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From back-arc spreading center to volcanic arc: Hydrothermal vent fluid chemistry across the North-East Lau Basin, SW Pacific
No full textThis PhD thesis focuses on the investigation of high-temperature hydrothermal vent fluids from multiple vent sites between the North-Eastern Lau Spreading Center and the Tofua arc.
The sampling area is located in the northeastern part of the Lau Basin which is affected by some of earths’ highest subduction rate, a highly complex microplate tectonic, an influence of hot spot material from the Samoan mantle plume as well as the subduction of the Louisville Seamount Chain. This study extends our knowledge of high-temperature hydrothermal systems in the North-East Lau Basin, in that it reports for the first time on the chemical and isotopic composition of vent fluids from Maka volcano and Niuatahi volcano. This cumulative PhD thesis highlights the compositional variability of hydrothermal fluids associated with different geologic settings. The newly reported vent fluid data as well as systematic spatial distribution of trace metals and metalloids adds to our understanding of hydrothermal processes and in the future may help improve the estimates of element specific fluxes associated with seafloor hydrothermalism
Improved Steel Production Planning through Data Analysis and Optimization
No full textThe following thesis addresses several shortcomings in the academic literature surrounding steel production planning. These shortcomings are summarized as (i) failure to incorporate tacit production knowledge into steel decision support systems, (ii) negligence of physical boundaries / limitations of the steel manufacturing process, and (iii) lack of global (as opposed to local) optimization approaches in steel scheduling algorithms. Not incorporating tacit production knowledge typically leads to wrong decision advice and sub-optimal decision-making, whereas neglecting the theoretical output limits of the steel production process can cause unnecessary machine breakdowns and diminished productivity; also, if production scheduling algorithms focus too much on specific sub-elements of the optimization problem (e.g. upstream production lines), this will adverse effects on the remaining elements (e.g. downstream production lines). To overcome these shortcomings, different methodologies are applied: (i) Through a mixture of association rules mining and complex network analysis, we extract production knowledge hidden in historical production data that documents the decisions of a human expert planner; this extracted knowledge could now be utilized by decision support systems. (ii) In historical production data, we identify a theoretical upper limit of the casting speed that mitigates the productivity of continuous casters; adapting the average casting speed to this limit could increase the production output. This phenomenon is further investigated through minimal models of production systems which are characterized by (a) stochastic production inputs and (b) disruptive thresholds on the production output. (iii) We develop two genetic algorithms out of which the first algorithm optimizes multiple production sequences at the same time as opposed to one after another, while the second algorithm simultaneously generates schedules for two production processes
Microplastics in the Weser – North Sea transitional system: Potential pathways and methodological improvements
No full textMicroplastics (MP) have received increased scientific, political and societal attention due to their environmental omnipresence. This thesis aims to provide comprehensive data on aquatic MP pollution through the application of state-of-the-art analytical methods, and compares data outputs from two data pipelines.
Within the River Weser–North Sea transitional system, small MP (500 µm) exhibited low abundances, mainly composed of the common plastic polymers polyethylene and polypropylene. The estuary’s turbidity maximum zone showed the highest MP concentrations, then declining towards the North Sea, possibly influenced by increased vertical and horizontal export or dilution in the larger marine water body. Additionally, this thesis evaluated two wastewater treatment plants as potential riverine MP point sources. Interference by post-processing residual material required an adaptation of the FTIR reference database by the inclusion of new reference material. Results showed that polyolefins were prevalent in the effluent, and that observed temporal patterns in MP concentrations could be partially explained by technical and environmental parameters. Input of MP into the River Weser via effluent is likely, necessitating more research to understand the full dynamics of MP pollution within this river system. Furthermore, the MP analysis pipeline comparison study showed discrepancies for certain polymer types, possibly due to different polymer grouping methods, or overestimation effects. By excluding these polymer types, both datasets generally were in accordance, suggesting a harmonization of both pipelines should be undertaken to improve comparability of MP data.
In summary, this thesis provides a detailed foundation for understanding MP dynamics in the River Weser–North Sea system and highlights methodological challenges inherent in the field of MP pollution research
Thermodynamics and Dynamics of Random Spin Chains with Long-range Interactions.
No full textIn this thesis, we discuss the properties of quantum antiferromagnetic spin chains with long-range (LR) tunable interactions and positional disorder. By long-range, we mean that the range of interactions falls-off as a power law with the distance. We mainly focus on the entanglement properties of these systems and consider both ground state and high-energy eigenstates.
Additionally, the dynamical properties of the LR random spin chain are considered by investigating the post-quench entanglement growth as a function of time. Finally, we study the response of this system to a local perturbation by considering the quantum fidelity variations with system size.
