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Die vorliegende Arbeit thematisiert die Synthese und die Polymerisation von Monomeren auf der Basis nachwachsender Rohstoffe wie zum Beispiel in Gewürzen und ätherischen Ölen enthaltenen kommerziell verfügbaren Phenylpropanoiden (Eugenol, Isoeugenol, Zimtalkohol, Anethol und Estragol) und des Terpenoids Myrtenol sowie ausgehend von der Rinde einer Birke (Betula pendula) und der Korkeiche (Quercus suber). Ausgewählte Phenylpropanoide (Eugenol, Isoeugenol und Zimtalkohol) und das Terpenoid Myrtenol wurden zunächst in den jeweiligen Laurylester überführt und anschließend das olefinische Strukturelement epoxidiert, wobei 4 neue (2-Methoxy-4-(oxiran-2-ylmethyl)phenyldodecanoat, 2-Methoxy-4-(3-methyl-oxiran-2-yl)phenyldodecanoat, (3-Phenyloxiran-2-yl)methyldodecanoat, (7,7-Dimethyl-3-oxatricyclo[4.1.1.02,4]octan-2-yl)methyldodecanoat) und 2 bereits bekannte monofunktionelle Epoxide (2-(4-Methoxybenzyl)oxiran und 2-(4-Methoxyphenyl)-3-methyloxiran) erhalten wurden, die mittels 1H-NMR-, 13C-NMR- und FT-IR-Spektroskopie sowie mit DSC untersucht wurden. Die Photo-DSC Untersuchung der Epoxidmonomere in einer kationischen Photopolymerisation bei 40 °C ergab die maximale Polymerisationsgeschwindigkeit (Rpmax: 0,005 s-1 bis 0,038 s-1) sowie die Zeit (tmax: 13 s bis 26 s) bis zum Erreichen des Rpmax-Wertes und führte zu flüssigen Oligomeren, deren zahlenmittlerer Polymerisationsgrad mit 3 bis 6 mittels GPC bestimmt wurde. Die Umsetzung von 2-Methoxy-4-(oxiran-2-ylmethyl)phenyldodecanoat mit Methacrylsäure ergab ein Isomerengemisch (2-Methoxy-4-(2-hydroxy-3-(methacryloyloxy)propyl)phenyldodecanoat und 2-Methoxy-4-(2-(methacryl-oyloxy)-3-hydroxypropyl)phenyldodecanoat), das mittels Photo-DSC in einer freien radikalischen Photopolymerisation untersucht wurde (Rpmax: 0,105 s-1 und tmax: 5 s), die zu festen in Chloroform unlöslichen Polymeren führte.
Aus Korkpulver und gemahlener Birkenrinde wurden selektiv 2 kristalline
ω-Hydroxyfettsäuren (9,10-Epoxy-18-hydroxyoctadecansäure und 22-Hydroxydocosansäure) isoliert. Die kationische Photopolymerisation der 9,10-Epoxy-18-hydroxyoctadecansäure ergab einen nahezu farblosen transparenten und bei Raumtemperatur elastischen Film, welcher ein Anwendungspotential für Oberflächenbeschichtungen hat. Aus der Reaktion von 9,10-Epoxy-18-hydroxyoctadecansäure mit Methacrylsäure wurde ein bei Raumtemperatur flüssiges Gemisch aus zwei Konstitutionsisomeren (9,18-Dihydroxy-10-(methacryloyl-oxy)octadecansäure und 9-(Methacryloyloxy)-10,18-dihydroxyoctadecansäure) erhalten
(Tg: -60 °C). Die radikalische Photopolymerisation dieser Konstitutionsisomere wurde ebenfalls mittels Photo-DSC untersucht (Rpmax: 0,098 s-1 und tmax: 3,8 s). Die Reaktion von 22-Hydroxydocosansäure mit Methacryloylchlorid ergab die kristalline 22-(Methacryloyl-oxy)docosansäure, welche ebenfalls in einer radikalischen Photopolymerisation mittels Photo-DSC untersucht wurde (Rpmax: 0,023 s-1 und tmax: 9,6 s).
