs-metal composites has been proposed, which utilizes a versatile GP biomolecule both as a stabilizer for CNTs in water and as a reducing agent for noble metal ions. The abundant hydrogen bonds in GP molecules bestow the formed GP-CNTs with excellent plasticity, enabling the availability of polymorphic CNTs species ranging from dispersion to viscous paste, gel, and even dough by increasing their concentration. The GP molecules can reduce metal precursors at room temperature without additional reducing agents, enabling the in situ immobilization of metal NPs (e.g. Au, Ag, and Pd) on the CNTs surface. The combination of excellent catalytic property of Pd NPs with photothermal conversion capability of CNTs makes the GP-CNTs-Pd composite a promising catalyst for the efficient degradation of 4-NP. The obtained composite displays a 1.6-fold increase in conversion under NIR light illumination in the reduction of 4-NP, mainly owing to the strong light-to-heat conversion effect of CNTs. Overall, the proposed method opens a new avenue for the synthesis of CNTs composite as a sustainable and versatile catalyst platform.
The results presented in the current thesis demonstrate the significance of using soft templates for the synthesis of versatile composites with tailored nanostructure and functionalities. The investigation of these composite nanomaterials in the catalytic reactions reveals their potential in the development of desired catalysts for emerging catalytic processes, e.g. photothermal-assisted catalysis and electrocatalysis.
The Security Operations Center (SOC) represents a specialized unit responsible for managing security within enterprises. To aid in its responsibilities, the SOC relies heavily on a Security Information and Event Management (SIEM) system that functions as a centralized repository for all security-related data, providing a comprehensive view of the organization's security posture. Due to the ability to offer such insights, SIEMS are considered indispensable tools facilitating SOC functions, such as monitoring, threat detection, and incident response.
Despite advancements in big data architectures and analytics, most SIEMs fall short of keeping pace. Architecturally, they function merely as log search engines, lacking the support for distributed large-scale analytics. Analytically, they rely on rule-based correlation, neglecting the adoption of more advanced data science and machine learning techniques.
This thesis first proposes a blueprint for next-generation SIEM systems that emphasize distributed processing and multi-layered storage to enable data mining at a big data scale. Next, with the architectural support, it introduces two data mining approaches for advanced threat detection as part of SOC operations.
First, a novel graph mining technique that formulates threat detection within the SIEM system as a large-scale graph mining and inference problem, built on the principles of guilt-by-association and exempt-by-reputation. The approach entails the construction of a Heterogeneous Information Network (HIN) that models shared characteristics and associations among entities extracted from SIEM-related events/logs. Thereon, a novel graph-based inference algorithm is used to infer a node's maliciousness score based on its associations with other entities in the HIN. Second, an innovative outlier detection technique that imitates a SOC analyst's reasoning process to find anomalies/outliers. The approach emphasizes explainability and simplicity, achieved by combining the output of simple context-aware univariate submodels that calculate an outlier score for each entry.
Both approaches were tested in academic and real-world settings, demonstrating high performance when compared to other algorithms as well as practicality alongside a large enterprise's SIEM system.
This thesis establishes the foundation for next-generation SIEM systems that can enhance today's SOCs and facilitate the transition from human-centric to data-driven security operations.
Inflammatory bowel diseases (IBD), characterised by a chronic inflammation of the gut wall, develop as consequence of an overreacting immune response to commensal bacteria, caused by a combination of genetic and environmental conditions. Large inter-individual differences in the outcome of currently available therapies complicate the decision for the best option for an individual patient. Predicting the prospects of therapeutic success for an individual patient is currently only possible to a limited extent; for this, a better understanding of possible differences between responders and non-responders is needed.
In this thesis, we have developed a mathematical model describing the most important processes of the gut mucosal immune system on the cellular level. The model is based on literature data, which were on the one hand used (qualitatively) to choose which cell types and processes to incorporate and to derive the model structure, and on the other hand (quantitatively) to derive the parameter values. Using ordinary differential equations, it describes the concentration-time course of neutrophils, macrophages, dendritic cells, T cells and bacteria, each subdivided into different cell types and activation states, in the lamina propria and mesenteric lymph nodes. We evaluate the model by means of simulations of the healthy immune response to salmonella infection and mucosal injury.
A virtual population includes IBD patients, which we define through their initially asymptomatic, but after a trigger chronically inflamed gut wall. We demonstrate the model's usefulness in different analyses: (i) The comparison of virtual IBD patients with virtual healthy individuals shows that the disease is elicited by many small or fewer large changes, and allows to make hypotheses about dispositions relevant for development of the disease. (ii) We simulate the effects of different therapeutic targets and make predictions about the therapeutic outcome based on the pre-treatment state. (iii) From the analysis of differences between virtual responders and non-responders, we derive hypotheses about reasons for the inter-individual variability in treatment outcome. (iv) For the example of anti-TNF-alpha therapy, we analyse, which alternative therapies are most promising in case of therapeutic failure, and which therapies are most suited for combination therapies: For drugs also directly targeting the cytokine levels or inhibiting the recruitment of innate immune cells, we predict a low probability of success when used as alternative treatment, but a large gain when used in a combination treatment. For drugs with direct effects on T cells, via modulation of the sphingosine-1-phosphate receptor or inhibition of T cell proliferation, we predict a considerably larger probability of success when used as alternative treatment, but only a small additional gain when used in a combination therapy.
