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Die vorliegende Studie beschäftigt sich mit dem nach einer Strukturveränderung in der Sekundarstufe I entstandenen Schulmodell der Neuen Mittelschule. Untersucht wird, ob sich durch dieses Schulmodell und der damit intendierten neuen Lehr-, Lern- und Prüfungskultur Zusammenhänge zwischen gemessenen mathematischen Kompetenzen der Schüler und den durch Lehrer vergebenen Jahresnoten feststellen lassen.
Die Literaturrecherche macht deutlich, dass die Kritik an der Monokultur des leh-rerzentrierten Unterrichts zwar zu einer neuen Lehr-, Lern- und Prüfungskultur führt, deren Inhalte sind aber recht unterschiedlich, komplex und nicht eindeutig definiert. In der NMS soll die Leistungsbewertung als Lernhilfe fungieren, aber auch verlässliche Aussagen über die Leistung der Schüler treffen. Zur Wirkung der neuen Lernkultur in der NMS gibt es ebenso keine empirischen Befunde wie über die Wirkung der Leistungsbewertung.
An der empirischen Untersuchung nehmen 79 Schüler der sechsten Schulstufe aus drei Neuen Mittelschulen (dicht besiedelte, mittel besiedelte, dünn besiedelte Gemeinde) in Niederösterreich teil. In jeder Schule werden zwei Klassen untersucht. Dabei werden der Kompetenzstand in Mathematik, Schülerzentriertheit sowie Sozial- und Leistungsdruck aus Sicht der Schüler gemeinsam mit der Jah-resnote erhoben.
Für die Studie wird ein Pfadmodell entwickelt und mit einer Pfadanalyse ausge-wertet. Dabei zeigen sich zwar Zusammenhänge zwischen den gemessenen Kompetenzen in Mathematik und den Jahresnoten. Diese Jahresnoten besitzen über die Klasse bzw. die Schule hinaus aber nur eine bedingte Aussagekraft über die erbrachten Leistungen.
With the recent growth of sensors, cloud computing handles the data processing of many applications. Processing some of this data on the cloud raises, however, many concerns regarding, e.g., privacy, latency, or single points of failure. Alternatively, thanks to the development of embedded systems, smart wireless devices can share their computation capacity, creating a local wireless cloud for in-network processing. In this context, the processing of an application is divided into smaller jobs so that a device can run one or more jobs.
The contribution of this thesis to this scenario is divided into three parts. In part one, I focus on wireless aspects, such as power control and interference management, for deciding which jobs to run on which node and how to route data between nodes. Hence, I formulate optimization problems and develop heuristic and meta-heuristic algorithms to allocate wireless and computation resources. Additionally, to deal with multiple applications competing for these resources, I develop a reinforcement learning (RL) admission controller to decide which application should be admitted. Next, I look into acoustic applications to improve wireless throughput by using microphone clock synchronization to synchronize wireless transmissions.
In the second part, I jointly work with colleagues from the acoustic processing field to optimize both network and application (i.e., acoustic) qualities. My contribution focuses on the network part, where I study the relation between acoustic and network qualities when selecting a subset of microphones for collecting audio data or selecting a subset of optional jobs for processing these data; too many microphones or too many jobs can lessen quality by unnecessary delays. Hence, I develop RL solutions to select the subset of microphones under network constraints when the speaker is moving while still providing good acoustic quality. Furthermore, I show that autonomous vehicles carrying microphones improve the acoustic qualities of different applications. Accordingly, I develop RL solutions (single and multi-agent ones) for controlling these vehicles.
In the third part, I close the gap between theory and practice. I describe the features of my open-source framework used as a proof of concept for wireless in-network processing. Next, I demonstrate how to run some algorithms developed by colleagues from acoustic processing using my framework. I also use the framework for studying in-network delays (wireless and processing) using different distributions of jobs and network topologies.
Background: The worldwide prevalence of diabetes has been increasing in recent years, with a projected prevalence of 700 million patients by 2045, leading to economic burdens on societies. Type 2 diabetes mellitus (T2DM), representing more than 95% of all diabetes cases, is a multifactorial metabolic disorder characterized by insulin resistance leading to an imbalance between insulin requirements and supply. Overweight and obesity are the main risk factors for developing type 2 diabetes mellitus. The lifestyle modification of following a healthy diet and physical activity are the primary successful treatment and prevention methods for type 2 diabetes mellitus. Problems may exist with patients not achieving recommended levels of physical activity. Electrical muscle stimulation (EMS) is an increasingly popular training method and has become in the focus of research in recent years. It involves the external application of an electric field to muscles, which can lead to muscle contraction. Positive effects of EMS training have been found in healthy individuals as well as in various patient groups. New EMS devices offer a wide range of mobile applications for whole-body electrical muscle stimulation (WB-EMS) training, e.g., the intensification of dynamic low-intensity endurance exercises through WB-EMS. This dissertation project aims to investigate whether WB-EMS is suitable for intensifying low-intensive dynamic exercises such as walking and Nordic walking.
Methods: Two independent studies were conducted. The first study aimed to investigate the reliability of exercise parameters during the 10-meter Incremental Shuttle Walk Test (10MISWT) using superimposed WB-EMS (research question 1, sub-question a) and the difference in exercise intensity compared to conventional walking (CON-W, research question 1, sub-question b). The second study aimed to compare differences in exercise parameters between superimposed WB-EMS (WB-EMS-W) and conventional walking (CON-W), as well as between superimposed WB-EMS (WB-EMS-NW) and conventional Nordic walking (CON-NW) on a treadmill (research question 2). Both studies took place in participant groups of healthy, moderately active men aged 35-70 years. During all measurements, the Easy Motion Skin® WB-EMS low frequency stimulation device with adjustable intensities for eight muscle groups was used. The current intensity was individually adjusted for each participant at each trial to ensure safety, avoiding pain and muscle cramps. In study 1, thirteen individuals were included for each sub question. A randomized cross-over design with three measurement appointments used was to avoid confounding factors such as delayed onset muscle soreness. The 10MISWT was performed until the participants no longer met the criteria of the test and recording five outcome measures: peak oxygen uptake (VO2peak), relative VO2peak (rel.VO2peak), maximum walk distance (MWD), blood lactate concentration, and the rate of perceived exertion (RPE).
Eleven participants were included in study 2. A randomized cross-over design in a study with four measurement appointments was used to avoid confounding factors. A treadmill test protocol at constant velocity (6.5 m/s) was developed to compare exercise intensities. Oxygen uptake (VO2), relative VO2 (rel.VO2) blood lactate, and the RPE were used as outcome variables. Test-retest reliability between measurements was determined using a compilation of absolute and relative measures of reliability. Outcome measures in study 2 were studied using multifactorial analyses of variances.
Results: Reliability analysis showed good reliability for VO2peak, rel.VO2peak, MWD and RPE with no statistically significant difference for WB-EMS-W during 10WISWT. However, differences compared to conventional walking in outcome variables were not found. The analysis of the treadmill tests showed significant effects for the factors CON/WB-EMS and W/NW for the outcome variables VO2, rel.VO2 and lactate, with both factors leading to higher results. However, the difference in VO2 and relative VO2 is within the range of biological variability of ± 12%. The factor combination EMS∗W/NW is statistically non-significant for all three variables. WB-EMS resulted in the higher RPE values, RPE differences for W/NW and EMS∗W/NW were not significant.
Discussion: The present project found good reliability for measuring VO2peak, rel. VO2peak, MWD and RPE during 10MISWT during WB-EMS-W, confirming prior research of the test. The test appears technically limited rather than physiologically in healthy, moderately active men. However, it is unsuitable for investigating differences in exercise intensities using WB-EMS-W compared to CON-W due to different perceptions of current intensity between exercise and rest. A treadmill test with constant walking speed was conducted to adjust individual maximum tolerable current intensity for the second part of the project. The treadmill test showed a significant increase in metabolic demands during WB-EMS-W and WB-EMS-NW by an increased VO2 and blood lactate concentration. However, the clinical relevance of these findings remains debatable. The study also found that WB-EMS superimposed exercises are perceived as more strenuous than conventional exercise. While in parts comparable studies lead to higher results for VO2, our results are in line with those of other studies using the same frequency. Due to the minor clinical relevance the use of WB-EMS as exercise intensification tool during walking and Nordic walking is limited. High device cost should be considered. Habituation to WB-EMS could increase current intensity tolerance and VO2 and make it a meaningful method in the treatment of T2DM. Recent figures show that WB-EMS is used in obese people to achieve health and weight goals. The supposed benefit should be further investigated scientifically.
Hybrid nanomaterials offer the combination of individual properties of different types of nanoparticles. Some strategies for the development of new nanostructures in larger scale rely on the self-assembly of nanoparticles as a bottom-up approach. The use of templates provides ordered assemblies in defined patterns. In a typical soft-template, nanoparticles and other surface-active agents are incorporated into non-miscible liquids. The resulting self-organized dispersions will mediate nanoparticle interactions to control the subsequent self-assembly. Especially interactions between nanoparticles of very different dispersibility and functionality can be directed at a liquid-liquid interface.
In this project, water-in-oil microemulsions were formulated from quasi-ternary mixtures with Aerosol-OT as surfactant. Oleyl-capped superparamagnetic iron oxide and/or silver nanoparticles were incorporated in the continuous organic phase, while polyethyleneimine-stabilized gold nanoparticles were confined in the dispersed water droplets. Each type of nanoparticle can modulate the surfactant film and the inter-droplet interactions in diverse ways, and their combination causes synergistic effects. Interfacial assemblies of nanoparticles resulted after phase-separation. On one hand, from a biphasic Winsor type II system at low surfactant concentration, drop-casting of the upper phase afforded thin films of ordered nanoparticles in filament-like networks. Detailed characterization proved that this templated assembly over a surface is based on the controlled clustering of nanoparticles and the elongation of the microemulsion droplets. This process offers versatility to use different nanoparticle compositions by keeping the surface functionalization, in different solvents and over different surfaces. On the other hand, a magnetic heterocoagulate was formed at higher surfactant concentration, whose phase-transfer from oleic acid to water was possible with another auxiliary surfactant in ethanol-water mixture. When the original components were initially mixed under heating, defined oil-in-water, magnetic-responsive nanostructures were obtained, consisting on water-dispersible nanoparticle domains embedded by a matrix-shell of oil-dispersible nanoparticles.
Herein, two different approaches were demonstrated to form diverse hybrid nanostructures from reverse microemulsions as self-organized dispersions of the same components. This shows that microemulsions are versatile soft-templates not only for the synthesis of nanoparticles, but also for their self-assembly, which suggest new approaches towards the production of new sophisticated nanomaterials in larger scale.
Volcanoes are one of the Earth’s most dynamic zones and responsible for many changes in our planet. Volcano seismology aims to provide an understanding of the physical processes in volcanic systems and anticipate the style and timing of eruptions by analyzing the seismic records. Volcanic tremor signals are usually observed in the seismic records before or during volcanic eruptions. Their analysis contributes to evaluate the evolving volcanic activity and potentially predict eruptions. Years of continuous seismic monitoring now provide useful information for operational eruption forecasting. The continuously growing amount of seismic recordings, however, poses a challenge for analysis, information extraction, and interpretation, to support timely decision making during volcanic crises. Furthermore, the complexity of eruption processes and precursory activities makes the analysis challenging.
A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contribute to improving our understanding of the underlying physical processes. Some similar issues (data reduction, source separation, extraction, and classification) are addressed in the context of music information retrieval (MIR). The signal characteristics of acoustic and seismic recordings comprise a number of similarities. This thesis is going beyond classical signal analysis techniques usually employed in seismology by exploiting similarities of seismic and acoustic signals and building the information retrieval strategy on the expertise developed in the field of MIR.
First, inspired by the idea of harmonic–percussive separation (HPS) in musical signal processing, I have developed a method to extract harmonic volcanic tremor signals and to detect transient events from seismic recordings. This provides a clean tremor signal suitable for tremor investigation along with a characteristic function suitable for earthquake detection. Second, using HPS algorithms, I have developed a noise reduction technique for seismic signals. This method is especially useful for denoising ocean bottom seismometers, which are highly contaminated by noise. The advantage of this method compared to other denoising techniques is that it doesn’t introduce distortion to the broadband earthquake waveforms, which makes it reliable for different applications in passive seismological analysis. Third, to address the challenge of extracting information from high-dimensional data and investigating the complex eruptive phases, I have developed an advanced machine learning model that results in a comprehensive signal processing scheme for volcanic tremors. Using this method seismic signatures of major eruptive phases can be automatically detected. This helps to provide a chronology of the volcanic system. Also, this model is capable to detect weak precursory volcanic tremors prior to the eruption, which could be used as an indicator of imminent eruptive activity. The extracted patterns of seismicity and their temporal variations finally provide an explanation for the transition mechanism between eruptive phases.
In the last century, several astronomical measurements have supported that a significant percentage (about 22%) of the total mass of the Universe, on galactic and extragalactic scales, is composed of a mysterious ”dark” matter (DM). DM does not interact with the electromagnetic force; in other words it does not reflect, absorb or emit light. It is possible that DM particles are weakly interacting massive particles (WIMPs) that can annihilate (or decay) into Standard Model (SM) particles, and modern very- high-energy (VHE; > 100 GeV) instruments such as imaging atmospheric Cherenkov telescopes (IACTs) can play an important role in constraining the main properties of such DM particles, by detecting these products. One of the most privileged targets where to look for DM signal are dwarf spheroidal galaxies (dSphs), as they are expected to be high DM-dominated objects with a clean, gas-free environment. Some dSphs could be considered as extended sources, considering the angular resolution of IACTs; their angu- lar resolution is adequate to detect extended emission from dSphs. For this reason, we performed an extended-source analysis, by taking into account in the unbinned maximum likelihood estimation both the energy and the angular extension dependency of observed events. The goal was to set more constrained upper limits on the velocity-averaged cross-section annihilation of WIMPs with VERITAS data. VERITAS is an array of four IACTs, able to detect γ-ray photons ranging between 100 GeV and 30 TeV. The results of this extended analysis were compared against the traditional spectral analysis. We found that a 2D analysis may lead to more constrained results, depending on the DM mass, channel, and source. Moreover, in this thesis, the results of a multi-instrument project are presented too. Its goal was to combine already published 20 dSphs data from five different experiments, such as Fermi-LAT, MAGIC, H.E.S.S., VERITAS and HAWC, in order to set upper limits on the WIMP annihilation cross-section in the widest mass range ever reported.
