Refine
Has Fulltext
- yes (1727) (remove)
Year of publication
Document Type
- Doctoral Thesis (1727) (remove)
Language
- English (1727) (remove)
Keywords
- climate change (48)
- Klimawandel (47)
- Modellierung (26)
- Nanopartikel (22)
- machine learning (20)
- Fernerkundung (17)
- Blickbewegungen (16)
- Synchronisation (15)
- remote sensing (15)
- Satzverarbeitung (14)
Institute
- Institut für Physik und Astronomie (347)
- Institut für Geowissenschaften (298)
- Institut für Biochemie und Biologie (259)
- Institut für Chemie (192)
- Extern (126)
- Hasso-Plattner-Institut für Digital Engineering GmbH (83)
- Institut für Umweltwissenschaften und Geographie (83)
- Department Linguistik (64)
- Institut für Informatik und Computational Science (64)
- Institut für Mathematik (57)
Data integration aims to combine data of different sources and to provide users with a unified view on these data. This task is as challenging as valuable. In this thesis we propose algorithms for dependency discovery to provide necessary information for data integration. We focus on inclusion dependencies (INDs) in general and a special form named conditional inclusion dependencies (CINDs): (i) INDs enable the discovery of structure in a given schema. (ii) INDs and CINDs support the discovery of cross-references or links between schemas. An IND “A in B” simply states that all values of attribute A are included in the set of values of attribute B. We propose an algorithm that discovers all inclusion dependencies in a relational data source. The challenge of this task is the complexity of testing all attribute pairs and further of comparing all of each attribute pair's values. The complexity of existing approaches depends on the number of attribute pairs, while ours depends only on the number of attributes. Thus, our algorithm enables to profile entirely unknown data sources with large schemas by discovering all INDs. Further, we provide an approach to extract foreign keys from the identified INDs. We extend our IND discovery algorithm to also find three special types of INDs: (i) Composite INDs, such as “AB in CD”, (ii) approximate INDs that allow a certain amount of values of A to be not included in B, and (iii) prefix and suffix INDs that represent special cross-references between schemas. Conditional inclusion dependencies are inclusion dependencies with a limited scope defined by conditions over several attributes. Only the matching part of the instance must adhere the dependency. We generalize the definition of CINDs distinguishing covering and completeness conditions and define quality measures for conditions. We propose efficient algorithms that identify covering and completeness conditions conforming to given quality thresholds. The challenge for this task is twofold: (i) Which (and how many) attributes should be used for the conditions? (ii) Which attribute values should be chosen for the conditions? Previous approaches rely on pre-selected condition attributes or can only discover conditions applying to quality thresholds of 100%. Our approaches were motivated by two application domains: data integration in the life sciences and link discovery for linked open data. We show the efficiency and the benefits of our approaches for use cases in these domains.
The thesis assesses the contribution of technology option of Carbon Capture and Sequestration (CCS) to climate change mitigation. CCS means that CO2 is captured at large industrial facilities and sequestered in goelogical structures. The technology uses the endogenous growth model MIND. Herein the various climate change mitigation options of reducing economic growth, increasing energy efficiency, changing the energy mix and CCS are assessed simultaneously. An important question is whether CCS is a temporary or long-term solution. The results show that in the middle of the 21st century CCS has its peak contribution, which allows prolonged use of relatively cheap fossil energy carriers. However, this leads to delayed introduction of renewable energy carriers. The technology path ways are accombined with different costs of climate change mitigation. The use of CCS delays and reduces the costs of climate change mitigation. However, the delayed introduction of renewable energy carriers leads to reduced technological learning, which induces higher costs in the longer term. All in all the temporary use of CCS reduces the costs of climate change mitigation costs. The result is robust, which is tested with various uncertainty analysis.
Black shales are sedimentary rocks with a high content of organic carbon, which leads to a dark grayish to black color. Due to their potential to contain oil or gas, black shales are of great interest for the support of the worldwide energy supply. An integrated seismic investigation of the Lower Palaeozoic black shales was carried out at the Danish island Bornholm to locate the shallow-lying Alum Shale layer and its surrounding formations and to characterize its potential as a source rock. Therefore, two seismic experiments at a total of three crossing profiles were carried out in October 2010 and in June 2012 in the southern part of the island. Two different active measurements were conducted with either a weight drop source or a minivibrator. Additionally, the ambient noise field was recorded at the study location over a time interval of about one day, and also a laboratory analysis of borehole samples was carried out. The seismic profiles were positioned as close as possible to two scientific boreholes which were used for comparative purposes. The seismic field data was analyzed with traveltime tomography, surface wave inversion and seismic interferometry to obtain the P-wave and S-wave velocity models of the subsurface. The P-wave velocity models which were determined for all three profiles clearly locate the Alum Shale layer between the Komstad Limestone layer on top and the Læså Sandstone Formation at the base of the models. The black shale layer has P-wave velocities around 3 km/s which are lower compared to the adjacent formations. Due to a very good agreement of the sonic log and the vertical velocity profiles of the two seismic lines, which are directly crossing the borehole where the sonic log was conducted, the reliability of the traveltime tomography is proven. A correlation of the seismic velocities with the content of organic carbon is an important task for the characterization of the reservoir properties of a black shale formation. It is not possible without calibration but in combination with a full 2D tomographic image of the subsurface it gives the subsurface distribution of the organic material. The S-wave model obtained with surface wave inversion of the vibroseis data of one of the profiles images the Alum Shale layer also very well with S-wave velocities around 2 km/s. Although individual 1D velocity models for each of the source positions were determined, the subsurface S-wave velocity distribution is very uniform with a good match between the single models. A really new approach described here is the application of seismic interferometry to a really small study area and a quite short time interval. Also new is the selective procedure of only using time windows with the best crosscorrelation signals to achieve the final interferograms. Due to the small scale of the interferometry even P-wave signals can be observed in the final crosscorrelations. In the laboratory measurements the seismic body waves were recorded for different pressure and temperature stages. Therefore, samples of different depths of the Alum Shale were available from one of the scientific boreholes at the study location. The measured velocities have a high variance with changing pressure or temperature. Recordings with wave propagation both parallel and perpendicular to the bedding of the samples reveal a great amount of anisotropy for the P-wave velocity, whereas the S-wave velocity is almost independent of the wave direction. The calculated velocity ratio is also highly anisotropic with very low values for the perpendicular samples and very high values for the parallel ones. Interestingly, the laboratory velocities of the perpendicular samples are comparable to the velocities of the field experiments indicating that the field measurements are sensitive to wave propagation in vertical direction. The velocity ratio is also calculated with the P-wave and S-wave velocity models of the field experiments. Again, the Alum Shale can be clearly separated from the adjacent formations because it shows overall very low vP/vS ratios around 1.4. The very low velocity ratio indicates the content of gas in the black shale formation. With the combination of all the different methods described here, a comprehensive interpretation of the seismic response of the black shale layer can be made and the hydrocarbon source rock potential can be estimated.
Climatic variations and human activity now and increasingly in the future cause land cover changes and introduce perturbations in the terrestrial carbon reservoirs in vegetation, soil and detritus. Optical remote sensing and in particular Imaging Spectroscopy has shown the potential to quantify land surface parameters over large areas, which is accomplished by taking advantage of the characteristic interactions of incident radiation and the physico-chemical properties of a material. The objective of this thesis is to quantify key soil parameters, including soil organic carbon, using field and Imaging Spectroscopy. Organic carbon, iron oxides and clay content are selected to be analyzed to provide indicators for ecosystem function in relation to land degradation, and additionally to facilitate a quantification of carbon inventories in semiarid soils. The semiarid Albany Thicket Biome in the Eastern Cape Province of South Africa is chosen as study site. It provides a regional example for a semiarid ecosystem that currently undergoes land changes due to unadapted management practices and furthermore has to face climate change induced land changes in the future. The thesis is divided in three methodical steps. Based on reflectance spectra measured in the field and chemically determined constituents of the upper topsoil, physically based models are developed to quantify soil organic carbon, iron oxides and clay content. Taking account of the benefits limitations of existing methods, the approach is based on the direct application of known diagnostic spectral features and their combination with multivariate statistical approaches. It benefits from the collinearity of several diagnostic features and a number of their properties to reduce signal disturbances by influences of other spectral features. In a following step, the acquired hyperspectral image data are prepared for an analysis of soil constituents. The data show a large spatial heterogeneity that is caused by the patchiness of the natural vegetation in the study area that is inherent to most semiarid landscapes. Spectral mixture analysis is performed and used to deconvolve non-homogenous pixels into their constituent components. For soil dominated pixels, the subpixel information is used to remove the spectral influence of vegetation and to approximate the pure spectral signature coming from the soil. This step is an integral part when working in natural non-agricultural areas where pure bare soil pixels are rare. It is identified as the largest benefit within the multi-stage methodology, providing the basis for a successful and unbiased prediction of soil constituents from hyperspectral imagery. With the proposed approach it is possible (1) to significantly increase the spatial extent of derived information of soil constituents to areas with about 40 % vegetation coverage and (2) to reduce the influence of materials such as vegetation on the quantification of soil constituents to a minimum. Subsequently, soil parameter quantities are predicted by the application of the feature-based soil prediction models to the maps of locally approximated soil signatures. Thematic maps showing the spatial distribution of the three considered soil parameters in October 2009 are produced for the Albany Thicket Biome of South Africa. The maps are evaluated for their potential to detect erosion affected areas as effects of land changes and to identify degradation hot spots in regard to support local restoration efforts. A regional validation, carried out using available ground truth sites, suggests remaining factors disturbing the correlation of spectral characteristics and chemical soil constituents. The approach is developed for semiarid areas in general and not adapted to specific conditions in the study area. All processing steps of the developed methodology are implemented in software modules, where crucial steps of the workflow are fully automated. The transferability of the methodology is shown for simulated data of the future EnMAP hyperspectral satellite. Soil parameters are successfully predicted from these data despite intense spectral mixing within the lower spatial resolution EnMAP pixels. This study shows an innovative approach to use Imaging Spectroscopy for mapping of key soil constituents, including soil organic carbon, for large areas in a non-agricultural ecosystem and under consideration of a partially vegetation coverage. It can contribute to a better assessment of soil constituents that describe ecosystem processes relevant to detect and monitor land changes. The maps further provide an assessment of the current carbon inventory in soils, valuable for carbon balances and carbon mitigation products.
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.
Business process management is an acknowledged asset for running an organization in a productive and sustainable way. One of the most important aspects of business process management, occurring on a daily basis at all levels, is decision making. In recent years, a number of decision management frameworks have appeared in addition to existing business process management systems. More recently, Decision Model and Notation (DMN) was developed by the OMG consortium with the aim of complementing the widely used Business Process Model and Notation (BPMN). One of the reasons for the emergence of DMN is the increasing interest in the evolving paradigm known as the separation of concerns. This paradigm states that modeling decisions complementary to processes reduces process complexity by externalizing decision logic from process models and importing it into a dedicated decision model. Such an approach increases the agility of model design and execution. This provides organizations with the flexibility to adapt to the ever increasing rapid and dynamic changes in the business ecosystem. The research gap, identified by us, is that the separation of concerns, recommended by DMN, prescribes the externalization of the decision logic of process models in one or more separate decision models, but it does not specify this can be achieved.
The goal of this thesis is to overcome the presented gap by developing a framework for discovering decision models in a semi-automated way from information about existing process decision making. Thus, in this thesis we develop methodologies to extract decision models from: (1) control flow and data of process models that exist in enterprises; and (2) from event logs recorded by enterprise information systems, encapsulating day-to-day operations. Furthermore, we provide an extension of the methodologies to discover decision models from event logs enriched with fuzziness, a tool dealing with partial knowledge of the process execution information. All the proposed techniques are implemented and evaluated in case studies using real-life and synthetic process models and event logs. The evaluation of these case studies shows that the proposed methodologies provide valid and accurate output decision models that can serve as blueprints for executing decisions complementary to process models. Thus, these methodologies have applicability in the real world and they can be used, for example, for compliance checks, among other uses, which could improve the organization's decision making and hence it's overall performance.
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation
(2019)
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed:
• Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases?
• How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations?
• How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization?
To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis Program (EnMAP) satellite reflectance spectra from ground-based reflectance spectra as well as simulations of EnMAP imagery from aerial hyperspectral imagery were also obtained.
Results showed that canopy-level spectral variability within and between vegetation communities differed by phenological phase. The late season was identified as the most discriminative for identifying many dominant vegetation communities using both ground-based and simulated hyperspectral reflectance spectra. This was due to an overall reduction in spectral variability and comparable or greater differences in spectral reflectance between vegetation communities in the visible near infrared spectrum.
Red, green, and blue (RGB) indices extracted from nadir digital photographs and pigment-driven vegetation indices extracted from ground-based spectral measurements showed strong significant relationships. RGB indices also showed moderate relationships with chlorophyll and carotenoid pigment concentrations. The observed relationships with the broadband RGB channels of the digital camera indicate that vegetation colour strongly influences the response of pigment-driven spectral indices and digital cameras can track the seasonal development and degradation of photosynthetic pigments.
Spatial aggregation of hyperspectral data from the ground to airborne, to simulated satel-lite scale was influenced by non-photosynthetic components as demonstrated by the distinct shift of the red edge to shorter wavelengths. Correspondence between spectral reflectance at the three scales was highest in the red spectrum and lowest in the near infra-red. By artificially mixing litter spectra at different proportions to ground-based spectra, correspondence with aerial and satellite spectra increased. Greater proportions of litter were required to achieve correspondence at the satellite scale.
Overall this thesis found that integrating multiple temporal, spectral, and spatial data is necessary to monitor the complexity and heterogeneity of Arctic tundra ecosystems. The identification of spectrally similar vegetation communities can be optimized using non-peak season hyperspectral data leading to more detailed identification of vegetation communities. The results also highlight the power of vegetation colour to link ground-based and satellite data. Finally, a detailed characterization non-photosynthetic ecosystem components is crucial for accurate interpretation of vegetation signals at landscape scales.
Systems of Systems (SoS) have received a lot of attention recently. In this thesis we will focus on SoS that are built atop the techniques of Service-Oriented Architectures and thus combine the benefits and challenges of both paradigms. For this thesis we will understand SoS as ensembles of single autonomous systems that are integrated to a larger system, the SoS. The interesting fact about these systems is that the previously isolated systems are still maintained, improved and developed on their own. Structural dynamics is an issue in SoS, as at every point in time systems can join and leave the ensemble. This and the fact that the cooperation among the constituent systems is not necessarily observable means that we will consider these systems as open systems. Of course, the system has a clear boundary at each point in time, but this can only be identified by halting the complete SoS. However, halting a system of that size is practically impossible. Often SoS are combinations of software systems and physical systems. Hence a failure in the software system can have a serious physical impact what makes an SoS of this kind easily a safety-critical system. The contribution of this thesis is a modelling approach that extends OMG's SoaML and basically relies on collaborations and roles as an abstraction layer above the components. This will allow us to describe SoS at an architectural level. We will also give a formal semantics for our modelling approach which employs hybrid graph-transformation systems. The modelling approach is accompanied by a modular verification scheme that will be able to cope with the complexity constraints implied by the SoS' structural dynamics and size. Building such autonomous systems as SoS without evolution at the architectural level --- i. e. adding and removing of components and services --- is inadequate. Therefore our approach directly supports the modelling and verification of evolution.
In this thesis, we give two constructions for Riemannian metrics on Seiberg-Witten moduli spaces. Both these constructions are naturally induced from the L2-metric on the configuration space. The construction of the so called quotient L2-metric is very similar to the one construction of an L2-metric on Yang-Mills moduli spaces as given by Groisser and Parker. To construct a Riemannian metric on the total space of the Seiberg-Witten bundle in a similar way, we define the reduced gauge group as a subgroup of the gauge group. We show, that the quotient of the premoduli space by the reduced gauge group is isomorphic as a U(1)-bundle to the quotient of the premoduli space by the based gauge group. The total space of this new representation of the Seiberg-Witten bundle carries a natural quotient L2-metric, and the bundle projection is a Riemannian submersion with respect to these metrics. We compute explicit formulae for the sectional curvature of the moduli space in terms of Green operators of the elliptic complex associated with a monopole. Further, we construct a Riemannian metric on the cobordism between moduli spaces for different perturbations. The second construction of a Riemannian metric on the moduli space uses a canonical global gauge fixing, which represents the total space of the Seiberg-Witten bundle as a finite dimensional submanifold of the configuration space. We consider the Seiberg-Witten moduli space on a simply connected Käuhler surface. We show that the moduli space (when nonempty) is a complex projective space, if the perturbation does not admit reducible monpoles, and that the moduli space consists of a single point otherwise. The Seiberg-Witten bundle can then be identified with the Hopf fibration. On the complex projective plane with a special Spin-C structure, our Riemannian metrics on the moduli space are Fubini-Study metrics. Correspondingly, the metrics on the total space of the Seiberg-Witten bundle are Berger metrics. We show that the diameter of the moduli space shrinks to 0 when the perturbation approaches the wall of reducible perturbations. Finally we show, that the quotient L2-metric on the Seiberg-Witten moduli space on a Kähler surface is a Kähler metric.
The cytoskeletal motor protein kinesin-1 (conventional kinesin) is the fast carrier for intracellular cargo transport along microtubules. So far most studies aimed at investigating the transport properties of individual motor molecules. However, the transport in cells usually involves the collective work of more than one motor. In the present work, we have studied the movement of beads as artificial loads/organelles pulled by several kinesin-1 motors in vitro. For a wide range of motor coverage of the beads and different bead (cargo) sizes the transport parameters walking distance or run length, velocity and force generation are measured. The results indicate that the transport parameters are influenced by the number of motors carrying the bead. While the transport velocity slightly decreases, an increase in the run length was measured and higher forces are determined, when more motors are involved. The effective number of motors pulling a bead is estimated by measuring the change in the hydrodynamic diameter of kinesin-coated beads using dynamic light scattering. The geometrical constraints imposed by the transport system have been taken into account. Thus, results for beads of different size and motor-surface coverage could be compared. In addition, run length-distributions obtained for the smallest bead size were matched to theoretically calculated distributions. The latter yielded an average number of pulling motors, which is in agreement with the effective motor numbers determined experimentally.
Exploring elections features from a geographical perspective is the focus of this study. Its primary objective is to develop a scientific approach based on geoinformation technology (GIT) that promotes deeper understanding how geographical settings affect the spatial and temporal variations of voting behaviour and election outcomes. For this purpose, the five parliamentary elections (1991-2005) following the political turnaround in 1990 in the South East European reform country Albania have been selected as a case study. Elections, like other social phenomena that do not develop uniformly over a territory, inherit a spatial dimension. Despite of fact that elections have been researched by various scientific disciplines ranging from political science to geography, studies that incorporate their spatial dimension are still limited in number and approaches. Consequently, the methodologies needed to generate an integrated knowledge on many facets that constitute election features are lacking. This study addresses characteristics and interactions of the essential elements involved in an election process. Thus, the baseline of the approach presented here is the exploration of relations between three entities: electorate (political and sociodemographic features), election process (electoral system and code) and place (environment where voters reside). To express this interaction the concept of electoral pattern is introduced. Electoral patterns are defined by the study as the final view of election results, chiefly in tabular and/or map form, generated by the complex interaction of social, economic, juridical, and spatial features of the electorate, which has occurred at a specific time and in a particular geographical location. GIT methods of geoanalysis and geovisualization are used to investigate the characteristics of electoral patterns in their spatial and temporal distribution. Aggregate-level data modelled in map form were used to analyse and visualize the spatial distribution of election patterns components and relations. The spatial dimension of the study is addressed in the following three main relations: One, the relation between place and electorate and its expression through the social, demographic and economic features of the electorate resulting in the profile of the electorate’s context; second, the electorate-election interaction which forms the baseline to explore the perspective of local contextual effects in voting behaviour and election results; third, the relation between geographical location and election outcomes reflecting the implication of determining constituency boundaries on election results. To address the above relations, three types of variables: geo, independent and dependent, have been elaborated and two models have been created. The Data Model, developed in a GIS environment, facilitates structuring of election data in order to perform spatial analysis. The peculiarity of electoral patterns – a multidimensional array that contains information on three variables, stored in data layers of dissimilar spatial units of reference and scales of value measurement – prohibit spatial analysis based on the original source data. To perform a joint spatial analysis it is therefore mandatory to restructure the spatial units of reference while preserving their semantic content. In this operation, all relevant electoral as well as socio-demographic data referenced to different administrative spatial entities are re-referenced to uniform grid cells as virtual spatial units of reference. Depending on the scale of data acquisition and map presentation, a cell width of 0.5 km has been determined. The resulting fine grid forms the basis of subsequent data analyses and correlations. Conversion of the original vector data layers into target raster layers allows for unification of spatial units, at the same time retaining the existing level of detail of the data (variables, uniform distribution over space). This in turn facilitates the integration of the variables studied and the performance of GIS-based spatial analysis. In addition, conversion to raster format makes it possible to assign new values to the original data, which are based on a common scale eliminating existing differences in scale of measurement. Raster format operations of the type described are well-established data analysis techniques in GIT, yet they have rarely been employed to process and analyse electoral data. The Geovisualization Model, developed in a cartographic environment, complements the Data Model. As an analog graphic model it facilitates efficient communication and exploration of geographical information through cartographic visualization. Based on this model, 52 choropleth maps have been generated. They represent the outcome of the GIS-based electoral data analysis. The analog map form allows for in-depth visual analysis and interpretation of the distribution and correlation of the electoral data studied. For researchers, decision makers and a wider public the maps provide easy-to-access information on and promote easy-to-understand insight into the spatial dimension, regional variation and resulting structures of the electoral patterns defined.
New bio-based polymers
(2018)
Redox-responsive polymers, such as poly(disulfide)s, are a versatile class of polymers with potential applications including gene- and drug-carrier systems. Their degradability under reductive conditions allows for a controlled response to the different redox states that are present throughout the body. Poly(disulfide)s are typically synthesized by step growth polymerizations. Step growth polymerizations, however, may suffer from low conversions and therefore low molar masses, limiting potential applications. The purpose of this thesis was therefore to find and investigate new synthetic routes towards the synthesis of amino acid-based poly(disulfide)s.
The different routes in this thesis include entropy-driven ring opening polymerizations of novel macrocyclic monomers, derived from cystine derivatives. These monomers were obtained with overall yields of up to 77% and were analyzed by mass spectrometry as well as by 1D and 2D NMR spectroscopy. The kinetics of the entropy-driven ring-opening metathesis polymerization (ED-ROMP) were thoroughly investigated in dependence of temperature, monomer concentration, and catalyst concentration. The polymerization was optimized to yield poly(disulfide)s with weight average molar masses of up to 80 kDa and conversions of ~80%, at the thermodynamic equilibrium. Additionally, an alternative metal free polymerization, namely the entropy-driven ring-opening disulfide metathesis polymerization (ED-RODiMP) was established for the polymerization of the macrocyclic monomers. The effect of different solvents, concentrations and catalyst loadings on the polymerization process and its kinetics were studied. Polymers with very high weight average molar masses of up to 177 kDa were obtained. Moreover, various post-polymerization reactions were successfully performed.
This work provides the first example of the homopolymerization of endo-cyclic disulfides by ED-ROMP and the first substantial study into the kinetics of the ED-RODiMP process.
Causes for slow weathering and erosion in the steep, warm, monsoon-subjected Highlands of Sri Lanka
(2018)
In the Highlands of Sri Lanka, erosion and chemical weathering rates are among the lowest for global mountain denudation. In this tropical humid setting, highly weathered deep saprolite profiles have developed from high-grade metamorphic charnockite during spheroidal weathering of the bedrock. The spheroidal weathering produces rounded corestones and spalled rindlets at the rock-saprolite interface. I used detailed textural, mineralogical, chemical, and electron-microscopic (SEM, FIB, TEM) analyses to identify the factors limiting the rate of weathering front advance in the profile, the sequence of weathering reactions, and the underlying mechanisms. The first mineral attacked by weathering was found to be pyroxene initiated by in situ Fe oxidation, followed by in situ biotite oxidation. Bulk dissolution of the primary minerals is best described with a dissolution – re-precipitation process, as no chemical gradients towards the mineral surface and sharp structural boundaries are observed at the nm scale. Only the local oxidation in pyroxene and biotite is better described with an ion by ion process. The first secondary phases are oxides and amorphous precipitates from which secondary minerals (mainly smectite and kaolinite) form. Only for biotite direct solid state transformation to kaolinite is likely. The initial oxidation of pyroxene and biotite takes place in locally restricted areas and is relatively fast: log J = -11 molmin/(m2 s). However, calculated corestone-scale mineral oxidation rates are comparable to corestone-scale mineral dissolution rates: log R = -13 molpx/(m2 s) and log R = -15 molbt/(m2 s). The oxidation reaction results in a volume increase. Volumetric calculations suggest that this observed oxidation leads to the generation of porosity due to the formation of micro-fractures in the minerals and the bedrock allowing for fluid transport and subsequent dissolution of plagioclase. At the scale of the corestone, this fracture reaction is responsible for the larger fractures that lead to spheroidal weathering and to the formation of rindlets. Since these fractures have their origin from the initial oxidational induced volume increase, oxidation is the rate limiting parameter for weathering to take place. The ensuing plagioclase weathering leads to formation of high secondary porosity in the corestone over a distance of only a few cm and eventually to the final disaggregation of bedrock to saprolite. As oxidation is the first weathering reaction, the supply of O2 is a rate-limiting factor for chemical weathering. Hence, the supply of O2 and its consumption at depth connects processes at the weathering front with erosion at the surface in a feedback mechanism. The strength of the feedback depends on the relative weight of advective versus diffusive transport of O2 through the weathering profile. The feedback will be stronger with dominating diffusive transport. The low weathering rate ultimately depends on the transport of O2 through the whole regolith, and on lithological factors such as low bedrock porosity and the amount of Fe-bearing primary minerals. In this regard the low-porosity charnockite with its low content of Fe(II) bearing minerals impedes fast weathering reactions. Fresh weatherable surfaces are a pre-requisite for chemical weathering. However, in the case of the charnockite found in the Sri Lankan Highlands, the only process that generates these surfaces is the fracturing induced by oxidation. Tectonic quiescence in this region and low pre-anthropogenic erosion rate (attributed to a dense vegetation cover) minimize the rejuvenation of the thick and cohesive regolith column, and lowers weathering through the feedback with erosion.
The work done during the PhD studies has been focused on measurements of distribution functions of rotating galaxies using integral field spectroscopy observations.
Throughout the main body of research presented here we have been using CALIFA (Calar Alto Legacy Integral Field Area) survey stellar velocity fields to obtain robust measurements of circular velocities for rotating galaxies of all morphological types. A crucial part of the work was enabled by well-defined CALIFA sample selection criteria: it enabled reconstructing sample-independent distributions of galaxy properties.
In Chapter 2, we measure the distribution in absolute magnitude - circular velocity space for a well-defined sample of 199 rotating CALIFA galaxies using their stellar kinematics. Our aim in this analysis is to avoid subjective selection criteria and to take volume and large-scale structure factors into account. Using stellar velocity fields instead of gas emission line kinematics allows including rapidly rotating early type galaxies. Our initial sample contains 277 galaxies with available stellar velocity fields and growth curve r-band photometry. After rejecting 51 velocity fields that could not be modelled due to the low number of bins, foreground contamination or significant interaction we perform Markov Chain Monte Carlo (MCMC) modelling of the velocity fields, obtaining the rotation curve and kinematic parameters and their realistic uncertainties. We perform an extinction correction and calculate the circular velocity v_circ accounting for pressure support a given galaxy has. The resulting galaxy distribution on the M_r - v_circ plane is then modelled as a mixture of two distinct populations, allowing robust and reproducible rejection of outliers, a significant fraction of which are slow rotators. The selection effects are understood well enough that the incompleteness of the sample can be corrected and the 199 galaxies can be weighted by volume and large-scale structure factors enabling us to fit a volume-corrected Tully-Fisher relation (TFR). More importantly, we also provide the volume-corrected distribution of galaxies in the M_r - v_circ plane, which can be compared with cosmological simulations. The joint distribution of the luminosity and circular velocity space densities, representative over the range of -20 > M_r > -22 mag, can place more stringent constraints on the galaxy formation and evolution scenarios than linear TFR fit parameters or the luminosity function alone.