Die mittels AIBN in Dimethylsulfoxid initiierte Homopolymerisation der
22-(Methacryloyloxy)docosansäure und der Isomerengemische bestehend aus 2-Methoxy-4-(2-hydroxy-3-(methacryloyloxy)propyl)phenyldodecanoat und 2-Methoxy-4-(2-(methacryl-oyloxy)-3-hydroxypropyl)phenyldodecanoat sowie aus 9,18-Dihydroxy-10-(methacryloy-loxy)octadecansäure und 9-(Methacryloyloxy)-10,18-dihydroxyoctadecansäure ergab feste lösliche Polymere, die mittels 1H-NMR- und FT-IR-Spektroskopie, GPC (Poly(2-methoxy-4-(2-hydroxy-3-(methacryloyloxy)propyl)phenyldodecanoat / 2-methoxy-4-(2-(methacryloyl-oxy)-3-hydroxypropyl)phenyldodecanoat): Pn = 94) und DSC (Poly(2-methoxy-4-(2-hydroxy-3-(methacryloyloxy)propyl)phenyldodecanoat / 2-methoxy-4-(2-(methacryloyloxy)-3-hydroxypropyl)phenyldodecanoat): Tg: 52 °C; Poly(9,18-dihydroxy-10-(methacryloyloxy)-octadecansäure / 9-(methacryloyloxy)-10,18-dihydroxyoctadecansäure): Tg: 10 °C; Poly(22-(methacryloyloxy)docosansäure): Tm: 74,1 °C, wobei der Schmelzpunkt mit dem des Photopolymers (Tm = 76,8 °C) vergleichbar ist) charakterisiert wurden.
Das bereits bekannte Monomer 4-(4-Methacryloyloxyphenyl)butan-2-on wurde ausgehend von 4-(4-Hydroxyphenyl)butan-2-on hergestellt, welches aus Birkenrinde gewonnen werden kann, und unter identischen Bedingungen für einen Vergleich mit den neuen Monomeren polymerisiert. Die freie radikalische Polymerisation führte zu Poly(4-(4-methacryloyloxy-phenyl)butan-2-on) (Pn: 214 und Tg: 83 °C). Neben der Homopolymerisation wurde eine statistische Copolymerisation des Isomerengemisches 2-Methoxy-4-(2-hydroxy-3-(methacryl-oyloxy)propyl)phenyldodecanoat / 2-Methoxy-4-(2-(methacryloyl-oxy)-3-hydroxypropyl)-phenyldodecanoat mit 4-(4-Methacryloyloxyphenyl)butan-2-on untersucht, wobei ein äquimolarer Einsatz der Ausgangsmonomere zu einem Anstieg der Ausbeute, der Molmassenverteilung und der Dispersität des Copolymers (Tg: 44 °C) führte. Die unter Verwendung von Diethylcarbonat als „grünes“ Lösungsmittel mittels AIBN initiierten freien radikalischen Homopolymerisationen von 4-(4-Methacryloyloxyphenyl)butan-2-on und von Laurylmethacrylat ergaben vergleichbare Polymerisationsgrade der Homopolymere (Pn: 150), welche jedoch aufgrund ihrer Strukturunterschiede deutlich unterschiedliche Glasübergangstemperaturen hatten (Poly(4-(4-methacryloyloxyphenyl)butan-2-on): Tg: 70 °C, Poly(laurylmethacrylat) Tg: -49 °C. Eine statistische Copolymerisation äquimolarer Stoffmengen der beiden Monomere in Diethylcarbonat führte bei einer Polymerisationszeit von 60 Minuten zu einem leicht bevorzugten Einbau des 4-(4-Methacryloyloxyphenyl)butan-2-on in das Copolymer (Tg: 17 °C). Copolymerisationsdiagramme für die freien radikalischen Copolymerisationen von 4-(4-Methacryloyloxyphenyl)butan-2-on mit n-Butylmethacrylat beziehungsweise 2-(Dimethylamino)ethylmethacrylat (t: 20 min bis 60 min; Molenbrüche (X) für 4-(4-Methacryloyloxyphenyl)butan-2-on: 0,2; 0,4; 0,6 und 0,8) zeigten ein nahezu ideales azeotropes Copolymerisationsverhalten, obwohl ein leicht bevorzugter Einbau von
4-(4-Methacryloyloxyphenyl)butan-2-on in das jeweilige Copolymer beobachtet wurde. Dabei korreliert ein Anstieg der Ausbeute und der Glasübergangstemperatur der erhaltenen Copolymere mit einem zunehmenden Gehalt an 4-(4-Methacryloyloxyphenyl)butan-2-on im Reaktionsgemisch. Die unter Einsatz der modifizierten Gibbs-DiMarzio-Gleichung berechneten Glasübergangstemperaturen der Copolymere stimmten mit den gemessenen Werten gut überein. Das ist eine gute Ausgangsbasis für die Bestimmung der Glasübergangstemperatur eines Copolymers mit einer beliebigen Zusammensetzung.
