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- sedimentation (1)
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- semiconducting polymer (1)
- sensitivity analysis (1)
- sentence comprehension (1)
- sentence processing (1)
- sequential learning (1)
- sexualization (1)
- shape-memory polymer (1)
- shoot apical meristem (1)
- siamese neural networks (1)
- silica (1)
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- silicate melts (1)
- silikatische Schmelzen (1)
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- simulated patients (1)
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- snowmelt (1)
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- spatial dependence (1)
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- synthesis (1)
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Institute
- Institut für Biochemie und Biologie (28)
- Institut für Physik und Astronomie (28)
- Institut für Geowissenschaften (24)
- Institut für Chemie (17)
- Hasso-Plattner-Institut für Digital Engineering GmbH (13)
- Institut für Ernährungswissenschaft (13)
- Institut für Umweltwissenschaften und Geographie (8)
- Department Psychologie (7)
- Extern (5)
- Fachgruppe Politik- & Verwaltungswissenschaft (5)
- Institut für Informatik und Computational Science (5)
- Institut für Mathematik (5)
- Wirtschaftswissenschaften (5)
- Department Sport- und Gesundheitswissenschaften (4)
- Department Linguistik (3)
- Institut für Jüdische Studien und Religionswissenschaft (3)
- Fachgruppe Betriebswirtschaftslehre (2)
- Department Grundschulpädagogik (1)
- Foundations of Computational Linguistics (1)
- Institut für Anglistik und Amerikanistik (1)
- Institut für Germanistik (1)
- Institut für Künste und Medien (1)
- Institut für Philosophie (1)
- Potsdam Institute for Climate Impact Research (PIK) e. V. (1)
- Psycholinguistics and Neurolinguistics (1)
- Sozialwissenschaften (1)
- Strukturbereich Kognitionswissenschaften (1)
- Öffentliches Recht (1)
Participation has become an orthodoxy in the field of development, an essential element of projects and programmes. This book analyses participation in development interventions as an institutionalised expectation – a rationalized myth – and examines how organisations on different levels of government process it. At least two different objectives of participation are appropriate and legitimate for international organisations in the field: the empowerment of local beneficiaries and the achievement of programme goals. Both integrate participatory forums into the organisational logic of development interventions. Local administrations react to the institutionalised expectation with means-ends decoupling, where participatory forums are implemented superficially but de facto remain marginalised in local administrative processes and activities. The book furthermore provides a thick description of the organisationality of participation in development interventions. Participatory forums are shown to be a form of partial organisation. They establish an order in the relationship between administrations and citizens through the introduction of rules and the creation of a defined membership. At the same time, this order is found to be fragile and subject to criticism and negotiation.
Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR.
In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid.
This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses.
The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies.
All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research.
As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations.
With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation.
Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly.
The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design.
As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation.
The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments.
This thesis focuses on the study of marked Gibbs point processes, in particular presenting some results on their existence and uniqueness, with ideas and techniques drawn from different areas of statistical mechanics: the entropy method from large deviations theory, cluster expansion and the Kirkwood--Salsburg equations, the Dobrushin contraction principle and disagreement percolation.
We first present an existence result for infinite-volume marked Gibbs point processes. More precisely, we use the so-called entropy method (and large-deviation tools) to construct marked Gibbs point processes in R^d under quite general assumptions. In particular, the random marks belong to a general normed space S and are not bounded. Moreover, we allow for interaction functionals that may be unbounded and whose range is finite but random. The entropy method relies on showing that a family of finite-volume Gibbs point processes belongs to sequentially compact entropy level sets, and is therefore tight.
We then present infinite-dimensional Langevin diffusions, that we put in interaction via a Gibbsian description. In this setting, we are able to adapt the general result above to show the existence of the associated infinite-volume measure. We also study its correlation functions via cluster expansion techniques, and obtain the uniqueness of the Gibbs process for all inverse temperatures β and activities z below a certain threshold. This method relies in first showing that the correlation functions of the process satisfy a so-called Ruelle bound, and then using it to solve a fixed point problem in an appropriate Banach space. The uniqueness domain we obtain consists then of the model parameters z and β for which such a problem has exactly one solution.
Finally, we explore further the question of uniqueness of infinite-volume Gibbs point processes on R^d, in the unmarked setting. We present, in the context of repulsive interactions with a hard-core component, a novel approach to uniqueness by applying the discrete Dobrushin criterion to the continuum framework. We first fix a discretisation parameter a>0 and then study the behaviour of the uniqueness domain as a goes to 0. With this technique we are able to obtain explicit thresholds for the parameters z and β, which we then compare to existing results coming from the different methods of cluster expansion and disagreement percolation.
Throughout this thesis, we illustrate our theoretical results with various examples both from classical statistical mechanics and stochastic geometry.
The spread of shrubs in Namibian savannas raises questions about the resilience of these ecosystems to global change. This makes it necessary to understand the past dynamics of the vegetation, since there is no consensus on whether shrub encroachment is a new phenomenon, nor on its main drivers. However, a lack of long-term vegetation datasets for the region and the scarcity of suitable palaeoecological archives, makes reconstructing past vegetation and land cover of the savannas a challenge.
To help meet this challenge, this study addresses three main research questions: 1) is pollen analysis a suitable tool to reflect the vegetation change associated with shrub encroachment in savanna environments? 2) Does the current encroached landscape correspond to an alternative stable state of savanna vegetation? 3) To what extent do pollen-based quantitative vegetation reconstructions reflect changes in past land cover?
The research focuses on north-central Namibia, where despite being the region most affected by shrub invasion, particularly since the 21st century, little is known about the dynamics of this phenomenon.
Field-based vegetation data were compared with modern pollen data to assess their correspondence in terms of composition and diversity along precipitation and grazing intensity gradients. In addition, two sediment cores from Lake Otjikoto were analysed to reveal changes in vegetation composition that have occurred in the region over the past 170 years and their possible drivers. For this, a multiproxy approach (fossil pollen, sedimentary ancient DNA (sedaDNA), biomarkers, compound specific carbon (δ13C) and deuterium (δD) isotopes, bulk carbon isotopes (δ13Corg), grain size, geochemical properties) was applied at high taxonomic and temporal resolution. REVEALS modelling of the fossil pollen record from Lake Otjikoto was run to quantitatively reconstruct past vegetation cover. For this, we first made pollen productivity estimates (PPE) of the most relevant savanna taxa in the region using the extended R-value model and two pollen dispersal options (Gaussian plume model and Lagrangian stochastic model). The REVEALS-based vegetation reconstruction was then validated using remote sensing-based regional vegetation data.
The results show that modern pollen reflects the composition of the vegetation well, but diversity less well. Interestingly, precipitation and grazing explain a significant amount of the compositional change in the pollen and vegetation spectra. The multiproxy record shows that a state change from open Combretum woodland to encroached Terminalia shrubland can occur over a century, and that the transition between states spans around 80 years and is characterized by a unique vegetation composition. This transition is supported by gradual environmental changes induced by management (i.e. broad-scale logging for the mining industry, selective grazing and reduced fire activity associated with intensified farming) and related land-use change. Derived environmental changes (i.e. reduced soil moisture, reduced grass cover, changes in species composition and competitiveness, reduced fire intensity) may have affected the resilience of Combretum open woodlands, making them more susceptible to change to an encroached state by stochastic events such as consecutive years of precipitation and drought, and by high concentrations of pCO2. We assume that the resulting encroached state was further stabilized by feedback mechanisms that favour the establishment and competitiveness of woody vegetation.
The REVEALS-based quantitative estimates of plant taxa indicate the predominance of a semi-open landscape throughout the 20th century and a reduction in grass cover below 50% since the 21st century associated with the spread of encroacher woody taxa. Cover estimates show a close match with regional vegetation data, providing support for the vegetation dynamics inferred from multiproxy analyses. Reasonable PPEs were made for all woody taxa, but not for Poaceae.
In conclusion, pollen analysis is a suitable tool to reconstruct past vegetation dynamics in savannas. However, because pollen cannot identify grasses beyond family level, a multiproxy approach, particularly the use of sedaDNA, is required. I was able to separate stable encroached states from mere woodland phases, and could identify drivers and speculate about related feedbacks. In addition, the REVEALS-based quantitative vegetation reconstruction clearly reflects the magnitude of the changes in the vegetation cover that occurred during the last 130 years, despite the limitations of some PPEs.
This research provides new insights into pollen-vegetation relationships in savannas and highlights the importance of multiproxy approaches when reconstructing past vegetation dynamics in semi-arid environments. It also provides the first time series with sufficient taxonomic resolution to show changes in vegetation composition during shrub encroachment, as well as the first quantitative reconstruction of past land cover in the region. These results help to identify the different stages in savanna dynamics and can be used to calibrate predictive models of vegetation change, which are highly relevant to land management.
In Systems Medicine, in addition to high-throughput molecular data (*omics), the wealth of clinical characterization plays a major role in the overall understanding of a disease. Unique problems and challenges arise from the heterogeneity of data and require new solutions to software and analysis methods. The SMART and EurValve studies establish a Systems Medicine approach to valvular heart disease -- the primary cause of subsequent heart failure.
With the aim to ascertain a holistic understanding, different *omics as well as the clinical picture of patients with aortic stenosis (AS) and mitral regurgitation (MR) are collected. Our task within the SMART consortium was to develop an IT platform for Systems Medicine as a basis for data storage, processing, and analysis as a prerequisite for collaborative research. Based on this platform, this thesis deals on the one hand with the transfer of the used Systems Biology methods to their use in the Systems Medicine context and on the other hand with the clinical and biomolecular differences of the two heart valve diseases. To advance differential expression/abundance (DE/DA) analysis software for use in Systems Medicine, we state 21 general software requirements and features of automated DE/DA software, including a novel concept for the simple formulation of experimental designs that can represent complex hypotheses, such as comparison of multiple experimental groups, and demonstrate our handling of the wealth of clinical data in two research applications DEAME and Eatomics. In user interviews, we show that novice users are empowered to formulate and test their multiple DE hypotheses based on clinical phenotype. Furthermore, we describe insights into users' general impression and expectation of the software's performance and show their intention to continue using the software for their work in the future. Both research applications cover most of the features of existing tools or even extend them, especially with respect to complex experimental designs. Eatomics is freely available to the research community as a user-friendly R Shiny application.
Eatomics continued to help drive the collaborative analysis and interpretation of the proteomic profile of 75 human left myocardial tissue samples from the SMART and EurValve studies. Here, we investigate molecular changes within the two most common types of valvular heart disease: aortic valve stenosis (AS) and mitral valve regurgitation (MR). Through DE/DA analyses, we explore shared and disease-specific protein alterations, particularly signatures that could only be found in the sex-stratified analysis. In addition, we relate changes in the myocardial proteome to parameters from clinical imaging. We find comparable cardiac hypertrophy but differences in ventricular size, the extent of fibrosis, and cardiac function. We find that AS and MR show many shared remodeling effects, the most prominent of which is an increase in the extracellular matrix and a decrease in metabolism. Both effects are stronger in AS. In muscle and cytoskeletal adaptations, we see a greater increase in mechanotransduction in AS and an increase in cortical cytoskeleton in MR. The decrease in proteostasis proteins is mainly attributable to the signature of female patients with AS. We also find relevant therapeutic targets.
In addition to the new findings, our work confirms several concepts from animal and heart failure studies by providing the largest collection of human tissue from in vivo collected biopsies to date. Our dataset contributing a resource for isoform-specific protein expression in two of the most common valvular heart diseases. Apart from the general proteomic landscape, we demonstrate the added value of the dataset by showing proteomic and transcriptomic evidence for increased expression of the SARS-CoV-2- receptor at pressure load but not at volume load in the left ventricle and also provide the basis of a newly developed metabolic model of the heart.
Iron-sulfur clusters are essential enzyme cofactors. The most common and stable clusters are [2Fe-2S] and [4Fe-4S] that are found in nature. They are involved in crucial biological processes like respiration, gene regulation, protein translation, replication and DNA repair in prokaryotes and eukaryotes. In Escherichia coli, Fe-S clusters are essential for molybdenum cofactor (Moco) biosynthesis, which is a ubiquitous and highly conserved pathway. The first step of Moco biosynthesis is catalyzed by the MoaA protein to produce cyclic pyranopterin monophosphate (cPMP) from 5’GTP. MoaA is a [4Fe-4S] cluster containing radical S-adenosyl-L-methionine (SAM) enzyme. The focus of this study was to investigate Fe-S cluster insertion into MoaA under nitrate and TMAO respiratory conditions using E. coli as a model organism. Nitrate and TMAO respiration usually occur under anaerobic conditions, where oxygen is depleted. Under these conditions, E. coli uses nitrate and TMAO as terminal electron. Previous studies revealed that Fe-S cluster insertion is performed by Fe-S cluster carrier proteins. In E. coli, these proteins are known as A-type carrier proteins (ATC) by phylogenomic and genetic studies. So far, three of them have been characterized in detail in E. coli, namely IscA, SufA, and ErpA. This study shows that ErpA and IscA are involved in Fe-S cluster insertion into MoaA under nitrate and TMAO respiratory conditions. ErpA and IscA can partially replace each other in their role to provide [4Fe-4S] clusters for MoaA. SufA is not able to replace the functions of IscA or ErpA under nitrate respiratory conditions.
Nitrate reductase is a molybdoenzyme that coordinates Moco and Fe-S clusters. Under nitrate respiratory conditions, the expression of nitrate reductase is significantly increased in E. coli. Nitrate reductase is encoded in narGHJI genes, the expression of which is regulated by the transcriptional regulator, fumarate and nitrate reduction (FNR). The activation of FNR under conditions of nitrate respiration requires one [4Fe-4S] cluster. In this part of the study, we analyzed the insertion of Fe-S cluster into FNR for the expression of narGHJI genes in E. coli. The results indicate that ErpA is essential for the FNR-dependent expression of the narGHJI genes, a role that can be replaced partially by IscA and SufA when they are produced sufficiently under the conditions tested. This observation suggests that ErpA is indirectly regulating nitrate reductase expression via inserting Fe-S clusters into FNR.
Most molybdoenzymes are complex multi-subunit and multi-cofactor-containing enzymes that coordinate Fe-S clusters, which are functioning as electron transfer chains for catalysis. In E. coli, periplasmic aldehyde oxidoreductase (PaoAC) is a heterotrimeric molybdoenzyme that
consists of flavin, two [2Fe-2S], one [4Fe-4S] cluster and Moco. In the last part of this study, we investigated the insertion of Fe-S clusters into E. coli periplasmic aldehyde oxidoreductase (PaoAC). The results show that SufA and ErpA are involved in inserting [4Fe-4S] and [2Fe-2S] clusters into PaoABC, respectively under aerobic respiratory conditions.
Gravitational-wave (GW) astrophysics is a field in full blossom. Since the landmark detection of GWs from a binary black hole on September 14th 2015, fifty-two compact-object binaries have been reported by the LIGO-Virgo collaboration. Such events carry astrophysical and cosmological information ranging from an understanding of how black holes and neutron stars are formed, what neutron stars are composed of, how the Universe expands, and allow testing general relativity in the highly-dynamical strong-field regime. It is the goal of GW astrophysics to extract such information as accurately as possible. Yet, this is only possible if the tools and technology used to detect and analyze GWs are advanced enough. A key aspect of GW searches are waveform models, which encapsulate our best predictions for the gravitational radiation under a certain set of parameters, and that need to be cross-correlated with data to extract GW signals. Waveforms must be very accurate to avoid missing important physics in the data, which might be the key to answer the fundamental questions of GW astrophysics. The continuous improvements of the current LIGO-Virgo detectors, the development of next-generation ground-based detectors such as the Einstein Telescope or the Cosmic Explorer, as well as the development of the Laser Interferometer Space Antenna (LISA), demand accurate waveform models. While available models are enough to capture the low spins, comparable-mass binaries routinely detected in LIGO-Virgo searches, those for sources from both current and next-generation ground-based and spaceborne detectors must be accurate enough to detect binaries with large spins and asymmetry in the masses. Moreover, the thousands of sources that we expect to detect with future detectors demand accurate waveforms to mitigate biases in the estimation of signals’ parameters due to the presence of a foreground of many sources that overlap in the frequency band. This is recognized as one of the biggest challenges for the analysis of future-detectors’ data, since biases might hinder the extraction of important astrophysical and cosmological information from future detectors’ data. In the first part of this thesis, we discuss how to improve waveform models for binaries with high spins and asymmetry in the masses. In the second, we present the first generic metrics that have been proposed to predict biases in the presence of a foreground of many overlapping signals in GW data.
For the first task, we will focus on several classes of analytical techniques. Current models for LIGO and Virgo studies are based on the post-Newtonian (PN, weak-field, small velocities) approximation that is most natural for the bound orbits that are routinely detected in GW searches. However, two other approximations have risen in prominence, the post-Minkowskian (PM, weak- field only) approximation natural for unbound (scattering) orbits and the small-mass-ratio (SMR) approximation typical of binaries in which the mass of one body is much bigger than the other. These are most appropriate to binaries with high asymmetry in the masses that challenge current waveform models. Moreover, they allow one to “cover” regions of the parameter space of coalescing binaries, thereby improving the interpolation (and faithfulness) of waveform models. The analytical approximations to the relativistic two-body problem can synergically be included within the effective-one-body (EOB) formalism, in which the two-body information from each approximation can be recast into an effective problem of a mass orbiting a deformed Schwarzschild (or Kerr) black hole. The hope is that the resultant models can cover both the low-spin comparable-mass binaries that are routinely detected, and the ones that challenge current models. The first part of this thesis is dedicated to a study about how to best incorporate information from the PN, PM, SMR and EOB approaches in a synergistic way. We also discuss how accurate the resulting waveforms are, as compared against numerical-relativity (NR) simulations. We begin by comparing PM models, whether alone or recast in the EOB framework, against PN models and NR simulations. We will show that PM information has the potential to improve currently-employed models for LIGO and Virgo, especially if recast within the EOB formalism. This is very important, as the PM approximation comes with a host of new computational techniques from particle physics to exploit. Then, we show how a combination of PM and SMR approximations can be employed to access previously-unknown PN orders, deriving the third subleading PN dynamics for spin-orbit and (aligned) spin1-spin2 couplings. Such new results can then be included in the EOB models currently used in GW searches and parameter estimation studies, thereby improving them when the binaries have high spins. Finally, we build an EOB model for quasi-circular nonspinning binaries based on the SMR approximation (rather than the PN one as usually done). We show how this is done in detail without incurring in the divergences that had affected previous attempts, and compare the resultant model against NR simulations. We find that the SMR approximation is an excellent approximation for all (quasi-circular nonspinning) binaries, including both the equal-mass binaries that are routinely detected in GW searches and the ones with highly asymmetric masses. In particular, the SMR-based models compare much better than the PN models, suggesting that SMR-informed EOB models might be the key to model binaries in the future. In the second task of this thesis, we work within the linear-signal ap- proximation and describe generic metrics to predict inference biases on the parameters of a GW source of interest in the presence of confusion noise from unfitted foregrounds and from residuals of other signals that have been incorrectly fitted out. We illustrate the formalism with simple (yet realistic) LISA sources, and demonstrate its validity against Monte-Carlo simulations. The metrics we describe pave the way for more realistic studies to quantify the biases with future ground-based and spaceborne detectors.
Magmatic continental rifts often constitute the earliest stage of nascent plate boundaries. These extensional tectonic provinces are characterized by ubiquitous normal faulting and volcanic activity; the spatial pattern, the geometry, and the age of these normal faults can help to unravel the spatiotemporal relationships between extensional deformation, magmatism, and long-wavelength crustal deformation of continental rift provinces. This study focuses on the active faulting in the Kenya Rift of the Cenozoic East African Rift System (EARS) with a focus on the mid-Pleistocene to the present-day.
To examine the early stages of continental break-up in the EARS, this thesis presents a time-averaged minimum extension rate for the inner graben of the Northern Kenya Rift (NKR) for the last 0.5 m.y. Using the TanDEM-X digital elevation model, fault-scarp geometries and associated throws are determined across the volcano-tectonic axis of the inner graben of the NKR. By integrating existing geochronology of faulted units with new ⁴⁰Ar/³⁹Ar radioisotopic dates, time-averaged extension rates are calculated. This study reveals that in the inner graben of the NKR, the long-term extension rate based on mid-Pleistocene to recent brittle deformation has minimum values of 1.0 to 1.6 mm yr⁻¹, locally with values up to 2.0 mm yr⁻¹. In light of virtually inactive border faults of the NKR, we show that extension is focused in the region of the active volcano-tectonic axis in the inner graben, thus highlighting the maturing of continental rifting in the NKR.
The phenomenon of focused extension is further investigated with a structural analysis of the youngest volcanic manifestations of the Kenya Rift, their relationship with extensional structures, and their overprint by Holocene faulting. In this context I analyzed the fault characteristics at the ~36 ka old Menengai Caldera and adjacent areas in the Central Kenya Rift using detailed field mapping and a structure-from-motion-based DEM generated from UAV data. In general, the Holocene intra-rift normal faults are dip-slip faults which strike NNE and thus reflect the present-day tectonic stress field; however, inside Menengai caldera persistent magmatic activity and magmatic resurgence overprints these young structures significantly. The caldera is located at the center of an actively extending rift segment and this and the other volcanic edifices of the Kenya Rift may constitute nucleation points of faulting an magmatic extensional processes that ultimately lead into a future stage of magma-assisted rifting.
When viewed at the scale of the entire Kenya Rift the protracted normal faulting in this region compartmentalizes the larger rift depressions, and influences the sedimentology and the hydrology of the intra-rift basins at a scale of less than 100 km. In the present day, most of the fault-bounded sub-basins of the Kenya Rift are hydrologically isolated due to this combination of faulting and magmatic activity that has generated efficient hydrological barriers that maintain these basins as semi-independent geomorphic entities. This isolation, however, was overcome during wetter climatic conditions during the past when the basins were transiently connected. I therefore also investigated the hydrological connectivity of the rift basins during the African Humid Period of the early Holocene, when climate was wetter. With the help of DEM analysis, lake-highstand indicators, radiocarbon dating, and a review of the fossil record, two lake-river-cascades could be identified: one directed southward, and one directed northward. Both cascades connected presently isolated rift basins during the early Holocene via spillovers of lakes and incised river gorges. This hydrological connection fostered the dispersal of aquatic faunas along the rift, and in addition, the water divide between the two river systems represented the only terrestrial dispersal corridor across the Kenya Rift. The reconstruction explains isolated distributions of Nilotic fish species in Kenya Rift lakes and of Guineo-Congolian mammal species in forests east of the Kenya Rift. On longer timescales, repeated episodes of connectivity and isolation must have occurred. To address this problem I participated in research to analyze a sediment drill core from the Koora basin of the Southern Kenya Rift, which provides a paleo-environmental record of the last 1 Ma. Based on this record it can be concluded that at ~400 ka relatively stable environmental conditions were disrupted by tectonic, hydrological, and ecological changes, resulting in increasingly large and frequent fluctuations in water availability, grassland communities, and woody plant cover. The major environmental shifts reflected in the drill core data coincide with phases where volcano-tectonic activity affected the basin. This thesis therefore shows how protracted extensional tectonic processes and the resulting geomorphologic conditions can affect the hydrology, the paleo-environment and the biodiversity of extensional zones in Kenya and elsewhere.
In the last decades, there was a notable progress in solving the well-known Boolean satisfiability (Sat) problem, which can be witnessed by powerful Sat solvers. One of the reasons why these solvers are so fast are structural properties of instances that are utilized by the solver’s interna. This thesis deals with the well-studied structural property treewidth, which measures the closeness of an instance to being a tree. In fact, there are many problems parameterized by treewidth that are solvable in polynomial time in the instance size when parameterized by treewidth.
In this work, we study advanced treewidth-based methods and tools for problems in knowledge representation and reasoning (KR). Thereby, we provide means to establish precise runtime results (upper bounds) for canonical problems relevant to KR. Then, we present a new type of problem reduction, which we call decomposition-guided (DG) that
allows us to precisely monitor the treewidth when reducing from one problem to another problem. This new reduction type will be the basis for a long-open lower bound result for quantified Boolean formulas and allows us to design a new methodology for establishing runtime lower bounds for problems parameterized by treewidth.
Finally, despite these lower bounds, we provide an efficient implementation of algorithms that adhere to treewidth. Our approach finds suitable abstractions of instances, which are subsequently refined in a recursive fashion, and it uses Sat solvers for solving subproblems. It turns out that our resulting solver is quite competitive for two canonical counting problems related to Sat.
Precipitation forecasting has an important place in everyday life – during the day we may have tens of small talks discussing the likelihood that it will rain this evening or weekend. Should you take an umbrella for a walk? Or should you invite your friends for a barbecue? It will certainly depend on what your weather application shows.
While for years people were guided by the precipitation forecasts issued for a particular region or city several times a day, the widespread availability of weather radars allowed us to obtain forecasts at much higher spatiotemporal resolution of minutes in time and hundreds of meters in space. Hence, radar-based precipitation nowcasting, that is, very-short-range forecasting (typically up to 1–3 h), has become an essential technique, also in various professional application contexts, e.g., early warning, sewage control, or agriculture.
There are two major components comprising a system for precipitation nowcasting: radar-based precipitation estimates, and models to extrapolate that precipitation to the imminent future. While acknowledging the fundamental importance of radar-based precipitation retrieval for precipitation nowcasts, this thesis focuses only on the model development: the establishment of open and competitive benchmark models, the investigation of the potential of deep learning, and the development of procedures for nowcast errors diagnosis and isolation that can guide model development.
The present landscape of computational models for precipitation nowcasting still struggles with the availability of open software implementations that could serve as benchmarks for measuring progress. Focusing on this gap, we have developed and extensively benchmarked a stack of models based on different optical flow algorithms for the tracking step and a set of parsimonious extrapolation procedures based on image warping and advection. We demonstrate that these models provide skillful predictions comparable with or even superior to state-of-the-art operational software. We distribute the corresponding set of models as a software library, rainymotion, which is written in the Python programming language and openly available at GitHub (https://github.com/hydrogo/rainymotion). That way, the library acts as a tool for providing fast, open, and transparent solutions that could serve as a benchmark for further model development and hypothesis testing.
One of the promising directions for model development is to challenge the potential of deep learning – a subfield of machine learning that refers to artificial neural networks with deep architectures, which may consist of many computational layers. Deep learning showed promising results in many fields of computer science, such as image and speech recognition, or natural language processing, where it started to dramatically outperform reference methods.
The high benefit of using "big data" for training is among the main reasons for that. Hence, the emerging interest in deep learning in atmospheric sciences is also caused and concerted with the increasing availability of data – both observational and model-based. The large archives of weather radar data provide a solid basis for investigation of deep learning potential in precipitation nowcasting: one year of national 5-min composites for Germany comprises around 85 billion data points.
To this aim, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. RainNet was trained to predict continuous precipitation intensities at a lead time of 5 min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900 km x 900 km and has a resolution of 1 km in space and 5 min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In these experiments, RainNet was applied recursively in order to achieve lead times of up to 1 h. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the previously developed rainymotion library.
RainNet significantly outperformed the benchmark models at all lead times up to 60 min for the routine verification metrics mean absolute error (MAE) and critical success index (CSI) at intensity thresholds of 0.125, 1, and 5 mm/h. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15 mm/h). The limited ability of RainNet to predict high rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5 min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16 km and below.
Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5 min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5 min, however, the increasing level of smoothing is a mere artifact – an analogue to numerical diffusion – that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research on model development for precipitation nowcasting, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance.
The model development together with the verification experiments for both conventional and deep learning model predictions also revealed the need to better understand the source of forecast errors. Understanding the dominant sources of error in specific situations should help in guiding further model improvement. The total error of a precipitation nowcast consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time. So far, verification measures did not allow to isolate the location error, making it difficult to specifically improve nowcast models with regard to location prediction.
To fill this gap, we introduced a framework to directly quantify the location error. To that end, we detect and track scale-invariant precipitation features (corners) in radar images. We then consider these observed tracks as the true reference in order to evaluate the performance (or, inversely, the error) of any model that aims to predict the future location of a precipitation feature. Hence, the location error of a forecast at any lead time ahead of the forecast time corresponds to the Euclidean distance between the observed and the predicted feature location at the corresponding lead time.
Based on this framework, we carried out a benchmarking case study using one year worth of weather radar composites of the DWD. We evaluated the performance of four extrapolation models, two of which are based on the linear extrapolation of corner motion; and the remaining two are based on the Dense Inverse Search (DIS) method: motion vectors obtained from DIS are used to predict feature locations by linear and Semi-Lagrangian extrapolation.
For all competing models, the mean location error exceeds a distance of 5 km after 60 min, and 10 km after 110 min. At least 25% of all forecasts exceed an error of 5 km after 50 min, and of 10 km after 90 min. Even for the best models in our experiment, at least 5 percent of the forecasts will have a location error of more than 10 km after 45 min. When we relate such errors to application scenarios that are typically suggested for precipitation nowcasting, e.g., early warning, it becomes obvious that location errors matter: the order of magnitude of these errors is about the same as the typical extent of a convective cell. Hence, the uncertainty of precipitation nowcasts at such length scales – just as a result of locational errors – can be substantial already at lead times of less than 1 h. Being able to quantify the location error should hence guide any model development that is targeted towards its minimization. To that aim, we also consider the high potential of using deep learning architectures specific to the assimilation of sequential (track) data.
Last but not least, the thesis demonstrates the benefits of a general movement towards open science for model development in the field of precipitation nowcasting. All the presented models and frameworks are distributed as open repositories, thus enhancing transparency and reproducibility of the methodological approach. Furthermore, they are readily available to be used for further research studies, as well as for practical applications.
Simultaneously speculative and inspired by everyday experiences, this volume develops an aesthetics of metabolism that offers a new perspective on the human-environment relation, one that is processual, relational, and not dependent on conscious thought. In art installations, design prototypes, and researchcreation projects that utilize air, light, or temperature to impact subjective experience the author finds aesthetic milieus that shift our awareness to the role of different sense modalities in aesthetic experience. Metabolic and atmospheric processes allow for an aesthetics besides and beyond the usually dominant visual sense.
Media artists have been struggling for financial survival ever since media art came into being. The non-material value of the artwork, a provocative attitude towards the traditional arts world and originally anti-capitalist mindset of the movement makes it particularly difficult to provide a constructive solution. However, a cultural entrepreneurial approach can be used to build a framework in order to find a balance between culture and business while ensuring that the cultural mission remains the top priority.
Fluids in the Earth's crust can move by creating and flowing through fractures, in a process called `hydraulic fracturing’. The tip-line of such fluid-filled fractures grows at locations where stress is larger than the strength of the rock. Where the tip stress vanishes, the fracture closes and the fluid-front retreats. If stress gradients exist on the fracture's walls, induced by fluid/rock density contrasts or topographic stresses, this results in an asymmetric shape and growth of the fracture, allowing for the contained batch of fluid to propagate through the crust.
The state-of-the-art analytical and numerical methods to simulate fluid-filled fracture propagation are two-dimensional (2D). In this work I extend these to three dimensions (3D). In my analytical method, I approximate the propagating 3D fracture as a penny-shaped crack that is influenced by both an internal pressure and stress gradients. In addition, I develop a numerical method to model propagation where curved fractures can be simulated as a mesh of triangular dislocations, with the displacement of faces computed using the displacement discontinuity method. I devise a rapid technique to approximate stress intensity and use this to calculate the advance of the tip-line. My 3D models can be applied to arbitrary stresses, topographic and crack shapes, whilst retaining short computation times.