In Chapter 3, we measure one of the marginal distributions of the M_r - v_circ distribution: the circular velocity function of rotating galaxies. The velocity function is a fundamental observable statistic of the galaxy population, being of a similar importance as the luminosity function, but much more difficult to measure. We present the first directly measured circular velocity function that is representative between 60 < v_circ < 320 km s^-1 for galaxies of all morphological types at a given rotation velocity. For the low mass galaxy population 60 < v_circ < 170 km s^-1, we use the HIPASS velocity function. For the massive galaxy population 170 < v_circ < 320 km s^-1, we use stellar circular velocities from CALIFA. The CALIFA velocity function includes homogeneous velocity measurements of both late and early-type rotation-supported galaxies. It has the crucial advantage of not missing gas-poor massive ellipticals that HI surveys are blind to. We show that both velocity functions can be combined in a seamless manner, as their ranges of validity overlap. The resulting observed velocity function is compared to velocity functions derived from cosmological simulations of the z = 0 galaxy population. We find that dark matter-only simulations show a strong mismatch with the observed VF. Hydrodynamic Illustris simulations fare better, but still do not fully reproduce observations.
In Chapter 4, we present some other work done during the PhD studies, namely, a method that improves the precision of specific angular measurements by combining simultaneous Markov Chain Monte Carlo modelling of ionised gas 2D velocity fields and HI linewidths. To test the method we use a sample of 25 galaxies from the Sydney-AAO Multi-object Integral field (SAMI) survey that had matching ALFALFA HI linewidths. Such a method allows constraining the rotation curve both in the inner regions of a galaxy and in its outskirts, leading to increased precision of specific angular momentum measurements. It could be used to further constrain the observed relation between galaxy mass, specific angular momentum and morphology (Obreschkow & Glazebrook 2014).
Mathematical and computational methods are presented in the appendices.
We do magnetohydrodynamic (MHD) simulations of local box models of turbulent Interstellar Medium (ISM) and analyse the process of amplification and saturation of mean magnetic fields with methods of mean field dynamo theory. It is shown that the process of saturation of mean fields can be partially described by the prolonged diffusion time scales in presence of the dynamically significant magnetic fields. However, the outward wind also plays an essential role in the saturation in higher SN rate case. Algebraic expressions for the back reaction of the magnetic field onto the turbulent transport coefficients are derived, which allow a complete description of the nonlinear dynamo. We also present the effects of dynamically significant mean fields on the ISM configuration and pressure distribution. We further add the cosmic ray component in the simulations and investigate the kinematic growth of mean fields with a dynamo perspective.
Efficiently managing large state is a key challenge for data management systems. Traditionally, state is split into fast but volatile state in memory for processing and persistent but slow state on secondary storage for durability. Persistent memory (PMem), as a new technology in the storage hierarchy, blurs the lines between these states by offering both byte-addressability and low latency like DRAM as well persistence like secondary storage. These characteristics have the potential to cause a major performance shift in database systems.
Driven by the potential impact that PMem has on data management systems, in this thesis we explore their use of PMem. We first evaluate the performance of real PMem hardware in the form of Intel Optane in a wide range of setups. To this end, we propose PerMA-Bench, a configurable benchmark framework that allows users to evaluate the performance of customizable database-related PMem access. Based on experimental results obtained with PerMA-Bench, we discuss findings and identify general and implementation-specific aspects that influence PMem performance and should be considered in future work to improve PMem-aware designs. We then propose Viper, a hybrid PMem-DRAM key-value store. Based on PMem-aware access patterns, we show how to leverage PMem and DRAM efficiently to design a key database component. Our evaluation shows that Viper outperforms existing key-value stores by 4–18x for inserts while offering full data persistence and achieving similar or better lookup performance. Next, we show which changes must be made to integrate PMem components into larger systems. By the example of stream processing engines, we highlight limitations of current designs and propose a prototype engine that overcomes these limitations. This allows our prototype to fully leverage PMem's performance for its internal state management. Finally, in light of Optane's discontinuation, we discuss how insights from PMem research can be transferred to future multi-tier memory setups by the example of Compute Express Link (CXL).
Overall, we show that PMem offers high performance for state management, bridging the gap between fast but volatile DRAM and persistent but slow secondary storage. Although Optane was discontinued, new memory technologies are continuously emerging in various forms and we outline how novel designs for them can build on insights from existing PMem research.
Requirements engineers have to elicit, document, and validate how stakeholders act and interact to achieve their common goals in collaborative scenarios. Only after gathering all information concerning who interacts with whom to do what and why, can a software system be designed and realized which supports the stakeholders to do their work. To capture and structure requirements of different (groups of) stakeholders, scenario-based approaches have been widely used and investigated. Still, the elicitation and validation of requirements covering collaborative scenarios remains complicated, since the required information is highly intertwined, fragmented, and distributed over several stakeholders. Hence, it can only be elicited and validated collaboratively. In times of globally distributed companies, scheduling and conducting workshops with groups of stakeholders is usually not feasible due to budget and time constraints. Talking to individual stakeholders, on the other hand, is feasible but leads to fragmented and incomplete stakeholder scenarios. Going back and forth between different individual stakeholders to resolve this fragmentation and explore uncovered alternatives is an error-prone, time-consuming, and expensive task for the requirements engineers. While formal modeling methods can be employed to automatically check and ensure consistency of stakeholder scenarios, such methods introduce additional overhead since their formal notations have to be explained in each interaction between stakeholders and requirements engineers. Tangible prototypes as they are used in other disciplines such as design, on the other hand, allow designers to feasibly validate and iterate concepts and requirements with stakeholders. This thesis proposes a model-based approach for prototyping formal behavioral specifications of stakeholders who are involved in collaborative scenarios. By simulating and animating such specifications in a remote domain-specific visualization, stakeholders can experience and validate the scenarios captured so far, i.e., how other stakeholders act and react. This interactive scenario simulation is referred to as a model-based virtual prototype. Moreover, through observing how stakeholders interact with a virtual prototype of their collaborative scenarios, formal behavioral specifications can be automatically derived which complete the otherwise fragmented scenarios. This, in turn, enables requirements engineers to elicit and validate collaborative scenarios in individual stakeholder sessions – decoupled, since stakeholders can participate remotely and are not forced to be available for a joint session at the same time. This thesis discusses and evaluates the feasibility, understandability, and modifiability of model-based virtual prototypes. Similarly to how physical prototypes are perceived, the presented approach brings behavioral models closer to being tangible for stakeholders and, moreover, combines the advantages of joint stakeholder sessions and decoupled sessions.
Cargo transport by molecular motors is ubiquitous in all eukaryotic cells and is typically driven cooperatively by several molecular motors, which may belong to one or several motor species like kinesin, dynein or myosin. These motor proteins transport cargos such as RNAs, protein complexes or organelles along filaments, from which they unbind after a finite run length. Understanding how these motors interact and how their movements are coordinated and regulated is a central and challenging problem in studies of intracellular transport. In this thesis, we describe a general theoretical framework for the analysis of such transport processes, which enables us to explain the behavior of intracellular cargos based on the transport properties of individual motors and their interactions. Motivated by recent in vitro experiments, we address two different modes of transport: unidirectional transport by two identical motors and cooperative transport by actively walking and passively diffusing motors. The case of cargo transport by two identical motors involves an elastic coupling between the motors that can reduce the motors’ velocity and/or the binding time to the filament. We show that this elastic coupling leads, in general, to four distinct transport regimes. In addition to a weak coupling regime, kinesin and dynein motors are found to exhibit a strong coupling and an enhanced unbinding regime, whereas myosin motors are predicted to attain a reduced velocity regime. All of these regimes, which we derive both by analytical calculations and by general time scale arguments, can be explored experimentally by varying the elastic coupling strength. In addition, using the time scale arguments, we explain why previous studies came to different conclusions about the effect and relevance of motor-motor interference. In this way, our theory provides a general and unifying framework for understanding the dynamical behavior of two elastically coupled molecular motors. The second mode of transport studied in this thesis is cargo transport by actively pulling and passively diffusing motors. Although these passive motors do not participate in active transport, they strongly enhance the overall cargo run length. When an active motor unbinds, the cargo is still tethered to the filament by the passive motors, giving the unbound motor the chance to rebind and continue its active walk. We develop a stochastic description for such cooperative behavior and explicitly derive the enhanced run length for a cargo transported by one actively pulling and one passively diffusing motor. We generalize our description to the case of several pulling and diffusing motors and find an exponential increase of the run length with the number of involved motors.
For more than two centuries, plant ecologists have aimed to understand how environmental gradients and biotic interactions shape the distribution and co-occurrence of plant species. In recent years, functional trait–based approaches have been increasingly used to predict patterns of species co-occurrence and species distributions along environmental gradients (trait–environment relationships). Functional traits are measurable properties at the individual level that correlate well with important processes. Thus, they allow us to identify general patterns by synthesizing studies across specific taxonomic compositions, thereby fostering our understanding of the underlying processes of species assembly. However, the importance of specific processes have been shown to be highly dependent on the spatial scale under consideration. In particular, it remains uncertain which mechanisms drive species assembly and allow for plant species coexistence at smaller, more local spatial scales. Furthermore, there is still no consensus on how particular environmental gradients affect the trait composition of plant communities. For example, increasing drought because of climate change is predicted to be a main threat to plant diversity, although it remains unclear which traits of species respond to increasing aridity. Similarly, there is conflicting evidence of how soil fertilization affects the traits related to establishment ability (e.g., seed mass). In this cumulative dissertation, I present three empirical trait-based studies that investigate specific research questions in order to improve our understanding of species distributions along environmental gradients.
In the first case study, I analyze how annual species assemble at the local scale and how environmental heterogeneity affects different facets of biodiversity—i.e. taxonomic, functional, and phylogenetic diversity—at different spatial scales. The study was conducted in a semi-arid environment at the transition zone between desert and Mediterranean ecosystems that features a sharp precipitation gradient (Israel). Different null model analyses revealed strong support for environmentally driven species assembly at the local scale, since species with similar traits tended to co-occur and shared high abundances within microsites (trait convergence). A phylogenetic approach, which assumes that closely related species are functionally more similar to each other than distantly related ones, partly supported these results. However, I observed that species abundances within microsites were, surprisingly, more evenly distributed across the phylogenetic tree than expected (phylogenetic overdispersion). Furthermore, I showed that environmental heterogeneity has a positive effect on diversity, which was higher on functional than on taxonomic diversity and increased with spatial scale. The results of this case study indicate that environmental heterogeneity may act as a stabilizing factor to maintain species diversity at local scales, since it influenced species distribution according to their traits and positively influenced diversity. All results were constant along the precipitation gradient.
In the second case study (same study system as case study one), I explore the trait responses of two Mediterranean annuals (Geropogon hybridus and Crupina crupinastrum) along a precipitation gradient that is comparable to the maximum changes in precipitation predicted to occur by the end of this century (i.e., −30%). The heterocarpic G. hybridus showed strong trends in seed traits, suggesting that dispersal ability increased with aridity. By contrast, the homocarpic C. crupinastrum showed only a decrease in plant height as aridity increased, while leaf traits of both species showed no consistent pattern along the precipitation gradient. Furthermore, variance decomposition of traits revealed that most of the trait variation observed in the study system was actually found within populations. I conclude that trait responses towards aridity are highly species-specific and that the amount of precipitation is not the most striking environmental factor at this particular scale.
In the third case study, I assess how soil fertilization mediates—directly by increased nutrient addition and indirectly by increased competition—the effect of seed mass on establishment ability. For this experiment, I used 22 species differing in seed mass from dry grasslands in northeastern Germany and analyzed the interacting effects of seed mass with nutrient availability and competition on four key components of seedling establishment: seedling emergence, time of seedling emergence, seedling survival, and seedling growth. (Time of) seedling emergence was not affected by seed mass. However, I observed that the positive effect of seed mass on seedling survival is lowered under conditions of high nutrient availability, whereas the positive effect of seed mass on seedling growth was only reduced by competition. Based on these findings, I developed a conceptual model of how seed mass should change along a soil fertility gradient in order to reconcile conflicting findings from the literature. In this model, seed mass shows a U-shaped pattern along the soil fertility gradient as a result of changing nutrient availability and competition.
Overall, the three case studies highlight the role of environmental factors on species distribution and co-occurrence. Moreover, the findings of this thesis indicate that spatial heterogeneity at local scales may act as a stabilizing factor that allows species with different traits to coexist. In the concluding discussion, I critically debate intraspecific trait variability in plant community ecology, the use of phylogenetic relationships and easily measured key functional traits as a proxy for species’ niches. Finally, I offer my outlook for the future of functional plant community research.
In this work, an approach of paleoclimate reconstruction for tropical East Africa is presented. After giving a short summary of modern climate conditions in the tropics and the East African climate peculiarity, the potential of reconstructing climate from paleolake sediments is discussed. As demonstrated, the hydrologic sensitivity of high-elevated closed-basin lakes in the Central Kenya Rift yields valuable guaranties for the establishment of long-term climate records. Temporal fluctuations of the limnological characteristics saved in the lake sediments are used to define variations in the Quaternary climate history. Based on diatom analyses in radiocarbon- and 40Ar/39Ar-dated sediments, a chronology of paleoecologic fluctuations is developed for the Central Kenya Rift -lakes Nakuru, Elmenteita and Naivasha. At least during the penultimate interglacial (around 140 to 60 kyr BP) and during the last interglacial (around 12 to 4 kyr BP), these lakes experienced several transgression-regression cycles on time intervals of about 11,000 years. Additionally, a long-term trend of lake evolution is found suggesting the general succession from deep freshwater lakes towards more saline waters during the last million years. Using ecologic transfer functions and a simple lake-balance model, the observed paleohydrologic fluctuations are linked to potential precipitation-evaporation changes in the lake basins. Though also tectonic influences on the drainage pattern and the effect of varied seepage are investigated, it can be shown that already a small increase in precipitation of about 30±10 % may have affected the hydrologic budget of the intra-rift lakes within the reconstructed range. The findings of this study help to assess the natural climate variability of East Africa. They furthermore reflect the sensitivity of the Central Kenya Rift -lakes to fluctuations of large-scale climate parameters, such as solar radiation and sea-surface temperatures of the Indian Ocean.
In the present work synchronization phenomena in complex dynamical systems exhibiting multiple time scales have been analyzed. Multiple time scales can be active in different manners. Three different systems have been analyzed with different methods from data analysis. The first system studied is a large heterogenous network of bursting neurons, that is a system with two predominant time scales, the fast firing of action potentials (spikes) and the burst of repetitive spikes followed by a quiescent phase. This system has been integrated numerically and analyzed with methods based on recurrence in phase space. An interesting result are the different transitions to synchrony found in the two distinct time scales. Moreover, an anomalous synchronization effect can be observed in the fast time scale, i.e. there is range of the coupling strength where desynchronization occurs. The second system analyzed, numerically as well as experimentally, is a pair of coupled CO₂ lasers in a chaotic bursting regime. This system is interesting due to its similarity with epidemic models. We explain the bursts by different time scales generated from unstable periodic orbits embedded in the chaotic attractor and perform a synchronization analysis of these different orbits utilizing the continuous wavelet transform. We find a diverse route to synchrony of these different observed time scales. The last system studied is a small network motif of limit cycle oscillators. Precisely, we have studied a hub motif, which serves as elementary building block for scale-free networks, a type of network found in many real world applications. These hubs are of special importance for communication and information transfer in complex networks. Here, a detailed study on the mechanism of synchronization in oscillatory networks with a broad frequency distribution has been carried out. In particular, we find a remote synchronization of nodes in the network which are not directly coupled. We also explain the responsible mechanism and its limitations and constraints. Further we derive an analytic expression for it and show that information transmission in pure phase oscillators, such as the Kuramoto type, is limited. In addition to the numerical and analytic analysis an experiment consisting of electrical circuits has been designed. The obtained results confirm the former findings.
Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of the observations. Unraveling such transitions yields essential information for the understanding of the observed system’s intrinsic evolution and potential external influences. A precise detection of multiple changes is therefore of great importance for various research disciplines, such as environmental sciences, bioinformatics and economics. The primary purpose of the detection approach introduced in this thesis is the investigation of transitions underlying direct or indirect climate observations. In order to develop a diagnostic approach capable to capture such a variety of natural processes, the generic statistical features in terms of central tendency and dispersion are employed in the light of Bayesian inversion. In contrast to established Bayesian approaches to multiple changes, the generic approach proposed in this thesis is not formulated in the framework of specialized partition models of high dimensionality requiring prior specification, but as a robust kernel-based approach of low dimensionality employing least informative prior distributions.
First of all, a local Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of a single transition. The analysis of synthetic time series comprising changes of different observational evidence, data loss and outliers validates the performance, consistency and sensitivity of the inference algorithm. To systematically investigate time series for multiple changes, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the weighted kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. The detection approach is applied to environmental time series from the Nile river in Aswan and the weather station Tuscaloosa, Alabama comprising documented changes. The method’s performance confirms the approach as a powerful diagnostic tool to decipher multiple changes underlying direct climate observations.
Finally, the kernel-based Bayesian inference approach is used to investigate a set of complex terrigenous dust records interpreted as climate indicators of the African region of the Plio-Pleistocene period. A detailed inference unravels multiple transitions underlying the indirect climate observations, that are interpreted as conjoint changes. The identified conjoint changes coincide with established global climate events. In particular, the two-step transition associated to the establishment of the modern Walker-Circulation contributes to the current discussion about the influence of paleoclimate changes on the environmental conditions in tropical and subtropical Africa at around two million years ago.
Microsaccades
(2015)
The first thing we do upon waking is open our eyes. Rotating them in our eye sockets, we scan our surroundings and collect the information into a picture in our head. Eye movements can be split into saccades and fixational eye movements, which occur when we attempt to fixate our gaze. The latter consists of microsaccades, drift and tremor. Before we even lift our eye lids, eye movements – such as saccades and microsaccades that let the eyes jump from one to another position – have partially been prepared in the brain stem. Saccades and microsaccades are often assumed to be generated by the same mechanisms. But how saccades and microsaccades can be classified according to shape has not yet been reported in a statistical manner. Research has put more effort into the investigations of microsaccades’ properties and generation only since the last decade. Consequently, we are only beginning to understand the dynamic processes governing microsaccadic eye movements. Within this thesis, the dynamics governing the generation of microsaccades is assessed and the development of a model for the underlying processes. Eye movement trajectories from different experiments are used, recorded with a video-based eye tracking technique, and a novel method is proposed for the scale-invariant detection of saccades (events of large amplitude) and microsaccades (events of small amplitude). Using a time-frequency approach, the method is examined with different experiments and validated against simulated data. A shape model is suggested that allows for a simple estimation of saccade- and microsaccade related properties. For sequences of microsaccades, in this thesis a time-dynamic Markov model is proposed, with a memory horizon that changes over time and which can best describe sequences of microsaccades.
Nowadays, graph data models are employed, when relationships between entities have to be stored and are in the scope of queries. For each entity, this graph data model locally stores relationships to adjacent entities. Users employ graph queries to query and modify these entities and relationships. These graph queries employ graph patterns to lookup all subgraphs in the graph data that satisfy certain graph structures. These subgraphs are called graph pattern matches. However, this graph pattern matching is NP-complete for subgraph isomorphism. Thus, graph queries can suffer a long response time, when the number of entities and relationships in the graph data or the graph patterns increases.
One possibility to improve the graph query performance is to employ graph views that keep ready graph pattern matches for complex graph queries for later retrieval. However, these graph views must be maintained by means of an incremental graph pattern matching to keep them consistent with the graph data from which they are derived, when the graph data changes. This maintenance adds subgraphs that satisfy a graph pattern to the graph views and removes subgraphs that do not satisfy a graph pattern anymore from the graph views.
Current approaches for incremental graph pattern matching employ Rete networks. Rete networks are discrimination networks that enumerate and maintain all graph pattern matches of certain graph queries by employing a network of condition tests, which implement partial graph patterns that together constitute the overall graph query. Each condition test stores all subgraphs that satisfy the partial graph pattern. Thus, Rete networks suffer high memory consumptions, because they store a large number of partial graph pattern matches. But, especially these partial graph pattern matches enable Rete networks to update the stored graph pattern matches efficiently, because the network maintenance exploits the already stored partial graph pattern matches to find new graph pattern matches. However, other kinds of discrimination networks exist that can perform better in time and space than Rete networks. Currently, these other kinds of networks are not used for incremental graph pattern matching.
This thesis employs generalized discrimination networks for incremental graph pattern matching. These discrimination networks permit a generalized network structure of condition tests to enable users to steer the trade-off between memory consumption and execution time for the incremental graph pattern matching. For that purpose, this thesis contributes a modeling language for the effective definition of generalized discrimination networks. Furthermore, this thesis contributes an efficient and scalable incremental maintenance algorithm, which updates the (partial) graph pattern matches that are stored by each condition test. Moreover, this thesis provides a modeling evaluation, which shows that the proposed modeling language enables the effective modeling of generalized discrimination networks. Furthermore, this thesis provides a performance evaluation, which shows that a) the incremental maintenance algorithm scales, when the graph data becomes large, and b) the generalized discrimination network structures can outperform Rete network structures in time and space at the same time for incremental graph pattern matching.
The selective infrared (IR) excitation of molecular vibrations is a powerful tool to control the photoreactivity prior to electronic excitation in the ultraviolet / visible (UV/Vis) light regime ("vibrationally mediated chemistry"). For adsorbates on surfaces it has been theoretically predicted that IR preexcitation will lead to higher UV/Vis photodesorption yields and larger cross sections for other photoreactions. In a recent experiment, IR-mediated desorption of molecular hydrogen from a Si(111) surface on which atomic hydrogen and deuterium were co-adsorbed was achieved, following a vibrational mechanism as indicated by the isotope-selectivity. In the present work, selective vibrational IR excitation of adsorbate molecules, treated as multi-dimensional oscillators on dissipative surfaces, has been simulated within the framework of open-system density matrix theory. Not only potential-mediated, inter-mode coupling poses an obstacle to selective excitation but also the coupling of the adsorbate ("system") modes to the electronic and phononic degrees of freedom of the surface ("bath") does. Vibrational relaxation thereby takes place, depending on the availabilty of energetically fitting electron-hole (e/h) pairs and/or phonons (lattice vibrations) in the surface, on time-scales ranging from milliseconds to several hundreds of femtoseconds. On metal surfaces, where the relaxation process of the adsorbate via the e/h pair mechanism dominates, vibrational lifetimes are usually shorter than on insulator or semiconductor surfaces, in the range of picoseconds, being also the timescale of the IR pulses used here. Further inhibiting factors for selectivity can be the harmonicity of a mode and weak dipole activities ("dark modes") rendering vibrational excitation with moderate field intensities difficult. In addition to simple analytical pulses, optimal control theory (OCT) has been employed here to generate a suitable electric field to populate the target state/mode maximally. The complex OCT fields were analyzed by Husimi transformation, resolving the control field in time and energy. The adsorbate/surface systems investigated were CO/Cu(100), H/Si(100) and 2H/Ru(0001). These systems proved to be suitable models to study the above mentioned effects. Further, effects of temperature, pure dephasing (elastic scattering processes), pulse duration and dimensionality (up to four degrees of freedom) were studied. It was possible to selectively excite single vibrational modes, often even state-selective. Special processes like hot-band excitation, vibrationally mediated desorption and the excitation of "dark modes" were simulated. Finally, a novel OCT algorithm in density matrix representation has been developed which allows for time-dependent target operators and thus enables to control the excitation mechanism instead of only the final state. The algorithm is based on a combination of global (iterative) and local (non-iterative) OCT schemes, such that short, globally controlled time-intervals are coupled locally in time. Its numerical performance and accuracy were tested and verified and it was successfully applied to stabilize a two-state linear-combination and to enforce a successive "ladder climbing" in a rather harmonic system, where monochromatic, analytical pulses simultaneously excited several states, leading to a population loss in the target state.
In this work approaches for new detection system development for an Analytical Ultracentrifuge (AUC) were explored. Unlike its counterpart in chromatography fractionation techniques, the use of a Multidetection system for AUC has not yet been implemented to full extent despite its potential benefit. In this study we tried to couple existing fundamental spectroscopic and scattering techniques that are used in day to day science as tool for extracting analyte information. Trials were performed for adapting Raman, Light scattering and UV/Vis (with possibility to work with the whole range of wavelengths) to AUC. Conclusions were drawn for Raman and Light scattering to be a possible detection system for AUC, while the development for a fast fiber optics based multiwavelength detector was completed. The multiwavelength detector demonstrated the capability of data generation matching the literature and reference measurement data and faster data collection than that of the commercial instrument. It became obvious that with the generation of data in 3-D space in the UV/Vis detection system, the user can select the wavelength for the evaluation of experimental results as the data set contains the whole range of information from UV/Vis wavelength. The detector showed the data generation with much faster speed unlike the commercial instruments. The advantage of fast data generation was exemplified with the evaluation of data for a mixture of three colloids. These data were in conformity with measurement results from normal radial experiments and without significant diffusion broadening. Thus conclusions were drawn that with our designed Multiwavelength detector, meaningful data in 3-D space can be collected with much faster speed of data generation.
One of the main problems in machine learning is to train a predictive model from training data and to make predictions on test data. Most predictive models are constructed under the assumption that the training data is governed by the exact same distribution which the model will later be exposed to. In practice, control over the data collection process is often imperfect. A typical scenario is when labels are collected by questionnaires and one does not have access to the test population. For example, parts of the test population are underrepresented in the survey, out of reach, or do not return the questionnaire. In many applications training data from the test distribution are scarce because they are difficult to obtain or very expensive. Data from auxiliary sources drawn from similar distributions are often cheaply available. This thesis centers around learning under differing training and test distributions and covers several problem settings with different assumptions on the relationship between training and test distributions-including multi-task learning and learning under covariate shift and sample selection bias. Several new models are derived that directly characterize the divergence between training and test distributions, without the intermediate step of estimating training and test distributions separately. The integral part of these models are rescaling weights that match the rescaled or resampled training distribution to the test distribution. Integrated models are studied where only one optimization problem needs to be solved for learning under differing distributions. With a two-step approximation to the integrated models almost any supervised learning algorithm can be adopted to biased training data. In case studies on spam filtering, HIV therapy screening, targeted advertising, and other applications the performance of the new models is compared to state-of-the-art reference methods.
Carbonates play a key role in the chemistry and dynamics of our planet. They are directly connected to the CO2 budget of our atmosphere and have a great impact on the deep carbon cycle. Moreover, recent studies have shown that carbonates are stable along the geothermal gradient down to Earth's lower mantle conditions, changing their crystal structure and related properties. Subducted carbonates may also react with silicates to form new phases. These reactions will redistribute elements, such as calcium (Ca), magnesium (Mg), iron (Fe) and carbon in the form of carbon dioxide (CO2), but also trace elements, that are carried by the carbonates. The trace elements of most interest are strontium (Sr) and rare earth elements (REE) which have been found to be important constituents in the composition of the primitive lower mantle and in mineral inclusions found in super-deep diamonds. However, the stability of carbonates in presence of mantle silicates at relevant temperatures is far from being well understood. Related to this, very little is known about distribution processes of trace elements between carbonates and mantle silicates. To shed light on these processes, we studied reactions between Sr- and REE-containing CaCO3 and Mg/Fe-bearing silicates of the system (Mg,Fe)2SiO4 - (Mg,Fe)SiO3 at high pressure and high temperature using synchrotron radiation based μ-X-ray diffraction (μ-XRD) and μ-X-ray fluorescence (μ-XRF) with μm-resolution in a laser-heated diamond anvil cell. X-ray diffraction is used to derive the structural changes of the phase reactions whereas X-ray fluorescence gives information on the chemical changes in the sample. In-situ experiments at high pressure and high temperature were performed at beamline P02.2 at PETRA III (Hamburg, Germany) and at beamline ID27 at ESRF (Grenoble, France). In addition to μ-XRD and μ-XRF, ex-situ measurements were made on the recovered sample material using transmission electron microscopy (TEM) and provided further insights into the reaction kinetics of carbonate-silicate reactions.