Ecosystems play a pivotal role in addressing climate change but are also highly susceptible to drastic environmental changes. Investigating their historical dynamics can enhance our understanding of how they might respond to unprecedented future environmental shifts. With Arctic lakes currently under substantial pressure from climate change, lessons from the past can guide our understanding of potential disruptions to these lakes. However, individual lake systems are multifaceted and complex. Traditional isolated lake studies often fail to provide a global perspective because localized nuances—like individual lake parameters, catchment areas, and lake histories—can overshadow broader conclusions. In light of these complexities, a more nuanced approach is essential to analyze lake systems in a global context.
A key to addressing this challenge lies in the data-driven analysis of sedimentological records from various northern lake systems. This dissertation emphasizes lake systems in the northern Eurasian region, particularly in Russia (n=59). For this doctoral thesis, we collected sedimentological data from various sources, which required a standardized framework for further analysis. Therefore, we designed a conceptual model for integrating and standardizing heterogeneous multi-proxy data into a relational database management system (PostgreSQL). Creating a database from the collected data enabled comparative numerical analyses between spatially separated lakes as well as between different proxies.
When analyzing numerous lakes, establishing a common frame of reference was crucial. We achieved this by converting proxy values from depth dependency to age dependency. This required consistent age calculations across all lakes and proxies using one age-depth modeling software. Recognizing the broader implications and potential pitfalls of this, we developed the LANDO approach ("Linked Age and Depth Modelling"). LANDO is an innovative integration of multiple age-depth modeling software into a singular, cohesive platform (Jupyter Notebook). Beyond its ability to aggregate data from five renowned age-depth modeling software, LANDO uniquely empowers users to filter out implausible model outcomes using robust geoscientific data. Our method is not only novel but also significantly enhances the accuracy and reliability of lake analyses.
Considering the preceding steps, this doctoral thesis further examines the relationship between carbon in sediments and temperature over the last 21,000 years. Initially, we hypothesized a positive correlation between carbon accumulation in lakes and modelled paleotemperature. Our homogenized dataset from heterogeneous lakes confirmed this association, even if the highest temperatures throughout our observation period do not correlate with the highest carbon values. We assume that rapid warming events contribute more to high accumulation, while sustained warming leads to carbon outgassing. Considering the current high concentration of carbon in the atmosphere and rising temperatures, ongoing climate change could cause northern lake systems to contribute to a further increase in atmospheric carbon (positive feedback loop). While our findings underscore the reliability of both our standardized data and the LANDO method, expanding our dataset might offer even greater assurance in our conclusions.
Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
Legitimiertes Unrecht
(2024)
Das Oberste Gericht der DDR war integraler Bestandteil der sozialistischen Staatsführung und unterlag strengen Denk- und Organisationsstrukturen. Es war eng in die politische Agenda der SED eingebunden und genoss keinerlei Unabhängigkeit. Die Auslegung des DDR-Rechts durch das Gericht orientierte sich ausschließlich an den innen- und außenpolitischen Interessen der SED. Dies galt auch für die Rechtsprechung in Fällen der Republikflucht und ihrer gesetzlichen Vorläufer. Die höchste Gerichtsinstanz im Staat war aktiv an der Gestaltung und Umsetzung der Strafjustiz gegen Republikflüchtige beteiligt, was wesentlich zur Festigung der Herrschaftsgewalt der SED beitrug. Die vorliegende Untersuchung analysiert Urteile des Obersten Gerichts im historisch-politischen Kontext und zeigt auf, dass die Urteilspraxis ausschließlich im Interesse parteipolitischer Ziele handelte und weder dem Volk noch der eigentlichen Rechtsfindung verpflichtet war. Des Weiteren wird der maßgebliche Beitrag des Obersten Gerichts an der schrittweisen Kriminalisierung der Bürger der DDR beleuchtet. Dies wirft ein kritisches Licht auf die Rolle des Rechtssystems bei der Sicherung von Rechtsstaatlichkeit und Menschenrechten in autoritären Regimen.
