Refine
Has Fulltext
- yes (155) (remove)
Year of publication
- 2023 (155) (remove)
Document Type
- Doctoral Thesis (155) (remove)
Language
- English (155) (remove)
Is part of the Bibliography
- yes (155)
Keywords
- climate change (9)
- Klimawandel (8)
- machine learning (5)
- Modellierung (3)
- körperliche Fitness (3)
- maschinelles Lernen (3)
- physical fitness (3)
- reinforcement learning (3)
- Anden (2)
- Andes (2)
Institute
- Institut für Biochemie und Biologie (23)
- Extern (22)
- Institut für Geowissenschaften (22)
- Institut für Physik und Astronomie (20)
- Hasso-Plattner-Institut für Digital Engineering GmbH (17)
- Institut für Chemie (15)
- Institut für Umweltwissenschaften und Geographie (11)
- Department Psychologie (6)
- Department Sport- und Gesundheitswissenschaften (6)
- Institut für Ernährungswissenschaft (5)
- Department Linguistik (4)
- Institut für Mathematik (4)
- Digital Engineering Fakultät (3)
- Fachgruppe Betriebswirtschaftslehre (3)
- Fachgruppe Politik- & Verwaltungswissenschaft (3)
- Institut für Informatik und Computational Science (3)
- Department Erziehungswissenschaft (2)
- Applied Computational Linguistics (1)
- Fachgruppe Soziologie (1)
- Fachgruppe Volkswirtschaftslehre (1)
- Fakultät für Gesundheitswissenschaften (1)
- Institut für Künste und Medien (1)
- Patholinguistics/Neurocognition of Language (1)
- Phonology & Phonetics (1)
- Potsdam Institute for Climate Impact Research (PIK) e. V. (1)
- Strukturbereich Kognitionswissenschaften (1)
- Wirtschaftswissenschaften (1)
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.
Watershed management requires an understanding of key hydrochemical processes. The Pra Basin is one of the five major river basins in Ghana with a population of over 4.2 million people. Currently, water resources management faces challenges due to surface water pollution caused by the unregulated release of untreated household and industrial waste into aquatic ecosystems and illegal mining activities. This has increased the need for groundwater as the most reliable water supply. Our understanding of groundwater recharge mechanisms and chemical evolution in the basin has been inadequate, making effective management difficult. Therefore, the main objective of this work is to gain insight into the processes that determine the hydrogeochemical evolution of groundwater quality in the Pra Basin. The combined use of stable isotope, hydrochemistry, and water level data provides the basis for conceptualizing the chemical evolution of groundwater in the Pra Basin. For this purpose, the origin and evaporation rates of water infiltrating into the unsaturated zone were evaluated. In addition, Chloride Mass Balance (CMB) and Water Table Fluctuations (WTF) were considered to quantify groundwater recharge for the basin. Indices such as water quality index (WQI), sodium adsorption ratio (SAR), Wilcox diagram, and salinity (USSL) were used in this study to determine the quality of the resource for use as drinking water and for irrigation purposes. Due to the heterogeneity of the hydrochemical data, the statistical techniques of hierarchical cluster and factor analysis were applied to subdivide the data according to their spatial correlation. A conceptual hydrogeochemical model was developed and subsequently validated by applying combinatorial inverse and reaction pathway-based geochemical models to determine plausible mineral assemblages that control the chemical composition of the groundwater. The interactions between water and rock determine the groundwater quality in the Pra Basin. The results underline that the groundwater is of good quality and can be used for drinking water and irrigation purposes. It was demonstrated that there is a large groundwater potential to meet the entire Pra Basin’s current and future water demands. The main recharge area was identified as the northern zone, while the southern zone is the discharge area. The predominant influence of weathering of silicate minerals plays a key role in the chemical evolution of the groundwater. The work presented here provides fundamental insights into the hydrochemistry of the Pra Basin and provides data important to water managers for informed decision-making in planning and allocating water resources for various purposes. A novel inverse modelling approach was used in this study to identify different mineral compositions that determine the chemical evolution of groundwater in the Pra Basin. This modelling technique has the potential to simulate the composition of groundwater at the basin scale with large hydrochemical heterogeneity, using average water composition to represent established spatial groupings of water chemistry.
We live in an era driven by fossil fuels. The prevailing climate change suggests that we have to significantly reduce greenhouse gas emissions. The only way forward is to use renewable energy sources. Among those, solar energy is a clean, affordable, and sustainable source of energy. It has the potential to satisfy the world’s energy demand in the future. However, there is a need to develop new materials that can make solar energy usable. Photovoltaics (PV) are devices that convert photon energy into electrical energy. The most commonly used solar cells are based on crystalline silicon. However, the fabrication process for silicon solar cells is technologically difficult and costly. Solar cells based on lead halide perovskites (PSCs) have emerged as a new candidate for PV applications since 2009. To date, PSCs have achieved 26% power-conversion-efficiency (PCE) for its single junction, and 33.7% PCE for tandem junction devices. However, there is still room for improvement in overall performance. The main challenge for the commercialization of this technology is the stability of the solar cells under operational conditions. Inorganic perovskite CsPbI3 has attracted researchers’ interest due to its stability at elevated temperatures, however, inorganic perovskites also have associated challenges, e.g. phase stability, larger voltage loss compared to their organic-inorganic hybrid counterparts, and interface energy misalignment. The most efficient inorganic perovskite solar cell is stable for up to a few hundred hours while the most stable device in the field of inorganic PSCs reported so far is at 17% PCE. This suggests the need for improvement of the interfaces for enhanced open circuit voltage (VOC), and optimization of the energy alignment at the interfaces. This dissertation presents the study on interfaces between the perovskite layer and hole transport layer (HTL) for stable CsPbI3 solar cells.
The first part of the thesis presents an investigation of the CsPbI3 film annealing environment and its subsequent effects on the perovskite/HTL interface dynamics. Thin films annealed in dry air were compared with thin films annealed in ambient air. Synchrotron-based hard X-ray spectroscopy (HAXPES) measurements reveal that annealing in ambient air does not have an adverse effect; instead, those samples undergo surface band bending. This surface band modification induces changes in interface charge dynamics and, consequently, an improvement in charge extraction at the interfaces. Further, transient surface photovoltage (tr-SPV) simulations show that air-annealed samples exhibit fewer trap states compared to samples annealed in dry air. Finally, by annealing the CsPbI3 films in ambient air, a PCE of 19.8% and Voc of 1.23 V were achieved for an n-i-p structured device.
Interface engineering has emerged as a strategy to extract the charge and optimize the energy alignment in perovskite solar cells (PSCs). An interface with fewer trap states and energy band levels closer to the selective contact helps to attain improved efficiencies in PSCs. The second part of the thesis presents a design for the CsPbI3/HTM interface. In this work, an interface between CsPbI3 perovskite and its hole selective contact N2,N2,N2′,N2′,N7,N7,N7′,N7′-octakis(4-methoxyphenyl)-9,9′-spirobi[9H-fluorene]-2,2′,7,7′-tetramine(Spiro-OMeTAD), realized by trioctylphosphine oxide (TOPO), a dipole molecule is introduced. On top of a perovskite film well-passivated by n-octyl ammonium Iodide (OAI), it created an upward surface band-bending at the interface byTOPO that optimizes energy level alignment and enhances the extraction of holes from the perovskite layer to the hole transport material. Consequently, a Voc of 1.2 V and high-power conversion efficiency (PCE) of over 19% were achieved for inorganic CsPbI3 perovskite solar cells. In addition, the work also sheds light on the interfacial charge-selectivity and the long-term stability of CsPbI3 perovskite solar cells.
The third part of the thesis extends the previous studies to polymeric poly(3-hexylthiophene-2,5-diyl) (P3HT) as HTL. The CsPbI3/P3HT interface is critical due to high non-radiative recombination. This work presents a CsPbI3/P3HT interface modified with a long-chain alkyl halide molecule, n-hexyl trimethyl ammonium bromide (HTAB). This molecule largely passivates the CsPbI3 perovskite surface and improves the charge extraction across the interface. Consequently, a Voc of over 1.00 V and 14.2% PCE were achieved for CsPbI3 with P3HT as HTM.
Overall the results presented in this dissertation introduce and discuss methods to design and study the interfaces in CsPbI3-based solar cells. This study can pave the way for novel interface designs between CsPbI3 and HTM for charge extraction, efficiency and stability.
Within the context of United Nations (UN) environmental institutions, it has become apparent that intergovernmental responses alone have been insufficient for dealing with pressing transboundary environmental problems. Diverging economic and political interests, as well as broader changes in power dynamics and norms within global (environmental) governance, have resulted in negotiation and implementation efforts by UN member states becoming stuck in institutional gridlock and inertia. These developments have sparked a renewed debate among scholars and practitioners about an imminent crisis of multilateralism, accompanied by calls for reforming UN environmental institutions. However, with the rise of transnational actors and institutions, states are not the only relevant actors in global environmental governance. In fact, the fragmented architectures of different policy domains are populated by a hybrid mix of state and non-state actors, as well as intergovernmental and transnational institutions. Therefore, coping with the complex challenges posed by severe and ecologically interdependent transboundary environmental problems requires global cooperation and careful management from actors beyond national governments.
This thesis investigates the interactions of three intergovernmental UN treaty secretariats in global environmental governance. These are the secretariats of the United Nations Framework Convention on Climate Change, the Convention on Biological Diversity, and the United Nations Convention to Combat Desertification. While previous research has acknowledged the increasing autonomy and influence of treaty secretariats in global policy-making, little attention has been paid to their strategic interactions with non-state actors, such as non-governmental organizations, civil society actors, businesses, and transnational institutions and networks, or their coordination with other UN agencies. Through qualitative case-study research, this thesis explores the means and mechanisms of these interactions and investigates their consequences for enhancing the effectiveness and coherence of institutional responses to underlying and interdependent environmental issues.
Following a new institutionalist ontology, the conceptual and theoretical framework of this study draws on global governance research, regime theory, and scholarship on international bureaucracies. From an actor-centered perspective on institutional interplay, the thesis employs concepts such as orchestration and interplay management to assess the interactions of and among treaty secretariats. The research methodology involves structured, focused comparison, and process-tracing techniques to analyze empirical data from diverse sources, including official documents, various secondary materials, semi-structured interviews with secretariat staff and policymakers, and observations at intergovernmental conferences.
The main findings of this research demonstrate that secretariats employ tailored orchestration styles to manage or bypass national governments, thereby raising global ambition levels for addressing transboundary environmental problems. Additionally, they engage in joint interplay management to facilitate information sharing, strategize activities, and mobilize relevant actors, thereby improving coherence across UN environmental institutions. Treaty secretariats play a substantial role in influencing discourses and knowledge exchange with a wide range of actors. However, they face barriers, such as limited resources, mandates, varying leadership priorities, and degrees of politicization within institutional processes, which may hinder their impact. Nevertheless, the secretariats, together with non-state actors, have made progress in advancing norm-building processes, integrated policy-making, capacity building, and implementation efforts within and across framework conventions. Moreover, they utilize innovative means of coordination with actors beyond national governments, such as data-driven governance, to provide policy-relevant information for achieving overarching governance targets.
Importantly, this research highlights the growing interactions between treaty secretariats and non-state actors, which not only shape policy outcomes but also have broader implications for the polity and politics of international institutions. The findings offer opportunities for rethinking collective agency and actor dynamics within UN entities, addressing gaps in institutionalist theory concerning the interaction of actors in inter-institutional spaces. Furthermore, the study addresses emerging challenges and trends in global environmental governance that are pertinent to future policy-making. These include reflections for the debate on reforming international institutions, the role of emerging powers in a changing international world order, and the convergence of public and private authority through new alliance-building and a division of labor between international bureaucracies and non-state actors in global environmental governance.
Animal movement is a crucial aspect of life, influencing ecological and evolutionary processes. It plays an important role in shaping biodiversity patterns, connecting habitats and ecosystems. Anthropogenic landscape changes, such as in agricultural environments, can impede the movement of animals by affecting their ability to locate resources during recurring movements within home ranges and, on a larger scale, disrupt migration or dispersal. Inevitably, these changes in movement behavior have far-reaching consequences on the mobile link functions provided by species inhabiting such extensively altered matrix areas. In this thesis, I investigate the movement characteristics and activity patterns of the European hare (Lepus europaeus), aiming to understand their significance as a pivotal species in fragmented agricultural landscapes. I reveal intriguing results that shed light on the importance of hares for seed dispersal, the influence of personality traits on behavior and space use, the sensitivity of hares to extreme weather conditions, and the impacts of GPS collaring on mammals' activity patterns and movement behavior.
In Chapter I, I conducted a controlled feeding experiment to investigate the potential impact of hares on seed dispersal. By additionally utilizing GPS data of hares in two contrasting landscapes, I demonstrated that hares play a vital role, acting as effective mobile linkers for many plant species in small and isolated habitat patches. The analysis of seed intake and germination success revealed that distinct seed traits, such as density, surface area, and shape, profoundly affect hares' ability to disperse seeds through endozoochory. These findings highlight the interplay between hares and plant communities and thus provide valuable insights into seed dispersal mechanisms in fragmented landscapes.
By employing standardized behavioral tests in Chapter II, I revealed consistent behavioral responses among captive hares while simultaneously examining the intricate connection between personality traits and spatial patterns within wild hare populations. This analysis provides insights into the ecological interactions and dynamics within hare populations in agricultural habitats. Examining the concept of animal personality, I established a link between personality traits and hare behavior. I showed that boldness, measured through standardized tests, influences individual exploration styles, with shy and bold hares exhibiting distinct space use patterns. In addition to providing valuable insights into the role of animal personality in heterogeneous environments, my research introduced a novel approach demonstrating the feasibility of remotely assessing personality types using animal-borne sensors without additional disturbance of the focal individual.
While climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe, in Chapter III, I uncovered the sensitivity of hares to temperature, humidity, and wind speed during their peak reproduction period. I found a strong response in activity to high temperatures above 25°C, with a particularly pronounced effect during temperature extremes of over 35°C. The non-linear relationship between temperature and activity was characterized by contrasting responses observed for day and night. These findings emphasize the vulnerability of hares to climate change and the potential consequences for their fitness and population dynamics with the ongoing rise of temperature.
Since such insights can only be obtained through capturing and tagging free-ranging animals, I assessed potential impacts and the recovery process post-collar attachment in Chapter IV. For this purpose, I examined the daily distances moved and the temporal-associated activity of 1451 terrestrial mammals out of 42 species during their initial tracking period. The disturbance intensity and the speed of recovery varied across species, with herbivores, females, and individuals captured and collared in relatively secluded study areas experiencing more pronounced disturbances due to limited anthropogenic influences.
Mobile linkers are essential for maintaining biodiversity as they influence the dynamics and resilience of ecosystems. Furthermore, their ability to move through fragmented landscapes makes them a key component for restoring disturbed sites. Individual movement decisions determine the scale of mobile links, and understanding variations in space use among individuals is crucial for interpreting their functions. Climate change poses further challenges, with wildlife species expected to adjust their behavior, especially in response to high-temperature extremes, and comprehending the anthropogenic influence on animal movements will remain paramount to effective land use planning and the development of successful conservation strategies.
This thesis provides a comprehensive ecological understanding of hares in agricultural landscapes. My research findings underscore the importance of hares as mobile linkers, the influence of personality traits on behavior and spatial patterns, the vulnerability of hares to extreme weather conditions, and the immediate consequences of collar attachment on mammalian movements. Thus, I contribute valuable insights to wildlife conservation and management efforts, aiding in developing strategies to mitigate the impact of environmental changes on hare populations. Moreover, these findings enable the development of methodologies aimed at minimizing the impacts of collaring while also identifying potential biases in the data, thereby benefiting both animal welfare and the scientific integrity of localization studies.