Our investigations show that CaCO3 is unstable in presence of mantle silicates above 1700 K and a reaction takes place in which magnesite plus CaSiO3-perovskite are formed. In addition, we observed that a high content of iron in the carbonate-silicate system favours dolomite formation during the reaction. The subduction of natural carbonates with significant amounts of Sr leads to a comprehensive investigation of the stability not only of CaCO3 phases in contact with mantle silicates but also of SrCO3 (and of Sr-bearing CaCO3). We found that SrCO3 reacts with (Mg,Fe)SiO3-perovskite to form magnesite and gained evidence for the formation of SrSiO3-perovskite.
To complement our study on the stability of SrCO3 at conditions of the Earth's lower mantle, we performed powder X-ray diffraction and single crystal X-ray diffraction experiments at ambient temperature and up to 49 GPa. We observed a transformation from SrCO3-I into a new high-pressure phase SrCO3-II at around 26 GPa with Pmmn crystal structure and a bulk modulus of 103(10) GPa. This information is essential to fully understand the phase behaviour and stability of carbonates in the Earth's lower mantle and to elucidate the possibility of introducing Sr into mantle silicates by carbonate-silicate reactions.
Simultaneous recording of μ-XRD and μ-XRF in the μm-range over the heated areas provides spatial information not only about phase reactions but also on the elemental redistribution during the reactions. A comparison of the spatial intensity distribution of the XRF signal before and after heating indicates a change in the elemental distribution of Sr and an increase in Sr-concentration was found around the newly formed SrSiO3-perovskite. With the help of additional TEM analyses on the quenched sample material the elemental redistribution was studied at a sub-micrometer scale. Contrary to expectations from combined μ-XRD and μ-XRF measurements, we found that La and Eu were not incorporated into the silicate phases, instead they tend to form either isolated oxide phases (e.g. Eu2O3, La2O3) or hydroxyl-bastnäsite (La(CO3)(OH)). In addition, we observed the transformation from (Mg,Fe)SiO3-perovskite to low-pressure clinoenstatite during pressure release. The monoclinic structure (P21/c) of this phase allows the incorporation of Ca as shown by additional EDX analyses and, to a minor extent, Sr too.
Based on our experiments, we can conclude that a detection of the trace elements in-situ at high pressure and high temperature remains challenging. However, our first findings imply that silicates may incorporate the trace elements provided by the carbonates and indicate that carbonates may have a major effect on the trace element contents of mantle phases.
Sulphur, a macronutrient essential for plant growth, is among the most versatile elements in living organisms. Unfortunately, little is known about regulation of sulphate uptake and assimilation by plants. Identification of sulphate signalling processes will allow to control sulphate acquisition and assimilation and may prove useful in the future to improve sulphur-use efficiency in agriculture. Many of genes involved in sulphate metabolism are regulated on transcriptional level by products of other genes called transcription factors (TF). Several published experiments revealed TF genes that respond to sulphate deprivation, but none of these have been so far been characterized functionally. Thus, we aimed at identifying and characterising transcription factors that control sulphate metabolism in the model plant Arabidopsis thaliana. To achieve that goal we postulated that factors regulating Arabidopsis responses to inorganic sulphate deficiency change their transcriptional levels under sulphur-limited conditions. By comparing TF transcript profiles from plants grown on different sulphate regimes, we identified TF genes that may specifically induce or repress changes in expression of genes that allow plants to adapt to changes in sulphate availability. Candidate genes obtained from this screening were tested by reverse genetics approaches. Transgenic plants constitutively overproducing selected TF genes and mutant plants, lacking functional selected TF genes (knock out), were used. By comparing metabolite and transcript profiles from transgenic and wild type plants we aimed at confirming the role of selected AP2 TF candidate genes in plant adaptation to sulphur unavailability. After preliminary characterisation of WRKY24 and MYB93 TF genes, we postulate that these factors are involved in a complex multifactorial regulatory network, in which WRKY24 and MYB93 would act as superior factors regulating other transcription factors directly involved in the regulation of S-metabolism genes. Results obtained for plants overproducing TOE1 and TOE2 TF genes suggests that these factors may be involved in a mechanism, which is promoting synthesis of an essential amino acid, methionine, over synthesis of another amino acid, cysteine. Thus, TOE1 and TOE2 genes might be a part of transcriptional regulation of methionine synthesis. Approaches creating genetically manipulated plants may produce plant phenotypes of immediate biotechnological interest, such as plants with increased sulphate or sulphate-containing amino acid content, or better adapted to the sulphate unavailability.
Sucrose synthase (Susy) is a key enzyme of sucrose metabolism, catalysing the reversible conversion of sucrose and UDP to UDP-glucose and fructose. Therefore, its activity, localization and function have been studied in various plant species. It has been shown that Susy can play a role in supplying energy in companion cells for phloem loading (Fu and Park, 1995), provides substrates for starch synthesis (Zrenner et al., 1995), and supplies UDP-glucose for cell wall synthesis (Haigler et al., 2001). Analysis of the Arabidopsis genome identifies six Susy isoforms. The expression of these isoforms was investigated using promoter-reporter gene constructs (GUS) and real time RT-PCR. Although these isoforms are closely related at the protein level they have radically different spatial and temporal patterns of expression in the plant with no two isoforms showing the same distribution. More than one isoform is expressed in all organs examined. Some of them have high but specific expression in particular organs or developmental stages whilst others are constantly expressed throughout the whole plant and across various stages of development. The in planta function of the six Susy isoforms were explored through analysis of T-DNA insertion mutants and RNAi lines. Plants without the expression of individual isoforms show no differences in growth and development, and are not significantly different from wild type plants in soluble sugars, starch and cellulose contents under all growth conditions investigated. Analysis of T-DNA insertion mutant lacking Sus3 isoform that was exclusively expressed in stomata cells only had a minor influence on guard cell osmoregulation and/or bioenergetics. Although none of the sucrose synthases appear to be essential for normal growth under our standard growth conditions, they may be necessary for growth under stress conditions. Different isoforms of sucrose synthase respond differently to various abiotic stresses. It has been shown that oxygen deprivation up regulates Sus1 and Sus4 and increases total Susy activity. However, the analysis of the plants with reduced expression of both Sus1 and Sus4 revealed no obvious effects on plant performance under oxygen deprivation. Low temperature up regulates Sus1 expression but the loss of this isoform has no effect on the freezing tolerance of non acclimated and cold acclimated plants. These data provide a comprehensive overview of the expression of this gene family which supports some of the previously reported roles for Susy and indicates the involvement of specific isoforms in metabolism and/or signalling.
In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
This work analyzes the saving and consumption behavior of agents faced with the possibility of unemployment in a dynamic and stochastic life cycle model. The intertemporal optimization is based on Dynamic Programming with a backward recursion algorithm. The implemented uncertainty is not based on income shocks as it is done in traditional life cycle models but uses Markov probabilities where the probability for the next employment status of the agent depends on the current status. The utility function used is a CRRA function (constant relative risk aversion), combined with a CES function (constant elasticity of substitution) and has several consumption goods, a subsistence level, money and a bequest function.
Individuals have an intrinsic need to express themselves to other humans within a given community by sharing their experiences, thoughts, actions, and opinions. As a means, they mostly prefer to use modern online social media platforms such as Twitter, Facebook, personal blogs, and Reddit. Users of these social networks interact by drafting their own statuses updates, publishing photos, and giving likes leaving a considerable amount of data behind them to be analyzed. Researchers recently started exploring the shared social media data to understand online users better and predict their Big five personality traits: agreeableness, conscientiousness, extraversion, neuroticism, and openness to experience. This thesis intends to investigate the possible relationship between users’ Big five personality traits and the published information on their social media profiles. Facebook public data such as linguistic status updates, meta-data of likes objects, profile pictures, emotions, or reactions records were adopted to address the proposed research questions. Several machine learning predictions models were constructed with various experiments to utilize the engineered features correlated with the Big 5 Personality traits. The final predictive performances improved the prediction accuracy compared to state-of-the-art approaches, and the models were evaluated based on established benchmarks in the domain. The research experiments were implemented while ethical and privacy points were concerned. Furthermore, the research aims to raise awareness about privacy between social media users and show what third parties can reveal about users’ private traits from what they share and act on different social networking platforms.
In the second part of the thesis, the variation in personality development is studied within a cross-platform environment such as Facebook and Twitter platforms. The constructed personality profiles in these social platforms are compared to evaluate the effect of the used platforms on one user’s personality development. Likewise, personality continuity and stability analysis are performed using two social media platforms samples. The implemented experiments are based on ten-year longitudinal samples aiming to understand users’ long-term personality development and further unlock the potential of cooperation between psychologists and data scientists.
From its first use in the field of biochemistry, instrumental analysis offered a variety of invaluable tools for the comprehensive description of biological systems. Multi-selective methods that aim to cover as many endogenous compounds as possible in biological samples use different analytical platforms and include methods like gene expression profile and metabolite profile analysis. The enormous amount of data generated in application of profiling methods needs to be evaluated in a manner appropriate to the question under investigation. The new field of system biology rises to the challenge to develop strategies for collecting, processing, interpreting, and archiving this vast amount of data; to make those data available in form of databases, tools, models, and networks to the scientific community. On the background of this development a multi-selective method for the determination of phytohormones was developed and optimised, complementing the profile analyses which are already in use (Chapter I). The general feasibility of a simultaneous analysis of plant metabolites and phytohormones in one sample set-up was tested by studies on the analytical robustness of the metabolite profiling protocol. The recovery of plant metabolites proved to be satisfactory robust against variations in the extraction protocol by using common extraction procedures for phytohormones; a joint extraction of metabolites and hormones from plant tissue seems practicable (Chapter II). Quantification of compounds within the context of profiling methods requires particular scrutiny (Chapter II). In Chapter III, the potential of stable-isotope in vivo labelling as normalisation strategy for profiling data acquired with mass spectrometry is discussed. First promising results were obtained for a reproducible quantification by stable-isotope in vivo labelling, which was applied in metabolomic studies. In-parallel application of metabolite and phytohormone analysis to seedlings of the model plant Arabidopsis thaliana exposed to sulfate limitation was used to investigate the relationship between the endogenous concentration of signal elements and the ‘metabolic phenotype’ of a plant. An automated evaluation strategy was developed to process data of compounds with diverse physiological nature, such as signal elements, genes and metabolites – all which act in vivo in a conditional, time-resolved manner (Chapter IV). Final data analysis focussed on conditionality of signal-metabolome interactions.
The Arctic is considered as a focal region in the ongoing climate change debate. The currently observed and predicted climate warming is particularly pronounced in the high northern latitudes. Rising temperatures in the Arctic cause progressive deepening and duration of permafrost thawing during the arctic summer, creating an ‘active layer’ with high bioavailability of nutrients and labile carbon for microbial consumption. The microbial mineralization of permafrost carbon creates large amounts of greenhouse gases, including carbon dioxide and methane, which can be released to the atmosphere, creating a positive feedback to global warming. However, to date, the microbial communities that drive the overall carbon cycle and specifically methane production in the Arctic are poorly constrained. To assess how these microbial communities will respond to the predicted climate changes, such as an increase in atmospheric and soil temperatures causing increased bioavailability of organic carbon, it is necessary to investigate the current status of this environment, but also how these microbial communities reacted to climate changes in the past. This PhD thesis investigated three records from two different study sites in the Russian Arctic, including permafrost, lake shore and lake deposits from Siberia and Chukotka. A combined stratigraphic approach of microbial and molecular organic geochemical techniques were used to identify and quantify characteristic microbial gene and lipid biomarkers. Based on this data it was possible to characterize and identify the climate response of microbial communities involved in past carbon cycling during the Middle Pleistocene and the Late Pleistocene to Holocene. It is shown that previous warmer periods were associated with an expansion of bacterial and archaeal communities throughout the Russian Arctic, similar to present day conditions. Different from this situation, past glacial and stadial periods experienced a substantial decrease in the abundance of Bacteria and Archaea. This trend can also be confirmed for the community of methanogenic archaea that were highly abundant and diverse during warm and particularly wet conditions. For the terrestrial permafrost, a direct effect of the temperature on the microbial communities is likely. In contrast, it is suggested that the temperature rise in scope of the glacial-interglacial climate variations led to an increase of the primary production in the Arctic lake setting, as can be seen in the corresponding biogenic silica distribution. The availability of this algae-derived carbon is suggested to be a driver for the observed pattern in the microbial abundance. This work demonstrates the effect of climate changes on the community composition of methanogenic archae. Methanosarcina-related species were abundant throughout the Russian Arctic and were able to adapt to changing environmental conditions. In contrast, members of Methanocellales and Methanomicrobiales were not able to adapt to past climate changes. This PhD thesis provides first evidence that past climatic warming led to an increased abundance of microbial communities in the Arctic, closely linked to the cycling of carbon and methane production. With the predicted climate warming, it may, therefore, be anticipated that extensive amounts of microbial communities will develop. Increasing temperatures in the Arctic will affect the temperature sensitive parts of the current microbiological communities, possibly leading to a suppression of cold adapted species and the prevalence of methanogenic archaea that tolerate or adapt to increasing temperatures. These changes in the composition of methanogenic archaea will likely increase the methane production potential of high latitude terrestrial regions, changing the Arctic from a carbon sink to a source.
Adherent cells constantly collect information about the mechanical properties of their extracellular environment by actively pulling on it through cell-matrix contacts, which act as mechanosensors. In recent years, the sophisticated use of elastic substrates has shown that cells respond very sensitively to changes in effective stiffness in their environment, which results in a reorganization of the cytoskeleton in response to mechanical input. We develop a theoretical model to predict cellular self-organization in soft materials on a coarse grained level. Although cell organization in principle results from complex regulatory events inside the cell, the typical response to mechanical input seems to be a simple preference for large effective stiffness, possibly because force is more efficiently generated in a stiffer environment. The term effective stiffness comprises effects of both rigidity and prestrain in the environment. This observation can be turned into an optimization principle in elasticity theory. By specifying the cellular probing force pattern and by modeling the environment as a linear elastic medium, one can predict preferred cell orientation and position. Various examples for cell organization, which are of large practical interest, are considered theoretically: cells in external strain fields and cells close to boundaries or interfaces for different sample geometries and boundary conditions. For this purpose the elastic equations are solved exactly for an infinite space, an elastic half space and the elastic sphere. The predictions of the model are in excellent agreement with experiments for fibroblast cells, both on elastic substrates and in hydrogels. Mechanically active cells like fibroblasts could also interact elastically with each other. We calculate the optimal structures on elastic substrates as a function of material properties, cell density and the geometry of cell positioning, respectively, that allows each cell to maximize the effective stiffness in its environment due to the traction of all the other cells. Finally, we apply Monte Carlo simulations to study the effect of noise on cellular structure formation. The model not only contributes to a better understanding of many physiological situations. In the future it could also be used for biomedical applications to optimize protocols for artificial tissues with respect to sample geometry, boundary condition, material properties or cell density.
As of late, epidemiological studies have highlighted a strong association of dairy intake with lower disease risk, and similarly with an increased amount of odd-chain fatty acids (OCFA). While the OCFA also demonstrate inverse associations with disease incidence, the direct dietary sources and mode of action of the OCFA remain poorly understood.
The overall aim of this thesis was to determine the impact of two main fractions of dairy, milk fat and milk protein, on OCFA levels and their influence on health outcomes under high-fat (HF) diet conditions. Both fractions represent viable sources of OCFA, as milk fats contain a significant amount of OCFA and milk proteins are high in branched chain amino acids (BCAA), namely valine (Val) and isoleucine (Ile), which can produce propionyl-CoA (Pr-CoA), a precursor for endogenous OCFA synthesis, while leucine (Leu) does not. Additionally, this project sought to clarify the specific metabolic effects of the OCFA heptadecanoic acid (C17:0).
Both short-term and long-term feeding studies were performed using male C57BL/6JRj mice fed HF diets supplemented with milk fat or C17:0, as well as milk protein or individual BCAA (Val; Leu) to determine their influences on OCFA and metabolic health. Short-term feeding revealed that both milk fractions induce OCFA in vivo, and the increases elicited by milk protein could be, in part, explained by Val intake. In vitro studies using primary hepatocytes further showed an induction of OCFA after Val treatment via de novo lipogenesis and increased α-oxidation. In the long-term studies, both milk fat and milk protein increased hepatic and circulating OCFA levels; however, only milk protein elicited protective effects on adiposity and hepatic fat accumulation—likely mediated by the anti-obesogenic effects of an increased Leu intake. In contrast, Val feeding did not increase OCFA levels nor improve obesity, but rather resulted in glucotoxicity-induced insulin resistance in skeletal muscle mediated by its metabolite 3-hydroxyisobutyrate (3-HIB). Finally, while OCFA levels correlated with improved health outcomes, C17:0 produced negligible effects in preventing HF-diet induced health impairments.
The results presented herein demonstrate that the beneficial health outcomes associated with dairy intake are likely mediated through the effects of milk protein, while OCFA levels are likely a mere association and do not play a significant causal role in metabolic health under HF conditions. Furthermore, the highly divergent metabolic effects of the two BCAA, Leu and Val, unraveled herein highlight the importance of protein quality.
In this thesis, I investigated the factors influencing the growth and vertical distribution of planktonic algae in extremely acidic mining lakes (pH 2-3). In the focal study site, Lake 111 (pH 2.7; Lusatia, Germany), the chrysophyte, Ochromonas sp., dominates in the upper water strata and the chlorophyte, Chlamydomonas sp., in the deeper strata, forming a pronounced deep chlorophyll maximum (DCM). Inorganic carbon (IC) limitation influenced the phototrophic growth of Chlamydomonas sp. in the upper water strata. Conversely, in deeper strata, light limited its phototrophic growth. When compared with published data for algae from neutral lakes, Chlamydomonas sp. from Lake 111 exhibited a lower maximum growth rate, an enhanced compensation point and higher dark respiration rates, suggesting higher metabolic costs due to the extreme physico-chemical conditions. The photosynthetic performance of Chlamydomonas sp. decreased in high-light-adapted cells when IC limited. In addition, the minimal phosphorus (P) cell quota was suggestive of a higher P requirement under IC limitation. Subsequently, it was shown that Chlamydomonas sp. was a mixotroph, able to enhance its growth rate by taking up dissolved organic carbon (DOC) via osmotrophy. Therefore, it could survive in deeper water strata where DOC concentrations were higher and light limited. However, neither IC limitation, P availability nor in situ DOC concentrations (bottom-up control) could fully explain the vertical distribution of Chlamydomonas sp. in Lake 111. Conversely, when a novel approach was adopted, the grazing influence of the phagotrophic phototroph, Ochromonas sp., was found to exert top-down control on its prey (Chlamydomonas sp.) reducing prey abundance in the upper water strata. This, coupled with the fact that Chlamydomonas sp. uses DOC for growth, leads to a pronounced accumulation of Chlamydomonas sp. cells at depth; an apparent DCM. Therefore, grazing appears to be the main factor influencing the vertical distribution of algae observed in Lake 111. The knowledge gained from this thesis provides information essential for predicting the effect of strategies to neutralize the acidic mining lakes on the food-web.
Semi-empirical sea-level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers, in the following global mean temperature. This model class evolved as a supplement to process-based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea-level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea-level rise. Semi-empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea-level rise, consistently giving significantly higher projections than process-based models.
In the following different aspects of semi-empirical sea-level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level, and to infer past global temperature from sea-level data via inverse modelling. Periods studied encompass the instrumental period, covered by tide gauges (starting 1700 CE (Common Era) in Amsterdam) and satellites (first launched in 1992 CE), the era from 1000 BCE (before CE) to present, and the full length of the Holocene (using proxy data). Accordingly different data, model formulations and implementations have been used. It could be shown in Bittermann et al. (2013) that SEMs correctly predict 20th century sea-level when calibrated with data until 1900 CE. SEMs also turned out to give better predictions than the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report (AR4, IPCC (2007)) models, for the period from 1961–2003 CE.
With the first multi-proxy reconstruction of global sea-level as input, estimate of the human-induced component of modern sea-level change and projections of future sea-level rise were calculated (Kopp et al. (2016)). It turned out with 90% confidence that more than 40 % of the observed 20th century sea-level rise is indeed anthropogenic. With the new semi-empirical and IPCC (2013) 5th assessment report (AR5) projections the gap between SEM and process-based model projections closes, giving higher credibility to both. Combining all scenarios, from strong mitigation to business as usual, a global sea-level rise of 28–131 cm relative to 2000 CE, is projected with 90% confidence. The decision for a low carbon pathway could halve the expected global sea-level rise by 2100 CE.
Present day temperature and thus sea level are driven by the globally acting greenhouse-gas forcing. Unlike that, the Milankovich forcing, acting on Holocene timescales, results mainly in a northern-hemisphere temperature change. Therefore a semi-empirical model can be driven with northernhemisphere temperatures, which makes it possible to model the main subcomponent of sea-level change over this period. It showed that an additional positive constant rate of the order of the estimated Antarctic sea-level contribution is then required to explain the sea-level evolution over the Holocene. Thus the global sea level, following the climatic optimum, can be interpreted as the sum of a temperature induced sea-level drop and a positive long-term contribution, likely an ongoing response to deglaciation coming from Antarctica.
This work presents the synthesis and the self-assembly of symmetrical amphiphilic ABA and BAB triblock copolymers in dilute, semi-concentrated and highly concentrated aqueous solution. A series of new bifunctional bistrithiocarbonates as RAFT agents was used to synthesise these triblock copolymers, which are characterised by a long hydrophilic middle block and relatively small, but strongly hydrophobic end blocks. As hydrophilic A blocks, poly(N-isopropylacrylamide) (PNIPAM) and poly(methoxy diethylene glycol acrylate) (PMDEGA) were employed, while as hydrophobic B blocks, poly(4-tert-butyl styrene), polystyrene, poly(3,5-dibromo benzyl acrylate), poly(2-ethylhexyl acrylate), and poly(octadecyl acrylate) were explored as building blocks with different hydrophobicities and glass transition temperatures. The five bifunctional trithiocarbonates synthesised belong to two classes: the first are RAFT agents, which position the active group of the growing polymer chain at the outer ends of the polymer (Z-C(=S)-S-R-S-C(=S)-Z, type I). The second class places the active groups in the middle of the growing polymer chain (R-S-C(=S)-Z-C(=S)-S-R, type II). These RAFT agents enable the straightforward synthesis of amphiphilic triblock copolymers in only two steps, allowing to vary the nature of the hydrophobic blocks as well as the length of the hydrophobic and hydrophilic blocks broadly with good molar mass control and narrow polydispersities. Specific side reactions were observed among some RAFT agents including the elimination of ethylenetrithiocarbonate in the early stage of the polymerisation of styrene mediated by certain agents of the type II, while the use of the RAFT agents of type I resulted in retardation of the chain extension of PNIPAM with styrene. These results underline the need of a careful choice of RAFT agents for a given task. The various copolymers self-assemble in dilute and semi-concentrated aqueous solution into small flower-like micelles. No indication for the formation of micellar clusters was found, while only at high concentration, physical hydrogels are formed. The reversible thermoresponsive behaviour of the ABA and BAB type copolymer solutions in water with A made of PNIPAM was examined by turbidimetry and dynamic light scattering (DLS). The cloud point of the copolymers was nearly identical to the cloud point of the homopolymer and varied between 28-32 °C with concentrations from 0.01 to 50 wt%. This is attributed to the formation of micelles where the hydrophobic blocks are shielded from a direct contact with water, so that the hydrophobic interactions of the copolymers are nearly the same as for pure PNIPAM. Dynamic light scattering measurements showed the presence of small micelles at ambient temperature. The aggregate size dramatically increased above the cloud point, indicating a change of aggregate morphology into clusters due to the thermosensitivity of the PNIPAM block. The rheological behaviour of the amphiphilic BAB triblock copolymers demonstrated the formation of hydrogels at high concentrations, typically above 30-35 wt%. The minimum concentration to induce hydrogels decreased with the increasing glass transition temperatures and increasing length of the end blocks. The weak tendency to form hydrogels was attributed to a small share of bridged micelles only, due to the strong segregation regime occurring. In order to learn about the role of the nature of the thermoresponsive block for the aggregation, a new BAB triblock copolymer consisting of short polystyrene end blocks and PMDEGA as stimuli-responsive middle block was prepared and investigated. Contrary to PNIPAM, dilute aqueous solutions of PMDEGA and of its block copolymers showed reversible phase transition temperatures characterised by a strong dependence on the polymer composition. Moreover, the PMDEGA block copolymer allowed the formation of physical hydrogels at lower concentration, i.e. from 20 wt%. This result suggests that PMDEGA has a higher degree of water-swellability than PNIPAM.
‘Heterosis’ is a term used in genetics and breeding referring to hybrid vigour or the superiority of hybrids over their parents in terms of traits such as size, growth rate, biomass, fertility, yield, nutrient content, disease resistance or tolerance to abiotic and abiotic stress. Parental plants which are two different inbred (pure) lines that have desired traits are crossed to obtain hybrids. Maximum heterosis is observed in the first generation (F1) of crosses. Heterosis has been utilised in plant and animal breeding programs for at least 90 years: by the end of the 21st century, 65% of worldwide maize production was hybrid-based. Generally, it is believed that an understanding of the molecular basis of heterosis will allow the creation of new superior genotypes which could either be used directly as F1 hybrids or form the basis for the future breeding selection programmes. Two selected accessions of a research model plant Arabidopsis thaliana (thale cress) were crossed to obtain hybrids. These typically exhibited a 60-80% increase of biomass when compared to the average weight of both parents. This PhD project focused on investigating the role of selected regulatory genes given their potentially key involvement in heterosis. In the first part of the project, the most appropriate developmental stage for this heterosis study was determined by metabolite level measurements and growth observations in parents and hybrids. At the selected stage, around 60 candidate regulatory genes (i.e. differentially expressed in hybrids when compared to parents) were identified. Of these, the majority were transcription factors, genes that coordinate the expression of other genes. Subsequent expression analyses of the candidate genes in biomass-heterotic hybrids of other Arabidopsis accessions revealed a differential expression in a gene subset, highlighting their relevance for heterosis. Moreover, a fraction of the candidate regulatory genes were found within DNA regions closely linked to the genes that underlie the biomass or growth heterosis. Additional analyses to validate the role of selected candidate regulatory genes in heterosis appeared insufficient to establish their role in heterosis. This uncovered a need for using novel approaches as discussed in the thesis. Taken together, the work provided an insight into studies on the molecular mechanisms underlying heterosis. Although studies on heterosis date back to more than one hundred years, this project as many others revealed that more investigations will be needed to uncover this phenomenon.
The programmable network envisioned in the 1990s within standardization and research for the Intelligent Network is currently coming into reality using IPbased Next Generation Networks (NGN) and applying Service-Oriented Architecture (SOA) principles for service creation, execution, and hosting. SOA is the foundation for both next-generation telecommunications and middleware architectures, which are rapidly converging on top of commodity transport services. Services such as triple/quadruple play, multimedia messaging, and presence are enabled by the emerging service-oriented IPMultimedia Subsystem (IMS), and allow telecommunications service providers to maintain, if not improve, their position in the marketplace. SOA becomes the de facto standard in next-generation middleware systems as the system model of choice to interconnect service consumers and providers within and between enterprises. We leverage previous research activities in overlay networking technologies along with recent advances in network abstraction, service exposure, and service creation to develop a paradigm for a service environment providing converged Internet and Telecommunications services that we call Service Broker. Such a Service Broker provides mechanisms to combine and mediate between different service paradigms from the two domains Internet/WWW and telecommunications. Furthermore, it enables the composition of services across these domains and is capable of defining and applying temporal constraints during creation and execution time. By adding network-awareness into the service fabric, such a Service Broker may also act as a next generation network-to-service element allowing the composition of crossdomain and cross-layer network and service resources. The contribution of this research is threefold: first, we analyze and classify principles and technologies from Information Technologies (IT) and telecommunications to identify and discuss issues allowing cross-domain composition in a converging service layer. Second, we discuss service composition methods allowing the creation of converged services on an abstract level; in particular, we present a formalized method for model-checking of such compositions. Finally, we propose a Service Broker architecture converging Internet and Telecom services. This environment enables cross-domain feature interaction in services through formalized obligation policies acting as constraints during service discovery, creation, and execution time.