The dynamic landscape of digital transformation entails an impact on industrial-age manufacturing companies that goes beyond product offerings, changing operational paradigms, and requiring an organization-wide metamorphosis. An initiative to address the given challenges is the creation of Digital Innovation Units (DIUs) – departments or distinct legal entities that use new structures and practices to develop digital products, services, and business models and support or drive incumbents’ digital transformation. With more than 300 units in German-speaking countries alone and an increasing number of scientific publications, DIUs have become a widespread phenomenon in both research and practice.
This dissertation examines the evolution process of DIUs in the manufacturing
industry during their first three years of operation, through an extensive longitudinal single-case study and several cross-case syntheses of seven DIUs. Building on the lenses of organizational change and development, time, and socio-technical systems, this research provides insights into the fundamentals, temporal dynamics, socio-technical interactions, and relational dynamics of a DIU’s evolution process. Thus, the dissertation promotes a dynamic understanding of DIUs and adds a two-dimensional perspective to the often one-dimensional view of these units and their interactions with the main organization throughout the startup and growth phases of a DIU.
Furthermore, the dissertation constructs a phase model that depicts the early stages of DIU evolution based on these findings and by incorporating literature from information systems research. As a result, it illustrates the progressive intensification of collaboration between the DIU and the main organization. After being implemented, the DIU sparks initial collaboration and instigates change within (parts of) the main organization. Over time, it adapts to the corporate environment to some extent, responding to changing circumstances in order to contribute to long-term transformation. Temporally, the DIU drives the early phases of cooperation and adaptation in particular, while the main organization triggers the first major evolutionary step and realignment of the DIU.
Overall, the thesis identifies DIUs as malleable organizational structures that are crucial for digital transformation. Moreover, it provides guidance for practitioners on the process of building a new DIU from scratch or optimizing an existing one.
A comprehensive study on seismic hazard and earthquake triggering is crucial for effective mitigation of earthquake risks. The destructive nature of earthquakes motivates researchers to work on forecasting despite the apparent randomness of the earthquake occurrences. Understanding their underlying mechanisms and patterns is vital, given their potential for widespread devastation and loss of life. This thesis combines methodologies, including Coulomb stress calculations and aftershock analysis, to shed light on earthquake complexities, ultimately enhancing seismic hazard assessment.
The Coulomb failure stress (CFS) criterion is widely used to predict the spatial distributions of aftershocks following large earthquakes. However, uncertainties associated with CFS calculations arise from non-unique slip inversions and unknown fault networks, particularly due to the choice of the assumed aftershocks (receiver) mechanisms. Recent studies have proposed alternative stress quantities and deep neural network approaches as superior to CFS with predefined receiver mechanisms. To challenge these propositions, I utilized 289 slip inversions from the SRCMOD database to calculate more realistic CFS values for a layered-half space and variable receiver mechanisms. The analysis also investigates the impact of magnitude cutoff, grid size variation, and aftershock duration on the ranking of stress metrics using receiver operating characteristic (ROC) analysis. Results reveal the performance of stress metrics significantly improves after accounting for receiver variability and for larger aftershocks and shorter time periods, without altering the relative ranking of the different stress metrics.