While analytical results for LR interacting disordered systems are not abundant in the literature, we achieve the implementation of strong disorder renormalization group(SDRG) procedures (and variants) on such models. We systematically confront our results with numerical exact diagonalization(ED) to confirm the obtained predictions
Designing Virtual Constraints for IT-Supported Creativity
No full textIncreasingly decentralized collaboration drives the development of new creativity support systems (CSS) that offer virtual teams various means for communication, information exchange, and creative collaboration. As CSS aim to mitigate the limitations of virtual communication and collaboration, reason suggests that more functionalities yield better outcomes. Hence, a wide range of capabilities for interaction, knowledge sharing, or innovative collaboration processes is implemented into these CSS.
However, if CSS offer functionalities beyond the required level, they can become confusing to use, overload users, or cause feature fatigue. Previous research shows that having more options or functionalities does not always lead to better results, especially in the context of creativity, and suggests a curvilinear relationship between constraints and creativity. While the effects of constraints on creative collaboration have been studied in analogue settings before, their design and application to support creative collaboration in virtual contexts, remains under-researched.
This PhD thesis examines how constraints in CSS can be designed to foster creative collaboration and contribute to a better understanding of how limited functionalities and interactions during particular phases of creative collaboration can help individuals and teams access a CSS's instrumental potential and benefit from idea generation and exploration beyond routine performance, and encourage more radical forms of creativity. To support the evolution of knowledge about the theory and practice of CSS design, this research project follows a design science research (DSR) approach
A first approach to seawater gallium-aluminium systematics throughout Earth’s history
No full textMarine chemical sedimentary rocks, like banded iron formations (BIFs), ferromanganese (Fe-Mn) crusts and nodules, marine carbonates or cherts, are of great scientific interest because they can preserve primary information on the physico-chemical conditions of ambient seawater. Especially for research on the Precambrian, marine chemical sedimentary rocks are invaluable archives as they are the only remaining access point to the geochemical conditions of the Archaean and Palaeoproterozoic marine environment. This PhD thesis investigates the geochemical partner couples of gallium, aluminium (Ga-Al), germanium, and silicon (Ge-Si). Those two couples show mostly coherent geochemical behaviour in igneous and clastic sedimentary processes. However, in (low- low-temperature) aqueous environments, both partners decouple from each other. This thesis aims to investigate the behaviour of Ga-Al and Ge-Si during the precipitation of Fe (oxyhydr)oxides in the natural environment and to elaborate on whether characteristic distributions of Ga/Al and Ge/Si ratios in marine chemical sedimentary rocks can be applied as geochemical proxies
Trace metals and organic matter in the Amazon-Pará River Estuary
No full textThe Amazon is the largest River on earth, accounting for 15–20% of the global river freshwater discharge, and making it an important source of trace metals, nutrients and organic matter to the Atlantic Ocean. The nearby Pará River is the 5th largest river and converges to mix in the Amazon Estuary. Trace metals in the ocean (e.g., Mn, Co, Fe, Ni, Cu, Zn, Cd and Pb) act as important nutrients and/or toxins to marine organisms. However, no data exists for these trace metals in the Amazon Estuary after 1976. Therefore, it is of urgent importance to establish a baseline for trace metals in the Amazon estuary. A GEOTRACES process study (cruise GApr11) was conducted in the Amazon estuary during the wet season (April–May) of 2018. Herein we present data for dissolved trace metals and organic matter from samples collected from this cruise. Chapter 1 focuses on copper (Cu), a micronutrient and potential toxin, and its complexation to organic ligands. Chapter 2 discusses two other micronutrients, cobalt (Co) and nickel (Ni), in surface and depth samples analyzed by two different methods. Chapter 3 brings together all trace metals from this study (Al, Mn, Co, Fe, Ni, Cu, Zn, Cd, Pb and U) to calculate the fluxes from the Amazon and Pará Rivers into the Atlantic Ocean. Finally, chapter 4 describes depth profiles of bioactive metals in different size fractions. Trace metal cycling in the estuary was influenced by complex biogeochemical processes, including ligand complexation, particle adsorption-desorption, colloidal flocculation, physical mixing and biological activity. In addition, we observed distinct influences from the Amazon and Pará Rivers, which draw from distinct catchment areas. Cu was mostly conservative with respect to salinity, while Fe and Pb were highly particle reactive during early mixing and experienced the greatest estuary removal. We estimated that the Amazon and Pará Rivers account for ~21% and 18% of the global riverine Cu and Ni to the oceans
Extending the body in augmented reality: Behavioral and neural correlates of body schema plasticity during virtual tool-use in young and old adults
No full textIn our daily life, we are continuously required to learn new motor skills and adapt these skills to new situations, such as during tool-use. Tool-use as one of the hallmark skills in humans serves to functionally extend our body to overcome physical limitations to interact or manipulate other objects or organisms in an environment.