Streamflow dynamics in mountainous environments are controlled by runoff generation processes in the basin upstream. Runoff generation processes are thus a major control of the terrestrial part of the water cycle, influencing both, water quality and water quantity as well as their dynamics. The understanding of these processes becomes especially important for the prediction of floods, erosion, and dangerous mass movements, in particular as hydrological systems often show threshold behavior. In case of extensive environmental changes, be it in climate or in landuse, the understanding of runoff generation processes will allow us to better anticipate the consequences and can thus lead to a more responsible management of resources as well as risks. In this study the runoff generation processes in a small undisturbed catchment in the Chilean Andes were investigated. The research area is characterized by steep hillslopes, volcanic ash soils, undisturbed old growth forest and high rainfall amounts. The investigation of runoff generation processes in this data scarce area is of special interest as a) little is known on the hydrological functioning of the young volcanic ash soils, which are characterized by extremely high porosities and hydraulic conductivities, b) no process studies have been carried out in this area at either slope or catchment scale, and c) understanding the hydrological processes in undisturbed catchments will provide a basis to improve our understanding of disturbed systems, the shift in processes that followed the disturbance and maybe also future process evolution necessary for the achievement of a new steady state. The here studied catchment has thus the potential to serve as a reference catchment for future investigations. As no long term data of rainfall and runoff exists, it was necessary to replace long time series of data with a multitude of experimental methods, using the so called "multi-method approach". These methods cover as many aspects of runoff generation as possible and include not only the measurement of time series such as discharge, rainfall, soil water dynamics and groundwater dynamics, but also various short term measurements and experiments such as determination of throughfall amounts and variability, water chemistry, soil physical parameters, soil mineralogy, geo-electrical soundings and tracer techniques. Assembling the results like pieces of a puzzle produces a maybe not complete but nevertheless useful picture of the dynamic ensemble of runoff generation processes in this catchment. The employed methods were then evaluated for their usefulness vs. expenditures (labour and financial costs). Finally, the hypotheses - the perceptual model of runoff generation generated from the experimental findings - were tested with the physically based model Catflow. Additionally the process-based model Wasim-ETH was used to investigate the influence of landuse on runoff generation at the catchment scale. An initial assessment of hydrologic response of the catchment was achieved with a linear statistical model for the prediction of event runoff coefficients. The parameters identified as best predictors give a first indication of important processes. Various results acquired with the "multi-method approach" show that response to rainfall is generally fast. Preferential vertical flow is of major importance and is reinforced by hydrophobicity during the summer months. Rapid lateral water transport is necessary to produce the fast response signal, however, while lateral subsurface flow was observed at several soil moisture profiles, the location and type of structures causing fast lateral flow on the hillslope scale is still not clear and needs to be investigated in more detail. Surface runoff has not been observed and is unlikely due to the high hydraulic conductivities of the volcanic ash soils. Additionally, a large subsurface storage retains most of the incident rainfall amount during events (>90%, often even >95%) and produces streamflow even after several weeks of drought. Several findings suggest a shift in processes from summer to winter causing changes in flow patterns, changes in response of stream chemistry to rainfall events and also in groundwater-surface water interactions. The results of the modelling study confirm the importance of rapid and preferential flow processes. However, due to the limited knowledge on subsurface structures the model still does not fully capture runoff response. Investigating the importance of landuse on runoff generation showed that while peak runoff generally increased with deforested area, the location of these areas also had an effect. Overall, the "multi-method approach" of replacing long time series with a multitude of experimental methods was successful in the identification of dominant hydrological processes and thus proved its applicability for data scarce catchments under the constraint of limited resources.
The present thesis was born and evolved within the RAdial Velocity Experiment (RAVE) with the goal of measuring chemical abundances from the RAVE spectra and exploit them to investigate the chemical gradients along the plane of the Galaxy to provide constraints on possible Galactic formation scenarios. RAVE is a large spectroscopic survey which aims to observe spectroscopically ~10^6 stars by the end of 2012 and measures their radial velocities, atmospheric parameters and chemical abundances. The project makes use of the UK Schmidt telescope at Australian Astronomical Observatory (AAO) in Siding Spring, Australia, equipped with the multiobject spectrograph 6dF. To date, RAVE collected and measured more than 450,000 spectra. The precision of the chemical abundance estimations depends on the reliability of the atomic and atmosphere parameters adopted (in particular the oscillator strengths of the absorption lines and the effective temperature, gravity, and metallicity of the stars measured). Therefore we first identified 604 absorption lines in the RAVE wavelength range and refined their oscillator strengths with an inverse spectral analysis. Then, we improved the RAVE stellar parameters by modifying the RAVE pipeline and the spectral library the pipeline rely on. The modifications removed some systematic errors in stellar parameters discovered during this work. To obtain chemical abundances, we developed two different processing pipelines. Both of them perform chemical abundances measurements by assuming stellar atmospheres in Local Thermodynamic Equilibrium (LTE). The first one determines elements abundances from equivalent widths of absorption lines. Since this pipeline showed poor sensibility on abundances relative to iron, it has been superseded. The second one exploits the chi^2 minimization technique between observed and model spectra. Thanks to its precision, it has been adopted for the creation of the RAVE chemical catalogue. This pipeline provides abundances with uncertains of about ~0.2dex for spectra with signal-to-noise ratio S/N>40 and ~0.3dex for spectra with 20>S/N>40. For this work, the pipeline measured chemical abundances up to 7 elements for 217,358 RAVE stars. With these data we investigated the chemical gradients along the Galactic radius of the Milky Way. We found that stars with low vertical velocities |W| (which stay close to the Galactic plane) show an iron abundance gradient in agreement with previous works (~-0.07$ dex kpc^-1) whereas stars with larger |W| which are able to reach larger heights above the Galactic plane, show progressively flatter gradients. The gradients of the other elements follow the same trend. This suggests that an efficient radial mixing acts in the Galaxy or that the thick disk formed from homogeneous interstellar matter. In particular, we found hundreds of stars which can be kinetically classified as thick disk stars exhibiting a chemical composition typical of the thin disk. A few stars of this kind have already been detected by other authors, and their origin is still not clear. One possibility is that they are thin disk stars kinematically heated, and then underwent an efficient radial mixing process which blurred (and so flattened) the gradient. Alternatively they may be a transition population" which represents an evolutionary bridge between thin and thick disk. Our analysis shows that the two explanations are not mutually exclusive. Future follow-up high resolution spectroscopic observations will clarify their role in the Galactic disk evolution.
The problem under consideration in the thesis is a two level atom in a photonic crystal and a pumping laser. The photonic crystal provides an environment for the atom, that modifies the decay of the exited state, especially if the atom frequency is close to the band gap. The population inversion is investigated als well as the emission spectrum. The dynamics is analysed in the context of open quantum systems. Due to the multiple reflections in the photonic crystal, the system has a finite memory that inhibits the Markovian approximation. In the Heisenberg picture the equations of motion for the system variables form a infinite hierarchy of integro-differential equations. To get a closed system, approximations like a weak coupling approximation are needed. The thesis starts with a simple photonic crystal that is amenable to analytic calculations: a one-dimensional photonic crystal, that consists of alternating layers. The Bloch modes inside and the vacuum modes outside a finite crystal are linked with a transformation matrix that is interpreted as a transfer matrix. Formulas for the band structure, the reflection from a semi-infinite crystal, and the local density of states in absorbing crystals are found; defect modes and negative refraction are discussed. The quantum optics section of the work starts with the discussion of three problems, that are related to the full resonance fluorescence problem: a pure dephasing model, the driven atom and resonance fluorescence in free space. In the lowest order of the system-environment coupling, the one-time expectation values for the full problem are calculated analytically and the stationary states are discussed for certain cases. For the calculation of the two time correlation functions and spectra, the additional problem of correlations between the two times appears. In the Markovian case, the quantum regression theorem is valid. In the general case, the fluctuation dissipation theorem can be used instead. The two-time correlation functions are calculated by the two different methods. Within the chosen approximations, both methods deliver the same result. Several plots show the dependence of the spectrum on the parameters. Some examples for squeezing spectra are shown with different approximations. A projection operator method is used to establish two kinds of Markovian expansion with and without time convolution. The lowest order is identical with the lowest order of system environment coupling, but higher orders give different results.
Comparative study of gene expression during the differentiation of white and brown preadipocytes
(2002)
Introduction Mammals have two types of adipose tissue: the lipid storing white adipose tissue and the brown adipose tissue characterised by its capacity for non-shivering thermogenesis. White and brown adipocytes have the same origin in mesodermal stem cells. Yet nothing is known so far about the commitment of precursor cells to the white and brown adipose lineage. Several experimental approaches indicate that they originate from the differentiation of two distinct types of precursor cells, white and brown preadipocytes. Based on this hypothesis, the aim of this study was to analyse the gene expression of white and brown preadipocytes in a systematic approach. Experimental approach The white and brown preadipocytes to compare were obtained from primary cell cultures of preadipocytes from the Djungarian dwarf hamster. Representational difference analysis was used to isolate genes potentially differentially expressed between the two cell types. The thus obtained cDNA libraries were spotted on microarrays for a large scale gene expression analysis in cultured preadipocytes and adipocytes and in tissue samples. Results 4 genes with higher expression in white preadipocytes (3 members of the complement system and a fatty acid desaturase) and 8 with higher expression in brown preadipocytes were identified. From the latter 3 coded for structural proteins (fibronectin, metargidin and a actinin 4), 3 for proteins involved in transcriptional regulation (necdin, vigilin and the small nuclear ribonucleoprotein polypeptide A) and 2 are of unknown function. Cluster analysis was applied to the gene expression data in order to characterise them and led to the identification of four major typical expression profiles: genes up-regulated during differentiation, genes down-regulated during differentiation, genes higher expressed in white preadipocytes and genes higher expressed in brown preadipocytes. Conclusion This study shows that white and brown preadipocytes can be distinguished by different expression levels of several genes. These results draw attention to interesting candidate genes for the determination of white and brown preadipocytes (necdin, vigilin and others) and furthermore indicate that potential importance of several functional groups in the differentiation of white and brown preadipocytes, mainly the complement system and extracellular matrix.
It is a common finding that preschoolers have difficulties in identifying who is doing what to whom in non-canonical sentences, such as (object-verb-subject) OVS and passive sentences in German. This dissertation investigates how German monolingual and German-Italian simultaneous bilingual children process German OVS sentences in Study 1 and German passives in Study 2. Offline data (i.e., accuracy data) and online data (i.e., eye-gaze and pupillometry data) were analyzed to explore whether children can assign thematic roles during sentence comprehension and processing. Executive functions, language-internal and -external factors were investigated as potential predictors for children’s sentence comprehension and processing.
Throughout the literature, there are contradicting findings on the relation between language and executive functions. While some results show a bilingual cognitive advantage over monolingual speakers, others suggest there is no relationship between bilingualism and executive functions. If bilingual children possess more advanced executive function abilities than monolingual children, then this might also be reflected in a better performance on linguistic tasks. In the current studies monolingual and bilingual children were tested by means of two executive function tasks: the Flanker task and the task-switching paradigm. However, these findings showed no bilingual cognitive advantages and no better performance by bilingual children in the linguistic tasks. The performance was rather comparable between bilingual and monolingual children, or even better for the monolingual group. This may be due to cross-linguistic influences and language experience (i.e., language input and output). Italian was used because it does not syntactically overlap with the structure of German OVS sentences, and it only overlapped with one of the two types of sentence condition used for the passive study - considering the subject-(finite)verb alignment. The findings showed a better performance of bilingual children in the passive sentence structure that syntactically overlapped in the two languages, providing evidence for cross-linguistic influences.
Further factors for children’s sentence comprehension were considered. The parents’ education, the number of older siblings and language experience variables were derived from a language background questionnaire completed by parents. Scores of receptive vocabulary and grammar, visual and short-term memory and reasoning ability were measured by means of standardized tests. It was shown that higher German language experience by bilinguals correlates with better accuracy in German OVS sentences but not in passive sentences. Memory capacity had a positive effect on the comprehension of OVS and passive sentences in the bilingual group. Additionally, a role was played by executive function abilities in the comprehension of OVS sentences and not of passive sentences. It is suggested that executive function abilities might help children in the sentence comprehension task when the linguistic structures are not yet fully mastered.
Altogether, these findings show that bilinguals’ poorer performance in the comprehension and processing of German OVS is mainly due to reduced language experience in German, and that the different performance of bilingual children with the two types of passives is mainly due to cross-linguistic influences.
This publications-based thesis summarizes my contribution to the scientific field of ultrafast structural dynamics. It consists of 16 publications, about the generation, detection and coupling of coherent gigahertz longitudinal acoustic phonons, also called hypersonic waves. To generate such high frequency phonons, femtosecond near infrared laser pulses were used to heat nanostructures composed of perovskite oxides on an ultrashort timescale. As a consequence the heated regions of such a nanostructure expand and a high frequency acoustic phonon pulse is generated. To detect such coherent acoustic sound pulses I use ultrafast variants of optical Brillouin and x-ray scattering. Here an incident optical or x-ray photon is scattered by the excited sound wave in the sample. The scattered light intensity measures the occupation of the phonon modes.
The central part of this work is the investigation of coherent high amplitude phonon wave packets which can behave nonlinearly, quite similar to shallow water waves which show a steepening of wave fronts or solitons well known as tsunamis. Due to the high amplitude of the acoustic wave packets in the solid, the acoustic properties can change significantly in the vicinity of the sound pulse. This may lead to a shape change of the pulse. I have observed by time-resolved Brillouin scattering, that a single cycle hypersound pulse shows a wavefront steepening. I excited hypersound pulses with strain amplitudes until 1% which I have calibrated by ultrafast x-ray diffraction (UXRD).
On the basis of this first experiment we developed the idea of the nonlinear mixing of narrowband phonon wave packets which we call "nonlinear phononics" in analogy with the nonlinear optics, which summarizes a kaleidoscope of surprising optical phenomena showing up at very high electric fields. Such phenomena are for instance Second Harmonic Generation, four-wave-mixing or solitons. But in case of excited coherent phonons the wave packets have usually very broad spectra which make it nearly impossible to look at elementary scattering processes between phonons with certain momentum and energy.
For that purpose I tested different techniques to excite narrowband phonon wave packets which mainly consist of phonons with a certain momentum and frequency. To this end epitaxially grown metal films on a dielectric substrate were excited with a train of laser pulses. These excitation pulses drive the metal film to oscillate with the frequency given by their inverse temporal displacement and send a hypersonic wave of this frequency into the substrate. The monochromaticity of these wave packets was proven by ultrafast optical Brillouin and x-ray scattering.
Using the excitation of such narrowband phonon wave packets I was able to observe the Second Harmonic Generation (SHG) of coherent phonons as a first example of nonlinear wave mixing of nanometric phonon wave packets.
In the first section of the thesis graphitic carbon nitride was for the first time synthesised using the high-temperature condensation of dicyandiamide (DCDA) – a simple molecular precursor – in a eutectic salt melt of lithium chloride and potassium chloride. The extent of condensation, namely next to complete conversion of all reactive end groups, was verified by elemental microanalysis and vibrational spectroscopy. TEM- and SEM-measurements gave detailed insight into the well-defined morphology of these organic crystals, which are not based on 0D or 1D constituents like known molecular or short-chain polymeric crystals but on the packing motif of extended 2D frameworks. The proposed crystal structure of this g-C3N4 species was derived in analogy to graphite by means of extensive powder XRD studies, indexing and refinement. It is based on sheets of hexagonally arranged s-heptazine (C6N7) units that are held together by covalent bonds between C and N atoms. These sheets stack in a graphitic, staggered fashion adopting an AB-motif, as corroborated by powder X-ray diffractometry and high-resolution transmission electron microscopy. This study was contrasted with one of many popular – yet unsuccessful – approaches in the last 30 years of scientific literature to perform the condensation of an extended carbon nitride species through synthesis in the bulk. The second section expands the repertoire of available salt melts introducing the lithium bromide and potassium bromide eutectic as an excellent medium to obtain a new phase of graphitic carbon nitride. The combination of SEM, TEM, PXRD and electron diffraction reveals that the new graphitic carbon nitride phase stacks in an ABA’ motif forming unprecedentedly large crystals. This section seizes the notion of the preceding chapter, that condensation in a eutectic salt melt is the key to obtain a high degree of conversion mainly through a solvatory effect. At the close of this chapter ionothermal synthesis is seen established as a powerful tool to overcome the inherent kinetic problems of solid state reactions such as incomplete polymerisation and condensation in the bulk especially when the temperature requirement of the reaction in question falls into the proverbial “no man’s land” of classical solvents, i.e. above 250 to 300 °C. The following section puts the claim to the test, that the crystalline carbon nitrides obtained from a salt melt are indeed graphitic. A typical property of graphite – namely the accessibility of its interplanar space for guest molecules – is transferred to the graphitic carbon nitride system. Metallic potassium and graphitic carbon nitride are converted to give the potassium intercalation compound, K(C6N8)3 designated according to its stoichiometry and proposed crystal structure. Reaction of the intercalate with aqueous solvents triggers the exfoliation of the graphitic carbon nitride material and – for the first time – enables the access of singular (or multiple) carbon nitride sheets analogous to graphene as seen in the formation of sheets, bundles and scrolls of carbon nitride in TEM imaging. The thus exfoliated sheets form a stable, strongly fluorescent solution in aqueous media, which shows no sign in UV/Vis spectroscopy that the aromaticity of individual sheets was subject to degradation. The final section expands on the mechanism underlying the formation of graphitic carbon nitride by literally expanding the distance between the covalently linked heptazine units which constitute these materials. A close examination of all proposed reaction mechanisms to-date in the light of exhaustive DSC/MS experiments highlights the possibility that the heptazine unit can be formed from smaller molecules, even if some of the designated leaving groups (such as ammonia) are substituted by an element, R, which later on remains linked to the nascent heptazine. Furthermore, it is suggested that the key functional groups in the process are the triazine- (Tz) and the carbonitrile- (CN) group. On the basis of these assumptions, molecular precursors are tailored which encompass all necessary functional groups to form a central heptazine unit of threefold, planar symmetry and then still retain outward functionalities for self-propagated condensation in all three directions. Two model systems based on a para-aryl (ArCNTz) and para-biphenyl (BiPhCNTz) precursors are devised via a facile synthetic procedure and then condensed in an ionothermal process to yield the heptazine based frameworks, HBF-1 and HBF-2. Due to the structural motifs of their molecular precursors, individual sheets of HBF-1 and HBF-2 span cavities of 14.2 Å and 23.0 Å respectively which makes both materials attractive as potential organic zeolites. Crystallographic analysis confirms the formation of ABA’ layered, graphitic systems, and the extent of condensation is confirmed as next-to-perfect by elemental analysis and vibrational spectroscopy.
Organizations incorporate the institutional demands from their environment in order to be deemed legitimate and survive. Yet, complexifying societies promulgate multiple and sometimes inconsistent institutional prescriptions. When these prescriptions collide, organizations are said to face “institutional complexity”. How does an organization then incorporate incompatible demands? What are the consequences of institutional complexity for an organization? The literature provides contradictory conceptual and empirical insights on the matter. A central assumption, however, remains that internal incompatibilities generate tensions that, under certain conditions, can escalate into intractable conflicts, resulting in dysfunctionality and loss of legitimacy. The present research is an inquiry into what happens inside an organization when it incorporates complex institutional demands.
To answer this question, I focus on how individuals inside an organization interpret a complex institutional prescription. I examine how members of the French Development Agency interpret ‘results-based management’, a central but complex concept of organizing in the field of development aid. I use an inductive mixed methods design to systematically explore how different interpretations of results-based management relate to one another and to the organizational context in which they are embedded.
The results reveal that results-based management is a contested concept in the French Development Agency. I find multiple interpretations of the concept, which are attached to partly incompatible rationales about “who we are” and “what we do as an organization”. These rationales nevertheless coexist as balanced forces, without escalating into open conflict. The analysis points to four reasons for this peaceful coexistence of diverging rationales inside one and the same organization: 1) individuals’ capacity to manipulate different interpretations of a complex institutional demand, 2) the nature of interpretations, which makes them more or less prone to conflict, 3) the balanced distribution of rationales across the organizational sub-contexts and 4) the shared rules of interpretation provided by the larger socio-cultural context.
This research shows that an organization that incorporates institutional complexity comes to represent different, partly incompatible things to its members without being at war with itself. In doing so, it contributes to our knowledge of institutional complexity and organizational hybridity. It also advances our understanding of internal organizational legitimacy and of the translation of managerial concepts in organizations.
The India-Eurasia continental collision zone provides a spectacular example of active mountain building and climatic forcing. In order to quantify the critically important process of mass removal, I analyzed spatial and temporal precipitation patterns of the oscillating monsoon system and their geomorphic imprints. I processed passive microwave satellite data to derive high-resolution rainfall estimates for the last decade and identified an abnormal monsoon year in 2002. During this year, precipitation migrated far into the Sutlej Valley in the northwestern part of the Himalaya and reached regions behind orographic barriers that are normally arid. There, sediment flux, mean basin denudation rates, and channel-forming processes such as erosion by debris-flows increased significantly. Similarly, during the late Pleistocene and early Holocene, solar forcing increased the strength of the Indian summer monsoon for several millennia and presumably lead to analogous precipitation distribution as were observed during 2002. However, the persistent humid conditions in the steep, high-elevation parts of the Sutlej River resulted in deep-seated landsliding. Landslides were exceptionally large, mainly due to two processes that I infer for this time: At the onset of the intensified monsoon at 9.7 ka BP heavy rainfall and high river discharge removed material stored along the river, and lowered the baselevel. Second, enhanced discharge, sediment flux, and increased pore-water pressures along the hillslopes eventually lead to exceptionally large landslides that have not been observed in other periods. The excess sediments that were removed from the upstream parts of the Sutlej Valley were rapidly deposited in the low-gradient sectors of the lower Sutlej River. Timing of downcutting correlates with centennial-long weaker monsoon periods that were characterized by lower rainfall. I explain this relationship by taking sediment flux and rainfall dynamics into account: High sediment flux derived from the upstream parts of the Sutlej River during strong monsoon phases prevents fluvial incision due to oversaturation the fluvial sediment-transport capacity. In contrast, weaker monsoons result in a lower sediment flux that allows incision in the low-elevation parts of the Sutlej River.
Adjustment of empirically derived ground motion prediction equations (GMPEs), from a data- rich region/site where they have been derived to a data-poor region/site, is one of the major challenges associated with the current practice of seismic hazard analysis. Due to the fre- quent use in engineering design practices the GMPEs are often derived for response spectral ordinates (e.g., spectral acceleration) of a single degree of freedom (SDOF) oscillator. The functional forms of such GMPEs are based upon the concepts borrowed from the Fourier spectral representation of ground motion. This assumption regarding the validity of Fourier spectral concepts in the response spectral domain can lead to consequences which cannot be explained physically.
In this thesis, firstly results from an investigation that explores the relationship between Fourier and response spectra, and implications of this relationship on the adjustment issues of GMPEs, are presented. The relationship between the Fourier and response spectra is explored by using random vibration theory (RVT), a framework that has been extensively used in earthquake engineering, for instance within the stochastic simulation framework and in the site response analysis. For a 5% damped SDOF oscillator the RVT perspective of response spectra reveals that no one-to-one correspondence exists between Fourier and response spectral ordinates except in a limited range (i.e., below the peak of the response spectra) of oscillator frequencies. The high oscillator frequency response spectral ordinates are dominated by the contributions from the Fourier spectral ordinates that correspond to the frequencies well below a selected oscillator frequency. The peak ground acceleration (PGA) is found to be related with the integral over the entire Fourier spectrum of ground motion which is in contrast to the popularly held perception that PGA is a high-frequency phenomenon of ground motion.
This thesis presents a new perspective for developing a response spectral GMPE that takes the relationship between Fourier and response spectra into account. Essentially, this frame- work involves a two-step method for deriving a response spectral GMPE: in the first step two empirical models for the FAS and for a predetermined estimate of duration of ground motion are derived, in the next step, predictions from the two models are combined within the same RVT framework to obtain the response spectral ordinates. In addition to that, a stochastic model based scheme for extrapolating the individual acceleration spectra beyond the useable frequency limits is also presented. To that end, recorded acceleration traces were inverted to obtain the stochastic model parameters that allow making consistent extrapola- tion in individual (acceleration) Fourier spectra. Moreover an empirical model, for a dura- tion measure that is consistent within the RVT framework, is derived. As a next step, an oscillator-frequency-dependent empirical duration model is derived that allows obtaining the most reliable estimates of response spectral ordinates. The framework of deriving the response spectral GMPE presented herein becomes a self-adjusting model with the inclusion of stress parameter (∆σ) and kappa (κ0) as the predictor variables in the two empirical models. The entire analysis of developing the response spectral GMPE is performed on recently compiled RESORCE-2012 database that contains recordings made from Europe, the Mediterranean and the Middle East. The presented GMPE for response spectral ordinates should be considered valid in the magnitude range of 4 ≤ MW ≤ 7.6 at distances ≤ 200 km.
The Antarctic plays an important role in the global climate system. On the one hand, the Antarctic Ice Sheet is the largest freshwater reservoir on Earth. On the other hand, a major proportion of the global bottom-water formation takes place in Antarctic shelf regions, forcing the global thermohaline circulation. The main goal of this dissertation is to provide new insights into the dynamics and stability of the EAIS during the Quaternary. Additionally, variations in the activity of bottom-water formation and their causes are investigated. The dissertation is a German contribution to the International Polar Year 2007/ 2008 and was funded by the ‘Deutsche Forschungsgesellschaft’ (DFG) within the scope of priority program 1158 ‘Antarctic research with comparative studies in Arctic ice regions’. During RV Polarstern expedition ANT-XXIII/9, glaciomarine sediments were recovered from the Prydz Bay-Kerguelen region. Prydz Bay is a key region for the study of East EAIS dynamics, as 16% of the EAIS are drained through the Lambert Glacier into the bay. Thereby, the glacier transports sediment into Prydz Bay which is then further distributed by calving icebergs or by current transport. The scientific approach of this dissertation is the reconstruction of past glaciomarine environments to infer on the response of the Lambert Glacier-Amery Ice Shelf system to climate shifts during the Quaternary. To characterize the depositional setting, sedimentological methods are used and statistical analyses are applied. Mineralogical and (bio)geochemical methods provide a means to reconstruct sediment provenances and to provide evidence on changes in the primary production in the surface water column. Age-depth models were constructed based on palaeomagnetic and palaeointensity measurements, diatom stratigraphy and radiocarbon dating. Sea-bed surface sediments in the investigation area show distinct variations in terms of their clay minerals and heavy-mineral assemblages. Considerable differences in the mineralogical composition of surface sediments are determined on the continental shelf. Clay minerals as well as heavy minerals provide useful parameters to differentiate between sediments which originated from erosion of crystalline rocks and sediments originating from Permo-Triassic deposits. Consequently, mineralogical parameters can be used to reconstruct the provenance of current-transported and ice-rafted material. The investigated sediment cores cover the time intervals of the last 1.4 Ma (continental slope) and the last 12.8 cal. ka BP (MacRobertson shelf). The sediment deposits were mainly influenced by glacial and oceanographic processes and further by biological activity (continental shelf), meltwater input and possibly gravitational transport. Sediments from the continental slope document two major deglacial events: the first deglaciation is associated with the mid-Pleistocene warming recognized around the Antarctic. In Prydz Bay, the Lambert Glacier-Amery Ice Shelf retreated far to the south and high biogenic productivity commenced or biogenic remains were better preserved due to increased sedimentation rates. Thereafter, stable glacial conditions continued until 400 - 500 ka BP. Calving of icebergs was restricted to the western part of the Lambert Glacier. The deeper bathymetry in this area allows for floating ice shelf even during times of decreased sea-level. Between 400 - 500 ka BP and the last interglacial (marine isotope stage 5) the glacier was more dynamic. During or shortly after the last interglacial the LAIS retreated again due to sea-level rise of 6 - 9 m. Both deglacial events correlate with a reduction in the thickness of ice masses in the Prince Charles Mountains. It indicates that a disintegration of the Amery Ice Shelf possibly led to increased drainage of ice masses from the Prydz Bay hinterland. A new end-member modelling algorithm was successfully applied on sediments from the MacRobertson shelf used to unmix the sand grain size fractions sorted by current activity and ice transport, respectively. Ice retreat on MacRobertson Shelf commenced 12.8 cal. ka BP and ended around 5.5 cal. ka BP. During the Holocene, strong fluctuations of the bottomwater activity were observed, probably related to variations of sea-ice formation in the Cape Darnley polynya. Increased activity of bottom-water flow was reconstructed at transitions from warm to cool conditions, whereas bottom-water activity receded during the mid- Holocene climate optimum. It can be concluded that the Lambert Glacier-Amery Ice Shelf system was relatively stable in terms of climate variations during the Quaternary. In contrast, bottom-water formation due to polynya activity was very sensitive to changes in atmospheric forcing and should gain more attention in future research.
