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The theory of atomic Boson-Fermion mixtures in the dilute limit beyond mean-field is considered in this thesis. Extending the formalism of quantum field theory we derived expressions for the quasi-particle excitation spectra, the ground state energy, and related quantities for a homogenous system to first order in the dilute gas parameter. In the framework of density functional theory we could carry over the previous results to inhomogeneous systems. We then determined to density distributions for various parameter values and identified three different phase regions: (i) a stable mixed regime, (ii) a phase separated regime, and (iii) a collapsed regime. We found a significant contribution of exchange-correlation effects in the latter case. Next, we determined the shift of the Bose-Einstein condensation temperature caused by Boson-Fermion interactions in a harmonic trap due to redistribution of the density profiles. We then considered Boson-Fermion mixtures in optical lattices. We calculated the criterion for stability against phase separation, identified the Mott-insulating and superfluid regimes both, analytically within a mean-field calculation, and numerically by virtue of a Gutzwiller Ansatz. We also found new frustrated ground states in the limit of very strong lattices. ----Anmerkung: Der Autor ist Träger des durch die Physikalische Gesellschaft zu Berlin vergebenen Carl-Ramsauer-Preises 2004 für die jeweils beste Dissertation der vier Universitäten Freie Universität Berlin, Humboldt-Universität zu Berlin, Technische Universität Berlin und Universität Potsdam.
Planets outside our solar system, so-called "exoplanets", can be detected with different methods, and currently more than 5000 exoplanets have been confirmed, according to NASA Exoplanet Archive. One major highlight of the studies on exoplanets in the past twenty years is the characterization of their atmospheres usingtransmission spectroscopy as the exoplanet transits. However, this characterization is a challenging process and sometimes there are reported discrepancies in the literature regarding the atmosphere of the same exoplanet. One potential reason for the observed atmospheric inconsistencies is called impact parameter degeneracy, and it is highly driven by the limb darkening effect of the host star. A brief introductionto those topics in presented in chapter 1, while the motivation and objectives of thiswork are described in chapter 2.The first goal is to clarify the origin of the transmission spectrum, which is anindicator of an exoplanet’s atmosphere; whether it is real or influenced by the impactparameter degeneracy. A second goal is to determine whether photometry from space using the Transiting Exoplanet Survey Satellite (TESS), could improve on the major parameters, which are responsible for the aforementioned degeneracy, of known exoplanetary systems. Three individual projects were conducted in order toaddress those goals. The three manuscripts are presented, in short, in the manuscriptoverview in chapter 3.More specifically, in chapter 4, the first manuscript is presented, which is an ex-tended investigation on the impact parameter degeneracy and its application onsynthetic transmission spectra. Evidently, the limb darkening of the host star isan important driver for this effect. It keeps the degeneracy persisting through different groups of exoplanets, based on the uncertainty of their impact parameter and on the type of their host star. The second goal, was addressed in the second and third manuscripts (chapter 5 and chapter 6 respectively). Using observationsfrom the TESS mission, two samples of exoplanets were studied; 10 transiting inflated hot-Jupiters and 43 transiting grazing systems. Potentially, the refinement or confirmation of their major system parameters’ measurements can assist in solving current or future discrepancies regarding their atmospheric characterization.In chapter 7 the conclusions of this work are discussed, while in chapter 8 itis proposed how TESS’s measurements can be able to discern between erroneousinterpretations of transmission spectra, especially on systems where the impact parameter degeneracy is likely not applicable.