In the present dissertation, I used behavioral and neural oscillation correlates of body schema plasticity during virtual tool-use in young and older adults to investigate the embodiment of virtual tools into the body schema, body image and the association between body ownership and agency as well as their mutual dependency on action-related sensory feedback.
To do so, an arm-shaped virtual tool-use paradigm was employed in order to study forearm sensorimotor body schema, and its level of plasticity in young and older individuals during a sequential motor learning task.
Overall, our findings suggest that virtual tools can be incorporated into the existing body schema of the forearm in younger adults but not in older adults, while showcasing how future work may further disambiguate the contributions of tactile and visual feedback. Additionally, resting-state beta power and task-related theta, alpha and beta power predicts stronger practice effect during virtual tool-use in younger adults compared to older adults.
All together, I conclude that a sense of agency may strongly relate to improvement in tool-use in older adults dependent on practice effect but independent of alterations in the body schema, while ownership did not emerge due to a lack of body schema plasticity. Additionally, I concluded that the stronger practice effect during virtual tool-use training is positively related with resting-state relative beta power, higher task-related relative theta power and lower task-related alpha across frontal, parietal and occipital regions in younger adults but not in older adults
Applying Psychology to Improve Communication Behaviour and Patient Safety: A Needs Assessment, Two Interventions, and General Implications for Theory and Practice
No full textSustainable behaviour change in healthcare is a complex process influenced by a variety of dynamic factors. This thesis aims to close existing research gaps concerning psychological factors of patient safety behaviours to develop effective interventions to improve patient safety in the exemplary field of obstetrics.
Study 1 made 267 observations of hand hygiene behaviour over three time periods. Questionnaire data on psychological determinants were analysed with multiple regression and multiple mediation analyses. Study 2 reports results of path analyses and multiple regression analyses concerning a survey with N = 137 obstetric healthcare workers. Pre- and post-intervention data was compared in a repeated-measures multiple analysis of variance. In Study 3, a randomized-controlled trial was conducted with pregnant women. The intervention group (NT1 = 225; NT2 = 142) received an online training and was compared to a passive control group (NT1 = 199; NT2 = 144) using multilevel analyses and intention-to-treat analyses after multiple imputation.
In Study 1, it was found that adherence to hand hygiene recommendations increased during COVID-19 pandemic, depending on self-efficacy. Study 2 showed that perceived patient safety risks were associated with communication behaviour. After the intervention, fewer patient safety risks were reported and coping self-efficacy increased. In Study 3, intention-to-treat analyses confirmed a higher intervention effect for communication behaviour, perceived quality of birth, and coping planning in the intervention group.
This thesis emphasizes the role of psychology to understand behavioural determinants and change patient safety behaviour in healthcare. To improve interventions in healthcare, structured implementation guidelines should be used in multidisciplinary programmes. Future research needs to apply more high-quality research designs, look at multidisciplinary outcome measures, and target more diverse and marginalized groups
Challenges in Integration and Analysis of High-Dimensional Biological Data: Cases from Environmental and Health Research
No full textBiological data represent a large, challenging sector of data engineering applications. Biological data are typically complex and poorly standardized. Moreover, high value, rapid growth in volume and advances in acquisition technologies characterize modern environmental and health research data, humbling the classical practices for data transformation and analytics. Furthermore, data in biology make more sense when integrated with usually different data types, or data from different sources or even fields. In addition, the uniqueness of each case and research question call for a deep understanding of data life cycle and for customized solutions. Having a large volume and value, and being produced at a high velocity in a large variety, biological data encourage the investigation of scalable workflows to automate acquisition and integration, closing the gaps in optimizing analytics specially for heterogeneous data.
This thesis aims at exploring and optimizing the state-of-the-art methods for heterogeneous data integration and analysis, of sequence and non-sequence-based data, by identifying four areas of application concerning primary and secondary data from environmental and health research. It presents four challenges in data preparation and transformation for variable selection, and accompanying case studies. Particularly, the thesis investigates knowledge extraction from primary inherently high-dimensional marine sequence data, scalability in handling secondary photosynthetic sequence data, integration and statistical modeling of secondary high-dimensional relational health care claims data for adverse drug event prediction, and integration of heterogeneous primary epidemiological data for childhood obesity investigation. The thesis highlights the importance of data model development for data transformation and integration, and the role of scalable analytics in the foreseen increase in data dimensions