I cross-validate my analytical and numerical methods and apply them to various natural and man-made settings, to gain additional insights into the movements of hydraulic fractures such as magmatic dikes and fluid injections in rock. In particular, I calculate the `volumetric tipping point’, which once exceeded allows a fluid-filled fracture to propagate in a `self-sustaining’ manner. I discuss implications this has for hydro-fracturing in industrial operations. I also present two studies combining physical models that define fluid-filled fracture trajectories and Bayesian statistical techniques. In these studies I show that the stress history of the volcanic edifice defines the location of eruptive vents at volcanoes. Retrieval of the ratio between topographic to remote stresses allows for forecasting of probable future vent locations. Finally, I address the mechanics of 3D propagating dykes and sills in volcanic regions. I focus on Sierra Negra volcano in the Gal\'apagos islands, where in 2018, a large sill propagated with an extremely curved trajectory. Using a 3D analysis, I find that shallow horizontal intrusions are highly sensitive to topographic and buoyancy stress gradients, as well as the effects of the free surface.
3D point clouds are a universal and discrete digital representation of three-dimensional objects and environments. For geospatial applications, 3D point clouds have become a fundamental type of raw data acquired and generated using various methods and techniques. In particular, 3D point clouds serve as raw data for creating digital twins of the built environment.
This thesis concentrates on the research and development of concepts, methods, and techniques for preprocessing, semantically enriching, analyzing, and visualizing 3D point clouds for applications around transport infrastructure. It introduces a collection of preprocessing techniques that aim to harmonize raw 3D point cloud data, such as point density reduction and scan profile detection. Metrics such as, e.g., local density, verticality, and planarity are calculated for later use. One of the key contributions tackles the problem of analyzing and deriving semantic information in 3D point clouds. Three different approaches are investigated: a geometric analysis, a machine learning approach operating on synthetically generated 2D images, and a machine learning approach operating on 3D point clouds without intermediate representation.
In the first application case, 2D image classification is applied and evaluated for mobile mapping data focusing on road networks to derive road marking vector data. The second application case investigates how 3D point clouds can be merged with ground-penetrating radar data for a combined visualization and to automatically identify atypical areas in the data. For example, the approach detects pavement regions with developing potholes. The third application case explores the combination of a 3D environment based on 3D point clouds with panoramic imagery to improve visual representation and the detection of 3D objects such as traffic signs.
The presented methods were implemented and tested based on software frameworks for 3D point clouds and 3D visualization. In particular, modules for metric computation, classification procedures, and visualization techniques were integrated into a modular pipeline-based C++ research framework for geospatial data processing, extended by Python machine learning scripts. All visualization and analysis techniques scale to large real-world datasets such as road networks of entire cities or railroad networks.
The thesis shows that some use cases allow taking advantage of established image vision methods to analyze images rendered from mobile mapping data efficiently. The two presented semantic classification methods working directly on 3D point clouds are use case independent and show similar overall accuracy when compared to each other. While the geometry-based method requires less computation time, the machine learning-based method supports arbitrary semantic classes but requires training the network with ground truth data. Both methods can be used in combination to gradually build this ground truth with manual corrections via a respective annotation tool.
This thesis contributes results for IT system engineering of applications, systems, and services that require spatial digital twins of transport infrastructure such as road networks and railroad networks based on 3D point clouds as raw data. It demonstrates the feasibility of fully automated data flows that map captured 3D point clouds to semantically classified models. This provides a key component for seamlessly integrated spatial digital twins in IT solutions that require up-to-date, object-based, and semantically enriched information about the built environment.
Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, thereby allowing mammals to maintain a constant body temperature in a cold environment. Thermogenic capacity of this tissue is due to a high mitochondrial density and expression of uncoupling protein 1 (UCP1), a unique brown adipocyte marker which dissipates the mitochondrial proton gradient to produce heat instead of ATP. BAT is actively involved in whole-body metabolic homeostasis and during aging there is a loss of classical brown adipose tissue with concomitantly reduced browning capacity of white adipose tissue. Therefore, an age-dependent decrease of BAT-related energy expenditure capacity may exacerbate the development of metabolic diseases, including obesity and type 2 diabetes mellitus. Given that direct effects of age-related changes of BAT-metabolic flux have yet to be unraveled, the aim of the current thesis is to investigate potential metabolic mechanisms involved in BAT-dysfunction during aging and to identify suitable metabolic candidates as functional biomarkers of BAT-aging. To this aim, integration of transcriptomic, metabolomic and proteomic data analyses of BAT from young and aged mice was performed, and a group of candidates with age-related changes was revealed. Metabolomic analysis showed age-dependent alterations of metabolic intermediates involved in energy, nucleotide and vitamin metabolism, with major alterations regarding the purine nucleotide pool. These data suggest a potential role of nucleotide intermediates in age-related BAT defects. In addition, the screening of transcriptomic and proteomic data sets from BAT of young and aged mice allowed identification of a 60-kDa lysophospholipase, also known as L-asparaginase (Aspg), whose expression declines during BAT-aging. Involvement of Aspg in brown adipocyte thermogenic function was subsequently analyzed at the molecular level using in vitro approaches and animal models. The findings revealed sensitivity of Aspg expression to β3-adrenergic activation via different metabolic cues, including cold exposure and treatment with β3-adrenergic agonist CL. To further examine ASPG function in BAT, an over-expression model of Aspg in a brown adipocyte cell line was established and showed that these cells were metabolically more active compared to controls, revealing increased expression of the main brown-adipocyte specific marker UCP1, as well as higher lipolysis rates. An in vitro loss-of-function model of Aspg was also functionally analyzed, revealing reduced brown adipogenic characteristics and an impaired lipolysis, thus confirming physiological relevance of Aspg in brown adipocyte function. Characterization of a transgenic mouse model with whole-body inactivation of the Aspg gene (Aspg-KO) allowed investigation of the role of ASPG under in vivo conditions, indicating a mild obesogenic phenotype, hypertrophic white adipocytes, impairment of the early thermogenic response upon cold-stimulation and dysfunctional insulin sensitivity. Taken together, these data show that ASPG may represent a new functional biomarker of BAT-aging that regulates thermogenesis and therefore a potential target for the treatment of age-related metabolic disease.
This project describes the nominal, verbal and ‘truncation’ systems of Awing and explains the syntactic and semantic functions of the multifunctional l<-><-> (LE) morpheme in copular and wh-focused constructions. Awing is a Bantu Grassfields language spoken in the North West region of Cameroon. The work begins with morphological processes viz. deverbals, compounding, reduplication, borrowing and a thorough presentation of the pronominal system and takes on verbal categories viz. tense, aspect, mood, verbal extensions, negation, adverbs and triggers of a homorganic N(asal)-prefix that attaches to the verb and other verbal categories. Awing grammar also has a very unusual phenomenon whereby nouns and verbs take long and short forms. A chapter entitled truncation is dedicated to the phenomenon. It is observed that the truncation process does not apply to bare singular NPs, proper names and nouns derived via morphological processes. On the other hand, with the exception of the 1st person non-emphatic possessive determiner and the class 7 noun prefix, nouns generally take the truncated form with modifiers (i.e., articles, demonstratives and other possessives). It is concluded that nominal truncation depicts movement within the DP system (Abney 1987). Truncation of the verb occurs in three contexts: a mass/plurality conspiracy (or lattice structuring in terms of Link 1983) between the verb and its internal argument (i.e., direct object); a means to align (exhaustive) focus (in terms of Fery’s 2013), and a means to form polar questions.
The second part of the work focuses on the role of the LE morpheme in copular and wh-focused clauses. Firstly, the syntax of the Awing copular clause is presented and it is shown that copular clauses in Awing have ‘subject-focus’ vs ‘topic-focus’ partitions and that the LE morpheme indirectly relates such functions. Semantically, it is shown that LE does not express contrast or exhaustivity in copular clauses. Turning to wh-constructions, the work adheres to Hamblin’s (1973) idea that the meaning of a question is the set of its possible answers and based on Rooth’s (1985) underspecified semantic notion of alternative focus, concludes that the LE morpheme is not a Focus Marker (FM) in Awing: LE does not generate or indicate the presence of alternatives (Krifka 2007); The LE morpheme can associate with wh-elements as a focus-sensitive operator with semantic import that operates on the focus alternatives by presupposing an exhaustive answer, among other notions. With focalized categories, the project further substantiates the claim in Fominyam & Šimík (2017), namely that exhaustivity is part of the semantics of the LE morpheme and not derived via contextual implicature, via a number of diagnostics. Hence, unlike in copular clauses, the LE morpheme with wh-focused categories is analysed as a morphological exponent of a functional head Exh corresponding to Horvath's (2010) EI (Exhaustive Identification). The work ends with the syntax of verb focus and negation and modifies the idea in Fominyam & Šimík (2017), namely that the focalized verb that associates with the exhaustive (LE) particle is a lower copy of the finite verb that has been moved to Agr. It is argued that the LE-focused verb ‘cluster’ is an instantiation of adjunction. The conclusion is that verb doubling with verb focus in Awing is neither a realization of two copies of one and the same verb (Fominyam and Šimík 2017), nor a result of a copy triggered by a focus marker (Aboh and Dyakonova 2009). Rather, the focalized copy is said to be merged directly as the complement of LE forming a type of adjoining cluster.
The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.
The characterization of exoplanets applying high-resolution transmission spectroscopy ini- tiated a new era making it possible to trace atmospheric signature at high altitudes in exoplanet atmospheres and to determine atmospheric properties which enrich our under- standing of the formation and evolution of the solar system. In contrast to what is observed in our solar system, where gaseous planets orbit at wide orbits, Jupiter type exoplanets were detected in foreign stellar systems surrounding their host stars within few days, in close orbits, the so called hot- and ultra-hot Jupiters. The most well studied ones are HD209458b and HD189733b, which are the first exoplanets where absorption is detected in their atmospheres, namely from the alkali line sodium. For hot Jupiters, the resonant alkali lines are the atmospheric species with one of the strongest absorption signatures, due to their large absorption cross-section. However, al- though the alkali lines sodium and potassium were detected in low-resolution observations for various giant exoplanets, potassium was absent in different high-resolution investiga- tions in contrast to sodium. The reason for this is quite puzzling, since both alkalis have very similar physical and chemical properties (e.g. condensation and ionization proper- ties). Obtaining high-resolution transit observations of HD189733b and HD209458b, we were able to detect potassium on HD189733b (Manuscript 1), which was the first high-resolution detection of potassium on an exoplanet. The absence of potassium on HD209458b could be reasoned by depletion processes, such as condensation or photo-ionization or high-altitude clouds. In a further study (Manuscript II), we resolved the potassium line and compared this to a previously detected sodium absorption on this planet. The comparison showed, that the potassium lines are either tracing different altitudes and temperatures compared to the sodium lines, or are depleted so that the planetary Na/K- ratio is way larger than the stellar one. A comparison of the alkali lines with synthetic line profiles showed that the sodium lines were much broader than the potassium lines, probably being induced by winds. To investigate this, the effect of zonal streaming winds on the sodium lines on Jupiter-type planets is investigated in a further study (Manuscript III), showing that such winds can significantly broaden the Na- lines and that high-resolution observations can trace such winds with different properties. Furthermore, investigating the Na-line observations for different exoplanets, I showed that the Na-line broadening follows a trend with cooler planets showing stronger line broadening and so hinting on stronger winds, matching well into theoretical predictions. Each presented manuscript depends on the re- sults published within the previous manuscript, yielding a unitary study of the exoplanet HD189733b. The investigation of the potassium absorption required to account for different effects: The telluric lines removal and the effect of center-to-limb variation (see Manuscript I), the residual Rossiter-Mc-Laughlin effect (see Manuscript II) and the broadening of spectral lines on a translucent atmospheric ring by zonal jet streams (see Manuscript III). This thesis shows that high-resolution transmission spectroscopy is a powerful tool to probe sharp alkali line absorption on giant exoplanet atmospheres and to investigate on the properties and dynamics of hot Jupiter type atmospheres.
While patients are known to respond differently to drug therapies, current clinical practice often still follows a standardized dosage regimen for all patients. For drugs with a narrow range of both effective and safe concentrations, this approach may lead to a high incidence of adverse events or subtherapeutic dosing in the presence of high patient variability. Model-informedprecision dosing (MIPD) is a quantitative approach towards dose individualization based on mathematical modeling of dose-response relationships integrating therapeutic drug/biomarker monitoring (TDM) data. MIPD may considerably improve the efficacy and safety of many drug therapies. Current MIPD approaches, however, rely either on pre-calculated dosing tables or on simple point predictions of the therapy outcome. These
approaches lack a quantification of uncertainties and the ability to account for effects that are delayed. In addition, the underlying models are not improved while applied to patient data. Therefore, current approaches are not well suited for informed clinical decision-making based on a differentiated understanding of the individually predicted therapy outcome.
The objective of this thesis is to develop mathematical approaches for MIPD, which (i) provide efficient fully Bayesian forecasting of the individual therapy outcome including associated uncertainties, (ii) integrate Markov decision processes via reinforcement learning (RL) for a comprehensive decision framework for dose individualization, (iii) allow for continuous learning across patients and hospitals. Cytotoxic anticancer chemotherapy with its major dose-limiting toxicity, neutropenia, serves as a therapeutically relevant application example.
For more comprehensive therapy forecasting, we apply Bayesian data assimilation (DA) approaches, integrating patient-specific TDM data into mathematical models of chemotherapy-induced neutropenia that build on prior population analyses. The value of uncertainty quantification is demonstrated as it allows reliable computation of the patient-specific probabilities of relevant clinical quantities, e.g., the neutropenia grade. In view of novel home monitoring devices that increase the amount of TDM data available, the data processing of
sequential DA methods proves to be more efficient and facilitates handling of the variability between dosing events.
By transferring concepts from DA and RL we develop novel approaches for MIPD. While DA-guided dosing integrates individualized uncertainties into dose selection, RL-guided dosing provides a framework to consider delayed effects of dose selections. The combined
DA-RL approach takes into account both aspects simultaneously and thus represents a holistic approach towards MIPD. Additionally, we show that RL can be used to gain insights into important patient characteristics for dose selection. The novel dosing strategies substantially reduce the occurrence of both subtherapeutic and life-threatening neutropenia grades in a simulation study based on a recent clinical study (CEPAC-TDM trial) compared to currently used MIPD approaches.
If MIPD is to be implemented in routine clinical practice, a certain model bias with respect to the underlying model is inevitable, as the models are typically based on data from comparably small clinical trials that reflect only to a limited extent the diversity in real-world patient populations. We propose a sequential hierarchical Bayesian inference framework that enables continuous cross-patient learning to learn the underlying model parameters of the target patient population. It is important to note that the approach only requires summary information of the individual patient data to update the model. This separation of the individual inference from population inference enables implementation across different centers of care.
The proposed approaches substantially improve current MIPD approaches, taking into account new trends in health care and aspects of practical applicability. They enable progress towards more informed clinical decision-making, ultimately increasing patient benefits beyond the current practice.
The presented study investigated the influence of microbial and biogeochemical processes on the physical transport related properties and the fate of microplastics in freshwater reservoirs. The overarching goal was to elucidate the mechanisms leading to sedimentation and deposition of microplastics in such environments. This is of importance, as large amounts of initially buoyant microplastics are found in reservoir sediments worldwide. However, the transport processes which lead to microplastics accumulation in sediments, were up to now understudied.
The impact of biofilm formation on the density and subsequent sedimentation of microplastics was investigated in the eutrophic Bautzen reservoirs (Chapter 2). Biofilms are complex microbial communities fixed to submerged surfaces through a slimy organic film. The mineral calcite was detected in the biofilms, which led to the
sinking of the overgrown microplastic particles. The calcite was of biogenic origin, most likely precipitated by sessile cyanobacteria within the biofilms.
Biofilm formation was also studied in the mesotrophic Malter reservoir. Unlike in Bautzen reservoir, biofilm formation did not govern the sedimentation of different microplastics in Malter reservoir (Chapter 3). Instead autumnal lake mixing led to
the formation of sinking aggregates of microplastics and iron colloids. Such colloids form when anoxic, iron-rich water from the hypolimnion mixes with the oxygenated epilimnetic waters. The colloids bind organic material from the lake water, which leads to the formation of large and sinking iron-organo flocs.
Hence, iron-organo floc formation and their influence on the buoyancy or burial of microplastics into sediments of Bautzen reservoir was studied in laboratory experiments (Chapter 4). Microplastics of different shapes (fiber, fragment, sphere) and sizes were readily incorporated into sinking iron-organo flocs. By this initially buoyant polyethylene microplastics were transported on top of sediments from Bautzen reservoir. Shortly after deposition, the microplastic bearing flocs started to subside and transported the pollutants into deeper sediment layers. The microplastics were not released from the sediments within two months of laboratory incubation.
The stability of floc microplastic deposition was further investigated employing experiments with the iron reducing model organism Shewanella oneidensis (Chapter 5). It was shown, that reduction or re-mineralization of the iron minerals did not affect the integrity of the iron-organo flocs. The organic matrix was stable under iron reducing conditions. Hence, no incorporated microplastics were released from the flocs. As similar processes are likely to take place in natural sediments, this might explain the previous described low microplastic release from the sediments.
This thesis introduced different mechanisms leading to the sedimentation of initially buoyant microplastics and to their subsequent deposition in freshwater reservoirs. Novel processes such as the aggregation with iron-organo flocs were identified and the understudied issue of biofilm densification through biogenic mineral formation was further investigated. The findings might have implications for the fate of microplastics within the river-reservoir system and outline the role of freshwater reservoirs as important accumulation zone for microplastics. Microplastics deposited in the sediments of reservoirs might not be transported further by through flowing river. Hence the study might contribute to better risk assessment and transport balances of these anthropogenic contaminants.
Boon and bane
(2021)
Semi-natural habitats (SNHs) in agricultural landscapes represent important refugia for biodiversity including organisms providing ecosystem services. Their spill-over into agricultural fields may lead to the provision of regulating ecosystem services such as biological pest control ultimately affecting agricultural yield. Still, it remains largely unexplored, how different habitat types and their distributions in the surrounding landscape shape this provision of ecosystem services within arable fields. Hence, in this thesis I investigated the effect of SNHs on biodiversity-driven ecosystem services and disservices affecting wheat production with an emphasis on the role and interplay of habitat type, distance to the habitat and landscape complexity.
I established transects from the field border into the wheat field, starting either from a field-to-field border, a hedgerow, or a kettle hole, and assessed beneficial and detrimental organisms and their ecosystem functions as well as wheat yield at several in-field distances. Using this study design, I conducted three studies where I aimed to relate the impacts of SNHs at the field and at the landscape scale on ecosystem service providers to crop production.
In the first study, I observed yield losses close to SNHs for all transect types. Woody habitats, such as hedgerows, reduced yields stronger than kettle holes, most likely due to shading from the tall vegetation structure. In order to find the biotic drivers of these yield losses close to SNHs, I measured pest infestation by selected wheat pests as potential ecosystem disservices to crop production in the second study. Besides relating their damage rates to wheat yield of experimental plots, I studied the effect of SNHs on these pest rates at the field and at the landscape scale. Only weed cover could be associated to yield losses, having their strongest impact on wheat yield close to the SNH. While fungal seed infection rates did not respond to SNHs, fungal leaf infection and herbivory rates of cereal leaf beetle larvae were positively influenced by kettle holes. The latter even increased at kettle holes with increasing landscape complexity suggesting a release of natural enemies at isolated habitats within the field interior.
In the third study, I found that also ecosystem service providers benefit from the presence of kettle holes. The distance to a SNH decreased species richness of ecosystem service providers, whereby the spatial range depended on species mobility, i.e. arable weeds diminished rapidly while carabids were less affected by the distance to a SNH. Contrarily, weed seed predation increased with distance suggesting that a higher food availability at field borders might have diluted the predation on experimental seeds. Intriguingly, responses to landscape complexity were rather mixed: While weed species richness was generally elevated with increasing landscape complexity, carabids followed a hump-shaped curve with highest species numbers and activity-density in simple landscapes. The latter might give a hint that carabids profit from a minimum endowment of SNHs, while a further increase impedes their mobility. Weed seed predation was affected differently by landscape complexity depending on weed species displayed. However, in habitat-rich landscapes seed predation of the different weed species converged to similar rates, emphasising that landscape complexity can stabilize the provision of ecosystem services. Lastly, I could relate a higher weed seed predation to an increase in wheat yield even though seed predation did not diminish weed cover. The exact mechanisms of the provision of weed control to crop production remain to be investigated in future studies.
In conclusion, I found habitat-specific responses of ecosystem (dis)service providers and their functions emphasizing the need to evaluate the effect of different habitat types on the provision of ecosystem services not only at the field scale, but also at the landscape scale. My findings confirm that besides identifying species richness of ecosystem (dis)service providers the assessment of their functions is indispensable to relate the actual delivery of ecosystem (dis)services to crop production.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
Cellulose is the most abundant biopolymer on Earth and cell wall (CW) synthesis is one of the major carbon consumers in the plant cell. Structure and several interaction partners of plasma membrane (PM)-bound cellulose synthase (CESA) complexes, CSCs, have been studied extensively, but much less is understood about the signals that activate and translocate CESAs to the PM and how exactly cellulose synthesis is being regulated during the diel cycle. The literature describes CSC regulation possibilities through interactions with accessory proteins upon stress conditions (e.g. CC1), post-translational modifications that regulate CSC speed and their possible anchoring in the PM (e.g. with phosphorylation and S-acylation, respectively). In this thesis, 13CO2 labeling and imaging techniques were employed in the same Arabidopsis seedling growth system to elucidate how and when new carbon is incorporated into cell wall (CW) sugars and UDP-glucose, and to follow CSC behavior during the diel cycle. Additionally, an ubiquitination analysis was performed to investigate a possible mechanism to affect CSC trafficking to and/or from the PM. Carbon is being incorporated into CW glucose at a 3-fold higher rate during the light period in comparison to the night in wild-type seedlings. Furthermore, CSC density at the PM, as an indication of active cellulose synthesizing machinery, is increasing in the light and falling during the night, showing that CW biosynthesis is more active in the light. Therefore, CW synthesis might be regulated by the carbon status of the cell. This regulation is broken in the starchless pgm mutant where light and dark carbon incorporation rates into CW glucose are similar, possibly due to the high soluble sugar content in pgm during the first part of the night. Strikingly, pgm CSC abundance at the PM is constantly low during the whole diel cycle, indicating little or no cellulose synthesis, but can be restored with exogenous sucrose or a longer photoperiod. Ubiquitination was explored as a possible regulating mechanism for translocation of primary CW CSCs from the PM and several potential ubiquitination sites have been identified.. The approach in this thesis enabled to study cellulose/CW synthesis from different angles but in the same growth system, allowing direct comparison of those methodologies, which could help understand the relationship between the amount of available carbon in a plant cell and the cells capacity to synthesize cellulose/CW. Understanding which factors contribute to cellulose synthesis regulation and addressing those fundamental questions can provide essential knowledge to manage the need for increased crop production.
The energy required to drive photochemical reactions is derived from charge separation across the thylakoid membrane. As the consequence of difference in proton concentration between chloroplasts stroma and thylakoid lumen, a proton motive force (pmf) is generated. The pmf is composed out of the proton gradient (ΔpH) and membrane potential (ΔΨ), and together they drive the ATP synthesis. In nature, the amount of energy fueling photosynthesis varies due to frequent changes in the light intensity. Thylakoid ion transport can adapt the energy flow through a photosynthetic apparatus to the light availability by adjusting the pmf composition. Dissipation of ΔΨ reduces the charge recombination at the photosystem II, allowing for an increase in ΔpH component to trigger a feedback downregulation of photosynthesis. K+ Exchange Antiporter 3 (KEA3) driven K+/H+ antiport reduces the ΔpH fraction of pmf, thereby dampening a non-photochemical quenching (NPQ). As a result, it increases the photosynthesis efficiency during the transition to lower light intensity. This thesis aimed to find the answers for questions concerning KEA3 activity regulation and its role in plant development. Presented data shows that in plants lacking chloroplast ATP synthase assembly factor CGL160 with decreased ATP synthase activity, KEA3 has a pivotal role in photosynthesis regulation and plant growth during steady-state conditions. Lack of KEA3 in cgl160 mutant results in a strong growth impairment, as photosynthesis is limited due to increased pH-dependent NPQ and decreased electron flow through cytochrome b6f complex. Overexpression of KEA3 in cgl160 mutant increases charge recombination at photosystem II, promoting photosynthesis. Thus, during periods of low ATP synthase activity, plants benefit from KEA3 activity. The KEA3 undergoes dimerization via its regulatory C-terminus (RCT). The RCT responds to changes in light intensity as the plants expressing KEA3 without this domain show reduced photo-protective mechanism in light intensity transients. However, those plants fix more carbon during the photosynthesis induction phase as a trade-off for a long-term photoprotection, showing KEA3 regulatory role in plant development. The KEA3 RCT is facing thylakoid stroma, thus its regulation depends on light-induced changes in the stromal environment. KEA3 activity regulation overlaps with the stromal pH changes occurring during light fluctuations. The ATP and ADP has shown to have an affinity towards heterologously expressed KEA3 RCT. Such interaction causes conformational changes in RCT structure. The fold change of RCT-ligand interaction depends on the environmental pH value. With a combination of bioinformatics and in vitro approach, the ATP binding site at RCT was located. Introduction of binding site point mutation in planta KEA3 RCT resulted in antiporter activity deregulation during transition to low light. Together, the data presented in this thesis allowed us to assess more broadly a KEA3 role in photosynthesis adjustment and propose the models of KEA3 activity regulation throughout transition in light intensity.
Many children struggle with reading for comprehension. Reading is a complex cognitive task depending on various sub-tasks, such as word decoding and building connections across sentences. The task of connecting sentences is guided by referential expressions. References, such as anaphoric noun phrases (Minky/the cat) or pronouns (Minky/she), signal to the reader how the protagonists of adjacent sentences are connected. Readers construct a coherent mental model of the text by resolving these references. Personal pronouns (he/she) in particular need to be resolved towards an appropriate antecedent before they can be fully understood. Pronoun resolution therefore is vital for successful text comprehension. The present thesis investigated children’s resolution of personal pronouns during natural reading as a possible source of reading comprehension difficulty. Three eye tracking studies investigated whether children aged 8-9 (Grade 3-4) resolve pronouns online during reading and how the varying information around the pronoun region influences children’s eye movement behavior.
The first study investigated whether children prefer a pronoun over a noun phrase when the antecedent is highly accessible. Children read three-sentence stories that introduced a protagonist (Mia) in the first sentence and a reference to this protagonist in one of the following sentences using either a repeated name (Mia) or a pronoun (she). For proficient readers, it was repeatedly shown that there is a preference for a pronoun over the name in these contexts, i.e., when the antecedent is salient. The first study tested the repeated name penalty effect in children using eye tracking. It was hypothesized that in contrast to proficient readers, the fluency of children’s reading processing profits from an overlapping word form (i.e., the repeated noun phrase) compared to a pronoun. This is because overlapping word forms allow for direct mapping, whereas pronouns have to be resolved towards their antecedent first.
The second study investigated children’s online processing of pronominal gender in a mismatch paradigm. Children read sentences in which the pronoun either was a gender-match to the antecedent or a gender-mismatch. Reading skill and reading fluency were also tested and related to children’s ability to detect a mismatching pronoun during reading.
The third study investigated the online processing of gender information on the pronoun and whether disambiguating gender information improves the accuracy of pronoun comprehension. Offline comprehension accuracy, that is the comprehension of the pronoun, was related to children’s online eye movement behavior. This study was conducted in a semi-longitudinal paradigm: 70 children were tested in Grade 3 (age 8) and again in Grade 4 (age 9) to investigate effects of age and reading skill on pronoun processing and comprehension.
The results of this thesis clearly show that children aged 8-9, when they are in the second half of primary school, struggle with the comprehension of pronouns in reading tasks. The responses to pronoun comprehension questions revealed that children have difficulties with the comprehension of a pronoun in the absence of a disambiguating gender cue, that is when they have to apply context information. When there is a gender cue to disambiguate the pronoun, children’s accuracy improves significantly. This is true for children in Grade 3, but also in Grade 4, albeit their overall resolution accuracy slightly improves with age.
The results from the analyses of eye movements suggest that the discourse accessibility of an antecedent does play a role in children’s processing of pronouns and repeated names. The repetition of a name does not facilitate children’s reading processing like it was anticipated. Similar to adults, children showed a penalty effect for the repeated name where a pronoun is expected. However, this does not mean that children’s processing of pronouns is always adult-like. The results from eye movement analyses in the pronoun region during sentence reading revealed significant individual differences related to children’s individual reading skill and reading fluency.
The results from the mismatch study revealed that reading fluency is associated with children’s detection of incongruent pronouns. All children had longer gaze durations at mismatching than matching pronouns, but only fluent readers among the children followed this up with a regression out of the pronoun region. This was interpreted as an attempt to gain processing time and “repair” the inconsistency. Reading fluency was therefore associated with detection of the mismatch, while less fluent readers did not see any mismatch between pronoun and antecedent. The eye movement pattern of the “detectors” is more adult-like and was interpreted as reflecting successful monitoring and attempted pronoun resolution.
Children differ considerably in their reading comprehension skill. The results of this thesis show that only skilled readers among the children use gender information online for pronoun resolution. They took more time to read the pronoun when there was disambiguating gender information that was useful to resolve the pronoun, in contrast to the less skilled readers. Age was a less important factor in pronoun resolution processes and comprehension than were reading skill and reading fluency. Taken together, this suggests that the good readers direct cognitive resources towards pronoun resolution when the pronoun can be resolved, which is a successful comprehension strategy. Moreover, there was evidence that reading skill is a relevant factor in this task but not age.
The contribution of the present thesis is a depiction of the specific eye movement patterns that are related to successful and unsuccessful attempts at pronoun resolution in children. Eye movement behavior in the pronoun area is related to children’s reading skill and fluency. The results of this thesis suggest that many children do not resolve pronouns spontaneously during sentence reading, which is likely detrimental to their reading comprehension in more complex reading materials. The present thesis informs our understanding of the challenge that pronoun resolution poses for beginning readers, and gives new impulses for the study of higher-order reading processes in children’s natural reading.
Active Galactic Nuclei (AGN) are considered to be the main powering source of active galaxies, where central Super Massive Black Holes (SMBHs), with masses between 106 and 109 M⊙ gravitationally pull the surrounding material via accre- tion. AGN phenomenon expands over a very wide range of luminosities, from the most luminous high-redshift quasars (QSOs), to the local Low-Luminosity AGN (LLAGN), with significantly weaker luminosities. While "typical" luminous AGNs distinguish themselves by their characteristical blue featureless continuum, the Broad Emission Lines (BELs) with Full Widths at Half Maximum (FWHM) in order of few thousands km s1, arising from the so-called Broad Line Region (BLR), and strong radio and/or X-ray emission, detection of LLAGNs on the other hand is quite chal- lenging due to their extremely weak emission lines, and absence of the power-law continuum. In order to fully understand AGN evolution and their duty-cycles across cosmic history, we need a proper knowledge of AGN phenomenon at all luminosi- ties and redshifts, as well as perspectives from different wavelength bands.
In this thesis I present a search for AGN signatures in central spectra of 542 local (0.005 < z < 0.03) galaxies from the Calar Alto Legacy Integral Field Area (CALIFA) survey. The adopted aperture of 3′′ × 3′′ corresponds to central ∼ 100 − 500 pc for the redshift range of CALIFA. Using the standard emission-line ratio diagnostic diagrams, we initially classified all CALIFA emission-line galaxies (526) into star- forming, LINER-like, Seyfert 2 and intermediates. We further detected signatures of the broad Hα component in 89 spectra from the sample, of which more than 60% are present in the central spectra of LINER-like galaxies. These BELs are very weak, with luminosities in range 1038 − 1041 erg s−1, but with FWHMs between 1000 km s−1 and 6000 km s−1, comparable to those of luminous high-z AGN. This result implies that type 1 AGN are in fact quite frequent in the local Universe. We also identified additional 29 Seyfert 2 galaxies using the emission-line ratio diagnostic diagrams.