Investigation of Sirtuin 3 overexpression as a genetic model of fasting in hypothalamic neurons
(2021)
Characterization of altered inflorescence architecture in Arabidopsis thaliana BG-5 x Kro-0 hybrid
(2018)
A reciprocal cross between two A. thaliana accessions, Kro-0 (Krotzenburg, Germany) and BG-5 (Seattle, USA), displays purple rosette leaves and dwarf bushy phenotype in F1 hybrids when grown at 17 °C and a parental-like phenotype when grown at 21 °C. This F1 temperature-dependent-dwarf-bushy phenotype is characterized by reduced growth of the primary stem together with an increased number of branches. The reduced stem growth was the strongest at the first internode. In addition, we found that a temperature switch from 21 °C to 17 °C induced the phenotype only before the formation of the first internode of the stem. Similarly, the F1 dwarf-bushy phenotype could not be reversed when plants were shifted from 17 °C to 21 °C after the first internode was formed. Metabolic analysis showed that the F1 phenotype was associated with a significant upregulation of anthocyanin(s), kaempferol(s), salicylic acid, jasmonic acid and abscisic acid. As it has been previously shown that the dwarf-bushy phenotype is linked to two loci, one on chromosome 2 from Kro-0 and one on chromosome 3 from BG-5, an artificial micro-RNA approach was used to investigate the necessary genes on these intervals. From the results obtained, it was found that two genes, AT2G14120 that encodes for a DYNAMIN RELATED PROTEIN3B and AT2G14100 that encodes a member of the Cytochrome P450 family protein CYP705A13, were necessary for the appearance of the F1 phenotype on chromosome 2. It was also discovered that AT3G61035 that encodes for another cytochrome P450 family protein CYP705A13 and AT3G60840 that encodes for a MICROTUBULE-ASSOCIATED PROTEIN65-4 on chromosome 3 were both necessary for the induction of the F1 phenotype. To prove the causality of these genes, genomic constructs of the Kro-0 candidate genes on chromosome 2 were transferred to BG-5 and genomic constructs of the chromosome 3 candidate genes from BG-5 were transferred to Kro-0. The T1 lines showed that these genes are not sufficient alone to induce the phenotype. In addition to the F1 phenotype, more severe phenotypes were observed in the F2 generations that were grouped into five different phenotypic classes. Whilst seed yield was comparable between F1 hybrids and parental lines, three phenotypic classes in the F2 generation exhibited hybrid breakdown in the form of reproductive failure. This F2 hybrid breakdown was less sensitive to temperature and showed a dose-dependent effect of the loci involved in F1 phenotype. The severest class of hybrid breakdown phenotypes was observed only in the population of backcross with the parent Kro-0, which indicates a stronger contribution of the BG-5 allele when compared to the Kro-0 allele on the hybrid breakdown phenotypes. Overall, the findings of my thesis provide a further understanding of the genetic and metabolic factors underlying altered shoot architecture in hybrid dysfunction.
Classification, prediction and evaluation of graph neural networks on online social media platforms
(2024)
The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks.
This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes.
Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN.
Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse.
Bacteria are one of the most widespread kinds of microorganisms that play essential roles in many biological and ecological processes. Bacteria live either as independent individuals or in organized communities. At the level of single cells, interactions between bacteria, their neighbors, and the surrounding physical and chemical environment are the foundations of microbial processes. Modern microscopy imaging techniques provide attractive and promising means to study the impact of these interactions on the dynamics of bacteria. The aim of this dissertation is to deepen our understanding four fundamental bacterial processes – single-cell motility, chemotaxis, bacterial interactions with environmental constraints, and their communication with neighbors – through a live cell imaging technique. By exploring these processes, we expanded our knowledge on so far unexplained mechanisms of bacterial interactions.
Firstly, we studied the motility of the soil bacterium Pseudomonas putida (P. putida), which swims through flagella propulsion, and has a complex, multi-mode swimming tactic. It was recently reported that P. putida exhibits several distinct swimming modes – the flagella can push and pull the cell body or wrap around it. Using a new combined phase-contrast and fluorescence imaging set-up, the swimming mode (push, pull, or wrapped) of each run phase was automatically recorded, which provided the full swimming statistics of the multi-mode swimmer. Furthermore, the investigation of cell interactions with a solid boundary illustrated an asymmetry for the different swimming modes; in contrast to the push and pull modes, the curvature of runs in wrapped mode was not affected by the solid boundary. This finding suggested that having a multi-mode swimming strategy may provide further versatility to react to environmental constraints.
Then we determined how P. putida navigates toward chemoattractants, i.e. its chemotaxis strategies. We found that individual run modes show distinct chemotactic responses in nutrition gradients. In particular, P. putida cells exhibited an asymmetry in their chemotactic responsiveness; the wrapped mode (slow swimming mode) was affected by the chemoattractant, whereas the push mode (fast swimming mode) was not. These results can be seen as a starting point to understand more complex chemotaxis strategies of multi-mode swimmers going beyond the well-known paradigm of Escherichia coli, that exhibits only one swimming mode.
Finally we considered the cell dynamics in a dense population. Besides physical interactions with their neighbors, cells communicate their activities and orchestrate their population behaviors via quorum-sensing. Molecules that are secreted to the surrounding by the bacterial cells, act as signals and regulate the cell population behaviour. We studied P. putida’s motility in a dense population by exposing the cells to environments with different concentrations of chemical signals. We found that higher amounts of chemical signals in the surrounding influenced the single-cell behaviourr, suggesting that cell-cell communications may also affect the flagellar dynamics.
In summary, this dissertation studies the dynamics of a bacterium with a multi-mode swimming tactic and how it is affected by the surrounding environment using microscopy imaging. The detailed description of the bacterial motility in fundamental bacterial processes can provide new insights into the ecology of microorganisms.