Background: Physical fitness is a key aspect of children’s ability to perform activities of daily living, engage in leisure activities, and is associated with important health characteristics. As such, it shows multi-directional associations with weight status as well as executive functions, and varies according to a variety of moderating factors, such as the child’s gender, age, geographical location, and socioeconomic conditions and context. The assessment and monitoring of children’s physical fitness has gained attention in recent decades, as has the question of how to promote physical fitness through the implementation of a variety of programs and interventions. However, these programs and interventions rarely focus on children with deficits in their physical fitness. Due to their deficits, these children are at the highest risk of suffering health impairments compared to their more average fit peers. In efforts to promote physical fitness, schools could offer promising and viable approaches to interventions, as they provide access to large youth populations while providing useful infrastructure. Evidence suggests that school-based physical fitness interventions, particularly those that include supplementary physical education, are useful for promoting and improving physical fitness in children with normal fitness. However, there is little evidence on whether these interventions have similar or even greater effects on children with deficits in their physical fitness. Furthermore, the question arises whether these measures help to sustainably improve the development/trajectories of physical fitness in these children.
The present thesis aims to elucidate the following four objectives: (1) to evaluate the effects of a 14 week intervention with 2 x 45 minutes per week additional remedial physical education on physical fitness and executive function in children with deficits in their physical fitness; (2) to assess moderating effects of body height and body mass on physical fitness components in children with physical fitness deficits; (3) to assess moderating effects of age and skeletal growth on physical fitness in children with physical fitness deficits; and (4) to analyse moderating effects of different physical fitness components on executive function in children with physical fitness deficits.
Methods: Using physical fitness data from the EMOTIKON study, 76 third graders with physical fitness deficits were identified in 11 schools in Brandenburg state that met the requirements for implementing a remedial physical education intervention (i.e., employing specially trained physical education teachers). The fitness intervention was implemented in a cross-over design and schools were randomly assigned to either an intervention-control or control-intervention group. The remedial physical education intervention consisted of a 14 week, 2 x 45 minutes per week remedial physical education curriculum supplemented by a physical exercise homework program. Assessments were conducted at the beginning and end of each intervention and control period, and further assessments were conducted at the beginning and end of each school year until the end of sixth grade. Physical fitness as the primary outcome was assessed using fitness tests implemented in the EMOTIKON study (i.e., lower body muscular strength (standing long jump), speed (20 m sprint), cardiorespiratory fitness (6 min run), agility (star run), upper body muscular strength (ball push test), and balance (one leg balance)). Executive functions as a secondary outcome were assessed using attention and psychomotor processing speed (digit symbol substitution test), mental flexibility and fine motor skills (trail making test), and inhibitory control (Simon task). Anthropometric measures such as body height, body mass, maturity offset, and body composition parameters, as well as socioeconomic information were recorded as potential moderators.
Results: (1) The evaluation of possible effects of the remedial physical education intervention on physical fitness and executive functions of children with deficits in their physical fitness did not reveal any detectable intervention-related improvements in physical fitness or executive functions. The implemented analysis strategies also showed moderating effects of body mass index (BMI) on performance in 6 min run, star run, and standing long jump, with children with a lower BMI performing better, moderating effects of proximity to Berlin on performance in the 6 min run and standing long jump, better performances being found in children living closer to Berlin, and overall gendered differences in executive function test performance, with boys performing better compared to girls. (2) Analysing moderating effects of body height and body mass on physical fitness performance, better overall physical fitness performance was found for taller children. For body mass, a negative effect was found on performance in the 6 min run (linear), standing long jump (linear), and 20 m sprint (quadratic), with better performance associated with lighter children, and a positive effect of body mass on performance in the ball push test, with heavier children performing better. In addition, the analysis revealed significant interactions between body height and body mass on performance in 6 min run and 20 m sprint, with higher body mass being associated with performance improvements in larger children, while higher body mass was associated with performance declines in smaller children. In addition, the analysis revealed overall age-related improvements in physical fitness and was able to show that children with better overall physical fitness also elicit greater age-related improvements. (3) In the analysis of moderating effects of age and maturity offset on physical fitness performances, two unrotated principal components of z-transformed age and maturity offset values were calculated (i.e., relative growth = (age + maturity offset)/2; growth delay = (age - maturity offset)) to avoid colinearity. Analysing these constructs revealed positive effects of relative growth on performances in star run, 20 m sprint, and standing long jump, with children of higher relative growth performing better. For growth delay, positive effects were found on performances in 6 min run and 20 m sprint, with children having larger growth delays showing better performances. Further, the model revealed gendered differences in 6 min run and 20 m sprint performances with girls performing better than boys. (4) Analysing the effects of physical fitness tests on executive function revealed a positive effect of star run and one leg balance performance and a negative effect of 6 min run performance on reaction speed in the Simon task. However, these effects were not detectable when individual differences were accounted for. Then these effects showed overall positive effects, with better performances being associated with faster reaction speeds. In addition, the analysis revealed a positive correlation between overall reaction speed and effects of the 6 min run, suggesting that children with greater effects of 6 min run had faster overall reaction speeds. Negative correlations were found between star run effects and age effects on Simon task reaction speed, meaning that children with larger star run effects had smaller age effects, and between 6 min run effects and star run effects on Simon task reaction speed, meaning that children with larger 6 min run effects tended to have smaller star run effects on Simon task reaction speed and vice versa.
Conclusions: (1) The lack of detectable intervention-related effects could have been caused by an insufficient intervention period, by the implementation of comprehensive and thus non- specific exercises, or by both. Accordingly, longer intervention periods and/or more specific exercises may have been more beneficial and could have led to detectable improvements in physical fitness and/or executive function. However, it remains unclear whether these interventions can benefit children with deficits in physical fitness, as it is possible that their deficits are not caused by a mere lack of exercise, but rather depend on the socioeconomic conditions of the children and their families and areas. Therefore, further research is needed to assess the moderation of physical fitness in children with physical fitness deficits and, in particular, the links between children’s environment and their physical fitness trajectories. (2) Findings from this work suggest that using BMI as a composite of body height and body mass may not be able to capture the variation associated with these parameters and their interactions. In particular, because of their multidirectional associations, further research would help elucidate how BMI and its subcomponents influence physical fitness and how they vary between children with and without physical fitness deficits. (3) The assessment of growth- related changes indicated negative effects associated with the growth spurt approaching age of peak height velocity, and furthermore showed significant differences in these effects between children. Thus, these effects and possible interindividual differences should be considered in the assessment of the development of physical fitness in children. (4) Furthermore, this work has shown that the associations between physical fitness and executive functions vary between children and may be moderated by children’s socioeconomic conditions and the structure of their daily activities. Further research is needed to explore these associations using approaches that account for individual variance.
In this work, the role of the TusA protein was investigated for the cell functionality and FtsZ ring assembly in Escherichia coli. TusA is the tRNA-2-thiouridine synthase that acts as a sulfur transferase in tRNA thiolation for the formation of 2-thiouridine at the position 34 (wobble base) of tRNALys, tRNAGlu and tRNAGln. It binds the persulfide form of sulfur and transfers it to further proteins during mnm5s2U tRNA modification at wobble position and for Moco biosynthesis. With this thiomodification of tRNA, the ribosome binding is more efficient and frameshifting is averted during the protein translation. Previous studies have revealed an essential role of TusA in bacterial cell physiology since deletion of the tusA gene resulted in retarded growth and filamentous cells during the exponential growth phase in a rich medium which suddenly disappeared during the stationary phase. This indicates a problem in the cell division process. Therefore the focus of this work was to investigate the role of TusA for cell functionality and FtsZ ring formation and thus the cell separation.
The reason behind the filamentous growth of the tusA mutant strain was investigated by growth and morphological analyses. ΔtusA cells showed a retarded growth during the exponential phase compared to the WT strain. Also, morphological analysis of ΔtusA cells confirmed the filamentous cell shape. The growth and cell division defects in ΔtusA indicated a defect in FtsZ protein as a key player of cell division. The microscopic investigation revealed that filamentous ΔtusA cells possessed multiple DNA parts arranged next to each other. This suggested that although the DNA replication occurred correctly, there was a defect in the step where FtsZ should act; probably FtsZ is unable to assemble to the ring structure or the assembled ring is not able to constrict. All tested mutant strains (ΔtusD, ΔtusE and ΔmnmA) involved in the mnm5s2U34 tRNA modification pathway shared the similar retarded growth and filamentous cell shape like ΔtusA strain. Thus, the cell division defect arises from a defect in mnm5s2U34 tRNA thiolation.
Since the FtsZ ring formation was supposed to be defective in filaments, a possible intracellular interaction of TusA and FtsZ was examined by fluorescent (EGFP and mCherry) fusion proteins expression and FRET. FtsZ expressing tusA mutant (DE3) cells showed a red mCherry signal at the cell poles, indicating that FtsZ is still in the assembling phase. Interestingly, the cellular region of EGFP-TusA fusion protein expressed in ΔtusA (DE3) was conspicuous; the EGFP signal was spread throughout the whole cell and, in addition, a slight accumulation of the EGFP-TusA fluorescence was detectable at the cell poles, the same part of the cell as for mCherry-FtsZ. Thus, this strongly suggested an interaction of TusA and FtsZ.
Furthermore, the cellular FtsZ and Fis concentrations, and their change during different growth phases were determined via immunoblotting. All tested deletion strains of mnm5s2U34 tRNA modification show high cellular FtsZ and Fis levels in the exponential phase, shifting to the later growth phases. This shift reflects the retarded growth, whereby the deletion strains reach later the exponential phase. Conclusively, the growth and cell division defect, and thus the formation of filaments, is most likely caused by changes in the cellular FtsZ and Fis concentrations.
Finally, the translation efficiencies of certain proteins (RpoS, Fur, Fis and mFis) in tusA mutant and in additional gene deletion strains were studied whether they were affected by using unmodified U34 tRNAs of Lys, Glu and Gln. The translation efficiency is decreased in mnm5s2U34 tRNA modification-impaired strains in addition to their existing growth and cell division defect due to the elimination of these three amino acids. Finally, these results confirm and reinforce the importance of Lys, Glu and Gln and the mnm5s2U34 tRNA thiolation for efficient protein translation. Thus, these findings verify that the translation of fur, fis and rpoS is regulated by mnm5s2U34 tRNA modifications, which is growth phase-dependent.
In total, this work showed the importance of the role of TusA for bacterial cell functionality and physiology. The deletion of the tusA gene disrupted a complex regulatory network within the cell, that most influenced by the decreased translation of Fis and RpoS, caused by the absence of mnm5s2U34 tRNA modifications. The disruption of RpoS and Fis cellular network influences in turn the cellular FtsZ level in the early exponential phase. Finally, the reduced FtsZ concentration leads to elongated, filamentous E. coli cells, which are unable to divide.
Mountain ranges can fundamentally influence the physical and and chemical processes that shape Earths’ surface. With elevations of up to several kilometers they create climatic enclaves by interacting with atmospheric circulation and hydrologic systems, thus leading to a specific distribution of flora and fauna. As a result, the interiors of many Cenozoic mountain ranges are characterized by an arid climate, internally drained and sediment-filled basins, as well as unique ecosystems that are isolated from the adjacent humid, low-elevation regions along their flanks and forelands. These high-altitude interiors of orogens are often characterized by low relief and coalesced sedimentary basins, commonly referred to as plateaus, tectono-geomorphic entities that result from the complex interactions between mantle-driven geological and tectonic conditions and superposed atmospheric and hydrological processes. The efficiency of these processes and the fate of orogenic plateaus is therefore closely tied to the balance of constructive and destructive processes – tectonic uplift and erosion, respectively. In numerous geological studies it has been shown that mountain ranges are delicate systems that can be obliterated by an imbalance of these underlying forces. As such, Cenozoic mountain ranges might not persist on long geological timescales and will be destroyed by erosion or tectonic collapse. Advancing headward erosion of river systems that drain the flanks of the orogen may ultimately sever the internal drainage conditions and the maintenance of storage of sediments within the plateau, leading to destruction of plateau morphology and connectivity with the foreland. Orogenic collapse may be associated with the changeover from a compressional stress field with regional shortening and topographic growth, to a tensional stress field with regional extensional deformation and ensuing incision of the plateau. While the latter case is well-expressed by active extensional faults in the interior parts of the Tibetan Plateau and the Himalaya, for example, the former has been attributed to have breached the internally drained areas of the high-elevation sectors of the Iranian Plateau.
In the case of the Andes of South America and their internally drained Altiplano-Puna Plateau, signs of both processes have been previously described. However, in the orogenic collapse scenario the nature of the extensional structures had been primarily investigated in the northern and southern terminations of the plateau; in some cases, the extensional faults were even regarded to be inactive. After a shallow earthquake in 2020 within the Eastern Cordillera of Argentina that was associated with extensional deformation, the state of active deformation and the character of the stress field in the central parts of the plateau received renewed interest to explain a series of extensional structures in the northernmost sectors of the plateau in north-western Argentina. This study addresses (1) the issue of tectonic orogenic collapse of the Andes and the destruction of plateau morphology by studying the fill and erosion history of the central eastern Andean Plateau using sedimentological and geochronological data and (2) the kinematics, timing and magnitude of extensional structures that form well-expressed fault scarps in sediments of the regional San Juan del Oro surface, which is an integral part of the Andean Plateau and adjacent morphotectonic provinces to the east.
Importantly, sediment properties and depositional ages document that the San Juan del Oro Surface was not part of the internally-drained Andean Plateau, but rather associated with a foreland-directed drainage system, which was modified by the Andean orogeny and that became successively incorporated into the orogen by the eastward-migration of the Andean deformation front during late Miocene – Pliocene time. Structural and geomorphic observations within the plateau indicate that extensional processes must have been repeatedly active between the late Miocene and Holocene supporting the notion of plateau-wide extensional processes, potentially associated with Mw ~ 7 earthquakes. The close relationship between extensional joints and fault orientations underscores that 3 was oriented horizontally in NW-SE direction and 1 was vertical. This unambiguously documents that the observed deformation is related to gravitational forces that drive the orogenic collapse of the plateau. Applied geochronological analyses suggest that normal faulting in the northern Puna was active at about 3 Ma, based on paired cosmogenic nuclide dating of sediment fill units. Possibly due to regional normal faulting the drainage system within the plateau was modified, promoting fluvial incision.
Advancements in computer vision techniques driven by machine learning have facilitated robust and efficient estimation of attributes such as depth, optical flow, albedo, and shading. To encapsulate all such underlying properties associated with images and videos, we evolve the concept of intrinsic images towards intrinsic attributes. Further, rapid hardware growth in the form of high-quality smartphone cameras, readily available depth sensors, mobile GPUs, or dedicated neural processing units have made image and video processing pervasive. In this thesis, we explore the synergies between the above two advancements and propose novel image and video processing techniques and systems based on them. To begin with, we investigate intrinsic image decomposition approaches and analyze how they can be implemented on mobile devices. We propose an approach that considers not only diffuse reflection but also specular reflection; it allows us to decompose an image into specularity, albedo, and shading on a resource constrained system (e.g., smartphones or tablets) using the depth data provided by the built-in depth sensors. In addition, we explore how on-device depth data can further be used to add an immersive dimension to 2D photos, e.g., showcasing parallax effects via 3D photography. In this regard, we develop a novel system for interactive 3D photo generation and stylization on mobile devices. Further, we investigate how adaptive manipulation of baseline-albedo (i.e., chromaticity) can be used for efficient visual enhancement under low-lighting conditions. The proposed technique allows for interactive editing of enhancement settings while achieving improved quality and performance. We analyze the inherent optical flow and temporal noise as intrinsic properties of a video. We further propose two new techniques for applying the above intrinsic attributes for the purpose of consistent video filtering. To this end, we investigate how to remove temporal inconsistencies perceived as flickering artifacts. One of the techniques does not require costly optical flow estimation, while both provide interactive consistency control. Using intrinsic attributes for image and video processing enables new solutions for mobile devices – a pervasive visual computing device – and will facilitate novel applications for Augmented Reality (AR), 3D photography, and video stylization. The proposed low-light enhancement techniques can also improve the accuracy of high-level computer vision tasks (e.g., face detection) under low-light conditions. Finally, our approach for consistent video filtering can extend a wide range of image-based processing for videos.