The origin and evolution of granites has been widely studied because granitoid rocks constitute a major portion of the Earth ́s crust. The formation of granitic magma is, besides temperature mainly triggered by the water content of these rocks. The presence of water in magmas plays an important role due to the ability of aqueous fluids to change the chemical composition of the magma. The exsolution of aqueous fluids from melts is closely linked to a fractionation of elements between the two phases. Then, aqueous fluids migrate to shallower parts of the Earth ́s crust because of it ́s lower density compared to that of melts and adjacent rocks. This process separates fluids and melts, and furthermore, during the ascent, aqueous fluids can react with the adjacent rocks and alter their chemical signature. This is particularly impor- tant during the formation of magmatic-hydrothermal ore deposits or in the late stages of the evolution of magmatic complexes. For a deeper insight to these processes, it is essential to improve our knowledge on element behavior in such systems. In particular, trace elements are used for these studies and petrogenetic interpretations because, unlike major elements, they are not essential for the stability of the phases involved and often reflect magmatic processes with less ambiguity. However, for the majority of important trace elements, the dependence of the geochemical behavior on temperature, pressure, and in particular on the composition of the system are only incompletely or not at all experimentally studied. Former studies often fo- cus on the determination of fluid−melt partition coefficients (Df/m=cfluid/cmelt) of economically interesting elements, e.g., Mo, Sn, Cu, and there are some partitioning data available for ele- ments that are also commonly used for petrological interpretations. At present, no systematic experimental data on trace element behavior in fluid−melt systems as function of pressure, temperature, and chemical composition are available. Additionally, almost all existing data are based on the analysis of quenched phases. This results in substantial uncertainties, particularly for the quenched aqueous fluid because trace element concentrations may change upon cooling. The objective of this PhD thesis consisted in the study of fluid−melt partition coefficients between aqueous solutions and granitic melts for different trace elements (Rb, Sr, Ba, La, Y, and Yb) as a function of temperature, pressure, salinity of the fluid, composition of the melt, and experimental and analytical approach. The latter included the refinement of an existing method to measure trace element concentrations in fluids equilibrated with silicate melts di- rectly at elevated pressures and temperatures using a hydrothermal diamond-anvil cell and synchrotron radiation X-ray fluorescence microanalysis. The application of this in-situ method enables to avoid the main source of error in data from quench experiments, i.e., trace element concentration in the fluid. A comparison of the in-situ results to data of conventional quench experiments allows a critical evaluation of quench data from this study and literature data. In detail, starting materials consisted of a suite of trace element doped haplogranitic glasses with ASI varying between 0.8 and 1.4 and H2O or a chloridic solution with m NaCl/KCl=1 and different salinities (1.16 to 3.56 m (NaCl+KCl)). Experiments were performed at 750 to 950◦C and 0.2 or 0.5 GPa using conventional quench devices (externally and internally heated pressure vessels) with different quench rates, and at 750◦C and 0.2 to 1.4 GPa with in-situ analysis of the trace element concentration in the fluids. The fluid−melt partitioning data of all studied trace elements show 1. a preference for the melt (Df/m < 1) at all studied conditions, 2. one to two orders of magnitude higher Df/m using chloridic solutions compared to experiments with H2O, 3. a clear dependence on the melt composition for fluid−melt partitioning of Sr, Ba, La, Y, and Yb in experiments using chloridic solutions, 4. quench rate−related differences of fluid−melt partition coefficients of Rb and Sr, and 5. distinctly higher fluid−melt partitioning data obtained from in-situ experiments than from comparable quench runs, particularly in the case of H2O as starting solution. The data point to a preference of all studied trace elements for the melt even at fairly high salinities, which contrasts with other experimental studies, but is supported by data from studies of natural co-genetically trapped fluid and melt inclusions. The in-situ measurements of trace element concentrations in the fluid verify that aqueous fluids will change their composition upon cooling, which is in particular important for Cl free systems. The distinct differences of the in-situ results to quench data of this study as well as to data from the literature signify the im- portance of a careful fluid sampling and analysis. Therefore, the direct measurement of trace element contents in fluids equilibrated with silicate melts at elevated PT conditions represents an important development to obtain more reliable fluid−melt partition coefficients. For further improvement, both the aqueous fluid and the silicate melt need to be analyzed in-situ because partitioning data that are based on the direct measurement of the trace element content in the fluid and analysis of a quenched melt are still not completely free of quench effects. At present, all available data on element complexation in aqueous fluids in equilibrium with silicate melts at high PT are indirectly derived from partitioning data, which involves in these experiments assumptions on the species present in the fluid. However, the activities of chemical components in these partitioning experiments are not well constrained, which is required for the definition of exchange equilibria between melt and fluid species. For example, the melt-dependent variation of partition coefficient observed for Sr imply that this element can not only be complexed by Cl− as suggested previously. The data indicate a more complicated complexation of Sr in the aqueous fluid. To verify this hypothesis, the in-situ setup was also used to determine strontium complexation in fluids equilibrated with silicate melts at desired PT conditions by the application of X-ray absorption near edge structure (XANES) spectroscopy. First results show a strong effect of both fluid and melt composition on the resulting XANES spectra, which indicates different complexation environments for Sr.
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.
Orogenic peridotites represent portions of upper subcontinental mantle now incorporated in mountain belts. They often contain layers, lenses and irregular bodies of pyroxenite and eclogite. The origin of this heterogeneity and the nature of these layers is still debated but it is likely to involve processes such as transient melts coming from the crust or the mantle and segregating in magma conduits, crust-mantle interaction, upwelling of the asthenosphere and metasomatism. All these processes occur in the lithospheric mantle and are often related with the subduction of crustal rocks to mantle depths. In fact, during subduction, fluids and melts are released from the slab and can interact with the overlying mantle, making the study of deep melts in this environment crucial to understand mantle heterogeneity and crust-mantle interaction. The aim of this thesis is precisely to better constrain how such processes take place studying directly the melt trapped as primary inclusions in pyroxenites and eclogites. The Bohemian Massif, crystalline core of the Variscan belt, is targeted for these purposes because it contains orogenic peridotites with layers of pyroxenite and eclogite and other mafic rocks enclosed in felsic high pressure and ultra-high pressure crustal rocks. Within this Massif mafic rocks from two areas have been selected: the garnet clinopyroxenite in orogenic peridotite of the Granulitgebirge and the ultra-high pressure eclogite in the diamond-bearing gneisses of the Erzgebirge. In both areas primary melt inclusions were recognized in the garnet, ranging in size between 2-25 µm and with different degrees of crystallization, from glassy to polycrystalline. They have been investigated with Micro Raman spectroscopy and EDS mapping and the mineral assemblage is kumdykolite, phlogopite, quartz, kokchetavite, phase with a main Raman peak at 430 cm-1, phase with a main Raman peak at 412 cm-1, white mica and calcite with some variability in relative abundance depending on the case study. In the Granulitgebirge osumilite and pyroxene are also present, whereas calcite is one of the main phases in the Erzgebirge. The presence of glass and the mineral assemblage in the nanogranitoids suggest that they were former droplets of melt trapped in the garnet while it was growing. Glassy inclusions and re-homogenized nanogranitoids show a silicate melt that is granitic, hydrous, high in alkalis and weakly peraluminous. The melt is also enriched in both case studies in Cs, Pb, Rb, U, Th, Li and B suggesting the involvement of crustal component, i.e. white mica (main carrier of Cs, Pb, Rb, Li and B), and a fluid (Cs, Th and U) in the melt producing reaction. The whole rock in both cases mainly consists of garnet and clinopyroxene with, in Erzgebirge samples, the additional presence of quartz both in the matrix and as a polycrystalline inclusion in the garnet. The latter is interpreted as a quartz pseudomorph after coesite and occurs in the same microstructural position as the melt inclusions. Both rock types show a crustal and subduction zone signature with garnet and clinopyroxene in equilibrium. Melt was likely present during the metamorphic peak of the rock, as it occurs in garnet.
Our data suggest that the processes most likely responsible for the formation of the investigated rocks in both areas is a metasomatic reaction between a melt produced in the crust and mafic layers formerly located in the mantle wedge for the Granulitgebirge and in the subducted continental crust itself in the Erzgebirge. Thus metasomatism in the first case took place in the mantle overlying the slab, whereas in the second case metasomatism took place in the continental crust that already contained, before subduction, mafic layers. Moreover, the presence of former coesite in the same microstructural position of the melt inclusions in the Erzgebirge garnets suggest that metasomatism took place at ultra-high pressure conditions.
Summarizing, in this thesis we provide new insights into the geodynamic evolution of the Bohemian Massif based on the study of melt inclusions in garnet in two different mafic rock types, combining the direct microstructural and geochemical investigation of the inclusions with the whole-rock and mineral geochemistry. We report for the first time data, directly extracted from natural rocks, on the metasomatic melt responsible for the metasomatism of several areas of the Bohemian Massif. Besides the two locations here investigated, belonging to the Saxothuringian Zone, a signature similar to the investigated melt is clearly visible in pyroxenite and peridotite of the T-7 borehole (again Saxothuringian Zone) and the durbachite suite located in the Moldanubian Zone.
Metals are often used in environments that are conducive to corrosion, which leads to a reduction in their mechanical properties and durability. Coatings are applied to corrosion-prone metals such as aluminum alloys to inhibit the destructive surface process of corrosion in a passive or active way. Standard anticorrosive coatings function as a physical barrier between the material and the corrosive environment and provide passive protection only when intact. In contrast, active protection prevents or slows down corrosion even when the main barrier is damaged. The most effective industrially used active corrosion inhibition for aluminum alloys is provided by chromate conversion coatings. However, their toxicity and worldwide restriction provoke an urgent need for finding environmentally friendly corrosion preventing systems. A promising approach to replace the toxic chromate coatings is to embed particles containing nontoxic inhibitor in a passive coating matrix. This work presents the development and optimization of effective anticorrosive coatings for the industrially important aluminum alloy, AA2024-T3 using this approach. The protective coatings were prepared by dispersing mesoporous silica containers, loaded with the nontoxic corrosion inhibitor 2-mercaptobenzothiazole, in a passive sol-gel (SiOx/ZrOx) or organic water-based layer. Two types of porous silica containers with different sizes (d ≈ 80 and 700 nm, respectively) were investigated. The studied robust containers exhibit high surface area (≈ 1000 m² g-1), narrow pore size distribution (dpore ≈ 3 nm) and large pore volume (≈ 1 mL g-1) as determined by N2 sorption measurements. These properties favored the subsequent adsorption and storage of a relatively large amount of inhibitor as well as its release in response to pH changes induced by the corrosion process. The concentration, position and size of the embedded containers were varied to ascertain the optimum conditions for overall anticorrosion performance. Attaining high anticorrosion efficiency was found to require a compromise between delivering an optimal amount of corrosion inhibitor and preserving the coating barrier properties. This study broadens the knowledge about the main factors influencing the coating anticorrosion efficiency and assists the development of optimum active anticorrosive coatings doped with inhibitor loaded containers.
This work explores the equilibrium structure and thermodynamic phase behavior of complexes formed by charged polymer chains (polyelectrolytes) and oppositely charged spheres (macroions). Polyelectrolyte-macroion complexes form a common pattern in soft-matter physics, chemistry and biology, and enter in numerous technological applications as well. From a fundamental point of view, such complexes are interesting in that they combine the subtle interplay between electrostatic interactions and elastic as well as entropic effects due to conformational changes of the polymer chain, giving rise to a wide range of structural properties. This forms the central theme of theoretical studies presented in this thesis, which concentrate on a number of different problems involving strongly coupled complexes, i.e. complexes that are characterized by a large adsorption energy and small chain fluctuations. In the first part, a global analysis of the structural phase behavior of a single polyelectrolyte-macroion complex is presented based on a dimensionless representation, yielding results that cover a wide range of realistic system parameters. Emphasize is made on the interplay between the effects due to the polyelectrolytes chain length, salt concentration and the macroion charge as well as the mechanical chain persistence length. The results are summarized into generic phase diagrams characterizing the wrapping-dewrapping behavior of a polyelectrolyte chain on a macroion. A fully wrapped chain state is typically obtained at intermediate salt concentrations and chain lengths, where the amount of polyelectrolyte charge adsorbed on the macroion typically exceeds the bare macroion charge leading thus to a highly overcharged complex. Perhaps the most striking features occur when a single long polyelectrolyte chain is complexed with many oppositely charged spheres. In biology, such complexes form between DNA (which carries the cell's genetic information) and small oppositely charged histone proteins serving as an efficient mechanism for packing a huge amount of DNA into the micron-size cell nucleus in eucaryotic cells. The resultant complex fiber, known as the chromatin fiber, appears with a diameter of 30~nm under physiological conditions. Recent experiments indicate a zig-zag spatial arrangement for individual DNA-histone complexes (nucleosome core particles) along the chromatin fiber. A numerical method is introduced in this thesis based on a simple generic chain-sphere cell model that enables one to investigate the mechanism of fiber formation on a systematic level by incorporating electrostatic and elastic contributions. As will be shown, stable complex fibers exhibit an impressive variety of structures including zig-zag, solenoidal and beads-on-a-string patterns, depending on system parameters such as salt concentration, sphere charge as well as the chain contour length (per sphere). The present results predict fibers of compact zig-zag structure within the physiologically relevant regime with a diameter of about 30~nm, when DNA-histone parameters are adopted. In the next part, a numerical method is developed in order to investigate the role of thermal fluctuations on the structure and thermodynamic phase behavior of polyelectrolyte-macroion complexes. This is based on a saddle-point approximation, which allows to describe the experimentally observed reaction (or complexation) equilibrium in a dilute solution of polyelectrolytes and macroions on a systematic level. This equilibrium is determined by the entropy loss a single polyelectrolyte chain suffers as it binds to an oppositely charged macroion. This latter quantity can be calculated from the spectrum of polyelectrolyte fluctuations around a macroion, which is determined by means of a normal-mode analysis. Thereby, a stability phase diagram is obtained, which exhibits qualitative agreement with experimental findings. At elevated complex concentrations, one needs to account for the inter-complex interactions as well. It will be shown that at small separations, complexes undergo structural changes in such a way that positive patches from one complex match up with negative patches on the other. Furthermore, one of the polyelectrolyte chains may bridge between the two complexes. These mechanisms lead to a strong inter-complex attraction. As a result, the second virial coefficient associated with the inter-complex interaction becomes negative at intermediate salt concentrations in qualitative agreement with recent experiments on solutions of nucleosome core particles.
For the first time the transcriptional reprogramming of distinct root cortex cells during the arbuscular mycorrhizal (AM) symbiosis was investigated by combining Laser Capture Mirodissection and Affymetrix GeneChip® Medicago genome array hybridization. The establishment of cryosections facilitated the isolation of high quality RNA in sufficient amounts from three different cortical cell types. The transcript profiles of arbuscule-containing cells (arb cells), non-arbuscule-containing cells (nac cells) of Rhizophagus irregularis inoculated Medicago truncatula roots and cortex cells of non-inoculated roots (cor) were successfully explored. The data gave new insights in the symbiosis-related cellular reorganization processes and indicated that already nac cells seem to be prepared for the upcoming fungal colonization. The mycorrhizal- and phosphate-dependent transcription of a GRAS TF family member (MtGras8) was detected in arb cells and mycorrhizal roots. MtGRAS shares a high sequence similarity to a GRAS TF suggested to be involved in the fungal colonization processes (MtRAM1). The function of MtGras8 was unraveled upon RNA interference- (RNAi-) mediated gene silencing. An AM symbiosis-dependent expression of a RNAi construct (MtPt4pro::gras8-RNAi) revealed a successful gene silencing of MtGras8 leading to a reduced arbuscule abundance and a higher proportion of deformed arbuscules in root with reduced transcript levels. Accordingly, MtGras8 might control the arbuscule development and life-time. The targeting of MtGras8 by the phosphate-dependent regulated miRNA5204* was discovered previously (Devers et al., 2011). Since miRNA5204* is known to be affected by phosphate, the posttranscriptional regulation might represent a link between phosphate signaling and arbuscule development. In this work, the posttranscriptional regulation was confirmed by mis-expression of miRNA5204* in M. truncatula roots. The miRNA-mediated gene silencing affects the MtGras8 transcript abundance only in the first two weeks of the AM symbiosis and the mis-expression lines seem to mimic the phenotype of MtGras8-RNAi lines. Additionally, MtGRAS8 seems to form heterodimers with NSP2 and RAM1, which are known to be key regulators of the fungal colonization process (Hirsch et al., 2009; Gobbato et al., 2012). These data indicate that MtGras8 and miRNA5204* are linked to the sym pathway and regulate the arbuscule development in phosphate-dependent manner.
This thesis deals with the encoding and transmission of information through a quantum channel. A quantum channel is a quantum mechanical system whose state is manipulated by a sender and read out by a receiver. The individual state of the channel represents the message. The two topics of the thesis comprise 1) the possibility of compressing a message stored in a quantum channel without loss of information and 2) the possibility to communicate a message directly from one party to another in a secure manner, that is, a third party is not able to eavesdrop the message without being detected. The main results of the thesis are the following. A general framework for variable-length quantum codes is worked out. These codes are necessary to make lossless compression possible. Due to the quantum nature of the channel, the encoded messages are in general in a superposition of different lengths. It is found to be impossible to compress a quantum message without loss of information if the message is not apriori known to the sender. In the other case it is shown that lossless quantum data compression is possible and a lower bound on the compression rate is derived. Furthermore, an explicit compression scheme is constructed that works for arbitrarily given source message ensembles. A quantum cryptographic protocol - the “ping-pong protocol” - is presented that realizes the secure direct communication of classical messages through a quantum channel. The security of the protocol against arbitrary eavesdropping attacks is proven for the case of an ideal quantum channel. In contrast to other quantum cryptographic protocols, the ping-pong protocol is deterministic and can thus be used to transmit a random key as well as a composed message. The protocol is perfectly secure for the transmission of a key, and it is quasi-secure for the direct transmission of a message. The latter means that the probability of successful eavesdropping exponentially decreases with the length of the message.
The majority of baryons in the Universe is believed to reside in the intergalactic medium (IGM). This makes the IGM an important component in understanding cosmological structure formation. It is expected to trace the same dark matter distribution as galaxies, forming structures like filaments and clusters. However, whereas galaxies can be observed to be arranged along these large-scale structures, the spatial distribution of the diffuse IGM is not as easily unveiled. Absorption line studies of quasar (QSO) spectra can help with mapping the IGM, as well as the boundary layer between IGM and galaxies: the circumgalactic medium (CGM). By studying gas in the Local Group, as well as in the IGM, this study aims to get a better understanding of how the gas is linked to the large-scale structure of the local Universe and the galaxies residing in that structure.
Chapter 1 gives an introduction to the CGM and IGM, while the methods used in this study are explained in Chapter 2. Chapter 3 starts on a relatively small cosmological scale, namely that of our Local Group, which includes i.a. the Milky Way (MW) and the M31. Within the CGM of the MW, there exist denser clouds, some of which are infalling while others are moving away from the Galactic disc. To study these clouds, 29 QSO spectra obtained with the Cosmic Origins Spectrograph (COS) aboard the Hubble Space Telescope (HST) were analysed. Abundances of Si II, Si III, Si IV, C II, and C IV were measured for 69 HVCs belonging to two samples: one in the direction of the LG’s barycentre and the other in the anti-barycentre direction. Their velocities range from -100 ≥ vLSR ≥ -400 km/s for the barycentre sample and between +100 ≤ vLSR ≤ +300 km/s for the anti-barycentre sample. By using Cloudy models, these data could then be used to derive gas volume densities for the HVCs. Because of the relationship between density and pressure of the ambient medium, which is in turn determined by the Galactic radiation field, the distances of the HVCs could be estimated. From this, a subsample of absorbers located in the direction of M31 was found to exist outside of the MW’s virial radius, their low densities (log nH ≤ -3.54) making it likely for them to be part of the gas in between the MW and M31. No such low-density absorbers were found in the anti-barycentre sample. Our results thus hint at gas following the dark matter potential, which would be deeper between the MW and M31 as they are by far the most massive members of the LG.
From this bridge of gas in the LG, this study zooms out to the large-scale structure of the local Universe (z ~ 0) in Chapter 4. Galaxy data from the V8k catalogue and QSO spectra from COS were used to study the relation between the galaxies tracing large-scale filaments and the gas existing outside of those galaxies. This study used the filaments defined in Courtois et al. (2013). A total of 587 Lyman α (Lyα) absorbers were found in the 302 QSO spectra in the velocity range 1070 - 6700 km/s. After selecting sightlines passing through or close to these filaments, model spectra were made for 91 sightlines and 215 (227) Lyα absorbers (components) were measured in this sample. The velocity gradient along each filament was calculated and 74 absorbers were found within 1000 km/s of the nearest filament segment.
In order to find whether the absorbers are more tied to galaxies or to the large-scale structure, equivalent widths of the Lyα absorbers were plotted against both galaxy and filament impact parameters. While stronger absorbers do tend to be closer to either galaxies or filaments, there is a large scatter in this relation. Despite this large scatter, this study found that the absorbers do not follow a random distribution either. They cluster less strongly around filaments than galaxies, but stronger than random distributions, as confirmed by a Kolmogorov-Smirnov test.
Furthermore, the column density distribution function found in this study has a slope of -β = 1.63±0.12 for the total sample and -β =1.47±0.24 for the absorbers within 1000 km/s of a filament. The shallower slope for the latter subsample could indicate an excess of denser absorbers within the filament, but they are consistent within errors. These values are in agreement with values found in e.g. Lehner et al. (2007); Danforth et al. (2016).
The picture that emerges from this study regarding the relation between the IGM and the large-scale structure in the local Universe fits with what is found in other studies: while at least part of the gas traces the same filamentary structure as galaxies, the relation is complex. This study has shown that by taking a large sample of sightlines and comparing the data gathered from those with galaxy data, it is possible to study the gaseous large-scale structure. This approach can be used in the future together with simulations to get a better understanding of structure formation and evolution in the Universe.
While the last few decades have seen impressive improvements in several areas in Natural Language Processing, asking a computer to make sense of the discourse of utterances in a text remains challenging. There are several different theories that aim to describe and analyse the coherent structure that a well-written text inhibits. These theories have varying degrees of applicability and feasibility for practical use. Presumably the most data-driven of these theories is the paradigm that comes with the Penn Discourse TreeBank, a corpus annotated for discourse relations containing over 1 million words. Any language other than English however, can be considered a low-resource language when it comes to discourse processing.
This dissertation is about shallow discourse parsing (discourse parsing following the paradigm of the Penn Discourse TreeBank) for German. The limited availability of annotated data for German means the potential of modern, deep-learning based methods relying on such data is also limited. This dissertation explores to what extent machine-learning and more recent deep-learning based methods can be combined with traditional, linguistic feature engineering to improve performance for the discourse parsing task. A pivotal role is played by connective lexicons that exhaustively list the discourse connectives of a particular language along with some of their core properties.
To facilitate training and evaluation of the methods proposed in this dissertation, an existing corpus (the Potsdam Commentary Corpus) has been extended and additional data has been annotated from scratch. The approach to end-to-end shallow discourse parsing for German adopts a pipeline architecture and either presents the first results or improves over state-of-the-art for German for the individual sub-tasks of the discourse parsing task, which are, in processing order, connective identification, argument extraction and sense classification. The end-to-end shallow discourse parser for German that has been developed for the purpose of this dissertation is open-source and available online.
In the course of writing this dissertation, work has been carried out on several connective lexicons in different languages. Due to their central role and demonstrated usefulness for the methods proposed in this dissertation, strategies are discussed for creating or further developing such lexicons for a particular language, as well as suggestions on how to further increase their usefulness for shallow discourse parsing.
Obesity is a major health problem for many developing and industrial countries. Increasing rates reach almost 50 % of the population in some countries and related metabolic diseases including cardiovascular events and T2DM are challenging the health systems. Adiposity, an increase in body fat mass, is a major hallmark of obesity. Adipose tissue is long known not only to store lipids but also to influence whole-body metabolism including food intake, energy expenditure and insulin sensitivity. Adipocytes can store lipids and thereby protect other tissue from lipotoxic damage. However, if the energy intake is higher than the energy expenditure over a sustained time period, adipose tissue will expand. This can lead to an impaired adipose tissue function resulting in higher levels of plasma lipids, which can affect other tissue like skeletal muscle, finally leading to metabolic complications. Several studies showed beneficial metabolic effects of weight reduction in obese subjects immediately after weight loss. However, weight regain is frequently observed along with potential negative effects on cardiovascular risk factors and a high intra-individual response.
We performed a body weight maintenance study investigating the mechanisms of weight maintenance after intended WR. Therefore we used a low caloric diet followed by a 12-month life-style intervention. Comprehensive phenotyping including fat and muscle biopsies was conducted to investigate hormonal as well as metabolic influences on body weight regulation. In this study, we showed that weight reduction has numerous potentially beneficial effects on metabolic parameters. After 3-month WR subjects showed significant weight and fat mass reduction, lower TG levels as well as higher insulin sensitivity. Using RNA-Seq to analyse whole fat and muscle transcriptome a strong impact of weight reduction on adipose tissue gene expression was observed. Gene expression alterations over weight reduction included several cellular metabolic genes involved in lipid and glucose metabolism as well as insulin signalling and regulatory pathways. These changes were also associated with anthropometric parameters assigning body composition. Our data indicated that weight reduction leads to a decreased expression of several lipid catabolic as well as anabolic genes. Long-term body weight maintenance might be influenced by several parameters including hormones, metabolic intermediates as well as the transcriptional landscape of metabolic active tissues. Our data showed that genes involved in biosynthesis of unsaturated fatty acids might influence the BMI 18-month after a weight reduction phase. This was further supported by analysing metabolic parameters including RQ and FFA levels. We could show that subjects maintaining their lost body weight had a higher RQ and lower FFA levels, indicating increased metabolic flexibility in subjects.
Using this transcriptomic approach we hypothesize that low expression levels of lipid synthetic genes in adipose tissue together with a higher mitochondrial activity in skeletal muscle tissue might be beneficial in terms of body weight maintenance.
The negative impact of crude oil on the environment has led to a necessary transition toward alternative, renewable, and sustainable resources. In this regard, lignocellulosic biomass (LCB) is a promising renewable and sustainable alternative to crude oil for the production of fine chemicals and fuels in a so-called biorefinery process. LCB is composed of polysaccharides (cellulose and hemicellulose), as well as aromatics (lignin). The development of a sustainable and economically advantageous biorefinery depends on the complete and efficient valorization of all components. Therefore, in the new generation of biorefinery, the so-called biorefinery of type III, the LCB feedstocks are selectively deconstructed and catalytically transformed into platform chemicals. For this purpose, the development of highly stable and efficient catalysts is crucial for progress toward viability in biorefinery. Furthermore, a modern and integrated biorefinery relies on process and reactor design, toward more efficient and cost-effective methodologies that minimize waste. In this context, the usage of continuous flow systems has the potential to provide safe, sustainable, and innovative transformations with simple process integration and scalability for biorefinery schemes.