To corroborate Coulomb stress calculations with the findings of earthquake source studies in more detail, I studied the source properties of the 2005 Kashmir earthquake and its aftershocks, aiming to unravel the seismotectonics of the NW Himalayan syntaxis. I simultaneously relocated the mainshock and its largest aftershocks using phase data, followed by a comprehensive analysis of Coulomb stress changes on the aftershock planes. By computing the Coulomb failure stress changes on the aftershock faults, I found that all large aftershocks lie in regions of positive stress change, indicating triggering by either co-seismic or post-seismic slip on the mainshock fault.
Finally, I investigated the relationship between mainshock-induced stress changes and associated seismicity parameters, in particular those of the frequency-magnitude (Gutenberg-Richter) distribution and the temporal aftershock decay (Omori-Utsu law). For that purpose, I used my global data set of 127 mainshock-aftershock sequences with the calculated Coulomb Stress (ΔCFS) and the alternative receiver-independent stress metrics in the vicinity of the mainshocks and analyzed the aftershocks properties depend on the stress values. Surprisingly, the results show a clear positive correlation between the Gutenberg-Richter b-value and induced stress, contrary to expectations from laboratory experiments. This observation highlights the significance of structural heterogeneity and strength variations in seismicity patterns. Furthermore, the study demonstrates that aftershock productivity increases nonlinearly with stress, while the Omori-Utsu parameters c and p systematically decrease with increasing stress changes. These partly unexpected findings have significant implications for future estimations of aftershock hazard.
The findings in this thesis provides valuable insights into earthquake triggering mechanisms by examining the relationship between stress changes and aftershock occurrence. The results contribute to improved understanding of earthquake behavior and can aid in the development of more accurate probabilistic-seismic hazard forecasts and risk reduction strategies.
This thesis presents a comprehensive exploration of the application of DNA origami nanofork antennas (DONAs) in the field of spectroscopy, with a particular focus on the structural analysis of Cytochrome C (CytC) at the single-molecule level. The research encapsulates the design, optimization, and application of DONAs in enhancing the sensitivity and specificity of Raman spectroscopy, thereby offering new insights into protein structures and interactions.
The initial phase of the study involved the meticulous optimization of DNA origami structures. This process was pivotal in developing nanoscale tools that could significantly enhance the capabilities of Raman spectroscopy. The optimized DNA origami nanoforks, in both dimer and aggregate forms, demonstrated an enhanced ability to detect and analyze molecular vibrations, contributing to a more nuanced understanding of protein dynamics.
A key aspect of this research was the comparative analysis between the dimer and aggregate forms of DONAs. This comparison revealed that while both configurations effectively identified oxidation and spin states of CytC, the aggregate form offered a broader range of detectable molecular states due to its prolonged signal emission and increased number of molecules. This extended duration of signal emission in the aggregates was attributed to the collective hotspot area, enhancing overall signal stability and sensitivity.
Furthermore, the study delved into the analysis of the Amide III band using the DONA system. Observations included a transient shift in the Amide III band's frequency, suggesting dynamic alterations in the secondary structure of CytC. These shifts, indicative of transitions between different protein structures, were crucial in understanding the protein’s functional mechanisms and interactions.
The research presented in this thesis not only contributes significantly to the field of spectroscopy but also illustrates the potential of interdisciplinary approaches in biosensing. The use of DNA origami-based systems in spectroscopy has opened new avenues for research, offering a detailed and comprehensive understanding of protein structures and interactions. The insights gained from this research are expected to have lasting implications in scientific fields ranging from drug development to the study of complex biochemical pathways. This thesis thus stands as a testament to the power of integrating nanotechnology, biochemistry, and spectroscopic techniques in addressing complex scientific questions.
Knowledge about causal structures is crucial for decision support in various domains. For example, in discrete manufacturing, identifying the root causes of failures and quality deviations that interrupt the highly automated production process requires causal structural knowledge. However, in practice, root cause analysis is usually built upon individual expert knowledge about associative relationships. But, "correlation does not imply causation", and misinterpreting associations often leads to incorrect conclusions. Recent developments in methods for causal discovery from observational data have opened the opportunity for a data-driven examination. Despite its potential for data-driven decision support, omnipresent challenges impede causal discovery in real-world scenarios. In this thesis, we make a threefold contribution to improving causal discovery in practice.