Using the MBH − σ∗ correlation, we estimated black hole masses of 55 type 1 AGN from CALIFA, a sample for which we had estimates of bulge stellar velocity dispersions σ∗. We compared these masses to the ones that we estimated from the virial method and found large discrepancies. We analyzed the validity of both meth- ods for black hole mass estimation of local LLAGN, and concluded that most likely virial scaling relations can no longer be applied as a valid MBH estimator in such low-luminosity regime. These black holes accrete at very low rate, having Edding- ton ratios in range 4.1 × 10−5 − 2.4 × 10−3. Detection of BELs with such low lumi- nosities and at such low Eddington rates implies that these LLAGN are still able to form the BLR, although with probably modified structure of the central engine.
In order to obtain full picture of black hole growth across cosmic time, it is es- sential that we study them in different stages of their activity. For that purpose, we estimated the broad AGN Luminosity Function (AGNLF) of our entire type 1 AGN sample using the 1/Vmax method. The shape of AGNLF indicates an apparent flattening below luminosities LHα ∼ 1039 erg s−1. Correspondingly we estimated ac- tive Black Hole Mass Function (BHMF) and Eddington Ration Distribution Function (ERDF) for a sub-sample of type 1 AGN for which we have MBH and λ estimates. The flattening is also present in both BHMF and ERDF, around log(MBH) ∼ 7.7 and log(λ) < 3, respectively. We estimated the fraction of active SMBHs in CALIFA by comparing our active BHMF to the one of the local quiescent SMBHs. The shape of
the active fraction which decreases with increasing MBH, as well as the flattening of AGNLF, BHMF and ERDF is consistent with scenario of AGN cosmic downsizing.
To complete AGN census in the CALIFA galaxy sample, it is necessary to search for them in various wavelength bands. For the purpose of completing the census we performed cross-correlations between all 542 CALIFA galaxies and multiwavelength surveys, Swift – BAT 105 month catalogue (in hard 15 - 195 keV X-ray band), and NRAO VLA Sky Survey (NVSS, in 1.4 GHz radio domain). This added 1 new AGN candidate in X-ray, and 7 in radio wavelength band to our local LLAGN count.
It is possible to detect AGN emission signatures within 10 – 20 kpc outside of the central galactic regions. This may happen when the central AGN has recently switched off and the photoionized material is spread across the galaxy within the light-travel-time, or the photoionized material is blown away from the nucleus by outflows. In order to detect these extended AGN regions we constructed spatially resolved emission-line ratio diagnostic diagrams of all emission-line galaxies from the CALIFA, and found 1 new object that was previously not identified as AGN.
Obtaining the complete AGN census in CALIFA, with five different AGN types, showed that LLAGN contribute a significant fraction of 24% of the emission-line galaxies in the CALIFA sample. This result implies that AGN are quite common in the local Universe, and although being in very low activity stage, they contribute to large fraction of all local SMBHs. Within this thesis we approached the upper limit of AGN fraction in the local Universe and gained some deeper understanding of the LLAGN phenomenon.
One third of the world's population lives in areas where earthquakes causing at least slight damage are frequently expected. Thus, the development and testing of global seismicity models is essential to improving seismic hazard estimates and earthquake-preparedness protocols for effective disaster-risk mitigation. Currently, the availability and quality of geodetic data along plate-boundary regions provides the opportunity to construct global models of plate motion and strain rate, which can be translated into global maps of forecasted seismicity. Moreover, the broad coverage of existing earthquake catalogs facilitates in present-day the calibration and testing of global seismicity models. As a result, modern global seismicity models can integrate two independent factors necessary for physics-based, long-term earthquake forecasting, namely interseismic crustal strain accumulation and sudden lithospheric stress release.
In this dissertation, I present the construction of and testing results for two global ensemble seismicity models, aimed at providing mean rates of shallow (0-70 km) earthquake activity for seismic hazard assessment. These models depend on the Subduction Megathrust Earthquake Rate Forecast (SMERF2), a stationary seismicity approach for subduction zones, based on the conservation of moment principle and the use of regional "geodesy-to-seismicity" parameters, such as corner magnitudes, seismogenic thicknesses and subduction dip angles. Specifically, this interface-earthquake model combines geodetic strain rates with instrumentally-recorded seismicity to compute long-term rates of seismic and geodetic moment. Based on this, I derive analytical solutions for seismic coupling and earthquake activity, which provide this earthquake model with the initial abilities to properly forecast interface seismicity. Then, I integrate SMERF2 interface-seismicity estimates with earthquake computations in non-subduction zones provided by the Seismic Hazard Inferred From Tectonics based on the second iteration of the Global Strain Rate Map seismicity approach to construct the global Tectonic Earthquake Activity Model (TEAM). Thus, TEAM is designed to reduce number, and potentially spatial, earthquake inconsistencies of its predecessor tectonic earthquake model during the 2015-2017 period. Also, I combine this new geodetic-based earthquake approach with a global smoothed-seismicity model to create the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) model. This updated hybrid model serves as an alternative earthquake-rate approach to the Global Earthquake Activity Rate model for forecasting long-term rates of shallow seismicity everywhere on Earth.
Global seismicity models provide scientific hypotheses about when and where earthquakes may occur, and how big they might be. Nonetheless, the veracity of these hypotheses can only be either confirmed or rejected after prospective forecast evaluation. Therefore, I finally test the consistency and relative performance of these global seismicity models with independent observations recorded during the 2014-2019 pseudo-prospective evaluation period. As a result, hybrid earthquake models based on both geodesy and seismicity are the most informative seismicity models during the testing time frame, as they obtain higher information scores than their constituent model components. These results support the combination of interseismic strain measurements with earthquake-catalog data for improved seismicity modeling. However, further prospective evaluations are required to more accurately describe the capacities of these global ensemble seismicity models to forecast longer-term earthquake activity.
The business problem of having inefficient processes, imprecise process analyses, and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating, and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS), and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes.
In my doctoral thesis, I examine continuous gravity measurements for monitoring of the geothermal site at Þeistareykir in North Iceland. With the help of high-precision superconducting gravity meters (iGravs), I investigate underground mass changes that are caused by operation of the geothermal power plant (i.e. by extraction of hot water and reinjection of cold water). The overall goal of this research project is to make a statement about the sustainable use of the geothermal reservoir, from which also the Icelandic energy supplier and power plant operator Landsvirkjun should benefit.
As a first step, for investigating the performance and measurement stability of the gravity meters, in summer 2017, I performed comparative measurements at the gravimetric observatory J9 in Strasbourg. From the three-month gravity time series, I examined calibration, noise and drift behaviour of the iGravs in comparison to stable long-term time series of the observatory superconducting gravity meters. After preparatory work in Iceland (setup of gravity stations, additional measuring equipment and infrastructure, discussions with Landsvirkjun and meetings with the Icelandic partner institute ISOR), gravity monitoring at Þeistareykir was started in December 2017. With the help of the iGrav records of the initial 18 months after start of measurements, I carried out the same investigations (on calibration, noise and drift behaviour) as in J9 to understand how the transport of the superconducting gravity meters to Iceland may influence instrumental parameters.
In the further course of this work, I focus on modelling and reduction of local gravity contributions at Þeistareykir. These comprise additional mass changes due to rain, snowfall and vertical surface displacements that superimpose onto the geothermal signal of the gravity measurements. For this purpose, I used data sets from additional monitoring sensors that are installed at each gravity station and adapted scripts for hydro-gravitational modelling. The third part of my thesis targets geothermal signals in the gravity measurements.
Together with my PhD colleague Nolwenn Portier from France, I carried out additional gravity measurements with a Scintrex CG5 gravity meter at 26 measuring points within the geothermal field in the summers of 2017, 2018 and 2019. These annual time-lapse gravity measurements are intended to increase the spatial coverage of gravity data from the three continuous monitoring stations to the entire geothermal field. The combination of CG5 and iGrav observations, as well as annual reference measurements with an FG5 absolute gravity meter represent the hybrid gravimetric monitoring method for Þeistareykir. Comparison of the gravimetric data to local borehole measurements (of groundwater levels, geothermal extraction and injection rates) is used to relate the observed gravity changes to the actually extracted (and reinjected) geothermal fluids. An approach to explain the observed gravity signals by means of forward modelling of the geothermal production rate is presented at the end of the third (hybrid gravimetric) study. Further modelling with the help of the processed gravity data is planned by Landsvirkjun. In addition, the experience from time-lapse and continuous gravity monitoring will be used for future gravity measurements at the Krafla geothermal field 22 km south-east of Þeistareykir.
Contributions to the theoretical analysis of the algorithms with adversarial and dependent data
(2021)
In this work I present the concentration inequalities of Bernstein's type for the norms of Banach-valued random sums under a general functional weak-dependency assumption (the so-called $\cC-$mixing). The latter is then used to prove, in the asymptotic framework, excess risk upper bounds of the regularised Hilbert valued statistical learning rules under the τ-mixing assumption on the underlying training sample. These results (of the batch statistical setting) are then supplemented with the regret analysis over the classes of Sobolev balls of the type of kernel ridge regression algorithm in the setting of online nonparametric regression with arbitrary data sequences. Here, in particular, a question of robustness of the kernel-based forecaster is investigated. Afterwards, in the framework of sequential learning, the multi-armed bandit problem under $\cC-$mixing assumption on the arm's outputs is considered and the complete regret analysis of a version of Improved UCB algorithm is given. Lastly, probabilistic inequalities of the first part are extended to the case of deviations (both of Azuma-Hoeffding's and of Burkholder's type) to the partial sums of real-valued weakly dependent random fields (under the type of projective dependence condition).
The development and optimization of carbonaceous materials is of great interest for several applications including gas sorption, electrochemical storage and conversion, or heterogeneous catalysis. In this thesis, the exploration and optimization of nitrogen containing carbonaceous materials by direct condensation of smart chosen, molecular precursors will be presented. As suggested with the concept of noble carbons, the choice of a stable, nitrogen-containing precursor will lead to an even more stable, nitrogen doped carbonaceous material with a controlled structure and electronic properties. Molecules fulfilling this requirement are for example nucleobases. The direct condensation of nucleobases leads to highly nitrogen containing carbonaceous materials without any further post or pretreatment. By using salt melt templating, pore structure adjustment is possible without the use of hazardous or toxic reagents and the template can be reused.
Using these simple tools, the synergetic effect of the pore structure and nitrogen content of the materials can be explored. Within this thesis, the influence of the condensation parameters will be correlated to the structure and performance of the materials. First, the influence of the condensation temperature to the porosity and nitrogen content of guanine will be discussed and the exploration of highly CO2 selective structural pores in C1N1 materials will be shown. Further tuning the pore structure of the materials by salt melt templating will be then explored, the potential of the prepared materials as heterogeneous catalysts and their basic catalytic strength will be correlated to their nitrogen content and pore morphology. A similar approach is used to explore the water sorption behavior of uric acid derived carbonaceous materials as potential sorbents for heat transformation applications. Changes in maximum water uptake and hydrophilicity of the prepared materials will be correlated to the nitrogen content and pore architecture. Due to the high thermal stability, porosity, and nitrogen content of ionic liquid derived nitrogen doped carbonaceous materials, a simple impregnation and calcination route can be conducted to obtain copper nano cluster decorated nitrogen-doped carbonaceous materials. The activity as catalyst for the oxygen reduction reaction of the obtained materials will be shown and structure performance relations are discussed.
In conclusion, the versatility of nitrogen doped carbonaceous materials with a nitrogen to carbon ratio of up to one will be shown. The possibility to tune the pore structure as well as the nitrogen content by using a simple procedure including salt melt templating as well as the use of molecular precursors and their effect on the performance will be discussed.
Anthropogenic climate change alters the hydrological cycle. While certain areas experience more intense precipitation events, others will experience droughts and increased evaporation, affecting water storage in long-term reservoirs, groundwater, snow, and glaciers. High elevation environments are especially vulnerable to climate change, which will impact the water supply for people living downstream. The Himalaya has been identified as a particularly vulnerable system, with nearly one billion people depending on the runoff in this system as their main water resource. As such, a more refined understanding of spatial and temporal changes in the water cycle in high altitude systems is essential to assess variations in water budgets under different climate change scenarios.
However, not only anthropogenic influences have an impact on the hydrological cycle, but changes to the hydrological cycle can occur over geological timescales, which are connected to the interplay between orogenic uplift and climate change. However, their temporal evolution and causes are often difficult to constrain. Using proxies that reflect hydrological changes with an increase in elevation, we can unravel the history of orogenic uplift in mountain ranges and its effect on the climate.
In this thesis, stable isotope ratios (expressed as δ2H and δ18O values) of meteoric waters and organic material are combined as tracers of atmospheric and hydrologic processes with remote sensing products to better understand water sources in the Himalayas. In addition, the record of modern climatological conditions based on the compound specific stable isotopes of leaf waxes (δ2Hwax) and brGDGTs (branched Glycerol dialkyl glycerol tetraethers) in modern soils in four Himalayan river catchments was assessed as proxies of the paleoclimate and (paleo-) elevation. Ultimately, hydrological variations over geological timescales were examined using δ13C and δ18O values of soil carbonates and bulk organic matter originating from sedimentological sections from the pre-Siwalik and Siwalik groups to track the response of vegetation and monsoon intensity and seasonality on a timescale of 20 Myr.
I find that Rayleigh distillation, with an ISM moisture source, mainly controls the isotopic composition of surface waters in the studied Himalayan catchments. An increase in d-excess in the spring, verified by remote sensing data products, shows the significant impact of runoff from snow-covered and glaciated areas on the surface water isotopic values in the timeseries.
In addition, I show that biomarker records such as brGDGTs and δ2Hwax have the potential to record (paleo-) elevation by yielding a significant correlation with the temperature and surface water δ2H values, respectively, as well as with elevation. Comparing the elevation inferred from both brGDGT and δ2Hwax, large differences were found in arid sections of the elevation transects due to an additional effect of evapotranspiration on δ2Hwax. A combined study of these proxies can improve paleoelevation estimates and provide recommendations based on the results found in this study.
Ultimately, I infer that the expansion of C4 vegetation between 20 and 1 Myr was not solely dependent on atmospheric pCO2, but also on regional changes in aridity and seasonality from to the stable isotopic signature of the two sedimentary sections in the Himalaya (east and west).
This thesis shows that the stable isotope chemistry of surface waters can be applied as a tool to monitor the changing Himalayan water budget under projected increasing temperatures. Minimizing the uncertainties associated with the paleo-elevation reconstructions were assessed by the combination of organic proxies (δ2Hwax and brGDGTs) in Himalayan soil. Stable isotope ratios in bulk soil and soil carbonates showed the evolution of vegetation influenced by the monsoon during the late Miocene, proving that these proxies can be used to record monsoon intensity, seasonality, and the response of vegetation. In conclusion, the use of organic proxies and stable isotope chemistry in the Himalayas has proven to successfully record changes in climate with increasing elevation. The combination of δ2Hwax and brGDGTs as a new proxy provides a more refined understanding of (paleo-)elevation and the influence of climate.
The controlled dosage of substances from a device to its environment, such as a tissue or an organ in medical applications or a reactor, room, machinery or ecosystem in technical, should ideally match the requirements of the applications, e.g. in terms of the time point at which the cargo is released. On-demand dosage systems may enable such a desired release pattern, if the device contain suitable features that can translate external signals into a release function. This study is motivated by the opportunities arising from microsystems capable of an on-demand release and the contributions that geometrical design may have in realizing such features. The goals of this work included the design, fabrication, characterization and experimental proof-of-concept of geometry-assisted triggerable dosing effect (a) with a sequential dosing release and (b) in a self-sufficient dosage system. Structure-function relationships were addressed on the molecular, morphological and, with a particular attention, the device design level, which is on the micrometer scale. Models and/or computational tools were used to screen the parameter space and provide guidance for experiments.
Botulinum neurotoxin (BoNT) is produced by the anaerobic bacterium Clostridium botulinum. It is one of the most potent toxins found in nature and can enter motor neurons (MN) to cleave proteins necessary for neurotransmission, resulting in flaccid paralysis. The toxin has applications in both traditional and esthetic medicine. Since BoNT activity varies between batches despite identical protein concentrations, the activity of each lot must be assessed. The gold standard method is the mouse lethality assay, in which mice are injected with a BoNT dilution series to determine the dose at which half of the animals suffer death from peripheral asphyxia. Ethical concerns surrounding the use of animals in toxicity testing necessitate the creation of alternative model systems to measure the potency of BoNT.
Prerequisites of a successful model are that it is human specific; it monitors the complete toxic pathway of BoNT; and it is highly sensitive, at least in the range of the mouse lethality assay. One model system was developed by our group, in which human SIMA neuroblastoma cells were genetically modified to express a reporter protein (GLuc), which is packaged into neurosecretory vesicles, and which, upon cellular depolarization, can be released – or inhibited by BoNT – simultaneously with neurotransmitters. This assay has great potential, but includes the inherent disadvantages that the GLuc sequence was randomly inserted into the genome and the tumor cells only have limited sensitivity and specificity to BoNT. This project aims to improve these deficits, whereby induced pluripotent stem cells (iPSCs) were genetically modified by the CRISPR/Cas9 method to insert the GLuc sequence into the AAVS1 genomic safe harbor locus, precluding genetic disruption through non-specific integrations. Furthermore, GLuc was modified to associate with signal peptides that direct to the lumen of both large dense core vesicles (LDCV), which transport neuropeptides, and synaptic vesicles (SV), which package neurotransmitters. Finally, the modified iPSCs were differentiated into motor neurons (MNs), the true physiological target of BoNT, and hypothetically the most sensitive and specific cells available for the MoN-Light BoNT assay.
iPSCs were transfected to incorporate one of three constructs to direct GLuc into LDCVs, one construct to direct GLuc into SVs, and one “no tag” GLuc control construct. The LDCV constructs fused GLuc with the signal peptides for proopiomelanocortin (hPOMC-GLuc), chromogranin-A (CgA-GLuc), and secretogranin II (SgII-GLuc), which are all proteins found in the LDCV lumen. The SV construct comprises a VAMP2-GLuc fusion sequence, exploiting the SV membrane-associated protein synaptobrevin (VAMP2). The no tag GLuc expresses GLuc non-specifically throughout the cell and was created to compare the localization of vesicle-directed GLuc.
The clones were characterized to ensure that the GLuc sequence was only incorporated into the AAVS1 safe harbor locus and that the signal peptides directed GLuc to the correct vesicles. The accurate insertion of GLuc was confirmed by PCR with primers flanking the AAVS1 safe harbor locus, capable of simultaneously amplifying wildtype and modified alleles. The PCR amplicons, along with an insert-specific amplicon from candidate clones were Sanger sequenced to confirm the correct genomic region and sequence of the inserted DNA. Off-target integrations were analyzed with the newly developed dc-qcnPCR method, whereby the insert DNA was quantified by qPCR against autosomal and sex-chromosome encoded genes. While the majority of clones had off-target inserts, at least one on-target clone was identified for each construct.
Finally, immunofluorescence was utilized to localize GLuc in the selected clones. In iPSCs, the vesicle-directed GLuc should travel through the Golgi apparatus along the neurosecretory pathway, while the no tag GLuc should not follow this pathway. Initial analyses excluded the CgA-GLuc and SgII-GLuc clones due to poor quality protein visualization. The colocalization of GLuc with the Golgi was analyzed by confocal microscopy and quantified. GLuc was strongly colocalized with the Golgi in the hPOMC-GLuc clone (r = 0.85±0.09), moderately in the VAMP2-GLuc clone (r = 0.65±0.01), and, as expected, only weakly in the no tag GLuc clone (r = 0.44±0.10). Confocal microscopy of differentiated MNs was used to analyze the colocalization of GLuc with proteins associated with LDCVs and SVs, SgII in the hPOMC-GLuc clone (r = 0.85±0.08) and synaptophysin in the VAMP2-GLuc clone (r = 0.65±0.07). GLuc was also expressed in the same cells as the MN-associated protein, Islet1.
A significant portion of GLuc was found in the correct cell type and compartment. However, in the MoN-Light BoNT assay, the hPOMC-GLuc clone could not be provoked to reliably release GLuc upon cellular depolarization. The depolarization protocol for hPOMC-GLuc must be further optimized to produce reliable and specific release of GLuc upon exposure to a stimulus. On the other hand, the VAMP2-GLuc clone could be provoked to release GLuc upon exposure to the muscarinic and nicotinic agonist carbachol. Furthermore, upon simultaneous exposure to the calcium chelator EGTA, the carbachol-provoked release of GLuc could be significantly repressed, indicating the detection of GLuc was likely associated with vesicular fusion at the presynaptic terminal. The application of the VAMP2-GLuc clone in the MoN-Light BoNT assay must still be verified, but the results thus far indicate that this clone could be appropriate for the application of BoNT toxicity assessment.
Mycotoxins are secondary metabolites produced by several filamentous fungal species, thus occurring ubiquitously in the environment and food. While the heterogeneous group shows differences in their bioavailability and toxicity, the low-molecular-weight xenobiotics are capable of impacting human and animal health acutely and chronically. Therefore, maximum levels for the major mycotoxins in food and feed are regulated in the current European legislation. Besides free mycotoxins, naturally occurring modified mycotoxins are gaining more attention in recent years. Modified mycotoxins constitute toxins altered by plants, microorganisms, and living organisms in different metabolic pathways or food processing steps. The toxicological relevant compounds often co-occur with their free forms in infested food and feed. Thus, the toxins may contribute to the overall toxicity of mycotoxins, wherefore their presence and toxicity should be considered in risk assessment. Until now, however, there are no regulated limits for modified mycotoxins within the European Union. In this thesis, rapid, sensitive, and robust methods for the analysis of mycotoxins and their modified forms were developed and validated using state-of-the-art high performance liquid chromatography tandem mass spectrometry (LC-MS/MS) systems. Firstly, two analytical methods for determining 38 mycotoxins in cereals and 41 mycotoxins in beer were established since agricultural products count as the primary source of mycotoxin contamination. For the analysis of cereal samples, a QuEChERS- based extraction approach was pursued, while analytes from beer samples were extracted using an acetonitrile precipitation scheme. Validation in cereals, namely wheat, corn, rice, and barley, as well as in beer, demonstrated satisfactory results. To obtain information regarding the natural occurrence of mycotoxins in food products, the developed methods were applied to the analysis of several commercial samples partly produced worldwide. The Fusarium toxins deoxynivalenol and its conjugated metabolite deoxynivalenol-3-glucoside turned out to be the most abundant toxins. None of the other modified mycotoxins were quantified in the samples. However, one cereal sample showed traces of zearalenone- 14-sulfate below the limit of quantification. Moreover, pesticides, plant growth regulators, and tropane alkaloids were investigated in this thesis. Pesticides present biologically highly effective compounds applied in the environment to protect humans from the hazardous effects of pests. While plant growth regulators show similar functions, mainly improving agricultural production, tropane alkaloids are naturally occurring secondary metabolites mainly in the species of Solanaceae that may pose unintended poisoning of humans. The third part of the present thesis aimed to analyze cereal-relevant compounds simultaneously, wherefore a multi-method for the analysis of (modified) mycotoxins, pesticides, plant growth regulators, and tropane alkaloids was established. After processing the samples, this should be done in a single extraction step with subsequent one-time measurements. Various sample preparation procedures were compared, whereby an approach based on an acidified acetonitrile/water extraction, followed by an online clean-up, was finally chosen. The simultaneous determination of more than 350 analytes required an analytical tool that offered an increased resolving power, represented as an enhanced peak capacity, and the possibility of analyzing a broad polarity range. Thus, a two-dimensional LC-MS/MS system based on two different separation mechanisms that performed orthogonal to one another was used for the analysis. Validation of the developed method revealed good performance characteristics for most analytes, while subsequent application showed that 86% of the samples were contaminated with at least one compound. In summary, this thesis provides novel insights into the analysis of food-relevant (modified) mycotoxins. Different sample preparation and LC-MS/MS approaches were introduced, resulting in the development of three new analytical methods. For the first time, such a high number of modified mycotoxins was included in multi-mycotoxin methods and a multi-method ranging both contaminants and residues. Although first steps towards the analysis of modified mycotoxins have been made, further research is needed to elucidate their (co-) occurrence and toxicological behavior in order to understand their relevance to human health in the future.
Digital inclusion
(2021)
In this thesis, we tackle two social disruptions: recent refugee waves in Germany and the COVID-19 pandemic. We focus on the use of information and communication technology (ICT) as a key means of alleviating these disruptions and promoting social inclusion. As social disruptions typically lead to frustration and fragmentation, it is essential to ensure the social inclusion of individuals and societies during such times.
In the context of the social inclusion of refugees, we focus on the Syrian refugees who arrived in Germany as of 2015, as they form a large and coherent refugee community. In particular, we address the role of ICTs in refugees’ social inclusion and investigate how different ICTs (especially smartphones and social networks) can foster refugees’ integration and social inclusion. In the context of the COVID-19 pandemic, we focus on the widespread unconventional working model of work from home (WFH). Our research here centers on the main constructs of WFH and the key differences in WFH experiences based on personal characteristics such as gender and parental status.
We reveal novel insights through four well-established research methods: literature review, mixed methods, qualitative method, and quantitative method. The results of our research have been published in the form of eight articles in major information systems venues and journals. Key results from the refugee research stream include the following: Smartphones represent a central component of refugee ICT use; refugees view ICT as a source of information and power; the social connectedness of refugees is strongly correlated with their Internet use; refugees are not relying solely on traditional methods to learn the German language or pursue further education; the ability to use smartphones anytime and anywhere gives refugees an empowering feeling of global connectedness; and ICTs empower refugees on three levels (community participation, sense of control, and self-efficacy).
Key insights from the COVID-19 WFH stream include: Gender and the presence of children under the age of 18 affect workers’ control over their time, technology usefulness, and WFH conflicts, while not affecting their WFH attitudes; and both personal and technology-related factors affect an individual’s attitude toward WFH and their productivity. Further insights are being gathered at the time of submitting this thesis.
This thesis contributes to the discussion within the information systems community regarding how to use different ICT solutions to promote the social inclusion of refugees in their new communities and foster an inclusive society. It also adds to the growing body of research on COVID-19, in particular on the sudden workplace transformation to WFH. The insights gathered in this thesis reveal theoretical implications and future opportunities for research in the field of information systems, practical implications for relevant stakeholders, and social implications related to the refugee crisis and the COVID-19 pandemic that must be addressed.
Digital surveillance fiction
(2021)
One of the key challenges in modern Facility Management (FM) is to digitally reflect the current state of the built environment, referred to as-is or as-built versus as-designed representation. While the use of Building Information Modeling (BIM) can address the issue of digital representation, the generation and maintenance of BIM data requires a considerable amount of manual work and domain expertise. Another key challenge is being able to monitor the current state of the built environment, which is used to provide feedback and enhance decision making. The need for an integrated solution for all data associated with the operational life cycle of a building is becoming more pronounced as practices from Industry 4.0 are currently being evaluated and adopted for FM use. This research presents an approach for digital representation of indoor environments in their current state within the life cycle of a given building. Such an approach requires the fusion of various sources of digital data. The key to solving such a complex issue of digital data integration, processing and representation is with the use of a Digital Twin (DT). A DT is a digital duplicate of the physical environment, states, and processes. A DT fuses as-designed and as-built digital representations of built environment with as-is data, typically in the form of floorplans, point clouds and BIMs, with additional information layers pertaining to the current and predicted states of an indoor environment or a complete building (e.g., sensor data). The design, implementation and initial testing of prototypical DT software services for indoor environments is presented and described. These DT software services are implemented within a service-oriented paradigm, and their feasibility is presented through functioning and tested key software components within prototypical Service-Oriented System (SOS) implementations. The main outcome of this research shows that key data related to the built environment can be semantically enriched and combined to enable digital representations of indoor environments, based on the concept of a DT. Furthermore, the outcomes of this research show that digital data, related to FM and Architecture, Construction, Engineering, Owner and Occupant (AECOO) activity, can be combined, analyzed and visualized in real-time using a service-oriented approach. This has great potential to benefit decision making related to Operation and Maintenance (O&M) procedures within the scope of the post-construction life cycle stages of typical office buildings.
Selfsustained oscillations are some of the most commonly observed phenomena in biological systems. They emanate from non-linear systems in a heterogeneous environment and can be described by the theory of dynamical systems. Part of this theory considers reduced models of the oscillator dynamics by means of amplitudes and a phase variable. Such variables are highly attractive for theoretical and experimental studies. Theoretically these variables correspond to an integrable linearization of the generally non-linear system. Experimentally, there exist well established approaches to extract phases from oscillator signals. Notably, one can define phase models also for networks of oscillators. One highly active field examines effects of non-local coupling among oscillators, which is thought to play a key role in networks with strong coupling. The dissertation introduces and expands the knowledge about high-order phase coupling in networks of oscillators. Mathematical calculations consider the Stuart-Landau oscillator. A novel phase estimation scheme for direct observations of an oscillator dynamics is introduced based on numerics. A numerical study of high-order phase coupling applies a Fourier fit for the Stuart-Landau and for the van-der-Pol oscillator. The numerical approach is finally tested on observation-based phase estimates of the Morris-Lecar neuron. A popular approach for the construction of phases from signals is based on phase demodulation by means of the Hilbert transform. Generally, observations of oscillations contain a small and generic variation of their amplitude. The work presents a way to quantify how much the variations of signal amplitude spoil a phase demodulation procedure. For the ideal case of phase modulated signals, amplitude modulations vanish. However, the Hilbert transform produces artificial variations of the reconstructed amplitude even in this case. The work proposes a novel procedure called Iterative Hilbert Transform Embedding to obtain an optimal demodulation of signals. The text presents numerous examples and tests of application for the method, covering multicomponent signals, observables of highly stable limit cycle oscillations and noisy phase dynamics. The numerical results are supported by a spectral theory of convergence for weak phase modulations.
Eukaryotic cells can be regarded as complex microreactors capable of performing various biochemical reactions in parallel which are necessary to sustain life. An essential prerequisite for these complex metabolic reactions to occur is the evolution of lipid membrane-bound organelles enabling compartmental- ization of reactions and biomolecules. This allows for a spatiotemporal control over the metabolic reactions within the cellular system. Intracellular organi- zation arising due to compartmentalization is a key feature of all living cells and has inspired synthetic biologists to engineer such systems with bottom-up approaches.
Artificial cells provide an ideal platform to isolate and study specific re- actions without the interference from the complex network of biomolecules present in biological cells. To mimic the hierarchical architecture of eukaryotic cells, multi-compartment assemblies with nested liposomal structures also re- ferred to as multi-vesicular vesicles (MVVs) have been widely adopted. Most of the previously reported multi-compartment systems adopt bulk method- ologies which suffer from low yield and poor control over size. Microfluidic strategies help circumvent these issues and facilitate a high-throughput and robust technique to assemble MVVs of uniform size distribution.
In this thesis, firstly, the bulk methodologies are explored to build MVVs and implement a synthetic signalling cascade. Next, a polydimethylsiloxane (PDMS)-based microfluidic platform is introduced to build MVVs and the significance of PEGylated lipids for the successful encapsulation of inner com- partments to generate stable multi-compartment systems is highlighted.
Next, a novel two-inlet channel PDMS-based microfluidic device to create MVVs encompassing a three-step enzymatic reaction cascade is presented. A directed reaction pathway comprising of the enzymes α-glucosidase (α-Glc), glucose oxidase (GOx), and horseradish peroxidase (HRP) spanning across three compartments via reconstitution of size-selective membrane proteins is described. Furthermore, owing to the monodispersity of our MVVs due to microfluidic strategies, this platform is employed to study the effect of com- partmentalization on reaction kinetics.
Further integration of cell-free expression module into the MVVs would allow for gene-mediated signal transduction within artificial eukaryotic cells. Therefore, the chemically inducible cell-free expression of a membrane protein alpha-hemolysin and its further reconstitution into liposomes is carried out.
In conclusion, the present thesis aims to build artificial eukaryotic cells to achieve size-selective chemical communication that also show potential for applications as micro reactors and as vehicles for drug delivery.
