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Magnetische Eisenoxidnanopartikel werden bereits seit geraumer Zeit erfolgreich als MRT-Kontrastmittel in der klinischen Bildgebung eingesetzt. Durch Optimierung der magnetischen Eigenschaften der Nanopartikel kann die Aussagekraft von MR-Aufnahmen verbessert und somit der diagnostische Wert einer MR-Anwendung weiter erhöht werden. Neben der Verbesserung bestehender Verfahren wird die bildgebende Diagnostik ebenso durch die Entwicklung neuer Verfahren, wie dem Magnetic Particle Imaging, vorangetrieben. Da hierbei das Messsignal von den magnetischen Nanopartikeln selbst erzeugt wird, birgt das MPI einen enormen Vorteil hinsichtlich der Sensitivität bei gleichzeitig hoher zeitlicher und räumlicher Auflösung. Da es aktuell jedoch keinen kommerziell vertriebenen in vivo-tauglichen MPI-Tracer gibt, besteht ein dringender Bedarf an geeigneten innovativen Tracermaterialien. Daraus resultierte die Motivation dieser Arbeit biokompatible und superparamagnetische Eisenoxidnanopartikel für den Einsatz als in vivo-Diagnostikum insbesondere im Magnetic Particle Imaging zu entwickeln. Auch wenn der Fokus auf der Tracerentwicklung für das MPI lag, wurde ebenso die MR-Performance bewertet, da geeignete Partikel somit alternativ oder zusätzlich als MR-Kontrastmittel mit verbesserten Kontrasteigenschaften eingesetzt werden könnten.
Die Synthese der Eisenoxidnanopartikel erfolgte über die partielle Oxidation von gefälltem Eisen(II)-hydroxid und Green Rust sowie eine diffusionskontrollierte Kopräzipitation in einem Hydrogel.
Mit der partiellen Oxidation von Eisen(II)-hydroxid und Green Rust konnten erfolgreich biokompatible und über lange Zeit stabile Eisenoxidnanopartikel synthetisiert werden. Zudem wurden geeignete Methoden zur Formulierung und Sterilisierung etabliert, wodurch zahlreiche Voraussetzungen für eine Anwendung als in vivo-Diagnostikum geschaffen wurden. Weiterhin ist auf Grundlage der MPS-Performance eine hervorragende Eignung dieser Partikel als MPI-Tracer zu erwarten, wodurch die Weiterentwicklung der MPI-Technologie maßgeblich vorangetrieben werden könnte. Die Bestimmung der NMR-Relaxivitäten sowie ein initialer in vivo-Versuch zeigten zudem das große Potential der formulierten Nanopartikelsuspensionen als MRT-Kontrastmittel. Die Modifizierung der Partikeloberfläche ermöglicht ferner die Herstellung zielgerichteter Nanopartikel sowie die Markierung von Zellen, wodurch das mögliche Anwendungsspektrum maßgeblich erweitert wurde.
Im zweiten Teil wurden Partikel durch eine diffusionskontrollierte Kopräzipitation im Hydrogel, wobei es sich um eine bioinspirierte Modifikation der klassischen Kopräzipitation handelt, synthetisiert, wodurch Partikel mit einer durchschnittlichen Kristallitgröße von 24 nm generiert werden konnten. Die Bestimmung der MPS- und MR-Performance elektrostatisch stabilisierter Partikel ergab vielversprechende Resultate. In Vorbereitung auf die Entwicklung eines in vivo-Diagnostikums wurden die Partikel anschließend erfolgreich sterisch stabilisiert, wodurch der kolloidale Zustand in MilliQ-Wasser über lange Zeit aufrechterhalten werden konnte. Durch Zentrifugation konnten die Partikel zudem erfolgreich in verschiedene Größenfraktionen aufgetrennt werden. Dies ermöglichte die Bestimmung der idealen Aggregatgröße dieses Partikelsystems in Bezug auf die MPS-Performance.
Thermal cis-trans isomerization of azobenzene studied by path sampling and QM/MM stochastic dynamics
(2017)
Azobenzene-based molecular photoswitches have extensively been applied to biological systems, involving photo-control of peptides, lipids and nucleic acids. The isomerization between the stable trans and the metastable cis state of the azo moieties leads to pronounced changes in shape and other physico-chemical properties of the molecules into which they are incorporated. Fast switching can be induced via transitions to excited electronic states and fine-tuned by a large number of different substituents at the phenyl rings. But a rational design of tailor-made azo groups also requires control of their stability in the dark, the half-lifetime of the cis isomer. In computational chemistry, thermally activated barrier crossing on the ground state Born-Oppenheimer surface can efficiently be estimated with Eyring’s transition state theory (TST) approach; the growing complexity of the azo moiety and a rather heterogeneous environment, however, may render some of the underlying simplifying assumptions problematic.
In this dissertation, a computational approach is established to remove two restrictions at once: the environment is modeled explicitly by employing a quantum mechanical/molecular mechanics (QM/MM) description; and the isomerization process is tracked by analyzing complete dynamical pathways between stable states. The suitability of this description is validated by using two test systems, pure azo benzene and a derivative with electron donating and electron withdrawing substituents (“push-pull” azobenzene). Each system is studied in the gas phase, in toluene and in polar DMSO solvent. The azo molecules are treated at the QM level using a very recent, semi-empirical approximation to density functional theory (density functional tight binding approximation). Reactive pathways are sampled by implementing a version of the so-called transition path sampling method (TPS), without introducing any bias into the system dynamics. By analyzing ensembles of reactive trajectories, the change in isomerization pathway from linear inversion to rotation in going from apolar to polar solvent, predicted by the TST approach, could be verified for the push-pull derivative. At the same time, the mere presence of explicit solvation is seen to broaden the distribution of isomerization pathways, an effect TST cannot account for.
Using likelihood maximization based on the TPS shooting history, an improved reaction coordinate was identified as a sine-cosine combination of the central bend angles and the rotation dihedral, r (ω,α,α′). The computational van’t Hoff analysis for the activation entropies was performed to gain further insight into the differential role of solvent for the case of the unsubstituted and the push-pull azobenzene. In agreement with the experiment, it yielded positive activation entropies for azobenzene in the DMSO solvent while negative for the push-pull derivative, reflecting the induced ordering of solvent around the more dipolar transition state associated to the latter compound. Also, the dynamically corrected rate constants were evaluated using the reactive flux approach where an increase comparable to the experimental one was observed for a high polarity medium for both azobenzene derivatives.