Mit dem Alter kann eine Zunahme leichtgradiger Entzündungsprozesse beobachtet werden, von denen angenommen wird, dass sie den typischen, altersbedingten Verlust an Muskelmasse, -kraft und -funktion „befeuern“. Diese als Inflammaging bezeichneten Prozesse können auf ein komplexes Zusammenspiel aus einem dysfunktionalen (viszeralen) Fettgewebe, einer Dysbiose und damit einhergehender mikrobiellen Translokation und geringeren Abwehrfähigkeit sowie einer insgesamt zunehmenden Immunseneszenz zurückgeführt werden. In Summa begünstigt ein pro-inflammatorisches Milieu metabolische Störungen und chronische, altersassoziierte Erkrankungen, die das Entzündungsgeschehen aufrechterhalten oder vorantreiben. Neben einem essenziellen Bewegungsmangel trägt auch eine westlich geprägte, industrialisierte Ernährungsweise zum Entzündungsgeschehen und zur Entwicklung chronischer Erkrankungen bei. Daher liegt die Vermutung nahe, dem Entzündungsgeschehen mit ausreichend Bewegung und einer anti-inflammatorischen Ernährung entgegenzuwirken. In dieser Hinsicht werden insbesondere Omega-3-Fettsäuren (Omega-3) mit anti-inflammatorischen Eigenschaften verbunden. Obwohl ein Zusammenhang zwischen dem ernährungsbedingten Inflammationspotenzial bzw. der Zufuhr von Omega-3 und dem Inflammationsprofil bereits untersucht wurde, fehlen bislang Untersuchungen insbesondere bei älteren Erwachsenen, die den Link zwischen dem Inflammationspotenzial der Ernährung und Sarkopenie-relevanten Muskelparametern herstellen.
Aufgrund des Proteinmehrbedarfs zum Erhalt der funktionellen Muskulatur im Alter wurde bereits eine Vielzahl an Sport- und Ernährungsinterventionen durchgeführt, die eine Verbesserung des Muskelstatus mit Hilfe von strukturiertem Krafttraining und einer proteinreichen Ernährung zeigen. Es gibt zudem Hinweise, dass Omega-3 auch die Proteinsynthese verstärken könnten. Unklar ist jedoch, inwiefern eine anti-inflammatorische Ernährung mit Fokus auf Omega-3 sowohl die Entzündungsprozesse als auch den Muskelproteinmetabolismus und die neuromuskuläre Funktionalität im Alter günstig unterstützen kann. Dies vor allem im Hinblick auf die Muskelleistung, die eng mit der Sturzneigung und der Autonomie im Alltag verknüpft ist, aber in Interventionsstudien mit älteren Erwachsenen bisher wenig Berücksichtigung erhielt. Darüber hinaus werden häufig progressive Trainingselemente genutzt, die nach Studienabschluss oftmals wenig Anschluss im Lebensalltag der Betroffenen finden und somit wenig nachhaltig sind. Ziel dieser Arbeit war demnach die Evaluierung einer proteinreichen und zusätzlich mit Omega-3 supplementierten Ernährung in Kombination mit einem wöchentlichen Vibrationstraining und altersgemäßen Bewegungsprogramm auf Inflammation und neuromuskuläre Funktion bei älteren, selbständig lebenden Erwachsenen.
Hierzu wurden zunächst mögliche Zusammenhänge zwischen dem ernährungsbedingten Inflammationspotenzial, ermittelt anhand des Dietary Inflammatory Index, und dem Muskelstatus sowie dem Inflammationsprofil im Alter eruiert. Dazu dienten die Ausgangswerte von älteren, selbständig lebenden Erwachsenen einer postprandialen Interventionsstudie (POST-Studie), die im Querschnitt analysiert wurden. Die Ergebnisse bestätigten, dass eine pro-inflammatorische Ernährung sich einerseits in einem stärkeren Entzündungsgeschehen widerspiegelt und andererseits mit Sarkopenie-relevanten Parametern, wie einer geringeren Muskelmasse und Gehgeschwindigkeit, ungünstig assoziiert ist. Darüber hinaus zeigten sich diese Zusammenhänge auch in Bezug auf die Handgreifkraft bei den inaktiven, älteren Erwachsenen der Studie.
Anschließend wurde in einer explorativ ausgerichteten Pilot-Interventionsstudie (AIDA-Studie) in einem dreiarmigen Design untersucht, inwieweit sich eine Supplementierung mit Omega-3 unter Voraussetzung einer optimierten Proteinzufuhr und altersgemäßen Sportintervention mit Vibrationstraining auf die neuromuskuläre Funktion und Inflammation bei selbständig lebenden, älteren Erwachsenen auswirkt. Nach acht Wochen Intervention zeigte sich, dass eine mit Omega-3 supplementierte, proteinreiche Ernährung die Muskelleistung insbesondere bei den älteren Männern steigerte. Während sich die Kontrollgruppe nach acht Wochen Sportintervention nicht verbesserte, bestätigte sich zusätzlich eine Verbesserung der Beinkraft und der Testzeit beim Stuhl-Aufsteh-Test der älteren Erwachsenen mit einer proteinreichen Ernährung in Kombination mit der Sportintervention.
Darüber hinaus wurde deutlich, dass die zusätzliche Omega-3-Supplementierung insbesondere bei den Männern eine Reduktion der pro-inflammatorischen Zytokine im Serum zur Folge hatte. Allerdings spiegelten sich diese Beobachtungen nicht auf Genexpressionsebene in mononukleären Immunzellen oder in der LPS-induzierten Sekretion der Zytokine und Chemokine in Vollblutzellkulturen wider. Dies erfordert weitere Untersuchungen.
Most machine learning methods provide only point estimates when being queried to predict on new data. This is problematic when the data is corrupted by noise, e.g. from imperfect measurements, or when the queried data point is very different to the data that the machine learning model has been trained with. Probabilistic modelling in machine learning naturally equips predictions with corresponding uncertainty estimates which allows a practitioner to incorporate information about measurement noise into the modelling process and to know when not to trust the predictions. A well-understood, flexible probabilistic framework is provided by Gaussian processes that are ideal as building blocks of probabilistic models. They lend themself naturally to the problem of regression, i.e., being given a set of inputs and corresponding observations and then predicting likely observations for new unseen inputs, and can also be adapted to many more machine learning tasks. However, exactly inferring the optimal parameters of such a Gaussian process model (in a computationally tractable manner) is only possible for regression tasks in small data regimes. Otherwise, approximate inference methods are needed, the most prominent of which is variational inference.
In this dissertation we study models that are composed of Gaussian processes embedded in other models in order to make those more flexible and/or probabilistic. The first example are deep Gaussian processes which can be thought of as a small network of Gaussian processes and which can be employed for flexible regression. The second model class that we study are Gaussian process state-space models. These can be used for time-series modelling, i.e., the task of being given a stream of data ordered by time and then predicting future observations. For both model classes the state-of-the-art approaches offer a trade-off between expressive models and computational properties (e.g. speed or convergence properties) and mostly employ variational inference. Our goal is to improve inference in both models by first getting a deep understanding of the existing methods and then, based on this, to design better inference methods. We achieve this by either exploring the existing trade-offs or by providing general improvements applicable to multiple methods.
We first provide an extensive background, introducing Gaussian processes and their sparse (approximate and efficient) variants. We continue with a description of the models under consideration in this thesis, deep Gaussian processes and Gaussian process state-space models, including detailed derivations and a theoretical comparison of existing methods.
Then we start analysing deep Gaussian processes more closely: Trading off the properties (good optimisation versus expressivity) of state-of-the-art methods in this field, we propose a new variational inference based approach. We then demonstrate experimentally that our new algorithm leads to better calibrated uncertainty estimates than existing methods.
Next, we turn our attention to Gaussian process state-space models, where we closely analyse the theoretical properties of existing methods.The understanding gained in this process leads us to propose a new inference scheme for general Gaussian process state-space models that incorporates effects on multiple time scales. This method is more efficient than previous approaches for long timeseries and outperforms its comparison partners on data sets in which effects on multiple time scales (fast and slowly varying dynamics) are present.
Finally, we propose a new inference approach for Gaussian process state-space models that trades off the properties of state-of-the-art methods in this field. By combining variational inference with another approximate inference method, the Laplace approximation, we design an efficient algorithm that outperforms its comparison partners since it achieves better calibrated uncertainties.
This thesis explores the variation in coreference patterns across language modes (i.e., spoken and written) and text genres. The significance of research on variation in language use has been emphasized in a number of linguistic studies. For instance, Biber and Conrad [2009] state that “register/genre variation is a fundamental aspect of human language” and “Given the ubiquity of register/genre variation, an understanding of how linguistic features are used in patterned ways across text varieties is of central importance for both the description of particular languages and the development of cross-linguistic theories of language use.”[p.23]
We examine the variation across genres with the primary goal of contributing to the body of knowledge on the description of language use in English. On the computational side, we believe that incorporating linguistic knowledge into learning-based systems can boost the performance of automatic natural language processing systems, particularly for non-standard texts. Therefore, in addition to their descriptive value, the linguistic findings we provide in this study may prove to be helpful for improving the performance of automatic coreference resolution, which is essential for a good text understanding and beneficial for several downstream NLP applications, including machine translation and text summarization.
In particular, we study a genre of texts that is formed of conversational interactions on the well-known social media platform Twitter. Two factors motivate us: First, Twitter conversations are realized in written form but resemble spoken communication [Scheffler, 2017], and therefore they form an atypical genre for the written mode. Second, while Twitter texts are a complicated genre for automatic coreference resolution, due to their widespread use in the digital sphere, at the same time they are highly relevant for applications that seek to extract information or sentiments from users’ messages. Thus, we are interested in discovering more about the linguistic and computational aspects of coreference in Twitter conversations. We first created a corpus of such conversations for this purpose and annotated it for coreference. We are interested in not only the coreference patterns but the overall discourse behavior of Twitter conversations. To address this, in addition to the coreference relations, we also annotated the coherence relations on the corpus we compiled. The corpus is available online in a newly developed form that allows for separating the tweets from their annotations.
This study consists of three empirical analyses where we independently apply corpus-based, psycholinguistic and computational approaches for the investigation of variation in coreference patterns in a complementary manner. (1) We first make a descriptive analysis of variation across genres through a corpus-based study. We investigate the linguistic aspects of nominal coreference in Twitter conversations and we determine how this genre relates to other text genres in spoken and written modes. In addition to the variation across genres, studying the differences in spoken-written modes is also in focus of linguistic research since from Woolbert [1922]. (2) In order to investigate whether the language mode alone has any effect on coreference patterns, we carry out a crowdsourced experiment and analyze the patterns in the same genre for both spoken and written modes. (3) Finally, we explore the potentials of domain adaptation of automatic coreference resolution (ACR) for the conversational Twitter data. In order to answer the question of how the genre of Twitter conversations relates to other genres in spoken and written modes with respect to coreference patterns, we employ a state-of-the-art neural ACR model [Lee et al., 2018] to examine whether ACR on Twitter conversations will benefit from mode-based separation in out-of-domain training data.
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.
Air pollution has been a persistent global problem in the past several hundred years. While some industrialized nations have shown improvements in their air quality through stricter regulation, others have experienced declines as they rapidly industrialize. The WHO’s 2021 update of their recommended air pollution limit values reflects the substantial impacts on human health of pollutants such as NO2 and O3, as recent epidemiological evidence suggests substantial long-term health impacts of air pollution even at low concentrations. Alongside developments in our understanding of air pollution's health impacts, the new technology of low-cost sensors (LCS) has been taken up by both academia and industry as a new method for measuring air pollution. Due primarily to their lower cost and smaller size, they can be used in a variety of different applications, including in the development of higher resolution measurement networks, in source identification, and in measurements of air pollution exposure. While significant efforts have been made to accurately calibrate LCS with reference instrumentation and various statistical models, accuracy and precision remain limited by variable sensor sensitivity. Furthermore, standard procedures for calibration still do not exist and most proprietary calibration algorithms are black-box, inaccessible to the public. This work seeks to expand the knowledge base on LCS in several different ways: 1) by developing an open-source calibration methodology; 2) by deploying LCS at high spatial resolution in urban environments to test their capability in measuring microscale changes in urban air pollution; 3) by connecting LCS deployments with the implementation of local mobility policies to provide policy advice on resultant changes in air quality.
In a first step, it was found that LCS can be consistently calibrated with good performance against reference instrumentation using seven general steps: 1) assessing raw data distribution, 2) cleaning data, 3) flagging data, 4) model selection and tuning, 5) model validation, 6) exporting final predictions, and 7) calculating associated uncertainty. By emphasizing the need for consistent reporting of details at each step, most crucially on model selection, validation, and performance, this work pushed forward with the effort towards standardization of calibration methodologies. In addition, with the open-source publication of code and data for the seven-step methodology, advances were made towards reforming the largely black-box nature of LCS calibrations.
With a transparent and reliable calibration methodology established, LCS were then deployed in various street canyons between 2017 and 2020. Using two types of LCS, metal oxide (MOS) and electrochemical (EC), their performance in capturing expected patterns of urban NO2 and O3 pollution was evaluated. Results showed that calibrated concentrations from MOS and EC sensors matched general diurnal patterns in NO2 and O3 pollution measured using reference instruments. While MOS proved to be unreliable for discerning differences among measured locations within the urban environment, the concentrations measured with calibrated EC sensors matched expectations from modelling studies on NO2 and O3 pollution distribution in street canyons. As such, it was concluded that LCS are appropriate for measuring urban air quality, including for assisting urban-scale air pollution model development, and can reveal new insights into air pollution in urban environments.
To achieve the last goal of this work, two measurement campaigns were conducted in connection with the implementation of three mobility policies in Berlin. The first involved the construction of a pop-up bike lane on Kottbusser Damm in response to the COVID-19 pandemic, the second surrounded the temporary implementation of a community space on Böckhstrasse, and the last was focused on the closure of a portion of Friedrichstrasse to all motorized traffic. In all cases, measurements of NO2 were collected before and after the measure was implemented to assess changes in air quality resultant from these policies. Results from the Kottbusser Damm experiment showed that the bike-lane reduced NO2 concentrations that cyclists were exposed to by 22 ± 19%. On Friedrichstrasse, the street closure reduced NO2 concentrations to the level of the urban background without worsening the air quality on side streets. These valuable results were communicated swiftly to partners in the city administration responsible for evaluating the policies’ success and future, highlighting the ability of LCS to provide policy-relevant results.
As a new technology, much is still to be learned about LCS and their value to academic research in the atmospheric sciences. Nevertheless, this work has advanced the state of the art in several ways. First, it contributed a novel open-source calibration methodology that can be used by a LCS end-users for various air pollutants. Second, it strengthened the evidence base on the reliability of LCS for measuring urban air quality, finding through novel deployments in street canyons that LCS can be used at high spatial resolution to understand microscale air pollution dynamics. Last, it is the first of its kind to connect LCS measurements directly with mobility policies to understand their influences on local air quality, resulting in policy-relevant findings valuable for decisionmakers. It serves as an example of the potential for LCS to expand our understanding of air pollution at various scales, as well as their ability to serve as valuable tools in transdisciplinary research.
To grant high-quality evidence-based research in the field of exercise sciences, it is often necessary for various institutions to collaborate over longer distances and internationally. Here, not only with regard to the recent COVID-19-pandemic, digital means provide new options for remote scientific exchanges. This thesis is meant to analyse and test digital opportunities to support the dissemination of knowledge and instruction of investigators about defined examination protocols in an international multi-center context.