Lanthanide based ceria nanomaterials are important practical materials due to their redox properties that are useful in technology and life sciences. This PhD thesis examined various properties and potential for catalytic and bio-applications of Ln3+-doped ceria nanomaterials. Ce1-xGdxO2-y: Eu3+, gadolinium doped ceria (GDC) (0 ≤ x ≤ 0.4) nanoparticles were synthesized by flame spray pyrolysis (FSP) and studied, followed by 15 % CexZr1-xO2-y: Eu3+|YSZ (0 ≤ x ≤ 1) nanocomposites. Furthermore, Ce1-xYb xO2-y (0.004 ≤ x ≤ 0.22) nanoparticles were synthesized by thermal decomposition and characterized. Finally, CeO2-y: Eu3+ nanoparticles were synthesized by a microemulsion method, biofunctionalized and characterized. The studies undertaken presents a novel approach to structurally elucidate ceria-based nanomaterials by way of Eu3+ and Yb3+ spectroscopy and processing the spectroscopic data with the multi-way decomposition method PARAFAC. Data sets of the three variables: excitation wavelength, emission wavelength and time were used to perform the deconvolution of spectra.
GDC nanoparticles from FSP are nano-sized and of roughly cubic shape and crystal structure (Fm3̅m). Raman data revealed four vibrational modes exhibited by Gd3+ containing samples whereas CeO2-y: Eu3+ displays only two. The room temperature, time-resolved emission spectra recorded at λexcitation = 464 nm show that Gd3+ doping results in significantly altered emission spectra compared to pure ceria. The PARAFAC analysis for the pure ceria samples reveals two species; a high-symmetry species and a low-symmetry species. The GDC samples yield two low-symmetry spectra in the same experiment. High-resolution emission spectra recorded at 4 K after probing the 5D0-7F0 transition revealed additional variation in the low symmetry Eu3+ sites in pure ceria and GDC. The data of the Gd3+-containing samples indicates that the average charge density around the Eu3+ ions in the lattice is inversely related to Gd3+ and oxygen vacancy concentration.
The particle crystallites of the 773 K and 1273 K annealed Yb3+ -ceria nanostructure materials are nano-sized and have a cubic fluorite structure with four Raman vibrational modes. Elemental maps clearly show that cluster formation occurs for 773 K annealed with high Yb3+ ion concentration from 15 mol % in the ceria lattice. These clusters are destroyed with annealing to 1273 K. The emission spectra observed from room temperature and 4 K measurements for the Ce1-xYb xO2-y samples have a manifold that corresponds to the 2F5/2-2F7/2 transition of Yb3+ ions. Some small shifts are observed in the Stark splitting pattern and are induced by the variations of the crystal field influenced by where the Yb3+ ions are located in the crystal lattices in the samples. Upon mixing ceria with high Yb3+ concentrations, the 2F5/2-2F7/2 transition is also observed in the Stark splitting pattern, but the spectra consist of two broad high background dominated peaks. Annealing the nanomaterials at 1273 K for 2 h changes the spectral signature as new peaks emerge. The deconvolution yielded luminescence decay kinetics as well as the accompanying luminescence spectra of three species for each of the low Yb3+ doped ceria samples annealed at 773 K and one species for the 1273 K annealed samples. However, the ceria samples with high Yb3+ concentration annealed at the two temperatures yielded one species with lower decay times as compared to the Yb3+ doped ceria samples after PARAFAC analysis.
Through the calcination of the nanocomposites at two high temperatures, the evolution of the emission patterns from specific Eu3+ lattice sites to indicate structural changes for the nanocomposites was followed. The spectroscopy results effectively complemented the data obtained from the conventional techniques. Annealing the samples at 773 K, resulted in amorphous, unordered domains whereas the TLS of the 1273 K nanocomposites reveal two distinct sites, with most red shifted Eu3+ species coming from pure Eu3+ doped ZrO2 on the YSZ support.
Finally, for Eu3+ doped ceria, successful transfer from hydrophobic to water phase and subsequent biocompatibility was achieved using ssDNA. PARAFAC analysis for the Eu3+ in nanoparticles dispersed in toluene and water revealed one Eu3+ species, with slightly differing surface properties for the nanoparticles as far as the luminescence kinetics and solvent environments were concerned. Several functionalized nanoparticles conjugated onto origami triangles after hybridization were visualized by atomic force microscopy (AFM). Putting all into consideration, Eu3+ and Yb3+ spectroscopy was used to monitor the structural changes and determining the feasibility of the nanoparticle transfer into water. PARAFAC proves to be a powerful tool to analyze lanthanide spectra in crystalline solid materials and in solutions, which are characterized by numerous Stark transitions and where measurements usually yield a superposition of different emission contributions to any given spectrum.
Earthquake modeling is the key to a profound understanding of a rupture. Its kinematics or dynamics are derived from advanced rupture models that allow, for example, to reconstruct the direction and velocity of the rupture front or the evolving slip distribution behind the rupture front. Such models are often parameterized by a lattice of interacting sub-faults with many degrees of freedom, where, for example, the time history of the slip and rake on each sub-fault are inverted. To avoid overfitting or other numerical instabilities during a finite-fault estimation, most models are stabilized by geometric rather than physical constraints such as smoothing.
As a basis for the inversion approach of this study, we build on a new pseudo-dynamic rupture model (PDR) with only a few free parameters and a simple geometry as a physics-based solution of an earthquake rupture. The PDR derives the instantaneous slip from a given stress drop on the fault plane, with boundary conditions on the developing crack surface guaranteed at all times via a boundary element approach. As a side product, the source time function on each point on the rupture plane is not constraint and develops by itself without additional parametrization. The code was made publicly available as part of the Pyrocko and Grond Python packages. The approach was compared with conventional modeling for different earthquakes. For example, for the Mw 7.1 2016 Kumamoto, Japan, earthquake, the effects of geometric changes in the rupture surface on the slip and slip rate distributions could be reproduced by simply projecting stress vectors. For the Mw 7.5 2018 Palu, Indonesia, strike-slip earthquake, we also modelled rupture propagation using the 2D Eikonal equation and assuming a linear relationship between rupture and shear wave velocity. This allowed us to give a deeper and faster propagating rupture front and the resulting upward refraction as a new possible explanation for the apparent supershear observed at the Earth's surface.
The thesis investigates three aspects of earthquake inversion using PDR: (1) to test whether implementing a simplified rupture model with few parameters into a probabilistic Bayesian scheme without constraining geometric parameters is feasible, and whether this leads to fast and robust results that can be used for subsequent fast information systems (e.g., ground motion predictions). (2) To investigate whether combining broadband and strong-motion seismic records together with near-field ground deformation data improves the reliability of estimated rupture models in a Bayesian inversion. (3) To investigate whether a complex rupture can be represented by the inversion of multiple PDR sources and for what type of earthquakes this is recommended.
I developed the PDR inversion approach and applied the joint data inversions to two seismic sequences in different tectonic settings. Using multiple frequency bands and a multiple source inversion approach, I captured the multi-modal behaviour of the Mw 8.2 2021 South Sandwich subduction earthquake with a large, curved and slow rupturing shallow earthquake bounded by two faster and deeper smaller events. I could cross-validate the results with other methods, i.e., P-wave energy back-projection, a clustering analysis of aftershocks and a simple tsunami forward model.
The joint analysis of ground deformation and seismic data within a multiple source inversion also shed light on an earthquake triplet, which occurred in July 2022 in SE Iran. From the inversion and aftershock relocalization, I found indications for a vertical separation between the shallower mainshocks within the sedimentary cover and deeper aftershocks at the sediment-basement interface. The vertical offset could be caused by the ductile response of the evident salt layer to stress perturbations from the mainshocks.
The applications highlight the versatility of the simple PDR in probabilistic seismic source inversion capturing features of rather different, complex earthquakes. Limitations, as the evident focus on the major slip patches of the rupture are discussed as well as differences to other finite fault modeling methods.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
Conservation of the jaguar relies on holistic and transdisciplinary conservation strategies that integratively safeguard essential, connected habitats, sustain viable populations and their genetic exchange, and foster peaceful human-jaguar coexistence. These strategies define four research priorities to advance jaguar conservation throughout the species’ range. In this thesis I provide several relevant ecological and sociological insights into these research priorities, each addressed in a separate chapter. I focus on the effects of anthropogenic landscapes on jaguar habitat use and population gene flow, spatial patterns of jaguar habitat suitability and functional population connectivity, and on innovative governance approaches which can work synergistically to help achieve human-wildlife conviviality. Furthermore, I translate these insights into recommendations for conservation practice by providing tools and suggestions that conservation managers and stakeholders can use to implement local actions but also make broad scale conservation decisions in Central America. In Chapter 2, I model regional habitat use of jaguars, producing spatially-explicit maps for management of key areas of habitat suitability. Using an occupancy model of 13-year-camera-trap occurrence data, I show that human influence has the strongest impact on jaguar habitat use, and that Jaguar Conservation Units are the most important reservoirs of high quality habitat in this region. I build upon these results by zooming in to an area of high habitat suitability loss in Chapter 3, northern Central America. Here I study the drivers of jaguar gene flow and I produce spatially-explicit maps for management of key areas of functional population connectivity in this region. I use microsatellite data and pseudo-optimized multiscale, multivariate resistance surfaces of gene flow to show that jaguar gene flow is influenced by environmental, and even more strongly, by human influence variables; and that the areas of lowest gene flow resistance largely coincide with the location of the Jaguar Conservation Units. Given that human activities significantly impact jaguar habitat use and gene flow, securing viable jaguar populations in anthropogenic landscapes also requires fostering peaceful human-wildlife coexistence. This is a complex challenge that cannot be met without transdisciplinary academic research and cross-sectoral, collaborative governance structures that effectively respond to the multiple challenges of such coexistence. With this in mind, I focus in Chapter 4 on carnivore conservation initiatives that apply transformative governance approaches to enact transformative change towards human-carnivore coexistence. Using the frameworks of transformative biodiversity governance and convivial conservation, I highlight in this chapter concrete pathways, supported by more inclusive, democratic forms of conservation decision-making and participation that promote truly transformative changes towards human-jaguar conviviality.
Strings of words can correspond to more than one interpretation or underlying structure, which makes them ambiguous. Prosody can be used to resolve this structural ambiguity. This dissertation investigates the use of prosodic cues in the domains of fundamental frequency (f0) and duration to disambiguate between two interpretations of ambiguous structures when speakers addressed different interlocutors. The dissertation comprises of three production studies and one comprehension study.
Prosodic disambiguation was studied with a focus on German name sequences of three names (coordinates) in two conditions: without (Name1 and Name2 and Name3) and with internal grouping of the first two names ([Name1 and Name2] and Name3). The study of coordinates was complemented with production data of locally ambiguous sentences with a case-ambiguous first noun phrase.
Variability was studied in a controlled setting: Productions were elicited with a within-subject manipulation of context in a referential communication task in order to evoke prosodic adaptations to different conversational contexts. Context had five levels and involved interlocutors in three age groups (child, young adult, elderly adult) with German as L1 in the absence of background white noise, the young adult with background white noise, and a young adult without German as L1. Variability was explored at different levels: within a group of young individuals (intra-group level), within and between young individuals (intra-individual level and inter-individual level, respectively), and comparing between the group of young and a group of older speakers (inter-group level).
Our data replicate the use of the three prosodic cues (f0-movement, final lengthening, and pause) in productions of young adult speakers and extend their use to productions of older adult speakers. Both age groups distinguished consistently between the two coordinate conditions. Prosodic grouping in production was evident not only on the group-final Name2 but also at earlier stages in the utterance, on the group-internal Name1 (early cues). For some speakers, some listeners were able to decode these early cues effectively as they were able to reliably predict the upcoming structure after listening to Name1 only. Thus, prosodic grouping appears as a globally marked phenomenon building up along the utterance. The internal structure of coordinates was disambiguated irrespective of the conversational context. In our data, speakers only slightly modified the prosodic cues marking the disambiguation in the different contexts. Listeners were unable to identify to which interlocutor the sequence had been produced. We interpret this intra-individual consistency in the production of disambiguating prosodic cues as support for a strong link between prosody and syntax. The findings support models in favour of situational independence of disambiguating prosody. All speakers reliably marked the distinction between the grouping conditions with at least one of the three prosodic cues investigated and most of the speakers used at least two of these cues. Further, individual differences in prosodic grouping did not lead to difficulties in recovering the grouping in comprehension. Taken together, these findings support the existence of a phonological category of prosodic grouping.
Starch is a biopolymer for which, despite its simple composition, understanding the precise mechanism behind its formation and regulation has been challenging. Several approaches and bioanalytical tools can be used to expand the knowledge on the different parts involved in the starch metabolism. In this sense, a comprehensive analysis targeting two of the main groups of molecules involved in this process: proteins, as effectors/regulators of the starch metabolism, and maltodextrins as starch components and degradation products, was conducted in this research work using potato plants (Solanum tuberosum L. cv. Desiree) as model of study. On one side, proteins physically interacting to potato starch were isolated and analyzed through mass spectrometry and western blot for their identification. Alternatively, starch interacting proteins were explored in potato tubers from transgenic plants having antisense inhibition of starch-related enzymes and on tubers stored under variable environmental conditions. Most of the proteins recovered from the starch granules corresponded to previously described proteins having a specific role in the starch metabolic pathway. Another set of proteins could be grouped as protease inhibitors, which were found weakly interacting to starch. Variations in the protein profile obtained after electrophoresis separation became clear when tubers were stored under different temperatures, indicating a differential expression of proteins in response to changing environmental conditions.
On the other side, since maltodextrin metabolism is thought to be involved in both starch initiation and degradation, soluble maltooligosaccharide content in potato tubers was analyzed in this work under diverse experimental variables. For this, tuber disc samples from wild type and transgenic lines strongly repressing either the plastidial or cytosolic form of the -glucan phosphorylase and phosphoglucomutase were incubated with glucose, glucose-6-phosphate, and glucose-1-phosphate solutions to evaluate the influence of such enzymes on the conversion of the carbon sources into soluble maltodextrins, in comparison to wild-type samples. Relative maltodextrin amounts analyzed through capillary electrophoresis equipped with laser-induced fluorescence (CE-LIF) revealed that tuber discs could immediately uptake glucose-1-phosphate and use it to produce maltooligosaccharides with a degree of polymerization of up to 30 (DP30), in contrast to transgenic tubers with strong repression of the plastidial glucan phosphorylase. The results obtained from the maltodextrin analysis support previous indications that a specific transporter for glucose-1-phosphate may exist in both the plant cells and the plastidial membranes, thereby allowing a glucose-6-phosphate independent transport. Furthermore, it confirms that the plastidial glucan phosphorylase is responsible for producing longer maltooligosaccharides in the plastids by catalyzing a glucan polymerization reaction when glucose-1-phosphate is available. All these findings contribute to a better understanding of the role of the plastidial glucan phosphorylase as a key enzyme directly involved in the synthesis and degradation of glucans and their implication on starch metabolism.
The deformation style of mountain belts is greatly influenced by the upper plate architecture created during preceding deformation phases. The Mesozoic Salta Rift extensional phase has created a dominant structural and lithological framework that controls Cenozoic deformation and exhumation patterns in the Central Andes. Studying the nature of these pre-existing anisotropies is a key to understanding the spatiotemporal distribution of exhumation and its controlling factors. The Eastern Cordillera in particular, has a structural grain that is in part controlled by Salta Rift structures and their orientation relative to Andean shortening. As a result, there are areas in which Andean deformation prevails and areas where the influence of the Salta Rift is the main control on deformation patterns.