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.
With Saccharomyces cerevisiae being a commonly used host organism for synthetic biology and biotechnology approaches, the work presented here aims at the development of novel tools to improve and facilitate pathway engineering and heterologous protein production in yeast. Initially, the multi-part assembly strategy AssemblX was established, which allows the fast, user-friendly and highly efficient construction of up to 25 units, e.g. genes, into a single DNA construct. To speed up complex assembly projects, starting from sub-gene fragments and resulting in mini-chromosome sized constructs, AssemblX follows a level-based approach: Level 0 stands for the assembly of genes from multiple sub-gene fragments; Level 1 for the combination of up to five Level 0 units into one Level 1 module; Level 2 for linkages of up to five Level 1 modules into one Level 2 module. This way, all Level 0 and subsequently all Level 1 assemblies can be carried out simultaneously. Individually planned, overlap-based Level 0 assemblies enable scar-free and sequence-independent assemblies of transcriptional units, without limitations in fragment number, size or content. Level 1 and Level 2 assemblies, which are carried out via predefined, computationally optimized homology regions, follow a standardized, highly efficient and PCR-free scheme. AssemblX follows a virtually sequence-independent scheme with no need for time-consuming domestication of assembly parts. To minimize the risk of human error and to facilitate the planning of assembly projects, especially for individually designed Level 0 constructs, the whole AssemblX process is accompanied by a user-friendly webtool. This webtool provides the user with an easy-to-use operating surface and returns a bench-protocol including all cloning steps. The efficiency of the assembly process is further boosted through the implementation of different features, e.g. ccdB counter selection and marker switching/reconstitution. Due to the design of homology regions and vector backbones the user can flexibly choose between various overlap-based cloning methods, enabling cost-efficient assemblies which can be carried out either in E. coli or yeast. Protein production in yeast is additionally supported by a characterized library of 40 constitutive promoters, fully integrated into the AssemblX toolbox. This provides the user with a starting point for protein balancing and pathway engineering. Furthermore, the final assembly cassette can be subcloned into any vector, giving the user the flexibility to transfer the individual construct into any host organism different from yeast.
As successful production of heterologous compounds generally requires a precise adjustment of protein levels or even manipulation of the host genome to e.g. inhibit unwanted feedback regulations, the optogenetic transcriptional regulation tool PhiReX was designed. In recent years, light induction was reported to enable easy, reversible, fast, non-toxic and nearly gratuitous regulation, thereby providing manifold advantages compared to conventional chemical inducers. The optogenetic interface established in this study is based on the photoreceptor PhyB and its interacting protein PIF3. Both proteins, derived from Arabidopsis thaliana, dimerize in a red/far-red light-responsive manner. This interaction depends on a chromophore, naturally not available in yeast. By fusing split proteins to both components of the optical dimerizer, active enzymes can be reconstituted in a light-dependent manner. For the construction of the red/far-red light sensing gene expression system PhiReX, a customizable synTALE-DNA binding domain was fused to PhyB, and a VP64 activation domain to PIF3. The synTALE-based transcription factor allows programmable targeting of any desired promoter region. The first, plasmid-based PhiReX version mediates chromophore- and light-dependent expression of the reporter gene, but required further optimization regarding its robustness, basal expression and maximum output. This was achieved by genome-integration of the optical regulator pair, by cloning the reporter cassette on a high-copy plasmid and by additional molecular modifications of the fusion proteins regarding their cellular localization. In combination, this results in a robust and efficient activation of cells over an incubation time of at least 48 h. Finally, to boost the potential of PhiReX for biotechnological applications, yeast was engineered to produce the chromophore. This overcomes the need to supply the expensive and photo-labile compound exogenously. The expression output mediated through PhiReX is comparable to the strong constitutive yeast TDH3 promoter and - in the experiments described here - clearly exceeds the commonly used galactose inducible GAL1 promoter.
The fast-developing field of synthetic biology enables the construction of complete synthetic genomes. The upcoming Synthetic Yeast Sc2.0 Project is currently underway to redesign and synthesize the S. cerevisiae genome. As a prerequisite for the so-called “SCRaMbLE” system, all Sc2.0 chromosomes incorporate symmetrical target sites for Cre recombinase (loxPsym sites), enabling rearrangement of the yeast genome after induction of Cre with the toxic hormonal substance beta-estradiol. To overcome the safety concern linked to the use of beta-estradiol, a red light-inducible Cre recombinase, dubbed L-SCRaMbLE, was established in this study. L-SCRaMbLE was demonstrated to allow a time- and chromophore-dependent recombination with reliable off-states when applied to a plasmid containing four genes of the beta-carotene pathway, each flanked with loxPsym sites. When directly compared to the original induction system, L-SCRaMbLE generates a larger variety of recombination events and lower basal activity. In conclusion, L-SCRaMbLE provides a promising and powerful tool for genome rearrangement.
The three tools developed in this study provide so far unmatched possibilities to tackle complex synthetic biology projects in yeast by addressing three different stages: fast and reliable biosynthetic pathway assembly; highly specific, orthogonal gene regulation; and tightly controlled synthetic evolution of loxPsym-containing DNA constructs.
The functioning of the surface water-groundwater interface as buffer, filter and reactive zone is important for water quality, ecological health and resilience of streams and riparian ecosystems. Solute and heat exchange across this interface is driven by the advection of water. Characterizing the flow conditions in the streambed is challenging as flow patterns are often complex and multidimensional, driven by surface hydraulic gradients and groundwater discharge. This thesis presents the results of an integrated approach of studies, ranging from the acquisition of field data, the development of analytical and numerical approaches to analyse vertical temperature profiles to the detailed, fully-integrated 3D numerical modelling of water and heat flux at the reach scale. All techniques were applied in order to characterize exchange flux between stream and groundwater, hyporheic flow paths and temperature patterns.
The study was conducted at a reach-scale section of the lowland Selke River, characterized by distinctive pool riffle sequences and fluvial islands and gravel bars. Continuous time series of hydraulic heads and temperatures were measured at different depths in the river bank, the hyporheic zone and within the river. The analyses of the measured diurnal temperature variation in riverbed sediments provided detailed information about the exchange flux between river and groundwater. Beyond the one-dimensional vertical water flow in the riverbed sediment, hyporheic and parafluvial flow patterns were identified. Subsurface flow direction and magnitude around fluvial islands and gravel bars at the study site strongly depended on the position around the geomorphological structures and on the river stage. Horizontal water flux in the streambed substantially impacted temperature patterns in the streambed. At locations with substantial horizontal fluxes the penetration depths of daily temperature fluctuations was reduced in comparison to purely vertical exchange conditions.