The project consisted of three studies. The first study, a questionnaire-based survey, aimed at learning about the opinions and preferences of digital learning or social media among students of sport science faculties in two universities each in Germany, the UK and Italy. Based on these findings, in a second study, an examination video of an ultrasound determination of the intima-media-thickness and diameter of an artery was distributed by a messenger app to doctors and nursing personnel as simulated investigators and efficacy of the test setting was analysed. Finally, a third study integrated the use of an augmented reality device for direct remote supervision of the same ultrasound examinations in a long-distance international setting with international experts from the fields of engineering and sports science and later remote supervision of augmented reality equipped physicians performing a given task.
The first study with 229 participating students revealed a high preference for YouTube to receive video-based knowledge as well as a preference for using WhatsApp and Facebook for peer-to-peer contacts for learning purposes and to exchange and discuss knowledge. In the second study, video-based instructions send by WhatsApp messenger
showed high approval of the setup in both study groups, one with doctors familiar with the use of ultrasound technology as well as one with nursing staff who were not familiar with the device, with similar results in overall time of performance and the measurements of the femoral arteries. In the third and final study, experts from different continents were connected remotely to the examination site via an augmented reality device with good transmission quality. The remote supervision to doctors ́ examination produced a good interrater correlation. Experiences with the augmented reality-based setting were rated as highly positive by the participants. Potential benefits of this technique were seen in the fields of education, movement analysis, and supervision.
Concluding, the findings of this thesis were able to suggest modern and addressee- centred digital solutions to enhance the understanding of given examinations techniques of potential investigators in exercise science research projects. Head-mounted augmented reality devices have a special value and may be recommended for collaborative research projects with physical examination–based research questions. While the established setting should be further investigated in prospective clinical studies, digital competencies of future researchers should already be enhanced during the early stages of their education.
Im Rahmen dieser Dissertation wurden die erstmaligen Totalsynthesen der Arylnaphthalen-Lignane Alashinol D, Vitexdoin C, Vitrofolal E, Noralashinol C1 und Ternifoliuslignan E vorgestellt. Der Schlüsselschritt der entwickelten Methode, basiert auf einer regioselektiven intramolekularen Photo-Dehydro-Diels-Alder (PDDA)-Reaktion, die mittels UV-Strahlung im Durchflussreaktor durchgeführt wurde. Bei der Synthese der PDDA-Vorläufer (Diarylsuberate) wurde eine Synthesestrategie nach dem Baukastenprinzip verfolgt. Diese ermöglicht die Darstellung asymmetrischer komplexer Systeme aus nur wenigen Grundbausteinen und die Totalsynthese einer Vielzahl an Lignanen. In systematischen Voruntersuchungen konnte zudem die klare Überlegenheit der intra- gegenüber der intermolekularen PDDA-Reaktion aufgezeigt werden. Dabei stellte sich eine Verknüpfung der beiden Arylpropiolester über einen Korksäurebügel, in para-Position, als besonders effizient heraus. Werden asymmetrisch substituierte Diarylsuberate, bei denen einer der endständigen Estersubstituenten durch eine Trimethylsilyl-Gruppe oder ein Wasserstoffatom ersetzt wurde, verwendet, durchlaufen diese Systeme eine regioselektive Cyclisierung und als Hauptprodukt werden Naphthalenophane mit einem Methylester in 3-Position erhalten. Mit Hilfe von umfangreichen Experimenten zur Funktionalisierung der 4-Position, konnte zudem gezeigt werden, dass die Substitution der nucleophilen Cycloallen-Intermediate, während der PDDA-Reaktion, generell durch die Zugabe von N-Halogen-Succinimiden möglich ist. In Anbetracht der geringen Ausbeuten haben diese intermolekularen Abfangreaktionen, jedoch keinen präparativen Nutzen für die Totalsynthesen von Lignanen. Mit dem Ziel die allgemeinen photochemischen Reaktionsbedingungen zu optimieren, wurde erstmalig die triplettsensibilisierte PDDA-Reaktion vorgestellt. Durch die Verwendung von Xanthon als Sensibilisator wurde der Einsatz von effizienteren UVA-Lichtquellen ermöglicht, wodurch die Gefahr einer Photozersetzung durch Überbestrahlung minimiert wurde. Im Vergleich zur direkten Anregung mit UVB-Strahlung, konnten die Ausbeuten mit indirekter Anregung durch einen Photokatalysator signifikant gesteigert werden. Die grundlegenden Erkenntnisse und die entwickelten Synthesestrategien dieser Arbeit, können dazu beitragen zukünftig die Erschließung neuer pharmakologisch interessanter Lignane voranzutreiben.
1 Bisher ist nur die semisynthetische Darstellung von Noralashinol C ausgehend von Hydroxymatairesinol literaturbekannt.
The amount of data stored in databases and the complexity of database workloads are ever- increasing. Database management systems (DBMSs) offer many configuration options, such as index creation or unique constraints, which must be adapted to the specific instance to efficiently process large volumes of data. Currently, such database optimization is complicated, manual work performed by highly skilled database administrators (DBAs). In cloud scenarios, manual database optimization even becomes infeasible: it exceeds the abilities of the best DBAs due to the enormous number of deployed DBMS instances (some providers maintain millions of instances), missing domain knowledge resulting from data privacy requirements, and the complexity of the configuration tasks.
Therefore, we investigate how to automate the configuration of DBMSs efficiently with the help of unsupervised database optimization. While there are numerous configuration options, in this thesis, we focus on automatic index selection and the use of data dependencies, such as functional dependencies, for query optimization. Both aspects have an extensive performance impact and complement each other by approaching unsupervised database optimization from different perspectives.
Our contributions are as follows: (1) we survey automated state-of-the-art index selection algorithms regarding various criteria, e.g., their support for index interaction. We contribute an extensible platform for evaluating the performance of such algorithms with industry-standard datasets and workloads. The platform is well-received by the community and has led to follow-up research. With our platform, we derive the strengths and weaknesses of the investigated algorithms. We conclude that existing solutions often have scalability issues and cannot quickly determine (near-)optimal solutions for large problem instances. (2) To overcome these limitations, we present two new algorithms. Extend determines (near-)optimal solutions with an iterative heuristic. It identifies the best index configurations for the evaluated benchmarks. Its selection runtimes are up to 10 times lower compared with other near-optimal approaches. SWIRL is based on reinforcement learning and delivers solutions instantly. These solutions perform within 3 % of the optimal ones. Extend and SWIRL are available as open-source implementations.
(3) Our index selection efforts are complemented by a mechanism that analyzes workloads to determine data dependencies for query optimization in an unsupervised fashion. We describe and classify 58 query optimization techniques based on functional, order, and inclusion dependencies as well as on unique column combinations. The unsupervised mechanism and three optimization techniques are implemented in our open-source research DBMS Hyrise. Our approach reduces the Join Order Benchmark’s runtime by 26 % and accelerates some TPC-DS queries by up to 58 times.
Additionally, we have developed a cockpit for unsupervised database optimization that allows interactive experiments to build confidence in such automated techniques. In summary, our contributions improve the performance of DBMSs, support DBAs in their work, and enable them to contribute their time to other, less arduous tasks.
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.
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.
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.
Selenium (Se) is an essential trace element that is ubiquitously present in the environment in small concentrations. Essential functions of Se in the human body are manifested through the wide range of proteins, containing selenocysteine as their active center. Such proteins are called selenoproteins which are found in multiple physiological processes like antioxidative defense and the regulation of thyroid hormone functions. Therefore, Se deficiency is known to cause a broad spectrum of physiological impairments, especially in endemic regions with low Se content. Nevertheless, being an essential trace element, Se could exhibit toxic effects, if its intake exceeds tolerable levels. Accordingly, this range between deficiency and overexposure represents optimal Se supply. However, this range was found to be narrower than for any other essential trace element. Together with significantly varying Se concentrations in soil and the presence of specific bioaccumulation factors, this represents a noticeable difficulty in the assessment of Se
epidemiological status. While Se is acting in the body through multiple selenoproteins, its intake occurs mainly in form of small organic or inorganic molecular mass species. Thus, Se exposure not only depends on daily intake but also on the respective chemical form, in which it is present.
The essential functions of selenium have been known for a long time and its primary forms in different food sources have been described. Nevertheless, analytical capabilities for a comprehensive investigation of Se species and their derivatives have been introduced only in the last decades. A new Se compound was identified in 2010 in the blood and tissues of bluefin tuna. It was called selenoneine (SeN) since it is an isologue of naturally occurring antioxidant ergothioneine (ET), where Se replaces sulfur. In the following years, SeN was identified in a number of edible fish species and attracted attention as a new dietary Se source and potentially strong antioxidant. Studies in populations whose diet largely relies on fish revealed that SeN
represents the main non-protein bound Se pool in their blood. First studies, conducted with enriched fish extracts, already demonstrated the high antioxidative potential of SeN and its possible function in the detoxification of methylmercury in fish. Cell culture studies demonstrated, that SeN can utilize the same transporter as ergothioneine, and SeN metabolite was found in human urine.
Until recently, studies on SeN properties were severely limited due to the lack of ways to obtain the pure compound. As a predisposition to this work was firstly a successful approach to SeN synthesis in the University of Graz, utilizing genetically modified yeasts. In the current study, by use of HepG2 liver carcinoma cells, it was demonstrated, that SeN does not cause toxic effectsup to 100 μM concentration in hepatocytes. Uptake experiments showed that SeN is not bioavailable to the used liver cells.
In the next part a blood-brain barrier (BBB) model, based on capillary endothelial cells from the porcine brain, was used to describe the possible transfer of SeN into the central nervous system (CNS). The assessment of toxicity markers in these endothelial cells and monitoring of barrier conditions during transfer experiments demonstrated the absence of toxic effects from SeN on the BBB endothelium up to 100 μM concentration. Transfer data for SeN showed slow but substantial transfer. A statistically significant increase was observed after 48 hours following SeN incubation from the blood-facing side of the barrier. However, an increase in Se content was clearly visible already after 6 hours of incubation with 1 μM of SeN. While the transfer rate of SeN after application of 0.1 μM dose was very close to that for 1 μM, incubation with 10 μM of SeN resulted in a significantly decreased transfer rate. Double-sided application of SeN caused no side-specific transfer of SeN, thus suggesting a passive diffusion mechanism of SeN across the BBB. This data is in accordance with animal studies, where ET accumulation was observed in the rat brain, even though rat BBB does not have the primary ET transporter – OCTN1. Investigation of capillary endothelial cell monolayers after incubation with SeN and reference selenium compounds showed no significant increase of intracellular selenium concentration. Speciesspecific Se measurements in medium samples from apical and basolateral compartments, as good as in cell lysates, showed no SeN metabolization. Therefore, it can be concluded that SeN may reach the brain without significant transformation.
As the third part of this work, the assessment of SeN antioxidant properties was performed in Caco-2 human colorectal adenocarcinoma cells. Previous studies demonstrated that the intestinal epithelium is able to actively transport SeN from the intestinal lumen to the blood side and accumulate SeN. Further investigation within current work showed a much higher antioxidant potential of SeN compared to ET. The radical scavenging activity after incubation with SeN was close to the one observed for selenite and selenomethionine. However, the SeN effect on the viability of intestinal cells under oxidative conditions was close to the one caused by ET. To answer the question if SeN is able to be used as a dietary Se source and induce the activity of selenoproteins, the activity of glutathione peroxidase (GPx) and the secretion of selenoprotein P (SelenoP) were measured in Caco-2 cells, additionally. As expected, reference selenium compounds selenite and selenomethionine caused efficient induction of GPx activity. In contrast to those SeN had no effect on GPx activity. To examine the possibility of SeN being embedded into the selenoproteome, SelenoP was measured in a culture medium. Even though Caco-2 cells effectively take up SeN in quantities much higher than selenite or selenomethionine, no secretion of SelenoP was observed after SeN incubation.
Summarizing, we can conclude that SeN can hardly serve as a Se source for selenoprotein synthesis. However, SeN exhibit strong antioxidative properties, which appear when sulfur in ET is exchanged by Se. Therefore, SeN is of particular interest for research not as part of Se metabolism, but important endemic dietary antioxidant.
Casualties and damages from urban pluvial flooding are increasing. Triggered by short, localized, and intensive rainfall events, urban pluvial floods can occur anywhere, even in areas without a history of flooding. Urban pluvial floods have relatively small temporal and spatial scales. Although cumulative losses from urban pluvial floods are comparable, most flood risk management and mitigation strategies focus on fluvial and coastal flooding. Numerical-physical-hydrodynamic models are considered the best tool to represent the complex nature of urban pluvial floods; however, they are computationally expensive and time-consuming. These sophisticated models make large-scale analysis and operational forecasting prohibitive. Therefore, it is crucial to evaluate and benchmark the performance of other alternative methods.
The findings of this cumulative thesis are represented in three research articles. The first study evaluates two topographic-based methods to map urban pluvial flooding, fill–spill–merge (FSM) and topographic wetness index (TWI), by comparing them against a sophisticated hydrodynamic model. The FSM method identifies flood-prone areas within topographic depressions while the TWI method employs maximum likelihood estimation to calibrate a TWI threshold (τ) based on inundation maps from the 2D hydrodynamic model. The results point out that the FSM method outperforms the TWI method. The study highlights then the advantage and limitations of both methods.
Data-driven models provide a promising alternative to computationally expensive hydrodynamic models. However, the literature lacks benchmarking studies to evaluate the different models' performance, advantages and limitations. Model transferability in space is a crucial problem. Most studies focus on river flooding, likely due to the relative availability of flow and rain gauge records for training and validation. Furthermore, they consider these models as black boxes. The second study uses a flood inventory for the city of Berlin and 11 predictive features which potentially indicate an increased pluvial flooding hazard to map urban pluvial flood susceptibility using a convolutional neural network (CNN), an artificial neural network (ANN) and the benchmarking machine learning models random forest (RF) and support vector machine (SVM). I investigate the influence of spatial resolution on the implemented models, the models' transferability in space and the importance of the predictive features. The results show that all models perform well and the RF models are superior to the other models within and outside the training domain. The models developed using fine spatial resolution (2 and 5 m) could better identify flood-prone areas. Finally, the results point out that aspect is the most important predictive feature for the CNN models, and altitude is for the other models.
While flood susceptibility maps identify flood-prone areas, they do not represent flood variables such as velocity and depth which are necessary for effective flood risk management. To address this, the third study investigates data-driven models' transferability to predict urban pluvial floodwater depth and the models' ability to enhance their predictions using transfer learning techniques. It compares the performance of RF (the best-performing model in the previous study) and CNN models using 12 predictive features and output from a hydrodynamic model. The findings in the third study suggest that while CNN models tend to generalise and smooth the target function on the training dataset, RF models suffer from overfitting. Hence, RF models are superior for predictions inside the training domains but fail outside them while CNN models could control the relative loss in performance outside the training domains. Finally, the CNN models benefit more from transfer learning techniques than RF models, boosting their performance outside training domains.