Discriminative Models for Biometric Identification using Micro- and Macro-Movements of the Eyes
(2021)
Human visual perception is an active process. Eye movements either alternate between fixations and saccades or follow a smooth pursuit movement in case of moving targets. Besides these macroscopic gaze patterns, the eyes perform involuntary micro-movements during fixations which are commonly categorized into micro-saccades, drift and tremor. Eye movements are frequently studied in cognitive psychology, because they reflect a complex interplay of perception, attention and oculomotor control.
A common insight of psychological research is that macro-movements are highly individual. Inspired by this finding, there has been a considerable amount of prior research on oculomotoric biometric identification. However, the accuracy of known approaches is too low and the time needed for identification is too long for any practical application. This thesis explores discriminative models for the task of biometric identification.
Discriminative models optimize a quality measure of the predictions and are usually superior to generative approaches in discriminative tasks. However, using discriminative models requires to select a suitable form of data representation for sequential eye gaze data; i.e., by engineering features or constructing a sequence kernel and the performance of the classification model strongly depends on the data representation. We study two fundamentally different ways of representing eye gaze within a discriminative framework. In the first part of this thesis, we explore the integration of data and psychological background knowledge in the form of generative models to construct representations. To this end, we first develop generative statistical models of gaze behavior during reading and scene viewing that account for viewer-specific distributional properties of gaze patterns. In a second step, we develop a discriminative identification model by deriving Fisher kernel functions from these and several baseline models. We find that an SVM with Fisher kernel is able to reliably identify users based on their eye gaze during reading and scene viewing. However, since the generative models are constrained to use low-frequency macro-movements, they discard a significant amount of information contained in the raw eye tracking signal at a high cost: identification requires about one minute of input recording, which makes it inapplicable for real world biometric systems. In the second part of this thesis, we study a purely data-driven modeling approach. Here, we aim at automatically discovering the individual pattern hidden in the raw eye tracking signal. To this end, we develop a deep convolutional neural network DeepEyedentification that processes yaw and pitch gaze velocities and learns a representation end-to-end. Compared to prior work, this model increases the identification accuracy by one order of magnitude and the time to identification decreases to only seconds. The DeepEyedentificationLive model further improves upon the identification performance by processing binocular input and it also detects presentation-attacks.
We find that by learning a representation, the performance of oculomotoric identification and presentation-attack detection can be driven close to practical relevance for biometric applications. Eye tracking devices with high sampling frequency and precision are expensive and the applicability of eye movement as a biometric feature heavily depends on cost of recording devices.
In the last part of this thesis, we therefore study the requirements on data quality by evaluating the performance of the DeepEyedentificationLive network under reduced spatial and temporal resolution. We find that the method still attains a high identification accuracy at a temporal resolution of only 250 Hz and a precision of 0.03 degrees. Reducing both does not have an additive deteriorating effect.
Generative adversarial networks (GANs) have been broadly applied to a wide range of application domains since their proposal. In this thesis, we propose several methods that aim to tackle different existing problems in GANs. Particularly, even though GANs are generally able to generate high-quality samples, the diversity of the generated set is often sub-optimal. Moreover, the common increase of the number of models in the original GANs framework, as well as their architectural sizes, introduces additional costs. Additionally, even though challenging, the proper evaluation of a generated set is an important direction to ultimately improve the generation process in GANs. We start by introducing two diversification methods that extend the original GANs framework to multiple adversaries to stimulate sample diversity in a generated set. Then, we introduce a new post-training compression method based on Monte Carlo methods and importance sampling to quantize and prune the weights and activations of pre-trained neural networks without any additional training. The previous method may be used to reduce the memory and computational costs introduced by increasing the number of models in the original GANs framework. Moreover, we use a similar procedure to quantize and prune gradients during training, which also reduces the communication costs between different workers in a distributed training setting. We introduce several topology-based evaluation methods to assess data generation in different settings, namely image generation and language generation. Our methods retrieve both single-valued and double-valued metrics, which, given a real set, may be used to broadly assess a generated set or separately evaluate sample quality and sample diversity, respectively. Moreover, two of our metrics use locality-sensitive hashing to accurately assess the generated sets of highly compressed GANs. The analysis of the compression effects in GANs paves the way for their efficient employment in real-world applications. Given their general applicability, the methods proposed in this thesis may be extended beyond the context of GANs. Hence, they may be generally applied to enhance existing neural networks and, in particular, generative frameworks.
There is a general consensus that diverse ecological communities are better equipped to adapt to changes in their environment, but our understanding of the mechanisms by which they do so remains incomplete. Accurately predicting how the global biodiversity crisis affects the functioning of ecosystems, and the services they provide, requires extensive knowledge about these mechanisms.
Mathematical models of food webs have been successful in uncovering many aspects of the link between diversity and ecosystem functioning in small food web modules, containing at most two adaptive trophic levels. Meaningful extrapolation of this understanding to the functioning of natural food webs remains difficult, due to the presence of complex interactions that are not always accurately captured by bitrophic descriptions of food webs. In this dissertation, we expand this approach to tritrophic food web models by including the third trophic level. Using a functional trait approach, coexistence of all species is ensured using fitness-balancing trade-offs. For example, the defense-growth trade-off implies that species may be defended against predation, but this defense comes at the cost of a lower maximal growth rate. In these food webs, the functional diversity on a given trophic level can be varied by modifying the trait differences between the species on that level.
In the first project, we find that functional diversity promotes high biomass on the top level, which, in turn, leads to a reduction in the temporal variability due to compensatory dynamical patterns governed by the top level. Next, these results are generalized by investigating the average behavior of tritrophic food webs, for wide intervals of all parameters describing species interactions in the food web. We find that the diversity on the top level is most important for determining the biomass and temporal variability of all other trophic levels, and show how biomass is only transferred efficiently to the top level when diversity is high everywhere in the food web. In the third project, we compare the response of a simple food chain against a nutrient pulse perturbation, to that of a food web with diversity on every trophic level. By joint consideration of the resistance, resilience, and elasticity, we uncover that the response is efficiently buffered when biomass on the top level is high, which is facilitated by functional diversity on every trophic level in the food web. Finally, in the fourth project, we show that even in a simple consumer-resource model without any diversity, top-down control on the intermediate level frequently causes the phase difference between the intermediate and basal level to deviate from the quarter-cycle lag rule. By adding a top predator, we show that these deviations become even more likely, and anti-phase cycles are often observed.
The combined results of these projects show how the properties of the top trophic level, including its functional diversity, have a decisive influence on the functioning of tritrophic food webs from a mechanistic perspective. Because top species are often among the most vulnerable to extinction, our results emphasize the importance of their conservation in ecosystem management and restoration strategies.
Kenya and Uganda are amongst the countries that, for different historical, political, and economic reasons, have embarked on law reform processes as regards to citizenship. In 2009, Uganda made provisions in its laws to allow citizens to have dual citizenship while Kenya’s 2010 constitution similarly introduced it, and at the same time, a general prohibition on dual citizenship was lifted, that is, a ban on state officers, including the President and Deputy President, being dual nationals (Manby, 2018).
Against this background, I analysed the reasons for which these countries that previously held stringent laws and policies against dual citizenship, made a shift in a close time proximity. Given their geo-political roles, location, regional, continental, and international obligations, I conducted a comparative study on the processes, actors, impact, and effect. A specific period of 2000 to 2010 was researched, that is, from when the debates for law reforms emerged, to the processes being implemented, the actors, and the implications.
According to Rubenstein (2000, p. 520), citizenship is observed in terms of “political institutions” that are free to act according to the will of, in the interests of, or with authority over, their citizenry. Institutions are emergent national or international, higher-order factors above the individual spectrum, having the interests and political involvement of their actors without requiring recurring collective mobilisation or imposing intervention to realise these regularities. Transnational institutions are organisations with authority beyond single governments. Given their International obligations, I analysed the role of the UN, AU, and EAC in influencing the citizenship debates and reforms in Kenya and Uganda. Further, non-state actors, such as civil society, were considered.
Veblen, (1899) describes institutions as a set of settled habits of thought common to the generality of men. Institutions function only because the rules involved are rooted in shared habits of thought and behaviour although there is some ambiguity in the definition of the term “habit”. Whereas abstracts and definitions depend on different analytical procedures, institutions restrain some forms of action and facilitate others. Transnational institutions both restrict and aid behaviour. The famous “invisible hand” is nothing else but transnational institutions. Transnational theories, as applied to politics, posit two distinct forms that are of influence over policy and political action (Veblen, 1899). This influence and durability of institutions is “a function of the degree to which they are instilled in political actors at the individual or organisational level, and the extent to which they thereby “tie up” material resources and networks. Against this background, transitional networks with connection to Kenya and Uganda were considered alongside the diaspora from these two countries and their role in the debate and reforms on Dual citizenship.
Sterian (2013, p. 310) notes that Nation states may be vulnerable to institutional influence and this vulnerability can pose a threat to a nation’s autonomy, political legitimacy, and to the democratic public law. Transnational institutions sometimes “collide with the sovereignty of the state when they create new structures for regulating cross-border relationships”. However, Griffin (2003) disagrees that transnational institutional behaviour is premised on the principles of neutrality, impartiality, and independence. Transnational institutions have become the main target of the lobby groups and civil society, consequently leading to excessive politicisation. Kenya and Uganda are member states not only of the broader African union but also of the E.A.C which has adopted elements of socio-economic uniformity. Therefore, in the comparative analysis, I examine the role of the East African Community and its partners in the dual citizenship debate on the two countries.
I argue in the analysis that it is not only important to be a citizen within Kenya or Uganda but also important to discover how the issue of dual citizenship is legally interpreted within the borders of each individual nation-state. In light of this discussion, I agree with Mamdani’s definition of the nation-state as a unique form of power introduced in Africa by colonial powers between 1880 and 1940 whose outcomes can be viewed as “debris of a modernist postcolonial project, an attempt to create a centralised modern state as the bearer of Westphalia sovereignty against the background of indirect rule” (Mamdani, 1996, p. xxii). I argue that this project has impacted the citizenship debate through the adopted legal framework of post colonialism, built partly on a class system, ethnic definitions, and political affiliation. I, however, insist that the nation-state should still be a vital custodian of the citizenship debate, not in any way denying the individual the rights to identity and belonging. The question then that arises is which type of nation-state? Mamdani (1996, p. 298) asserts that the core agenda that African states faced at independence was threefold: deracialising civil society; detribalising the native authority; and developing the economy in the context of unequal international relations. Post-independence governments grappled with overcoming the citizen and subject dichotomy through either preserving the customary in the name of “defending tradition against alien encroachment or abolishing it in the name of overcoming backwardness and embracing triumphant modernism”. Kenya and Uganda are among countries that have reformed their citizenship laws attesting to Mamdani’s latter assertion.
Mamdani’s (1996) assertions on how African states continue to deal with the issue of citizenship through either the defence of tradition against subjects or abolishing it in the name of overcoming backwardness and acceptance of triumphant modernism are based on the colonial legal theory and the citizen-subject dichotomy within Africa communities. To further create a wider perspective on legal theory, I argue that those assertions above, point to the historical divergence between the republican model of citizenship, which places emphasis on political agency as envisioned in Rousseau´s social contract, as opposed to the liberal model of citizenship, which stresses the legal status and protection (Pocock, 1995).
I, therefore, compare the contexts of both Kenya and Uganda, the actors, the implications of transnationalism and post-nationalism, on the citizens, the nation-state and the region. I conclude by highlighting the shortcomings in the law reforms that allowed for dual citizenship, further demonstrating an urgent need to address issues, such as child statelessness, gender nationality laws, and the rights of dual citizens. Ethnicity, a weak nation state, and inconsistent citizenship legal reforms are closely linked to the historical factors of both countries. I further indicate the economic and political incentives that influenced the reform.
Keywords: Citizenship, dual citizenship, nation state, republicanism, liberalism, transnationalism, post-nationalism
Compound values are not universally supported in virtual machine (VM)-based programming systems and languages. However, providing data structures with value characteristics can be beneficial. On one hand, programming systems and languages can adequately represent physical quantities with compound values and avoid inconsistencies, for example, in representation of large numbers. On the other hand, just-in-time (JIT) compilers, which are often found in VMs, can rely on the fact that compound values are immutable, which is an important property in optimizing programs. Considering this, compound values have an optimization potential that can be put to use by implementing them in VMs in a way that is efficient in memory usage and execution time. Yet, optimized compound values in VMs face certain challenges: to maintain consistency, it should not be observable by the program whether compound values are represented in an optimized way by a VM; an optimization should take into account, that the usage of compound values can exhibit certain patterns at run-time; and that necessary value-incompatible properties due to implementation restrictions should be reduced.
We propose a technique to detect and compress common patterns of compound value usage at run-time to improve memory usage and execution speed. Our approach identifies patterns of frequent compound value references and introduces abbreviated forms for them. Thus, it is possible to store multiple inter-referenced compound values in an inlined memory representation, reducing the overhead of metadata and object references. We extend our approach by a notion of limited mutability, using cells that act as barriers for our approach and provide a location for shared, mutable access with the possibility of type specialization. We devise an extension to our approach that allows us to express automatic unboxing of boxed primitive data types in terms of our initial technique. We show that our approach is versatile enough to express another optimization technique that relies on values, such as Booleans, that are unique throughout a programming system. Furthermore, we demonstrate how to re-use learned usage patterns and optimizations across program runs, thus reducing the performance impact of pattern recognition.
We show in a best-case prototype that the implementation of our approach is feasible and can also be applied to general purpose programming systems, namely implementations of the Racket language and Squeak/Smalltalk. In several micro-benchmarks, we found that our approach can effectively reduce memory consumption and improve execution speed.
To achieve a sustainable energy economy, it is necessary to turn back on the combustion of fossil fuels as a means of energy production and switch to renewable sources. However, their temporal availability does not match societal consumption needs, meaning that renewably generated energy must be stored in its main generation times and allocated during peak consumption periods. Electrochemical energy storage (EES) in general is well suited due to its infrastructural independence and scalability. The lithium ion battery (LIB) takes a special place, among EES systems due to its energy density and efficiency, but the scarcity and uneven geological occurrence of minerals and ores vital for many cell components, and hence the high and fluctuating costs will decelerate its further distribution.
The sodium ion battery (SIB) is a promising successor to LIB technology, as the fundamental setup and cell chemistry is similar in the two systems. Yet, the most widespread negative electrode material in LIBs, graphite, cannot be used in SIBs, as it cannot store sufficient amounts of sodium at reasonable potentials. Hence, another carbon allotrope, non-graphitizing or hard carbon (HC) is used in SIBs. This material consists of turbostratically disordered, curved graphene layers, forming regions of graphitic stacking and zones of deviating layers, so-called internal or closed pores.
The structural features of HC have a substantial impact of the charge-potential curve exhibited by the carbon when it is used as the negative electrode in an SIB. At defects and edges an adsorption-like mechanism of sodium storage is prevalent, causing a sloping voltage curve, ill-suited for the practical application in SIBs, whereas a constant voltage plateau of relatively high capacities is found immediately after the sloping region, which recent research attributed to the deposition of quasimetallic sodium into the closed pores of HC.
Literature on the general mechanism of sodium storage in HCs and especially the role of the closed pore is abundant, but the influence of the pore geometry and chemical nature of the HC on the low-potential sodium deposition is yet in an early stage. Therefore, the scope of this thesis is to investigate these relationships using suitable synthetic and characterization methods. Materials of precisely known morphology, porosity, and chemical structure are prepared in clear distinction to commonly obtained ones and their impact on the sodium storage characteristics is observed. Electrochemical impedance spectroscopy in combination with distribution of relaxation times analysis is further established as a technique to study the sodium storage process, in addition to classical direct current techniques, and an equivalent circuit model is proposed to qualitatively describe the HC sodiation mechanism, based on the recorded data. The obtained knowledge is used to develop a method for the preparation of closed porous and non-porous materials from open porous ones, proving not only the necessity of closed pores for efficient sodium storage, but also providing a method for effective pore closure and hence the increase of the sodium storage capacity and efficiency of carbon materials.
The insights obtained and methods developed within this work hence not only contribute to the better understanding of the sodium storage mechanism in carbon materials of SIBs, but can also serve as guidance for the design of efficient electrode materials.
Any physical system can be described on the level of interacting particles, thus it is of fundamental importance to improve the scientific understanding of interacting many-body systems. This thesis experimentally addresses specific quasi-particle interactions, namely interactions be- tween electrons and between electrons and phonons. It describes the consequential effects of those processes on the electronic structure and the core-hole relaxation pathways in 3d metals. Despite the great amount of experimental and theoretical studies of these interactions and their impact on the behavior of solid-state matter, there are still open questions concerning the cor- responding physical, chemical and mechanical properties of solid-state matter. Especially, the study of 3d metals and their compounds is a great experimental challenge, since those exhibit a variety of spectral features originating from many-body effects such as multiplet splitting, shake up/off satellites, vibrationally excited states or more complex effects like superconductivity and ultrafast demagnetization. In X-ray spectroscopy, these effects often produce overlapping fea- tures, complicating the analysis and limiting the understanding. In this thesis, to overcome the limitations set by conventional X-ray spectroscopy, two different experimental approaches were successfully refined, namely Auger electron photoelectron coincidence spectroscopy (APECS) and temperature-dependent X-ray emission spectroscopy (tXES), which enabled the separation of different core-hole relaxation pathways and the isolation of the impact of specific many-body interactions in the experimental spectra. APECS was utilized at the new Coincidence electron spectroscopy for chemical analysis (Co- ESCA) station at BESSY II to study the core-hole decay and electron-correlation effects in single- crystal Ni, Cu and Co. The observation of photoelectrons in coincidence with Auger electrons allows for the separation of the initial and final state effects in the Auger electron spectra. The results show that a Cu LV V Auger spectrum can be represented by broadened atomic multiplets confirming the localized nature of the intermediate core-hole states. In contrast, the Co LV V Auger spectrum is band-like and can be represented by the self-convolution of the valence band. Ni behaves mixed, localized and itinerant. Thus, the Ni Auger spectrum can only be represented by a mixture of atomic multiplet peaks and the self-convoluted valence band. In the case of Ni, the LV V Auger electrons in coincidence with the 6 eV satellite photoelectrons were also stud- ied. Utilizing the core-hole clock method, the lifetime of the localized double-hole intermediate 2 p53d9 states of 1.8 fs could be determined. However, a fraction of these states delocalizes before the Auger decay contributing to the main peak. A similar delocalization was observed for the double-hole states produced by the L2L3M4,5 Coster-Kronig process. Additionally, the influence of surface oxidation on the Ni(111) 3p levels was studied with APECS. The Ni 3p PES spectrum is broad and featureless, due to overlapping many-body effects and gives little chance for exact analysis using conventional photoelectron spectroscopy. Utilizing APECS or precisely the final state selectivity of the method, the spectral width of the 3p levels could be narrowed and their positions and the spin-orbit splitting were determined. Moreover, due to the surface sensitivity of the method, the chemically shifted 3p photoelectron peaks originating from the oxidized surface and the bulk Ni were disentangled. For the study of the atomic electron-phonon spin-flip scattering in 3d metals as a spin-relaxation channel, the tXES method at the SolidFlexRIXS station was developed. The atomic spin-flip scat- tering was studied in single-crystal Ni, Cu, Co and in FeNi alloys, which show considerable dif- ferences in their behavior. The scattering rate in Ni increases with temperature, whereas the rate in Cu and Co remains constant within the measured temperature range up to 1000 K. In FeNi alloys, our results reveal that the spin-flip scattering is restricted by sublattice exchange energies J. The electron-phonon scattering driven spin-flips only appear in the case where the thermal energy ex- ceeds the exchange energy kT > J. This thresholding is an important microscopic process for the description of the sublattice dynamics in alloys, but as shown also relevant for elemental magnetic systems. Overall, the results strongly indicate that the spin-flip probability is correlated with the exchange energy, which might become an important parameter in the ultrafast demagnetization debate. Taken together, the applied experimental approaches allowed to study complex many-body effects in 3d metals. The results show that utilizing APECS enabled the distinction and clear assignment of otherwise overlapping features in AES or PES spectra of Ni, Cu, Co and NiO. This is of fundamental importance for the basic understanding of photoionization and core-hole decay processes but also for the chemical analysis in applied science. The measurement of the atomic electron-phonon spin-flip scattering rate utilizing tXES shows that the electron-phonon spin-flip scattering is a relevant atomic process for the macroscopic demagnetization process. Additionally, a temperature-dependent thresholding mechanism was discovered, which introduces an important dynamic factor into the electron-phonon spin-flip model.
Elucidating the molecular basis of enhanced growth in the Arabidopsis thaliana accession Bur-0
(2021)
The life cycle of flowering plants is a dynamic process that involves successful passing through several developmental phases and tremendous progress has been made to reveal cellular and molecular regulatory mechanisms underlying these phases, morphogenesis, and growth. Although several key regulators of plant growth or developmental phase transitions have been identified in Arabidopsis, little is known about factors that become active during embryogenesis, seed development and also during further postembryonic growth. Much less is known about accession-specific factors that determine plant architecture and organ size. Bur-0 has been reported as a natural Arabidopsis thaliana accession with exceptionally big seeds and a large rosette; its phenotype makes it an interesting candidate to study growth and developmental aspects in plants, however, the molecular basis underlying this big phenotype remains to be elucidated. Thus, the general aim of this PhD project was to investigate and unravel the molecular mechanisms underlying the big phenotype in Bur-0.
Several natural Arabidopsis accessions and late flowering mutant lines were analysed in this study, including Bur-0. Phenotypes were characterized by determining rosette size, seed size, flowering time, SAM size and growth in different photoperiods, during embryonic and postembryonic development. Our results demonstrate that Bur-0 stands out as an interesting accession with simultaneously larger rosettes, larger SAM, later flowering phenotype and larger seeds, but also larger embryos. Interestingly, inter-accession crosses (F1) resulted in bigger seeds than the parental self-crossed accessions, particularly when Bur-0 was used as the female parental genotype, suggesting parental effects on seed size that might be maternally controlled. Furthermore, developmental stage-based comparisons revealed that the large embryo size of Bur-0 is achieved during late embryogenesis and the large rosette size is achieved during late postembryonic growth. Interestingly, developmental phase progression analyses revealed that from germination onwards, the length of developmental phases during postembryonic growth is delayed in Bur-0, suggesting that in general, the mechanisms that regulate developmental phase progression are shared across developmental phases.
On the other hand, a detailed physiological characterization in different tissues at different developmental stages revealed accession-specific physiological and metabolic traits that underlie accession-specific phenotypes and in particular, more carbon resources during embryonic and postembryonic development were found in Bur-0, suggesting an important role of carbohydrates in determination of the bigger Bur-0 phenotype. Additionally, differences in the cellular organization, nuclei DNA content, as well as ploidy level were analyzed in different tissues/cell types and we found that the large organ size in Bur-0 can be mainly attributed to its larger cells and also to higher cell proliferation in the SAM, but not to a different ploidy level.
Furthermore, RNA-seq analysis of embryos at torpedo and mature stage, as well as SAMs at vegetative and floral transition stage from Bur-0 and Col-0 was conducted to identify accession-specific genetic determinants of plant phenotypes, shared across tissues and developmental stages during embryonic and postembryonic growth. Potential candidate genes were identified and further validation of transcriptome data by expression analyses of candidate genes as well as known key regulators of organ size and growth during embryonic and postembryonic development confirmed that the high confidence transcriptome datasets generated in this study are reliable for elucidation of molecular mechanisms regulating plant growth and accession-specific phenotypes in Arabidopsis.
Taken together, this PhD project contributes to the plant development research field providing a detailed analysis of mechanisms underlying plant growth and development at different levels of biological organization, focusing on Arabidopsis accessions with remarkable phenotypical differences. For this, the natural accession Bur-0 was an ideal outlier candidate and different mechanisms at organ and tissue level, cell level, metabolism, transcript and gene expression level were identified, providing a better understanding of different factors involved in plant growth regulation and mechanisms underlying different growth patterns in nature.
Ground-based astronomy is set to employ next-generation telescopes with apertures larger than 25 m in diameter before this decade is out. Such giant telescopes observe their targets through a larger patch of turbulent atmosphere, demanding that most of the instruments behind them must also grow larger to make full use of the collected stellar flux. This linear scaling in size greatly complicates the design of astronomical instrumentation, inflating their cost quadratically. Adaptive optics (AO) is one approach to circumvent this scaling law, but it can only be done to an extent before the cost of the corrective system itself overwhelms that of the instrument or even that of the telescope. One promising technique for miniaturizing the instruments and thus driving down their cost is to replace some, or all, of the free space bulk optics in the optical train with integrated photonic components.
Photonic devices, however, do their work primarily in single-mode waveguides, and the atmospherically-distorted starlight must first be efficiently coupled into them if they are to outperform their bulk optic counterparts. This is doable by two means: AO systems can again help control the angular size and motion of seeing disks to the point where they will couple efficiently into astrophotonic components, but this is only feasible for the brightest of objects and over limited fields of view. Alternatively, tapered fiber devices known as photonic lanterns — with their ability to convert multimode into single-mode optical fields — can be used to feed speckle patterns into single-mode integrated optics. They, nonetheless, must conserve the degrees of freedom, and the number of output waveguides will quickly grow out of control for uncorrected large telescopes. An AO-assisted photonic lantern fed by a partially corrected wavefront presents a compromise that can have a manageable size if the trade-off between the two methods is chosen carefully. This requires end-to-end simulations that take into account all the subsystems upstream of the astrophotonic instrument, i.e., the atmospheric layers, the telescope, the AO system, and the photonic lantern, before a decision can be made on sizing the multiplexed integrated instrument.
The numerical models that simulate atmospheric turbulence and AO correction are presented in this work. The physics and models for optical fibers, arrays of waveguides, and photonic lanterns are also provided. The models are on their own useful in understanding the behavior of the individual subsystems involved and are also used together to compute the optimum sizing of photonic lanterns for feeding astrophotonic instruments. Additionally, since photonic lanterns are a relatively new concept, two novel applications are discussed for them later in this thesis: the use of mode-selective photonic lanterns (MSPLs) to reduce the multiplicity of multiplexed integrated instruments and the combination of photonic lanterns with discrete beam combiners (DBCs) to retrieve the modal content in an optical waveguide.
Humans are frequently exposed to a variety of endocrine disrupting chemicals (EDCs), which can cause harmful effects, e.g. disturbance of growth, development and reproduction, and cancer (UBA, 2016). EDCs are often components of synthetically manufactured products. Materials made of plastics, building materials, electronic items, textiles or cosmetic products can be particularly contaminated (Ain et al., 2021). One group of EDCs that has gained increased interest in recent years is phthalates. They are used as plasticizers in plastic materials to which people are daily exposed to. Phthalate plasticizers exert their harmful effects among others via activation of the estrogen receptor α (ERα), the estrogen receptor β (ERβ) and via inhibition of the androgen receptor (AR). Some phthalates have already been classified by the EU as Cancerogenic-, Mutagenic-, Reprotoxic- (CMR) substances and their use in industry has been restricted. After oral ingestion, phthalates are metabolized and are finally excreted with the urine. Numerous toxicological studies exist on phthalates, but mainly with the parent substances, not with their primary and secondary metabolites. In the course of the restriction of phthalates by the EU, the phthalate-free plasticizer di-isononylcyclohexane-1,2-dicarboxylate (DINCH®), was introduced to the market. So far, almost no toxicologically relevant properties have been identified for DINCH®. However, the effects of DINCH® have only been studied in animal experiments and, as with phthalates, almost exclusively with the parent substance. However, toxic effects of a particular compound may be induced by its metabolites and not by the parent compound itself. Therefore, potential endocrine effects of 15 phthalates, 19 phthalate metabolites, DINCH®, and five of its metabolites were investigated using reporter gene assays on the ERα, ERβ, and the AR. In addition, studies of the influence of some selected plasticizers on peroxisome proliferator-activated receptor α (PPARα) and peroxisome proliferator-activated receptor γ (PPARγ) activity were performed. Furthermore, a H295R steroidogenesis assay was performed to determine the influence of DINCH® and its metabolites on estradiol or testosterone synthesis. Analysis of the experiments shows that the phthalates either stimulated or inhibited ERα and ERβ activity and inhibited AR activity, whereas the phthalate metabolites did not affect the activity of these human hormone receptors. In contrast, metabolites of di-(2-ethylhexyl) phthalate (DEHP) stimulated transactivation of the human PPARα and PPARγ in analogous reporter gene assays, although DEHP itself did not activate these nuclear receptors. Therefore, primary and secondary phthalate metabolites appear to exert different effects at the molecular level compared to the parent compounds. Similarly, the results showed that the phthalate-free plasticizer DINCH® itself did not affect the activity of ERα, ERβ, AR, PPARα and PPARγ, while the DINCH® metabolites were shown to activate all these receptors. In the case of AR, DINCH® metabolites mainly enhanced AR activity stimulated by dihydrotestosterone (DHT). In the H295R steroidogenesis assay, neither DINCH® nor any of its metabolites affected estradiol or testosterone synthesis. Primary and secondary metabolites of DINCH® thus exert different effects at the molecular level than DINCH® itself. However, all these in vitro effects of DINCH® metabolites were observed only at high concentrations, which were about three orders of magnitude higher than the reported DINCH® metabolite concentrations in human urine. Therefore, the in vitro data does not support the assumption that DINCH® or any of the metabolites studied could have significant endocrine effects in vivo at relevant exposure levels in humans. Following the demonstration of direct and indirect endocrine effects of the studied plasticizers, a new effect-based in vitro 3D screening tool for toxicity assays of non-genotoxic carcinogens was developed using estrogen receptor-negative (ER-) MCF10-A cells and estrogen receptor-positive (ER+) MCF-12A cells. This arose from the background that breast cancer is the most common cancer occurring in women and estrogenic substances, such as phthalates, can probably influence the disease. The human mammary epithelial cell lines MCF-10A and MCF-12A form well-differentiated acini-like structures when cultured in three-dimensional Matrigel culture for a period of 20 days. The model should make it possible to detect substance effects on cell differentiation and growth, on mammary cell acini, and to differentiate between estrogenic and non-estrogenic effects at the same time. In the present study, both cell lines were tested for their suitability as an effect-based in vitro assay system for non-genotoxic carcinogens. An Automated Acinus Detection And Morphological Evaluation (ADAME) software solution has been developed for automatic acquisition of acinus images and determination of morphological parameters such as acinus size, lumen size, and acinus roundness. Several test substances were tested for their ability to affect acinus formation and cellular differentiation. Human epithelial growth factor (EGF) stimulated acinus growth for both cell lines, while all trans retinoic acid (RA) inhibited acinar growth. The potent estrogen 17β-estradiol had no effect on acinus formation of MCF-10A cells but resulted in larger MCF-12A acini. Thus, the parallel use of both cell lines together with the developed high content screening and evaluation tool allows the rapid identification of the estrogenic and cancerogenic properties of a given test compound. The morphogenesis of the acini was only slightly affected by the test substances. On the one hand, this suggests a robust test system, on the other hand, it probably cannot detect low-potent estrogenic compounds such as phthalates or DINCH®. The advantage of the robustness of the system, however, may be that vast numbers of "positive" results with questionable biological relevance could be avoided, such as those observed in sensitive reporter gene assays.
Smart contracts promise to reform the legal domain by automating clerical and procedural work, and minimizing the risk of fraud and manipulation. Their core idea is to draft contract documents in a way which allows machines to process them, to grasp the operational and non-operational parts of the underlying legal agreements, and to use tamper-proof code execution alongside established judicial systems to enforce their terms. The implementation of smart contracts has been largely limited by the lack of an adequate technological foundation which does not place an undue amount of trust in any contract party or external entity. Only recently did the emergence of Decentralized Applications (DApps) change this: Stored and executed via transactions on novel distributed ledger and blockchain networks, powered by complex integrity and consensus protocols, DApps grant secure computation and immutable data storage while at the same time eliminating virtually all assumptions of trust.