The calibrated and validated 3D fully-integrated model of reach-scale water and heat fluxes across the river-groundwater interface was able to accurately represent the real system. The magnitude and variations of the simulated temperatures matched the observed ones, with an average mean absolute error of 0.7 °C and an average Nash Sutcliffe Efficiency of 0.87. The simulation results showed that the water and heat exchange at the surface water-groundwater interface is highly variable in space and time with zones of daily temperature oscillations penetrating deep into the sediment and spots of daily constant temperature following the average groundwater temperature. The average hyporheic flow path temperature was found to strongly correlate with the flow path residence time (flow path length) and the temperature gradient between river and groundwater. Despite the complexity of these processes, the simulation results allowed the derivation of a general empirical relationship between the hyporheic residence times and temperature patterns. The presented results improve our understanding of the complex spatial and temporal dynamics of water flux and thermal processes within the shallow streambed. Understanding these links provides a general basis from which to assess hyporheic temperature conditions in river reaches.
In this thesis, stochastic dynamics modelling collective motions of populations, one of the most mysterious type of biological phenomena, are considered. For a system of N particle-like individuals, two kinds of asymptotic behaviours are studied : ergodicity and flocking properties, in long time, and propagation of chaos, when the number N of agents goes to infinity. Cucker and Smale, deterministic, mean-field kinetic model for a population without a hierarchical structure is the starting point of our journey : the first two chapters are dedicated to the understanding of various stochastic dynamics it inspires, with random noise added in different ways. The third chapter, an attempt to improve those results, is built upon the cluster expansion method, a technique from statistical mechanics. Exponential ergodicity is obtained for a class of non-Markovian process with non-regular drift. In the final part, the focus shifts onto a stochastic system of interacting particles derived from Keller and Segel 2-D parabolicelliptic model for chemotaxis. Existence and weak uniqueness are proven.
Das Thema der vorliegenden Arbeit ist die semantische Suche im Kontext heutiger Informationsmanagementsysteme. Zu diesen Systemen zählen Intranets, Web 3.0-Anwendungen sowie viele Webportale, die Informationen in heterogenen Formaten und Strukturen beinhalten. Auf diesen befinden sich einerseits Daten in strukturierter Form und andererseits Dokumente, die inhaltlich mit diesen Daten in Beziehung stehen. Diese Dokumente sind jedoch in der Regel nur teilweise strukturiert oder vollständig unstrukturiert. So beschreiben beispielsweise Reiseportale durch strukturierte Daten den Zeitraum, das Reiseziel, den Preis einer Reise und geben in unstrukturierter Form weitere Informationen, wie Beschreibungen zum Hotel, Zielort, Ausflugsziele an.
Der Fokus heutiger semantischer Suchmaschinen liegt auf dem Finden von Wissen entweder in strukturierter Form, auch Faktensuche genannt, oder in semi- bzw. unstrukturierter Form, was üblicherweise als semantische Dokumentensuche bezeichnet wird. Einige wenige Suchmaschinen versuchen die Lücke zwischen diesen beiden Ansätzen zu schließen. Diese durchsuchen zwar gleichzeitig strukturierte sowie unstrukturierte Daten, werten diese jedoch entweder weitgehend voneinander unabhängig aus oder schränken die Suchmöglichkeiten stark ein, indem sie beispielsweise nur bestimmte Fragemuster unterstützen. Hierdurch werden die im System verfügbaren Informationen nicht ausgeschöpft und gleichzeitig unterbunden, dass Zusammenhänge zwischen einzelnen Inhalten der jeweiligen Informationssysteme und sich ergänzende Informationen den Benutzer erreichen.
Um diese Lücke zu schließen, wurde in der vorliegenden Arbeit ein neuer hybrider semantischer Suchansatz entwickelt und untersucht, der strukturierte und semi- bzw. unstrukturierte Inhalte während des gesamten Suchprozesses kombiniert. Durch diesen Ansatz werden nicht nur sowohl Fakten als auch Dokumente gefunden, es werden auch Zusammenhänge, die zwischen den unterschiedlich strukturierten Daten bestehen, in jeder Phase der Suche genutzt und fließen in die Suchergebnisse mit ein. Liegt die Antwort zu einer Suchanfrage nicht vollständig strukturiert, in Form von Fakten, oder unstrukturiert, in Form von Dokumenten vor, so liefert dieser Ansatz eine Kombination der beiden. Die Berücksichtigung von unterschiedlich Inhalten während des gesamten Suchprozesses stellt jedoch besondere Herausforderungen an die Suchmaschine. Diese muss in der Lage sein, Fakten und Dokumente in Abhängigkeit voneinander zu durchsuchen, sie zu kombinieren sowie die unterschiedlich strukturierten Ergebnisse in eine geeignete Rangordnung zu bringen. Weiterhin darf die Komplexität der Daten nicht an die Endnutzer weitergereicht werden. Die Darstellung der Inhalte muss vielmehr sowohl bei der Anfragestellung als auch bei der Darbietung der Ergebnisse verständlich und leicht interpretierbar sein.
Die zentrale Fragestellung der Arbeit ist, ob ein hybrider Ansatz auf einer vorgegebenen Datenbasis die Suchanfragen besser beantworten kann als die semantische Dokumentensuche und die Faktensuche für sich genommen, bzw. als eine Suche die diese Ansätze im Rahmen des Suchprozesses nicht kombiniert. Die durchgeführten Evaluierungen aus System- und aus Benutzersicht zeigen, dass die im Rahmen der Arbeit entwickelte hybride semantische Suchlösung durch die Kombination von strukturierten und unstrukturierten Inhalten im Suchprozess bessere Antworten liefert als die oben genannten Verfahren und somit Vorteile gegenüber bisherigen Ansätzen bietet. Eine Befragung von Benutzern macht deutlich, dass die hybride semantische Suche als verständlich empfunden und für heterogen strukturierte Datenmengen bevorzugt wird.