Between 23 and 24°S, lithological and structural heterogeneities imposed by the Lomas de Olmedo sub-basin (Salta Rift basin) affect the development of the Eastern Cordillera fold-and-thrust belt. The inverted northern margin of the sub-basin now forms the southern boundary of the intermontane Cianzo basin. The former western margin of the sub-basin is located at the confluence of the Subandean Zone, the Santa Barbara System and the Eastern Cordillera. Here, the Salta Rift basin architecture is responsible for the distribution of these morphotectonic provinces. In this study we use a multi-method approach consisting of low-temperature (U-Th-Sm)/He and apatite fission track thermochronology, detrital geochronology, structural and sedimentological analyses to investigate the Mesozoic structural inheritance of the Lomas de Olmedo sub-basin and Cenozoic exhumation patterns.
Characterization of the extension-related Tacurú Group as an intermediate succession between Paleozoic basement and the syn-rift infill of the Lomas de Olmedo sub-basin reveals a Jurassic maximum depositional age. Zircon (U-Th-Sm)/He cooling ages record a pre-Cretaceous onset of exhumation for the rift shoulders in the northern part of the sub-basin, whereas the western shoulder shows a more recent onset (140–115 Ma). Variations in the sedimentary thickness of syn- and post-rift strata document the evolution of accommodation space in the sub-basin. While the thickness of syn-rift strata increases rapidly toward the northern basin margin, the post-rift strata thickness decreases toward the margin and forms a condensed section on the rift shoulder.
Inversion of Salta Rift structures commenced between the late Oligocene and Miocene (24–15 Ma) in the ranges surrounding the Cianzo basin. The eastern and western limbs of the Cianzo syncline, located in the hanging wall of the basin-bounding Hornocal fault, show diachronous exhumation. At the same time, western fault blocks of Tilcara Range, south of the Cianzo basin, began exhuming in the late Oligocene to early Miocene (26–16 Ma). Eastward propagation to the frontal thrust and to the Paleozoic strata east of the Tilcara Range occurred in the middle Miocene (22–10 Ma) and the late Miocene–early Pliocene (10–4 Ma), respectively.
Background and aims:
To succeed in competition, elite team and individual athletes often seek the development of both, high levels of muscle strength and power as well as cardiorespiratory endurance. In this context, concurrent training (CT) is a commonly applied and effective training approach. While being exposed to high training loads, youth athletes (≤ 18 years) are yet underrepresented in the scientific literature. Besides, immunological responses to CT have received little attention. Therefore, the aims of this work were to examine the acute (< 15min) and delayed (≥ 6 hours) effects of dif-ferent exercise order in CT on immunological stress responses, muscular fitness, metabolic response, and rating of perceived exertion (RPE) in highly trained youth male and female judo athletes.
Methods:
A total of twenty male and thirteen female participants, with an average age of 16 ± 1.8 years and 14.4 ± 2.1 years, respectively, were included in the study. They were randomly assigned to two CT sessions; power-endurance versus endurance-power (i.e., study 1), or strength-endurance versus endurance-strength (i.e., study 2). Markers of immune response (i.e., white-blood-cells, granulocytes, lymphocytes, mon-ocytes, and lymphocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index), muscular fitness (i.e., counter-movement jump [CMJ]), metabolic responses (i.e., blood lactate, glucose), and RPE were collected at different time points (i.e., PRE12H, PRE, MID, POST, POST6H, POST22H).
Results (study 1):
There were significant time*order interactions for white-blood-cells, lymphocytes, granulocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The power-endurance order resulted in significantly larger PRE-to-POST increases in white-blood-cells, monocytes, and lymphocytes while the endur-ance-power order resulted in significantly larger PRE-to-POST increases in the granu-locyte-lymphocyte-ratio and systemic-inflammation-index. Likewise, significantly larger increases from PRE-to-POST6H in white-blood-cells and granulocytes were observed following the power-endurance order compared to endurance-power. All markers of immune response returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. Following the endur-ance-power order, blood lactate and glucose increased from PRE-to-MID but not from PRE-to-POST. Meanwhile, in the power-endurance order blood lactate and glucose increased from PRE-to-POST but not from PRE-to-MID. A significant time*order inter-action was observed for CMJ-force with larger PRE-to-POST decreases in the endur-ance-power order compared to power-endurance order. Further, CMJ-power showed larger PRE-to-MID performance decreases following the power-endurance order, com-pared to the endurance-power order. Regarding RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endurance-power order and larger PRE-to-POST values following the power-endurance order.
Results (study 2):
There were significant time*order interactions for lymphocytes, monocytes, granulocyte-lymphocyte-ratio, and systemic-inflammation-index. The strength-endurance order resulted in significantly larger PRE-to-POST increases in lymphocytes while the endurance-strength order resulted in significantly larger PRE-to-POST increases in the granulocyte-lymphocyte-ratio and systemic-inflammation-index. All markers of the immune system returned toward baseline values at POST22H. Moreover, there was a significant time*order interaction for blood glucose and lactate. From PRE-to-MID, there was a significantly greater increase in blood lactate and glu-cose following the endurance-strength order compared to strength-endurance order. Meanwhile, from PRE-to-POST there was a significantly higher increase in blood glu-cose following the strength-endurance order compared to endurance-strength order. Regarding physical fitness, a significant time*order interaction was observed for CMJ-force and CMJ-power with larger PRE-to-MID increases following the endurance-strength order compared to the strength-endurance order. For RPE, significant time*order interactions were noted with larger PRE-to-MID values following the endur-ance-power order and larger PRE-to-POST values following the power-endurance or-der.
Conclusions:
The primary findings from both studies revealed order-dependent effects on immune responses. In male youth judo athletes, the results demonstrated greater immunological stress responses, both immediately (≤ 15 min) and delayed (≥ 6 hours), following the power-endurance order compared to the endurance-power order. For female youth judo athletes, the results indicated higher acute, but not delayed, order-dependent changes in immune responses following the strength-endurance order compared to the endurance-strength order. It is worth noting that in both studies, all markers of immune system response returned to baseline levels within 22 hours. This suggests that successful recovery from the exercise-induced immune stress response was achieved within 22 hours. Regarding metabolic responses, physical fitness, and perceived exertion, the findings from both studies indicated acute (≤ 15 minutes) alterations that were dependent on the exercise order. These alterations were primarily influ-enced by the endurance exercise component. Moreover, study 1 provided substantial evidence suggesting that internal load measures, such as immune markers, may differ from external load measures. This indicates a disparity between immunological, perceived, and physical responses following both concurrent training orders. Therefore, it is crucial for practitioners to acknowledge these differences and take them into consideration when designing training programs.
The present work focuses on the preparation and characterisation of various nanoplastic reference material candidates. Nanoplastics are plastic particles in a size range of 1 − 1000 nm. The term has emerged in recent years as a distinction from the larger microplastic (1 − 1000 μm). Since the properties of the two plastic particles differ significantly due to their size, it is important to have nanoplastic reference material. This was produced for the polymer types polypropylene (PP) and polyethylene (PE) as well as poly(lactic acid) (PLA).
A top-down method was used to produce the nanoplastic for the polyolefins PP and PE (Section 3.1). The material was crushed in acetone using an Ultra-Turrax disperser and then transferred to water. This process produces reproducible results when repeated, making it suitable for the production of a reference material candidate. The resulting dispersions were investigated using dynamic and electrophoretic light scattering. The dispersion of PP particles gave a mean hydrodynamic diameter Dh = 180.5±5.8 nm with a PDI = 0.08±0.02 and a zeta potential ζ = −43.0 ± 2.0 mV. For the PE particles, a diameter Dh = 344.5 ± 34.6 nm, with a PDI = 0.39 ± 0.04 and a zeta potential of ζ = −40.0 ± 4.2 mV was measured. This means that both dispersions are nanoplastics, as the particles are < 1000 nm. Furthermore, the starting material of these polyolefin particles was mixed with a gold salt and thereby the nanoplastic production was repeated in order to obtain nanoplastic particles doped with gold, which should simplify the detection of the particles.
In addition to the top-down approach, a bottom-up method was chosen for the PLA (Section 3.2). Here, the polymer was first dissolved in THF and stabilised with a surfactant. Then water was added and THF evaporated, leaving an aqueous PLA dispersion. This experiment was also investigated using dynamic light scattering and, when repeated, yielded reproducible results, i. e. an average hydrodynamic diameter of Dh = 89.2 ± 3.0 nm. Since the mass concentration of PLA in the dispersion is known due to the production method, a Python notebook was tested for these samples to calculate the number and mass concentration of nano(plastic) particles using the MALS results. Similar to the plastic produced in Section 3.1, gold was also incorporated into the particle, which was achieved by adding a dispersion of gold clusters with a diameter of D = 1.15 nm in an ionic liquid (IL) in the production process. Here, the preparation of the gold clusters in the ionic liquid 1-ethyl-3-methylimidazolium dicyanamide ([Emim][DCA]) represented the first use of an IL both as a reducing agent for gold and as a solvent for the gold clusters. Two volumes of gold cluster dispersion were added during the PLA particle synthesis. The addition of the gold clusters leads to much larger particles. The nanoPLA with 0.8% Au has a diameter of Dh = 198.0 ± 10.8 nm and the nanoPLA with 4.9% Au has a diameter of Dh = 259.1 ± 23.7 nm. First investigations by TEM imaging show that the nanoPLA particles form hollow spheres when gold clusters are added. However, the mechanism leading to these structures remains unclear.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
Stars under influence: evidence of tidal interactions between stars and substellar companions
(2023)
Tidal interactions occur between gravitationally bound astrophysical bodies. If their spatial separation is sufficiently small, the bodies can induce tides on each other, leading to angular momentum transfer and altering of evolutionary path the bodies would have followed if they were single objects. The tidal processes are well established in the Solar planet-moon systems and close stellar binary systems. However, how do stars behave if they are orbited by a substellar companion (e.g. a planet or a brown dwarf) on a tight orbit?
Typically, a substellar companion inside the corotation radius of a star will migrate toward the star as it loses orbital angular momentum. On the other hand, the star will gain angular momentum which has the potential to increase its rotation rate. The effect should be more pronounced if the substellar companion is more massive. As the stellar rotation rate and the magnetic activity level are coupled, the star should appear more magnetically active under the tidal influence of the orbiting substellar companion. However, the difficulty in proving that a star has a higher magnetic activity level due to tidal interactions lies in the fact that (I) substellar companions around active stars are easier to detect if they are more massive, leading to a bias toward massive companions around active stars and mimicking the tidal interaction effect, and that (II) the age of a main-sequence star cannot be easily determined, leaving the possibility that a star is more active due to its young age.
In our work, we overcome these issues by employing wide stellar binary systems where one star hosts a substellar companion, and where the other star provides the magnetic activity baseline for the host star, assuming they have coevolved, and thereby provides the host's activity level if tidal interactions have no effect on it. Firstly, we find that extrasolar planets can noticeably increase the host star's X-ray luminosity and that the effect is more pronounced if the exoplanet is at least Jupiter-like in mass and close to the star. Further, we find that a brown dwarf will have an even stronger effect, as expected, and that the X-ray surface flux difference between the host star and the wide stellar companion is a significant outlier when compared to a large sample of similar wide binary systems without any known substellar companions. This result proves that substellar hosting wide binary systems can be good tools to reveal the tidal effect on host stars, and also show that the typical stellar age indicators as activity or rotation cannot be used for these stars. Finally, knowing that the activity difference is a good tracer of the substellar companion's tidal impact, we develop an analytical method to calculate the modified tidal quality factor Q' of individual host stars, which defines the tidal dissipation efficiency in the convective envelope of a given main-sequence star.
Point processes are a common methodology to model sets of events. From earthquakes to social media posts, from the arrival times of neuronal spikes to the timing of crimes, from stock prices to disease spreading -- these phenomena can be reduced to the occurrences of events concentrated in points. Often, these events happen one after the other defining a time--series.
Models of point processes can be used to deepen our understanding of such events and for classification and prediction. Such models include an underlying random process that generates the events. This work uses Bayesian methodology to infer the underlying generative process from observed data. Our contribution is twofold -- we develop new models and new inference methods for these processes.
We propose a model that extends the family of point processes where the occurrence of an event depends on the previous events. This family is known as Hawkes processes. Whereas in most existing models of such processes, past events are assumed to have only an excitatory effect on future events, we focus on the newly developed nonlinear Hawkes process, where past events could have excitatory and inhibitory effects. After defining the model, we present its inference method and apply it to data from different fields, among others, to neuronal activity.
The second model described in the thesis concerns a specific instance of point processes --- the decision process underlying human gaze control. This process results in a series of fixated locations in an image. We developed a new model to describe this process, motivated by the known Exploration--Exploitation dilemma. Alongside the model, we present a Bayesian inference algorithm to infer the model parameters.
Remaining in the realm of human scene viewing, we identify the lack of best practices for Bayesian inference in this field. We survey four popular algorithms and compare their performances for parameter inference in two scan path models.
The novel models and inference algorithms presented in this dissertation enrich the understanding of point process data and allow us to uncover meaningful insights.
Traditionally, mental disorders have been identified based on specific symptoms and standardized diagnostic systems such as the DSM-5 and ICD-10. However, these symptom-based definitions may only partially represent neurobiological and behavioral research findings, which could impede the development of targeted treatments. A transdiagnostic approach to mental health research, such as the Research Domain Criteria (RDoC) approach, maps resilience and broader aspects of mental health to associated components. By investigating mental disorders in a transnosological way, we can better understand disease patterns and their distinguishing and common factors, leading to more precise prevention and treatment options.
Therefore, this dissertation focuses on (1) the latent domain structure of the RDoC approach in a transnosological sample including healthy controls, (2) its domain associations to disease severity in patients with anxiety and depressive disorders, and (3) an overview of the scientific results found regarding Positive (PVS) and Negative Valence Systems (NVS) associated with mood and anxiety disorders.
The following main results were found: First, the latent RDoC domain structure for PVS and NVS, Cognitive Systems (CS), and Social Processes (SP) could be validated using self-report and behavioral measures in a transnosological sample. Second, we found transdiagnostic and disease-specific associations between those four domains and disease severity in patients with depressive and anxiety disorders. Third, the scoping review showed a sizable amount of RDoC research conducted on PVS and NVS in mood and anxiety disorders, with research gaps for both domains and specific conditions.
In conclusion, the research presented in this dissertation highlights the potential of the transnosological RDoC framework approach in improving our understanding of mental disorders. By exploring the latent RDoC structure and associations with disease severity and disease-specific and transnosological associations for anxiety and depressive disorders, this research provides valuable insights into the full spectrum of psychological functioning. Additionally, this dissertation highlights the need for further research in this area, identifying both RDoC indicators and research gaps. Overall, this dissertation represents an important contribution to the ongoing efforts to improve our understanding and the treatment of mental disorders, particularly within the commonly comorbid disease spectrum of mood and anxiety disorders.