In conclusion, this thesis has evaluated both topographic-based methods and data-driven models to map urban pluvial flooding. However, further studies are crucial to have methods that completely overcome the limitation of 2D hydrodynamic models.
Towards unifying approaches in exposure modelling for scenario-based multi-hazard risk assessments
(2023)
This cumulative thesis presents a stepwise investigation of the exposure modelling process for risk assessment due to natural hazards while highlighting its, to date, not much-discussed importance and associated uncertainties. Although “exposure” refers to a very broad concept of everything (and everyone) that is susceptible to damage, in this thesis it is narrowed down to the modelling of large-area residential building stocks. Classical building exposure models for risk applications have been constructed fully relying on unverified expert elicitation over data sources (e.g., outdated census datasets), and hence have been implicitly assumed to be static in time and in space. Moreover, their spatial representation has also typically been simplified by geographically aggregating the inferred composition onto coarse administrative units whose boundaries do not always capture the spatial variability of the hazard intensities required for accurate risk assessments. These two shortcomings and the related epistemic uncertainties embedded within exposure models are tackled in the first three chapters of the thesis. The exposure composition of large-area residential building stocks is studied on the scope of scenario-based earthquake loss models. Then, the proposal of optimal spatial aggregation areas of exposure models for various hazard-related vulnerabilities is presented, focusing on ground-shaking and tsunami risks. Subsequently, once the experience is gained in the study of the composition and spatial aggregation of exposure for various hazards, this thesis moves towards a multi-hazard context while addressing cumulative damage and losses due to consecutive hazard scenarios. This is achieved by proposing a novel method to account for the pre-existing damage descriptions on building portfolios as a key input to account for scenario-based multi-risk assessment. Finally, this thesis shows how the integration of the aforementioned elements can be used in risk communication practices. This is done through a modular architecture based on the exploration of quantitative risk scenarios that are contrasted with social risk perceptions of the directly exposed communities to natural hazards.
In Chapter 1, a Bayesian approach is proposed to update the prior assumptions on such composition (i.e., proportions per building typology). This is achieved by integrating high-quality real observations and then capturing the intrinsic probabilistic nature of the exposure model. Such observations are accounted as real evidence from both: field inspections (Chapter 2) and freely available data sources to update existing (but outdated) exposure models (Chapter 3). In these two chapters, earthquake scenarios with parametrised ground motion fields were transversally used to investigate the role of such epistemic uncertainties related to the exposure composition through sensitivity analyses. Parametrised scenarios of seismic ground shaking were the hazard input utilised to study the physical vulnerability of building portfolios. The second issue that was investigated, which refers to the spatial aggregation of building exposure models, was investigated within two decoupled vulnerability contexts: due to seismic ground shaking through the integration of remote sensing techniques (Chapter 3); and within a multi-hazard context by integrating the occurrence of associated tsunamis (Chapter 4). Therein, a careful selection of the spatial aggregation entities while pursuing computational efficiency and accuracy in the risk estimates due to such independent hazard scenarios (i.e., earthquake and tsunami) are discussed. Therefore, in this thesis, the physical vulnerability of large-area building portfolios due to tsunamis is considered through two main frames: considering and disregarding the interaction at the vulnerability level, through consecutive and decoupled hazard scenarios respectively, which were then contrasted.
Contrary to Chapter 4, where no cumulative damages are addressed, in Chapter 5, data and approaches, which were already generated in former sections, are integrated with a novel modular method to ultimately study the likely interactions at the vulnerability level on building portfolios. This is tested by evaluating cumulative damages and losses after earthquakes with increasing magnitude followed by their respective tsunamis. Such a novel method is grounded on the possibility of re-using existing fragility models within a probabilistic framework. The same approach is followed in Chapter 6 to forecast the likely cumulative damages to be experienced by a building stock located in a volcanic multi-hazard setting (ash-fall and lahars). In that section, special focus was made on the manner the forecasted loss metrics are communicated to locally exposed communities. Co-existing quantitative scientific approaches (i.e., comprehensive exposure models; explorative risk scenarios involving single and multiple hazards) and semi-qualitative social risk perception (i.e., level of understanding that the exposed communities have about their own risk) were jointly considered. Such an integration ultimately allowed this thesis to also contribute to enhancing preparedness, science divulgation at the local level as well as technology transfer initiatives.
Finally, a synthesis of this thesis along with some perspectives for improvement and future work are presented.
The shallow Earth’s layers are at the interplay of many physical processes: some being driven by atmospheric forcing (precipitation, temperature...) whereas others take their origins at depth, for instance ground shaking due to seismic activity. These forcings cause the subsurface to continuously change its mechanical properties, therefore modulating the strength of the surface geomaterials and hydrological fluxes. Because our societies settle and rely on the layers hosting these time-dependent properties, constraining the hydro-mechanical dynamics of the shallow subsurface is crucial for our future geographical development. One way to investigate the ever-changing physical changes occurring under our feet is through the inference of seismic velocity changes from ambient noise, a technique called seismic interferometry. In this dissertation, I use this method to monitor the evolution of groundwater storage and damage induced by earthquakes. Two research lines are investigated that comprise the key controls of groundwater recharge in steep landscapes and the predictability and duration of the transient physical properties due to earthquake ground shaking. These two types of dynamics modulate each other and influence the velocity changes in ways that are challenging to disentangle. A part of my doctoral research also addresses this interaction. Seismic data from a range of field settings spanning several climatic conditions (wet to arid climate) in various seismic-prone areas are considered. I constrain the obtained seismic velocity time-series using simple physical models, independent dataset, geophysical tools and nonlinear analysis. Additionally, a methodological development is proposed to improve the time-resolution of passive seismic monitoring.
The impact of individual differences in cognitive skills and socioeconomic background on key educational, occupational, and health outcomes, as well as the mechanisms underlying inequalities in these outcomes across the lifespan, are two central questions in lifespan psychology. The contextual embeddedness of such questions in ontogenetic (i.e., individual, age-related) and historical time is a key element of lifespan psychological theoretical frameworks such as the HIstorical changes in DEvelopmental COntexts (HIDECO) framework (Drewelies et al., 2019). Because the dimension of time is also a crucial part of empirical research designs examining developmental change, a third central question in research on lifespan development is how the timing and spacing of observations in longitudinal studies might affect parameter estimates of substantive phenomena. To address these questions in the present doctoral thesis, I applied innovative state-of-the-art methodology including static and dynamic longitudinal modeling approaches, used data from multiple international panel studies, and systematically simulated data based on empirical panel characteristics, in three empirical studies.
The first study of this dissertation, Study I, examined the importance of adolescent intelligence (IQ), grade point average (GPA), and parental socioeconomic status (pSES) for adult educational, occupational, and health outcomes over ontogenetic and historical time. To examine the possible impact of historical changes in the 20th century on the relationships between adolescent characteristics and key adult life outcomes, the study capitalized on data from two representative US cohort studies, the National Longitudinal Surveys of Youth 1979 and 1997, whose participants were born in the late 1960s and 1980s, respectively. Adolescent IQ, GPA, and pSES were positively associated with adult educational attainment, wage levels, and mental and physical health. Across historical time, the influence of IQ and pSES for educational, occupational, and health outcomes remained approximately the same, whereas GPA gained in importance over time for individuals born in the 1980s.
The second study of this dissertation, Study II, aimed to examine strict cumulative advantage (CA) processes as possible mechanisms underlying individual differences and inequality in wage development across the lifespan. It proposed dynamic structural equation models (DSEM) as a versatile statistical framework for operationalizing and empirically testing strict CA processes in research on wages and wage dynamics (i.e., wage levels and growth rates). Drawing on longitudinal representative data from the US National Longitudinal Survey of Youth 1979, the study modeled wage levels and growth rates across 38 years. Only 0.5 % of the sample revealed strict CA processes and explosive wage growth (autoregressive coefficients AR > 1), with the majority of individuals following logarithmic wage trajectories across the lifespan. Adolescent intelligence (IQ) and adult highest educational level explained substantial heterogeneity in initial wage levels and long-term wage growth rates over time.
The third study of this dissertation, Study III, investigated the role of observation timing variability in the estimation of non-experimental intervention effects in panel data. Although longitudinal studies often aim at equally spaced intervals between their measurement occasions, this goal is hardly ever met. Drawing on continuous time dynamic structural equation models, the study examines the –seemingly counterintuitive – potential benefits of measurement intervals that vary both within and between participants (often called individually varying time intervals, IVTs) in a panel study. It illustrates the method by modeling the effect of the transition from primary to secondary school on students’ academic motivation using empirical data from the German National Educational Panel Study (NEPS). Results of a simulation study based on this real-life example reveal that individual variation in time intervals can indeed benefit the estimation precision and recovery of the true intervention effect parameters.
This dissertation focuses on the handling of time in dialogue. Specifically, it investigates how humans bridge time, or “buy time”, when they are expected to convey information that is not yet available to them (e.g. a travel agent searching for a flight in a long list while the customer is on the line, waiting). It also explores the feasibility of modeling such time-bridging behavior in spoken dialogue systems, and it examines
how endowing such systems with more human-like time-bridging capabilities may affect humans’ perception of them.
The relevance of time-bridging in human-human dialogue seems to stem largely from a need to avoid lengthy pauses, as these may cause both confusion and discomfort among the participants of a conversation (Levinson, 1983; Lundholm Fors, 2015). However, this avoidance of prolonged silence is at odds with the incremental nature of speech production in dialogue (Schlangen and Skantze, 2011): Speakers often start to verbalize their contribution before it is fully formulated, and sometimes even before they possess the information they need to provide, which may result in them running out of content mid-turn.
In this work, we elicit conversational data from humans, to learn how they avoid being silent while they search for information to convey to their interlocutor. We identify commonalities in the types of resources employed by different speakers, and we propose a classification scheme. We explore ways of modeling human time-buying behavior computationally, and we evaluate the effect on human listeners of embedding this behavior in a spoken dialogue system.
Our results suggest that a system using conversational speech to bridge time while searching for information to convey (as humans do) can provide a better experience in several respects than one which remains silent for a long period of time. However, not all speech serves this purpose equally: Our experiments also show that a system whose time-buying behavior is more varied (i.e. which exploits several categories from the classification scheme we developed and samples them based on information from human data) can prevent overestimation of waiting time when compared, for example, with a system that repeatedly asks the interlocutor to wait (even if these requests for waiting are phrased differently each time). Finally, this research shows that it is possible to model human time-buying behavior on a relatively small corpus, and that a system using such a model can be preferred by participants over one employing a simpler strategy, such as randomly choosing utterances to produce during the wait —even when the utterances used by both strategies are the same.
Despite the popularity of thermoresponsive polymers, much is still unknown about their behavior, how it is triggered, and what factors influence it, hindering the full exploitation of their potential. One particularly puzzling phenomenon is called co-nonsolvency, in which a polymer is soluble in two individual solvents, but counter-intuitively becomes insoluble in mixtures of both. Despite the innumerous potential applications of such systems, including actuators, viscosity regulators and as carrier structures, this field has not yet been extensively studied apart from the classical example of poly(N isopropyl acrylamide) (PNIPAM) in mixtures of water and methanol. Therefore, this thesis focuses on evaluating how changes in the chemical structure of the polymers impact the thermoresponsive, aggregation and co-nonsolvency behaviors of both homopolymers and amphiphilic block copolymers. Within this scope, both the synthesis of the polymers and their characterization in solution is investigated. Homopolymers were synthesized by conventional free radical polymerization, whereas block copolymers were synthesized by consecutive reversible addition fragmentation chain transfer (RAFT) polymerizations. The synthesis of the monomers N isopropyl methacrylamide (NIPMAM) and N vinyl isobutyramide (NVIBAM), as well as a few chain transfer agents is also covered. Through turbidimetry measurements, the thermoresponsive and co-nonsolvency behavior of PNIPMAM and PNVIBAM homopolymers is then compared to the well-known PNIPAM, in aqueous solutions with 9 different organic co-solvents. Additionally, the effects of end-groups, molar mass, and concentration are investigated. Despite the similarity of their chemical structures, the 3 homopolymers show significant differences in transition temperatures and some divergences in their co-nonsolvency behavior. More complex systems are also evaluated, namely amphiphilic di- and triblock copolymers of PNIPAM and PNIPMAM with polystyrene and poly(methyl methacrylate) hydrophobic blocks. Dynamic light scattering is used to evaluate their aggregation behavior in aqueous and mixed aqueous solutions, and how it is affected by the chemical structure of the blocks, the chain architecture, presence of cosolvents and polymer concentration. The results obtained shed light into the thermoresponsive, co-nonsolvency and aggregation behavior of these polymers in solution, providing valuable information for the design of systems with a desired aggregation behavior, and that generate targeted responses to temperature and solvent mixture changes.
Background: The concept self-compassion (SC), a special way of being compassionate with oneself while dealing with stressful life circumstances, has attracted increasing attention in research over the past two decades. Research has already shown that SC has beneficial effects on affective well-being and other mental health outcomes. However, little is known in which ways SC might facilitate our affective well-being in stressful situations. Hence, a central concern of this dissertation was to focus on the question which underlying processes might influence the link between SC and affective well-being. Two established components in stress processing, which might also play an important role in this context, could be the amount of experienced stress and the way of coping with a stressor. Thus, using a multi-method approach, this dissertation aimed at finding to which extent SC might help to alleviate the experienced stress and promotes the use of more salutary coping, while dealing with stressful circumstances. These processes might ultimately help improve one’s affective well-being. Derived from that, it was hypothesized that more SC is linked to less perceived stress and intensified use of salutary coping responses. Additionally, it was suggested that perceived stress and coping mediate the relation between SC and affective well-being.
Method: The research questions were targeted in three single studies and one meta-study. To test my assumptions about the relations of SC and coping in particular, a systematic literature search was conducted resulting in k = 136 samples with an overall sample size of N = 38,913. To integrate the z-transformed Pearson correlation coefficients, random-effects models were calculated. All hypotheses were tested with a three-wave cross-lagged design in two short-term longitudinal online studies assessing SC, perceived stress and coping responses in all waves. The first study explored the assumptions in a student sample (N = 684) with a mean age of 27.91 years over a six-week period, whereas the measurements were implemented in the GESIS Panel (N = 2934) with a mean age of 52.76 years analyzing the hypotheses in a populationbased sample across eight weeks. Finally, an ambulatory assessment study was designed to expand the findings of the longitudinal studies to the intraindividual level. Thus, a sample of 213 participants completed questionnaires of momentary SC, perceived stress, engagement and disengagement coping, and affective well-being on their smartphones three times per day over seven consecutive days. The data was processed using 1-1-1 multilevel mediation analyses.
Results: Results of the meta-analysis indicated that higher SC is significantly associated with more use of engagement coping and less use of disengagement coping. Considering the relations between SC and stress processing variables in all three single studies, cross-lagged paths from the longitudinal data, as well as multilevel modeling paths from the ambulatory assessment data indicated a notable relation between all relevant stress variables. As expected, results showed a significant negative relation between SC and perceived stress and disengagement coping, as well as a positive connection with engagement coping responses at the dispositional and intra-individual level. However, considering the mediational hypothesis, the most promising pathway in the link between SC and affective well-being turned out to be perceived stress in all three studies, while effects of the mediational pathways through coping responses were less robust.