Estuarine marshes are ecosystems that are situated at the transition zone between land and water and are thus controlled by physical and biological interactions. Marsh vegetation offers important ecosystem services by filtrating solid and dissolved substances from the water and providing habitat. By buffering a large part of the arriving flow velocity, attenuating wave energy and serving as erosion control for riverbanks, tidal marshes furthermore reduce the destructive effects of storm surges and storm waves and thus contribute to ecosystem-based shore protection. However, in many estuaries, extensive embankments, artificial bank protection, river dredging and agriculture threaten tidal marshes. Global warming might entail additional risks, such as changes in water levels, an increase of the tidal amplitude and a resulting shift of the salinity zones. This can affect the dynamics of the shore and foreland vegetation, and vegetation belts can be narrowed or fragmented. Against this background, it is crucial to gain a better understanding of the processes underlying the spatio temporal vegetation dynamics in brackish marshes. Furthermore, a better understanding of how plant-habitat relationships generate patterns in tidal marsh vegetation is vital to maintain ecosystem functions and assess the response of marshes to environmental change as well as the success of engineering and restoration projects.
For this purpose, three research objectives were addressed within this thesis: (1) to explore the possibility of vegetation serving as self-adaptive shore protection by quantifying the reduction of current velocity in the vegetation belt and the morphologic plasticity of a brackish marsh pioneer, (2) to disentangle the roles of abiotic factors and interspecific competition on species distribution and stand characteristics in brackish marshes, and (3) to develop a mechanistic vegetation model that helps analysing the influence of habitat conditions on the spatio-temporal dynamic of tidal marsh vegetation. These aspects were investigated using a combination of field studies and statistical as well as process-based modelling.
To explore the possibility of vegetation serving as self-adaptive coastal protection, in the first study, we measured current velocity with and without living vegetation, recorded ramet density and plant thickness during two growing periods at two locations in the Elbe estuary and assessed the adaptive value of a larger stem diameter of plants at locations with higher mechanical stress by biomechanical measurements. The results of this study show that under non-storm conditions, the vegetation belt of the marsh pioneer Bolboschoenus maritimus is able to buffer a large proportion of the flow velocity. We were furthermore able to show that morphological traits of plant species are adapted to hydrodynamic forces by demonstrating a positive correlation between ramet thickness and cross-shore current. In addition, our measurements revealed that thicker ramets growing at the front of the vegetation belt have a significantly higher stability than ramets inside the vegetation belt. This self-adaptive effect improves the ability of B. maritimus to grow and persist in the pioneer zone and could provide an adaptive value in habitats with high mechanical stress.
In the second study, we assessed the distribution of the two marsh species and a set of stand characteristics, namely aboveground and belowground biomass, ramet density, ramet height and the percentage of flowering ramets. Furthermore, we collected information on several abiotic habitat factors to test their effect on plant growth and zonation with generalised linear models (GLMs). Our results demonstrate that flow velocity is the main factor controlling the distribution of Bolboschoenus maritimus and Phragmites australis. Additionally, inundation height and duration, as well as intraspecific competition affect distribution patterns. This study furthermore shows that cross-shore flow velocity does not only directly influence the distribution of the two marsh species, but also alters the plants’ occurrence relative to inun-dation height and duration. This suggests an effect of cross-shore flow velocity on their tolerance to inundation. The analysis of the measured stand characteristics revealed a negative effect of total flow velocity on all measured parameters of B. maritimus and thus confirmed our expectation that flow velocity is a decisive stressor which influences the growth of this species.
To gain a better understanding of the processes and habitat factors influencing the spatio-temporal vegetation dynamics in brackish marshes, I built a spatially explicit, mechanistic model applying a pattern-oriented modelling approach. A sensitivity analysis of the para-meters of this dynamic habitat-macrophyte model HaMac suggests that rhizome growth is the key process for the lateral dynamics of brackish marshes. From the analysed habitat factors, P. australis patterns were mainly influenced by flow velocity. The competition with P. australis was of key importance for the belowground biomass of B. maritimus. Concerning vegetation dynamics, the model results emphasise that without the effect of flow velocity the B. maritimus vegetation belt would expand into the tidal flat at locations with present vegetation recession, suggesting that flow velocity is the main reason for vegetation recession at exposed locations.
Overall, the results of this thesis demonstrate that brackish marsh vegetation considerably contributes to flow reduction under average flow conditions and can hence be a valuable component of shore-protection schemes. At the same time, the distribution, growth and expansion of tidal marsh vegetation is substantially influenced by flow. Altogether, this thesis provides a clear step forward in understanding plant-habitat interactions in tidal marshes. Future research should integrate studies of vertical marsh accretion with research on the factors that control the lateral position of marshes.
Information on the contemporary in-situ stress state of the earth’s crust is essential for geotechnical applications and physics-based seismic hazard assessment. Yet, stress data records for a data point are incomplete and their availability is usually not dense enough to allow conclusive statements. This demands a thorough examination of the in-situ stress field which is achieved by 3D geomechanicalnumerical models. However, the models spatial resolution is limited and the resulting local stress state is subject to large uncertainties that confine the significance of the findings. In addition, temporal variations of the in-situ stress field are naturally or anthropogenically induced. In my thesis I address these challenges in three manuscripts that investigate (1) the current crustal stress field orientation, (2) the 3D geomechanical-numerical modelling of the in-situ stress state, and (3) the phenomenon of injection induced temporal stress tensor rotations. In the first manuscript I present the first comprehensive stress data compilation of Iceland with 495 data records. Therefore, I analysed image logs from 57 boreholes in Iceland for indicators of the orientation of the maximum horizontal stress component. The study is the first stress survey from different kinds of stress indicators in a geologically very young and tectonically active area of an onshore spreading ridge. It reveals a distinct stress field with a depth independent stress orientation even very close to the spreading centre. In the second manuscript I present a calibrated 3D geomechanical-numerical modelling approach of the in-situ stress state of the Bavarian Molasse Basin that investigates the regional (70x70x10km³) and local (10x10x10km³) stress state. To link these two models I develop a multi-stage modelling approach that provides a reliable and efficient method to derive from the larger scale model initial and boundary conditions for the smaller scale model. Furthermore, I quantify the uncertainties in the models results which are inherent to geomechanical-numerical modelling in general and the multi-stage approach in particular. I show that the significance of the models results is mainly reduced due to the uncertainties in the material properties and the low number of available stress magnitude data records for calibration. In the third manuscript I investigate the phenomenon of injection induced temporal stress tensor rotation and its controlling factors. I conduct a sensitivity study with a 3D generic thermo-hydro-mechanical model. I show that the key control factors for the stress tensor rotation are the permeability as the decisive factor, the injection rate, and the initial differential stress. In particular for enhanced geothermal systems with a low permeability large rotations of the stress tensor are indicated. According to these findings the estimation of the initial differential stress in a reservoir is possible provided the permeability is known and the angle of stress rotation is observed. I propose that the stress tensor rotations can be a key factor in terms of the potential for induced seismicity on pre-existing faults due to the reorientation of the stress field that changes the optimal orientation of faults.