Digitalisation in industry – also called “Industry 4.0” – is seen by numerous actors as an opportunity to reduce the environmental impact of the industrial sector. The scientific assessments of the effects of digitalisation in industry on environmental sustainability, however, are ambivalent. This cumulative dissertation uses three empirical studies to examine the expected and observed effects of digitalisation in industry on environmental sustainability. The aim of this dissertation is to identify opportunities and risks of digitalisation at different system levels and to derive options for action in politics and industry for a more sustainable design of digitalisation in industry. I use an interdisciplinary, socio-technical approach and look at selected countries of the Global South (Study 1) and the example of China (all studies). In the first study (section 2, joint work with Marcel Matthess), I use qualitative content analysis to examine digital and industrial policies from seven different countries in Africa and Asia for expectations regarding the impact of digitalisation on sustainability and compare these with the potentials of digitalisation for sustainability in the respective country contexts. The analysis reveals that the documents express a wide range of vague expectations that relate more to positive indirect impacts of information and communication technology (ICT) use, such as improved energy efficiency and resource management, and less to negative direct impacts of ICT, such as electricity consumption through ICT. In the second study (section 3, joint work with Marcel Matthess, Grischa Beier and Bing Xue), I conduct and analyse interviews with 18 industry representatives of the electronics industry from Europe, Japan and China on digitalisation measures in supply chains using qualitative content analysis. I find that while there are positive expectations regarding the effects of digital technologies on supply chain sustainability, their actual use and observable effects are still limited. Interview partners can only provide few examples from their own companies which show that sustainability goals have already been pursued through digitalisation of the supply chain or where sustainability effects, such as resource savings, have been demonstrably achieved. In the third study (section 4, joint work with Peter Neuhäusler, Melissa Dachrodt and Marcel Matthess), I conduct an econometric panel data analysis. I examine the relationship between the degree of Industry 4.0, energy consumption and energy intensity in ten manufacturing sectors in China between 2006 and 2019. The results suggest that overall, there is no significant relationship between the degree of Industry 4.0 and energy consumption or energy intensity in manufacturing sectors in China. However, differences can be found in subgroups of sectors. I find a negative correlation of Industry 4.0 and energy intensity in highly digitalised sectors, indicating an efficiency-enhancing effect of Industry 4.0 in these sectors. On the other hand, there is a positive correlation of Industry 4.0 and energy consumption for sectors with low energy consumption, which could be explained by the fact that digitalisation, such as the automation of previously mainly labour-intensive sectors, requires energy and also induces growth effects. In the discussion section (section 6) of this dissertation, I use the classification scheme of the three levels macro, meso and micro, as well as of direct and indirect environmental effects to classify the empirical observations into opportunities and risks, for example, with regard to the probability of rebound effects of digitalisation at the three levels. I link the investigated actor perspectives (policy makers, industry representatives), statistical data and additional literature across the system levels and consider political economy aspects to suggest fields of action for more sustainable (digitalised) industries. The dissertation thus makes two overarching contributions to the academic and societal discourse. First, my three empirical studies expand the limited state of research at the interface between digitalisation in industry and sustainability, especially by considering selected countries in the Global South and the example of China. Secondly, exploring the topic through data and methods from different disciplinary contexts and taking a socio-technical point of view, enables an analysis of (path) dependencies, uncertainties, and interactions in the socio-technical system across different system levels, which have often not been sufficiently considered in previous studies. The dissertation thus aims to create a scientifically and practically relevant knowledge basis for a value-guided, sustainability-oriented design of digitalisation in industry.
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.
Aptamers are single-stranded DNA (ssDNA) or RNA molecules that can bind specifically and with high affinity to target molecules due to their unique three-dimensional structure. For this reason, they are often compared to antibodies and sometimes even referred to as “chemical antibodies”. They are simple and inexpensive to synthesize, easy to modify, and smaller than conventional antibodies. Enzymes, especially hydrolases, are interesting targets in this context. This class of enzymes is capable of hydrolytically cleaving various macromolecules such as proteins, as well as smaller molecules such as antibiotics. Hence, they play an important role in many biological processes including diseases and their treatment. Hydrolase detection as well as the understanding of their function is therefore of great importance for diagnostics and therapy. Due to their various desirable features compared to antibodies, aptamers are being discussed as alternative agents for analytical and diagnostic use in various applications. The use of aptamers in therapy is also frequently investigated, as the binding of aptamers can have effects on the catalytic activity, protein-protein interactions, or proteolytic cascades. Aptamers are generated by an in vitro selection process. Potential aptamer candidates are selected from a pool of enriched nucleic acid sequences with affinity to the target, and their binding affinity and specificity is investigated. This is one of the most important steps in aptamer generation to obtain specific aptamers with high affinity for use in analytical and diagnostic applications. The binding properties or binding domains and their effects on enzyme functions form the basis for therapeutic applications.
In this work, the binding properties of DNA aptamers against two different hydrolases were investigated. In view of their potential utility for analytical methods, aptamers against human urokinase (uPA) and New Delhi metallo-β-lactamase-1 (NDM-1) were evaluated for their binding affinity and specificity using different methods. Using the uPA aptamers, a protocol for measuring the binding kinetics of an aptamer-protein-interaction by surface plasmon resonance spectroscopy (SPR) was developed. Based on the increased expression of uPA in different types of cancer, uPA is discussed as a prognostic and diagnostic tumor marker. As uPA aptamers showed different binding sites on the protein, microtiter plate-based aptamer sandwich assay systems for the detection of uPA were developed. Because of the function of urokinase in cancer cell proliferation and metastasis, uPA is also discussed as a therapeutic target. In this regard, the different binding sites of aptamers showed different effects on uPA function. In vitro experiments demonstrated both inhibition of uPA binding to its receptor as well as the inhibition of uPA catalytic activity for different aptamers. Thus, in addition to their specificity and affinity for their targets, the utility of the aptamers for potential diagnostic and therapeutic applications was demonstrated. First, as an alternative inhibitor of human urokinase for therapeutic purposes, and second, as valuable recognition molecules for the detection of urokinase, as a prognostic and diagnostic marker for cancer, and for NDM-1 to detect resistance to carbapenem antibiotics.
Late-type stars are by far the most frequent stars in the universe and of fundamental interest to various fields of astronomy – most notably to Galactic archaeology and exoplanet research. However, such stars barely change during their main sequence lifetime; their temperature, luminosity, or chemical composition evolve only very slowly over the course of billions of years. As such, it is difficult to obtain the age of such a star, especially when it is isolated and no other indications (like cluster association) can be used. Gyrochronology offers a way to overcome this problem.
Stars, just like all other objects in the universe, rotate and the rate at which stars rotate impacts many aspects of their appearance and evolution. Gyrochronology leverages the observed rotation rate of a late-type main sequence star and its systematic evolution to estimate their ages. Unlike the above-mentioned parameters, the rotation rate of a main sequence star changes drastically throughout its main sequence lifetime; stars spin down. The youngest stars rotate every few hours, whereas much older stars rotate only about once a month, or – in the case of some late M-stars – once in a hundred days. Given that this spindown is systematic (with an additional mass dependence), it gave rise to the idea of using the observed rotation rate of a star (and its mass or a suitable proxy thereof) to estimate a star’s age. This has been explored widely in young stellar open clusters but remains essentially unconstrained for stars older than the sun, and K and M stars older than 1 Gyr.
This thesis focuses on the continued exploration of the spindown behavior to assess, whether gyrochronology remains applicable for stars of old ages, whether it is universal for late-type main sequence stars (including field stars), and to provide calibration mileposts for spindown models. To accomplish this, I have analyzed data from Kepler space telescope for the open clusters Ruprecht 147 (2.7 Gyr old) and M 67 (4 Gyr). Time series photometry data (light curves)
were obtained for both clusters during Kepler’s K2 mission. However, due to technical limitations and telescope malfunctions, extracting usable data from the K2 mission to identify (especially long) rotation periods requires extensive data preparation.
For Ruprecht 147, I have compiled a list of about 300 cluster members from the literature and adopted preprocessed light curves from the Kepler archive where available. They have been cleaned of the gravest of data artifacts but still contained systematics. After correcting them for said artifacts, I was able to identify rotation periods in 31 of them.
For M 67 more effort was taken. My work on Ruprecht 147 has shown the limitations imposed by the preselection of Kepler targets. Therefore, I adopted the time series full frame image directly and performed photometry on a much higher spatial resolution to be able to obtain data for as many stars as possible. This also means that I had to deal with the ubiquitous artifacts in Kepler data. For that, I devised a method that correlates the artificial flux variations with the ongoing drift of the telescope pointing in order to remove it. This process was a large success and I was able to create light curves whose quality match and even exceede those that were created by the Kepler mission – all while operating on higher spatial resolution and processing fainter stars. Ultimately, I was able to identify signs of periodic variability in the (created) light curves for 31 and 47 stars in Ruprecht 147 and M 67, respectively. My data connect well to bluer stars of cluster of the same age and extend for the first time to stars redder than early-K and older than 1 Gyr. The cluster data show a clear flattening in the distribution of Ruprecht 147 and even a downturn for M 67, resulting in a somewhat sinusoidal shape. With that, I have shown that the systematic spindown of stars continues at least until 4 Gyr and stars continue to live on a single surface in age-rotation periods-mass space which allows gyrochronology to be used at least up to that age. However, the shape of the spindown – as exemplified by the newly discovered sinusoidal shape of the cluster sequence – deviates strongly from the expectations.
I then compiled an extensive sample of rotation data in open clusters – very much including my own work – and used the resulting cluster skeleton (with each cluster forming a rip in color-rotation period-mass space) to investigate if field stars follow the same spindown as cluster stars. For the field stars, I used wide binaries, which – with their shared origin and coevality – are in a sense the smallest possible open clusters. I devised an empirical method to evaluate the consistency between the rotation rates of the wide binary components and found that the vast majority of them are in fact consistent with what is observed in open clusters. This leads me to conclude that gyrochronology – calibrated on open clusters – can be applied to determine the ages of field stars.
Amoeboid cell motility takes place in a variety of biomedical processes such as cancer metastasis, embryonic morphogenesis, and wound healing. In contrast to other forms of cell motility, it is mainly driven by substantial cell shape changes. Based on the interplay of explorative membrane protrusions at the front and a slower-acting membrane retraction at the rear, the cell moves in a crawling kind of way. Underlying these protrusions and retractions are multiple physiological processes resulting in changes of the cytoskeleton, a meshwork of different multi-functional proteins. The complexity and versatility of amoeboid cell motility raise the need for novel computational models based on a profound theoretical framework to analyze and simulate the dynamics of the cell shape.
The objective of this thesis is the development of (i) a mathematical framework to describe contour dynamics in time and space, (ii) a computational model to infer expansion and retraction characteristics of individual cell tracks and to produce realistic contour dynamics, (iii) and a complementing Open Science approach to make the above methods fully accessible and easy to use.
In this work, we mainly used single-cell recordings of the model organism Dictyostelium discoideum. Based on stacks of segmented microscopy images, we apply a Bayesian approach to obtain smooth representations of the cell membrane, so-called cell contours. We introduce a one-parameter family of regularized contour flows to track reference points on the contour (virtual markers) in time and space. This way, we define a coordinate system to visualize local geometric and dynamic quantities of individual contour dynamics in so-called kymograph plots. In particular, we introduce the local marker dispersion as a measure to identify membrane protrusions and retractions in a fully automated way.
This mathematical framework is the basis of a novel contour dynamics model, which consists of three biophysiologically motivated components: one stochastic term, accounting for membrane protrusions, and two deterministic terms to control the shape and area of the contour, which account for membrane retractions. Our model provides a fully automated approach to infer protrusion and retraction characteristics from experimental cell tracks while being also capable of simulating realistic and qualitatively different contour dynamics. Furthermore, the model is used to classify two different locomotion types: the amoeboid and a so-called fan-shaped type.
With the complementing Open Science approach, we ensure a high standard regarding the usability of our methods and the reproducibility of our research. In this context, we introduce our software publication named AmoePy, an open-source Python package to segment, analyze, and simulate amoeboid cell motility. Furthermore, we describe measures to improve its usability and extensibility, e.g., by detailed run instructions and an automatically generated source code documentation, and to ensure its functionality and stability, e.g., by automatic software tests, data validation, and a hierarchical package structure.
The mathematical approaches of this work provide substantial improvements regarding the modeling and analysis of amoeboid cell motility. We deem the above methods, due to their generalized nature, to be of greater value for other scientific applications, e.g., varying organisms and experimental setups or the transition from unicellular to multicellular movement. Furthermore, we enable other researchers from different fields, i.e., mathematics, biophysics, and medicine, to apply our mathematical methods. By following Open Science standards, this work is of greater value for the cell migration community and a potential role model for other Open Science contributions.
The field of exercise psychology has established robust evidence on the health benefits of physical activity. However, interventions to promote sustained exercise behavior have often proven ineffective. This dissertation addresses challenges in the field, particularly the neglect of situated and affective processes in understanding and changing exercise behavior. Dual process models, considering both rational and affective processes, have gained recognition. The Affective Reflective Theory of Physical Inactivity and Exercise (ART) is a notable model in this context, positing that situated processes in-the-moment of choice influence exercise decisions and subsequent exercise behavior.
The dissertation identifies current challenges within exercise psychology and proposes methodological and theoretical advancements. It emphasizes the importance of momentary affective states and situated processes, offering alternatives to self-reported measures and advocating for a more comprehensive modeling of individual variability. The focus is on the affective processes during exercise, theorized to reappear in momentary decision-making, shaping overall exercise behavior.
The first publication introduces a new method by using automated facial action analysis to measure variable affective responses during exercise. It explores how these behavioral indicators covary with self-reported measures of affective valence and perceived exertion. The second publication delves into situated processes at the moment of choice between exercise and non-exercise options, revealing that intraindividual factors play a crucial role in explaining exercise-related choices. The third publication presents an open-source research tool, the Decisional Preferences in Exercising Test (DPEX), designed to capture repeated situated decisions and predict exercise behavior based on past experiences.
The findings challenge previous assumptions and provide insights into the complex interplay of affective responses, situated processes, and exercise choices. The dissertation underscores the need for individualized interventions that manipulate affective responses during exercise and calls for systematic testing to establish causal links to automatic affective processes and subsequent exercise behavior. This dissertation highlights the necessity for methodological and conceptual refinements in understanding and promoting exercise behavior, ultimately contributing to the broader goal of combating increasing inactivity trends.
This thesis is concerned with the phenomenon of quantifier scope ambiguities. This phenomenon has been researched extensively, both from a theoretical and from an empirical point of view. Nevertheless, there are still a number of under-researched topics in the field of quantifier scope, which will be the main focus of this thesis. I will take a closer look at three languages, English, German, and the Asante Twi dialect of Akan (Kwa, Niger-Kongo). The goal is a better understanding of the phenomenon of quantifier scope both within each language, as well as from a cross-linguistic perspective. First, this thesis will provide a series of experiments that allow a direct cross-linguistic comparison between English and German – two languages about which specific claims have been made in the literature. I will also provide exploratory research in the case of Asante Twi, where so far, no work has been dedicated specifically to the study of quantifier scope. The work on Asante Twi will go beyond quantifier scope and also target the quantifier and determiner system in general. The question is not only if particular scope readings are possible or not, but also which factors contribute to an increase or decrease of scope availability, and if there are factors that block certain scope readings altogether. While some of the results confirm and thereby strengthen previous claims, other results contradict general assumptions in the literature. This is particularly the case for inverse readings in German and inverse readings across clause-boundaries.
Volcanic hazard assessment relies on physics-based models of hazards, such as lava flows and pyroclastic density currents, whose outcomes are very sensitive to the location where future eruptions will occur. On the contrary, forecast of vent opening locations in volcanic areas typically relies on purely data-driven approaches, where the spatial density of past eruptive vents informs the probability maps of future vent opening. Such techniques may be suboptimal in volcanic systems with missing or scarce data, and where the controls on magma pathways may change over time. An alternative approach was recently proposed, relying on a model of stress-driven pathways of magmatic dikes. In that approach, the crustal stress was optimized so that dike trajectories linked consistently the location of the magma chamber to that of past vents. The retrieved information on the stress state was then used to forecast future dike trajectories. The validation of such an approach requires extensive application to nature. Before doing so, however, several important limitations need to be removed, most importantly the two-dimensional (2D) character of the models and theoretical concepts. In this thesis, I develop methods and tools so that a physics-based strategy of stress inversion and eruptive vent forecast in volcanoes can be applied to three dimensional (3D) problems. In the first part, I test the stress inversion and vent forecast strategy on analog models, still within a 2D framework, but improving on the efficiency of the stress optimization. In the second part, I discuss how to correctly account for gravitational loading/unloading due to complex 3D topography with a Boundary-Element numerical model. Then, I develop a new, simplified but fast model of dike pathways in 3D, designed for running large numbers of simulations at minimal computational cost, and able to backtrack dike trajectories from vents on the surface. Finally, I combine the stress and dike models to simulate dike pathways in synthetic calderas. In the third part, I describe a framework of stress inversion and vent forecast strategy in 3D for calderas. The stress inversion relies on, first, describing the magma storage below a caldera in terms of a probability density function. Next, dike trajectories are backtracked from the known locations of past vents down through the crust, and the optimization algorithm seeks for the stress models which lead trajectories through the regions of highest probability. I apply the new strategy to the synthetic scenarios presented in the second part, and I exploit the results from the stress inversions to produce probability maps of future vent locations for some of those scenarios. In the fourth part, I present the inversion of different deformation source models applied to the ongoing ground deformation observed across the Rhenish Massif in Central Europe. The region includes the Eifel Volcanic Fields in Germany, a potential application case for the vent forecast strategy. The results show how the observed deformation may be due to melt accumulation in sub-horizontal structures in the lower crust or upper mantle. The thesis concludes with a discussion of the stress inversion and vent forecast strategy, its limitations and applicability to real volcanoes. Potential developments of the modeling tools and concepts presented here are also discussed, as well as possible applications to other geophysical problems.