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
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.
Biomolecules such as proteins and lipids have vital roles in numerous cellular functions, including biomolecule transport, protein functions, cellular homeostasis and biomembrane integrity. Traditional biochemistry methods do not provide precise information about cellular biomolecule distribution and behavior under native environmental conditions since they are not transferable to live cell samples. Consequently, this can lead to inaccuracies in quantifying biomolecule interactions due to potential complexities arising from the heterogeneity of native biomembranes. To overcome these limitations, minimal invasive microscopic techniques, such as fluorescence fluctuation spectroscopy (FFS) in combination with fluorescence proteins (FPs) and fluorescence lipid analogs, have been developed. FFS techniques and membrane property sensors enable the quantification of various parameters, including concentration, dynamics, oligomerization, and interaction of biomolecules in live cell samples.
In this work, several FFS approaches and membrane property sensors were implemented and employed to examine biological processes of diverse context. Multi-color scanning fluorescence fluctuation spectroscopy (sFCS) was used the examine protein oligomerization, protein-protein interactions (PPIs) and protein dynamics at the cellular plasma membrane (PM). Additionally, two-color number and brightness (N&B) analysis was extended with the cross-correlation analysis in order to quantify hetero-interactions of proteins in the PM with very slow motion, which would not accessible with sFCS due strong initial photobleaching. Furthermore, two semi-automatic analysis pipelines were designed: spectral Förster resonance energy transfer (FRET) analysis to study changes in membrane charge at the inner leaflet of the PM, and spectral generalized polarization (GP) imaging and spectral phasor analysis to monitor changes in membrane fluidity and order.
An important parameter for studying PPIs is molecular brightness, which directly determines oligomerization and can be extracted from FFS data. However, FPs often display complex photophysical transitions, including dark states. Therefore, it is crucial to characterize FPs for their dark-states to ensure reliable oligomerization measurements. In this study, N&B and sFCS analysis were applied to determine photophysical properties of novel green FPs under different conditions (i.e., excitation power and pH) in living cells. The results showed that the new FPs, mGreenLantern (mGL) and Gamillus, exhibited the highest molecular brightness at the cost of lower photostability. The well-established monomeric enhanced green fluorescent protein (mEGFP) remained the best option to investigate PPIs at lower pH, while mGL was best suited for neutral pH, and Gamillus for high pH. These findings provide guidance for selecting an appropriate FP to quantify PPIs via FFS under different environmental conditions.
Next, several biophysical fluorescence microscopy approaches (i.e., sFCS, GP imaging, membrane charge FRET) were employed to monitor changes in lipid-lipid-packing in biomembranes in different biological context. Lipid metabolism in cancer cells is known to support rapid proliferation and metastasis. Therefore, targeting lipid synthesis or membrane integrity holds immense promise as an anticancer strategy. However, the mechanism of action of the novel agent erufosine (EPC3) on membrane stability is not fully under
stood. The present work revealed that EPC3 reduces lipid packing and composition as well as increased membrane fluidity and dynamic, hence, modifies lipid-lipid-interaction. These effects on membrane integrity were likely triggered by modulations in lipid metabolism and membrane organization. In the case of influenza A virus (IAV) infection, regulation of lipid metabolism is crucial for multiple steps in IAV replication and is related to the pathogenicity of IAV. Here, it is shown for the first time that IAV infection triggers a local enrichment of negatively charged lipids at the inner leaflet of the PM, which decreases membrane fluidity and dynamic, as well as increases lipid packing at the assembly site in living cells. This suggests that IAV alters lipid-lipid interactions and organization at the PM. Overall, this work highlights the potential of biophysical techniques as a screening platform for studying membrane properties in living cells at the single-cell level.
Finally, this study addressed remaining questions about the early stage of IAV assembly. The recruitment of matrix protein 1 (M1) and its interaction with other viral surface proteins, hemagglutinin (HA), neuraminidase (NA), and matrix protein 2 (M2), has been a subject of debate due to conflicting results. In this study, different FFS approaches were performed in transfected cells to investigate interactions between IAV proteins themselves and host factors at the PM. FFS measurements revealed that M2 interacts strongly with M1, leading to the translocation of M1 to the PM. This interaction likely took place along the non-canonical pathway, as evidenced by the detection of an interaction between M2 and the host factor LC3-II, leading to the recruitment of LC3-II to the PM. Moreover, weaker interaction was observed between HA and membrane-bound M1, and no interaction between NA and M1. Interestingly, higher oligomeric states of M1 were only detectable in infected cells. These results indicate that M2 initiates virion assembly by recruiting M1 to the PM, which may serve as a platform for further interactions with viral proteins and host factors.