The existence of diverse and active microbial ecosystems in the deep subsurface – a biosphere that was originally considered devoid of life – was discovered in multiple microbiological studies. However, most of the studies are restricted to marine ecosystems, while our knowledge about the microbial communities in the deep subsurface of lake systems and their potentials to adapt to changing environmental conditions is still fragmentary. This doctoral thesis aims to build up a unique data basis for providing the first detailed high-throughput characterization of the deep biosphere of lacustrine sediments and to emphasize how important it is to differentiate between the living and the dead microbial community in deep biosphere studies.
In this thesis, up to 3.6 Ma old sediments (up to 317 m deep) of the El’gygytgyn Crater Lake were examined, which represents the oldest terrestrial climate record of the Arctic. Combining next generation sequencing with detailed geochemical characteristics and other environmental parameters, the microbial community composition was analyzed in regard to changing climatic conditions within the last 3.6 Ma to 1.0 Ma (Pliocene and Pleistocene). DNA from all investigated sediments was successfully extracted and a surprisingly diverse (6,910 OTUs) and abundant microbial community in the El’gygytgyn deep sediments were revealed. The bacterial abundance (10³-10⁶ 16S rRNA copies g⁻¹ sediment) was up to two orders of magnitudes higher than the archaeal abundance (10¹-10⁵) and fluctuates with the Pleistocene glacial/interglacial cyclicality. Interestingly, a strong increase in the microbial diversity with depth was observed (approximately 2.5 times higher diversity in Pliocene sediments compared to Pleistocene sediments). The increase in diversity with depth in the Lake El’gygytgyn is most probably caused by higher sedimentary temperatures towards the deep sediment layers as well as an enhanced temperature-induced intra-lake bioproductivity and higher input of allochthonous organic-rich material during Pliocene climatic conditions. Moreover, the microbial richness parameters follow the general trends of the paleoclimatic parameters, such as the paleo-temperature and paleo-precipitation. The most abundant bacterial representatives in the El’gygytgyn deep biosphere are affiliated with the phyla Proteobacteria, Actinobacteria, Bacteroidetes, and Acidobacteria, which are also commonly distributed in the surrounding permafrost habitats. The predominated taxon was the halotolerant genus Halomonas (in average 60% of the total reads per sample).
Additionally, this doctoral thesis focuses on the live/dead differentiation of microbes in cultures and environmental samples. While established methods (e.g., fluorescence in situ hybridization, RNA analyses) are not applicable to the challenging El’gygytgyn sediments, two newer methods were adapted to distinguish between DNA from live cells and free (extracellular, dead) DNA: the propidium monoazide (PMA) treatment and the cell separation adapted for low amounts of DNA. The applicability of the DNA-intercalating dye PMA was successfully evaluated to mask free DNA of different cultures of methanogenic archaea, which play a major role in the global carbon cycle. Moreover, an optimal procedure to simultaneously treat bacteria and archaea was developed using 130 µM PMA and 5 min of photo-activation with blue LED light, which is also applicable on sandy environmental samples with a particle load of ≤ 200 mg mL⁻¹. It was demonstrated that the soil texture has a strong influence on the PMA treatment in particle-rich samples and that in particular silt and clay-rich samples (e.g., El’gygytgyn sediments) lead to an insufficient shielding of free DNA by PMA. Therefore, a cell separation protocol was used to distinguish between DNA from live cells (intracellular DNA) and extracellular DNA in the El’gygytgyn sediments. While comparing these two DNA pools with a total DNA pool extracted with a commercial kit, significant differences in the microbial composition of all three pools (mean distance of relative abundance: 24.1%, mean distance of OTUs: 84.0%) was discovered. In particular, the total DNA pool covers significantly fewer taxa than the cell-separated DNA pools and only inadequately represents the living community. Moreover, individual redundancy analyses revealed that the microbial community of the intra- and extracellular DNA pool are driven by different environmental factors. The living community is mainly influenced by life-dependent parameters (e.g., sedimentary matrix, water availability), while the extracellular DNA is dependent on the biogenic silica content. The different community-shaping parameters and the fact, that a redundancy analysis of the total DNA pool explains significantly less variance of the microbial community, indicate that the total DNA represents a mixture of signals of the live and dead microbial community.
This work provides the first fundamental data basis of the diversity and distribution of microbial deep biosphere communities of a lake system over several million years. Moreover, it demonstrates the substantial importance of extracellular DNA in old sediments. These findings may strongly influence future environmental community analyses, where applications of live/dead differentiation avoid incorrect interpretations due to a failed extraction of the living microbial community or an overestimation of the past community diversity in the course of total DNA extraction approaches.
We analyze an inverse noisy regression model under random design with the aim of estimating the unknown target function based on a given set of data, drawn according to some unknown probability distribution. Our estimators are all constructed by kernel methods, which depend on a Reproducing Kernel Hilbert Space structure using spectral regularization methods.
A first main result establishes upper and lower bounds for the rate of convergence under a given source condition assumption, restricting the class of admissible distributions. But since kernel methods scale poorly when massive datasets are involved, we study one example for saving computation time and memory requirements in more detail. We show that Parallelizing spectral algorithms also leads to minimax optimal rates of convergence provided the number of machines is chosen appropriately.
We emphasize that so far all estimators depend on the assumed a-priori smoothness of the target function and on the eigenvalue decay of the kernel covariance operator, which are in general unknown. To obtain good purely data driven estimators constitutes the problem of adaptivity which we handle for the single machine problem via a version of the Lepskii principle.
Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles.
Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations.
Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years.
Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect.
Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication.
Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified.
Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk.
Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures.
Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes.