(1) The growing interest in causal discovery has led to a broad spectrum of methods with specific assumptions on the data and various implementations. Hence, application in practice requires careful consideration of existing methods, which becomes laborious when dealing with various parameters, assumptions, and implementations in different programming languages. Additionally, evaluation is challenging due to the lack of ground truth in practice and limited benchmark data that reflect real-world data characteristics.
To address these issues, we present a platform-independent modular pipeline for causal discovery and a ground truth framework for synthetic data generation that provides comprehensive evaluation opportunities, e.g., to examine the accuracy of causal discovery methods in case of inappropriate assumptions.
(2) Applying constraint-based methods for causal discovery requires selecting a conditional independence (CI) test, which is particularly challenging in mixed discrete-continuous data omnipresent in many real-world scenarios. In this context, inappropriate assumptions on the data or the commonly applied discretization of continuous variables reduce the accuracy of CI decisions, leading to incorrect causal structures.
Therefore, we contribute a non-parametric CI test leveraging k-nearest neighbors methods and prove its statistical validity and power in mixed discrete-continuous data, as well as the asymptotic consistency when used in constraint-based causal discovery. An extensive evaluation of synthetic and real-world data shows that the proposed CI test outperforms state-of-the-art approaches in the accuracy of CI testing and causal discovery, particularly in settings with low sample sizes.
(3) To show the applicability and opportunities of causal discovery in practice, we examine our contributions in real-world discrete manufacturing use cases. For example, we showcase how causal structural knowledge helps to understand unforeseen production downtimes or adds decision support in case of failures and quality deviations in automotive body shop assembly lines.
The mobile-immobile model (MIM) has been established in geoscience in the context of contaminant transport in groundwater. Here the tracer particles effectively immobilise, e.g., due to diffusion into dead-end pores or sorption. The main idea of the MIM is to split the total particle density into a mobile and an immobile density. Individual tracers switch between the mobile and immobile state following a two-state telegraph process, i.e., the residence times in each state are distributed exponentially. In geoscience the focus lies on the breakthrough curve (BTC), which is the concentration at a fixed location over time. We apply the MIM to biological experiments with a special focus on anomalous scaling regimes of the mean squared displacement (MSD) and non-Gaussian displacement distributions. As an exemplary system, we have analysed the motion of tau proteins, that diffuse freely inside axons of neurons. Their free diffusion thereby corresponds to the mobile state of the MIM. Tau proteins stochastically bind to microtubules, which effectively immobilises the tau proteins until they unbind and continue diffusing. Long immobilisation durations compared to the mobile durations give rise to distinct non-Gaussian Laplace shaped distributions. It is accompanied by a plateau in the MSD for initially mobile tracer particles at relevant intermediate timescales. An equilibrium fraction of initially mobile tracers gives rise to non-Gaussian displacements at intermediate timescales, while the MSD remains linear at all times. In another setting bio molecules diffuse in a biosensor and transiently bind to specific receptors, where advection becomes relevant in the mobile state. The plateau in the MSD observed for the advection-free setting and long immobilisation durations persists also for the case with advection. We find a new clear regime of anomalous diffusion with non-Gaussian distributions and a cubic scaling of the MSD. This regime emerges for initially mobile and for initially immobile tracers. For an equilibrium fraction of initially mobile tracers we observe an intermittent ballistic scaling of the MSD. The long-time effective diffusion coefficient is enhanced by advection, which we physically explain with the variance of mobile durations. Finally, we generalize the MIM to incorporate arbitrary immobilisation time distributions and focus on a Mittag-Leffler immobilisation time distribution with power-law tail ~ t^(-1-mu) with 0<mu<1 and diverging mean immobilisation durations. A fit of our model to the BTC of experimental data from tracer particles in aquifers matches the BTC including the power-law tail. We use the fit parameters for plotting the displacement distributions and the MSD. We find Gaussian normal diffusion at short times and long-time power-law decay of mobile mass accompanied by anomalous diffusion at long times. The long-time diffusion is subdiffusive in the advection-free setting, while it is either subdiffusive for 0<mu<1/2 or superdiffusive for 1/2<mu<1 when advection is present. In the long-time limit we show equivalence of our model to a bi-fractional diffusion equation.