This thesis addresses three main challenges for future biorefinery: catalyst synthesis, waste feedstock valorization, and usage of continuous flow technology. Firstly, a cheap, scalable, and sustainable approach is presented for the synthesis of an efficient and stable 35 wt.-% Ni catalyst on highly porous nitrogen-doped carbon support (35Ni/NDC) in pellet shape. Initially, the performance of this catalyst was evaluated for the aqueous phase hydrogenation of LCB-derived compounds such as glucose, xylose, and vanillin in continuous flow systems. The 35Ni/NDC catalyst exhibited high catalytic performances in three tested hydrogenation reactions, i.e., sorbitol, xylitol, and 2-methoxy-4-methylphenol with yields of 82 mol%, 62 mol%, and 100 mol% respectively. In addition, the 35Ni/NDC catalyst exhibited remarkable stability over a long time on stream in continuous flow (40 h). Furthermore, the 35Ni/NDC catalyst was combined with commercially available Beta zeolite in a dual–column integrated process for isosorbide production from glucose (yield 83 mol%).
Finally, 35Ni/NDC was applied for the valorization of industrial waste products, namely sodium lignosulfonate (LS) and beech wood sawdust (BWS) in continuous flow systems. The LS depolymerization was conducted combining solvothermal fragmentation of water/alcohol mixtures (i.e.,methanol/water and ethanol/water) with catalytic hydrogenolysis/hydrogenation (SHF). The depolymerization was found to occur thermally in absence of catalyst with a tunable molecular weight according to temperature. Furthermore, the SHF generated an optimized cumulative yield of lignin-derived phenolic monomers of 42 mg gLS-1. Similarly, a solvothermal and reductive catalytic fragmentation (SF-RCF) of BWS was conducted using MeOH and MeTHF as a solvent. In this case, the optimized total lignin-derived phenolic monomers yield was found of 247 mg gKL-1.
This thesis investigates the gradient flow of Dirac-harmonic maps. Dirac-harmonic maps are critical points of an energy functional that is motivated from supersymmetric field theories. The critical points of this energy functional couple the equation for harmonic maps with spinor fields. At present, many analytical properties of Dirac-harmonic maps are known, but a general existence result is still missing. In this thesis the existence question is studied using the evolution equations for a regularized version of Dirac-harmonic maps. Since the energy functional for Dirac-harmonic maps is unbounded from below the method of the gradient flow cannot be applied directly. Thus, we first of all consider a regularization prescription for Dirac-harmonic maps and then study the gradient flow. Chapter 1 gives some background material on harmonic maps/harmonic spinors and summarizes the current known results about Dirac-harmonic maps. Chapter 2 introduces the notion of Dirac-harmonic maps in detail and presents a regularization prescription for Dirac-harmonic maps. In Chapter 3 the evolution equations for regularized Dirac-harmonic maps are introduced. In addition, the evolution of certain energies is discussed. Moreover, the existence of a short-time solution to the evolution equations is established. Chapter 4 analyzes the evolution equations in the case that the domain manifold is a closed curve. Here, the existence of a smooth long-time solution is proven. Moreover, for the regularization being large enough, it is shown that the evolution equations converge to a regularized Dirac-harmonic map. Finally, it is discussed in which sense the regularization can be removed. In Chapter 5 the evolution equations are studied when the domain manifold is a closed Riemmannian spin surface. For the regularization being large enough, the existence of a global weak solution, which is smooth away from finitely many singularities is proven. It is shown that the evolution equations converge weakly to a regularized Dirac-harmonic map. In addition, it is discussed if the regularization can be removed in this case.
Previous studies on the acquisition of verb inflection in normally developing children have revealed an astonishing pattern: children use correctly inflected verbs in their own speech but fail to make use of verb inflections when comprehending sentences uttered by others. Thus, a three-year old might well be able to say something like ‘The cat sleeps on the bed’, but fails to understand that the same sentence, when uttered by another person, refers to only one sleeping cat but not more than one. The previous studies that have examined children's comprehension of verb inflections have employed a variant of a picture selection task in which the child was asked to explicitly indicate (via pointing) what semantic meaning she had inferred from the test sentence. Recent research on other linguistic structures, such as pronouns or focus particles, has indicated that earlier comprehension abilities can be found when methods are used that do not require an explicit reaction, like preferential looking tasks. This dissertation aimed to examine whether children are truly not able to understand the connection the the verb form and the meaning of the sentence subject until the age of five years or whether earlier comprehension can be found when a different measure, preferential looking, is used. Additionally, children's processing of subject-verb agreement violations was examined. The three experiments of this thesis that examined children's comprehension of verb inflections revealed the following: German-speaking three- to four-year old children looked more to a picture showing one actor when hearing a sentence with a singular inflected verb but only when their eye gaze was tracked and they did not have to perform a picture selection task. When they were asked to point to the matching picture, they performed at chance-level. This pattern indicates asymmetries in children's language performance even within the receptive modality. The fourth experiment examined sensitivity to subject-verb agreement violations and did not reveal evidence for sensitivity toward agreement violations in three- and four-year old children, but only found that children's looking patterns were influenced by the grammatical violations at the age of five. The results from these experiments are discussed in relation to the existence of a production-comprehension asymmetry in the use of verb inflections and children's underlying grammatical knowledge.
Since available phosphate (Pi) resources in soil are limited, symbiotic interactions between plant roots and arbuscular mycorrhizal (AM) fungi are a widespread strategy to improve plant phosphate nutrition. The repression of AM symbiosis by a high plant Pi-status indicates a link between Pi homeostasis signalling and AM symbiosis development. This assumption is supported by the systemic induction of several microRNA399 (miR399) primary transcripts in shoots and a simultaneous accumulation of mature miR399 in roots of mycorrhizal plants. However, the physiological role of this miR399 expression pattern is still elusive and offers the question whether other miRNAs are also involved in AM symbiosis. Therefore, a deep sequencing approach was applied to investigate miRNA-mediated posttranscriptional gene regulation in M. truncatula mycorrhizal roots. Degradome analysis revealed that 185 transcripts were cleaved by miRNAs, of which the majority encoded transcription factors and disease resistance genes, suggesting a tight control of transcriptional reprogramming and a downregulation of defence responses by several miRNAs in mycorrhizal roots. Interestingly, 45 of the miRNA-cleaved transcripts showed a significant differentially regulated between mycorrhizal and non-mycorrhizal roots. In addition, key components of the Pi homeostasis signalling pathway were analyzed concerning their expression during AM symbiosis development. MtPhr1 overexpression and time course expression data suggested a strong interrelation between the components of the PHR1-miR399-PHO2 signalling pathway and AM symbiosis, predominantly during later stages of symbiosis. In situ hybridizations confirmed accumulation of mature miR399 in the phloem and in arbuscule-containing cortex cells of mycorrhizal roots. Moreover, a novel target of the miR399 family, named as MtPt8, was identified by the above mentioned degradome analysis. MtPt8 encodes a Pi-transporter exclusively transcribed in mycorrhizal roots and its promoter activity was restricted to arbuscule-containing cells. At a low Pi-status, MtPt8 transcript abundance inversely correlated with a mature miR399 expression pattern. Increased MtPt8 transcript levels were accompanied by elevated symbiotic Pi-uptake efficiency, indicating its impact on balancing plant and fungal Pi-acquisition. In conclusion, this study provides evidence for a direct link of the regulatory mechanisms of plant Pi-homeostasis and AM symbiosis at a cell-specific level. The results of this study, especially the interaction of miR399 and MtPt8 provide a fundamental step for future studies of plant-microbe-interactions with regard to agricultural and ecological aspects.
The Milky Way is only one out of billions of galaxies in the universe. However, it is a special galaxy because it allows to explore the main mechanisms involved in its evolution and formation history by unpicking the system star-by-star. Especially, the chemical fingerprints of its stars provide clues and evidence of past events in the Galaxy’s lifetime. These information help not only to decipher the current structure and building blocks of the Milky Way, but to learn more about the general formation process of galaxies.
In the past decade a multitude of stellar spectroscopic Galactic surveys have scanned millions of stars far beyond the rim of the solar neighbourhood. The obtained spectroscopic information provide unprecedented insights to the chemo-dynamics of the Milky Way. In addition analytic models and numerical simulations of the Milky Way provide necessary descriptions and predictions suited for comparison with observations in order to decode the physical properties that underlie the complex system of the Galaxy.
In the thesis various approaches are taken to connect modern theoretical modelling of galaxy formation and evolution with observations from Galactic stellar surveys. With its focus on the chemo-kinematics of the Galactic disk this work aims to determine new observational constraints on the formation of the Milky Way providing also proper comparisons with two different models. These are the population synthesis model TRILEGAL based on analytical distribution functions, which aims to simulate the number and distribution of stars in the Milky Way and its different components, and a hybrid model (MCM) that combines an N-body simulation of a Milky Way like galaxy in the cosmological framework with a semi-analytic chemical evolution model for the Milky Way. The major observational data sets in use come from two surveys, namely the “Radial Velocity Experiment” (RAVE) and the “Sloan Extension for Galactic Understanding and Exploration” (SEGUE).
In the first approach the chemo-kinematic properties of the thin and thick disk of the Galaxy as traced by a selection of about 20000 SEGUE G-dwarf stars are directly compared to the predictions by the MCM model. As a necessary condition for this, SEGUE's selection function and its survey volume are evaluated in detail to correct the spectroscopic observations for their survey specific selection biases. Also, based on a Bayesian method spectro-photometric distances with uncertainties below 15% are computed for the selection of SEGUE G-dwarfs that are studied up to a distance of 3 kpc from the Sun.
For the second approach two synthetic versions of the SEGUE survey are generated based on the above models. The obtained synthetic stellar catalogues are then used to create mock samples best resembling the compiled sample of observed SEGUE G-dwarfs. Generally, mock samples are not only ideal to compare predictions from various models. They also allow validation of the models' quality and improvement as with this work could be especially achieved for TRILEGAL. While TRILEGAL reproduces the statistical properties of the thin and thick disk as seen in the observations, the MCM model has shown to be more suitable in reproducing many chemo-kinematic correlations as revealed by the SEGUE stars. However, evidence has been found that the MCM model may be missing a stellar component with the properties of the thick disk that the observations clearly show. While the SEGUE stars do indicate a thin-thick dichotomy of the stellar Galactic disk in agreement with other spectroscopic stellar studies, no sign for a distinct metal-poor disk is seen in the MCM model.
Usually stellar spectroscopic surveys are limited to a certain volume around the Sun covering different regions of the Galaxy’s disk. This often prevents to obtain a global view on the chemo-dynamics of the Galactic disk. Hence, a suitable combination of stellar samples from independent surveys is not only useful for the verification of results but it also helps to complete the picture of the Milky Way. Therefore, the thesis closes with a comparison of the SEGUE G-dwarfs and a sample of RAVE giants. The comparison reveals that the chemo-kinematic relations agree in disk regions where the samples of both surveys show a similar number of stars. For those parts of the survey volumes where one of the surveys lacks statistics they beautifully complement each other. This demonstrates that the comparison of theoretical models on the one side, and the combined observational data gathered by multiple surveys on the other side, are key ingredients to understand and disentangle the structure and formation history of the Milky Way.
The valorization of carbohydrates is one of the most promising fields in green chemistry, as it enables to produce bulk chemicals and fuels out of renewable and abundant resources, instead of further exploiting fossil feedstocks. The focus in this thesis is the conversion of fructose, using dehydration and hydrodeoxygenation reactions. The main goal is to find an easy continuous process, including the solubility of the sugar in a green solvent, the conversion over a solid acid as well as over a metal@tungsten carbide catalyst.
At the beginning of this thesis, solid acid catalysts are synthesized by using carbohydrate material like glucose and starch at high temperatures (up to 600 °C). Additionally a third carbon is synthesized, using an activation method based on Ca(OH)2. After carbonization and further sulfonation, using fuming sulfuric acid, the three resulting catalysts are characterized together with sulfonated carbon black and Amberlyst 15 as references. In order to test all solid acid catalysts in reaction, a 250 mm x 4.6 mm stainless steel column is used as a fixed-bed continuous reactor. The temperature (110 °C to 250 °C) and residence time (2 to 30 minutes) is varied, and a direct relationship between contact time and selectivity is determined. The reaction mechanism, as well as the product distribution is showing a dehydration step of fructose towards 5-hydroxymethylfurfural (HMF). These furan-ring molecules are considered as “sleeping giants”, due to the possibility of using them as fuel, but also for upgrading them to chemicals like terephthalic acid or p-xylene. Consecutive reactions are producing levulinic acid, as well as condensation products with ethanol and formic acid. The activated carbon is additionally showing a 2 % yield of 2,5-Dimethylfuran (DMF) production, pointing towards the extraordinary properties of this catalyst. Without a metal catalyst present, what is normally necessary for hydrogenation reactions, a transferhydrogenation (with formic acid) is observed. The active catalyst was therefore carbon itself, what activated the hydrogen on its surface. This phenomenon was just very rarely observed so far. Expensive noble metals are the material of choice, when it comes to hydrogenation reactions nowadays and cheaper alternatives are necessary.
By postulating a similar electronic structure of tungsten carbide (WC) to platinum by Lewy and Boudart, research is focusing on the replacement of Pt. The production of nano-sized tungsten carbide particles (7.5 ± 2.5 nm, 70 m2 g-1) is enabled by the so called “urea glass route” and its catalytic performances are compared to commercial material. It is shown, that the activity is strongly dependent on the size of the particles as well as the surface area. Nano-sized tungsten carbide is showing activity for hydrogenation reactions under mild conditions (maximum 150 °C, 30 bar). This material therefore opens up new possibilities for replacing the rare and expensive platinum with tungsten carbide based catalysts.
Additionally different metal nanoparticles of palladium, copper and nickel are deposited on top of WC to further promote its reactivity. The nickel nanoparticles are strongly connected to WC and showed the best activity as well as selectivity for upgrading HMF with hydrodeoxygenation. The Ni@WC is not leaching and is showing very good hydrodeoxygenation properties with DMF yields up to 90 percent. Copper@WC is not showing good activity and palladium@WC enables undesired consecutive reactions, hydrogenating the furan ring system.
In order to enable the upgrade of fructose to DMF directly in a continuous system, the current H CUBE Pro TM hydrogenation system is customized with a second reaction column. A 250 mm x 4.6 mm stainless steel reactor column is connected ahead of the hydrogen insertion, enabling the dehydration of fructose to HMF derivatives, before pumping these products into the second column for hydrogenation. The overall residence time in the two column reactor system is 14 minutes. The overall results are an almost full conversion with a yield of 38.5 % DMF and 47 % yield of EL. The main disadvantage is the formation of higher mass products, so called humins, which start depositing on top of the catalysts, blocking their active sites.
In general it can be stated, that a two column system goes along with a higher investment as well as more maintenance costs, compared to a one column catalytic approach. To develop a catalyst, which is on the one hand able to dehydrate as well as hydrodeoxygenate the reactants, is aimed for at the last part of the thesis. The activated carbon however shows already activity for hydrodeoxygenation without any metal present and offers itself therefore as an alternative to overcome the temperature instability of Amberlyst 15 (max. 120 °C) for a combined DMF production directly from fructose. The activity for the upgrade to DMF is increased from 2 % to 12 % DMF yield in one mixed continuous column.
In order to scale up the entire one column approach, an 800 mm x 28.5 mm inner diameter column was planned and manufactured. The system is scaled up and assembled, whereas this flow reactor system is able to be run with 50 mL min-1 maximum flow rate, to stand a pressure of maximum 100 bar and be heated to around 500 °C. The tubing and connections, as well as the used devices are planned according to be safe and easy in use. The scaled-up approach offers a reaction column 120 times bigger (510 ml) then the first extension of the commercial system. This further extension offers the possibility of ranging between 1 and 1000 mL min-1, making it possible to use the approach in pilot plant applications.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
In this thesis sentence processing was investigated using a psychophysiological measure known as pupillometry as well as Event-Related Potentials (ERP). The scope of the the- sis was broad, investigating the processing of several different movement constructions with native speakers of English and second language learners of English, as well as word order and case marking in German speaking adults and children. Pupillometry and ERP allowed us to test competing linguistic theories and use novel methodologies to investigate the processing of word order. In doing so we also aimed to establish pupillometry as an effective way to investigate the processing of word order thus broadening the methodological spectrum.
Light-switchable proteins are being used increasingly to understand and manipulate complex molecular systems. The success of this approach has fueled the development of tailored photo-switchable proteins, to enable targeted molecular events to be studied using light. The development of novel photo-switchable tools has to date largely relied on rational design. Complementing this approach with directed evolution would be expected to facilitate these efforts. Directed evolution, however, has been relatively infrequently used to develop photo-switchable proteins due to the challenge presented by high-throughput evaluation of switchable protein activity. This thesis describes the development of two genetic circuits that can be used to evaluate libraries of switchable proteins, enabling optimization of both the on- and off-states. A screening system is described, which permits detection of DNA-binding activity based on conditional expression of a fluorescent protein. In addition, a tunable selection system is presented, which allows for the targeted selection of protein-protein interactions of a desired affinity range. This thesis additionally describes the development and characterization of a synthetic protein that was designed to investigate chromophore reconstitution in photoactive yellow protein (PYP), a promising scaffold for engineering photo-controlled protein tools.
According to the classical plume hypothesis, mantle plumes are localized upwellings of hot, buoyant material in the Earth’s mantle. They have a typical mushroom shape, consisting of a large plume head, which is associated with the formation of voluminous flood basalts (a Large
Igneous Province) and a narrow plume tail, which generates a linear, age-progressive chain of volcanic edifices (a hotspot track) as the tectonic plate migrates over the relatively stationary plume. Both plume heads and tails reshape large areas of the Earth’s surface over many tens of millions of years.
However, not every plume has left an exemplary record that supports the classical hypothesis. The main objective of this thesis is therefore to study how specific hotspots have created the crustal thickness pattern attributed to their volcanic activities. Using regional geodynamic
models, the main chapters of this thesis address the challenge of deciphering the three individual (and increasingly complex) Réunion, Iceland, and Kerguelen hotspot histories, especially focussing on the interactions between the respective plume and nearby spreading ridges.
For this purpose, the mantle convection code ASPECT is used to set up three-dimensional numerical models, which consider the specific local surroundings of each plume by prescribing time-dependent boundary conditions for temperature and mantle flow. Combining reconstructed plate boundaries and plate motions, large-scale global flow velocities and an inhomogeneous lithosphere thickness distribution together with a dehydration rheology represents a novel setup for regional convection models.
The model results show the crustal thickness pattern produced by the plume, which is compared to present-day topographic structures, crustal thickness estimates and age determinations of volcanic provinces associated with hotspot activity. Altogether, the model results agree well
with surface observations. Moreover, the dynamic development of the plumes in the models provide explanations for the generation of smaller, yet characteristic volcanic features that were previously unexplained. Considering the present-day state of a model as a prediction for the
current temperature distribution in the mantle, it cannot only be compared to observations on the surface, but also to structures in the Earth’s interior as imaged by seismic tomography.
More precisely, in the case of the Réunion hotspot, the model demonstrates how the distinctive gap between the Maldives and Chagos is generated due to the combination of the ridge geometry and plume-ridge interaction. Further, the Rodrigues Ridge is formed as the surface expression
of a long-distance sublithospheric flow channel between the upwelling plume and the closest ridge segment, confirming the long-standing hypothesis of Morgan (1978) for the first time in a dynamic context. The Réunion plume has been studied in connection with the seismological
RHUM-RUM project, which has recently provided new seismic tomography images that yield an excellent match with the geodynamic model.
Regarding the Iceland plume, the numerical model shows how plume material may have accumulated in an east-west trending corridor of thin lithosphere across Greenland and resulted in simultaneous melt generation west and east of Greenland. This provides an explanation for the
extremely widespread volcanic material attributed to magma production of the Iceland hotspot and demonstrates that the model setup is also able to explain more complicated hotspot histories. The Iceland model results also agree well with newly derived seismic tomographic images.
The Kerguelen hotspot has an extremely complex history and previous studies concluded that the plume might be dismembered or influenced by solitary waves in its conduit to produce the reconstructed variable melt production rate. The geodynamic model, however, shows that a constant plume influx can result in a variable magma production rate if the plume interacts with nearby mid-ocean ridges. Moreover, the Ninetyeast Ridge in the model is created by on-ridge activities, while the Kerguelen plume was located beneath the Australian plate. This is also a contrast to earlier studies, which described the Ninetyeast Ridge as the result of the Indian plate passing over the plume. Furthermore, the Amsterdam-Saint Paul Plateau in the model is the result of plume material flowing from the upwelling toward the Southeast Indian Ridge, whereas previous geochemical studies attributed that volcanic province to a separate deep plume.
In summary, the three case studies presented in this thesis consistently highlight the importance of plume-ridge interaction in order to reconstruct the overall volcanic hotspot record as well as specific smaller features attributed to a certain hotspot. They also demonstrate that it is not necessary to attribute highly complicated properties to a specific plume in order to account for complex observations. Thus, this thesis contributes to the general understanding of plume dynamics and extends the very specific knowledge about the Réunion, Iceland, and Kerguelen mantle plumes.
Connective ties in discourse: Three ERP studies on causal, temporal and concessive connective ties and their influence on language processing. Questions In four experiments the influence of lexical connectives such as " darum", therefore, " danach", afterwards, and " trotzdem", nevertheless, on the processing of short two-sentence discourses was examined and compared to the processing of deictical sentential adverbs such as " gestern", yesterday, and " lieber", rather. These latter words do not have the property of signaling a certain discourse relation between two sentences, as connective ties do. Three questions were central to the work: * Do the processing contrasts found between connective and non-connective elements extend to connective ties and deictical sentential adverbs (experiments 2 and 3)? * Does the semantic content of the connective ties play the primary role, i.e is the major distinction to be made indeed between connective and non-connective or instead between causal, temporal and concessive? * When precisely is the information provided by connective ties used? There is some evidence that connective ties can have an immediate influence on the integration of subsequent elements, but the end of the second sentences appears to play an important role as well: experiments 2, 3, and 4. Conclusions First of all, the theoretical distinction between connective and non-connective elements does indeed have " cognitive reality" . This has already been shown in previous studies. The present studies do however show, that there is also a difference between one-place discourse elements (deictical sentential adverbs) and two-place discourse elements, namely connective ties, since all experiments examining this contrast found evidence for qualitatively and quantitatively different processing (experiments 1, 2, and 3). Secondly, the semantic type of the connective ties also plays a role. This was not shown for the LAN, found for all connective ties when compared to non-connective elements, and consequently interpreted as a more abstract reflection of the integration of connective ties. There was also no difference between causal and temporal connective ties before the end of the discourses in experiment 3. However, the N400 found for incoherent discourses in experiment 2, larger for connective incoherent than non-connective incoherent discourses, as well as the P3b found for concessive connective ties in the comparison between causal and concessive connective ties gave reason to assume that the semantic content of connective ties is made use of in incremental processing, and that the relation signaled by the connective tie is the one that readers attempt to construct. Concerning when the information provided by connective ties is used, it appears as if connectivity is generally and obligatorily taken at face value. As long as the meaning of a connective tie did not conflict with a preferred canonical discourse relation, there were no differences found for varying connective discourses (experiment 3). However, the fact that concessive connective ties announce the need for a more complex text representation was recognized and made use of immediately (experiment 4). Additionally, a violation of the discourse relation resulted in more difficult semantic integration if a connective tie was present (experiment 2). It is therefore concluded here that connective ties influence processing immediately. This claim has to be modified somewhat, since the sentence-final elements suggested that connective ties trigger different integration processes than non-connective elements. It seems as if the answer to the question of when connective ties are processed is neither exclusively immediately nor exclusively afterwards, but that both viewpoints are correct. It is suggested here that before the end of a discourse economy plays a central role in that a canonical relation is assumed unless there is evidence to the contrary. A connective tie could have the function of reducing the dimensions evaluated in a discourse to the one signaled by the connective tie. At the end of the discourse the representation is evaluated and verified, and an integrated situation model constructed. Here, the complexity of the different discourse relations that connective ties can signal, is expressed.
Polymers at membranes
(2000)
The surface of biological cells consists of a lipid membrane and a large amount of various proteins and polymers, which are embedded in the membrane or attached to it. We investigate how membranes are influenced by polymers, which are anchored to the membrane by one end. The entropic pressure exerted by the polymer induces a curvature, which bends the membrane away from the polymer. The resulting membrane shape profile is a cone in the vicinity of the anchor segment and a catenoid far away from it. The perturbative calculations are confirmed by Monte-Carlo simulations. An additional attractive interaction between polymer and membrane reduces the entropically induced curvature. In the limit of strong adsorption, the polymer is localized directly on the membrane surface and does not induce any pressure, i.e. the membrane curvature vanishes. If the polymer is not anchored directly on the membrane surface, but in a non-vanishing anchoring distance, the membrane bends towards the polymer for strong adsorption. In the last part of the thesis, we study membranes under the influence of non-anchored polymers in solution. In the limit of pure steric interactions between the membrane and free polymers, the membrane curves towards the polymers (in contrast to the case of anchored polymers). In the limit of strong adsorption the membrane bends away from the polymers.
Recent years witnessed a vast advent of stalagmites as palaeoclimate archives. The multitude of geochemical and physical proxies and a promise of a precise and accurate age model greatly appeal to palaeoclimatologists. Although substantial progress was made in speleothem-based palaeoclimate research and despite high-resolution records from low-latitudinal regions, proving that palaeo-environmental changes can be archived on sub-annual to millennial time scales our comprehension of climate dynamics is still fragmentary. This is in particular true for the summer monsoon system on the Indian subcontinent. The Indian summer monsoon (ISM) is an integral part of the intertropical convergence zone (ITCZ). As this rainfall belt migrates northward during boreal summer, it brings monsoonal rainfall. ISM strength depends however on a variety of factors, including snow cover in Central Asia and oceanic conditions in the Indic and Pacific. Presently, many of the factors influencing the ISM are known, though their exact forcing mechanism and mutual relations remain ambiguous. Attempts to make an accurate prediction of rainfall intensity and frequency and drought recurrence, which is extremely important for South Asian countries, resemble a puzzle game; all interaction need to fall into the right place to obtain a complete picture. My thesis aims to create a faithful picture of climate change in India, covering the last 11,000 ka. NE India represents a key region for the Bay of Bengal (BoB) branch of the ISM, as it is here where the monsoon splits into a northwestward and a northeastward directed arm. The Meghalaya Plateau is the first barrier for northward moving air masses and receives excessive summer rainfall, while the winter season is very dry. The proximity of Meghalaya to the Tibetan Plateau on the one hand and the BoB on the other hand make the study area a key location for investigating the interaction between different forcings that governs the ISM. A basis for the interpretation of palaeoclimate records, and a first important outcome of my thesis is a conceptual model which explains the observed pattern of seasonal changes in stable isotopes (d18O and d2H) in rainfall. I show that although in tropical and subtropical regions the amount effect is commonly called to explain strongly depleted isotope values during enhanced rainfall, alone it cannot account for observed rainwater isotope variability in Meghalaya. Monitoring of rainwater isotopes shows no expected negative correlation between precipitation amount and d18O of rainfall. In turn I find evidence that the runoff from high elevations carries an inherited isotopic signature into the BoB, where during the ISM season the freshwater builds a strongly depleted plume on top of the marine water. The vapor originating from this plume is likely to memorize' and transmit further very negative d18O values. The lack of data does not allow for quantication of this plume effect' on isotopes in rainfall over Meghalaya but I suggest that it varies on seasonal to millennial timescales, depending on the runoff amount and source characteristics. The focal point of my thesis is the extraction of climatic signals archived in stalagmites from NE India. High uranium concentration in the stalagmites ensured excellent age control required for successful high-resolution climate reconstructions. Stable isotope (d18O and d13C) and grey-scale data allow unprecedented insights into millennial to seasonal dynamics of the summer and winter monsoon in NE India. ISM strength (i. e. rainfall amount) is recorded in changes in d18Ostalagmites. The d13C signal, reflecting drip rate changes, renders a powerful proxy for dry season conditions, and shows similarities to temperature-related changes on the Tibetan Plateau. A sub-annual grey-scale profile supports a concept of lower drip rate and slower stalagmite growth during dry conditions. During the Holocene, ISM followed a millennial-scale decrease of insolation, with decadal to centennial failures resulting from atmospheric changes. The period of maximum rainfall and enhanced seasonality corresponds to the Holocene Thermal Optimum observed in Europe. After a phase of rather stable conditions, 4.5 kyr ago, the strengthening ENSO system dominated the ISM. Strong El Nino events weakened the ISM, especially when in concert with positive Indian Ocean dipole events. The strongest droughts of the last 11 kyr are recorded during the past 2 kyr. Using the advantage of a well-dated stalagmite record at hand I tested the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to detect sub-annual to sub-decadal changes in element concentrations in stalagmites. The development of a large ablation cell allows for ablating sample slabs of up to 22 cm total length. Each analyzed element is a potential proxy for different climatic parameters. Combining my previous results with the LAICP- MS-generated data shows that element concentration depends not only on rainfall amount and associated leaching from the soil. Additional factors, like biological activity and hydrogeochemical conditions in the soil and vadose zone can eventually affect the element content in drip water and in stalagmites. I present a theoretical conceptual model for my study site to explain how climatic signals can be transmitted and archived in stalagmite carbonate. Further, I establish a first 1500 year long element record, reconstructing rainfall variability. Additionally, I hypothesize that volcanic eruptions, producing large amounts of sulfuric acid, can influence soil acidity and hence element mobilization.