We present electrical impedance measurements of amoeboid cells on microelectrodes. The model organism Dictyostelium discoideum shows under starvation conditions a transition to collective behavior when chemotactic cells collect in multicellular aggregates. We show how impedance recordings give a precise picture of the stages of aggregation by tracing the dynamics of cell-substrate adhesion. Furthermore, we present for the first time systematic single cell measurements of wild type cells and four mutant strains that differ in their substrate adhesion strength. We recorded the projected cell area by time lapse microscopy and found a correlation between quasi-periodic oscillations in the kinetics of the projected area - the cell shape oscillation - and the long-term trend in the impedance signal. Typically, amoeboid motility advances via a cycle of membrane protrusion, substrate adhesion, traction of the cell body and tail retraction. This motility cycle results in the quasi-periodic oscillations of the projected cell area and the impedance. In all cell lines measured, similar periods were observed for this cycle, despite the differences in attachment strength. We observed that cell-substrate attachment strength strongly affects the impedance in that the deviations from mean (the magnitude of fluctuations) are enhanced in cells that effectively transmit forces, generated by the cytoskeleton, to the substrate. For example, in talA- cells, which lack the actin anchoring protein talin, the fluctuations are strongly reduced. Single cell force spectroscopy and results from a detachment assay, where adhesion is measured by exposing cells to shear stress, confirm that the magnitude of impedance fluctuations is a correct measure for the strength of substrate adhesion. Finally, we also worked on the integration of cell-substrate impedance sensors into microfluidic devices. A chip-based electrical chemotaxis assay is designed which measures the speed of chemotactic cells migrating over microelectrodes along a chemical concentration gradient.
During the course of millions of years, evolutionary forces have shaped the current distribution of species and their genetic variability, by influencing their phylogeny, adaptability and probability of survival. Southeast Asia is an extraordinary biodiverse region, where past climate events have resulted in dramatic changes in land availability and distribution of vegetation, resulting likewise in periodic connections between isolated islands and the mainland. These events have influenced the way species are distributed throughout this region but, more importantly, they influenced the genesis of genetic diversity. Despite the observation that a shared paleo-history resulted in very diverse species phylogeographic patterns, the mechanisms behind these patterns are still poorly understood.
In this thesis, I investigated and contrasted the phylogeography of three groups of ungulate species distributed within South and Southeast Asia, aiming to understand what mechanisms have shaped speciation and geographical distribution of genetic variability. For that purpose, I analysed the mitogenomes of historical samples, in order to account for populations from the entire range of species distributions – including populations that no longer exist. This thesis is organized in three manuscripts, which correspond to the three investigated groups: red muntjacs, Rusa deer and Asian rhinoceros.
Red muntjacs are a widely distributed species and occur in very different habitats. We found evidence for gene-flow among populations of different islands, indicative of their ability to utilize the available land corridors. However, we described also the existence of at least two dispersal barriers that created population differentiation within this group; one isolated Sundaic and Mainland populations and the second separated individuals from Sri Lanka.
Second, the two Rusa species investigated here revealed another consequence of the historical land connections. While the two species were monophyletic, we found evidence of hybridisation in Java, facilitated by the expansion of the widespread sambar, Rusa unicolor. Consequently, I found that all the individuals of Javan deer, R. timorensis which were transported to the east of Sundaland by humans, to be of hybrid descent.
In the last manuscript, we were able to include samples from the extinct mainland populations of both Sumatran and Javan rhinoceros. The results revealed a much higher genetic diversity of the historical populations than ever reported for the contemporaneous survivors. Their evolutionary histories revealed a close relationship to climatic events of the Pleistocene but, more importantly, point out the vast extent of genetic erosion within these two endangered species.
The specific phylogeographic history of the species showed some common patters of genetic differentiation that could be directly linked to the climatic and geological changes on the Sunda Shelf during the Pleistocene. However, by contrasting these results I discussed that the same geological events
did not always result in similar histories. One obvious example was the different permeability of the land corridors of Sundaland, as the ability of each species to utilize this newly available land was directly related to their specific ecological requirements. Taken together, these results have an important contribution to the general understanding of evolution in this biodiversity hotspot and the main drivers shaping the distribution of genetic diversity, but could also have important consequences for taxonomy and conservation of the three investigated groups.
Im Fokus der kumulativen Dissertationsschrift stehen Grundschullehrerinnen und Grundschullehrer in ihrer Rolle als Diagnostikerinnen und Diagnostiker. Exemplarisch werden mit der Einschätzung von Aufgabenschwierigkeiten und der Feststellung von Sprachförderbedarf zwei diagnostische Herausforderungen untersucht, die Lehrkräfte an Grundschulen bewältigen müssen.
Die vorliegende Arbeit umfasst drei empirische Teilstudien, die in einem Rahmentext integriert sind, in dem zunächst die theoretischen Hintergründe und die empirische Befundlage erläutert werden. Hierbei wird auf die diagnostische Kompetenz von Lehrkräften bzw. die Genauigkeit von Lehrerurteilen eingegangen. Ferner wird der Einsatz standardisierter Testinstrumente als wichtiger Bestandteil des diagnostischen Aufgabenfeldes von Lehrkräften charakterisiert. Außerdem werden zentrale Aspekte der Sprachdiagnostik in der Grundschule dargestellt.
In Teilstudie 1 (Hoffmann & Böhme, 2014b) wird der Frage nachgegangen, wie akkurat Grundschullehrerinnen und -lehrer die Schwierigkeit von Deutsch- und Mathematikaufgaben einschätzen. Darüber hinaus wird untersucht, welche Faktoren mit der Über- oder Unterschätzung der Schwierigkeit von Aufgaben zusammenhängen.
In Teilstudie 2 (Hoffmann & Böhme, 2017) wird geprüft, inwiefern die Klassifikationsgüte von Entschei¬dungen zum sprachlichen Förderbedarf mit den hierfür genutzten diagnostischen Informationsquellen kovariiert. Der Fokus liegt hierbei vor allem auf der Untersuchung von Effekten des Einsatzes von sprachdiagnostischen Verfahren.
Teilstudie 3 (Hoffmann, Böhme & Stanat, 2017) untersucht schließlich die Frage, welche diagnostischen Verfahren gegenwärtig bundesweit an den Grundschulen zur Feststellung sprachlichen Förderbedarfs genutzt werden und ob diese Verfahren etwa testtheoretischen Gütekriterien genügen.