However, research on how to effectively capture, deploy, and most of all enforce smart contracts with DApps in mind is still in its infancy. Starting from the initial expression of a smart contract's intent and logic, to the operation of concrete instances in practical environments, to the limits of automatic enforcement---many challenges remain to be solved before a widespread use and acceptance of smart contracts can be achieved.
This thesis proposes a model-driven smart contract management approach to tackle some of these issues. A metamodel and semantics of smart contracts are presented, containing concepts such as legal relations, autonomous and non-autonomous actions, and their interplay. Guided by the metamodel, the notion and a system architecture of a Smart Contract Management System (SCMS) is introduced, which facilitates smart contracts in all phases of their lifecycle. Relying on DApps in heterogeneous multi-chain environments, the SCMS approach is evaluated by a proof-of-concept implementation showing both its feasibility and its limitations.
Further, two specific enforceability issues are explored in detail: The performance of fully autonomous tamper-proof behavior with external off-chain dependencies and the evaluation of temporal constraints within DApps, both of which are essential for smart contracts but challenging to support in the restricted transaction-driven and closed environment of blockchain networks. Various strategies of implementing or emulating these capabilities, which are ultimately applicable to all kinds of DApp projects independent of smart contracts, are presented and evaluated.
Due to global climate change providing food security for an increasing world population is a big challenge. Especially abiotic stressors have a strong negative effect on crop yield. To develop climate-adapted crops a comprehensive understanding of molecular alterations in the response of varying levels of environmental stresses is required. High throughput or ‘omics’ technologies can help to identify key-regulators and pathways of abiotic stress responses. In addition to obtain omics data also tools and statistical analyses need to be designed and evaluated to get reliable biological results.
To address these issues, I have conducted three different studies covering two omics technologies. In the first study, I used transcriptomic data from the two polymorphic Arabidopsis thaliana accessions, namely Col-0 and N14, to evaluate seven computational tools for their ability to map and quantify Illumina single-end reads. Between 92% and 99% of the reads were mapped against the reference sequence. The raw count distributions obtained from the different tools were highly correlated. Performing a differential gene expression analysis between plants exposed to 20 °C or 4°C (cold acclimation), a large pairwise overlap between the mappers was obtained. In the second study, I obtained transcript data from ten different Oryza sativa (rice) cultivars by PacBio Isoform sequencing that can capture full-length transcripts. De novo reference transcriptomes were reconstructed resulting in 38,900 to 54,500 high-quality isoforms per cultivar. Isoforms were collapsed to reduce sequence redundancy and evaluated, e.g. for protein completeness level (BUSCO), transcript length, and number of unique transcripts per gene loci. For the heat and drought tolerant aus cultivar N22, I identified around 650 unique and novel transcripts of which 56 were significantly differentially expressed in developing seeds during combined drought and heat stress. In the last study, I measured and analyzed the changes in metabolite profiles of eight rice cultivars exposed to high night temperature (HNT) stress and grown during the dry and wet season on the field in the Philippines. Season-specific changes in metabolite levels, as well as for agronomic parameters, were identified and metabolic pathways causing a yield decline at HNT conditions suggested.
In conclusion, the comparison of mapper performances can help plant scientists to decide on the right tool for their data. The de novo reconstruction of rice cultivars without a genome sequence provides a targeted, cost-efficient approach to identify novel genes responding to stress conditions for any organism. With the metabolomics approach for HNT stress in rice, I identified stress and season-specific metabolites which might be used as molecular markers for crop improvement in the future.
In C3 plants, CO2 diffuses into the leaf and is assimilated by the Calvin-Benson cycle in the mesophyll cells. It leaves Rubisco open to its side reaction with O2, resulting in a wasteful cycle known as photorespiration. A sharp fall in atmospheric CO2 levels about 30 million years ago have further increased the side reaction with O2. The pressure to reduce photorespiration led, in over 60 plant genera, to the evolution of a CO2-concentrating mechanism called C4 photosynthesis; in this mode, CO2 is initially incorporated into 4-carbon organic acids, which diffuse to the bundle sheath and are decarboxylated to provide CO2 to Rubisco. Some genera, like Flaveria, contain several species that represent different steps in this complex evolutionary process. However, the majority of terrestrial plant species did not evolve a CO2-concentrating mechanism and perform C3 photosynthesis.
This thesis compares photosynthetic metabolism in several species with C3, C4 and intermediate modes of photosynthesis. Metabolite profiling and stable isotope labelling were performed to detect inter-specific differences changes in metabolite profile and, hence, how a pathway operates. The results obtained were subjected to integrative data analyses like hierarchical clustering and principal component analysis, and were deepened by correlation analyses to uncover specific metabolic features and reaction steps that were conserved or differed between species.
The main findings are that Calvin-Benson cycle metabolite profiles differ between C3 and C4 species and between different C3 species, including a very different response to rising irradiance in Arabidopsis and rice. These findings confirm Calvin-Benson cycle operation diverged between C3 and C4 species and, most unexpectedly, even between different C3 species. Moreover, primary metabolic profiles supported the current C4 evolutionary model in the genus Flaveria and also provided new insights and opened up new questions. Metabolite profiles also point toward a progressive adjustment of the Calvin-Benson cycle during the evolution of C4 photosynthesis. Overall, this thesis point out the importance of a metabolite-centric approach to uncover underlying differences in species apparently sharing the same photosynthetic routes and as a valid method to investigate evolutionary transition between C3 and C4 photosynthesis.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
Energy is at the heart of the climate crisis—but also at the heart of any efforts for climate change mitigation. Energy consumption is namely responsible for approximately three quarters of global anthropogenic greenhouse gas (GHG) emissions. Therefore, central to any serious plans to stave off a climate catastrophe is a major transformation of the world's energy system, which would move society away from fossil fuels and towards a net-zero energy future. Considering that fossil fuels are also a major source of air pollutant emissions, the energy transition has important implications for air quality as well, and thus also for human and environmental health. Both Europe and Germany have set the goal of becoming GHG neutral by 2050, and moreover have demonstrated their deep commitment to a comprehensive energy transition. Two of the most significant developments in energy policy over the past decade have been the interest in expansion of shale gas and hydrogen, which accordingly have garnered great interest and debate among public, private and political actors.
In this context, sound scientific information can play an important role by informing stakeholder dialogue and future research investments, and by supporting evidence-based decision-making. This thesis examines anticipated environmental impacts from possible, relevant changes in the European energy system, in order to impart valuable insight and fill critical gaps in knowledge. Specifically, it investigates possible future shale gas development in Germany and the United Kingdom (UK), as well as a hypothetical, complete transition to hydrogen mobility in Germany. Moreover, it assesses the impacts on GHG and air pollutant emissions, and on tropospheric ozone (O3) air quality. The analysis is facilitated by constructing emission scenarios and performing air quality modeling via the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The work of this thesis is presented in three research papers.
The first paper finds that methane (CH4) leakage rates from upstream shale gas development in Germany and the UK would range between 0.35% and 1.36% in a realistic, business-as-usual case, while they would be significantly lower - between 0.08% and 0.15% - in an optimistic, strict regulation and high compliance case, thus demonstrating the value and potential of measures to substantially reduce emissions. Yet, while the optimistic case is technically feasible, it is unlikely that the practices and technologies assumed would be applied and accomplished on a systematic, regular basis, owing to economics and limited monitoring resources. The realistic CH4 leakage rates estimated in this study are comparable to values reported by studies carried out in the US and elsewhere. In contrast, the optimistic rates are similar to official CH4 leakage data from upstream gas production in Germany and in the UK. Considering that there is a lack of systematic, transparent and independent reports supporting the official values, this study further highlights the need for more research efforts in this direction. Compared with national energy sector emissions, this study suggests that shale gas emissions of volatile organic compounds (VOCs) could be significant, though relatively insignificant for other air pollutants. Similar to CH4, measures could be effective for reducing VOCs emissions.
The second paper shows that VOC and nitrogen oxides (NOx) emissions from a future shale gas industry in Germany and the UK have potentially harmful consequences for European O3 air quality on both the local and regional scale. The results indicate a peak increase in maximum daily 8-hour average O3 (MDA8) ranging from 3.7 µg m-3 to 28.3 µg m-3. Findings suggest that shale gas activities could result in additional exceedances of MDA8 at a substantial percentage of regulatory measurement stations both locally and in neighboring and distant countries, with up to circa one third of stations in the UK and one fifth of stations in Germany experiencing additional exceedances. Moreover, the results reveal that the shale gas impact on the cumulative health-related metric SOMO35 (annual Sum of Ozone Means Over 35 ppb) could be substantial, with a maximum increase of circa 28%. Overall, the findings suggest that shale gas VOC emissions could play a critical role in O3 enhancement, while NOx emissions would contribute to a lesser extent. Thus, the results indicate that stringent regulation of VOC emissions would be important in the event of future European shale gas development to minimize deleterious health outcomes.
The third paper demonstrates that a hypothetical, complete transition of the German vehicle fleet to hydrogen fuel cell technology could contribute substantially to Germany's climate and air quality goals. The results indicate that if the hydrogen were to be produced via renewable-powered water electrolysis (green hydrogen), German carbon dioxide equivalent (CO2eq) emissions would decrease by 179 MtCO2eq annually, though if electrolysis were powered by the current electricity mix, emissions would instead increase by 95 MtCO2eq annually. The findings generally reveal a notable anticipated decrease in German energy emissions of regulated air pollutants. The results suggest that vehicular hydrogen demand is 1000 PJ annually, which would require between 446 TWh and 525 TWh for electrolysis, hydrogen transport and storage. When only the heavy duty vehicle segment (HDVs) is shifted to green hydrogen, the results of this thesis show that vehicular hydrogen demand drops to 371 PJ, while a deep emissions cut is still realized (-57 MtCO2eq), suggesting that HDVs are a low-hanging fruit for contributing to decarbonization of the German road transport sector with hydrogen energy.
Fibroblast growth differentiation factor 21 (FGF21) is known as a pivotal regulator of the glucose and lipid metabolism. As such, it is considered beneficial and has even been labelled a longevity hormone. Nevertheless, recent observational studies have shown that FGF21 is increased in higher age with possible negative effects such as loss of lean and bone mass as well as decreased survival. Hepatic FGF21 secretion can be induced by various nutritional stimuli such as starvation, high carbohydrate and fat intake as well as protein deficiency.. So far it is still unclear whether the FGF21 response to different macronutrients is altered in older age. An altered response would potentially contribute to explain the higher FGF21 concentrations found in older age. In this publication-based doctoral dissertation, a cross-sectional study as well as a dietary challenge were conducted to investigate the influence of nutrition on FGF21 concentrations and response in older age. In a cross-sectional study, FGF21 concentrations were assessed in older patients with and without cachexia anorexia syndrome anorexia syndrome compared to an older community-dwelling control group. Cachexia anorexia syndrome is a multifactorial syndrome frequently occurring in old age or in the context of an underlying disease. It is characterized by a severe involuntary weight loss, loss of appetite (anorexia) and reduced food intake, therefore representing a state of severe nutrient deficiency, in some aspects similar to starvation. The highest FGF21 concentrations were found in patients with cachexia anorexia syndrome. Moreover, FGF21 was positively correlated with weight loss and loss of appetite. In addition, cachexia anorexia syndrome itself was associated with FGF21 independent of sex, age and body mass index. As cachectic patients presumably exhibit protein malnutrition and FGF21 has been proposed a marker for protein insufficiency, the higher levels of FGF21 in patients with cachexia anorexia syndrome might be partly explained by insufficient protein intake. In order to investigate the acute response of FGF21 to different nutritional stimuli, a dietary challenge with a parallel group design was conducted. Here, healthy older (65-85 years) and younger (18-35 years) adults were randomized to one of four test meals: a dextrose drink, a high carbohydrate, high fat or high protein meal. Over the course of four hours, postprandial FGF21 concentrations (dynamics) were assessed and the FGF21 response (incremental area under the curve) to each test meal was examined.. In a sub-group of older and younger women, also the adiponectin response was investigated, as adiponectin is a known mediator of FGF21 effects on glucose and lipid metabolism. The dietary meal challenge revealed that dextrose and high carbohydrate intake result in higher FGF21 concentrations after four hours in older adults. This was partly explained by higher postprandial glucose concentrations in the old. For high fat ingestion no age differences were found. For the first time, acute FGF21 response to high protein intake was shown. Here, protein ingestion resulted in lower FGF21 concentrations in younger compared to older adults. Furthermore, sufficient protein intake, according to age-dependent recommendations, of the previous day, was associated with lower FGF21 concentrations in both age groups. The higher FGF21 response to dextrose ingestion resulted in a higher adiponectin response in older women, independent of fat mass, insulin resistance, triglyceride concentrations, inflammation and oxidative stress. Following the high fat meal, adiponectin concentrations declined in older women. Adiponectin response was not affected by meal composition in younger women. In summary, this thesis showed a positive association of FGF21 and cachexia anorexia syndrome with concomitant anorexia in older patients. Regarding the acute FGF21 response, a higher response following dextrose and carbohydrate ingestion was found in older compared with younger subjects. This might be attributed to a higher glucose response in older age. Furthermore, it was shown that the higher FGF21 response after dextrose ingestion possibly contributes to a higher adiponectin response in older women, independent of potential metabolic and inflammatory confounders. Acute protein ingestion resulted in a significant decrease in FGF21 concentrations. Moreover, protein intake of the previous day was inversely associated with fasting FGF21 concentrations. This might explain why FGF21 concentrations are higher in cachexia anorexia syndrome. These results therefore support the role of FGF21 as a sensor of protein restriction.
Today, the Mekong Delta in the southern of Vietnam is home for 18 million people. The delta also accounts for more than half of the country’s food production and 80% of the exported rice. Due to the low elevation, it is highly susceptible to the risk of fluvial and coastal flooding. Although extreme floods often result in excessive damages and economic losses, the annual flood pulse from the Mekong is vital to sustain agricultural cultivation and livelihoods of million delta inhabitants.
Delta-wise risk management and adaptation strategies are required to mitigate the adverse impacts from extreme events while capitalising benefits from floods. However, a proper flood risk management has not been implemented in the VMD, because the quantification of flood damage is often overlooked and the risks are thus not quantified. So far, flood management has been exclusively focused on engineering measures, i.e. high- and low- dyke systems, aiming at flood-free or partial inundation control without any consideration of the actual risks or a cost-benefit analysis. Therefore, an analysis of future delta flood dynamics driven these stressors is valuable to facilitate the transition from sole hazard control towards a risk management approach, which is more cost-effective and also robust against future changes in risk.
Built on these research gaps, this thesis investigates the current state and future projections of flood hazard, damage and risk to rice cultivation, the most important economic activity in the VMD. The study quantifies the changes in risk and hazard brought by the development of delta-based flood control measures in the last decades, and analyses the expected changes in risk driven by the changing climate, rising sea-level and deltaic land subsidence, and finally the development of hydropower projects in the Mekong Basin. For this purpose, flood trend analyses and comprehensive hydraulic modelling were performed, together with the development of a concept to quantify flood damage and risk to rice plantation.
The analysis of observed flood levels revealed strong and robust increasing trends of peak and duration downstream of the high-dyke areas with a step change in 2000/2001, i.e. after the disastrous flood which initiated the high-dyke development. These changes were in contrast to the negative trends detected upstream, suggested that high-dyke development has shifted flood hazard downstream. Findings of the trend’s analysis were later confirmed by hydraulic simulations of the two recent extreme floods in 2000 and 2011, where the hydrological boundaries and dyke system settings were interchanged.
However, the high-dyke system was not the only and often not the main cause for a shift of flood hazard, as a comparative analysis of these two extreme floods proved. The high-dyke development was responsible for 20–90% of the observed changes in flood level between 2000 and 2011, with large spatial variances. The particular flood hydrograph of the two events had the highest contribution in the northern part of the delta, while the tidal level had 2–3 times higher influence than the high-dyke in the lower-central and coastal areas downstream of high-dyke areas. The impact of the high-dyke development was highest in the areas closely downstream of the high-dyke area just south of the Cambodia-Vietnam border. The hydraulic simulations also validated that the concurrence of the flood peak with spring tides, i.e. high sea level along the coast, amplified the flood level and inundation in the central and coastal regions substantially.
The risk assessment quantified the economic losses of rice cultivation to USD 25.0 and 115 million (0.02–0.1% of the total GDP of Vietnam in 2011) corresponding to the 10-year and the 100-year floods, with an expected annual damage of about USD 4.5 million. A particular finding is that the flood damage was highly sensitive to flood timing. Here, a 10-year event with an early peak, i.e. late August-September, could cause as much damage as a 100-year event that peaked in October. This finding underlines the importance of a reliable early flood warning, which could substantially reduce the damage to rice crops and thus the risk.
The developed risk assessment concept was furthermore applied to investigate two high-dyke development alternatives, which are currently under discussion among the administrative bodies in Vietnam, but also in the public. The first option favouring the utilization of the current high-dyke compartments as flood retention areas instead for rice cropping during the flood season could reduce flood hazard and expected losses by 5–40%, depending on the region of the delta. On the contrary, the second option promoting the further extension of the areas protected by high-dyke to facilitate third rice crop planting on a larger area, tripled the current expected annual flood damage. This finding challenges the expected economic benefit of triple rice cultivation, in addition to the already known reducing of nutrient supply by floodplain sedimentation and thus higher costs for fertilizers.
The economic benefits of the high-dyke and triple rice cropping system is further challenged by the changes in the flood dynamics to be expected in future. For the middle of the 21st century (2036-2065) the effective sea-level rise an increase of the inundation extent by 20–27% was projected. This corresponds to an increase of flood damage to rice crops in dry, normal and wet year by USD 26.0, 40.0 and 82.0 million in dry, normal and wet year compared to the baseline period 1971-2000.
Hydraulic simulations indicated that the planned massive development of hydropower dams in the Mekong Basin could potentially compensate the increase in flood hazard and agriculture losses stemming from climate change. However, the benefits of dams as mitigation of flood losses are highly uncertain, because a) the actual development of the dams is highly disputed, b) the operation of the dams is primarily targeted at power generation, not flood control, and c) this would require international agreements and cooperation, which is difficult to achieve in South-East Asia. The theoretical flood mitigation benefit is additionally challenged by a number of negative impacts of the dam development, e.g. disruption of floodplain inundation in normal, non-extreme flood years. Adding to the certain reduction of sediment and nutrient load to the floodplains, hydropower dams will drastically impair rice and agriculture production, the basis livelihoods of million delta inhabitants.
In conclusion, the VMD is expected to face increasing threats of tidal induced floods in the coming decades. Protection of the entire delta coastline solely with “hard” engineering flood protection structures is neither technically nor economically feasible, adaptation and mitigation actions are urgently required. Better control and reduction of groundwater abstraction is thus strongly recommended as an immediate and high priority action to reduce the land subsidence and thus tidal flooding and salinity intrusion in the delta. Hydropower development in the Mekong basin might offer some theoretical flood protection for the Mekong delta, but due to uncertainties in the operation of the dams and a number of negative effects, the dam development cannot be recommended as a strategy for flood management. For the Vietnamese authorities, it is advisable to properly maintain the existing flood protection structures and to develop flexible risk-based flood management plans. In this context the study showed that the high-dyke compartments can be utilized for emergency flood management in extreme events. For this purpose, a reliable flood forecast is essential, and the action plan should be materialised in official documents and legislation to assure commitment and consistency in the implementation and operation.
By regulating the concentration of carbon in our atmosphere, the global carbon cycle drives changes in our planet’s climate and habitability. Earth surface processes play a central, yet insufficiently constrained role in regulating fluxes of carbon between terrestrial reservoirs and the atmosphere. River systems drive global biogeochemical cycles by redistributing significant masses of carbon across the landscape. During fluvial transit, the balance between carbon oxidation and preservation determines whether this mass redistribution is a net atmospheric CO2 source or sink. Existing models for fluvial carbon transport fail to integrate the effects of sediment routing processes, resulting in large uncertainties in fluvial carbon fluxes to the oceans.
In this Ph.D. dissertation, I address this knowledge gap through three studies that focus on the timescale and routing pathways of fluvial mass transfer and show their effect on the composition and fluxes of organic carbon exported by rivers. The hypotheses posed in these three studies were tested in an analog lowland alluvial river system – the Rio Bermejo in Argentina. The Rio Bermejo annually exports more than 100 Mt of sediment and organic matter from the central Andes, and transports this material nearly 1300 km downstream across the lowland basin without influence from tributaries, allowing me to isolate the effects of geomorphic processes on fluvial organic carbon cycling. These studies focus primarily on the geochemical composition of suspended sediment collected from river depth profiles along the length of the Rio Bermejo.
In Chapter 3, I aimed to determine the mean fluvial sediment transit time for the Rio Bermejo and evaluate the geomorphic processes that regulate the rate of downstream sediment transfer. I developed a framework to use meteoric cosmogenic 10Be (10Bem) as a chronometer to track the duration of sediment transit from the mountain front downstream along the ~1300 km channel of the Rio Bermejo. I measured 10Bem concentrations in suspended sediment sampled from depth profiles, and found a 230% increase along the fluvial transit pathway. I applied a simple model for the time-dependent accumulation of 10Bem on the floodplain to estimate a mean sediment transit time of 8.5±2.2 kyr. Furthermore, I show that sediment transit velocity is influenced by lateral migration rate and channel morphodynamics. This approach to measuring sediment transit time is much more precise than other methods previously used and shows promise for future applications.
In Chapter 4, I aimed to quantify the effects of hydrodynamic sorting on the composition and quantity of particulate organic carbon (POC) export transported by lowland rivers. I first used scanning electron miscroscopy (SEM) coupled with nanoscale secondary ion mass spectrometry (NanoSIMS) analyses to show that the Bermejo transports two principal types of POC: 1) mineral-bound organic carbon associated with <4 µm, platy grains, and 2) coarse discrete organic particles. Using n-alkane stable isotope data and particle shape analysis, I showed that these two carbon pools are vertically sorted in the water column, due to differences in particle settling velocity. This vertical sorting may drive modern POC to be transported efficiently from source-to-sink, driving efficient CO2 drawdown. Simultaneously, vertical sorting may drive degraded, mineral-bound POC to be deposited overbank and stored on the floodplain for centuries to millennia, resulting in enhanced POC remineralization. In the Rio Bermejo, selective deposition of coarse material causes the proportion of mineral-bound POC to increase with distance downstream, but the majority of exported POC is composed of discrete organic particles, suggesting that the river is a net carbon sink. In summary, this study shows that selective deposition and hydraulic sorting control the composition and fate of fluvial POC during fluvial transit.
In Chapter 5, I characterized and quantified POC transformation and oxidation during fluvial transit. I analyzed the radiocarbon content and stable carbon isotopic composition of Rio Bermejo suspended sediment and found that POC ages during fluvial transit, but is also degraded and oxidized during transient floodplain storage. Using these data, I developed a conceptual model for fluvial POC cycling that allows the estimation of POC oxidation relative to POC export, and ultimately reveals whether a river is a net source or sink of CO2 to the atmosphere. Through this study, I found that the Rio Bermejo annually exports more POC than is oxidized during transit, largely due to high rates of lateral migration that cause erosion of floodplain vegetation and soil into the river. These results imply that human engineering of rivers could alter the fluvial carbon balance, by reducing lateral POC inputs and increasing the mean sediment transit time.
Together, these three studies quantitatively link geomorphic processes to rates of POC transport and degradation across sub-annual to millennial time scales and nanoscale to 103 km spatial scales, laying the groundwork for a global-scale fluvial organic carbon cycling model.
Foresight in networks
(2021)
The goal of this dissertation is to contribute to the corporate foresight research field by investigating capabilities, practices, and challenges particularly in the context of interorganizational settings and networked organizations informed by the theoretical perspectives of the relational view and dynamic capabilities.
Firms are facing an increasingly complex environment and highly complex product and service landscapes that often require multiple organizations to collaborate for innovation and offerings. Public-private partnerships that are targeted at supporting this have been introduced by policy-makers in the recent past. One example for such a partnership is the European Institute of Innovation and Technology (EIT) with multiple Knowledge and Innovation Communities (KICs). The EIT has been initiated by the European Commission in 2008 with the ambition of addressing grand societal challenges, driving innovativeness of European companies, and supporting systemic change. The resulting network organizations are managed similarly to corporations with managers, boards, and firm-like governance structures. EIT Digital as one of the EIT KICs are a central case of this work.
Research in this dissertation was based on the expectation that corporate foresight activities will increasingly be embedded in such interorganizational settings and a) can draw on such settings for the benefit of themselves and b) may contribute to shared visions, trust building and planning in these network organizations. In this dissertation the EIT Digital (formerly EIT ICT Labs) is a central case, supplemented with insights from three additional cases. I draw on the rich theoretical understanding of the resource-based view, dynamic capabilities, and particularly the relational view to further the discussion in the field of corporate foresight—defined as foresight in organizations in contrast to foresight with a macro-economical perspective—towards a relational understanding. Further, I use and revisit Rohrbeck’s Maturity Model for the Future Orientation of Firms as conceptual frame for corporate foresight in interorganizational settings. The analyses—available as four individual publications complemented by on additional chapter—are designed as exploratory case studies based on multiple data sources including an interview series with 49 persons, two surveys (N=54, n=20), three supplementary interviews, access to key documents and presentations, and observation through participation in meetings and activities of the EIT Digital. This research setting allowed me to contribute to corporate foresight research and practice by 1) integrating relational constructs primarily drawn from the relational view and dynamic capabilities research into the corporate foresight research stream, 2) exploring and understanding capabilities that are required for corporate foresight in interorganizational and networked organizations, 3) discussing and extending the Maturity Model for network organizations, and 4) to support individual organizations to tie their foresight systems effectively to networked foresight systems.
Inequalities in health are a prevalent feature of societies. And as societies, we condemn inequalities that are rooted in immutable circumstances such as gender, race, and parental background. Consequently, policy makers are interested in measuring and understanding the causes of health inequalities rooted in circumstances. However, identifying causal estimates of these relationships is very ambitious for reasons such as the presence of confounders or measurement error in the data. This thesis contributes to this ambitious endeavour by addressing these challenges in four chapters.
In the first Chapter, I use 25 years of rich health information to describe three features of intergenerational health mobility in Germany. First, we describe the joint permanent health distribution of the parents and their children. A ten percentile increase in parental permanent health is associated with a 2.3 percentile increase in their child’s health. Second, a percentile point increase in permanent health ranks is associated with a 0.8% to 1.4% increase in permanent income for, both, children, and parents, respectively. Non-linearities in the association between permanent health and income create incentives to escape the bottom of the permanent health distribution. Third, upward mobility in permanent health varies with parental socio-economic status.
In the second Chapter, we estimate the effect of maternal schooling on children’s mental health in adulthood. Using the Socio-Economic Panel and the mental health measure based on the SF-12 questionnaire, we exploit a compulsory schooling law reform to identify the causal effect of maternal schooling on children’s mental health. While the theoretical considerations are not clear, we do not find that the mother’s schooling has an effect on the mental health of the children. However, we find a positive effect on children’s physical health operating mainly through physical functioning. In addition, albeit with the absence of a reduced-form effect on mental health, we find evidence that the number of friends moderates the relationship between maternal schooling and their children’s mental health.
In the third Chapter, against a background of increasing violence against non-natives, we estimate the effect of hate crime on refugees’ mental health in Germany. For this purpose, we combine two datasets: administrative records on xenophobic crime against refugee shelters by the Federal Criminal Office and the IAB-BAMF-SOEP Survey of Refugees. We apply a regression discontinuity design in time to estimate the effect of interest. Our results indicate that hate crime has a substantial negative effect on several mental health indicators, including the Mental Component Summary score and the Patient Health Questionnaire-4 score. The effects are stronger for refugees with closer geographic proximity to the focal hate crime and refugees with low country-specific human capital. While the estimated effect is only transitory, we argue that negative mental health shocks during the critical period after arrival have important long-term consequences.
In the last Chapter of this thesis, we investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed – particularly women– in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
We developed an orbital tuned age model for the composite Chew Bahir sediment core, obtained from the Chew Bahir basin (CHB), southern Ethiopia. To account for the effects of sedimentation rate changes on the spectral expression of the orbital cycles we developed a new method: the Multi-band Wavelet Age modeling technique (MUBAWA). By using a Continuous Wavelet Transformation, we were able to track frequency shifts that resulted from changing sedimentation rates and thus calculated tuned age model encompassing the last 620 kyrs. The results show a good agreement with the directly dated age model that is available from the dating of volcanic ashes. Then we used the XRF data from CHB and developed a new and robust humid-arid index of east African climate during the last 620 kyrs. To disentangle the relationship of the selected elements we performed a principal component analysis (PCA). In a following step we applied a continuous wavelet transformation on the PC1, using the directly dated age model. The resulting wavelet power spectrum, unlike a normal power spectrum, displays the occurrence of cycles/frequencies in time. The results highlight that the precession cycles are most dominantly expressed under the 400 kyrs eccentricity maximum whereas weakly expressed during eccentricity minimum. This suggests that insolation is a key driver of the climatic variability observed at CHB throughout the last 620 kyrs. In addition, the prevalence of half-precession and obliquity signals was documented. The latter is attributed to the inter-tropical insolation gradient and not interpreted as an imprint of high latitudes forcing on climatic changes in the tropics. In addition, a windowed analysis of variability was used to detect changes in variance over time and showed that strong climate variability occurred especially along the transition from a dominant insolation-controlled humid climate background state towards a predominantly dry and less-insolation controlled climate. The last chapter dealt with non-linear aspects of climate changes represented by the sediments of the CHB. We use recurrence quantification analysis to detect non-linear changes within the potassium concentration of Chew Bahir sediment cores during the last 620 kyrs. The concentration of potassium in the sediments of the lake is subject to geochemical processes related to the evaporation rate of the lake water at the time of deposition. Based on recurrence analysis, two types of variabilities could be distinguished. Type 1 represents slow variations within the precession period bandwidth of 20 kyrs and a tendency towards extreme climatic events whereas type 2 represents fast, highly variable climatic transitions between wet and dry climate states. While type 1 variability is linked to eccentricity maxima, type 2 variability occurs during the 400 kyrs eccentricity minimum. The climate history presented here shows that during high eccentricity a strongly insolation-driven climate system prevailed, whereas during low eccentricity the climate was more strongly affected by short-term variability changes. The short-term environmental changes, reflected in the increased variability might have influenced the evolution, technological advances and expansion of early modern humans who lived in this region. In the Olorgesaille Basin the temporal changes in the occurrence of stone tools, which bracket the transition from Acheulean to Middle Stone Age (MSA) technologies at between 499–320 kyrs, could potentially correlate to the marked transition from a rather stable climate with less variability to a climate with increased variability in the CHB. We conclude that populations of early anatomically modern humans are more likely to have experienced climatic stress during episodes of low eccentricity, associated with dry and high variability climate conditions, which may have led to technological innovation, such as the transition from the Acheulean to the Middle Stone Age.
Angular momentum is a particularly sensitive probe into stellar evolution because it changes significantly over the main sequence life of a star. In this thesis, I focus on young main sequence stars of which some feature a rapid evolution in their rotation rates. This transition from fast to slow rotation is inadequately explored observationally and this work aims to provide insights into the properties and time scales but also investigates stellar rotation in young open clusters in general.
I focus on the two open clusters NGC 2516 and NGC 3532 which are ~150 Myr (zero-age main sequence age) and ~300 Myr old, respectively. From 42 d-long time series photometry obtained at the Cerro Tololo Inter-American Observatory, I determine stellar rotation periods in both clusters. With accompanying low resolution spectroscopy, I measure radial velocities and chromospheric emission for NGC 3532, the former to establish a clean membership and the latter to probe the rotation-activity connection.