Conclusion: Thus, a more self-compassionate attitude and higher momentary SC, when needed in specific situations, can help to engage in effective stress processing. Considering the underlying mechanisms in the link between SC and affective well-being, stress perception in particular seemed to be the most promising candidate for enhancing affective well-being at the dispositional and at the intraindividual level. Future research should explore the pathways between SC and affective well-being in specific contexts and samples, and also take into account additional influential factors.
The Andean Cordillera is a mountain range located at the western South American margin and is part of the Eastern- Circum-Pacific orogenic Belt. The ~7000 km long mountain range is one of the longest on Earth and hosts the second largest orogenic plateau in the world, the Altiplano-Puna plateau. The Andes are known as a non-collisional subduction-type orogen which developed as a result of the interaction between the subducted oceanic Nazca plate and the South American continental plate. The different Andean segments exhibit along-strike variations of morphotectonic provinces characterized by different elevations, volcanic activity, deformation styles, crustal thickness, shortening magnitude and oceanic plate geometry. Most of the present-day elevation can be explained by crustal shortening in the last ~50 Ma, with the shortening magnitude decreasing from ~300 km in the central (15°S-30°S) segment to less than half that in the southern part (30°S-40°S). Several factors were proposed that might control the magnitude and acceleration of shortening of the Central Andes in the last 15 Ma. One important factor is likely the slab geometry. At 27-33°S, the slab dips horizontally at ~100 km depth due to the subduction of the buoyant Juan Fernandez Ridge, forming the Pampean flat-slab. This horizontal subduction is thought to influence the thermo-mechanical state of the Sierras Pampeanas foreland, for instance, by strengthening the lithosphere and promoting the thick-skinned propagation of deformation to the east, resulting in the uplift of the Sierras Pampeanas basement blocks. The flat-slab has migrated southwards from the Altiplano latitude at ~30 Ma to its present-day position and the processes and consequences associated to its passage on the contemporaneous acceleration of the shortening rate in Central Andes remain unclear. Although the passage of the flat-slab could offer an explanation to the acceleration of the shortening, the timing does not explain the two pulses of shortening at about 15 Ma and 4 Ma that are suggested from geological observations. I hypothesize that deformation in the Central Andes is controlled by a complex interaction between the subduction dynamics of the Nazca plate and the dynamic strengthening and weakening of the South American plate due to several upper plate processes. To test this hypothesis, a detailed investigation into the role of the flat-slab, the structural inheritance of the continental plate, and the subduction dynamics in the Andes is needed. Therefore, I have built two classes of numerical thermo-mechanical models: (i) The first class of models are a series of generic E-W-oriented high-resolution 2D subduction models thatinclude flat subduction in order to investigate the role of the subduction dynamics on the temporal variability of the shortening rate in the Central Andes at Altiplano latitudes (~21°S). The shortening rate from the models was then validated with the observed tectonic shortening rate in the Central Andes. (ii) The second class of models are a series of 3D data-driven models of the present-day Pampean flat-slab configuration and the Sierras Pampeanas (26-42°S). The models aim to investigate the relative contribution of the present-day flat subduction and inherited structures in the continental lithosphere on the strain localization. Both model classes were built using the advanced finite element geodynamic code ASPECT.
The first main finding of this work is to suggest that the temporal variability of shortening in the Central Andes is primarily controlled by the subduction dynamics of the Nazca plate while it penetrates into the mantle transition zone. These dynamics depends on the westward velocity of the South American plate that provides the main crustal shortening force to the Andes and forces the trench to retreat. When the subducting plate reaches the lower mantle, it buckles on it-self until the forced trench retreat causes the slab to steepen in the upper mantle in contrast with the classical slab-anchoring model. The steepening of the slab hinders the trench causing it to resist the advancing South American plate, resulting in the pulsatile shortening. This buckling and steepening subduction regime could have been initiated because of the overall decrease in the westwards velocity of the South American plate. In addition, the passage of the flat-slab is required to promote the shortening of the continental plate because flat subduction scrapes the mantle lithosphere, thus weakening the continental plate. This process contributes to the efficient shortening when the trench is hindered, followed by mantle lithosphere delamination at ~20 Ma. Finally, the underthrusting of the Brazilian cratonic shield beneath the orogen occurs at ~11 Ma due to the mechanical weakening of the thick sediments covered the shield margin, and due to the decreasing resistance of the weakened lithosphere of the orogen.
The second main finding of this work is to suggest that the cold flat-slab strengthens the overriding continental lithosphere and prevents strain localization. Therefore, the deformation is transmitted to the eastern front of the flat-slab segment by the shear stress operating at the subduction interface, thus the flat-slab acts like an indenter that “bulldozes” the mantle-keel of the continental lithosphere. The offset in the propagation of deformation to the east between the flat and steeper slab segments in the south causes the formation of a transpressive dextral shear zone. Here, inherited faults of past tectonic events are reactivated and further localize the deformation in an en-echelon strike-slip shear zone, through a mechanism that I refer to as “flat-slab conveyor”. Specifically, the shallowing of the flat-slab causes the lateral deformation, which explains the timing of multiple geological events preceding the arrival of the flat-slab at 33°S. These include the onset of the compression and of the transition between thin to thick-skinned deformation styles resulting from the crustal contraction of the crust in the Sierras Pampeanas some 10 and 6 Myr before the Juan Fernandez Ridge collision at that latitude, respectively.
This thesis bridges two areas of mathematics, algebra on the one hand with the Milnor-Moore theorem (also called Cartier-Quillen-Milnor-Moore theorem) as well as the Poincaré-Birkhoff-Witt theorem, and analysis on the other hand with Shintani zeta functions which generalise multiple zeta functions.
The first part is devoted to an algebraic formulation of the locality principle in physics and generalisations of classification theorems such as Milnor-Moore and Poincaré-Birkhoff-Witt theorems to the locality framework. The locality principle roughly says that events that take place far apart in spacetime do not infuence each other. The algebraic formulation of this principle discussed here is useful when analysing singularities which arise from events located far apart in space, in order to renormalise them while keeping a memory of the fact that they do not influence each other. We start by endowing a vector space with a symmetric relation, named the locality relation, which keeps track of elements that are "locally independent". The pair of a vector space together with such relation is called a pre-locality vector space. This concept is extended to tensor products allowing only tensors made of locally independent elements. We extend this concept to the locality tensor algebra, and locality symmetric algebra of a pre-locality vector space and prove the universal properties of each of such structures. We also introduce the pre-locality Lie algebras, together with their associated locality universal enveloping algebras and prove their universal property. We later upgrade all such structures and results from the pre-locality to the locality context, requiring the locality relation to be compatible with the linear structure of the vector space. This allows us to define locality coalgebras, locality bialgebras, and locality Hopf algebras. Finally, all the previous results are used to prove the locality version of the Milnor-Moore and the Poincaré-Birkhoff-Witt theorems. It is worth noticing that the proofs presented, not only generalise the results in the usual (non-locality) setup, but also often use less tools than their counterparts in their non-locality counterparts.
The second part is devoted to study the polar structure of the Shintani zeta functions. Such functions, which generalise the Riemman zeta function, multiple zeta functions, Mordell-Tornheim zeta functions, among others, are parametrised by matrices with real non-negative arguments. It is known that Shintani zeta functions extend to meromorphic functions with poles on afine hyperplanes. We refine this result in showing that the poles lie on hyperplanes parallel to the facets of certain convex polyhedra associated to the defining matrix for the Shintani zeta function. Explicitly, the latter are the Newton polytopes of the polynomials induced by the columns of the underlying matrix. We then prove that the coeficients of the equation which describes the hyperplanes in the canonical basis are either zero or one, similar to the poles arising when renormalising generic Feynman amplitudes. For that purpose, we introduce an algorithm to distribute weight over a graph such that the weight at each vertex satisfies a given lower bound.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
Technologically important, environmentally friendly InP quantum dots (QDs) typically used as green and red emitters in display devices can achieve exceptional photoluminescence quantum yields (PL QYs) of near-unity (95-100%) when the-state-of-the-art core/shell heterostructure of the ZnSe inner/ZnS outer shell is elaborately applied. Nevertheless, it has only led to a few industrial applications as QD liquid crystal display (QD–LCD) which is applied to blue backlight units, even though QDs has a lot of possibilities that able to realize industrially feasible applications, such as QD light-emitting diodes (QD‒LEDs) and luminescence solar concentrator (LSC), due to their functionalizable characteristics.
Before introducing the main research, the theoretical basis and fundamentals of QDs are described in detail on the basis of the quantum mechanics and experimental synthetic results, where a concept of QD and colloidal QD, a type-I core/shell structure, a transition metal doped semiconductor QDs, the surface chemistry of QD, and their applications (LSC, QD‒LEDs, and EHD jet printing) are sequentially elucidated for better understanding. This doctoral thesis mainly focused on the connectivity between QD materials and QD devices, based on the synthesis of InP QDs that are composed of inorganic core (core/shell heterostructure) and organic shell (surface ligands on the QD surface). In particular, as for the former one (core/shell heterostructure), the ZnCuInS mid-shell as an intermediate layer is newly introduced between a Cu-doped InP core and a ZnS shell for LSC devices. As for the latter one (surface ligands), the ligand effect by 1-octanethiol and chloride ion are investigated for the device stability in QD‒LEDs and the printability of electro-hydrodynamic (EHD) jet printing system, in which this research explores the behavior of surface ligands, based on proton transfer mechanism on the QD surface.
Chapter 3 demonstrates the synthesis of strain-engineered highly emissive Cu:InP/Zn–Cu–In–S (ZCIS)/ZnS core/shell/shell heterostructure QDs via a one-pot approach. When this unconventional combination of a ZCIS/ZnS double shelling scheme is introduced to a series of Cu:InP cores with different sizes, the resulting Cu:InP/ZCIS/ZnS QDs with a tunable near-IR PL range of 694–850 nm yield the highest-ever PL QYs of 71.5–82.4%. These outcomes strongly point to the efficacy of the ZCIS interlayer, which makes the core/shell interfacial strain effectively alleviated, toward high emissivity. The presence of such an intermediate ZCIS layer is further examined by comparative size, structural, and compositional analyses. The end of this chapter briefly introduces the research related to the LSC devices, fabricated from Cu:InP/ZCIS/ZnS QDs, currently in progress.
Chapter 4 mainly deals with ligand effect in 1-octanethiol passivation of InP/ZnSe/ZnS QDs in terms of incomplete surface passivation during synthesis. This chapter demonstrates the lack of anionic carboxylate ligands on the surface of InP/ZnSe/ZnS quantum dots (QDs), where zinc carboxylate ligands can be converted to carboxylic acid or carboxylate ligands via proton transfer by 1-octanethiol. The as-synthesized QDs initially have an under-coordinated vacancy surface, which is passivated by solvent ligands such as ethanol and acetone. Upon exposure of 1-octanethiol to the QD surface, 1-octanthiol effectively induces the surface binding of anionic carboxylate ligands (derived from zinc carboxylate ligands) by proton transfer, which consequently exchanges ethanol and acetone ligands that bound on the incomplete QD surface. The systematic chemical analyses, such as thermogravimetric analysis‒mass spectrometry and proton nuclear magnetic resonance spectroscopy, directly show the interplay of surface ligands, and it associates with QD light-emitting diodes (QD‒LEDs).
Chapter 5 shows the relation between material stability of QDs and device stability of QD‒LEDs through the investigation of surface chemistry and shell thickness. In typical III–V colloidal InP quantum dots (QDs), an inorganic ZnS outermost shell is used to provide stability when overcoated onto the InP core. However, this work presents a faster photo-degradation of InP/ZnSe/ZnS QDs with a thicker ZnS shell than that with a thin ZnS shell when 1-octanethiol was applied as a sulfur source to form ZnS outmost shell. Herein, 1-octanethiol induces the form of weakly-bound carboxylate ligand via proton transfer on the QD surface, resulting in a faster degradation at UV light even though a thicker ZnS shell was formed onto InP/ZnSe QDs. Detailed insight into surface chemistry was obtained from proton nuclear magnetic resonance spectroscopy and thermogravimetric analysis–mass spectrometry. However, the lifetimes of the electroluminescence devices fabricated from InP/ZnSe/ZnS QDs with a thick or a thin ZnS shell show surprisingly the opposite result to the material stability of QDs, where the QD light-emitting diodes (QD‒LEDs) with a thick ZnS shelled QDs maintained its luminance more stable than that with a thin ZnS shelled QDs. This study elucidates the degradation mechanism of the QDs and the QD light-emitting diodes based on the results and discuss why the material stability of QDs is different from the lifetime of QD‒LEDs.
Chapter 6 suggests a method how to improve a printability of EHD jet printing when QD materials are applied to QD ink formulation, where this work introduces the application of GaP mid-shelled InP QDs as a role of surface charge in EHD jet printing technique. In general, GaP intermediate shell has been introduced in III–V colloidal InP quantum dots (QDs) to enhance their thermal stability and quantum efficiency in the case of type-I core/shell/shell heterostructure InP/GaP/ZnSeS QDs. Herein, these highly luminescent InP/GaP/ZnSeS QDs were synthesized and applied to EHD jet printing, by which this study demonstrates that unreacted Ga and Cl ions on the QD surface induce the operating voltage of cone jet and cone jet formation to be reduced and stabilized, respectively. This result indicates GaP intermediate shell not only improves PL QY and thermal stability of InP QDs but also adjusts the critical flow rate required for cone-jet formation. In other words, surface charges of quantum dots can have a significant role in forming cone apex in the EHD capillary nozzle. For an industrially convenient validation of surface charges on the QD surface, Zeta potential analyses of QD solutions as a simple method were performed, as well as inductively coupled plasma optical emission spectrometry (ICP-OES) for a composition of elements.
Beyond the generation of highly emissive InP QDs with narrow FWHM, these studies talk about the connection between QD material and QD devices not only to make it a vital jumping-off point for industrially feasible applications but also to reveal from chemical and physical standpoints the origin that obstructs the improvement of device performance experimentally and theoretically.
In dieser Dissertation konnten erfolgreich mechanisch stabile Hydrogele über eine freie radikalische Polymerisation (FRP) in Wasser synthetisiert werden. Dabei diente vor allem das Sulfobetain SPE als Monomer. Dieses wurde mit dem über eine nukleophile Substitution erster bzw. zweiter Ordnung hergestellten Vernetzer TMBEMPA/Br umgesetzt.
Die entstandenen Netzwerke wurden im Gleichgewichtsquellzustand im Wesentlichen mittels Niederfeld-Kernresonanzspektroskopie, Röntgenkleinwinkelstreuung (SAXS), Rasterelektronenmikroskopie mit Tieftemperaturtechnik (Kryo-REM), dynamisch-mechanische Analyse (DMA), Rheologie, thermogravimetrische Analyse (TGA) und dynamische Differenzkalorimetrie (DSC) analysiert.