Die zentralen Ergebnisse der Teilstudien werden im Rahmentext zusammen¬gefasst und studienübergreifend diskutiert. Hierbei wird auch auf methodische Stärken und Schwächen der drei Beiträge sowie auf Implikationen für die zukünftige Forschung und die schulische Praxis hingewiesen.
In der vorliegenden Arbeit konnten erfolgreich zwei unterschiedliche Hybridmaterialien (HM) über die Sol-Gel-Methode synthetisiert werden. Bei den HM handelt es sich um Monolithe mit einem Durchmesser von bis zu 4,5 cm. Das erste HM besteht aus Titandioxid und Bombyx mori Seide und wird als TS bezeichnet, während das zweite weniger Seide und zusätzlich Polyethylenoxid (PEO) enthält und daher als TPS abgekürzt wird. Einige der HM wurden nach der Synthese in eine wässrige Tetrachloridogoldsäure-Lösung getaucht, wodurch sich auf der Oberfläche Goldnanopartikel gebildet haben.
Die Materialien wurden mittels Elektronenmikroskopie, energiedispersiver Röntgenspektroskopie, Ramanspektroskopie sowie Röntgenpulverdiffraktometrie charakterisiert. Die Ergebnisse zeigen, dass beide HM aus etwa 5 nm großen, sphärischen Titandioxidnanopartikeln aufgebaut sind, die primär aus Anatas und zu einem geringen Anteil aus Brookit bestehen. Die Goldnanopartikel bei TPS_Au waren größer und polydisperser als die Goldnanopartikel auf dem TS_Au HM. Darüber hinaus sind die Goldnanopartikel im TS HM tiefer in das Material eingedrungen als beim TPS HM.
Die weiterführende Analyse der HM mittels Elementaranalyse und thermogravimetrischer Analyse ergab für TPS einen geringeren Anteil an organischen Bestandteilen im HM als für TS, obwohl für beide Synthesen die gleiche Masse an organischen Materialien eingesetzt wurde. Es wird vermutet, dass das PEO während der Synthese teilweise wieder aus dem Material herausgewaschen wird. Diese Theorie korreliert mit den Ergebnissen aus der Stickstoffsorption und der Quecksilberporosimetrie, die für das TPS HM eine höhere Oberfläche als für das TS HM anzeigten.
Die Variation einiger Syntheseparameter wie die Menge an Seide und PEO oder die Zusammensetzung der Titandioxidvorläuferlösung hatte einen großen Einfluss auf die synthetisierten HM. Während unterschiedliche Mengen an PEO die Größe des HM beeinflussten, konnte ohne Seide kein HM in einer ähnlichen Größe hergestellt werden. Die Bildung der HM wird stark von der Zusammensetzung der Titandioxidvorläuferlösung beeinflusst. Eine Veränderung führte daher nur selten zur Bildung eines homogenen HM.
Die in dieser Arbeit synthetisierten HM wurden als Photokatalysatoren für die Wasserspaltung und den Abbau von Methylenblau eingesetzt. Bei der photokatalytischen Wasserspaltung wurde zunächst der Einfluss unterschiedlicher Goldkonzentrationen beim TPS HM auf die Wasserstoffausbeute untersucht. Die besten Ergebnisse wurden bei einer Menge von 2,5 mg Tetrachloridogoldsäure erhalten. Darüber hinaus wurde gezeigt, dass mit dem TPS HM eine deutlich höhere Menge an Wasserstoff gewonnen werden konnte als mit dem TS HM. Die Ursachen für die schlechtere Aktivität werden in der geringeren spezifischen Oberfläche, der unterschiedlichen Porenstruktur, dem höheren Anteil an Seide und besonders in der geringeren Größe und höheren Eindringtiefe der Goldnanopartikel vermutet. Darüber hinaus konnte mit einem höheren UV-Anteil in der Lichtquelle sowie durch die Zugabe von Ethanol als Opferreagenz eine Zunahme der Wasserstoffausbeute erzielt werden.
Bei dem Methylenblauabbau wurde für beide HM zunächst nur eine Adsorption des Methylenblaus beobachtet. Nach der Zugabe von Wasserstoffperoxid konnte nach 8 h bereits eine fast vollständige Oxidation des Methylenblaus unter sichtbarem Licht beobachtet werden. Die Ursache für die etwas höhere Aktivität von TPS gegenüber TS wird in der unterschiedlichen Porenstruktur und dem höheren Anteil an Seide im TS HM vermutet. Insgesamt zeigen beide HM eine gute photokatalytische Aktivität für den Abbau von Methylenblau im Vergleich zu den erhaltenen Werten aus der Literatur.
To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing factors.
Given these research gaps, this work presents a general framework to systematically quantify the UHI effect based on an automated algorithm, whereby cities are defined as clusters of maximum spatial continuity on the basis of land use data, with their rural hinterland being defined analogously. By combining land use data with spatially explicit surface skin temperatures from satellites, the surface UHI intensity can be calculated in a consistent and robust manner. This facilitates monitoring, benchmarking, and categorizing UHI intensities for cities across scales. In light of this innovation, the relationship between city size and UHI intensity has been investigated, as well as the contributions of urban form indicators to the UHI intensity.
This work delivers manifold contributions to the understanding of the UHI, which have complemented and advanced a number of previous studies. Firstly, a log-linear relationship between surface UHI intensity and city size has been confirmed among the 5,000 European cities. The relationship can be extended to a log-logistic one, when taking a wider range of small-sized cities into account. Secondly, this work reveals a complex interplay between UHI intensity and urban form. City size is found to have the strongest influence on the UHI intensity, followed by the fractality and the anisometry. However, their relative contributions to the surface UHI intensity depict a pronounced regional heterogeneity, indicating the importance of considering spatial patterns of UHI while implementing UHI adaptation measures.
Lastly, this work presents a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves, implying a phase shift between the time series of UHI intensity and background temperatures. Combining satellite observation and urban boundary layer simulation, the seasonal variations of UHI are assessed from both screen and skin levels. Taking London as an example, this work ascribes the discrepancies between the seasonality observed at different levels mainly to the peculiarities of surface skin temperatures associated with the incoming solar radiation. In addition, the efforts in classifying cities according to their UHI characteristics highlight the important role of regional climates in determining the UHI.
This work serves as one of the first studies conducted to systematically and statistically scrutinize the UHI. The outcomes of this work are of particular relevance for the overall spatial planning and regulation at meso- and macro levels in order to harness the benefits of rapid urbanization, while proactively minimizing its ensuing thermal stress.