The rotation period distribution derived for NGC 2516 is identical to that of four other coeval open clusters, including the Pleiades, which shows the universality of stellar rotation at the zero-age main sequence. Among the similarities (with the Pleiades) the "extended slow rotator sequence" is a new, universal, yet sparse, feature in the colour-period diagrams of open clusters. From a membership study, I find NGC 3532 to be one of the richest nearby open clusters with 660 confirmed radial velocity members and to be slightly sub-solar in metallicity. The stellar rotation periods for NGC 3532 are the first published for a 300 Myr-old open cluster, a key age to understand the transition from fast to slow rotation. The fast rotators at this age have significantly evolved beyond what is observed in NGC 2516 which allows to estimate the spin-down timescale and to explore the issues that angular momentum models have in describing this transition. The transitional sequence is also clearly identified in a colour-activity diagram of stars in NGC 3532. The synergies of the chromospheric activity and the rotation periods allow to understand the colour-activity-rotation connection for NGC 3532 in unprecedented detail and to estimate additional rotation periods for members of NGC 3532, including stars on the "extended slow rotator sequence".
In conclusion, this thesis probes the transition from fast to slow rotation but has also more general implications for the angular momentum evolution of young open clusters.
The incorporation of proteins in artificial materials such as membranes offers great opportunities to avail oneself the miscellaneous qualities of proteins and enzymes perfected by nature over millions of years. One possibility to leverage proteins is the modification with artificial polymers. To obtain such protein-polymer conjugates, either a polymer can be grown from the protein surface (grafting-from) or a pre-synthesized polymer attached to the protein (grafting-to). Both techniques were used to synthesize conjugates of different proteins with thermo-responsive polymers in this thesis.
First, conjugates were analyzed by protein NMR spectroscopy. Typical characterization techniques for conjugates can verify the successful conjugation and give hints on the secondary structure of the protein. However, the 3-dimensional structure, being highly important for the protein function, cannot be probed by standard techniques. NMR spectroscopy is a unique method allowing to follow even small alterations in the protein structure. A mutant of the carbohydrate binding module 3b (CBM3bN126W) was used as model protein and functionalized with poly(N-isopropylacrylamide). Analysis of conjugates prepared by grafting-to or grafting-from revealed a strong impact of conjugation type on protein folding. Whereas conjugates prepared by grafting a pre-formed polymer to the protein resulted in complete preservation of protein folding, grafting the polymer from the protein surface led to (partial) disruption of the protein structure.
Next, conjugates of bovine serum albumin (BSA) as cheap and easily accessible protein were synthesized with PNIPAm and different oligoethylene glycol (meth)acrylates. The obtained protein-polymer conjugates were analyzed by an in-line combination of size exclusion chromatography and multi-angle laser light scattering (SEC-MALS). This technique is particular advantageous to determine molar masses, as no external calibration of the system is needed. Different SEC column materials and operation conditions were tested to evaluate the applicability of this system to determine absolute molar masses and hydrodynamic properties of heterogeneous conjugates prepared by grafting-from and grafting-to. Hydrophobic and non-covalent interactions of conjugates lead to error-prone values not in accordance to expected molar masses based on conversions and extents of modifications.
As alternative to this method, conjugates were analyzed by sedimentation velocity analytical ultracentrifugation (SV-AUC) to gain insights in the hydrodynamic properties and how they change after conjugation. Within a centrifugal field, a sample moves and fractionates according to the mass, density, and shape of its individual components. Conjugates of BSA with PNIPAm were analyzed below and above the cloud point temperature of the thermo-responsive polymer component. It was identified that the polymer characteristics were transferred to the conjugate molecule which than showed a decreased ideality – defined as increased deviation from a perfect sphere model – below and increased ideality above the cloud point temperature. This effect can be attributed to an arrangement of the polymer chain pointing towards the solvent (expanded state) or snuggling around the protein surface depending on the applied temperature.
The last project dealt with the synthesis of ferric hydroxamate uptake protein component A (FhuA)-polymer conjugates as building blocks for novel membrane materials. The shape of FhuA can be described as barrel and removal of a cork domain inside the protein results in a passive channel aimed to be utilized as pores in the membrane system. The polymer matrix surrounding the membrane protein is composed of a thermo-responsive and a UV-crosslinkable part. Therefore, an external trigger for covalent immobilization of these building blocks in the membrane and switchability of the membrane between different states was incorporated. The overall performance of membranes prepared by a drying-mediated self-assembly approach was evaluated by permeability and size exclusion experiments. The obtained membranes displayed an insufficiency in interchain crosslinking and therefore a lack in performance. Furthermore, the aimed switch between a hydrophilic and hydrophobic state of the polymer matrix did not occur. Correspondingly, size exclusion experiments did not result in a retention of analytes larger than the pores defined by the dimension of the used FhuA variant.
Overall, different paths to generate protein-polymer conjugates by either grafting-from or grafting-to the protein surface were presented paving the way to the generation of new hybrid materials. Different analytical methods were utilized to describe the folding and hydrodynamic properties of conjugates providing a deeper insight in the overall characteristics of these seminal building blocks.
Detecting and categorizing particular entities in the environment are important visual tasks that humans have had to solve at various points in our evolutionary time. The question arises whether characteristics of entities that were of ecological significance for humans play a particular role during the development of visual categorization.
The current project addressed this question by investigating the effects of developing visual abilities, visual properties and ecological significance on categorization early in life. Our stimuli were monochromatic photographs of structure-like assemblies and surfaces taken from three categories: vegetation, non-living natural elements, and artifacts. A set of computational and rated visual properties were assessed for these stimuli. Three empirical studies applied coherent research concepts and methods in young children and adults, comprising (a) two card-sorting tasks with preschool children (age: 4.1-6.1 years) and adults (age: 18-50 years) which assessed classification and similarity judgments, (b) a gaze contingent eye-tracking search task which investigated the impact of visual properties and category membership on 8-month-olds' ability to segregate visual structure. Because eye-tracking with infants still provides challenges, a methodological study (c) assessed the effect of infant eye-tracking procedures on data quality with 8- to 12-month-old infants and adults.
In the categorization tasks we found that category membership and visual properties impacted the performance of all participant groups. Sensitivity to the respective categories varied between tasks and over the age groups. For example, artifact images hindered infants' visual search but were classified best by adults, whereas sensitivity to vegetation was highest during similarity judgments. Overall, preschool children relied less on visual properties than adults, but some properties (e.g., rated depth, shading) were drawn upon similarly strong. In children and infants, depth predicted task performance stronger than shape-related properties. Moreover, children and infants were sensitive to variations in the complexity of low-level visual statistics. These results suggest that classification of visual structures, and attention to particular visual properties is affected by the functional or ecological significance these categories and properties may have for each of the respective age groups.
Based on this, the project highlights the importance of further developmental research on visual categorization with naturalistic, structure-like stimuli. As intended with the current work, this would allow important links between developmental and adult research.
History of Forgetfulness
(2021)
Forming as a result of the collision between the Adriatic and European plates, the Alpine orogen exhibits significant lithospheric heterogeneity due to the long history of interplay between these plates, other continental and oceanic blocks in the region, and inherited features from preceeding orogenies. This implies that the thermal and rheological configuration of the lithosphere also varies significantly throughout the region. Lithology and temperature/pressure conditions exert a first order control on rock strength, principally via thermally activated creep deformation and on the distribution at depth of the brittle-ductile transition zone, which can be regarded as the lower bound to the seismogenic zone. Therefore, they influence the spatial distribution of seismicity within a lithospheric plate. In light of this, accurately constrained geophysical models of the heterogeneous Alpine lithospheric configuration, are crucial in describing regional deformation patterns. However, despite the amount of research focussing on the area, different hypotheses still exist regarding the present-day lithospheric state and how it might relate to the present-day seismicity distribution.
This dissertaion seeks to constrain the Alpine lithospheric configuration through a fully 3D integrated modelling workflow, that utilises multiple geophysical techniques and integrates from all available data sources. The aim is therefore to shed light on how lithospheric heterogeneity may play a role in influencing the heterogeneous patterns of seismicity distribution observed within the region. This was accomplished through the generation of: (i) 3D seismically constrained, structural and density models of the lithosphere, that were adjusted to match the observed gravity field; (ii) 3D models of the lithospheric steady state thermal field, that were adjusted to match observed wellbore temperatures; and (iii) 3D rheological models of long term lithospheric strength, with the results of each step used as input for the following steps.
Results indicate that the highest strength within the crust (~ 1 GPa) and upper mantle (> 2 GPa), are shown to occur at temperatures characteristic for specific phase transitions (more felsic crust: 200 – 400 °C; more mafic crust and upper lithospheric mantle: ~600 °C) with almost all seismicity occurring in these regions. However, inherited lithospheric heterogeneity was found to significantly influence this, with seismicity in the thinner and more mafic Adriatic crust (~22.5 km, 2800 kg m−3, 1.30E-06 W m-3) occuring to higher temperatures (~600 °C) than in the thicker and more felsic European crust (~27.5 km, 2750 kg m−3, 1.3–2.6E-06 W m-3, ~450 °C). Correlation between seismicity in the orogen forelands and lithospheric strength, also show different trends, reflecting their different tectonic settings. As such, events in the plate boundary setting of the southern foreland correlate with the integrated lithospheric strength, occurring mainly in the weaker lithosphere surrounding the strong Adriatic indenter. Events in the intraplate setting of the northern foreland, instead correlate with crustal strength, mainly occurring in the weaker and warmer crust beneath the Upper Rhine Graben.
Therefore, not only do the findings presented in this work represent a state of the art understanding of the lithospheric configuration beneath the Alps and their forelands, but also a significant improvement on the features known to significantly influence the occurrence of seismicity within the region. This highlights the importance of considering lithospheric state in regards to explaining observed patterns of deformation.
This work develops hybrid methods of imaging spectroscopy for open pit mining and examines their feasibility compared with state-of-the-art. The material distribution within a mine face differs in the small scale and within daily assigned extraction segments. These changes can be relevant to subsequent processing steps but are not always visually identifiable prior to the extraction. Misclassifications that cause false allocations of extracted material need to be minimized in order to reduce energy-intensive material re-handling. The use of imaging spectroscopy aspires to the allocation of relevant deposit-specific materials before extraction, and allows for efficient material handling after extraction. The aim of this work is the parameterization of imaging spectroscopy for pit mining applications and the development and evaluation of a workflow for a mine face, ground- based, spectral characterization. In this work, an application-based sensor adaptation is proposed. The sensor complexity is reduced by down-sampling the spectral resolution of the system based on the samples’ spectral characteristics. This was achieved by the evaluation of existing hyperspectral outcrop analysis approaches based on laboratory sample scans from the iron quadrangle in Minas Gerais, Brazil and by the development of a spectral mine face monitoring workflow which was tested for both an operating and an inactive open pit copper mine in the Republic of Cyprus.
The workflow presented here is applied to three regional data sets: 1) Iron ore samples from Brazil, (laboratory); 2) Samples and hyperspectral mine face imagery from the copper-gold-pyrite mine Apliki, Republic of Cyprus (laboratory and mine face data); and 3) Samples and hyperspectral mine face imagery from the copper-gold-pyrite deposit Three Hills, Republic of Cyprus (laboratory and mine face data). The hyperspectral laboratory dataset of fifteen Brazilian iron ore samples was used to evaluate different analysis methods and different sensor models. Nineteen commonly used methods to analyze and map hyperspectral data were compared regarding the methods’ resulting data products and the accuracy of the mapping and the analysis computation time. Four of the evaluated methods were determined for subsequent analyses to determine the best-performing algorithms: The spectral angle mapper (SAM), a support vector machine algorithm (SVM), the binary feature fitting algorithm (BFF) and the EnMap geological mapper (EnGeoMap). Next, commercially available imaging spectroscopy sensors were evaluated for their usability in open pit mining conditions. Step-wise downsampling of the data - the reduction of the number of bands with an increase of each band’s bandwidth - was performed to investigate the possible simplification and ruggedization of a sensor without a quality fall-off of the mapping results. The impact of the atmosphere visible in the spectrum between 1300–2010nm was reduced by excluding the spectral range from the data for mapping. This tested the feasibility of the method under realistic open pit data conditions. Thirteen datasets based on the different, downsampled sensors were analyzed with the four predetermined methods. The optimum sensor for spectral mine face material distinction was determined as a VNIR-SWIR sensor with 40nm bandwidths in the VNIR and 15nm bandwidths in the SWIR spectral range and excluding the atmospherically impacted bands. The Apliki mine sample dataset was used for the application of the found optimal analyses and sensors. Thirty-six samples were analyzed geochemically and mineralogically. The sample spectra were compiled to two spectral libraries, both distinguishing between seven different geochemical-spectral clusters. The reflectance dataset was downsampled to five different sensors. The five different datasets were mapped with the SAM, BFF and SVM method achieving mapping accuracies of 85-72%, 85-76% and 57-46% respectively. One mine face scan of Apliki was used for the application of the developed workflow. The mapping results were validated against the geochemistry and mineralogy of thirty-six documented field sampling points and a zonation map of the mine face which is based on sixty-six samples and field mapping. The mine face was analyzed with SAM and BFF. The analysis maps were visualized on top of a Structure-from-Motion derived 3D model of the open pit. The mapped geological units and zones correlate well with the expected zonation of the mine face. The third set of hyperspectral imagery from Three Hills was available for applying the fully-developed workflow. Geochemical sample analyses and laboratory spectral data of fifteen different samples from the Three Hills mine, Republic of Cyprus, were used to analyse a downsampled mine face scan of the open pit. Here, areas of low, medium and high ore content were identified.
The developed workflow is successfully applied to the open pit mines Apliki and Three Hills and the spectral maps reflect the prevailing geological conditions. This work leads through the acquisition, preparation and processing of imaging spectroscopy data, the optimum choice of analysis methodology, and the utilization of simplified, robust sensors that meet the requirements of open pit mining conditions. It accentuates the importance of a site-specific and deposit-specific spectral library for the mine face analysis and underlines the need for geological and spectral analysis experts to successfully implement imaging spectroscopy in the field of open pit mining.
Identification of chemical mediators that regulate the specialized metabolism in Nostoc punctiforme
(2021)
Specialized metabolites, so-called natural products, are produced by a variety of different organisms, including bacteria and fungi. Due to their wide range of different biological activities, including pharmaceutical relevant properties, microbial natural products are an important source for drug development. They are encoded by biosynthetic gene clusters (BGCs), which are a group of locally clustered genes. By screening genomic data for genes encoding typical core biosynthetic enzymes, modern bioinformatical approaches are able to predict a wide range of BGCs. To date, only a small fraction of the predicted BGCs have their associated products identified.
The phylum of the cyanobacteria has been shown to be a prolific, but largely untapped source for natural products. Especially multicellular cyanobacterial genera, like Nostoc, harbor a high amount of BGCs in their genomes.
A main goal of this study was to develop new concepts for the discovery of natural products in cyanobacteria. Due to its diverse setup of orphan BGCs and its amenability to genetic manipulation, Nostoc punctiforme PCC 73102 (N. punctiforme) appeared to be a promising candidate to be established as a model organism for natural product discovery in cyanobacteria. By utilizing a combination of genome-mining, bioactivity-screening, variations of culture conditions, as well as metabolic engineering, not only two new polyketides were discovered, but also first-time insights into the regulation of the specialized metabolism in N. punctiforme were gained during this study.
The cultivation of N. punctiforme to very high densities by utilizing increasing light intensities and CO2 levels, led to an enhanced metabolite production, causing rather complex metabolite extracts. By utilizing a library of CFP reporter mutant strains, each strain reporting for one of the predicted BGCs, it was shown that eight out of 15 BGCs were upregulated under high density (HD) cultivation conditions. Furthermore, it could be demonstrated that the supernatant of an HD culture can increase the expression of four of the influenced BGCs, even under conventional cultivation conditions. This led to the hypothesis that a chemical mediator encoded by one of the affected BGCs is accumulating in the HD supernatant and is able to increase the expression of other BGCs as part of a cell-density dependent regulatory circuit. To identify which of the BGCs could be a main trigger of the presumed regulatory circuit, it was tried to activate four BGCs (pks1, pks2, ripp3, ripp4) selectively by overexpression of putative pathway-specific regulatory genes that were found inside the gene clusters. Transcriptional analysis of the mutants revealed that only the mutant strain targeting the pks1 BGC, called AraC_PKS1, was able to upregulate the expression of its associated BGC. From an RNA sequencing study of the AraC_PKS1 mutant strain, it was discovered that beside pks1, the orphan BGCs ripp3 and ripp4 were also upregulated in the mutant strain. Furthermore, it was observed that secondary metabolite production in the AraC_PKS1 mutant strain is further enhanced under high-light and high-CO2 cultivation conditions. The increased production of the pks1 regulator NvlA also had an impact on other regulatory factors, including sigma factors and the RNA chaperone Hfq. Analysis of the AraC_PKS1 cell and supernatant extracts led to the discovery of two novel polyketides, nostoclide and nostovalerolactone, both encoded by the pks1 BGC. Addition of the polyketides to N. punctiforme WT demonstrated that the pks1-derived compounds are able to partly reproduce the effects on secondary metabolite production found in the AraC_PKS1 mutant strain. This indicates that both compounds are acting as extracellular signaling factors as part of a regulatory network. Since not all transcriptional effects that were found in the AraC_PKS1 mutant strain could be reproduced by the pks1 products, it can be assumed that the regulator NvlA has a global effect and is not exclusively specific to the pks1 pathway.
This study was the first to use a putative pathway specific regulator for the specific activation of BGC expression in cyanobacteria. This strategy did not only lead to the detection of two novel polyketides, it also gave first-time insights into the regulatory mechanism of the specialized metabolism in N. punctiforme. This study illustrates that understanding regulatory pathways can aid in the discovery of novel natural products. The findings of this study can guide the design of new screening strategies for bioactive compounds in cyanobacteria and help to develop high-titer production platforms for cyanobacterial natural products.
The life cycle of higher plants is based on recurring phases of growth and development based on repetitive sequences of cell division, cell expansion and cell differentiation. This dissertation deals with two projects, each of them investigating two different topics that are related to cell expansion. The first project is examining an Arabidopsis thaliana mutant exhibiting overall cell enlargement and the second project is analysing two naturally occurring floral morphs of Amsinckia spectabilis (Boraginaceae) differing (amongst others) in style length and anther heights due to differences in longitudinal cell elongation. The EMS-mutant eop1 was shown to exhibit a petal size increase of 26% caused by cell enlargement. Further phenotypes were detected, such as cotyledon size increase (based on larger cells) as well as increased carpel, sepal, leaf and pollen sizes. Plant height was shown to be increased and more highly branched trichomes explained the hairy eop1 phenotype. Fine mapping revealed the causal SNP to be a C to T transition at the last nucleotide of intron 7 of the INCURVATA11 (ICU11) gene, a 2-oxoglutarate /Fe(II)-dependant dioxygenase, and thus causing missplicing of the mRNA. Two T-DNA insertion lines (icu11-2 & icu11-4) confirmed ICU11 as causal gene by exhibiting increased petal size. A comparison of three icu11 alleles, which possessed different mutation-related changes, either overexpressing ICU11 or modified mRNAs, was the base for investigating the molecular mechanism that underlies the observed phenotype. Different approaches revealed contradictory results regarding ICU11 protein functionality in the icu11 mutants. A complementation assay proved the three mutants to be exchangeable and ICU11 overexpression in the wild-type led to an icu11-like phenotype, arguing for all three icu11 mutants to be GOF mutants. Contradicting this conclusion, the icu11-4 line could be rescued by a genomic ICU11 transgene. A model, based on the assumption that an overexpression of ICU11 is inhibiting the function of the protein, and thus causing the same effect as a LOF protein was proposed. Further, icu11-3 (eop1) mutants were shown to have an increased resistance towards paclobutrazol, a gibberellin (GA) inhibitor and an upregulation of AtGA20ox2, a main GA biosynthesis gene. Additionally, ICU11 subcellular localization was discovered to be cytoplasmic, supporting the assumption, that ICU11 affects GA biosynthesis and overall GA level, possibly explaining the observed (GA-overdose) phenotype.
The second project aimed to identify the genetic base of the S-locus in Amsinckia spectabilis, as the Amsinckia genus represents untypical characteristics for a heterostylous species, such as no obvious self-incompatibility (SI) and the repeated transition towards homostylous and fully selfing variants. The work was based on three Amsinckia spectabilis forms: a heterostylous form, consisting of two floral morphs with reciprocal positioning of sexual organs (S-morph: high anthers and a short style and L-morph: low anthers and a long style), and two homostylous forms, one large-flowered and partially selfing and the other small-flowered and fully selfing. The maintenance of the two floral morphs is genetically based on the S-locus region, containing genes that encode for the morph-specific traits, which are marked by a tight linkage due to suppressed recombination. Natural populations are found to possess a 1:1 S:L morph ratio, that can be explained by predominant disassortative mating of the two morphs, causing the occurrence of the dominant S-allele only in the heterozygous state (heterozygous (Ss) for the S-morph and homozygous recessive (ss) for the L-morph). Investigation of morph-specific phenotypes detected 56% elongated L-morph styles and 58% higher positioned S-morph anthers. Approximately 50% of the observed size differences were explained by an increase in cell elongation. Moreover, additional phenotypes were found, such as 21% enlarged S-morph pollen and no obvious SI, confirmed by hand pollinated seed counts, in vivo pollen tube growth and the development of homozygous dominant SS individuals via selfing. The Amsinckia spec. S-locus was assumed to at least consist of the G- (style length), the A- (anther height) and the P- (pollen size) locus. Comparative Transcriptomics of the two morphs revealed 22 differentially expressed markers that were found to be located within two contigs of a SS individual PacBio genome assembly, allowing the localization of the S-locus to be delimited to a region of approximately 23 Mb. Contradictory to revealed S-loci within the plant kingdom, no strong argument for a present hemizygous region was found to be causal for the suppressed recombination of the S-locus, so that an inversion was assumed to be the causal mechanism.
Cyanobacteria are an abundant bacterial group and are found in a variety of ecological niches all around the globe. They can serve as a real threat for fish or mammals and can restrict the use of lakes or rivers for recreational purposes or as a source of drinking water, when they form blooms. One of the most abundant bloom-forming cyanobacteria is Microcystis aeruginosa.
In the first part of the study, the role and possible dynamics of RubisCO in M. aeruginosa during high-light irradiation were examined. Its response was analyzed on the protein and peptide level via immunoblotting, immunofluorescence microscopy and with high performance liquid chromatography (HPLC). It was revealed that large amounts of RubisCO were located outside of carboxysomes under the applied high light stress. RubisCO aggregated mainly underneath the cytoplasmic membrane. There it forms a putative Calvin-Benson-Bassham (CBB) super complex together with other enzymes of photosynthesis. This complex could be part of an alternative carbon-concentrating mechanism (CCM) in M. aeruginosa, which enables a faster, and energy saving adaptation to high light stress of the whole bloom.
Furthermore, the re-localization of RubisCO was delayed in the microcystin-deficient mutant ΔmcyB and RubisCO was more evenly distributed over the cell in comparison to the wild type. Since ΔmcyB is not harmed in its growth, possibly other produced cyanopeptides as aeruginosin or cyanopeptolin also play a role in the stabilization of RubisCO and the putative CBB complex, especially in the microcystin-free mutant.
In the second part of this work, the possible role of microcystin as an extracellular signaling peptide during the diurnal cycle was studied. HPLC analysis showed a strong increase of extracellular microcystin in the wild type when the population entered nighttime and it resumed into the next day as well. Together with the increase of extracellular microcystin, a strong decrease of protein-bound intracellular microcystin was observed via immunoblot analysis. Interestingly, the signal of the large subunit of RubisCO (RbcL) also diminished when high amounts of microcystin were present in the surrounding medium. Microcystin addition experiments to M. aeruginosa WT and ΔmcyB cultures support this observation, since the immunoblot signal of both subunits of RubisCO and CcmK, a shell protein of carboxysomes, diminished after the addition of microcystin. In addition, the fluctuation of cyanopeptolin during the diurnal cycle indicates a more prominent role of other cyanopeptides besides microcystin as a signaling peptide, intracellularly as well as extracellularly.
Anthropogenic activities such as continuous landscape changes threaten biodiversity at both local and regional scales. Metacommunity models attempt to combine these two scales and continuously contribute to a better mechanistic understanding of how spatial processes and constraints, such as fragmentation, affect biodiversity. There is a strong consensus that such structural changes of the landscape tend to negatively effect the stability of metacommunities. However, in particular the interplay of complex trophic communities and landscape structure is not yet fully understood.
In this present dissertation, a metacommunity approach is used based on a dynamic and spatially explicit model that integrates population dynamics at the local scale and dispersal dynamics at the regional scale. This approach allows the assessment of complex spatial landscape components such as habitat clustering on complex species communities, as well as the analysis of population dynamics of a single species. In addition to the impact of a fixed landscape structure, periodic environmental disturbances are also considered, where a periodical change of habitat availability, temporally alters landscape structure, such as the seasonal drying of a water body.
On the local scale, the model results suggest that large-bodied animal species, such as predator species at high trophic positions, are more prone to extinction in a state of large patch isolation than smaller species at lower trophic levels.
Increased metabolic losses for species with a lower body mass lead to increased energy limitation for species on higher trophic levels and serves as an explanation for a predominant loss of these species. This effect is particularly pronounced for food webs, where species are more sensitive to increased metabolic losses through dispersal and a change in landscape structure.
In addition to the impact of species composition in a food web for diversity, the strength of local foraging interactions likewise affect the synchronization of population dynamics. A reduced predation pressure leads to more asynchronous population dynamics, beneficial for the stability of population dynamics as it reduces the risk of correlated extinction events among habitats. On the regional scale, two landscape aspects, which are the mean patch isolation and the formation of local clusters of two patches, promote an increase in $\beta$-diversity. Yet, the individual composition and robustness of the local species community equally explain a large proportion of the observed diversity patterns.
A combination of periodic environmental disturbance and patch isolation has a particular impact on population dynamics of a species. While the periodic disturbance has a synchronizing effect, it can even superimpose emerging asynchronous dynamics in a state of large patch isolation and unifies trends in synchronization between different species communities.
In summary, the findings underline a large local impact of species composition and interactions on local diversity patterns of a metacommunity. In comparison, landscape structures such as fragmentation have a negligible effect on local diversity patterns, but increase their impact for regional diversity patterns. In contrast, at the level of population dynamics, regional characteristics such as periodic environmental disturbance and patch isolation have a particularly strong impact and contribute substantially to the understanding of the stability of population dynamics in a metacommunity. These studies demonstrate once again the complexity of our ecosystems and the need for further analysis for a better understanding of our surrounding environment and more targeted conservation of biodiversity.
The prevalence of diseases associated with misfolded proteins increases with age. When cellular defense mechanisms become limited, misfolded proteins form aggregates and may also develop more stable cross-β structures ultimately forming amyloid aggregates. Amyloid aggregates are associated with neurodegenerative diseases such as Alzheimer’s disease and Huntington’s disease. The formation of amyloid deposits, their toxicity and cellular defense mechanisms have been intensively studied. However, surprisingly little is known about the effects of protein aggregates on cellular signal transduction. It is also not understood whether the presence of aggregation-prone, but still soluble proteins affect signal transduction.
In this study, the still soluble aggregation-prone HttExon1Q74 and its amyloid aggregates were used to analyze the effect of amyloid aggregates on internalization and receptor activation of G protein-coupled receptors (GPCRs), the largest protein family of mammalian cell surface receptors involved in signal transduction. The aggregated HttExon1Q74, but not its soluble form, could inhibit ligand-induced clathrin-mediated endocytosis (CME) of various GPCRs. Most likely this inhibitory effect is based on a terminal sequestration of the HSC70 chaperone to the aggregates which is necessary for CME. Using the vasopressinV1a receptor (V1aR) and the corticotropin-releasing factor receptor 1 (CRF1R) as a model, it could be shown that the presence of HttExon1Q74 aggregates and the inhibition of ligand-induced CME leads to an accumulation of desensitized receptors at the plasma membrane. In turn, this disrupts Gq-mediated Ca2+ signaling and Gs-mediated cAMP signaling of the V1aR and the CRF1R respectively. In contrast to HttExon1Q74 amyloid aggregates, soluble HttExon1Q74 as well as amorphous aggregates did not inhibit GPCR internalization and signaling demonstrating that cellular signal transduction mechanisms are specifically impaired in response to the formation of amyloid aggregates.
In addition, preliminary experiments could show that HttExon1Q74 aggregates provoke an increase in membrane expression of a protein from a structurally and functionally unrelated membrane protein family, namely the serotonin transporter SERT. As SERT is the main pharmacological target to treat depression this could shed light on this commonly occurring comorbidity in neurodegenerative diseases, in particular in early disease states.
Artificial light at night (ALAN), one form of human-induced rapid environmental change, is continuously spreading in space and time and increasing in intensity as part of the ongoing urbanization. A vast range of animals is known to be affected by ALAN as, among other things, it can mask natural light cues and change both the perceived as well as the actual predation risk. Since ALAN per se is restricted to the night, the majority of studies so far have focused on nocturnal species or behavioral changes during the night. How polyphasic species respond to ALAN has been largely overlooked, although they can possibly carry over effects of nighttime illumination into the day. Additionally, individuals within a species are known to consistently differ in their personality which includes risk-taking behavior. While this implies that ALAN can lead to varying anti-predatory responses in animals within a population, knowledge on this topic is still very limited. This thesis aims at investigating what initial behavioral reaction is caused by ALAN in polyphasic small mammals while also incorporating an animal’s personality. Nighttime and daytime activity, movement and foraging behavior of the bank vole (Myodes glareolus) were investigated in regards to effects of different light intensities and partial illumination in the laboratory. Additionally, changes in intra- and interspecific interactions of bank voles and striped field mice (Apodemus agrarius) subjected to ALAN were studied in experimental populations in semi-natural outdoor enclosures. Chapter I explores whether behavioral responses to ALAN of varying intensity are related to animal personality. Results showed that bank voles reduced movement and foraging already under dim light and that bold animals generally moved and foraged more than shy animals. Exclusively under bright illumination did bold animals exploit the food patches more than shy animals. The results demonstrate that bank voles are affected by light intensities prevalent in urban habitats. Additionally, certain light scenarios might lead to an advantage of and a shift towards certain personality types. Chapter II focusses on the effects of partial ALAN on foraging behavior of animals with varying animal personalities while extending the view towards possible carry-over effects of ALAN into the daytime. While bank voles reduced foraging behavior in illuminated areas at night, they increased foraging behavior in those areas at the subsequent day. Bold individuals generally had lower giving-up densities than shy individuals but this difference was especially pronounced during daytime at formerly illuminated food patches. Thus, ALAN can have carry-over effects into the daytime in polyphasic animals and thus has the potential to affect daytime intra- and interspecific interactions. Chapter III broadens the view from the individual to the population level. Experimental populations consisting of bank voles and striped field mice were established in large outdoor enclosures successively experienced natural and artificial light conditions at night. VHF telemetry data revealed that animals were predominantly active during the day under natural conditions. This difference between day and night vanished under ALAN. Additionally, conspecifics reduced home range overlap, proximity and activity synchrony while boldness was not associated with behavioral changed due to ALAN. The results suggest that ALAN has the potential to alter intraspecific interactions and thus can have fitness consequences on the population level. Overall, the present thesis shows that ALAN can affect nighttime and daytime behavior as well as intraspecific interactions of polyphasic small mammals. Differences in risk- taking behavior of individuals may vary in importance depending on other environmental variables. Thus, this thesis hopefully triggers broadening the view regarding the role of an animal’s personality in coping with ALAN and the effects on daytime behavior and diurnal species.