Reactive eutectic media based on ammonium formate for the valorization of bio-sourced materials
(2023)
In the last several decades eutectic mixtures of different compositions were successfully used as solvents for vast amount of chemical processes, and only relatively recently they were discovered to be widely spread in nature. As such they are discussed as a third liquid media of the living cell, that is composed of common cell metabolites. Such media may also incorporate water as a eutectic component in order to regulate properties such as enzyme activity or viscosity. Taking inspiration form such sophisticated use of eutectic mixtures, this thesis will explore the use of reactive eutectic media (REM) for organic synthesis. Such unconventional media are characterized by the reactivity of their components, which means that mixture may assume the role of the solvent as well as the reactant itself.
The thesis focuses on novel REM based on ammonium formate and investigates their potential for the valorization of bio-sourced materials. The use of REM allows the performance of a number of solvent-free reactions, which entails the benefits of a superior atom and energy economy, higher yields and faster rates compared to reactions in solution. This is evident for the Maillard reaction between ammonium formate and various monosaccharides for the synthesis of substituted pyrazines as well as for a Leuckart type reaction between ammonium formate and levulinic acid for the synthesis of 5-methyl-2-pyrrolidone. Furthermore, reaction of ammonium formate with citric acid for the synthesis of yet undiscovered fluorophores, shows that synthesis in REM can open up unexpected reaction pathways.
Another focus of the thesis is the study of water as a third component in the REM. As a result, the concept of two different dilution regimes (tertiary REM and in REM in solvent) appears useful for understanding the influence of water. It is shown that small amounts of water can be of great benefit for the reaction, by reducing viscosity and at the same time increasing reaction yields.
REM based on ammonium formate and organic acids are employed for lignocellulosic biomass treatment. The thesis thereby introduces an alternative approach towards lignocellulosic biomass fractionation that promises a considerable process intensification by the simultaneous generation of cellulose and lignin as well as the production of value-added chemicals from REM components. The thesis investigates the generated cellulose and the pathway to nanocellulose generation and also includes the structural analysis of extracted lignin.
Finally, the thesis investigates the potential of microwave heating to run chemical reactions in REM and describes the synergy between these two approaches. Microwave heating for chemical reactions and the use of eutectic mixtures as alternative reaction media are two research fields that are often described in the scope of green chemistry. The thesis will therefore also contain a closer inspection of this terminology and its greater goal of sustainability.
The Lyman-𝛼 (Ly𝛼) line commonly assists in the detection of high-redshift galaxies, the so-called Lyman-alpha emitters (LAEs). LAEs are useful tools to study the baryonic matter distribution of the high-redshift universe. Exploring their spatial distribution not only reveals the large-scale structure of the universe at early epochs, but it also provides an insight into the early formation and evolution of the galaxies we observe today. Because dark matter halos (DMHs) serve as sites of galaxy formation, the LAE distribution also traces that of the underlying dark matter. However, the details of this relation and their co-evolution over time remain unclear. Moreover, theoretical studies predict that the spatial distribution of LAEs also impacts their own circumgalactic medium (CGM) by influencing their extended Ly𝛼 gaseous halos (LAHs), whose origin is still under investigation. In this thesis, I make several contributions to improve the knowledge on these fields using samples of LAEs observed with the Multi Unit Spectroscopic Explorer (MUSE) at redshifts of 3 < 𝑧 < 6.
Soft-template strategy enables the fabrication of composite nanomaterials with desired functionalities and structures. In this thesis, soft templates, including poly(ionic liquid) nanovesicles (PIL NVs), self-assembled polystyrene-b-poly(2-vinylpyridine) (PS-b-P2VP) particles, and glycopeptide (GP) biomolecules have been applied for the synthesis of versatile composite particles of PILs/Cu, molybdenum disulfide/carbon (MoS2/C), and GP-carbon nanotubes-metal (GP-CNTs-metal) composites, respectively. Subsequently, their possible applications as efficient catalysts in two representative reactions, i.e. CO2 electroreduction (CO2ER) and reduction of 4-nitrophenol (4-NP), have been studied, respectively.
In the first work, PIL NVs with a tunable particle size of 50 to 120 nm and a shell thickness of 15 to 60 nm have been prepared via one-step free radical polymerization. By increasing monomer concentration for polymerization, their nanoscopic morphology can evolve from hollow NVs to dense spheres, and finally to directional worms, in which a multi-lamellar packing of PIL chains occurred in all samples. The obtained PIL NVs with varied shell thickness have been in situ functionalized with ultra-small Cu nanoparticles (Cu NPs, 1-3 nm) and subsequently employed as the electrocatalysts for CO2ER. The hollow PILs/Cu composite catalysts exhibit a 2.5-fold enhancement in selectivity towards C1 products compared to the pristine Cu NPs. This enhancement is primarily attributed to the strong electronic interactions between the Cu NPs and the surface functionalities of PIL NVs. This study casts new aspects on using nanostructured PILs as novel electrocatalyst supports in efficient CO2 conversion.
In the second work, a novel approach towards fast degradation of 4-NP has been developed using porous MoS2/C particles as catalysts, which integrate the intrinsically catalytic property of MoS2 with its photothermal conversion capability. Various MoS2/C composite particles have been prepared using assembled PS-b-P2VP block copolymer particles as sacrificed soft templates. Intriguingly, the MoS2/C particles exhibit tailored morphologies including pomegranate-like, hollow, and open porous structures. Subsequently, the photothermal conversion performance of these featured particles has been compared under near infrared (NIR) light irradiation. When employing the open porous MoS2/C particles as the catalyst for the reduction of 4-NP, the reaction rate constant has increased by 1.5-fold under light illumination. This catalytic enhancement mainly results from the open porous architecture and photothermal conversion performance of the MoS2 particles. This proposed strategy offers new opportunities for efficient photothermal-assisted catalysis.
In the third work, a facile and green approach towards the fabrication of GP-CNTs-metal composites has been proposed, which utilizes a versatile GP biomolecule both as a stabilizer for CNTs in water and as a reducing agent for noble metal ions. The abundant hydrogen bonds in GP molecules bestow the formed GP-CNTs with excellent plasticity, enabling the availability of polymorphic CNTs species ranging from dispersion to viscous paste, gel, and even dough by increasing their concentration. The GP molecules can reduce metal precursors at room temperature without additional reducing agents, enabling the in situ immobilization of metal NPs (e.g. Au, Ag, and Pd) on the CNTs surface. The combination of excellent catalytic property of Pd NPs with photothermal conversion capability of CNTs makes the GP-CNTs-Pd composite a promising catalyst for the efficient degradation of 4-NP. The obtained composite displays a 1.6-fold increase in conversion under NIR light illumination in the reduction of 4-NP, mainly owing to the strong light-to-heat conversion effect of CNTs. Overall, the proposed method opens a new avenue for the synthesis of CNTs composite as a sustainable and versatile catalyst platform.
The results presented in the current thesis demonstrate the significance of using soft templates for the synthesis of versatile composites with tailored nanostructure and functionalities. The investigation of these composite nanomaterials in the catalytic reactions reveals their potential in the development of desired catalysts for emerging catalytic processes, e.g. photothermal-assisted catalysis and electrocatalysis.
The Security Operations Center (SOC) represents a specialized unit responsible for managing security within enterprises. To aid in its responsibilities, the SOC relies heavily on a Security Information and Event Management (SIEM) system that functions as a centralized repository for all security-related data, providing a comprehensive view of the organization's security posture. Due to the ability to offer such insights, SIEMS are considered indispensable tools facilitating SOC functions, such as monitoring, threat detection, and incident response.
Despite advancements in big data architectures and analytics, most SIEMs fall short of keeping pace. Architecturally, they function merely as log search engines, lacking the support for distributed large-scale analytics. Analytically, they rely on rule-based correlation, neglecting the adoption of more advanced data science and machine learning techniques.
This thesis first proposes a blueprint for next-generation SIEM systems that emphasize distributed processing and multi-layered storage to enable data mining at a big data scale. Next, with the architectural support, it introduces two data mining approaches for advanced threat detection as part of SOC operations.
First, a novel graph mining technique that formulates threat detection within the SIEM system as a large-scale graph mining and inference problem, built on the principles of guilt-by-association and exempt-by-reputation. The approach entails the construction of a Heterogeneous Information Network (HIN) that models shared characteristics and associations among entities extracted from SIEM-related events/logs. Thereon, a novel graph-based inference algorithm is used to infer a node's maliciousness score based on its associations with other entities in the HIN. Second, an innovative outlier detection technique that imitates a SOC analyst's reasoning process to find anomalies/outliers. The approach emphasizes explainability and simplicity, achieved by combining the output of simple context-aware univariate submodels that calculate an outlier score for each entry.
Both approaches were tested in academic and real-world settings, demonstrating high performance when compared to other algorithms as well as practicality alongside a large enterprise's SIEM system.
This thesis establishes the foundation for next-generation SIEM systems that can enhance today's SOCs and facilitate the transition from human-centric to data-driven security operations.
Inflammatory bowel diseases (IBD), characterised by a chronic inflammation of the gut wall, develop as consequence of an overreacting immune response to commensal bacteria, caused by a combination of genetic and environmental conditions. Large inter-individual differences in the outcome of currently available therapies complicate the decision for the best option for an individual patient. Predicting the prospects of therapeutic success for an individual patient is currently only possible to a limited extent; for this, a better understanding of possible differences between responders and non-responders is needed.
In this thesis, we have developed a mathematical model describing the most important processes of the gut mucosal immune system on the cellular level. The model is based on literature data, which were on the one hand used (qualitatively) to choose which cell types and processes to incorporate and to derive the model structure, and on the other hand (quantitatively) to derive the parameter values. Using ordinary differential equations, it describes the concentration-time course of neutrophils, macrophages, dendritic cells, T cells and bacteria, each subdivided into different cell types and activation states, in the lamina propria and mesenteric lymph nodes. We evaluate the model by means of simulations of the healthy immune response to salmonella infection and mucosal injury.
A virtual population includes IBD patients, which we define through their initially asymptomatic, but after a trigger chronically inflamed gut wall. We demonstrate the model's usefulness in different analyses: (i) The comparison of virtual IBD patients with virtual healthy individuals shows that the disease is elicited by many small or fewer large changes, and allows to make hypotheses about dispositions relevant for development of the disease. (ii) We simulate the effects of different therapeutic targets and make predictions about the therapeutic outcome based on the pre-treatment state. (iii) From the analysis of differences between virtual responders and non-responders, we derive hypotheses about reasons for the inter-individual variability in treatment outcome. (iv) For the example of anti-TNF-alpha therapy, we analyse, which alternative therapies are most promising in case of therapeutic failure, and which therapies are most suited for combination therapies: For drugs also directly targeting the cytokine levels or inhibiting the recruitment of innate immune cells, we predict a low probability of success when used as alternative treatment, but a large gain when used in a combination treatment. For drugs with direct effects on T cells, via modulation of the sphingosine-1-phosphate receptor or inhibition of T cell proliferation, we predict a considerably larger probability of success when used as alternative treatment, but only a small additional gain when used in a combination therapy.
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
This thesis discusses heat and charge transport phenomena in single-crystalline Silicon penetrated by nanometer-sized pores, known as mesoporous Silicon (pSi). Despite the extensive attention given to it as a thermoelectric material of interest, studies on microscopic thermal and electronic transport beyond its macroscopic characterizations are rarely reported. In contrast, this work reports the interplay of both.
PSi samples synthesized by electrochemical anodization display a temperature dependence of specific heat 𝐶𝑝 that deviates from the characteristic 𝑇^3 behaviour (at 𝑇<50𝐾). A thorough analysis reveals that both 3D and 2D Einstein and Debye modes contribute to this specific heat. Additional 2D Einstein modes (~3 𝑚𝑒𝑉) agree reasonably well with the boson peak of SiO2 in pSi pore walls. 2D Debye modes are proposed to account for surface acoustic modes causing a significant deviation from the well-known 𝑇^3 dependence of 𝐶𝑝 at 𝑇<50𝐾.
A novel theoretical model gives insights into the thermal conductivity of pSi in terms of porosity and phonon scattering on the nanoscale. The thermal conductivity analysis utilizes the peculiarities of the pSi phonon dispersion probed by the inelastic neutron scattering experiments. A phonon mean-free path of around 10 𝑛𝑚 extracted from the presented model is proposed to cause the reduced thermal conductivity of pSi by two orders of magnitude compared to p-doped bulk Silicon. Detailed analysis indicates that compound averaging may cause a further 10-50% reduction. The percolation threshold of 65% for thermal conductivity of pSi samples is subsequently determined by employing theoretical effective medium models.
Temperature-dependent electrical conductivity measurements reveal a thermally activated transport process. A detailed analysis of the activation energy 𝐸𝐴𝜎 in the thermally activated transport exhibits a Meyer Neldel compensation rule between different samples that originates in multi-phonon absorption upon carrier transport. Activation energies 𝐸𝐴𝑆 obtained from temperature-dependent thermopower measurements provide further evidence for multi-phonon assisted hopping between localized states as a dominant charge transport mechanism in pSi, as they systematically differ from the determined 𝐸𝐴𝜎 values.
Biomolecules such as proteins and lipids have vital roles in numerous cellular functions, including biomolecule transport, protein functions, cellular homeostasis and biomembrane integrity. Traditional biochemistry methods do not provide precise information about cellular biomolecule distribution and behavior under native environmental conditions since they are not transferable to live cell samples. Consequently, this can lead to inaccuracies in quantifying biomolecule interactions due to potential complexities arising from the heterogeneity of native biomembranes. To overcome these limitations, minimal invasive microscopic techniques, such as fluorescence fluctuation spectroscopy (FFS) in combination with fluorescence proteins (FPs) and fluorescence lipid analogs, have been developed. FFS techniques and membrane property sensors enable the quantification of various parameters, including concentration, dynamics, oligomerization, and interaction of biomolecules in live cell samples.
In this work, several FFS approaches and membrane property sensors were implemented and employed to examine biological processes of diverse context. Multi-color scanning fluorescence fluctuation spectroscopy (sFCS) was used the examine protein oligomerization, protein-protein interactions (PPIs) and protein dynamics at the cellular plasma membrane (PM). Additionally, two-color number and brightness (N&B) analysis was extended with the cross-correlation analysis in order to quantify hetero-interactions of proteins in the PM with very slow motion, which would not accessible with sFCS due strong initial photobleaching. Furthermore, two semi-automatic analysis pipelines were designed: spectral Förster resonance energy transfer (FRET) analysis to study changes in membrane charge at the inner leaflet of the PM, and spectral generalized polarization (GP) imaging and spectral phasor analysis to monitor changes in membrane fluidity and order.