Underground coal gasification (UCG) has the potential to increase worldwide coal reserves by developing coal resources, currently not economically extractable by conventional mining methods. For that purpose, coal is combusted in situ to produce a high-calorific synthesis gas with different end-use options, including electricity generation as well as production of fuels and chemical feedstock. Apart from the high economic potentials, UCG may induce site‐specific environmental impacts, including ground surface subsidence and pollutant migration of UCG by-products into shallow freshwater aquifers. Sustainable and efficient UCG operation requires a thorough understanding of the coupled thermal, hydraulic and mechanical processes, occurring in the UCG reactor vicinity. The development and infrastructure costs of UCG trials are very high; therefore, numerical simulations of coupled processes in UCG are essential for the assessment of potential environmental impacts. Therefore, the aim of the present study is to assess UCG-induced permeability changes, potential hydraulic short circuit formation and non-isothermal multiphase fluid flow dynamics by means of coupled numerical simulations. Simulation results on permeability changes in the UCG reactor vicinity demonstrate that temperature-dependent thermo-mechanical parameters have to be considered in near-field assessments, only. Hence, far-field simulations do not become inaccurate, but benefit from increased computational efficiency when thermo-mechanical parameters are maintained constant. Simulations on potential hydraulic short circuit formation between single UCG reactors at regional-scale emphasize that geologic faults may induce hydraulic connections, and thus compromise efficient UCG operation. In this context, the steam jacket surrounding high-temperature UCG reactors plays a vital role in avoiding UCG by-products escaping into freshwater aquifers and in minimizing energy consumption by formation fluid evaporation. A steam jacket emerges in the close reactor vicinity due to phase transition of formation water and is a non-isothermal flow phenomenon. Considering this complex multiphase flow behavior, an innovative conceptual modeling approach, validated against field data, enables the quantification and prediction of UCG reactor water balances. The findings of this doctoral thesis provide an important basis for integration of thermo-hydro-mechanical simulations in UCG, required for the assessment and mitigation of its potential environmental impacts as well as optimization of its efficiency.
Contemporary multi-core processors are parallel systems that also provide shared memory for programs running on them. Both the increasing number of cores in so-called many-core systems and the still growing computational power of the cores demand for memory systems that are able to deliver high bandwidths. Caches are essential components to satisfy this requirement. Nevertheless, hardware-based cache coherence in many-core chips faces practical limits to provide both coherence and high memory bandwidths. In addition, a shift away from global coherence can be observed. As a result, alternative architectures and suitable programming models need to be investigated.
This thesis focuses on fast communication for non-cache-coherent many-core architectures. Experiments are conducted on the Single-Chip Cloud Computer (SCC), a non-cache-coherent many-core processor with 48 mesh-connected cores. Although originally designed for message passing, the results of this thesis show that shared memory can be efficiently used for one-sided communication on this kind of architecture. One-sided communication enables data exchanges between processes where the receiver is not required to know the details of the performed communication. In the notion of the Message Passing Interface (MPI) standard, this type of communication allows to access memory of remote processes. In order to support this communication scheme on non-cache-coherent architectures, both an efficient process synchronization and a communication scheme with software-managed cache coherence are designed and investigated.
The process synchronization realizes the concept of the general active target synchronization scheme from the MPI standard. An existing classification of implementation approaches is extended and used to identify an appropriate class for the non-cache-coherent shared memory platform. Based on this classification, existing implementations are surveyed in order to find beneficial concepts, which are then used to design a lightweight synchronization protocol for the SCC that uses shared memory and uncached memory accesses. The proposed scheme is not prone to process skew and also enables direct communication as soon as both communication partners are ready. Experimental results show very good scaling properties and up to five times lower synchronization latency compared to a tuned message-based MPI implementation for the SCC.
For the communication, SCOSCo, a shared memory approach with software-managed cache coherence, is presented. According requirements for the coherence that fulfill MPI's separate memory model are formulated, and a lightweight implementation exploiting SCC hard- and software features is developed. Despite a discovered malfunction in the SCC's memory subsystem, the experimental evaluation of the design reveals up to five times better bandwidths and nearly four times lower latencies in micro-benchmarks compared to the SCC-tuned but message-based MPI library. For application benchmarks, like a parallel 3D fast Fourier transform, the runtime share of communication can be reduced by a factor of up to five. In addition, this thesis postulates beneficial hardware concepts that would support software-managed coherence for one-sided communication on future non-cache-coherent architectures where coherence might be only available in local subdomains but not on a global processor level.
In der vorliegenden Dissertation werden lebensweltliche Erfahrungszusammenhänge in 128 Aufsätzen ausländischer Studierender, die oft auch als Bildungsausländer bezeichnet werden, und grundsätzliche Prozesse bei der Herausbildung sowie Veränderung kollektiver Zuschreibungen im Rahmen der sozialen Identitätsbildung hermeneutisch untersucht.
Mit Hilfe der nach der empirischen Methode der Grounded Theory kodierten Interpretationsergebnisse werden in der qualitativen Längsschnittstudie Vergleiche angestellt, sowohl fallintern als auch fallübergreifend, um Muster zu entdecken, Typologien zu konstruieren und die jeweiligen (kulturellen) Horizonte in den Aufsätzen zu verallgemeinern.
Neben der Grounded Theory bildet die Theorie der „alltäglichen Lebenswelt“ (Alfred Schütz) eine Basis der Herangehensweise an die Untersuchung der Aufsätze. In diesem Kontext wird ausgehend von der graduellen Unterteilung der Fremdheit in alltägliche, strukturelle und radikale Fremdheit sowie ausgehend von Goffmans Identitätskonzept der Frage nachgegangen, inwieweit sich in den untersuchten Texten die Bildung und Veränderung sozialer Identitäten feststellen lassen. Dabei werden Akkulturationsprozesse und Prozesse der Selbstidentifikation, bezüglich einer angenommenen Gemeinschaft, analysiert, die von kollektiven (kulturellen) Schemata bestimmt sind. In diesem Zusammenhang kann die vorliegende Dissertation zeigen, dass sich bestimmte kulturelle Schemata in der Auseinandersetzung mit dem vormals neuen Leben in Deutschland herausgebildet haben und bestimmte ältere Erfahrungen immer wieder zur Bestätigung dieser Bilder bzw. Erfahrungsschemata herangezogen und wie der Abdruck in Gestein fossiliert werden.