Das hierarchisch aufgebaute Netzwerk wurde anschließend für die matrixgesteuerten Mineralisation von Calciumphosphat und –carbonat genutzt. Über das alternierende Eintauchverfahren (engl. „alternate soaking method“) und der Variation von Mineralisationsparametern, wie pH-Wert, Konzentration c und Temperatur T konnten dann verschiedene Modifikationen des Calciumphosphats generiert werden. Das entstandene Hybridmaterial wurde qualitativ mittels Röntgenpulverdiffraktometrie (XRD), abgeschwächte Totalreflexion–fouriertransformierte Infrarot Spektroskopie (ATR-FTIR), Raman-Spektroskopie, Rasterelektronenmikroskopie (REM) mit energiedispersiver Röntgenspektroskopie (EDXS) und optischer Mikroskopie (OM) als auch quantitative mittels Gravimetrie und TGA analysiert.
Für die potentielle Verwendung in der Medizintechnik, z.B. als Implantatmaterial, ist die grundlegende Einschätzung der Wechselwirkung zwischen Hydrogel bzw. Hybridmaterial und verschiedener Zelltypen unerlässlich. Dazu wurden verschiedene Zelltypen, wie Einzeller, Bakterien und adulte Stammzellen verwendet. Die Wechselwirkung mit Peptidsequenzen von Phagen komplettiert das biologische Unterkapitel.
Hydrogele sind mannigfaltig einsetzbar. Diese Arbeit fasst daher weitere Projektperspektiven, auch außerhalb des biomedizinischem Anwendungsspektrums, auf. So konnten erste Ansätze zur serienmäßige bzw. maßgeschneiderte Produktion über das „Inkjet“ Verfahren erreicht werden. Um dies ermöglichen zu können wurden erfolgreich weitere Synthesestrategien, wie die Photopolymerisation und die redoxinitiierte Polymerisation, ausgenutzt. Auch die Eignung als Filtermaterial oder Superabsorber wurde analysiert.
Layered structures are ubiquitous in nature and industrial products, in which individual layers could have different mechanical/thermal properties and functions independently contributing to the performance of the whole layered structure for their relevant application. Tuning each layer affects the performance of the whole layered system.
Pores are utilized in various disciplines, where low density, but large surfaces are demanded. Besides, open and interconnected pores would act as a transferring channel for guest chemical molecules. The shape of pores influences compression behavior of the material. Moreover, introducing pores decreases the density and subsequently the mechanical strength. To maintain defined mechanical strength under various stress, porous structure can be reinforced by adding reinforcement agent such as fiber, filler or layered structure to bear the mechanical stress on demanded application.
In this context, this thesis aimed to generate new functions in bilayer systems by combining layers having different moduli and/or porosity, and to develop suitable processing techniques to access these structures.
Manufacturing processes of layered structures employ often organic solvents mostly causing environmental pollution. In this regard, the studied bilayer structures here were manufactured by processes free of organic solvents.
In this thesis, three bilayer systems were studied to answer the individual questions.
First, while various methods of introducing pores in melt-phase are reported for one-layer constructs with simple geometry, can such methods be applied to a bilayer structure, giving two porous layers?
This was addressed with Bilayer System 1. Two porous layers were obtained from melt-blending of two different polyurethanes (PU) and polyvinyl alcohol (PVA) in a co-continuous phase followed by sequential injection molding and leaching the PVA phase in deionized water. A porosity of 50 ± 5% with a high interconnectivity was obtained, in which the pore sizes in both layers ranged from 1 µm to 100 µm with an average of 22 µm in both layers. The obtained pores were tailored by applying an annealing treatment at relevant high temperatures of 110 °C and 130 °C, which allowed the porosity to be kept constant. The disadvantage of this system is that a maximum of 50% porosity could be reached and removal of leaching material in the weld line section of both layers is not guaranteed. Such a construct serves as a model for bilayer porous structure for determining structure-property relationships with respect to the pore size, porosity and mechanical properties of each layer. This fabrication method is also applicable to complex geometries by designing a relevant mold for injection molding.
Secondly, utilizing scCO2 foaming process at elevated temperature and pressure is considered as a green manufacturing process. Employing this method as a post-treatment can alter the history orientation of polymer chains created by previous fabrication methods. Can a bilayer structure be fabricated by a combination of sequential injection molding and scCO2 foaming process, in which a porous layer is supported by a compact layer?
Such a construct (Bilayer System 2) was generated by sequential injection molding of a PCL (Tm ≈ 58 °C) layer and a PLLA (Tg ≈ 58 °C) layer. Soaking this structure in the autoclave with scCO2 at T = 45 °C and P = 100 bar led to the selective foaming of PCL with a porosity of 80%, while the PLA layer was kept compact. The scCO2 autoclave led to the formation of a porous core and skin layer of the PCL, however, the degree of crystallinity of PLLA layer increased from 0 to 50% at the defined temperature and pressure. The microcellular structure of PCL as well as the degree of crystallinity of PLLA were controlled by increasing soaking time.
Thirdly, wrinkles on surfaces in micro/nano scale alter the properties, which are surface-related. Wrinkles are formed on a surface of a bilayer structure having a compliant substrate and a stiff thin film. However, the reported wrinkles were not reversible. Moreover, dynamic wrinkles in nano and micro scale have numerous examples in nature such as gecko foot hair offering reversible adhesion and an ability of lotus leaves for self-cleaning altering hydrophobicity of the surface. It was envisioned to imitate this biomimetic function on the bilayer structure, where self-assembly on/off patterns would be realized on the surface of this construct.
In summary, developing layered constructs having different properties/functions in the individual layer or exhibiting a new function as the consequence of layered structure can give novel insight for designing layered constructs in various disciplines such as packaging and transport industry, aerospace industry and health technology.
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.
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.
Residential segregation is a widespread phenomenon that can be observed in almost every major city. In these urban areas, residents with different ethnical or socioeconomic backgrounds tend to form homogeneous clusters. In Schelling’s classical segregation model two types of agents are placed on a grid. An agent is content with its location if the fraction of its neighbors, which have the same type as the agent, is at least 𝜏, for some 0 < 𝜏 ≤ 1. Discontent agents simply swap their location with a randomly chosen other discontent agent or jump to a random empty location. The model gives a coherent explanation of how clusters can form even if all agents are tolerant, i.e., if they agree to live in mixed neighborhoods. For segregation to occur, all it needs is a slight bias towards agents preferring similar neighbors.
Although the model is well studied, previous research focused on a random process point of view. However, it is more realistic to assume instead that the agents strategically choose where to live. We close this gap by introducing and analyzing game-theoretic models of Schelling segregation, where rational agents strategically choose their locations.
As the first step, we introduce and analyze a generalized game-theoretic model that allows more than two agent types and more general underlying graphs modeling the residential area. We introduce different versions of Swap and Jump Schelling Games. Swap Schelling Games assume that every vertex of the underlying graph serving as a residential area is occupied by an agent and pairs of discontent agents can swap their locations, i.e., their occupied vertices, to increase their utility. In contrast, for the Jump Schelling Game, we assume that there exist empty vertices in the graph and agents can jump to these vacant vertices if this increases their utility. We show that the number of agent types as well as the structure of underlying graph heavily influence the dynamic properties and the tractability of finding an optimal strategy profile.
As a second step, we significantly deepen these investigations for the swap version with 𝜏 = 1 by studying the influence of the underlying topology modeling the residential area on the existence of equilibria, the Price of Anarchy, and the dynamic properties. Moreover, we restrict the movement of agents locally. As a main takeaway, we find that both aspects influence the existence and the quality of stable states.
Furthermore, also for the swap model, we follow sociological surveys and study, asking the same core game-theoretic questions, non-monotone singlepeaked utility functions instead of monotone ones, i.e., utility functions that are not monotone in the fraction of same-type neighbors. Our results clearly show that moving from monotone to non-monotone utilities yields novel structural properties and different results in terms of existence and quality of stable states.
In the last part, we introduce an agent-based saturated open-city variant, the Flip Schelling Process, in which agents, based on the predominant type in their neighborhood, decide whether to change their types. We provide a general framework for analyzing the influence of the underlying topology on residential segregation and investigate the probability that an edge is monochrome, i.e., that both incident vertices have the same type, on random geometric and Erdős–Rényi graphs. For random geometric graphs, we prove the existence of a constant c > 0 such that the expected fraction of monochrome edges after the Flip Schelling Process is at least 1/2 + c. For Erdős–Rényi graphs, we show the expected fraction of monochrome edges after the Flip Schelling Process is at most 1/2 + o(1).
With the implementation of intense, short pulsed light sources throughout the last years, the powerful technique of resonant inelastic X-ray scattering (RIXS) became feasible for a wide range of experiments within femtosecond dynamics in correlated materials and molecules.
In this thesis I investigate the potential to bring RIXS into the fluence regime of nonlinear X-ray-matter interactions, especially focusing on the impact of stimulated scattering on RIXS in transition metal systems in a transmission spectroscopy geometry around transition metal L-edges.
After presenting the RIXS toolbox and the capabilities of free electron laser light sources for ultrafast intense X-ray experiments, the thesis explores an experiment designed to understand the impact of stimulated scattering on diffraction and direct beam transmission spectroscopy on a CoPd multilayer system. The experiments require short X-ray pulses that can only be generated at free electron lasers (FEL). Here the pulses are not only short, but also very intense, which opens the door to nonlinear X-ray-matter interactions. In the second part of this thesis, we investigate observations in the nonlinear interaction regime, look at potential difficulties for classic spectroscopy and investigate possibilities to enhance the RIXS through stimulated scattering. Here, a study on stimulated RIXS is presented, where we investigate the light field intensity dependent CoPd demagnetization in transmission as well as scattering geometry. Thereby we show the first direct observation of stimulated RIXS as well as light field induced nonlinear effects,
namely the breakdown of scattering intensity and the increase in sample transmittance. The topic is of ongoing interest and will just increase in relevance as more free electron lasers are planned and the number of experiments at such light sources will continue to increase in the near future.
Finally we present a discussion on the accessibility of small DOS shifts in the absorption-band of transition metal complexes through stimulated resonant X-ray scattering. As these shifts occur for example in surface states this finding could expand the experimental selectivity of NEXAFS and RIXS to the detectability of surface states. We show how stimulation can indeed enhance the visibility of DOS shifts through the detection of stimulated spectral shifts and enhancements in this theoretical study. We also forecast the observation of stimulated enhancements in resonant excitation experiments at FEL sources in systems with a high density of states just below the Fermi edge and in systems with an occupied to unoccupied DOS ratio in the valence band above 1.
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.
Carbonates carried in subducting slabs may play a major role in sourcing and storing carbon in the deep Earth’s interior. Current estimates indicate that between 40 to 66 million tons of carbon per year enter subduction zones, but it is uncertain how much of it reaches the lower mantle. It appears that most of this carbon might be extracted from subducting slabs at the mantle wedge and only a limited amount continues deeper and eventually reaches the deep mantle. However, estimations on deeply subducted carbon broadly range from 0.0001 to 52 million tons of carbon per year. This disparity is primarily due to the limited understanding of the survival of carbonate minerals during their transport to deep mantle conditions. Indeed, carbon has very low solubility in mantle silicates, therefore it is expected to be stored primarily in accessory phases such as carbonates. Among those carbonates, magnesite (MgCO3), as a single phase, is the most stable under all mantle conditions. However, experimental investigation on the stability of magnesite in contact with SiO2 at lower mantle conditions suggests that magnesite is stable only along a cold subducted slab geotherm. Furthermore, our understanding of magnesite’s stability when interacting with more complex mantle silicate phases remains incomplete. In the first part of this dissertation, laser-heated diamond anvil cells and multi-anvil apparatus experiments were performed to investigate the stability of magnesite in contact with iron-bearing mantle silicates. Sub-solidus reactions, melting, decarbonation and diamond formation were examined from shallow to mid-lower mantle conditions (25 to 68 GPa; 1300 to 2000 K). Multi-anvil experiments at 25 GPa show the formation of carbonate-rich melt, bridgmanite, and stishovite with melting occurring at a temperature corresponding to all geotherms except the coldest one. In situ X-ray diffraction, in laser-heating diamond anvil cells experiments, shows crystallization of bridgmanite and stishovite but no melt phase was detected in situ at high temperatures. To detect decarbonation phases such as diamond, Raman spectroscopy was used. Crystallization of diamonds is observed as a sub-solidus process even at temperatures relevant and lower than the coldest slab geotherm (1350 K at 33 GPa). Data obtained from this work suggest that magnesite is unstable in contact with the surrounding peridotite mantle in the upper-most lower mantle. The presence of magnesite instead induces melting under oxidized conditions and/or foster diamond formation under more reduced conditions, at depths ∼700 km. Consequently, carbonates will be removed from the carbonate-rich slabs at shallow lower mantle conditions, where subducted slabs can stagnate. Therefore, the transport of carbonate to deeper depths will be restricted, supporting the presence of a barrier for carbon subduction at the top of the lower mantle. Moreover, the reduction of magnesite, forming diamonds provides additional evidence that super-deep diamond crystallization is related to the reduction of carbonates or carbonated-rich melt.
The second part of this dissertation presents the development of a portable laser-heating system optimized for X-ray emission spectroscopy (XES) or nuclear inelastic scattering (NIS) spectroscopy with signal collection at near 90◦. The laser-heated diamond anvil cell is the only static pressure device that can replicate the pressure and temperatures of the Earth’s lower mantle and core. The high temperatures are reached by using high-powered lasers focused on the sample contained between the diamond anvils. Moreover, diamonds’ transparency to X-rays enables in situ X-ray spectroscopy measurements that can probe the sample under high-temperature and high-pressure conditions. Therefore, the development of portable laser-heating systems has linked high-pressure and temperature research with high-resolution X-ray spectroscopy techniques to synchrotron beamlines that do not have a dedicated, permanent, laser-heating system. A general description of the system is provided, as well as details on the use of a parabolic mirror as a reflective imaging objective for on-axis laser heating and radiospectrometric temperature measurements with zero attenuation of incoming X-rays. The parabolic mirror improves the accuracy of temperature measurements free from chromatic aberrations in a wide spectral range and its perforation permits in situ X-rays measurement at synchrotron facilities. The parabolic mirror is a well-suited alternative to refractive objectives in laser heating systems, which will facilitate future applications in the use of CO2 lasers.
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 central gas in half of all galaxy clusters shows short cooling times. Assuming unimpeded cooling, this should lead to high star formation and mass cooling rates, which are not observed. Instead, it is believed that condensing gas is accreted by the central black hole that powers an active galactic nuclei jet, which heats the cluster. The detailed heating mechanism remains uncertain. A promising mechanism invokes cosmic ray protons that scatter on self-generated magnetic fluctuations, i.e. Alfvén waves. Continuous damping of Alfvén waves provides heat to the intracluster medium. Previous work has found steady state solutions for a large sample of clusters where cooling is balanced by Alfvénic wave heating. To verify modeling assumptions, we set out to study cosmic ray injection in three-dimensional magnetohydrodynamical simulations of jet feedback in an idealized cluster with the moving-mesh code arepo. We analyze the interaction of jet-inflated bubbles with the turbulent magnetized intracluster medium.