An important parameter for studying PPIs is molecular brightness, which directly determines oligomerization and can be extracted from FFS data. However, FPs often display complex photophysical transitions, including dark states. Therefore, it is crucial to characterize FPs for their dark-states to ensure reliable oligomerization measurements. In this study, N&B and sFCS analysis were applied to determine photophysical properties of novel green FPs under different conditions (i.e., excitation power and pH) in living cells. The results showed that the new FPs, mGreenLantern (mGL) and Gamillus, exhibited the highest molecular brightness at the cost of lower photostability. The well-established monomeric enhanced green fluorescent protein (mEGFP) remained the best option to investigate PPIs at lower pH, while mGL was best suited for neutral pH, and Gamillus for high pH. These findings provide guidance for selecting an appropriate FP to quantify PPIs via FFS under different environmental conditions.
Next, several biophysical fluorescence microscopy approaches (i.e., sFCS, GP imaging, membrane charge FRET) were employed to monitor changes in lipid-lipid-packing in biomembranes in different biological context. Lipid metabolism in cancer cells is known to support rapid proliferation and metastasis. Therefore, targeting lipid synthesis or membrane integrity holds immense promise as an anticancer strategy. However, the mechanism of action of the novel agent erufosine (EPC3) on membrane stability is not fully under
stood. The present work revealed that EPC3 reduces lipid packing and composition as well as increased membrane fluidity and dynamic, hence, modifies lipid-lipid-interaction. These effects on membrane integrity were likely triggered by modulations in lipid metabolism and membrane organization. In the case of influenza A virus (IAV) infection, regulation of lipid metabolism is crucial for multiple steps in IAV replication and is related to the pathogenicity of IAV. Here, it is shown for the first time that IAV infection triggers a local enrichment of negatively charged lipids at the inner leaflet of the PM, which decreases membrane fluidity and dynamic, as well as increases lipid packing at the assembly site in living cells. This suggests that IAV alters lipid-lipid interactions and organization at the PM. Overall, this work highlights the potential of biophysical techniques as a screening platform for studying membrane properties in living cells at the single-cell level.
Finally, this study addressed remaining questions about the early stage of IAV assembly. The recruitment of matrix protein 1 (M1) and its interaction with other viral surface proteins, hemagglutinin (HA), neuraminidase (NA), and matrix protein 2 (M2), has been a subject of debate due to conflicting results. In this study, different FFS approaches were performed in transfected cells to investigate interactions between IAV proteins themselves and host factors at the PM. FFS measurements revealed that M2 interacts strongly with M1, leading to the translocation of M1 to the PM. This interaction likely took place along the non-canonical pathway, as evidenced by the detection of an interaction between M2 and the host factor LC3-II, leading to the recruitment of LC3-II to the PM. Moreover, weaker interaction was observed between HA and membrane-bound M1, and no interaction between NA and M1. Interestingly, higher oligomeric states of M1 were only detectable in infected cells. These results indicate that M2 initiates virion assembly by recruiting M1 to the PM, which may serve as a platform for further interactions with viral proteins and host factors.
Life on Earth is diverse and ranges from unicellular organisms to multicellular creatures like humans. Although there are theories about how these organisms might have evolved, we understand little about how ‘life’ started from molecules. Bottom-up synthetic biology aims to create minimal cells by combining different modules, such as compartmentalization, growth, division, and cellular communication.
All living cells have a membrane that separates them from the surrounding aqueous medium and helps to protect them. In addition, all eukaryotic cells have organelles that are enclosed by intracellular membranes. Each cellular membrane is primarily made of a lipid bilayer with membrane proteins. Lipids are amphiphilic molecules that assemble into molecular bilayers consisting of two leaflets. The hydrophobic chains of the lipids in the two leaflets face each other, and their hydrophilic headgroups face the aqueous surroundings. Giant unilamellar vesicles (GUVs) are model membrane systems that form large compartments with a size of many micrometers and enclosed by a single lipid bilayer. The size of GUVs is comparable to the size of cells, making them good membrane models which can be studied using an optical microscope. However, after the initial preparation, GUV membranes lack membrane proteins which have to be reconstituted into these membranes by subsequent preparation steps. Depending on the protein, it can be either attached via anchor lipids to one of the membrane leaflets or inserted into the lipid bilayer via its transmembrane domains.
The first step is to prepare the GUVs and then expose them to an exterior solution with proteins. Various protocols have been developed for the initial preparation of GUVs. For the second step, the GUVs can be exposed to a bulk solution of protein or can be trapped in a microfluidic device and then supplied with the protein solution. To minimize the amount of solution and for more precise measurements, I have designed a microfluidic device that has a main channel, and several dead-end side channels that are perpendicular to the main channel. The GUVs are trapped in the dead-end channels. This design exchanges the solution around the GUVs via diffusion from the main channel, thus shielding the GUVs from the flow within the main channel. This device has a small volume of just 2.5 μL, can be used without a pump and can be combined with a confocal microscope, enabling uninterrupted imaging of the GUVs during the experiments. I used this device for most of the experiments on GUVs that are discussed in this thesis.
In the first project of the thesis, a lipid mixture doped with an anchor lipid was used that can bind to a histidine chain (referred to as His-tag(ged) or 6H) via the metal cation Ni2+. This method is widely used for the biofunctionalization of GUVs by attaching proteins without a transmembrane domain. Fluorescently labeled His-tags which are bound to a membrane can be observed in a confocal microscope. Using the same lipid mixture, I prepared the GUVs with different protocols and investigated the membrane composition of the resulting GUVs by evaluating the amount of fluorescently labeled His-tagged molecules bound to their membranes. I used the microfluidic device described above to expose the outer leaflet of the vesicle to a constant concentration of the His-tagged molecules. Two fluorescent molecules with a His-tag were studied and compared: green fluorescent protein (6H-GFP) and fluorescein isothiocyanate (6H-FITC). Although the quantum yield in solution is similar for both molecules, the brightness of the membrane-bound 6H-GFP is higher than the brightness of the membrane-bound 6H-FITC. The observed difference in the brightness reveals that the fluorescence of the 6H-FITC is quenched by the anchor lipid via the Ni2+ ion. Furthermore, my measurements also showed that the fluorescence intensity of the membranebound His-tagged molecules depends on microenvironmental factors such as pH. For both 6H-GFP and 6H-FITC, the interaction with the membrane is quantified by evaluating the equilibrium dissociation constant. The membrane fluorescence is measured as a function of the fluorophores’ molar concentration. Theoretical analysis of these data leads to the equilibrium dissociation constants of (37.5 ± 7.5) nM for 6H-GFP and (18.5 ± 3.7) nM for 6H-FITC.
The anchor lipid mentioned previously used the metal cation Ni2+ to mediate the bond between the anchor lipid and the His-tag. The Ni2+ ion can be replaced by other transition metal ions. Studies have shown that Co3+ forms the strongest bonds with the His-tags attached to proteins. In these studies, strong oxidizing agents were used to oxidize the Co2+ mediated complex with the His-tagged protein to a Co3+ mediated complex. This procedure puts the proteins at risk of being oxidized as well. In this thesis, the vesicles were first prepared with anchor lipids without any metal cation. The Co3+ was added to these anchor lipids and finally the His-tagged protein was added to the GUVs to form the Co3+ mediated bond. This system was also established using the microfluidic device.
The different preparation procedures of GUVs usually lead to vesicles with a spherical morphology. On the other hand, many cell organelles have a more complex architecture with a non spherical topology. One fascinating example is provided by the endoplasmic reticulum (ER) which is made of a continuous membrane and extends throughout the cell in the form of tubes and sheets. The tubes are connected by three-way junctions and form a tubular network of irregular polygons. The formation and maintenance of these reticular networks requires membrane proteins that hydrolyize guanosine triphosphate (GTP). One of these membrane proteins is atlastin. In this thesis, I reconstituted the atlastin protein in GUV membranes using detergent-assisted reconstitution protocols to insert the proteins directly into lipid bilayers.
This thesis focuses on protein reconstitution by binding His-tagged proteins to anchor lipids and by detergent-assisted insertion of proteins with transmembrane domains. It also provides the design of a microfluidic device that can be used in various experiments, one example is the evaluation of the equilibrium dissociation constant for membrane-protein interactions. The results of this thesis will help other researchers to understand the protocols for preparing GUVs, to reconstitute proteins in GUVs, and to perform experiments using the microfluidic device. This knowledge should be beneficial for the long-term goal of combining the different modules of synthetic biology to make a minimal cell.
Housing in metabolic cages can induce a pronounced stress response. Metabolic cage systems imply housing mice on metal wire mesh for the collection of urine and feces in addition to monitoring food and water intake. Moreover, mice are single-housed, and no nesting, bedding, or enrichment material is provided, which is often argued to have a not negligible impact on animal welfare due to cold stress. We therefore attempted to reduce stress during metabolic cage housing for mice by comparing an innovative metabolic cage (IMC) with a commercially available metabolic cage from Tecniplast GmbH (TMC) and a control cage. Substantial refinement measures were incorporated into the IMC cage design. In the frame of a multifactorial approach for severity assessment, parameters such as body weight, body composition, food intake, cage and body surface temperature (thermal imaging), mRNA expression of uncoupling protein 1 (Ucp1) in brown adipose tissue (BAT), fur score, and fecal corticosterone metabolites (CMs) were included. Female and male C57BL/6J mice were single-housed for 24 h in either conventional Macrolon cages (control), IMC, or TMC for two sessions. Body weight decreased less in the IMC (females—1st restraint: 6.94%; 2nd restraint: 6.89%; males—1st restraint: 8.08%; 2nd restraint: 5.82%) compared to the TMC (females—1st restraint: 13.2%; 2nd restraint: 15.0%; males—1st restraint: 13.1%; 2nd restraint: 14.9%) and the IMC possessed a higher cage temperature (females—1st restraint: 23.7°C; 2nd restraint: 23.5 °C; males—1st restraint: 23.3 °C; 2nd restraint: 23.5 °C) compared with the TMC (females—1st restraint: 22.4 °C; 2nd restraint: 22.5 °C; males—1st restraint: 22.6 °C; 2nd restraint: 22.4 °C). The concentration of fecal corticosterone metabolites in the TMC (females—1st restraint: 1376 ng/g dry weight (DW); 2nd restraint: 2098 ng/g DW; males—1st restraint: 1030 ng/g DW; 2nd restraint: 1163 ng/g DW) was higher compared to control cage housing (females—1st restraint:
640 ng/g DW; 2nd restraint: 941 ng/g DW; males—1st restraint: 504 ng/g DW; 2nd restraint: 537 ng/g DW). Our results show the stress potential induced by metabolic cage restraint that is markedly influenced by the lower housing temperature. The IMC represents a first attempt to target cold stress reduction during metabolic cage application thereby producing more animal welfare friendly data.
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.
Due to anthropogenic greenhouse gas emissions, Earth’s average surface temperature is steadily increasing. As a consequence, many weather extremes are likely to become more frequent and intense. This poses a threat to natural and human systems, with local impacts capable of destroying exposed assets and infrastructure, and disrupting economic and societal activity. Yet, these effects are not locally confined to the directly affected regions, as they can trigger indirect economic repercussions through loss propagation along supply chains. As a result, local extremes yield a potentially global economic response. To build economic resilience and design effective adaptation measures that mitigate adverse socio-economic impacts of ongoing climate change, it is crucial to gain a comprehensive understanding of indirect impacts and the underlying economic mechanisms.
Presenting six articles in this thesis, I contribute towards this understanding. To this end, I expand on local impacts under current and future climate, the resulting global economic response, as well as the methods and tools to analyze this response.
Starting with a traditional assessment of weather extremes under climate change, the first article investigates extreme snowfall in the Northern Hemisphere until the end of the century. Analyzing an ensemble of global climate model projections reveals an increase of the most extreme snowfall, while mean snowfall decreases.
Assessing repercussions beyond local impacts, I employ numerical simulations to compute indirect economic effects from weather extremes with the numerical agent-based shock propagation model Acclimate. This model is used in conjunction with the recently emerged storyline framework, which involves analyzing the impacts of a particular reference extreme event and comparing them to impacts in plausible counterfactual scenarios under various climate or socio-economic conditions. Using this approach, I introduce three primary storylines that shed light on the complex mechanisms underlying economic loss propagation.
In the second and third articles of this thesis, I analyze storylines for the historical Hurricanes Sandy (2012) and Harvey (2017) in the USA. For this, I first estimate local economic output losses and then simulate the resulting global economic response with Acclimate. The storyline for Hurricane Sandy thereby focuses on global consumption price anomalies and the resulting changes in consumption. I find that the local economic disruption leads to a global wave-like economic price ripple, with upstream effects propagating in the supplier direction and downstream effects in the buyer direction. Initially, an upstream demand reduction causes consumption price decreases, followed by a downstream supply shortage and increasing prices, before the anomalies decay in a normalization phase. A dominant upstream or downstream effect leads to net consumption gains or losses of a region, respectively. Moreover, I demonstrate that a longer direct economic shock intensifies the downstream effect for many regions, leading to an overall consumption loss.
The third article of my thesis builds upon the developed loss estimation method by incorporating projections to future global warming levels. I use these projections to explore how the global production response to Hurricane Harvey would change under further increased global warming. The results show that, while the USA is able to nationally offset direct losses in the reference configuration, other countries have to compensate for increasing shares of counterfactual future losses. This compensation is mainly achieved by large exporting countries, but gradually shifts towards smaller regions. These findings not only highlight the economy’s ability to flexibly mitigate disaster losses to a certain extent, but also reveal the vulnerability and economic disadvantage of regions that are exposed to extreme weather events.
The storyline in the fourth article of my thesis investigates the interaction between global economic stress and the propagation of losses from weather extremes. I examine indirect impacts of weather extremes — tropical cyclones, heat stress, and river floods — worldwide under two different economic conditions: an unstressed economy and a globally stressed economy, as seen during the Covid-19 pandemic. I demonstrate that the adverse effects of weather extremes on global consumption are strongly amplified when the economy is under stress. Specifically, consumption losses in the USA and China double and triple, respectively, due to the global economy’s decreased capacity for disaster loss compensation. An aggravated scarcity intensifies the price response, causing consumption losses to increase.
Advancing on the methods and tools used here, the final two articles in my thesis extend the agent-based model Acclimate and formalize the storyline approach. With the model extension described in the fifth article, regional consumers make rational choices on the goods bought such that their utility is maximized under a constrained budget. In an out-of-equilibrium economy, these rational consumers are shown to temporarily increase consumption of certain goods in spite of rising prices.
The sixth article of my thesis proposes a formalization of the storyline framework, drawing on multiple studies including storylines presented in this thesis. The proposed guideline defines eight central elements that can be used to construct a storyline.
Overall, this thesis contributes towards a better understanding of economic repercussions of weather extremes. It achieves this by providing assessments of local direct impacts, highlighting mechanisms and impacts of loss propagation, and advancing on methods and tools used.
Magmatic-hydrothermal systems form a variety of ore deposits at different proximities to upper-crustal hydrous magma chambers, ranging from greisenization in the roof zone of the intrusion, porphyry mineralization at intermediate depths to epithermal vein deposits near the surface. The physical transport processes and chemical precipitation mechanisms vary between deposit types and are often still debated.
The majority of magmatic-hydrothermal ore deposits are located along the Pacific Ring of Fire, whose eastern part is characterized by the Mesozoic to Cenozoic orogenic belts of the western North and South Americas, namely the American Cordillera. Major magmatic-hydrothermal ore deposits along the American Cordillera include (i) porphyry Cu(-Mo-Au) deposits (along the western cordilleras of Mexico, the western U.S., Canada, Chile, Peru, and Argentina); (ii) Climax- (and sub−) type Mo deposits (Colorado Mineral Belt and northern New Mexico); and (iii) porphyry and IS-type epithermal Sn(-W-Ag) deposits of the Central Andean Tin Belt (Bolivia, Peru and northern Argentina).