The scapula plays a significant role in efficient shoulder movement. Thus, alterations from typical scapular motion during upper limb movements are thought to be associated with shoulder pathologies. However, a clear understanding of the relationship is not yet obtained.. Scapular alterations may only represent physiological variability as their occurrence can appear equally as frequent in individuals with and without shoulder disorders. Evaluation of scapular motion during increased load might be a beneficial approach to detect clinically relevant alterations. However, functional motion adaptations in response to maximum effort upper extremity loading has not been established yet. Therefore, the overall purpose of this research project was to give further insight in physiological adaptations of scapular kinematics and their underlying scapular muscle activity in response to high demanding shoulder movements in healthy asymptomatic individuals. Prior to the investigation of the effect of various load situation, the reproducibility of scapular kinematics and scapular muscle activity were evaluated under maximum effort arm movements. Healthy asymptomatic adults performed unloaded and maximal loaded concentric and eccentric isokinetic shoulder flexion and extension movements in the scapular plane while scapular kinematics and scapular muscle activity were simultaneously assessed. A 3D motion capture system (infra-red cameras & reflective markers) was utilized to track scapular and humerus motion in relation to the thorax. 3D scapular position angles were given for arm raising and lowering between humerus positions of 20° and 120° flexion. To further characterize the scapular pattern, the scapular motion extent and scapulohumeral rhythm (ratio of scapular and humerus motion extent) were determined. Muscle activity of the upper and lower trapezius and the serratus anterior were assessed with surface electromyography. Amplitudes were calculated for the whole ROM and four equidistant movement phases. Reliability was characterized by overall moderate to good reproducibility across the load conditions. Irrespective of applied load, scapular kinematics followed a motion pattern of continuous upward rotation, posterior tilt and external rotation during arm elevation and a continuous downward rotation, anterior tilt and internal rotation during arm lowering. However, kinematics were altered between maximal loaded and unloaded conditions showing increased upward rotation, reduced posterior tilt and external rotation. Further, the scapulohumeral rhythm was decreased and scapular motion extent increased under maximal loaded movements. Muscle activity during maximum effort were of greater magnitude and differed in their pattern in comparison to the continuous increase and decrease of activity during unloaded shoulder flexion and extension. Relationships between scapular kinematics and their underlying scapular muscle activity could only be identified for a few isolated combinations, whereas the majority showed no associations. Scapular kinematics and scapular muscle activity pattern alter according to the applied load. Alterations between the load conditions comply in magnitude and partially in direction with differences seen between symptomatic and asymptomatic individuals. Even though long-term effects of identified adaptations in response to maximum load are so far unclear, deviations from typical scapular motion or muscle activation should not per se be seen as indicators of shoulder impairment. However, evaluation of alterations in scapular motion and activation in response to maximum effort may have the potential to identify individuals that are unable to cope with increased upper limb demands. Findings further challenge the understanding of scapular motion and stabilization by the trapezius and serratus anterior muscles, as clear relationships between the underlying scapular muscle activity and scapular kinematics were neither observed during unloaded nor maximal loaded shoulder movements.
Influenza A virus (IAV) is a pathogen responsible for severe seasonal epidemics threatening human and animal populations every year. During the viral assembly process in the infected cells, the plasma membrane (PM) has to bend in localized regions into a vesicle towards the extracellular side. Studies in cellular models have proposed that different viral proteins might be responsible for inducing membrane curvature in this context (including M1), but a clear consensus has not been reached. M1 is the most abundant protein in IAV particles. It plays an important role in virus assembly and budding at the PM. M1 is recruited to the host cell membrane where it associates with lipids and other viral proteins. However, the details of M1 interactions with the cellular PM, as well as M1-mediated membrane bending at the budozone, have not been clarified.
In this work, we used several experimental approaches to analyze M1-lipids and M1-M1 interactions. By performing SPR analysis, we quantified membrane association for full-length M1 and different genetically engineered M1 constructs (i.e., N- and C-terminally truncated constructs and a mutant of the polybasic region). This allowed us to obtain novel information on the protein regions mediating M1 binding to membranes. By using fluorescence microscopy, cryogenic transmission electron microscopy (cryo-TEM), and three-dimensional (3D) tomography (cryo-ET), we showed that M1 is indeed able to cause membrane deformation on vesicles containing negatively-charged lipids, in the absence of other viral components. Further, sFCS analysis proved that simple protein binding is not sufficient to induce membrane restructuring. Rather, it appears that stable M1-M1 interactions and multimer formation are required to alter the bilayer three-dimensional structure through the formation of a protein scaffold.
Finally, to mimic the budding mechanism in cells that arise by the lateral organization of the virus membrane components on lipid raft domains, we created vesicles with lipid domains. Our results showed that local binding of M1 to spatial confined acidic lipids within membrane domains of vesicles led to local M1 inward curvature.
Intentionality in Sellars
(2021)
This book argues that Sellars’ theory of intentionality can be understood as an advancement of a transcendental philosophical approach. It shows how Sellars develops his theory of intentionality through his engagement with the theoretical philosophy of Immanuel Kant.
The book delivers a provocative reinterpretation of one of the most problematic and controversial concepts of Sellars' philosophy: the picturing-relation. Sellars' theory of intentionality addresses the question of how to reconcile two aspects that seem opposed: the non-relational theory of intellectual and linguistic content and a causal-transcendental theory of representation inspired by the philosophy of the early Wittgenstein. The author explains how both parts cohere in a transcendental account of finite knowledge. He claims that this can only be achieved by reading Sellars as committed to a transcendental methodology inspired by Kant. In a final step, he brings his interpretation to bear on the contemporary metaphilosophical debate on pragmatism and expressivism.
Intentionality in Sellars will be of interest to scholars of Sellars and Kant, as well as researchers working in philosophy of mind, epistemology, and the history of nineteenth- and twentieth-century philosophy.
The objective of this book is to provide ICAO, States, competent authorities and aerodrome operators with a comprehensive overview of legal challenges related to international aerodrome planning. Answers to derived legal questions as well as recommendations thereafter shall help to enhance regulatory systems and to establish a safer aerodrome environment worldwide. Compliant aerodrome planning has an immense impact on the safety of passengers, personnel, aircraft – and of course the airport. Achieving a high safety standard is crucial, as many incidents and accidents in aviation happen at or in the vicinity of airports. Currently, more than 40% of the ICAO Member States do not fully comply with international legal requirements for aerodrome planning. Representatives of ICAO and States, as well as aerodrome and authority personnel, will understand why compliance with the different legal facets of aerodrome planning is challenging and learn how shortcomings can be solved.
Plants possess cell wall, a polysaccharide exoskeleton which encompasses all plant cells. Cell wall gives plant cells mechanical support, defines their shape, enables growth and water transport through a plant. It also has important role in communication with the external environment. Regulation of plant cell wall biosynthesis and cell and organ morphogenesis depends on cell’s ability to detect mechanical signals originating both from the external environment and from internal plant tissues. Thanks to the presence of the cell wall, all living plant cells develop constant internal pressure generated by the active water uptake, known as turgor pressure, which enables them to grow. Thus, actively growing cells in the tissue are exerting mechanical stress to each other. In order to properly coordinate cell growth, tissue morphogenesis and maintain cell-to-cell adhesion, plant cell have to detect these mechanical signals. That is performed by a group of still not well enough characterized plant mechanosensitive proteins. Mechanosensors are proteins capable of detecting changes in mechanical stress patterns and translating them into physiological and developmental outputs. One of plant mechanosensitive proteins, DEFECTIVE KERNEL1 (DEK1) has shown to be a very important in proper plant development. DEK1 bears similarity with animal cysteine proteases of Calpain superfamily. DEK1 is very important for plant development since all null alleles are embryo lethal. During the last 20 years of DEK1 studies, this protein has proven to be a very difficult for different molecular and biochemical manipulations. As a consequence, very little is known about its direct target proteins. Wang and co-workers (2003) and Johnson and co-workers (2008) have given a valuable contribution to biochemical understanding of DEK1 by determining that it functions as Cys-protease in similar way as animal calpains. However, a lot of indirect knowledge was gathered about the effects of disruption and modulation of DEK1 activity. DEK1 is important for proper organ development, epidermal specification, and maintenance. However, some studies have inferred that DEK1 affects expression of different cell wall related genes, and it regulates cell-to-cell adhesion in epidermal cells. This led to two extensive studies (Amanda et al., 2016, 2017) which demonstrated importance of DEK1 in regulation leaf epidermal cell walls in A. thaliana mature leaves and inflorescence stems. These studies demonstrated that DEK1 also influences cell wall thickness and cell-to-cell adhesion and that it could potentially regulate cell growth and expansion. Building up on this research, we decided to try to further characterize molecular and biomechanical aspects of DEK1 mediated cell wall regulation, with special emphasis on regulation of cellulose synthesis. We used two mutant lines, with modulated DEK1 activity, a constitutive overexpressor for DEK1 CALPAIN domain and a point mutant in CALPAIN domain, dek1-4. In Chapter 3 we demonstrated that DEK1 regulates dynamics of Cellulose Synthase Complexes (CSCs). Both lines showed decreased crystalline cellulose contents. This led us to investigate if velocity of CSCs in cotyledons, was affected, since it is known that changes in cellulose contents are often caused by defects in CSC. We found that bothDEK1 modulated lines we used have significantly decreased velocity of CSCs. We have also examined plasma membrane turnover rates of CSCs and found out that after photo-bleaching OE CALPAIN has much faster recovery rates compared to Col-0 wild type, while dek1-4 has lower exocytotic rates of CSCs, and much longer life-time of CSCs inserted into the plasma membrane. These results suggested that DEK1 regulates different aspects of CSC dynamics, possibly through interaction with different regulatory proteins. Decrease in cellulose contents we observed in DEK1 modulated lines, prompted us to investigate how this reflects biomechanics and structural properties of epidermal cotyledon cell walls of DEK1 modulated lines, which is described in Chapter 4. To achieve this, we developed a novel microdissection method for isolation and mechanical and structural characterization of native epidermal cell wall monolayers using atomic force microscopy (AFM). AFM force spectroscopy assays showed that both DEK1 modulated lines had stiffer cell walls compared to Col-0. This was awkward since we initially detected decrease in crystalline cellulose which implied decrease in cell wall stiffness. However, subsequent high-resolution AFM imaging has revealed that DEK1 modulate lines cells walls have their cellulose microfibrils organized in thicker bundles than Col-0. Also, polysaccharide composition analysis has revealed that DEK1 modulated lines have increased abundance of pectins, which could also be responsible for the observed increase in cell wall stiffness. Previous work has shown that different dek1 mutants and modulated lines have defects in cell-to-cell adhesion. This implied that DEK1 may be involved in sensing and/or maintaining cell wall integrity (CWI). We performed several growth assays to determine role of DEK1 in CWI, which is described in Chapter 5. We performed cellulose synthesis perturbation assays with cellulose synthesis inhibitor Isoxaben and obtained very interesting results. While OE CALPAIN plants were hypersensitive to Isoxaben, dek1-4 has shown complete insensitivity. Furthermore, a regular CWI maintenance response, reported in A. thaliana as result of compromised CWI, ectopic lignification in seedlings’ roots was absent in both DEK1 modulated lines we examined. We detected interesting growth response of DEK1 lines to NaCl and mannitol treatments as well. Although these findings are pointing out that DEK1 could be part of CWI signalling pathways, more experiments are necessary to fully elucidate possible role of DEK1 in CWI sensing and/or maintenance pathways, especially to check if DEK1 is interacting with Catharanthus roseus Receptor Like Kinase group of CWI sensors. Studies on 4-month old short day grown DEK1 modulated lines, have shown defects in branching, with development of fasciated stem branches in a DEK1 modulated line overexpressing CALPAIN domain (Amanda et al., 2017). This result pointed out to a possibility that DEK1 may regulate organ morphogenesis and patterning at the level of shoot apical meristem (SAM). Work towards elucidating role of DEK1 in SAM maintenance and organ patterning is detailed in Chapter 6. We determined that OE CALPAIN had significantly larger central zone of SAM as well as larger individual SAM cells in central zone, as well as higher distribution of cell sizes, implying possible cell expansion defects. dek1-4 did not exhibited changes in SAM central zone size or individual stem cell size, but it seemed that it had increased number of stem cells in SAM central zone. Both DEK1 lines had perturbation of phyllotaxis on SAM level, with disturbed divergence angles between floral primordia. Disturbed phyllotaxis was also observed between siliques, in mature plants. In addition to this, OE CALPAIN has exhibited occurrence of multiple (up to four) siliques growing from a single stem node. All this is pointing out that DEK1 might participate in hormone-signalling in the SAM.. DEK1 is a highly intriguing protein. However, since it is a unigene, and in addition to that, a regulatory protease, it probably participates in multiple signalling pathways, which makes understanding its function much more complicated.
The mitochondrial chaperone complex HSP60/HSP10 facilitates mitochondrial protein homeostasis by folding more than 300 mitochondrial matrix proteins. It has been shown previously that HSP60 is downregulated in brains of type 2 diabetic (T2D) mice and patients,
causing mitochondrial dysfunction and insulin resistance. As HSP60 is also decreased in peripheral tissues in T2D animals, this thesis investigated the effect of overall reduced HSP60 in the development of obesity and associated co-morbidities.
To this end, both female and male C57Bl/6N control (i.e. without further alterations in their genome, Ctrl) and heterozygous whole-body Hsp60 knock-out (Hsp60+/-) mice, which exhibit a 50 % reduction of HSP60 in all tissues, were fed a normal chow diet (NCD) or a highfat diet (HFD, 60 % calories from fat) for 16 weeks and were subjected to extensive metabolic phenotyping including indirect calorimetry, NMR spectroscopy, insulin, glucose and pyruvate tolerance tests, vena cava insulin injections, as well as histological and molecular analysis.
Interestingly, NCD feeding did not result in any striking phenotype, only a mild increase in energy expenditure in Hsp60+/- mice. Exposing mice to a HFD however revealed an increased body weight due to higher muscle mass in female Hsp60+/- mice, with a simultaneous decrease in energy expenditure. Additionally, these mice displayed decreased fasting glycemia. Opposingly, male Hsp60+/- compared to control mice showed lower body weight gain due to decreased fat mass and an increased energy expenditure, strikingly independent of lean mass. Further, only male Hsp60+/- mice display improved HOMA-IR and Matsuda
insulin sensitivity indices.
Despite the opposite phenotype in regards to body weight development, Hsp60+/- mice of both sexes show a significantly higher cell number, as well as a reduction in adipocyte size in the subcutaneous and gonadal white adipose tissue (sc/gWAT). Curiously, this adipocyte hyperplasia – usually associated with positive aspects of WAT function – is disconnected from metabolic improvements, as the gWAT of male Hsp60+/- mice shows mitochondrial dysfunction, oxidative stress, and insulin resistance. Transcriptomic analysis of gWAT shows an up
regulation of genes involved in macroautophagy. Confirmatory, expression of microtubuleassociated protein 1A/1B light chain 3B (LC3), as a protein marker of autophagy, and direct measurement of lysosomal activity is increased in the gWAT of male Hsp60+/- mice.
In summary, this thesis revealed a novel gene-nutrient interaction. The reduction of the crucial chaperone HSP60 did not have large effects in mice fed a NCD, but impacted metabolism during DIO in a sex-specific manner, where, despite opposing body weight and
body composition phenotypes, both female and male Hsp60+/- mice show signs of protection from high fat diet-induced systemic insulin resistance.
Halide perovskites are a class of novel photovoltaic materials that have recently attracted much attention in the photovoltaics research community due to their highly promising optoelectronic properties, including large absorption coefficients and long carrier lifetimes. The charge carrier mobility of halide perovskites is investigated in this thesis by THz spectroscopy, which is a contact-free technique that yields the intra-grain sum mobility of electrons and holes
in a thin film.
The polycrystalline halide perovskite thin films, provided from Potsdam University, show moderate mobilities in the range from 21.5 to 33.5 cm2V-1s-1. It is shown in this work that the room temperature mobility is limited by charge carrier scattering at polar optical phonons. The mobility at low temperature is likely to be limited by scattering at charged and neutral impurities at impurity concentration N=1017-1018 cm-3. Furthermore, it is shown that exciton formation
may decrease the mobility at low temperatures. Scattering at acoustic phonons can be neglected at both low and room temperatures. The analysis of mobility spectra over a broad range of temperatures for perovskites with various cation compounds shows that cations have a minor impact on charge carrier mobility.
The low-dimensional thin films of quasi-2D perovskite with different numbers of [PbI6]4−sheets (n=2-4) alternating with long organic spacer molecules were provided by S. Zhang from Potsdam University. They exhibit mobilities in the range from 3.7 to 8 cm2V-1s-1. A clear
decrease of mobility is observed with decrease in number of metal-halide sheets n, which likely arises from charge carrier confinement within metal-halide layers. Modelling the measured THz mobility with the modified Drude-Smith model yields localization length from 0.9 to 3.7 nm, which agrees well on the thicknesses of the metal-halide layers. Additionally, the mobilities are found to be dependent on the orientation of the layers. The charge carrier dynamics is also
dependent on the number of metal-halide sheets n. For the thin films with n =3-4 the dynamics is similar to the 3D MHPs. However, the thin film with n = 2 shows clearly different dynamics, where the signs of exciton formation are observed within 390 fs timeframe after
photoexcitation.
Also, the charge carrier dynamics of CsPbI3 perovskite nanocrystals was investigated, in particular the effect of post treatments on the charge carrier transport.
Investigation of Sirtuin 3 overexpression as a genetic model of fasting in hypothalamic neurons
(2021)
Diabetes is a major public health problem with increasing global prevalence. Type 2 diabetes (T2D), which accounts for 90% of all diagnosed cases, is a complex polygenic disease also modulated by epigenetics and lifestyle factors. For the identification of T2D-associated genes, linkage analyses combined with mouse breeding strategies and bioinformatic tools were useful in the past. In a previous study in which a backcross population of the lean and diabetes-prone dilute brown non-agouti (DBA) mouse and the obese and diabetes-susceptible New Zealand obese (NZO) mouse was characterized, a major diabetes quantitative trait locus (QTL) was identified on chromosome 4. The locus was designated non-insulin dependent diabetes from DBA (Nidd/DBA). The aim of this thesis was (i) to perform a detailed phenotypic characterization of the Nidd/DBA mice, (ii) to further narrow the critical region and (iii) to identify the responsible genetic variant(s) of the Nidd/DBA locus. The phenotypic characterization of recombinant congenic mice carrying a 13.6 Mbp Nidd/DBA fragment with 284 genes presented a gradually worsening metabolic phenotype. Nidd/DBA allele carriers exhibited severe hyperglycemia (~19.9 mM) and impaired glucose clearance at 12 weeks of age. Ex vivo perifusion experiments with islets of 13-week-old congenic mice revealed a tendency towards reduced insulin secretion in homozygous DBA mice. In addition, 16-week-old mice showed a severe loss of β-cells and reduced pancreatic insulin content. Pathway analysis of transcriptome data from islets of congenic mice pointed towards a downregulation of cell survival genes. Morphological analysis of pancreatic sections displayed a reduced number of bi-hormonal cells co-expressing glucagon and insulin in homozygous DBA mice, which could indicate a reduced plasticity of endocrine cells in response to hyperglycemic stress. Further generation and phenotyping of recombinant congenic mice enabled the isolation of a 3.3 Mbp fragment that was still able to induce hyperglycemia and contained 61 genes. Bioinformatic analyses including haplotype mapping, sequence and transcriptome analysis were integrated in order to further reduce the number of candidate genes and to identify the presumable causative gene variant. Four putative candidate genes (Ttc39a, Kti12, Osbpl9, Calr4) were defined, which were either differentially expressed or carried a sequence variant. In addition, in silico ChIP-Seq analyses of the 3.3 Mbp region indicated a high number of SNPs located in active regions of binding sites of β-cell transcription factors. This points towards potentially altered cis-regulatory elements that could be responsible for the phenotype conferred by the Nidd/DBA locus. In summary, the Nidd/DBA locus mediates impaired glucose homeostasis and reduced insulin secretion capacity which finally leads to β-cell death. The downregulation of cell survival genes and reduced plasticity of endocrine cells could further contribute to the β-cell loss. The critical region was narrowed down to a 3.3 Mbp fragment containing 61 genes, of which four might be involved in the development of the diabetogenic Nidd/DBA phenotype.
Carbonatite magmatism is a highly efficient transport mechanism from Earth’s mantle to the crust, thus providing insights into the chemistry and dynamics of the Earth’s mantle. One evolving and promising tool for tracing magma interaction are stable iron isotopes, particularly because iron isotope fractionation is controlled by oxidation state and bonding environment. Meanwhile, a large data set on iron isotope fractionation in igneous rocks exists comprising bulk rock compositions and fractionation between mineral groups. Iron isotope data from natural carbonatite rocks are extremely light and of remarkably high variability. This resembles iron isotope data from mantle xenoliths, which are characterized by a variability in δ56Fe spanning three times the range found in basalts, and by the extremely light values of some whole rock samples, reaching δ56Fe as low as -0.69 ‰ in a spinel lherzolite. Cause to this large range of variations may be metasomatic processes, involving metasomatic agents like volatile bearing high-alkaline silicate melts or carbonate melts. The expected effects of metasomatism on iron isotope fractionation vary with parameters like melt/rock-ratio, reaction time, and the nature of metasomatic agents and mineral reactions involved. An alternative or additional way to enrich light isotopes in the mantle could be multiple phases of melt extraction. To interpret the existing data sets more knowledge on iron isotope fractionation factors is needed.
To investigate the behavior of iron isotopes in the carbonatite systems, kinetic and equilibration experiments in natro-carbonatite systems between immiscible silicate and carbonate melts were performed in an internally heated gas pressure vessel at intrinsic redox conditions at temperatures between 900 and 1200 °C and pressures of 0.5 and 0.7 GPa. The iron isotope compositions of coexisting silicate melt and carbonate melt were analyzed by solution MC-ICP-MS. The kinetic experiments employing a Fe-58 spiked starting material show that isotopic equilibrium is obtained after 48 hours. The experimental studies of equilibrium iron isotope fractionation between immiscible silicate and carbonate melts have shown that light isotopes are enriched in the carbonatite melt. The highest Δ56Fesil.m.-carb.melt (mean) of 0.13 ‰ was determined in a system with a strongly peralkaline silicate melt composition (ASI ≥ 0.21, Na/Al ≤ 2.7). In three systems with extremely peralkaline silicate melt compositions (ASI between 0.11 and 0.14) iron isotope fractionation could analytically not be resolved. The lowest Δ56Fesil.m.-carb.melt (mean) of 0.02 ‰ was determined in a system with an extremely peralkaline silicate melt composition (ASI ≤ 0.11 , Na/Al ≥ 6.1). The observed iron isotope fractionation is most likely governed by the redox conditions of the system. Yet, in the systems, where no fractionation occurred, structural changes induced by compositional changes possibly overrule the influence of redox conditions. This interpretation implicates, that the iron isotope system holds the potential to be useful not only for exploring redox conditions in magmatic systems, but also for discovering structural changes in a melt.
In situ iron isotope analyses by femtosecond laser ablation coupled to MC-ICP-MS on magnetite and olivine grains were performed to reveal variations in iron isotope composition on the micro scale. The investigated sample is a melilitite bomb from the Salt Lake Crater group at Honolulu (Oahu, Hawaii), showing strong evidence for interaction with a carbonatite melt. While magnetite grains are rather homogeneous in their iron isotope compositions, olivine grains span a far larger range in iron isotope ratios. The variability of δ56Fe in magnetite is limited from - 0.17 ‰ (± 0.11 ‰, 2SE) to +0.08 ‰ (± 0.09 ‰, 2SE). δ56Fe in olivine range from -0.66‰ (± 0.11 ‰, 2SE) to +0.10 ‰ (± 0.13 ‰, 2SE). Olivine and magnetite grains hold different informations regarding kinetic and equilibrium fractionation due to their different Fe diffusion coefficients. The observations made in the experiments and in the in situ iron isotope analyses suggest that the extremely light iron isotope signatures found in carbonatites are generated by several steps of isotope fractionation during carbonatite genesis. These may involve equilibrium and kinetic fractionation. Since iron isotopic signatures in natural systems are generated by a combination of multiple factors (pressure, temperature, redox conditions, phase composition and structure, time scale), multi tracer approaches are needed to explain signatures found in natural rocks.
Modern knowledge bases contain and organize knowledge from many different topic areas. Apart from specific entity information, they also store information about their relationships amongst each other. Combining this information results in a knowledge graph that can be particularly helpful in cases where relationships are of central importance. Among other applications, modern risk assessment in the financial sector can benefit from the inherent network structure of such knowledge graphs by assessing the consequences and risks of certain events, such as corporate insolvencies or fraudulent behavior, based on the underlying network structure. As public knowledge bases often do not contain the necessary information for the analysis of such scenarios, the need arises to create and maintain dedicated domain-specific knowledge bases.
This thesis investigates the process of creating domain-specific knowledge bases from structured and unstructured data sources. In particular, it addresses the topics of named entity recognition (NER), duplicate detection, and knowledge validation, which represent essential steps in the construction of knowledge bases.
As such, we present a novel method for duplicate detection based on a Siamese neural network that is able to learn a dataset-specific similarity measure which is used to identify duplicates. Using the specialized network architecture, we design and implement a knowledge transfer between two deduplication networks, which leads to significant performance improvements and a reduction of required training data.
Furthermore, we propose a named entity recognition approach that is able to identify company names by integrating external knowledge in the form of dictionaries into the training process of a conditional random field classifier. In this context, we study the effects of different dictionaries on the performance of the NER classifier. We show that both the inclusion of domain knowledge as well as the generation and use of alias names results in significant performance improvements.
For the validation of knowledge represented in a knowledge base, we introduce Colt, a framework for knowledge validation based on the interactive quality assessment of logical rules. In its most expressive implementation, we combine Gaussian processes with neural networks to create Colt-GP, an interactive algorithm for learning rule models. Unlike other approaches, Colt-GP uses knowledge graph embeddings and user feedback to cope with data quality issues of knowledge bases. The learned rule model can be used to conditionally apply a rule and assess its quality.
Finally, we present CurEx, a prototypical system for building domain-specific knowledge bases from structured and unstructured data sources. Its modular design is based on scalable technologies, which, in addition to processing large datasets, ensures that the modules can be easily exchanged or extended. CurEx offers multiple user interfaces, each tailored to the individual needs of a specific user group and is fully compatible with the Colt framework, which can be used as part of the system.
We conduct a wide range of experiments with different datasets to determine the strengths and weaknesses of the proposed methods. To ensure the validity of our results, we compare the proposed methods with competing approaches.
Learning analytics at scale
(2021)
Digital technologies are paving the way for innovative educational approaches. The learning format of Massive Open Online Courses (MOOCs) provides a highly accessible path to lifelong learning while being more affordable and flexible than face-to-face courses. Thereby, thousands of learners can enroll in courses mostly without admission restrictions, but this also raises challenges. Individual supervision by teachers is barely feasible, and learning persistence and success depend on students' self-regulatory skills. Here, technology provides the means for support. The use of data for decision-making is already transforming many fields, whereas in education, it is still a young research discipline. Learning Analytics (LA) is defined as the measurement, collection, analysis, and reporting of data about learners and their learning contexts with the purpose of understanding and improving learning and learning environments. The vast amount of data that MOOCs produce on the learning behavior and success of thousands of students provides the opportunity to study human learning and develop approaches addressing the demands of learners and teachers.
The overall purpose of this dissertation is to investigate the implementation of LA at the scale of MOOCs and to explore how data-driven technology can support learning and teaching in this context. To this end, several research prototypes have been iteratively developed for the HPI MOOC Platform. Hence, they were tested and evaluated in an authentic real-world learning environment. Most of the results can be applied on a conceptual level to other MOOC platforms as well. The research contribution of this thesis thus provides practical insights beyond what is theoretically possible. In total, four system components were developed and extended:
(1) The Learning Analytics Architecture: A technical infrastructure to collect, process, and analyze event-driven learning data based on schema-agnostic pipelining in a service-oriented MOOC platform. (2) The Learning Analytics Dashboard for Learners: A tool for data-driven support of self-regulated learning, in particular to enable learners to evaluate and plan their learning activities, progress, and success by themselves. (3) Personalized Learning Objectives: A set of features to better connect learners' success to their personal intentions based on selected learning objectives to offer guidance and align the provided data-driven insights about their learning progress. (4) The Learning Analytics Dashboard for Teachers: A tool supporting teachers with data-driven insights to enable the monitoring of their courses with thousands of learners, identify potential issues, and take informed action.
For all aspects examined in this dissertation, related research is presented, development processes and implementation concepts are explained, and evaluations are conducted in case studies. Among other findings, the usage of the learner dashboard in combination with personalized learning objectives demonstrated improved certification rates of 11.62% to 12.63%. Furthermore, it was observed that the teacher dashboard is a key tool and an integral part for teaching in MOOCs. In addition to the results and contributions, general limitations of the work are discussed—which altogether provide a solid foundation for practical implications and future research.
Learning to read in German
(2021)
In the present dissertation, the development of eye movement behavior and the perceptual span of German beginning readers was investigated in Grades 1 to 3 (Study 1) and longitudinally within a one-year time interval (Study 2), as well as in relation to intrinsic and extrinsic reading motivation (Study 3). The presented results are intended to fill the gap of only sparse information on young readers’ eye movements and completely missing information on German young readers’ perceptual span and its development. On the other hand, reading motivation data have been scrutinized with respect to reciprocal effects on reading comprehension but not with respect to more immediate, basic cognitive processing (e.g., word decoding) that is indicated by different eye movement measures. Based on a longitudinal study design, children in Grades 1–3 participated in a moving window reading experiment with eye movement recordings in two successive years. All children were participants of a larger longitudinal study on intrapersonal developmental risk factors in childhood and adolescence (PIER study). Motivation data and other psychometric reading data were collected during individual inquiries and tests at school. Data analyses were realized in three separate studies that focused on different but related aspects of reading and perceptual span development. Study 1 presents the first cross-sectional report on the perceptual span of beginning German readers. The focus was on reading rate changes in Grades 1 to 3 and on the issue of the onset of the perceptual span development and its dependence on basic foveal reading processes. Study 2 presents a successor of Study 1 providing first longitudinal data of the perceptual span in elementary school children. It also includes information on the stability of observed and predicted reading rates and perceptual span sizes and introduces a new measure of the perceptual span based on nonlinear mixed-effects models. Another issue addressed in this study is the longitudinal between-group comparison of slower and faster readers which refers to the detection of developmental patterns. Study 3 includes longitudinal reading motivation data and investigates the relation between different eye movement measures including perceptual span and intrinsic as well as extrinsic reading motivation. In Study 1, a decelerated increase in reading rate was observed between Grades 1 to 3. Grade effects were also reported for saccade length, refixation probability, and different fixation duration measures. With higher grade, mean saccade length increased, whereas refixation probability, first-fixation duration, gaze duration, and total reading time decreased. Perceptual span development was indicated by an increase in window size effects with grade level. Grade level differences with respect to window size effects were stronger between Grades 2 and 3 than between Grades 1 and 2. These results were replicated longitudinally in Study 2. Again, perceptual span size significantly changed between Grades 2 and 3, but not between Grades 1 and 2 or Grades 3 and 4. Observed and predicted reading rates were found to be highly stable after first grade, whereas stability of perceptual span was only moderate for all grade levels. Group differences between slower and faster readers in Year 1 remained observable in Year 2 showing a pattern of stable achievement differences rather than a compensatory pattern. Between Grades 2 and 3, between-group differences in reading rate even increased resulting in a Matthew effect. A similar effect was observed for perceptual span development between Grades 3 and 4. Finally, in Study 3, significant relations between beginning readers’ eye movements and their reading motivation were observed. In both years of measurement, higher intrinsic reading motivation was related to more skilled eye movement patterns as indicated by short fixations, longer saccades, and higher reading rates. In Year 2, intrinsic reading motivation was also significantly and negatively correlated with refixation probability. These correlational patterns were confirmed in cross-sectional linear models controlling for grade level and reading amount and including both reading motivation measures, extrinsic and intrinsic motivation. While there were significant positive relations between intrinsic reading motivation and word decoding as indicated by the above stated eye movement measures, extrinsic reading motivation only predicted variance in eye movements in Year 2 (significant for fixation durations and reading rate), with a consistently opposite pattern of effects as compared to intrinsic reading motivation. Finally, longitudinal effects of Year 1 intrinsic reading motivation on Year 2 word decoding were observed for gaze duration, total reading time, refixation probability, and perceptual span within cross-lagged panel models. These effects were reciprocal because all eye movement measures significantly predicted variance in intrinsic reading motivation. Extrinsic reading motivation in Year 1 did not affect any eye movement measure in Year 2, and vice versa, except for a significant, negative relation with perceptual span. Concluding, the present dissertation demonstrates that largest gains in reading development in terms of eye movement changes are observable between Grades 1 and 2. Together with the observed pattern of stable differences between slower and faster readers and a widening achievement gap between Grades 2 and 3 for reading rate, these results underline the importance of the first year(s) of formal reading instruction. The development of the perceptual span lags behind as it is most apparent between Grades 2 and 3. This suggests that efficient parafoveal processing presupposes a certain degree of foveal reading proficiency (e.g., word decoding). Finally, this dissertation demonstrates that intrinsic reading motivation—but not extrinsic motivation—effectively supports the development of skilled reading.