Furthermore, jet dynamics and heating are closely linked to the largely unconstrained jet composition. Interactions of electrons with photons of the cosmic microwave background result in observational signatures that depend on the bubble content. Those recent observations provided evidence for underdense bubbles with a relativistic filling while adopting simplifying modeling assumptions for the bubbles. By reproducing the observations with our simulations, we confirm the validity of their modeling assumptions and as such, confirm the important finding of low-(momentum) density jets.
In addition, the velocity and magnetic field structure of the intracluster medium have profound consequences for bubble evolution and heating processes. As velocity and magnetic fields are physically coupled, we demonstrate that numerical simulations can help link and thereby constrain their respective observables. Finally, we implement the currently preferred accretion model, cold accretion, into the moving-mesh code arepo and study feedback by light jets in a radiatively cooling magnetized cluster. While self-regulation is attained independently of accretion model, jet density and feedback efficiencies, we find that in order to reproduce observed cold gas morphology light jets are preferred.
Cosmic rays (CRs) constitute an important component of the interstellar medium (ISM) of galaxies and are thought to play an essential role in governing their evolution. In particular, they are able to impact the dynamics of a galaxy by driving galactic outflows or heating the ISM and thereby affecting the efficiency of star-formation. Hence, in order to understand galaxy formation and evolution, we need to accurately model this non-thermal constituent of the ISM. But except in our local environment within the Milky Way, we do not have the ability to measure CRs directly in other galaxies. However, there are many ways to indirectly observe CRs via the radiation they emit due to their interaction with magnetic and interstellar radiation fields as well as with the ISM.
In this work, I develop a numerical framework to calculate the spectral distribution of CRs in simulations of isolated galaxies where a steady-state between injection and cooling is assumed. Furthermore, I calculate the non-thermal emission processes arising from the modelled CR proton and electron spectra ranging from radio wavelengths up to the very high-energy gamma-ray regime.
I apply this code to a number of high-resolution magneto-hydrodynamical (MHD) simulations of isolated galaxies, where CRs are included. This allows me to study their CR spectra and compare them to observations of the CR proton and electron spectra by the Voyager-1 satellite and the AMS-02 instrument in order to reveal the origin of the measured spectral features.
Furthermore, I provide detailed emission maps, luminosities and spectra of the non-thermal emission from our simulated galaxies that range from dwarfs to Milk-Way analogues to starburst galaxies at different evolutionary stages. I successfully reproduce the observed relations between the radio and gamma-ray luminosities with the far-infrared (FIR) emission of star-forming (SF) galaxies, respectively, where the latter is a good tracer of the star-formation rate. I find that highly SF galaxies are close to the limit where their CR population would lose all of their energy due to the emission of radiation, whereas CRs tend to escape low SF galaxies more quickly. On top of that, I investigate the properties of CR transport that are needed in order to match the observed gamma-ray spectra.
Furthermore, I uncover the underlying processes that enable the FIR-radio correlation (FRC) to be maintained even in starburst galaxies and find that thermal free-free-emission naturally explains the observed radio spectra in SF galaxies like M82 and NGC 253 thus solving the riddle of flat radio spectra that have been proposed to contradict the observed tight FRC.
Lastly, I scrutinise the steady-state modelling of the CR proton component by investigating for the first time the influence of spectrally resolved CR transport in MHD simulations on the hadronic gamma-ray emission of SF galaxies revealing new insights into the observational signatures of CR transport both spectrally and spatially.
The relevance of physical fitness for children’s and adolescents’ health is indisputable and it is crucial to regularly assess and evaluate children’s and adolescents’ individual physical fitness development to detect potential negative health consequences in time. Physical fitness tests are easy-to-administer, reliable, and valid which is why they should be widely used to provide information on performance development and health status of children and adolescents. When talking about development of physical fitness, two perspectives can be distinguished. One perspective is how the physical fitness status of children and adolescents changed / developed over the past decades (i.e., secular trends). The other perspective covers the analyses how physical fitness develops with increasing age due to growth and maturation processes. Although, the development of children’s and adolescents’ physical fitness has been extensively described and analyzed in the literature, still some questions remain to be uncovered that will be addressed in the present doctoral thesis.
Previous systematic reviews and meta-analyses have examined secular trends in children’s and adolescents’ physical fitness. However, considering that those analyses are by now 15 years old and that updates are available only to limited components of physical fitness, it is time to re-analyze the literature and examine secular trends for selected components of physical fitness (i.e., cardiorespiratory endurance, muscle strength, proxies of muscle power, and speed). Fur-thermore, the available studies on children’s development of physical fitness as well as the ef-fects of moderating variables such as age and sex have been investigated within a long-term ontogenetic perspective. However, the effects of age and sex in the transition from pre-puberty to puberty in the ninth year of life using a short-term ontogenetic perspective and the effect of timing of school enrollment on children’s development of physical fitness have not been clearly identified. Therefore, the present doctoral thesis seeks to complement the knowledge of children’s and adolescents’ physical fitness development by updating secular trend analysis in selected components of physical fitness, by examining short-term ontogenetic cross-sectional developmental differences in children`s physical fitness, and by comparing physical fitness of older- and younger-than-keyage children versus keyage-children. These findings provide valuable information about children’s and adolescents’ physical fitness development to help prevent potential deficits in physical fitness as early as possible and consequently ensure a holistic development and a lifelong healthy life.
Initially, a systematic review to provide an ‘update’ on secular trends in selected components of physical fitness (i.e., cardiorespiratory endurance, relative muscle strength, proxies of muscle power, speed) in children and adolescents aged 6 to 18 years was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guidelines. To examine short-term ontogenetic cross-sectional developmental differences and to compare physical fitness of older- and younger-than-keyage children versus keyage-children physical fitness data of 108,295 keyage-children (i.e., aged 8.00 to 8.99 years), 2,586 younger-than-keyage children (i.e., aged 7.00 to 7.99 years), and 26,540 older-than-keyage children (i.e., aged 9.00 to 9.99 years) from the third grade were analyzed. Physical fitness was assessed through the EMOTIKON test battery measuring cardiorespiratory endurance (i.e., 6-min-run test), coordina-tion (i.e., star-run test), speed (i.e., 20-m linear sprint test), and proxies of lower (i.e., standing long jump test) and upper limbs (i.e., ball-push test) muscle power. Statistical inference was based on Linear Mixed Models.
Findings from the systematic review revealed a large initial improvement and an equally large subsequent decline between 1986 and 2010 as well as a stabilization between 2010 and 2015 in cardiorespiratory endurance, a general trend towards a small improvement in relative muscle strength from 1972 to 2015, an overall small negative quadratic trend for proxies of muscle power from 1972 to 2015, and a small-to-medium improvement in speed from 2002 to 2015. Findings from the cross-sectional studies showed that even in a single prepubertal year of life (i.e., ninth year) physical fitness performance develops linearly with increasing chronological age, boys showed better performances than girls in all physical fitness components, and the components varied in the size of sex and age effects. Furthermore, findings revealed that older-than-keyage children showed poorer performance in physical fitness compared to keyage-children, older-than-keyage girls showed better performances than older-than-keyage boys, and younger-than-keyage children outperformed keyage-children.
Due to the varying secular trends in physical fitness, it is recommended to promote initiatives for physical activity and physical fitness for children and adolescents to prevent adverse effects on health and well-being. More precisely, public health initiatives should specifically consider exercising cardiorespiratory endurance and muscle strength because both components showed strong positive associations with markers of health. Furthermore, the findings implied that physical education teachers, coaches, or researchers can utilize a proportional adjustment to individually interpret physical fitness of prepubertal school-aged children. Special attention should be given to the promotion of physical fitness of older-than-keyage children because they showed poorer performance in physical fitness than keyage-children. Therefore, it is necessary to specifically consider this group and provide additional health and fitness programs to reduce their deficits in physical fitness experienced during prior years to guarantee a holistic development.
Search for light primordial black holes with VERITAS using gamma γ-ray and optical observations
(2023)
The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four imaging atmospheric Cherenkov telescopes (IACTs). VERITAS is sensitive to very-high-energy gamma-rays in the range of 100 GeV to >30 TeV. Hypothesized primordial black holes (PBHs) are attractive targets for IACTs. If they exist, their potential cosmological impact reaches beyond the candidacy for constituents of dark matter. The sublunar mass window is the largest unconstrained range of PBH masses. This thesis aims to develop novel concepts searching for light PBHs with VERITAS. PBHs below the sublunar window lose mass due to Hawking radiation. They would evaporate at the end of their lifetime, leading to a short burst of gamma-rays. If PBHs formed at about 10^15 g, the evaporation would occur nowadays. Detecting these signals might not only confirm the existence of PBHs but also prove the theory of Hawking radiation. This thesis probes archival VERITAS data recorded between 2012 and 2021 for possible PBH signals. This work presents a new automatic approach to assess the quality of the VERITAS data. The array-trigger rate and far infrared temperature are well suited to identify periods with poor data quality. These are masked by time cuts to obtain a consistent and clean dataset which contains about 4222 hours. The PBH evaporations could occur at any location in the field of view or time within this data. Only a blind search can be performed to identify these short signals. This thesis implements a data-driven deep learning based method to search for short transient signals with VERITAS. It does not depend on the modelling of the effective area and radial acceptance. This work presents the first application of this method to actual observational IACT data. This thesis develops new concepts dealing with the specifics of the data and the transient detection method. These are reflected in the developed data preparation pipeline and search strategies. After correction for trial factors, no candidate PBH evaporation is found in the data. Thus, new constraints of the local rate of PBH evaporations are derived. At the 99% confidence limit it is below <1.07 * 10^5 pc^-3 yr^-1. This constraint with the new, independent analysis approach is in the range of existing limits for the evaporation rate.
This thesis also investigates an alternative novel approach to searching for PBHs with IACTs. Above the sublunar window, the PBH abundance is constrained by optical microlensing studies. The sampling speed, which is of order of minutes to hours for traditional optical telescopes, is a limiting factor in expanding the limits to lower masses. IACTs are also powerful instruments for fast transient optical astronomy with up to O(ns) sampling. This thesis investigates whether IACTs might constrain the sublunar window with optical microlensing observations. This study confirms that, in principle, the fast sampling speed might allow extending microlensing searches into the sublunar mass window. However, the limiting factor for IACTs is the modest sensitivity to detect changes in optical fluxes. This thesis presents the expected rate of detectable events for VERITAS as well as prospects of possible future next-generation IACTs. For VERITAS, the rate of detectable microlensing events in the sublunar range is ~10^-6 per year of observation time. The future prospects for a 100 times more sensitive instrument are at ~0.05 events per year.
Sulfur is essential for the functionality of some important biomolecules in humans. Biomolecules like the Iron-sulfur clusters, tRNAs, Molybdenum cofactor, and some vitamins. The trafficking of sulfur involves proteins collectively called sulfurtransferase. Among these are TUM1, MOCS3, and NFS1.
This research investigated the role of TUM1 for molybdenum cofactor biosynthesis and cytosolic tRNA thiolation in humans. The rhodanese-like protein MOCS3 and the L-cysteine desulfurase (NFS1) have been previously demonstrated to interact with TUM1. These interactions suggested a dual function of TUM1 in sulfur transfer for Moco biosynthesis and cytosolic tRNA thiolation. TUM1 deficiency has been implicated to be responsible for a rare inheritable disorder known as mercaptolactate cysteine disulfiduria (MCDU), which is associated with a mental disorder. This mental disorder is similar to the symptoms of sulfite oxidase deficiency which is characterised by neurological disorders. Therefore, the role of TUM1 as a sulfurtransferase in humans was investigated, in CRISPR/Cas9 generated TUM1 knockout HEK 293T cell lines.
For the first time, TUM1 was implicated in Moco biosynthesis in humans by quantifying the intermediate product cPMP and Moco using HPLC. Comparing the TUM1 knockout cell lines to the wild-type, accumulation and reduction of cPMP and Moco were observed respectively. The effect of TUM1 knockout on the activity of a Moco-dependent enzyme, Sulfite oxidase, was also investigated. Sulfite oxidase is essential for the detoxification of sulfite to sulfate. Sulfite oxidase activity and protein abundance were reduced due to less availability of Moco. This shows that TUM1 is essential for efficient sulfur transfer for Moco biosynthesis. Reduction in cystathionin -lyase in TUM1 knockout cells was quantified, a possible coping mechanism of the cell against sulfite production through cysteine catabolism.
Secondly, the involvement of TUM1 in tRNA thio-modification at the wobble Uridine-34 was reported by quantifying the amount of mcm5s2U and mcm5U via HPLC. The reduction and accumulation of mcm5s2U and mcm5U in TUM1 knockout cells were observed in the nucleoside analysis. Herein, exogenous treatment with NaHS, a hydrogen sulfide donor, rescued the Moco biosynthesis, cytosolic tRNA thiolation, and cell proliferation deficits in TUM1 knockout cells.
Further, TUM1 was shown to impact mitochondria bioenergetics through the measurement of the oxygen consumption rate and extracellular acidification rate (ECAR) via the seahorse cell Mito stress analyzer. Reduction in total ATP production was also measured. This reveals how important TUM1 is for H2S biosynthesis in the mitochondria of HEK 293T.
Finally, the inhibition of NFS1 in HEK 293T and purified NFS1 protein by 2-methylene 3-quinuclidinone was demonstrated via spectrophotometric and radioactivity quantification. Inhibition of NFS1 by MQ further affected the iron-sulfur cluster-dependent enzyme aconitase activity.
Over the last decades, interest in the impact of the intestinal microbiota on host health has steadily increased. Diet is a major factor that influences the gut microbiota and thereby indirectly affects human health. For example, a high fat diet rich in saturated fatty acids led to an intestinal proliferation of the colitogenic bacterium Bilophila (B.) wadsworthia by stimulating the release of the bile acid taurocholate (TC). TC contains the sulfonated head group taurine, which undergoes conversion to sulfide (H2S) by B. wadsworthia. In a colitis prone murine animal model (IL10 / mice), the bloom of B. wadsworthia was accompanied by an exacerbation of intestinal inflammation. B. wadsworthia is able to convert taurine and also other sulfonates to H2S, indicating the potential association of sulfonate utilization and the stimulation of colitogenic bacteria.
This potential link raised the question, whether dietary sulfonates or their sulfonated metabolites stimulate the growth of colitogenic bacteria such as B. wadsworthia and whether these bacteria convert sulfonates to H2S. Besides taurine, which is present in meat, fish and life-style beverages, other dietary sulfonates are part of daily human nutrition. Sulfolipids such as sulfoquinovosyldiacylglycerols (SQDG) are highly abundant in salad, parsley and the cyanobacterium Arthrospira platensis (Spirulina). Based on previous findings, Escherichia (E.) coli releases the polar headgroup sulfoquinovose (SQ) from SQDG. Moreover, E. coli is able to convert SQ to 2,3 dihydroxypropane 1 sulfonate (DHPS) under anoxic conditions. DHPS is also converted to H2S by B. wadsworthia or by other potentially harmful gut bacteria such as members of the genus Desulfovibrio. However, only few studies report the conversion of sulfonates to H2S by bacteria directly isolated from the human intestinal tract. Most sulfonate utilizing bacteria were obtained from environmental sources such as soil or lake sediment or from potentially intestinal sources such as sewage.