The individual studies presented in this thesis primarily focus on the formation of different styles of mineralization located at different proximities to the intrusion in magmatic-hydrothermal systems along the American Cordillera. This includes (i) two individual geochemical studies on the Sweet Home Mine in the Colorado Mineral Belt (potential endmember of peripheral Climax-type mineralization); (ii) one numerical modeling study setup in a generic porphyry Cu-environment; and (iii) a numerical modeling study on the Central Andean Tin Belt-type Pirquitas Mine in NW Argentina.
Microthermometric data of fluid inclusions trapped in greisen quartz and fluorite from the Sweet Home Mine (Detroit City Portal) suggest that the early-stage mineralization precipitated from low- to medium-salinity (1.5-11.5 wt.% equiv. NaCl), CO2-bearing fluids at temperatures between 360 and 415°C and at depths of at least 3.5 km. Stable isotope and noble gas isotope data indicate that greisen formation and base metal mineralization at the Sweet Home Mine was related to fluids of different origins. Early magmatic fluids were the principal source for mantle-derived volatiles (CO2, H2S/SO2, noble gases), which subsequently mixed with significant amounts of heated meteoric water. Mixing of magmatic fluids with meteoric water is constrained by δ2Hw-δ18Ow relationships of fluid inclusions. The deep hydrothermal mineralization at the Sweet Home Mine shows features similar to deep hydrothermal vein mineralization at Climax-type Mo deposits or on their periphery. This suggests that fluid migration and the deposition of ore and gangue minerals in the Sweet Home Mine was triggered by a deep-seated magmatic intrusion.
The second study on the Sweet Home Mine presents Re-Os molybdenite ages of 65.86±0.30 Ma from a Mo-mineralized major normal fault, namely the Contact Structure, and multimineral Rb-Sr isochron ages of 26.26±0.38 Ma and 25.3±3.0 Ma from gangue minerals in greisen assemblages. The age data imply that mineralization at the Sweet Home Mine formed in two separate events: Late Cretaceous (Laramide-related) and Oligocene (Rio Grande Rift-related). Thus, the age of Mo mineralization at the Sweet Home Mine clearly predates that of the Oligocene Climax-type deposits elsewhere in the Colorado Mineral Belt. The Re-Os and Rb-Sr ages also constrain the age of the latest deformation along the Contact Structure to between 62.77±0.50 Ma and 26.26±0.38 Ma, which was employed and/or crosscut by Late Cretaceous and Oligocene fluids. Along the Contact Structure Late Cretaceous molybdenite is spatially associated with Oligocene minerals in the same vein system, a feature that precludes molybdenite recrystallization or reprecipitation by Oligocene ore fluids.
Ore precipitation in porphyry copper systems is generally characterized by metal zoning (Cu-Mo to Zn-Pb-Ag), which is suggested to be variably related to solubility decreases during fluid cooling, fluid-rock interactions, partitioning during fluid phase separation and mixing with external fluids. The numerical modeling study setup in a generic porphyry Cu-environment presents new advances of a numerical process model by considering published constraints on the temperature- and salinity-dependent solubility of Cu, Pb and Zn in the ore fluid. This study investigates the roles of vapor-brine separation, halite saturation, initial metal contents, fluid mixing, and remobilization as first-order controls of the physical hydrology on ore formation. The results show that the magmatic vapor and brine phases ascend with different residence times but as miscible fluid mixtures, with salinity increases generating metal-undersaturated bulk fluids. The release rates of magmatic fluids affect the location of the thermohaline fronts, leading to contrasting mechanisms for ore precipitation: higher rates result in halite saturation without significant metal zoning, lower rates produce zoned ore shells due to mixing with meteoric water. Varying metal contents can affect the order of the final metal precipitation sequence. Redissolution of precipitated metals results in zoned ore shell patterns in more peripheral locations and also decouples halite saturation from ore precipitation.
The epithermal Pirquitas Sn-Ag-Pb-Zn mine in NW Argentina is hosted in a domain of metamorphosed sediments without geological evidence for volcanic activity within a distance of about 10 km from the deposit. However, recent geochemical studies of ore-stage fluid inclusions indicate a significant contribution of magmatic volatiles. This study tested different formation models by applying an existing numerical process model for porphyry-epithermal systems with a magmatic intrusion located either at a distance of about 10 km underneath the nearest active volcano or hidden underneath the deposit. The results show that the migration of the ore fluid over a 10-km distance results in metal precipitation by cooling before the deposit site is reached. In contrast, simulations with a hidden magmatic intrusion beneath the Pirquitas deposit are in line with field observations, which include mineralized hydrothermal breccias in the deposit area.
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.
Predator-forager interactions are a major factor in evolutionary adaptation of many species, as predators need to gain energy by consuming prey species, and foragers needs to avoid the worst fate of mortality while still consuming resources for energetic gains. In this evolutionary arms race, the foragers have constantly evolved anti-predator behaviours (e.g. foraging activity changes). To describe all these complex changes, researchers developed the framework of the landscape of fear, that is, the spatio-temporal variation of perceived predation risk. This concept simplifies all the involved ecological processes into one framework, by integrating animal biology and distribution with habitat characteristics. Researchers can then evaluate the perception of predation risk in prey species, what are the behavioural responses of the prey and, therefore, understand the cascading effects of landscapes of fear at the resource levels (tri-trophic effects). Although tri-trophic effects are well studied at the predator-prey interaction level, little is known on how the forager-resource interactions are part of the overall cascading effects of landscapes of fear, despite the changes of forager feeding behaviour - that occur with perceived predation risk - affecting directly the level of the resources.
This thesis aimed to evaluate the cascading effects of the landscape of fear on biodiversity of resources, and how the feeding behaviour and movement of foragers shaped the final resource species composition (potential coexistence mechanisms). We studied the changes caused by landscapes of fear on wild and captive rodent communities and evaluated: the cascading effects of different landscapes of fear on a tri-trophic system (I), the effects of fear on a forager’s movement patterns and dietary preferences (II) and cascading effects of different types of predation risk (terrestrial versus avian, III).
In Chapter I, we applied a novel measure to evaluate the cascading effects of fear at the level of resources, by quantifying the diversity of resources left after the foragers gave-up on foraging (diversity at the giving-up density). We tested the measure at different spatial levels (local and regional) and observed that with decreased perceived predation risk, the density and biodiversity of resources also decreased. Foragers left a very dissimilar community of resources based on perceived risk and resources functional traits, and therefore acted as an equalising mechanism.
In Chapter II, we wanted to understand further the decision-making processes of rodents in different landscapes of fear, namely, in which resource species rodents decided to forage on (based on three functional traits: size, nutrients and shape) and how they moved depending on perceived predation risk. In safe landscapes, individuals increased their feeding activity and movements and despite the increased costs, they visited more often patches that were further away from their central-place. Despite a preference for the bigger resources regardless of risk, when perceived predation risk was low, individuals changed their preference to fat-rich resources.
In Chapter III, we evaluated the cascading effects of two different types of predation risk in rodents: terrestrial (raccoon) versus avian predation risk. Raccoon presence or absence did not alter the rodents feeding behaviour in different landscapes of fear. Rodent’s showed risk avoidance behaviours towards avian predators (spatial risk avoidance), but not towards raccoons (lack of temporal risk avoidance).
By analysing the effects of fear in tri-trophic systems, we were able to deepen the knowledge of how non-consumptive effects of predators affect the behaviour of foragers, and quantitatively measure the cascading effects at the level of resources with a novel measure. Foragers are at the core of the ecological processes and responses to the landscape of fear, acting as variable coexistence agents for resource species depending on perceived predation risk. This newly found measures and knowledge can be applied to more trophic chains, and inform researchers on biodiversity patterns originating from landscapes of fear.
Continental rifts are key geodynamic regions where the complex interplay of magmatism and faulting activity can be studied to understand the driving forces of extension and the formation of new divergent plate boundaries. Well-preserved rift morphology can provide a wealth of information on the growth, interaction, and linkage of normal-fault systems through time. If rift basins are preserved over longer geologic time periods, sedimentary archives generated during extensional processes may mirror tectonic and climatic influences on erosional and sedimentary processes that have varied over time. Rift basins are furthermore strategic areas for hydrocarbon and geothermal energy exploration, and they play a central role in species dispersal and evolution as well as providing or inhibiting hydrologic connectivity along basins at emerging plate boundaries.
The Cenozoic East African rift system (EARS) is one of the most important continental extension zones, reflecting a range of evolutionary stages from an early rift stage with isolated basins in Malawi to an advanced stage of continental extension in southern Afar. Consequently, the EARS is an ideal natural laboratory that lends itself to the study of different stages in the breakup of a continent. The volcanically and seismically active eastern branch of the EARS is characterized by multiple, laterally offset tectonic and magmatic segments where adjacent extensional basins facilitate crustal extension either across a broad deformation zone or via major transfer faulting. The Broadly Rifted Zone (BRZ) in southern Ethiopia is an integral part of the eastern branch of the EARS; in this region, rift segments of the southern Ethiopian Rift (sMER) and northern Kenyan Rift (nKR) propagate in opposite directions in a region with one of the earliest manifestations of volcanism and extensional tectonism in East Africa. The basin margins of the Chew-Bahir Basin and the Gofa Province, characterized by a semi-arid climate and largely uniform lithology, provide ideal conditions for studying the tectonic and geomorphologic features of this complex kinematic transfer zone, but more importantly, this area is suitable for characterizing and quantifying the overlap between the propagating structures of the sMER and nKR and the resulting deformation patterns of the BRZ transfer zones.
In this study, I have combined data from thermochronology, thermal modeling, morphometry, paleomagnetic analysis, geochronology, and geomorphological field observations with information from published studies to reconstruct the spatiotemporal relationship between volcanism and fault activity in the BRZ and quantify the deformation patterns of the overlapping rift segments. I present the following results: (1) new thermochronological data from the en-échelon basin margins and footwall blocks of the rift flanks and morphometric results verified in the field to link different phases of magmatism and faulting during extension and infer geomorphological landscape features related to the current tectonic interaction between the nKR and the sMER; (2) temporally constrained paleomagnetic data from the BRZ overlap zone between the Ethiopian and Kenyan rifts to quantitatively determine block rotation between the two segments. Combining the collected data, time-temperature histories of thermal modeling results from representative samples show well-defined deformation phases between 25–20 Ma, 15–9Ma, and ~5 Ma to the present. Each deformation phase is characterized by the onset of rapid cooling (>2°C/Ma) of the crust associated with uplift or exhumation of the rift shoulder. After an initial, spatially very diffuse phase of extension, the rift has gradually evolved into a system of connected structures formed in an increasingly focused rift zone during the last 5 Ma. Regarding the morphometric analysis of the rift structures, it can be shown that normalized slope indices of the river courses, spatial arrangement of knickpoints in the river longitudinal profiles of the footwall blocks, local relief values, and the average maximum values of the slope of the river profiles indicate a gradual increase in the extension rate from north (Sawula basin: mature) to south (Chew Bahir: young). The complexity of the structural evolution of the BRZ overlap zone between nKR and sMER is further emphasized by the documentation of crustal blocks around a vertical axis. A comparison of the mean directions obtained for the Eo-Oligocene (Ds=352.6°, Is=-17.0°, N=18, α95=5.5°) and Miocene (Ds=2.9°, Is=0.9°, N=9, α95=12.4°) volcanics relative to the pole for stable South Africa and with respect to the corresponding ages of the analyzed units record a significant counterclockwise rotation of ~11.1°± 6.4° and insignificant CCW rotation of ~3.2° ± 11.5°, respectively.
Modern datasets often exhibit diverse, feature-rich, unstructured data, and they are massive in size. This is the case of social networks, human genome, and e-commerce databases. As Artificial Intelligence (AI) systems are increasingly used to detect pattern in data and predict future outcome, there are growing concerns on their ability to process large amounts of data. Motivated by these concerns, we study the problem of designing AI systems that are scalable to very large and heterogeneous data-sets.
Many AI systems require to solve combinatorial optimization problems in their course of action. These optimization problems are typically NP-hard, and they may exhibit additional side constraints. However, the underlying objective functions often exhibit additional properties. These properties can be exploited to design suitable optimization algorithms. One of these properties is the well-studied notion of submodularity, which captures diminishing returns. Submodularity is often found in real-world applications. Furthermore, many relevant applications exhibit generalizations of this property.
In this thesis, we propose new scalable optimization algorithms for combinatorial problems with diminishing returns. Specifically, we focus on three problems, the Maximum Entropy Sampling problem, Video Summarization, and Feature Selection. For each problem, we propose new algorithms that work at scale. These algorithms are based on a variety of techniques, such as forward step-wise selection and adaptive sampling. Our proposed algorithms yield strong approximation guarantees, and the perform well experimentally.
We first study the Maximum Entropy Sampling problem. This problem consists of selecting a subset of random variables from a larger set, that maximize the entropy. By using diminishing return properties, we develop a simple forward step-wise selection optimization algorithm for this problem. Then, we study the problem of selecting a subset of frames, that represent a given video. Again, this problem corresponds to a submodular maximization problem. We provide a new adaptive sampling algorithm for this problem, suitable to handle the complex side constraints imposed by the application. We conclude by studying Feature Selection. In this case, the underlying objective functions generalize the notion of submodularity. We provide a new adaptive sequencing algorithm for this problem, based on the Orthogonal Matching Pursuit paradigm.
Overall, we study practically relevant combinatorial problems, and we propose new algorithms to solve them. We demonstrate that these algorithms are suitable to handle massive datasets. However, our analysis is not problem-specific, and our results can be applied to other domains, if diminishing return properties hold. We hope that the flexibility of our framework inspires further research into scalability in AI.
Solar photocatalysis is the one of leading concepts of research in the current paradigm of sustainable chemical industry. For actual practical implementation of sunlight-driven catalytic processes in organic synthesis, a cheap, efficient, versatile and robust heterogeneous catalyst is necessary. Carbon nitrides are a class of organic semiconductors who are known to fulfill these requirements.
First, current state of solar photocatalysis in economy, industry and lab research is overviewed, outlining EU project funding, prospective synthetic and reforming bulk processes, small scale solar organic chemistry, and existing reactor designs and prototypes, concluding feasibility of the approach.
Then, the photocatalytic aerobic cleavage of oximes to corresponding aldehydes and ketones by anionic poly(heptazine imide) carbon nitride is discussed. The reaction provides a feasible method of deprotection and formation of carbonyl compounds from nitrosation products and serves as a convenient model to study chromoselectivity and photophysics of energy transfer in heterogeneous photocatalysis.
Afterwards, the ability of mesoporous graphitic carbon nitride to conduct proton-coupled electron transfer was utilized for the direct oxygenation of 1,3-oxazolidin-2-ones to corresponding 1,3-oxazlidine-2,4-diones. This reaction provides an easier access to a key scaffold of diverse types of drugs and agrochemicals.
Finally, a series of novel carbon nitrides based on poly(triazine imide) and poly(heptazine imide) structure was synthesized from cyanamide and potassium rhodizonate. These catalysts demonstrated a good performance in a set of photocatalytic benchmark reactions, including aerobic oxidation, dual nickel photoredox catalysis, hydrogen peroxide evolution and chromoselective transformation of organosulfur precursors.
Concluding, the scope of carbon nitride utilization for net-oxidative and net-neutral photocatalytic processes was expanded, and a new tunable platform for catalyst synthesis was discovered.
Essays in public economics
(2023)
This cumulative dissertation uses economic theory and micro-econometric tools and evaluation methods to analyse public policies and their impact on welfare and individual behaviour. In particular, it focuses on policies in two distinct areas that represent fundamental societal challenges in the 21st century: the ageing of society and life in densely-populated urban agglomerations. Together, these areas shape important financial decisions in a person's life, impact welfare, and are driving forces behind many of the challenges in today's societies. The five self-contained research chapters of this thesis analyse the forward looking effects of pension reforms, affordable housing policies as well as a public transport subsidy and its effect on air pollution.