Silicate melts are major components of the Earth’s interior and as such they make an essential contribution in igneous processes, in the dynamics of the solid Earth and the chemical development of the entire Earth. Macroscopic physical and chemical properties such as density, compressibility, viscosity, degree of polymerization etc. are determined by the atomic structure of the melt. Depending on the pressure, but also on the temperature and the chemical composition, silicate melts show different structural properties. These properties are best described by the local coordination environment, i.e. symmetry and number of neighbors (coordination number) of an atom, as well as the distance between the central atom and its neighbors (inter-atomic distance). With increasing pressure and temperature, i.e. with increasing depth in the Earth, the density of the melt increases, which can lead to changes in coordination number and distances. If the coordination number remains the same, the distance usually decreases. If the coordination number increases, the distance can increase. These general trends can, however, vary greatly, which can be attributed in particular to the chemical composition.
Due to the fact that natural melts of the deep earth are not accessible to direct investigations, in order to understand their properties under the relevant conditions, extensive experimental and theoretical investigations have been carried out so far. This has often been studied using the example of amorphous samples of the end-members SiO2 and GeO2 , with the latter serving as a structural and chemical analog model to SiO2. Commonly, the experiments were carried out at high pressure and at room temperature. Natural melts are chemically much more complex than the simple end-member SiO2 and GeO2, so that observations made on them may lead to incorrect compression models. Furthermore, the investigations on glasses at room temperature can show potentially strong deviations from the properties of melts under natural thermodynamic conditions.
The aim of this thesis was to explain the influence of the composition and the temperature on the structural properties of the melts at high pressures. To understand this, we studied complex alumino-germanate and alumino-silicate glasses. More precisely, we studied synthetic glasses that have a composition like the mineral albite and like a mixture of albite-diopside at the eutectic point. The albite glass is structurally similar to a simplified granitic melt, while the albite-diopside glass simulates a simplified basaltic melt. To study the local coordination environment of the elements, we used X-ray absorption spectroscopy in combination with a diamond anvil cell. Because the diamonds have a high absorbance for X-rays with energies below 10 keV, the direct investigation of the geologically relevant elements such as Si, Al, Ca, Mg etc. with this spectroscopic probe technique in combination with a diamond anvil cell is not possible. Therefore the glasses were doped with Ge and Sr. These elements serve partially or fully as substitutes for important major elements. In this sense, Ge serves as an a substitute for Si and other network formers, while Sr replaces network modifiers such as Ca, Na, Mg etc.,
as well as other cations with a large ionic radius.
In the first step we studied the Ge K-edge in Ge-Albit-glass, NaAlGe3O8, at room temperature up to 131 GPa. This glass has a higher chemical complexity than SiO2 and GeO2, but it is still fully polymerized. The differences in the compression mechanism between this glass and the simple oxides can clearly be attributed to higher chemical complexity. The albite and albite-diopside compositions partially doped with Ge and Sr were probed at room temperature for Ge up to 164 GPa and for Sr up to 42 GPa. While the albite glass is nominally fully polymerized like NaAlGe3O8, the albite-diopside glass is partially depolymerized. The results show that structural changes take place in all three glasses in the first 25 to a maximum of 30 GPa, with both Ge and Sr reaching the maximum coordination number 6 and ∼9, respectively. At higher pressures, only isostructural shrinkage of the coordination polyhedra takes place in the glasses. The most important finding of the high pressure studies on the alumino-silicate and alumino-germanate glasses is that in these complex glasses the polyhedra show a much higher compressibility than what can be observed in the end-members. This is shown in particular by the strong shortening of the Ge-O distances in the amorphous NaAlGe3O8 and albite-diopside glass at pressures above 30 GPa.
In addition to the effects of the composition on the compaction process, we investigated the influence of temperature on the structural changes. To do this, we probed the albite-diopside glass, as it is chemically most similar to the melts in the lower mantle. We studied the Ge K edge of the sample with a resistively heated and a laser-heated diamond anvil cell, for a pressure range of up to 48 GPa and a temperature range of up to 5000 K. High temperatures at which the sample is liquid and that are relevant for the Earth mantle, have a significant impact on the structural transformation, with a shift of approx. 30% to significantly lower pressures, compared to the glasses at room temperature and below 1000 K.
The results of this thesis represent an important contribution to the understanding of the properties of melts at conditions of the lower mantle. In the context of the discussion about the existence and origin of ultra-dense silicate melts at the core-mantle boundary, these investigations show that the higher density compared to the surrounding material cannot be explained by only structural features, but by a distinct chemical composition. The results also suggest that only very low solubilities of noble gases are to be expected for melts in the lower mantle, so that the structural properties clearly influence the overall budget and transport of noble gases in the Earth’s mantle.
The galactic interstellar medium is magnetized and turbulent. The magnetic field and turbulence play important roles in many astrophysical mechanisms, including cosmic ray transport, star formation, etc. Therefore, measurements of magnetic field and turbulence information are crucial for the proper interpretation of astronomical observations. Nonetheless, the magnetic field observation is quite challenging, especially, there is not universal magnetic tracer for diffuse medium. Moreover, the modelling of turbulence can be oversimplified due to the lack of observational tools to diagnose the plasma properties of the turbulence in the galactic interstellar medium. The studies presented in this thesis have addressed these challenges by bridging the theoretical studies of magnetic field and turbulence with numerical simulations and observations.
The following research are presented in this thesis. The first observational evidence of the novel magnetic tracer, ground state alignment (GSA), is discovered, revealing the three-dimensional magnetic field as well as 2 orders of magnitude higher precision comparing to previous observational study in the stellar atmosphere of the post-AGB 89 Herculis. Moreover, the application of GSA in the sub-millimeter fine-structure lines is comprehensively studied for different elements and with magnetohydrodynamic simulations. Furthermore, the influence of GSA effect on the spectroscopy is analyzed and it is found that measurable variation will be produced on the spectral line intensity and the line ratio without accounting for the optical pumping process or magnetic field.
Additionally, a novel method to measure plasma modes in the interstellar medium, Signatures from Polarization Analysis (SPA), is proposed and applied to real observations. Magneto-sonic modes are discovered in different types of interstellar medium. An explanation is provided for the long-standing mystery, the origin of γ-ray enhanced emission “Cygnus Cocoon”, based on the comparison between the outcome of SPA and multi-waveband observational data. These novel methods have strong potentials for broader observational applications and will play crucial roles in future multi-wavelength astronomy.
Magnetic strain contributions in laser-excited metals studied by time-resolved X-ray diffraction
(2021)
In this work I explore the impact of magnetic order on the laser-induced ultrafast strain response of metals. Few experiments with femto- or picosecond time-resolution have so far investigated magnetic stresses. This is contrasted by the industrial usage of magnetic invar materials or magnetostrictive transducers for ultrasound generation, which already utilize magnetostrictive stresses in the low frequency regime.
In the reported experiments I investigate how the energy deposition by the absorption of femtosecond laser pulses in thin metal films leads to an ultrafast stress generation. I utilize that this stress drives an expansion that emits nanoscopic strain pulses, so called hypersound, into adjacent layers. Both the expansion and the strain pulses change the average inter-atomic distance in the sample, which can be tracked with sub-picosecond time resolution using an X-ray diffraction setup at a laser-driven Plasma X-ray source. Ultrafast X-ray diffraction can also be applied to buried layers within heterostructures that cannot be accessed by optical methods, which exhibit a limited penetration into metals. The reconstruction of the initial energy transfer processes from the shape of the strain pulse in buried detection layers represents a contribution of this work to the field of picosecond ultrasonics.
A central point for the analysis of the experiments is the direct link between the deposited energy density in the nano-structures and the resulting stress on the crystal lattice. The underlying thermodynamical concept of a Grüneisen parameter provides the theoretical framework for my work. I demonstrate how the Grüneisen principle can be used for the interpretation of the strain response on ultrafast timescales in various materials and that it can be extended to describe magnetic stresses. The class of heavy rare-earth elements exhibits especially large magnetostriction effects, which can even lead to an unconventional contraction of the laser-excited transducer material. Such a dominant contribution of the magnetic stress to the motion of atoms has not been demonstrated previously. The observed rise time of the magnetic stress contribution in Dysprosium is identical to the decrease in the helical spin-order, that has been found previously using time-resolved resonant X-ray diffraction. This indicates that the strength of the magnetic stress can be used as a proxy of the underlying magnetic order. Such magnetostriction measurements are applicable even in case of antiparallel or non-collinear alignment of the magnetic moments and a vanishing magnetization.
The strain response of metal films is usually determined by the pressure of electrons and lattice vibrations. I have developed a versatile two-pulse excitation routine that can be used to extract the magnetic contribution to the strain response even if systematic measurements above and below the magnetic ordering temperature are not feasible. A first laser pulse leads to a partial ultrafast demagnetization so that the amplitude and shape of the strain response triggered by the second pulse depends on the remaining magnetic order. With this method I could identify a strongly anisotropic magnetic stress contribution in the magnetic data storage material iron-platinum and identify the recovery of the magnetic order by the variation of the pulse-to-pulse delay. The stark contrast of the expansion of iron-platinum nanograins and thin films shows that the different constraints for the in-plane expansion have a strong influence on the out-of-plane expansion, due to the Poisson effect. I show how such transverse strain contributions need to be accounted for when interpreting the ultrafast out-of-plane strain response using thermal expansion coefficients obtained in near equilibrium conditions.
This work contributes an investigation of magnetostriction on ultrafast timescales to the literature of magnetic effects in materials. It develops a method to extract spatial and temporal varying stress contributions based on a model for the amplitude and shape of the emitted strain pulses. Energy transfer processes result in a change of the stress profile with respect to the initial absorption of the laser pulses. One interesting example occurs in nanoscopic gold-nickel heterostructures, where excited electrons rapidly transport energy into a distant nickel layer, that takes up much more energy and expands faster and stronger than the laser-excited gold capping layer. Magnetic excitations in rare earth materials represent a large energy reservoir that delays the energy transfer into adjacent layers. Such magneto-caloric effects are known in thermodynamics but not extensively covered on ultrafast timescales. The combination of ultrafast X-ray diffraction and time-resolved techniques with direct access to the magnetization has a large potential to uncover and quantify such energy transfer processes.
The evolution of life on Earth has been driven by disturbances of different types and magnitudes over the 4.6 million years of Earth’s history (Raup, 1994, Alroy, 2008). One example for such disturbances are mass extinctions which are characterized by an exceptional increase in the extinction rate affecting a great number of taxa in a short interval of geologic time (Sepkoski, 1986). During the 541 million years of the Phanerozoic, life on Earth suffered five exceptionally severe mass extinctions named the “Big Five Extinctions”. Many mass extinctions are linked to changes in climate
(Feulner, 2009). Hence, the study of past mass extinctions is not only intriguing, but can also provide insights into the complex nature of the Earth system. This thesis aims at deepening our understanding of the triggers of mass extinctions and how they affected life. To accomplish this, I investigate changes in climate during two of the Big Five extinctions using a coupled climate model.
During the Devonian (419.2–358.9 million years ago) the first vascular plants and vertebrates evolved on land while extinction events occurred in the ocean (Algeo et al., 1995). The causes of these formative changes, their interactions and their links to changes in climate are still poorly understood. Therefore, we explore the sensitivity of the Devonian climate to various boundary conditions using an intermediate-complexity climate model (Brugger et al., 2019). In contrast to Le Hir et al. (2011), we find only a minor biogeophysical effect of changes in vegetation cover due to unrealistically high soil albedo values used in the earlier study. In addition, our results cannot support the strong influence of orbital parameters on the Devonian climate, as simulated with a climate model with a strongly simplified ocean model (De Vleeschouwer et al., 2013, 2014, 2017). We can only reproduce the changes in Devonian climate suggested by proxy data by decreasing atmospheric CO2. Still, finding agreement between the evolution of sea surface temperatures reconstructed from proxy data (Joachimski et al., 2009) and our simulations remains challenging and suggests a lower δ18O ratio of Devonian seawater. Furthermore, our study of the sensitivity of the Devonian climate reveals a prevailing mode of climate variability on a timescale of decades to centuries. The quasi-periodic ocean temperature fluctuations are linked to a physical mechanism of changing sea-ice cover, ocean convection and overturning in high northern latitudes.
In the second study of this thesis (Dahl et al., under review) a new reconstruction of atmospheric CO2 for the Devonian, which is based on CO2-sensitive carbon isotope fractionation in the earliest vascular plant fossils, suggests a much earlier drop of atmo- spheric CO2 concentration than previously reconstructed, followed by nearly constant CO2 concentrations during the Middle and Late Devonian. Our simulations for the Early Devonian with identical boundary conditions as in our Devonian sensitivity study (Brugger et al., 2019), but with a low atmospheric CO2 concentration of 500 ppm, show no direct conflict with available proxy and paleobotanical data and confirm that under the simulated climatic conditions carbon isotope fractionation represents a robust proxy for atmospheric CO2. To explain the earlier CO2 drop we suggest that early forms of vascular land plants have already strongly influenced weathering. This new perspective on the Devonian questions previous ideas about the climatic conditions and earlier explanations for the Devonian mass extinctions.
The second mass extinction investigated in this thesis is the end-Cretaceous mass extinction (66 million years ago) which differs from the Devonian mass extinctions in terms of the processes involved and the timescale on which the extinctions occurred. In the two studies presented here (Brugger et al., 2017, 2021), we model the climatic effects of the Chicxulub impact, one of the proposed causes of the end-Cretaceous extinction, for the first millennium after the impact. The light-dimming effect of stratospheric sulfate aerosols causes severe cooling, with a decrease of global annual mean surface air temperature of at least 26◦C and a recovery to pre-impact temperatures after more than 30 years. The sudden surface cooling of the ocean induces deep convection which brings nutrients from the deep ocean via upwelling to the surface ocean. Using an ocean biogeochemistry model we explore the combined effect of ocean mixing and iron-rich dust originating from the impactor on the marine biosphere. As soon as light levels have recovered, we find a short, but prominent peak in marine net primary productivity. This newly discovered mechanism could result in toxic effects for marine near-surface ecosystems. Comparison of our model results to proxy data (Vellekoop et al., 2014, 2016, Hull et al., 2020) suggests that carbon release from the terrestrial biosphere is required in addition to the carbon dioxide which can be attributed to the target material. Surface ocean acidification caused by the addition of carbon dioxide and sulfur is only moderate. Taken together, the results indicate a significant contribution of the Chicxulub impact to the end-Cretaceous mass extinction by triggering multiple stressors for the Earth system.
Although the sixth extinction we face today is characterized by human intervention in nature, this thesis shows that we can gain many insights into future extinctions from studying past mass extinctions, such as the importance of the rate of change (Rothman, 2017), the interplay of multiple stressors (Gunderson et al., 2016), and changes in the carbon cycle (Rothman, 2017, Tierney et al., 2020).
We investigate models for incremental binary classification, an example for supervised online learning. Our starting point is a model for human and machine learning suggested by E.M.Gold.
In the first part, we consider incremental learning algorithms that use all of the available binary labeled training data in order to compute the current hypothesis. For this model, we observe that the algorithm can be assumed to always terminate and that the distribution of the training data does not influence learnability. This is still true if we pose additional delayable requirements that remain valid despite a hypothesis output delayed in time. Additionally, we consider the non-delayable requirement of consistent learning. Our corresponding results underpin the claim for delayability being a suitable structural property to describe and collectively investigate a major part of learning success criteria. Our first theorem states the pairwise implications or incomparabilities between an established collection of delayable learning success criteria, the so-called complete map. Especially, the learning algorithm can be assumed to only change its last hypothesis in case it is inconsistent with the current training data. Such a learning behaviour is called conservative.
By referring to learning functions, we obtain a hierarchy of approximative learning success criteria. Hereby we allow an increasing finite number of errors of the hypothesized concept by the learning algorithm compared with the concept to be learned. Moreover, we observe a duality depending on whether vacillations between infinitely many different correct hypotheses are still considered a successful learning behaviour. This contrasts the vacillatory hierarchy for learning from solely positive information.
We also consider a hypothesis space located between the two most common hypothesis space types in the nearby relevant literature and provide the complete map.
In the second part, we model more efficient learning algorithms. These update their hypothesis referring to the current datum and without direct regress to past training data. We focus on iterative (hypothesis based) and BMS (state based) learning algorithms. Iterative learning algorithms use the last hypothesis and the current datum in order to infer the new hypothesis.
Past research analyzed, for example, the above mentioned pairwise relations between delayable learning success criteria when learning from purely positive training data. We compare delayable learning success criteria with respect to iterative learning algorithms, as well as learning from either exclusively positive or binary labeled data. The existence of concept classes that can be learned by an iterative learning algorithm but not in a conservative way had already been observed, showing that conservativeness is restrictive. An additional requirement arising from cognitive science research %and also observed when training neural networks is U-shapedness, stating that the learning algorithm does diverge from a correct hypothesis. We show that forbidding U-shapes also restricts iterative learners from binary labeled data.
In order to compute the next hypothesis, BMS learning algorithms refer to the currently observed datum and the actual state of the learning algorithm. For learning algorithms equipped with an infinite amount of states, we provide the complete map. A learning success criterion is semantic if it still holds, when the learning algorithm outputs other parameters standing for the same classifier. Syntactic (non-semantic) learning success criteria, for example conservativeness and syntactic non-U-shapedness, restrict BMS learning algorithms. For proving the equivalence of the syntactic requirements, we refer to witness-based learning processes. In these, every change of the hypothesis is justified by a later on correctly classified witness from the training data. Moreover, for every semantic delayable learning requirement, iterative and BMS learning algorithms are equivalent. In case the considered learning success criterion incorporates syntactic non-U-shapedness, BMS learning algorithms can learn more concept classes than iterative learning algorithms.
The proofs are combinatorial, inspired by investigating formal languages or employ results from computability theory, such as infinite recursion theorems (fixed point theorems).
Deoxyribonucleic acid (DNA) nanostructures enable the attachment of functional molecules to nearly any unique location on their underlying structure. Due to their single-base-pair structural resolution, several ligands can be spatially arranged and closely controlled according to the geometry of their desired target, resulting in optimized binding and/or signaling interactions.
This dissertation covers three main projects. All of them use variations of functionalized DNA nanostructures that act as platform for oligovalent presentation of ligands. The purpose of this work was to evaluate the ability of DNA nanostructures to precisely display different types of functional molecules and to consequently enhance their efficacy according to the concept of multivalency. Moreover, functionalized DNA structures were examined for their suitability in functional screening assays. The developed DNA-based compound ligands were used to target structures in different biological systems.
One part of this dissertation attempted to bind pathogens with small modified DNA nanostructures. Pathogens like viruses and bacteria are known for their multivalent attachment to host cells membranes. By blocking their receptors for recognition and/or fusion with their targeted host in an oligovalent manner, the objective was to impede their ability to adhere to and invade cells. For influenza A, only enhanced binding of oligovalent peptide-DNA constructs compared to the monovalent peptide could be observed, whereas in the case of respiratory syncytial virus (RSV), binding as well as blocking of the target receptors led to an increased inhibition of infection in vitro.
In the final part, the ability of chimeric DNA-peptide constructs to bind to and activate signaling receptors on the surface of cells was investigated. Specific binding of DNA trimers, conjugated with up to three peptides, to EphA2 receptor expressing cells was evaluated in flow cytometry experiments. Subsequently, their ability to activate these receptors via phosphorylation was assessed. EphA2 phosphorylation was significantly increased by DNA trimers carrying three peptides compared to monovalent peptide. As a result of activation, cells underwent characteristic morphological changes, where they "round up" and retract their periphery.
The results obtained in this work comprehensively prove the capability of DNA nanostructures to serve as stable, biocompatible, controllable platforms for the oligovalent presentation of functional ligands. Functionalized DNA nanostructures were used to enhance biological effects and as tool for functional screening of bio-activity. This work demonstrates that modified DNA structures have the potential to improve drug development and to unravel the activation of signaling pathways.
Polymeric films and coatings derived from semi-crystalline oligomers are of relevance for medical and pharmaceutical applications. In this context, the material surface is of particular importance, as it mediates the interaction with the biological system. Two dimensional (2D) systems and ultrathin films are used to model this interface. However, conventional techniques for their preparation, such as spin coating or dip coating, have disadvantages, since the morphology and chain packing of the generated films can only be controlled to a limited extent and adsorption on the substrate used affects the behavior of the films. Detaching and transferring the films prepared by such techniques requires additional sacrificial or supporting layers, and free-standing or self supporting domains are usually of very limited lateral extension. The aim of this thesis is to study and modulate crystallization, melting, degradation and chemical reactions in ultrathin films of oligo(ε-caprolactone)s (OCL)s with different end-groups under ambient conditions. Here, oligomeric ultrathin films are assembled at the air-water interface using the Langmuir technique. The water surface allows lateral movement and aggregation of the oligomers, which, unlike solid substrates, enables dynamic physical and chemical interaction of the molecules. Parameters like surface pressure (π), temperature and mean molecular area (MMA) allow controlled assembly and manipulation of oligomer molecules when using the Langmuir technique. The π-MMA isotherms, Brewster angle microscopy (BAM), and interfacial infrared spectroscopy assist in detecting morphological and physicochemical changes in the film. Ultrathin films can be easily transferred to the solid silicon surface via Langmuir Schaefer (LS) method (horizontal substrate dipping). Here, the films transferred on silicon are investigated using atomic force microscopy (AFM) and optical microscopy and are compared to the films on the water surface.
The semi-crystalline morphology (lamellar thicknesses, crystal number densities, and lateral crystal dimensions) is tuned by the chemical structure of the OCL end-groups (hydroxy or methacrylate) and by the crystallization temperature (Tc; 12 or 21 °C) or MMAs. Compression to lower MMA of ~2 Å2, results in the formation of a highly crystalline film, which consists of tightly packed single crystals. Preparation of tightly packed single crystals on a cm2 scale is not possible by conventional techniques. Upon transfer to a solid surface, these films retain their crystalline morphology whereas amorphous films undergo dewetting.
The melting temperature (Tm) of OCL single crystals at the water and the solid surface is found proportional to the inverse crystal thickness and is generally lower than the Tm of bulk PCL. The impact of OCL end-groups on melting behavior is most noticeable at the air-solid interface, where the methacrylate end-capped OCL (OCDME) melted at lower temperatures than the hydroxy end-capped OCL (OCDOL). When comparing the underlying substrate, melting/recrystallization of OCL ultrathin films is possible at lower temperatures at the air water interface than at the air-solid interface, where recrystallization is not visible. Recrystallization at the air-water interface usually occurs at a higher temperature than the initial Tc.
Controlled degradation is crucial for the predictable performance of degradable polymeric biomaterials. Degradation of ultrathin films is carried out under acidic (pH ~ 1) or enzymatic catalysis (lipase from Pseudomonas cepcia) on the water surface or on a silicon surface as transferred films. A high crystallinity strongly reduces the hydrolytic but not the enzymatic degradation rate. As an influence of end-groups, the methacrylate end-capped linear oligomer, OCDME (~85 ± 2 % end-group functionalization) hydrolytically degrades faster than the hydroxy end capped linear oligomer, OCDOL (~95 ± 3 % end-group functionalization) at different temperatures. Differences in the acceleration of hydrolytic degradation of semi-crystalline films were observed upon complete melting, partial melting of the crystals, or by heating to temperatures close to Tm. Therefore, films of densely packed single crystals are suitable as barrier layers with thermally switchable degradation rates.
Chemical modification in ultrathin films is an intricate process applicable to connect functionalized molecules, impart stability or create stimuli-sensitive cross-links. The reaction of end-groups is explored for transferred single crystals on a solid surface or amorphous monolayer at the air-water interface. Bulky methacrylate end-groups are expelled to the crystal surface during chain-folded crystallization. The density of end-groups is inversely proportional to molecular weight and hence very pronounced for oligomers. The methacrylate end-groups at the crystal surface, which are present at high concentration, can be used for further chemical functionalization. This is demonstrated by fluorescence microscopy after reaction with fluorescein dimethacrylate. The thermoswitching behavior (melting and recrystallization) of fluorescein functionalized single crystals shows the temperature-dependent distribution of the chemically linked fluorescein moieties, which are accumulated on the surfaces of crystals, and homogeneously dispersed when the crystals are molten. In amorphous monolayers at the air-water interface, reversible cross-linking of hydroxy-terminated oligo(ε-caprolactone) monolayers using dialdehyde (glyoxal) lead to the formation of 2D networks. Pronounced contraction in the area occurred for 2D OCL films in dependence of surface pressure and time indicating the reaction progress. Cross linking inhibited crystallization and retarded enzymatic degradation of the OCL film. Altering the subphase pH to ~2 led to cleavage of the covalent acetal cross-links. Besides as model systems, these reversibly cross-linked films are applicable for drug delivery systems or cell substrates modulating adhesion at biointerfaces.
The present work focuses on minimising the usage of toxic chemicals by integration of the biobased monomers, derived from fatty acid esters, to photopolymerization processes, which are known to be nature friendly. Internal double bond present in the oleic acid was converted to more reactive (meth)acrylate or epoxy group. Biobased starting materials, functionalized by different pendant groups, were used for photopolymerizing formulations to design of new polymeric structures by using ultraviolet light emitting diode (UV-LED) (395 nm) via free radical polymerization or cationic polymerization.
New (meth)acrylates (2,3 and 4) consisting of two isomers, methyl 9-((meth)acryloyloxy)-10-hydroxyoctadecanoate / methyl 9-hydroxy-10-((meth)acryloyloxy)octadecanoate (2 and 3) and methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4), modified from oleic acid mix, and ionic liquid monomers (1a and 1b) bearing long alkyl chain were polymerized photochemically. New (meth)acrylates are based on vegetable oil, and ionic liquids (ILs) have nonvolatile behaviour. Therefore, both monomer types have green approach. Photoinitiated polymerization of new (meth)acrylates and ionic liquids was investigated in the presence of ethyl (2,4,6-trimethylbenzoyl) phenylphosphinate (Irgacure® TPO−L) or di(4-methoxybenzoyl)diethylgermane (Ivocerin®) as photoinitiator (PI). Additionally, the results were discussed in comparison with those obtained from commercial 1,6-hexanediol di(meth)acrylate (5 and 6) for deeper investigation of biobased monomer’s potential to substitute petroleum derived materials with renewable resources for possible coating applications. Kinetic study shows that methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4) and ionic liquids (1a and 1b) have quantitative conversion after irradiation process which is important for practical applications. On the other hand, heat generation occurs in a longer time during the polymerization of biobased systems or ILs.
The poly(meth)acrylates modified from (meth)acrylated fatty acid methyl ester monomers generally show a low glass transition temperature because of the presence of long aliphatic chain in the polymer structure. However, poly(meth)acrylates containing aromatic group have higher glass transition temperature. Therefore, new 4-(4-methacryloyloxyphenyl)-butan-2-one (7) was synthesized which can be a promising candidate for the green techniques, such as light induced polymerization. Photokinetic investigation of the new monomer, 4-(4-methacryloyloxyphenyl)-butan-2-one (7), was discussed using Irgacure® TPO−L or Ivocerin® as photoinitiator. The reactivity of that monomer was compared to commercial 2-phenoxyethyl methacrylate (8) and phenyl methacrylate (9) basis of the differences on monomer structures. The photopolymer of 4-(4-methacryloyloxyphenyl)-butan-2-one (7) might be an interesting candidate for the coating application with the properties of quantitative conversion and high molecular weight. It also shows higher glass transition temperature.
In addition to the linear systems based on renewable materials, new crosslinked polymers were also designed in this thesis. Therefore, isomer mixture consisting of ethane-1,2-diyl bis(9-methacryloyloxy-10-hydroxy octadecanoate), ethane-1,2-diyl 9-hydroxy-10-methacryloyloxy-9’-methacryloyloxy10’-hydroxy octadecanoate and ethane-1,2-diyl bis(9-hydroxy-10-methacryloyloxy octadecanoate) (10) was synthesized by derivation of the oleic acid which has not been previously described in the literature. Crosslinked material based on this biobased monomer was produced by photoinitiated free radical polymerization using Irgacure® TPO−L or Ivocerin® as photoinitiator. Furthermore, material properties were diversified by copolymerization of 10 with 4-(4-methacryloyloxyphenyl)-butan-2-one (7) or methyl 9-(1H-imidazol-1-yl)-10-(methacryloyloxy)octadecanoate / methyl 9-(methacryloyloxy)-10-(1H-imidazol-1-yl)octadecanoate (4). In addition to this, influence of comonomer with different chemical structure on the network system was investigated by analysis of thermo-mechanical properties, crosslink density and molecular weight between two crosslink junctions. An increase in the glass transition temperature caused by copolymerization of biobased monomer 10 with the excess amount of 4-(4-methacryloyloxyphenyl)-butan-2-one (7) was confirmed by both techniques, differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). On the other hand, crosslink density decreased as a result of copolymerization reactions due to the reduction in the mean functionality of the system. Furthermore, surface characterization has been tested by contact angle measurements using solvents with different polarity.
This work also contributes to the limited data reported about cationic photopolymerization of the epoxidized vegetable oils in the literature in contrast to the widely investigation of thermal curing of the biorenewable epoxy monomers. In addition to the 9,10-epoxystearic acid methyl ester (11), a new monomer of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) has been synthesized from oleic acid. These two biobased epoxies have been polymerized via cationic photoinitiated polymerization in the presence of bis(t-butyl)-iodonium-tetrakis(perfluoro-t-butoxy)aluminate ([Al(O-t-C4F9)4]-) and isopropylthioxanthone (ITX) as photinitiating system. Polymerization kinetic of 9,10-epoxystearic acid methyl ester (11) and bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) was investigated and compared with the kinetic of commercial monomers being 3,4-epoxycyclohexylmethyl-3’,4’-epoxycyclohexane carboxylate (13), 1,4-butanediol diglycidyl ether (14), and diglycidylether of bisphenol-A (15). Both biobased epoxies (11 and 12) showed higher conversion than cycloaliphatic epoxy (13), and lower reactivity than 1,4-butanediol diglycidyl ether (14). Additional network systems were designed by copolymerization of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) and diglycidylether of bisphenol-A (15) in different molar ratios (1:1; 1:5; 1:9). It addresses that, final conversion is dependent on polymerization rate as well as physical processes such as vitrification during polymerization. Moreover, low glass transition temperature of homopolymer derived from bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) was successfully increased by copolymerization with diglycidylether bisphenol-A (15). On the other hand, the surface produced from bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) shows hydrophobic character. Higher concentration of biobased diepoxy (12) in the copolymerizing mixture decreases surface free energy. Network systems were also investigated according to the rubber elasticity theory. Crosslinked polymer derived from the mixture of bis-(9,10-epoxystearic acid) 1,2-ethanediyl ester (12) and diglycidylether of bisphenol-A (15) (molar ratio=1:5) exhibits almost ideal polymer network.