This work reports about new high-resolution imaging and spectroscopic observations of solar type III radio bursts at low radio frequencies in the range from 30 to 80 MHz. Solar type III radio bursts are understood as result of the beam-plasma interaction of electron beams in the corona. The Sun provides a unique opportunity to study these plasma processes of an active star. Its activity appears in eruptive events like flares, coronal mass ejections and radio bursts which are all accompanied by enhanced radio emission. Therefore solar radio emission carries important information about plasma processes associated with the Sun’s activity. Moreover, the Sun’s atmosphere is a unique plasma laboratory with plasma processes under conditions not found in terrestrial laboratories. Because of the Sun’s proximity to Earth, it can be studied in greater detail than any other star but new knowledge about the Sun can be transfer to them. This “solar stellar connection” is important for the understanding of processes on other stars.
The novel radio interferometer LOFAR provides imaging and spectroscopic capabilities to study these processes at low frequencies. Here it was used for solar observations.
LOFAR, the characteristics of its solar data and the processing and analysis of the latter with the Solar Imaging Pipeline and Solar Data Center are described. The Solar Imaging Pipeline is the central software that allows using LOFAR for solar observations. So its development was necessary for the analysis of solar LOFAR data and realized here. Moreover a new density model with heat conduction and Alfvén waves was developed that provides the distance of radio bursts to the Sun from dynamic radio spectra.
Its application to the dynamic spectrum of a type III burst observed on March 16, 2016 by LOFAR shows a nonuniform radial propagation velocity of the radio emission. The analysis of an imaging observation of type III bursts on June 23, 2012 resolves a burst as bright, compact region localized in the corona propagating in radial direction along magnetic field lines with an average velocity of 0.23c. A nonuniform propagation velocity is revealed. A new beam model is presented that explains the nonuniform motion of the radio source as a propagation effect of an electron ensemble with a spread velocity distribution and rules out a monoenergetic electron distribution. The coronal electron number density is derived in the region from 1.5 to 2.5 R☉ and fitted with the newly developed density model. It determines the plasma density for the interplanetary space between Sun and Earth. The values correspond to a 1.25- and 5-fold Newkirk model for harmonic and fundamental emission, respectively. In comparison to data from other radio instruments the LOFAR data shows a high sensitivity and resolution in space, time and frequency.
The new results from LOFAR’s high resolution imaging spectroscopy are consistent with current theories of solar type III radio bursts and demonstrate its capability to track fast moving radio sources in the corona. LOFAR solar data is found to be a valuable source for solar radio physics and opens a new window for studying plasma processes associated with highly energetic electrons in the solar corona.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive.
This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches.
This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools.
Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
Cellulose is the most abundant biopolymer on earth and the main load-bearing structure in plant cell walls. Cellulose microfibrils are laid down in a tight parallel array, surrounding plant cells like a corset. Orientation of microfibrils determines the direction of growth by directing turgor pressure to points of expansion (Somerville et al., 2004). Hence, cellulose deficient mutants usually show cell and organ swelling due to disturbed anisotropic cell expansion (reviewed in Endler and Persson, 2011). How do cellulose microfibrils gain their parallel orientation? First experiments in the 1960s suggested, that cortical microtubules aid the cellulose synthases on their way around the cell (Green, 1962; Ledbetter and Porter, 1963). This was proofed in 2006 through life cell imaging (Paredez et al., 2006). However, how this guidance was facilitated, remained unknown. Through a combinatory approach, including forward and reverse genetics together with advanced co-expression analysis, we identified pom2 as a cellulose deficient mutant. Map- based cloning revealed that the gene locus of POM2 corresponded to CELLULOSE SYNTHASE INTERACTING 1 (CSI1). Intriguingly, we previously found the CSI1 protein to interact with the putative cytosolic part of the primary cellulose synthases in a yeast-two-hybrid screen (Gu et al., 2010). Exhaustive cell biological analysis of the POM2/CSI1 protein allowed to determine its cellular function. Using spinning disc confocal microscopy, we could show that in the absence of POM2/CSI1, cellulose synthase complexes lose their microtubule-dependent trajectories in the plasma membrane. The loss of POM2/CSI1, however does not influence microtubule- dependent delivery of cellulose synthases (Bringmann et al., 2012). Consequently, POM2/CSI1 acts as a bridging protein between active cellulose synthases and cortical microtubules. This thesis summarizes three publications of the author, regarding the identification of proteins that connect cellulose synthases to the cytoskeleton. This involves the development of bioinformatics tools allowing candidate gene prediction through co-expression studies (Mutwil et al., 2009), identification of candidate genes through interaction studies (Gu et al., 2010), and determination of the cellular function of the candidate gene (Bringmann et al., 2012).
Public administrations confront fundamental challenges, including globalization, digitalization, and an eroding level of trust from society. By developing joint public service delivery with other stakeholders, public administrations can respond to these challenges. This increases the importance of inter-organizational governance—a development often referred to as New Public Governance, which to date has not been realized because public administrations focus on intra-organizational practices and follow the traditional “governmental chain.”
E-government initiatives, which can lead to high levels of interconnected public services, are currently perceived as insufficient to meet this goal. They are not designed holistically and merely affect the interactions of public and non-public stakeholders. A fundamental shift toward a joint public service delivery would require scrutiny of established processes, roles, and interactions between stakeholders.
Various scientists and practitioners within the public sector assume that the use of blockchain institutional technology could fundamentally change the relationship between public and non-public stakeholders. At first glance, inter-organizational, joint public service delivery could benefit from the use of blockchain. This dissertation aims to shed light on this widespread assumption. Hence, the objective of this dissertation is to substantiate the effect of blockchain on the relationship between public administrations and non-public stakeholders.
This objective is pursued by defining three major areas of interest. First, this dissertation strives to answer the question of whether or not blockchain is suited to enable New Public Governance and to identify instances where blockchain may not be the proper solution. The second area aims to understand empirically the status quo of existing blockchain implementations in the public sector and whether they comply with the major theoretical conclusions. The third area investigates the changing role of public administrations, as the blockchain ecosystem can significantly increase the number of stakeholders.
Corresponding research is conducted to provide insights into these areas, for example, combining theoretical concepts with empirical actualities, conducting interviews with subject matter experts and key stakeholders of leading blockchain implementations, and performing a comprehensive stakeholder analysis, followed by visualization of its results.
The results of this dissertation demonstrate that blockchain can support New Public Governance in many ways while having a minor impact on certain aspects (e.g., decentralized control), which account for this public service paradigm. Furthermore, the existing projects indicate changes to relationships between public administrations and non-public stakeholders, although not necessarily the fundamental shift proposed by New Public Governance. Lastly, the results suggest that power relations are shifting, including the decreasing influence of public administrations within the blockchain ecosystem. The results raise questions about the governance models and regulations required to support mature solutions and the further diffusion of blockchain for public service delivery.
From dawn till dusk
(2020)
Supernova remnants are believed to be the source of cosmic rays with energies up to 10^15 eV that are produced within our Galaxy. The acceleration mechanism associated with the collision-less shocks in supernova remnants - diffusive shock acceleration - predicts a spectral index of the accelerated non-thermal particles of s = 2. However, measurements of non-thermal emission in radio, X-rays and gamma-rays reveal significant deviations of the particles spectral index from the canonical value of s = 2.
The youngest Galactic supernova remnant G1.9+0.3 is an interesting target for next-generation gamma-ray observatories. So far, the remnant is only detected in the radio and the X-ray bands, but its young age of ≈100 yrs and inferred shock speed of ≈ 14, 000 km/s could make it an efficient particle accelerator.
I performed spherical symmetric 1D simulations with the RATPaC code, in which I simultaneously solved the transport equation for cosmic rays, the transport equation for magnetic turbulence, and the hydro-dynamical equations for the gas flow. Separately computed distributions of the particles accelerated at the forward and the reverse shock were then used to calculate the spectra of synchrotron, inverse Compton, and Pion-decay radiation from the source.
The emission from G1.9+0.3 can be self-consistently explained within the test-particle limit. I find that the X-ray flux is dominated by emission from the forward shock while most of the radio emission originates near the reverse shock, which makes G1.9+0.3 the first remnant with non-thermal radiation detected from the reverse shock. The flux of very-high-energy gamma-ray emission from G1.9+0.3 is expected to be close to the sensitivity threshold of the Cherenkov Telescope Array. The limited time available to grow large-scale turbulence limits the maximum energy of particles to values below 100 TeV, hence G1.9+0.3 is not a PeVatron.
Although there are many models for the acceleration of cosmic rays in Supernova remnants, the escape of cosmic rays from these sources is yet understudied.
I use our time-dependent acceleration code RATPaC to study the acceleration of cosmic rays and their escape in post-adiabatic Supernova remnants and calculate the subsequent gamma-ray emission from inverse-Compton scattering and Pion decay. My simulations span 100,000 years, thus covering the free-expansion, the Sedov-Taylor, and the beginning of the post-adiabatic phase of the remnant’s evolution.
At later stages of the evolution cosmic rays over a wide range of energy can reside outside of the remnant, creating spectra that are softer than predicted by standard diffusive shock acceleration and feature breaks in the 10 - 100 GeV-range. The total spectrum of cosmic rays released into the interstellar medium has a spectral index of s ≈ 2.4 above roughly 10 GeV which is close to that required by Galactic propagation models. I further find the gamma-ray luminosity to peak around an age of 4,000 years for inverse-Compton-dominated high-energy emission. Remnants expanding in low-density media emit generally more inverse-Compton radiation matching the fact that the brightest known supernova remnants - RCW86, Vela Jr, HESSJ1721-347 and RXJ1713.7-3946 - are all expanding in low density environments.
The importance of feedback from the cosmic-rays on the hydrodynamical evolution of the remnants is debated as a possibility to obtain soft cosmic-ray spectra at low energies.
I performed spherically symmetric 1-D simulations with a modified version of the RATPaC code, in which I simultaneously solve the transport equation for cosmic rays and the hydrodynamical equations, including the back-reaction of the cosmic-ray pressure on the flow profiles.
Besides the known modification of the flow profiles and the consequently curved cosmic-ray spectra, steady-state models for non-linear diffusive shock acceleration overpredict the total compression ratio that can be reached with cosmic-ray feedback, as there is limited time for building these modifications. Further, I find modifications to the downstream flow structure that change the evolutionary behavior of the remnant and trigger a cosmic-ray-induced instability close to the contact discontinuity, if and when the cosmic-ray pressure becomes dominant there.
Spectral fingerprinting
(2015)
Current research on runoff and erosion processes, as well as an increasing demand for sustainable watershed management emphasize the need for an improved understanding of sediment dynamics. This involves the accurate assessment of erosion rates and sediment transfer, yield and origin. A variety of methods exist to capture these processes at the catchment scale. Among these, sediment fingerprinting, a technique to trace back the origin of sediment, has attracted increasing attention by the scientific community in recent years. It is a two-step procedure, based on the fundamental assumptions that potential sources of sediment can be reliably discriminated based on a set of characteristic ‘fingerprint’ properties, and that a comparison of source and sediment fingerprints allows to quantify the relative contribution of each source.
This thesis aims at further assessing the potential of spectroscopy to assist and improve the sediment fingerprinting technique. Specifically, this work focuses on (1) whether potential sediment sources can be reliably identified based on spectral features (‘fingerprints’), whether (2) these spectral fingerprints permit the quantification of relative source contribution, and whether (3) in situ derived source information is sufficient for this purpose. Furthermore, sediment fingerprinting using spectral information is applied in a study catchment to (4) identify major sources and observe how relative source contributions change between and within individual flood events. And finally, (5) spectral fingerprinting results are compared and combined with simultaneous sediment flux measurements to study sediment origin, transport and storage behaviour.
For the sediment fingerprinting approach, soil samples were collected from potential sediment sources within the Isábena catchment, a meso-scale basin in the central Spanish Pyrenees. Undisturbed samples of the upper soil layer were measured in situ using an ASD spectroradiometer and subsequently sampled for measurements in the laboratory. Suspended sediment was sampled automatically by means of ISCO samplers at the catchment as well as at the five major subcatchment outlets during flood events, and stored fine sediment from the channel bed was collected from 14 cross-sections along the main river. Artificial mixtures of known contributions were produced from source soil samples. Then, all source, sediment and mixture samples were dried and spectrally measured in the laboratory. Subsequently, colour coefficients and physically based features with relation to organic carbon, iron oxide, clay content and carbonate, were calculated from all in situ and laboratory spectra. Spectral parameters passing a number of prerequisite tests were submitted to principal component analyses to study natural clustering of samples, discriminant function analyses to observe source differentiation accuracy, and a mixing model for source contribution assessment. In addition, annual as well as flood event based suspended sediment fluxes from the catchment and its subcatchments were calculated from rainfall, water discharge and suspended sediment concentration measurements using rating curves and Quantile Regression Forests. Results of sediment flux monitoring were interpreted individually with respect to storage behaviour, compared to fingerprinting source ascriptions and combined with fingerprinting to assess their joint explanatory potential.
In response to the key questions of this work, (1) three source types (land use) and five spatial sources (subcatchments) could be reliably discriminated based on spectral fingerprints. The artificial mixture experiment revealed that while (2) laboratory parameters permitted source contribution assessment, (3) the use of in situ derived information was insufficient. Apparently, high discrimination accuracy does not necessarily imply good quantification results. When applied to suspended sediment samples of the catchment outlet, the spectral fingerprinting approach was able to (4) quantify the major sediment sources: badlands and the Villacarli subcatchment, respectively, were identified as main contributors, which is consistent with field observations and previous studies. Thereby, source contribution was found to vary both, within and between individual flood events. Also sediment flux was found to vary considerably, annually as well as seasonally and on flood event base. Storage was confirmed to play an important role in the sediment dynamics of the studied catchment, whereas floods with lower total sediment yield tend to deposit and floods with higher yield rather remove material from the channel bed. Finally, a comparison of flux measurements with fingerprinting results highlighted the fact that (5) immediate transport from sources to the catchment outlet cannot be assumed. A combination of the two methods revealed different aspects of sediment dynamics that none of the techniques could have uncovered individually.
In summary, spectral properties provide a fast, non-destructive, and cost-efficient means to discriminate and quantify sediment sources, whereas, unfortunately, straight-forward in situ collected source information is insufficient for the approach. Mixture modelling using artificial mixtures permits valuable insights into the capabilities and limitations of the method and similar experiments are strongly recommended to be performed in the future. Furthermore, a combination of techniques such as e.g. (spectral) sediment fingerprinting and sediment flux monitoring can provide comprehensive understanding of sediment dynamics.
Lakes are increasingly being recognized as an important component of the global carbon cycle, yet anthropogenic activities that alter their community structure may change the way they transport and process carbon. This research focuses on the relationship between carbon cycling and community structure of primary producers in small, shallow lakes, which are the most abundant lake type in the world, and furthermore subject to intense terrestrial-aquatic coupling due to their high perimeter:area ratio. Shifts between macrophyte and phytoplankton dominance are widespread and common in shallow lakes, with potentially large consequences to regional carbon cycling. I thus compared a lake with clear-water conditions and a submerged macrophyte community to a turbid, phytoplankton-dominated lake, describing differences in the availability, processing, and export of organic and inorganic carbon. I furthermore examined the effects of increasing terrestrial carbon inputs on internal carbon cycling processes. Pelagic diel (24-hour) oxygen curves and independent fluorometric approaches of individual primary producers together indicated that the presence of a submerged macrophyte community facilitated higher annual rates of gross primary production than could be supported in a phytoplankton-dominated lake at similar nutrient concentrations. A simple model constructed from the empirical data suggested that this difference between regime types could be common in moderately eutrophic lakes with mean depths under three to four meters, where benthic primary production is a potentially major contributor to the whole-lake primary production. It thus appears likely that a regime shift from macrophyte to phytoplankton dominance in shallow lakes would typically decrease the quantity of autochthonous organic carbon available to lake food webs. Sediment core analyses indicated that a regime shift from macrophyte to phytoplankton dominance was associated with a four-fold increase in carbon burial rates, signalling a major change in lake carbon cycling dynamics. Carbon mass balances suggested that increasing carbon burial rates were not due to an increase in primary production or allochthonous loading, but instead were due to a higher carbon burial efficiency (carbon burial / carbon deposition). This, in turn, was associated with diminished benthic mineralization rates and an increase in calcite precipitation, together resulting in lower surface carbon dioxide emissions. Finally, a period of unusually high precipitation led to rising water levels, resulting in a feedback loop linking increasing concentrations of dissolved organic carbon (DOC) to severely anoxic conditions in the phytoplankton-dominated system. High water levels and DOC concentrations diminished benthic primary production (via shading) and boosted pelagic respiration rates, diminishing the hypolimnetic oxygen supply. The resulting anoxia created redox conditions which led to a major release of nutrients, DOC, and iron from the sediments. This further transformed the lake metabolism, providing a prolonged summertime anoxia below a water depth of 1 m, and leading to the near-complete loss of fish and macroinvertebrates. Pelagic pH levels also decreased significantly, increasing surface carbon dioxide emissions by an order of magnitude compared to previous years. Altogether, this thesis adds an important body of knowledge to our understanding of the significance of the benthic zone to carbon cycling in shallow lakes. The contribution of the benthic zone towards whole-lake primary production was quantified, and was identified as an important but vulnerable site for primary production. Benthic mineralization rates were furthermore found to influence carbon burial and surface emission rates, and benthic primary productivity played an important role in determining hypolimnetic oxygen availability, thus controlling the internal sediment loading of nutrients and carbon. This thesis also uniquely demonstrates that the ecological community structure (i.e. stable regime) of a eutrophic, shallow lake can significantly influence carbon availability and processing. By changing carbon cycling pathways, regime shifts in shallow lakes may significantly alter the role of these ecosystems with respect to the global carbon cycle.
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).
Submarine landslides can generate local tsunamis posing a hazard to human lives and coastal facilities. Two major related problems are: (i) quantitative estimation of tsunami hazard and (ii) early detection of the most dangerous landslides. This thesis focuses on both those issues by providing numerical modeling of landslide-induced tsunamis and by suggesting and justifying a new method for fast detection of tsunamigenic landslides by means of tiltmeters. Due to the proximity to the Sunda subduction zone, Indonesian coasts are prone to earthquake, but also landslide tsunamis. The aim of the GITEWS-project (German-Indonesian Tsunami Early Warning System) is to provide fast and reliable tsunami warnings, but also to deepen the knowledge about tsunami hazards. New bathymetric data at the Sunda Arc provide the opportunity to evaluate the hazard potential of landslide tsunamis for the adjacent Indonesian islands. I present nine large mass movements in proximity to Sumatra, Java, Sumbawa and Sumba, whereof the largest event displaced 20 km³ of sediments. Using numerical modeling, I compute the generated tsunami of each event, its propagation and runup at the coast. Moreover, I investigate the age of the largest slope failures by relating them to the Great 1977 Sumba earthquake. Continental slopes off northwest Europe are well known for their history of huge underwater landslides. The current geological situation west of Spitsbergen is comparable to the continental margin off Norway after the last glaciation, when the large tsunamigenic Storegga slide took place. The influence of Arctic warming on the stability of the Svalbard glacial margin is discussed. Based on new geophysical data, I present four possible landslide scenarios and compute the generated tsunamis. Waves of 6 m height would be capable of reaching northwest Europe threatening coastal areas. I present a novel technique to detect large submarine landslides using an array of tiltmeters, as a possible tool in future tsunami early warning systems. The dislocation of a large amount of sediment during a landslide produces a permanent elastic response of the earth. I analyze this response with a mathematical model and calculate the theoretical tilt signal. Applications to the hypothetical Spitsbergen event and the historical Storegga slide show tilt signals exceeding 1000 nrad. The amplitude of landslide tsunamis is controlled by the product of slide volume and maximal velocity (slide tsunamigenic potential). I introduce an inversion routine that provides slide location and tsunamigenic potential, based on tiltmeter measurements. The accuracy of the inversion and of the estimated tsunami height near the coast depends on the noise level of tiltmeter measurements, the distance of tiltmeters from the slide, and the slide tsunamigenic potential. Finally, I estimate the applicability scope of this method by employing it to known landslide events worldwide.
In many applications one is faced with the problem of inferring some functional relation between input and output variables from given data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., spam labels) is a major goal of machine learning. Many learning methods assume that these training data are governed by the same distribution as the test data which the predictive model will be exposed to at application time. That assumption is violated when the test data are generated in response to the presence of a predictive model. This becomes apparent, for instance, in the above example of email spam filtering. Here, email service providers employ spam filters and spam senders engineer campaign templates such as to achieve a high rate of successful deliveries despite any filters. Most of the existing work casts such situations as learning robust models which are unsusceptible against small changes of the data generation process. The models are constructed under the worst-case assumption that these changes are performed such to produce the highest possible adverse effect on the performance of the predictive model. However, this approach is not capable to realistically model the true dependency between the model-building process and the process of generating future data. We therefore establish the concept of prediction games: We model the interaction between a learner, who builds the predictive model, and a data generator, who controls the process of data generation, as an one-shot game. The game-theoretic framework enables us to explicitly model the players' interests, their possible actions, their level of knowledge about each other, and the order at which they decide for an action. We model the players' interests as minimizing their own cost function which both depend on both players' actions. The learner's action is to choose the model parameters and the data generator's action is to perturbate the training data which reflects the modification of the data generation process with respect to the past data. We extensively study three instances of prediction games which differ regarding the order in which the players decide for their action. We first assume that both player choose their actions simultaneously, that is, without the knowledge of their opponent's decision. We identify conditions under which this Nash prediction game has a meaningful solution, that is, a unique Nash equilibrium, and derive algorithms that find the equilibrial prediction model. As a second case, we consider a data generator who is potentially fully informed about the move of the learner. This setting establishes a Stackelberg competition. We derive a relaxed optimization criterion to determine the solution of this game and show that this Stackelberg prediction game generalizes existing prediction models. Finally, we study the setting where the learner observes the data generator's action, that is, the (unlabeled) test data, before building the predictive model. As the test data and the training data may be governed by differing probability distributions, this scenario reduces to learning under covariate shift. We derive a new integrated as well as a two-stage method to account for this data set shift. In case studies on email spam filtering we empirically explore properties of all derived models as well as several existing baseline methods. We show that spam filters resulting from the Nash prediction game as well as the Stackelberg prediction game in the majority of cases outperform other existing baseline methods.
An increasing number of applications requires user interfaces that facilitate the handling of large geodata sets. Using virtual 3D city models, complex geospatial information can be communicated visually in an intuitive way. Therefore, real-time visualization of virtual 3D city models represents a key functionality for interactive exploration, presentation, analysis, and manipulation of geospatial data. This thesis concentrates on the development and implementation of concepts and techniques for real-time city model visualization. It discusses rendering algorithms as well as complementary modeling concepts and interaction techniques. Particularly, the work introduces a new real-time rendering technique to handle city models of high complexity concerning texture size and number of textures. Such models are difficult to handle by current technology, primarily due to two problems: - Limited texture memory: The amount of simultaneously usable texture data is limited by the memory of the graphics hardware. - Limited number of textures: Using several thousand different textures simultaneously causes significant performance problems due to texture switch operations during rendering. The multiresolution texture atlases approach, introduced in this thesis, overcomes both problems. During rendering, it permanently maintains a small set of textures that are sufficient for the current view and the screen resolution available. The efficiency of multiresolution texture atlases is evaluated in performance tests. To summarize, the results demonstrate that the following goals have been achieved: - Real-time rendering becomes possible for 3D scenes whose amount of texture data exceeds the main memory capacity. - Overhead due to texture switches is kept permanently low, so that the number of different textures has no significant effect on the rendering frame rate. Furthermore, this thesis introduces two new approaches for real-time city model visualization that use textures as core visualization elements: - An approach for visualization of thematic information. - An approach for illustrative visualization of 3D city models. Both techniques demonstrate that multiresolution texture atlases provide a basic functionality for the development of new applications and systems in the domain of city model visualization.
The Arctic tundra, covering approx. 5.5 % of the Earth’s land surface, is one of the last ecosystems remaining closest to its untouched condition. Remote sensing is able to provide information at regular time intervals and large spatial scales on the structure and function of Arctic ecosystems. But almost all natural surfaces reveal individual anisotropic reflectance behaviors, which can be described by the bidirectional reflectance distribution function (BRDF). This effect can cause significant changes in the measured surface reflectance depending on solar illumination and sensor viewing geometries. The aim of this thesis is the hyperspectral and spectro-directional reflectance characterization of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. Moreover, in preparation for the upcoming German EnMAP (Environmental Mapping and Analysis Program) satellite mission, the understanding of BRDF effects in Arctic tundra is essential for the retrieval of high quality, consistent and therefore comparable datasets. The research in this doctoral thesis is based on field spectroscopic and field spectro-goniometric investigations of representative Siberian and Alaskan measurement grids. The first objective of this thesis was the development of a lightweight, transportable, and easily managed field spectro-goniometer system which nevertheless provides reliable spectro-directional data. I developed the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS). The outcome of the field spectro-radiometrical measurements at the Low Arctic study sites along important environmental gradients (regional climate, soil pH, toposequence, and soil moisture) show that the different plant communities can be distinguished by their nadir-view reflectance spectra. The results especially reveal separation possibilities between the different tundra vegetation communities in the visible (VIS) blue and red wavelength regions. Additionally, the near-infrared (NIR) shoulder and NIR reflectance plateau, despite their relatively low values due to the low structure of tundra vegetation, are still valuable information sources and can separate communities according to their biomass and vegetation structure. In general, all different tundra plant communities show: (i) low maximum NIR reflectance; (ii) a weakly or nonexistent visible green reflectance peak in the VIS spectrum; (iii) a narrow “red-edge” region between the red and NIR wavelength regions; and (iv) no distinct NIR reflectance plateau. These common nadir-view reflectance characteristics are essential for the understanding of the variability of BRDF effects in Arctic tundra. None of the analyzed tundra communities showed an even closely isotropic reflectance behavior. In general, tundra vegetation communities: (i) usually show the highest BRDF effects in the solar principal plane; (ii) usually show the reflectance maximum in the backward viewing directions, and the reflectance minimum in the nadir to forward viewing directions; (iii) usually have a higher degree of reflectance anisotropy in the VIS wavelength region than in the NIR wavelength region; and (iv) show a more bowl-shaped reflectance distribution in longer wavelength bands (>700 nm). The results of the analysis of the influence of high sun zenith angles on the reflectance anisotropy show that with increasing sun zenith angles, the reflectance anisotropy changes to azimuthally symmetrical, bowl-shaped reflectance distributions with the lowest reflectance values in the nadir view position. The spectro-directional analyses also show that remote sensing products such as the NDVI or relative absorption depth products are strongly influenced by BRDF effects, and that the anisotropic characteristics of the remote sensing products can significantly differ from the observed BRDF effects in the original reflectance data. But the results further show that the NDVI can minimize view angle effects relative to the contrary spectro-directional effects in the red and NIR bands. For the researched tundra plant communities, the overall difference of the off-nadir NDVI values compared to the nadir value increases with increasing sensor viewing angles, but on average never exceeds 10 %. In conclusion, this study shows that changes in the illumination-target-viewing geometry directly lead to an altering of the reflectance spectra of Arctic tundra communities according to their object-specific BRDFs. Since the different tundra communities show only small, but nonetheless significant differences in the surface reflectance, it is important to include spectro-directional reflectance characteristics in the algorithm development for remote sensing products.