In the present study, fecal slurries from healthy human subjects were incubated with sulfonates under strictly anoxic conditions, using formate and lactate as electron donors. Fecal slurries that converted sulfonates to H2S, were used as a source for the isolation of H2S forming bacteria. Isolates were identified based on their 16S ribosomal RNA (16S rRNA) gene sequence. In addition, conventional C57BL/6 mice were fed a semisynthetic diet supplemented with the SQDG rich Spirulina (SD) or a Spirulina free control diet (CD). During the intervention, body weight, water and food intake were monitored and fecal samples were collected. After three weeks, mice were killed and organ weight and size were measured, intestinal sulfonate concentrations were quantified, gut microbiota composition was determined and parameters of intestinal and hepatic fat metabolism were analyzed.
Human fecal slurries converted taurine, isethionate, cysteate, 3 sulfolacate, SQ and DHPS to H2S. However, inter individual differences in the degradation of these sulfonates were observed. Taurine, isethionate, and 3 sulfolactate were utilized by fecal microbiota of all donors, while SQ, DHPS and cysteate were converted to H2S only by microbiota from certain individuals. Bacterial isolates from human feces able to convert sulfonates to H2S were identified as taurine-utilizing Desulfovibrio strains, taurine- and isethionate-utilizing B. wadsworthia, or as SQ- and 3-sulfolactate- utilizing E. coli. In addition, a co culture of E. coli and B. wadsworthia led to complete degradation of SQ to H2S, with DHPS as an intermediate. Of the human fecal isolates, B. wadsworthia and Desulfovibrio are potentially harmful. E. coli strains might be also pathogenic, but isolated E. coli strains from human feces were identified as commensal gut bacteria.
Feeding SD to mice increased the cecal and fecal SQ concentration and altered the microbiota composition, but the relative abundance of SQDG or SQ converting bacteria and colitogenic bacteria was not enriched in mice fed SD for 21 days. SD did not affect the relative abundance of Enterobacteriaceae, to which the SQDG- and SQ-utilizing E. coli strain belong to. Furthermore, the abundance of B. wadsworthia decreased from day 2 to day 9 in feces, but recovered afterwards in the same mice. In cecum, the family Desulfovibrionaceae, to which B. wadsworthia and Desulfovibrio belong to, were reduced. No changes in the number of B. wadsworthia in cecal contents or of Desulfovibrionaceae in feces were observed. SD led to a mild activation of the immune system, which was not observed in control mice fed CD. Mice fed SD had an increased body weight, a higher adipose tissue weight, and a decreased liver weight compared to the control mice, suggesting an impact of Spirulina supplementation on fat metabolism. However, expression levels of genes involved in intestinal and hepatic intracellular lipid uptake and availability were reduced. Further investigations on the lipid metabolism at protein level could help to clarify these discrepancies.
In summary, humans differ in the ability of their fecal microbiota to utilize dietary sulfonates. While sulfonates stimulated the proliferation of potentially colitogenic isolates from human fecal slurries, the increased availability of SQ in Spirulina fed conventional mice did not lead to an enrichment of such bacteria. Presence or absence of these bacteria may explain the inter individual differences in sulfonate conversion observed for fecal slurries. This work provides new insights in the ability of intestinal bacteria to utilize sulfonates and thus, contributes to a better understanding of microbiota-mediated effects on dietary sulfonate utilization. Interestingly, feeding of the Spirulina-supplemented diet led to body-weight gain in mice in the first two days of intervention, the reasons for which are unknown.
Ribosomes decode mRNA to synthesize proteins. Ribosomes, once considered static, executing machines, are now viewed as dynamic modulators of translation. Increasingly detailed analyses of structural ribosome heterogeneity led to a paradigm shift toward ribosome specialization for selective translation. As sessile organisms, plants cannot escape harmful environments and evolved strategies to withstand. Plant cytosolic ribosomes are in some respects more diverse than those of other metazoans. This diversity may contribute to plant stress acclimation. The goal of this thesis was to determine whether plants use ribosome heterogeneity to regulate protein synthesis through specialized translation. I focused on temperature acclimation, specifically on shifts to low temperatures. During cold acclimation, Arabidopsis ceases growth for seven days while establishing the responses required to resume growth. Earlier results indicate that ribosome biogenesis is essential for cold acclimation. REIL mutants (reil-dkos) lacking a 60S maturation factor do not acclimate successfully and do not resume growth. Using these genotypes, I ascribed cold-induced defects of ribosome biogenesis to the assembly of the polypeptide exit tunnel (PET) by performing spatial statistics of rProtein changes mapped onto the plant 80S structure. I discovered that growth cessation and PET remodeling also occurs in barley, suggesting a general cold response in plants. Cold triggered PET remodeling is consistent with the function of Rei-1, a REIL homolog of yeast, which performs PET quality control. Using seminal data of ribosome specialization, I show that yeast remodels the tRNA entry site of ribosomes upon change of carbon sources and demonstrate that spatially constrained remodeling of ribosomes in metazoans may modulate protein synthesis. I argue that regional remodeling may be a form of ribosome specialization and show that heterogeneous cytosolic polysomes accumulate after cold acclimation, leading to shifts in the translational output that differs between wild-type and reil-dkos. I found that heterogeneous complexes consist of newly synthesized and reused proteins. I propose that tailored ribosome complexes enable free 60S subunits to select specific 48S initiation complexes for translation. Cold acclimated ribosomes through ribosome remodeling synthesize a novel proteome consistent with known mechanisms of cold acclimation. The main hypothesis arising from my thesis is that heterogeneous/ specialized ribosomes alter translation preferences, adjust the proteome and thereby activate plant programs for successful cold acclimation.
Reiz der Revolution
(2023)
Die Dissertation untersucht die vielseitigen Verflechtungen und Transfers im Rahmen der deutschen Nicaraguasolidarität der späten 1970er und der 1980er Jahre. Bereits im Vorfeld ihres Machtantritts hatten die Sandinistas in beiden Lagern um ausländische staatliche und zivile Unterstützung geworben. Nun gestalteten sie mit dem sandinistischen Reformstaat zugleich ein internationales Netz an Solidaritätsbeziehungen aus, die zur Finanzierung ihrer sozialreformerischen Programme, aber auch zur Legitimation ihrer Herrschaft dienten.
Allein in der Bundesrepublik entstanden mehrere hundert Solidaritätsgruppen. In der DDR löste die politische Führung eine staatlich gelenkte Solidarisierung mit Nicaragua aus, der sich zehntausende Menschen und unabhängige Basisinitiativen anschlossen. Trotz ihrer Verwurzelung in rivalisierenden Systemen und der Heterogenität ihrer Weltbilder – von christlicher Soziallehre bis zur kritischen Linken – arbeiteten etliche Solidaritätsinitiativen in beiden Ländern am selben Zielobjekt: einem Nicaragua jenseits der Blöcke. Gemeinsam mit ihren nicaraguanischen Projektpartner_innen eröffneten sie auf transnationaler Ebene einen neuen Raum für Kommunikation und stießen dabei auf Differenzen und Auseinandersetzungen über politische Ideen, die beiderseits des Atlantiks neue Praktiken anregten.
Die Forschungsarbeit basiert auf einer umfangreichen Quellenauswertung in insgesamt 13 Archiven, darunter das Archiv der Robert-Havemann-Gesellschaft, das Archiv der BStU, verschiedene westdeutsche Bewegungsarchive und die archivalischen Nachlässe des nicaraguanischen Kulturministeriums.
Reflexion und Reflexivität
(2023)
Reflexion gilt in der Lehrkräftebildung als eine Schlüsselkategorie der professionellen Entwicklung. Entsprechend wird auf vielfältige Weise die Qualität reflexionsbezogener Kompetenzen untersucht. Eine Herausforderung hierbei kann in der Annahme bestehen, von der Analyse schriftlicher Reflexionen unmittelbar auf die Reflexivität einer Person zu schließen, da Reflexion stets kontextspezifisch als Abbild reflexionsbezogener Argumentationsprozesse angesehen werden sollte und reflexionsbezogenen Dispositionen unterliegt. Auch kann die Qualität einer Reflexion auf mehreren Dimensionen bewertet werden, ohne quantifizierbare, absolute Aussagen treffen zu können.
Daher wurden im Rahmen einer Physik-Videovignette N = 134 schriftliche Fremdreflexionen verfasst und kontextspezifische reflexionsbezogene Dispositionen erhoben. Expert*innen erstellten theoriegeleitet Qualitätsbewertungen zur Breite, Tiefe, Kohärenz und Spezifität eines jeden Reflexionstextes. Unter Verwendung computerbasierter Klassifikations- und Analyseverfahren wurden weitere Textmerkmale erhoben. Mittels explorativer Faktorenanalyse konnten die Faktoren Qualität, Quantität und Deskriptivität gefunden werden. Da alle konventionell eingeschätzten Qualitätsbewertungen durch einen Faktor repräsentiert wurden, konnte ein maximales Qualitätskorrelat kalkuliert werden, zu welchem jede schriftliche Fremdreflexion im Rahmen der vorliegenden Vignette eine computerbasiert bestimmbare Distanz aufweist. Diese Distanz zum maximalen Qualitätskorrelat konnte validiert werden und kann die Qualität der schriftlichen Reflexionen unabhängig von menschlichen Ressourcen quantifiziert repräsentieren. Abschließend konnte identifiziert werden, dass ausgewählte Dispositionen in unterschiedlichem Maße mit der Reflexionsqualität zusammenhängen. So konnten beispielsweise bezogen auf das Physik-Fachwissen minimale Zusammenhänge identifiziert werden, wohingegen Werthaltung sowie wahrgenommene Unterrichtsqualität eng mit der Qualität einer schriftlichen Reflexion in Verbindung stehen können.
Es wird geschlussfolgert, dass reflexionsbezogene Dispositionen moderierenden Einfluss auf Reflexionen nehmen können. Es wird empfohlen bei der Erhebung von Reflexion mit dem Ziel der Kompetenzmessung ausgewählte Dispositionen mit zu erheben. Weiter verdeutlicht diese Arbeit die Möglichkeit, aussagekräftige Quantifizierungen auch in der Analyse komplexer Konstrukte vorzunehmen. Durch computerbasierte Qualitätsabschätzungen können objektive und individuelle Analysen und differenzierteres automatisiertes Feedback ermöglicht werden.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
The East African Rift System (EARS) is a significant example of active tectonics, which provides opportunities to examine the stages of continental faulting and landscape evolution. The southwest extension of the EARS is one of the most significant examples of active tectonics nowadays, however, seismotectonic research in the area has been scarce, despite the fundamental importance of neotectonics. Our first study area is located between the Northern Province of Zambia and the southeastern Katanga Province of the Democratic Republic of Congo. Lakes Mweru and Mweru Wantipa are part of the southwest extension of the EARS. Fault analysis reveals that, since the Miocene, movements along the active Mweru-Mweru Wantipa Fault System (MMFS) have been largely responsible for the reorganization of the landscape and the drainage patterns across the southwestern branch of the EARS. To investigate the spatial and temporal patterns of fluvial-lacustrine landscape development, we determined in-situ cosmogenic 10Be and 26Al in a total of twenty-six quartzitic bedrock samples that were collected from knickpoints across the Mporokoso Plateau (south of Lake Mweru) and the eastern part of the Kundelungu Plateau (north of Lake Mweru). Samples from the Mporokoso Plateau and close to the MMFS provide evidence of temporary burial. By contrast, surfaces located far from the MMFS appear to have remained uncovered since their initial exposure as they show consistent 10Be and 26Al exposure ages ranging up to ~830 ka. Reconciliation of the observed burial patterns with morphotectonic and stratigraphic analysis reveals the existence of an extensive paleo-lake during the Pleistocene. Through hypsometric analyses of the dated knickpoints, the potential maximum water level of the paleo-lake is constrained to ~1200 m asl (present lake lavel: 917 m asl). High denudation rates (up to ~40 mm ka-1) along the eastern Kundelungu Plateau suggest that footwall uplift, resulting from normal faulting, caused river incision, possibly controlling paleo-lake drainage. The lake level was reduced gradually reaching its current level at ~350 ka.
Parallel to the MMFS in the north, the Upemba Fault System (UFS) extends across the southeastern Katanga Province of the Democratic Republic of Congo. This part of our research is focused on the geomorphological behavior of the Kiubo Waterfalls. The waterfalls are the currently active knickpoint of the Lufira River, which flows into the Upemba Depression. Eleven bedrock samples along the Lufira River and its tributary stream, Luvilombo River, were collected. In-situ cosmogenic 10Be and 26Al were used in order to constrain the K constant of the Stream Power Law equation. Constraining the K constant allowed us to calculate the knickpoint retreat rate of the Kiubo Waterfalls at ~0.096 m a-1. Combining the calculated retreat rate of the knickpoint with DNA sequencing from fish populations, we managed to present extrapolation models and estimate the location of the onset of the Kiubo Waterfalls, revealing its connection to the seismicity of the UFS.
Today, point clouds are among the most important categories of spatial data, as they constitute digital 3D models of the as-is reality that can be created at unprecedented speed and precision. However, their unique properties, i.e., lack of structure, order, or connectivity information, necessitate specialized data structures and algorithms to leverage their full precision. In particular, this holds true for the interactive visualization of point clouds, which requires to balance hardware limitations regarding GPU memory and bandwidth against a naturally high susceptibility to visual artifacts.
This thesis focuses on concepts, techniques, and implementations of robust, scalable, and portable 3D visualization systems for massive point clouds. To that end, a number of rendering, visualization, and interaction techniques are introduced, that extend several basic strategies to decouple rendering efforts and data management: First, a novel visualization technique that facilitates context-aware filtering, highlighting, and interaction within point cloud depictions. Second, hardware-specific optimization techniques that improve rendering performance and image quality in an increasingly diversified hardware landscape. Third, natural and artificial locomotion techniques for nausea-free exploration in the context of state-of-the-art virtual reality devices. Fourth, a framework for web-based rendering that enables collaborative exploration of point clouds across device ecosystems and facilitates the integration into established workflows and software systems.
In cooperation with partners from industry and academia, the practicability and robustness of the presented techniques are showcased via several case studies using representative application scenarios and point cloud data sets. In summary, the work shows that the interactive visualization of point clouds can be implemented by a multi-tier software architecture with a number of domain-independent, generic system components that rely on optimization strategies specific to large point clouds. It demonstrates the feasibility of interactive, scalable point cloud visualization as a key component for distributed IT solutions that operate with spatial digital twins, providing arguments in favor of using point clouds as a universal type of spatial base data usable directly for visualization purposes.