This thesis aims at a better mechanistic understanding of animal communities. Therefore, an allometry- and individual-based model has been developed which was used to simulate mammal and bird communities in heterogeneous landscapes, and to to better understand their response to landscape changes (habitat loss and fragmentation).
Nanostructured materials are materials consisting of nanoparticulate building blocks on the scale of nanometers (i.e. 10-9 m). Composition, crystallinity and morphology can enhance or even induce new properties of the materials, which are desirable for todays and future technological applications. In this work, we have shown new strategies to synthesise metal oxide and metal nitride nanomaterials. The first part of the work deals with the study of nonaqueous synthesis of metal oxide nanoparticles. We succeeded in the synthesis of In2O3 nanopartcles where we could clearly influence the morphology by varying the type of the precursors and the solvents; of ZnO mesocrystals by using acetonitrile as a solvent; of transition metal oxides (Nb2O5, Ta2O5 and HfO2) that are particularly hard to obtain on the nanoscale and other technologically important materials. Solvothermal synthesis however is not restricted to formation of oxide materials only. In the second part we show examples of nonaqueous, solvothermal reactions of metal nitrides, but the main focus lies on the investigation of the influence of different morphologies of metal oxide precursors on the formation of the metal nitride nanoparticles. In spite of various reports, the number and variety of nanocrystalline metal nitrides is marginally small by comparison to metal oxides; hence preformed metal oxides as precursors for the preparation of metal nitrides are a logical choice. By reacting oxide nanoparticles with cyanamide, urea or melamine, at temperatures of 800 to 900 °C under nitrogen flow metal nitrides could be obtained. We studied in detail the influence of the starting material and realized that size, crystallinity, type of nitrogen source and temperature play the most important role. We have managed to propose and verify a dissolution-recrystallisation model as the formation mechanism. Furthermore we could show that the initial morphology of the oxides could be retained when ammonia flow was used instead.
The economic impact analysis contained in this book shows how irrigation farming is particularly susceptible when applying certain water management policies in the Australian Murray-Darling Basin, one of the world largest river basins and Australia’s most fertile region. By comparing different pricing and non-pricing water management policies with the help of the Water Integrated Market Model, it is found that the impact of water demand reducing policies is most severe on crops that need to be intensively irrigated and are at the same time less water productive. A combination of increasingly frequent and severe droughts and the application of policies that decrease agricultural water demand, in the same region, will create a situation in which the highly water dependent crops rice and cotton cannot be cultivated at all.
Struggle for existence
(2022)
In this project, I sought to understand how Palestinian claim-making in the West Bank is possible within the context of continuing Israeli occupation and repression by the Palestinian political leadership. I explored the questions of what channels non-state actors use to advance their claims, what opportunities they have for making these claims, and what challenges they face. This exploration covers the time period from the Oslo Accords in the mid-1990s to the so-called Great March of Return in 2018.
I demonstrated that Palestinians used different modes and strategies of resistance in the past century, as the area of what today is Israel/Palestine has historically been a target for foreign penetration. Yet, the Oslo agreements between the Israeli government and the Palestinian leadership have ended Palestinians’ decentralized and pluralist social governance, reinforced Israeli rule in the Palestinian territories, promoted continuing dispossession and segregation of Palestinians, and further restricted their rights and their claim-making opportunities until this day. Therefore, today, Palestinian society in the West Bank is characterized by fragmentation, geographical and societal segregation, and double repression by Israeli occupation and Palestinian Authority (PA) policies. What is more, Palestinian claim-making is legally curtailed due to the establishment of different geographical entities in which Palestinians are subjugated to different forms of Israeli rule and regulations.
I argue that the concepts of civil society and acts of citizenship, which are often used to describe non-state actors’ rights-seeking activities, fall short on understanding and describing Palestinian claim-making in the West Bank comprehensively. By determining their boundaries, the concept of acts of subjecthood evolved as a novel theoretical approach within the research process and as a means of claim-making within repressive contexts where claim makers’ rights are curtailed and opportunities for rights-seeking activities are few. Thereby, this study applies a new theoretical framework to the conflict in Israel/Palestine and contributes to a better understanding of rights-seeking activities within the West Bank. Further, I argue that Palestinian acts of subjecthood against hostile Israeli rule in the West Bank are embedded within the comprehensive structure of settler colonialism. As a form of colonialism that aims at replacing an indigenous population, Israeli settler colonialism in the West Bank manifests itself in restrictions of Palestinian movement, settlement constructions, home demolitions, violence, and detentions.
By using grounded theory and inductive reasoning as methodological approaches, I was able to make generalizations about the state of Palestinian claim-making. These generalizations are based on the analysis of secondary materials and data collected via face-to-face and video interviews with non-state actors in Israel/Palestine. The conducted research shows that there is not a single measure or a standalone condition that hinders Palestinian claim-making, but a complex and comprehensive structure that, on the one hand, shrinks Palestinian living space by occupation and destruction and, on the other hand, diminishes Palestinian civic space by limiting the fundamental rights to organize and build social movements to change the status Palestinians live in.
Although the concrete, tangible outcomes of Palestinian acts of subjecthood are marginal, they contribute to strengthening and perpetuating Palestinian’s long history of resistance against Israeli oppression. With a lack of adherence to international law, the neglect of UN resolutions by the Israeli government, the continuous defeats of rights organizations in Israeli courts, and the repression of institutions based in the West Bank by PA and occupation policies, Palestinian acts of subjecthood cannot overturn current power structures. Nevertheless, the ongoing persistence of non-state actors claiming rights, as well as the pop-up of new initiatives and youth movements are all essential for strengthening Palestinians’ resilience and documenting current injustices. Therefore, they can build the pillars for social change in the future.
Das Ziel der vorliegenden Dissertation war es zu untersuchen, wie palästinensisches claim-making, also die Artikulation von Forderungen bzw. die Geltendmachung von bestimmten Rechten, vor dem Hintergrund der anhaltenden israelischen Besatzung und Repressalien durch die palästinensische politische Führung im Westjordanland durchgesetzt werden kann. Dabei soll der Frage nachgegangen werden, welche Kanäle nichtstaatliche Akteure nutzen, um ihre Ansprüche geltend zu machen, welche Möglichkeiten sich ihnen dafür bieten und vor welchen Herausforderungen sie stehen. Der Untersuchungszeitraum erstreckt sich dabei vom Osloer Friedensprozess Mitte der 1990er Jahre bis hin zum sogenannten Great March of Return im Jahr 2018.
Die im Gebiet des heutigen Israel/Palästina lebenden PalästinenserInnen bedienten sich in Zeiten ausländischer Einflussnahme, z.B. während der britischen Besatzung im vergangenen Jahrhundert, verschiedenster Widerstandsformen und -strategien. Jedoch haben die Osloer Abkommen zwischen der israelischen Regierung und der palästinensischen Führung die dezentrale und partizipative Mobilisierung der palästinensischen Gesellschaft erschwert, die andauernde Enteignung von PalästinenserInnen begünstigt und ihre Rechte bis zum heutigen Tag weiter eingeschränkt. Die heutige palästinensische Gesellschaft im Westjordanland ist daher durch Zersplitterung, geografische und gesellschaftliche Segregation und doppelte Un-terdrückung durch die israelische Besatzung sowie die Palästinensische Autonomiebehörde gekennzeichnet. Zudem führt die Etablierung verschiedener geografischer Entitäten, in denen PalästinenserInnen unterschiedlichen Formen israelischer Herrschaft, Regularien und Ein-griffsrechten unterworfen sind, dazu, dass palästinensisches claim-making auch formalrecht-lich eingeschränkt ist.
Um die Aktivitäten nichtstaatlicher Akteure in diesem Kontext beschreiben zu können, wer-den häufig das Konzept der Zivilgesellschaft oder das der acts of citizenship herangezogen. In der vorliegenden Arbeit wird jedoch argumentiert, dass diese Konzepte nur bedingt auf den Status Quo im Westjordanland anwendbar sind und palästinensisches claim-making nicht hinreichend verstehen und beschreiben können. Im Laufe des Forschungsprozesses hat sich daher das Konzept der acts of subjecthood als neuer theoretischer Ansatz herausgebildet, der claim-making in repressiven Kontexten beschreibt, in denen nichtstaatliche Akteure nur geringen Handlungsspielraum haben, ihre Forderungen durchsetzen zu können. Durch diese „Theorie-Brille“ ermöglicht meine Forschung einen neuartigen Blick auf den israelisch-palästinensischen Konflikt und trägt auf diese Weise zu einem besseren Verständnis von claim-making-Aktivitäten im Westjordanland bei. Darüber hinaus bettet die vorliegende Ar-beit acts of subjecthood in den größeren Kontext des Siedlungskolonialismus ein. Dieser beschreibt eine Form des Kolonialismus, die darauf abzielt, eine einheimische Bevölkerung durch die der Kolonialmacht zu ersetzen. Im Westjordanland manifestiert sich der israelische Siedlungskolonialismus in der Einschränkung der Bewegungsfreiheit von PalästinenserIn-nen, dem Bau von Siedlungen, der Zerstörung von Häusern, Gewalt und Inhaftierungen.
Die Verwendung der Grounded Theory und des induktiven Denkens als methodische Ansätze ermöglichte es, verallgemeinerbare Aussagen zum Zustand palästinensischen claim-makings treffen zu können. Diese Verallgemeinerungen beruhen auf der Analyse von Sekundärquellen und Daten, die im Rahmen von Interviews mit VertreterInnen nichtstaatlicher Organisationen in Israel/Palästina erhoben wurden. Die durchgeführte Analyse macht deutlich, dass nicht eine einzelne Maßnahme oder Bedingung palästinensisches claim-making behindert, sondern eine komplexe, vielschichtige und zielgerichtet implementierte Struktur. Diese verringert einerseits den Lebensraum von PalästinenserInnen durch Besatzung und Zerstörung und schränkt andererseits den zivilen Raum ein, indem sie ihnen grundlegende Rechte und fundamentale Freiheiten verwehrt.
Obwohl die konkreten Auswirkungen palästinensischer acts of subjecthood marginal sind, tragen sie dazu bei, den Widerstand gegen politische Unterdrückung zu stärken und fortzusetzen. Angesichts der Verletzung von Völkerrecht und der Missachtung zahlreicher UN-Resolutionen durch die israelische Regierung, der Niederlagen von Menschenrechtsorganisationen vor israelischen Gerichten, der Unterdrückung von Institutionen im Westjordanland durch die Palästinensische Autonomiebehörde und die Besatzungspolitik können acts of subjecthood die derzeitigen Machtstrukturen nicht aufbrechen. Dennoch sind die anhaltende Beharrlichkeit nichtstaatlicher Akteure, Forderungen zu artikulieren und Rechte einzufordern und die Gründung neuer Initiativen und Organisationen essenziell für die Stärkung gesellschaftlicher Resilienz sowie die Dokumentation von Ungerechtigkeiten und Rechtsverletzungen. Diese Akteure legen so den Grundstein für einen möglichen gesellschaftspolitischen Wandel in der Zukunft.
Role of dietary sulfonates in the stimulation of gut bacteria promoting intestinal inflammation
(2021)
The interplay between intestinal microbiota and host has increasingly been recognized as a major factor impacting health. Studies indicate that diet is the most influential determinant affecting the gut microbiota. A diet rich in saturated fat was shown to stimulate the growth of the colitogenic bacterium Bilophila wadsworthia by enhancing the secretion of the bile acid taurocholate (TC). The sulfonated taurine moiety of TC is utilized as a substrate by B. wadsworthia. The resulting overgrowth of B. wadsworthia was accompanied by an increased incidence and severity of colitis in interleukin (IL)-10-deficient mice, which are genetically prone to develop inflammation.
Based on these findings, the question arose whether the intake of dietary sulfonates also stimulates the growth of B. wadsworthia and thereby promotes intestinal inflammation in genetically susceptible mice. Dietary sources of sulfonates include green vegetables and cyanobacteria, which contain the sulfolipids sulfoquinovosyl diacylglycerols (SQDG) in considerable amounts. Based on literature reports, the gut commensal Escherichia coli is able to release sulfoquinovose (SQ) from SQDG and in further steps, convert SQ to 2,3-dihydroxypropane-1-sulfonate (DHPS) and dihydroxyacetone phosphate. DHPS may then be utilized as a growth substrate by B. wadsworthia, which results in the formation of sulfide. Both, sulfide formation and a high abundance of B. wadsworthia have been associated with intestinal inflammation.
In the present study, conventional IL-10-deficient mice were fed either a diet supplemented with the SQDG-rich cyanobacterium Spirulina (20%, SD) or a control diet. In addition SQ, TC, or water were orally applied to conventional or gnotobiotic IL-10-deficient mice. The gnotobiotic mice harbored a simplified human intestinal microbiota (SIHUMI) either with or without B. wadsworthia. During the intervention period, the body weight of the mice was monitored, the colon permeability was assessed and fecal samples were collected. After the three-week intervention, the animals were examined with regard to inflammatory parameters, microbiota composition and sulfonate concentrations in different intestinal sites.
None of the mice treated with the above-mentioned sulfonates showed weight loss or intestinal inflammation. Solely mice fed SD or gavaged with TC displayed a slight immune response. These mice also displayed an altered microbiota composition, which was not observed in mice gavaged with SQ. The abundance of B. wadsworthia was strongly reduced in mice fed SD, while that of mice treated with SQ or TC was in part slightly increased. The intestinal SQ-concentration was elevated in mice orally treated with SD or SQ, whereas neither TC nor taurine concentrations were consistently elevated in mice gavaged with TC. Additional colonization of SIHUMI mice with B. wadsworthia resulted in a mild inflammatory response, but only in mice treated with TC. In general, TC-mediated effects on the immune system and abundance of B. wadsworthia were not as strong as described in the literature.
In summary, neither the tested dietary sulfonates nor TC led to bacteria-induced intestinal inflammation in the IL-10-deficient mouse model, which was consistently observed in both conventional and gnotobiotic mice. For humans, this means that foods containing SQDG, such as spinach or Spirulina, do not increase the risk of intestinal inflammation.
Interlocutors typically link their utterances to the discourse environment and enrich communication by linguistic (e.g., information packaging) and extra-linguistic (e.g., eye gaze, gestures) means to optimize information transfer. Psycholinguistic studies underline that ‒for meaning computation‒ listeners profit from linguistic and visual cues that draw their focus of attention to salient information. This dissertation is the first work that examines how linguistic compared to visual salience cues influence sentence comprehension using the very same experimental paradigms and materials, that is, German subject-before-object (SO) and object-before-subject (OS) sentences, across the two cue modalities. Linguistic salience was induced by indicating a referent as the aboutness topic. Visual salience was induced by implicit (i.e., unconscious) or explicit (i.e., shared) manipulations of listeners’ attention to a depicted referent.
In Study 1, a selective, facilitative impact of linguistic salience on the context-sensitive OS word order was found using offline comprehensibility judgments. More precisely, during online sentence processing, this impact was characterized by a reduced sentence-initial Late positivity which reflects reduced processing costs for updating the current mental representation of discourse. This facilitative impact of linguistic salience was not replicated by means of an implicit visual cue (Study 2) shown to modulate word order preferences during sentence production. However, a gaze shift to a depicted referent as an indicator of shared attention eased sentence-initial processing similar to linguistic salience as revealed by reduced reading times (Study 3). Yet, this cue did not modulate the strong subject-antecedent preference during later pronoun resolution like linguistic salience. Taken together, these findings suggest a significant impact of linguistic and visual salience cues on sentence comprehension, which substantiates that both the information delivered via language and via the visual environment is integrated into the mental representation of the discourse; but, the way how salience is induced is crucial to its impact.
Our work goes in two directions. At first we want to transfer definitions, concepts and results of the theory of hyperidentities and solid varieties from the total to the partial case. (1) We prove that the operators chi^A_RNF and chi^E_RNF are only monotone and additive and we show that the sets of all fixed points of these operators are characterized only by three instead of four equivalent conditions for the case of closure operators. (2) We prove that V is n − SF-solid iff clone^SF V is free with respect to itself, freely generated by the independent set {[fi(x_1, . . . , x_n)]Id^SF_n V | i \in I}. (3) We prove that if V is n-fluid and ~V |P(V ) =~V −iso |P(V ) then V is kunsolid for k >= n (where P(V ) is the set of all V -proper hypersubstitutions of type \tau ). (4) We prove that a strong M-hyperquasi-equational theory is characterized by four equivalent conditions. The second direction of our work is to follow ideas which are typical for the partial case. (1) We characterize all minimal partial clones which are strongly solidifyable. (2)We define the operator Chi^A_Ph where Ph is a monoid of regular partial hypersubstitutions.Using this concept, we define the concept of a Phyp_R(\tau )-solid strong regular variety of partial algebras and we prove that a PHyp_R(\tau )-solid strong regular variety satisfies four equivalent conditions.
Injection of nanoscale zero-valent iron (nZVI) is an innovative technology for in situ installation of a permeable reactive barrier in the subsurface. Zerovalent iron (ZVI) is highly reactive with chlorinated hydrocarbons (CHCs) and renders them into less harmful substances. Application of nZVI instead of granular ZVI can increase rates of dechlorination of CHCs by orders of magnitude, due to its higher surface area. This approach is still difficult to apply due to fast agglomeration and sedimentation of colloidal suspensions of nZVI, which leads to very short transport distances. To overcome this issue of limited mobility, polyanionic stabilisers are added to increase surface charge and stability of suspensions. In field experiments maximum transport distances of a few metres were achieved. A new approach, which is investigated in this thesis, is enhanced mobility of nZVI by a more mobile carrier colloid. The investigated composite material consists of activated carbon, which is loaded with nZVI.
In this cumulative thesis, transport characteristics of carbon-colloid supported nZVI (c-nZVI) are investigated. Investigations started with column experiments in 40 cm columns filled with various porous media to investigate on physicochemical influences on transport characteristics. The experimental setup was enlarged to a transport experiment in a 1.2-m-sized two-dimensional aquifer tank experiment, which was filled with granular porous media. Further, a field experiment was performed in a natural aquifer system with a targeted transport distance of 5.3 m. Parallel to these investigations, alternative methods for transport observations were investigated by using noninvasive tomographic methods. Experiments using synchrotron radiation and magnetic resonance (MRI) were performed to investigate in situ transport characteristics in a non-destructive way.
Results from column experiments show potentially high mobility under environmental relevant conditions. Addition of mono-and bivalent salts, e.g. more than 0.5 mM/L CaCl2, might decrease mobility. Changes in pH to values below 6 can inhibit mobility at all. Measurements of colloid size show changes in the mean particle size by a factor of ten. Measurements of zeta potential revealed an increase of –62 mV to –82 mV. Results from the 2D-aquifer test system suggest strong particle deposition in the first centimetres and only weak straining in the further travel path and no gravitational influence on particle transport. Straining at the beginning of the travel path in the porous medium was observed with tomographic investigations of transport. MRI experiments revealed similar results to the previous experiments, and observations using synchrotron radiation suggest straining of colloids at pore throats. The potential for high transport distances, which was suggested from laboratory experiments, was confirmed in the field experiment, where the transport distance of 5.3 m was reached by at least 10% of injected nZVI. Altogether, transport distances of the investigated carbon-colloid supported nZVI are higher than published results of traditional nZVI.
Spatio-temporal data denotes a category of data that contains spatial as well as temporal components. For example, time-series of geo-data, thematic maps that change over time, or tracking data of moving entities can be interpreted as spatio-temporal data.
In today's automated world, an increasing number of data sources exist, which constantly generate spatio-temporal data. This includes for example traffic surveillance systems, which gather movement data about human or vehicle movements, remote-sensing systems, which frequently scan our surroundings and produce digital representations of cities and landscapes, as well as sensor networks in different domains, such as logistics, animal behavior study, or climate research.
For the analysis of spatio-temporal data, in addition to automatic statistical and data mining methods, exploratory analysis methods are employed, which are based on interactive visualization. These analysis methods let users explore a data set by interactively manipulating a visualization, thereby employing the human cognitive system and knowledge of the users to find patterns and gain insight into the data.
This thesis describes a software framework for the visualization of spatio-temporal data, which consists of GPU-based techniques to enable the interactive visualization and exploration of large spatio-temporal data sets. The developed techniques include data management, processing, and rendering, facilitating real-time processing and visualization of large geo-temporal data sets. It includes three main contributions:
- Concept and Implementation of a GPU-Based Visualization Pipeline.
The developed visualization methods are based on the concept of a GPU-based visualization pipeline, in which all steps -- processing, mapping, and rendering -- are implemented on the GPU. With this concept, spatio-temporal data is represented directly in GPU memory, using shader programs to process and filter the data, apply mappings to visual properties, and finally generate the geometric representations for a visualization during the rendering process. Data processing, filtering, and mapping are thereby executed in real-time, enabling dynamic control over the mapping and a visualization process which can be controlled interactively by a user.
- Attributed 3D Trajectory Visualization.
A visualization method has been developed for the interactive exploration of large numbers of 3D movement trajectories. The trajectories are visualized in a virtual geographic environment, supporting basic geometries such as lines, ribbons, spheres, or tubes. Interactive mapping can be applied to visualize the values of per-node or per-trajectory attributes, supporting shape, height, size, color, texturing, and animation as visual properties. Using the dynamic mapping system, several kind of visualization methods have been implemented, such as focus+context visualization of trajectories using interactive density maps, and space-time cube visualization to focus on the temporal aspects of individual movements.
- Geographic Network Visualization.
A method for the interactive exploration of geo-referenced networks has been developed, which enables the visualization of large numbers of nodes and edges in a geographic context. Several geographic environments are supported, such as a 3D globe, as well as 2D maps using different map projections, to enable the analysis of networks in different contexts and scales. Interactive filtering, mapping, and selection can be applied to analyze these geographic networks, and visualization methods for specific types of networks, such as coupled 3D networks or temporal networks have been implemented.
As a demonstration of the developed visualization concepts, interactive visualization tools for two distinct use cases have been developed. The first contains the visualization of attributed 3D movement trajectories of airplanes around an airport. It allows users to explore and analyze the trajectories of approaching and departing aircrafts, which have been recorded over the period of a month. By applying the interactive visualization methods for trajectory visualization and interactive density maps, analysts can derive insight from the data, such as common flight paths, regular and irregular patterns, or uncommon incidents such as missed approaches on the airport.
The second use case involves the visualization of climate networks, which are geographic networks in the climate research domain. They represent the dynamics of the climate system using a network structure that expresses statistical interrelationships between different regions. The interactive tool allows climate analysts to explore these large networks, analyzing the network's structure and relating it to the geographic background. Interactive filtering and selection enables them to find patterns in the climate data and identify e.g. clusters in the networks or flow patterns.
Increasing demand for food, healthcare, and transportation arising from the growing world population is accompanied by and driving global warming challenges due to the rise of the atmospheric CO2 concentration. Industrialization for human needs has been increasingly releasing CO2 into the atmosphere for the last century or more. In recent years, the possibility of recycling CO2 to stabilize the atmospheric CO2 concentration and combat rising temperatures has gained attention. Thus, using CO2 as the feedstock to address future world demands is the ultimate solution while controlling the rapid climate change. Valorizing CO2 to produce activated and stable one-carbon feedstocks like formate and methanol and further upgrading them to industrial microbial processes to replace unsustainable feedstocks would be crucial for a future biobased circular economy. However, not all microbes can grow on formate as a feedstock, and those microbes that can grow are not well established for industrial processes.
S. cerevisiae is one of the industrially well-established microbes, and it is a significant contributor to bioprocess industries. However, it cannot grow on formate as a sole carbon and energy source. Thus, engineering S. cerevisiae to grow on formate could potentially pave the way to sustainable biomass and value-added chemicals production.
The Reductive Glycine Pathway (RGP), designed as the aerobic twin of the anaerobic Reductive Acetyl-CoA pathway, is an efficient formate and CO2 assimilation pathway. The RGP comprises of the glycine synthesis module (Mis1p, Gcv1p, Gcv2p, Gcv3p, and Lpd1p), the glycine to serine conversion module (Shmtp), the pyruvate synthesis module (Cha1p), and the energy supply module (Fdh1p). The RGP requires formate and elevated CO2 levels to operate the glycine synthesis module. In this study, I established the RGP in the yeast system using growth-coupled selection strategies to achieve formate and CO2-dependent biomass formation in aerobic conditions.
Firstly, I constructed serine biosensor strains by disrupting the native serine and glycine biosynthesis routes in the prototrophic S288c and FL100 yeast strains and insulated serine, glycine, and one-carbon metabolism from the central metabolic network. These strains cannot grow on glucose as the sole carbon source but require the supply of serine or glycine to complement the engineered auxotrophies. Using growth as a readout, I employed these strains as selection hosts to establish the RGP. Initially, to achieve this, I engineered different serine-hydroxymethyltransferases in the genome of serine biosensor strains for efficient glycine to serine conversion. Then, I implemented the glycine synthesis module of the RGP in these strains for the glycine and serine synthesis from formate and CO2. I successfully conducted Adaptive Laboratory Evolution (ALE) using these strains, which yielded a strain capable of glycine and serine biosynthesis from formate and CO2. Significant growth improvements from 0.0041 h-1 to 0.03695 h-1 were observed during ALE. To validate glycine and serine synthesis, I conducted carbon tracing experiments with 13C formate and 13CO2, confirming that more than 90% of glycine and serine biosynthesis in the evolved strains occurs via the RGP. Interestingly, labeling data also revealed that 10-15% of alanine was labelled, indicating pyruvate synthesis from the formate-derived serine using native serine deaminase (Cha1p) activity. Thus, RGP contributes to a small pyruvate pool which is converted to alanine without any selection pressure for pyruvate synthesis from formate. Hence, this data confirms the activity of all three modules of RGP even in the presence of glucose. Further, ALE in glucose limiting conditions did not improve pyruvate flux via the RGP.
Growth characterization of these strains showed that the best growth rates were achieved in formate concentrations between 25 mM to 300 mM. Optimum growth required 5% CO2, and dropped when the CO2 concentration was reduced from 5% to 2.5%.
Whole-genome sequencing of these evolved strains revealed mutations in genes that encode Gdh1p, Pet9p, and Idh1p. These enzymes might influence intracellular NADPH, ATP, and NADH levels, indicating adjustment to meet the energy demand of the RGP. I reverse-engineered the GDH1 truncation mutation on unevolved serine biosensor strains and reproduced formate dependent growth. To elucidate the effect of the GDH1 mutation on formate assimilation, I reintroduced this mutation in the S288c strain and conducted carbon-tracing experiments to compared formate assimilation between WT and ∆gdh1 mutant strains. Comparatively, enhanced formate assimilation was recorded in the ∆gdh1 mutant strain.
Although the 13C carbon tracing experiments confirmed the activity of all three modules of the RGP, the overall pyruvate flux via the RGP might be limited by the supply of reducing power. Hence, in a different approach, I overexpressed the formate dehydrogenase (Fdh1p) for energy supply and serine deaminase (Cha1p) for active pyruvate synthesis in the S288c parental strain and established growth on formate and serine without glucose in the medium. Further reengineering and evolution of this strain with a consistent energy, and formate-derived serine supply for pyruvate synthesis, is essential to achieve complete formatotrophic growth in the yeast system.