The topic of synchronization forms a link between nonlinear dynamics and neuroscience. On the one hand, neurobiological research has shown that the synchronization of neuronal activity is an essential aspect of the working principle of the brain. On the other hand, recent advances in the physical theory have led to the discovery of the phenomenon of phase synchronization. A method of data analysis that is motivated by this finding - phase synchronization analysis - has already been successfully applied to empirical data. The present doctoral thesis ties up to these converging lines of research. Its subject are methodical contributions to the further development of phase synchronization analysis, as well as its application to event-related potentials, a form of EEG data that is especially important in the cognitive sciences. The methodical contributions of this work consist firstly in a number of specialized statistical tests for a difference in the synchronization strength in two different states of a system of two oscillators. Secondly, in regard of the many-channel character of EEG data an approach to multivariate phase synchronization analysis is presented. For the empirical investigation of neuronal synchronization a classic experiment on language processing was replicated, comparing the effect of a semantic violation in a sentence context with that of the manipulation of physical stimulus properties (font color). Here phase synchronization analysis detects a decrease of global synchronization for the semantic violation as well as an increase for the physical manipulation. In the latter case, by means of the multivariate analysis the global synchronization effect can be traced back to an interaction of symmetrically located brain areas.<BR> The findings presented show that the method of phase synchronization analysis motivated by physics is able to provide a relevant contribution to the investigation of event-related potentials in the cognitive sciences.
The controlled dosage of substances from a device to its environment, such as a tissue or an organ in medical applications or a reactor, room, machinery or ecosystem in technical, should ideally match the requirements of the applications, e.g. in terms of the time point at which the cargo is released. On-demand dosage systems may enable such a desired release pattern, if the device contain suitable features that can translate external signals into a release function. This study is motivated by the opportunities arising from microsystems capable of an on-demand release and the contributions that geometrical design may have in realizing such features. The goals of this work included the design, fabrication, characterization and experimental proof-of-concept of geometry-assisted triggerable dosing effect (a) with a sequential dosing release and (b) in a self-sufficient dosage system. Structure-function relationships were addressed on the molecular, morphological and, with a particular attention, the device design level, which is on the micrometer scale. Models and/or computational tools were used to screen the parameter space and provide guidance for experiments.
In this thesis, I examine different A-bar movement dependencies in Igbo, a Benue-Congo language spoken in southern Nigeria. Movement dependencies are found in constructions where an element is moved to the left edge of the clause to express information-structural categories such as in questions, relativization and focus. I show that these constructions in Igbo are very uniform from a syntactic point of view. The constructions are built on two basic fronting operations: relativization and focus movement, and are biclausal. I further investigate several morphophonological effects that are found in these A-bar constructions. I propose that these effects are reflexes of movement that are triggered when an element is moved overtly in relativization or focus. This proposal helps to explain the tone patterns that have previously been assumed to be a property of relative clauses. The thesis adds to the growing body of tonal reflexes of A-bar movement reported for a few African languages. The thesis also provides an insight into the complementizer domain (C-domain) of Igbo.
The Indian summer monsoon (ISM) is one of the largest climate systems on earth and impacts the livelihood of nearly 40% of the world’s population. Despite dedicated efforts, a comprehensive picture of monsoon variability has proved elusive largely due to the absence of long term high resolution records, spatial inhomogeneity of the monsoon precipitation, and the complex forcing mechanisms (solar insolation, internal teleconnections for e.g., El Niño-Southern Oscillation, tropical-midlatitude interactions). My work aims to improve the understanding of monsoon variability through generation of long term high resolution palaeoclimate data from climatically sensitive regions in the ISM and westerlies domain. To achieve this aim I have (i) identified proxies (sedimentological, geochemical, isotopic, and mineralogical) that are sensitive to environmental changes; (ii) used the identified proxies to generate long term palaeoclimate data from two climatically sensitive regions, one in NW Himalayas (transitional westerlies and ISM domain in the Spiti valley and one in the core monsoon zone (Lonar lake) in central India); (iii) undertaken a regional overview to generate “snapshots” of selected time slices; and (iv) interpreted the spatial precipitation anomalies in terms of those caused by modern teleconnections. This approach must be considered only as the first step towards identifying the past teleconnections as the boundary conditions in the past were significantly different from today and would have impacted the precipitation anomalies. As the Spiti valley is located in the in the active tectonic orogen of Himalayas, it was essential to understand the role of regional tectonics to make valid interpretations of catchment erosion and detrital influx into the lake. My approach of using integrated structural/morphometric and geomorphic signatures provided clear evidence for active tectonics in this area and demonstrated the suitability of these lacustrine sediments as palaleoseismic archives. The investigations on the lacustrine outcrops in Spiti valley also provided information on changes in seasonality of precipitation and occurrence of frequent and intense periods (ca. 6.8-6.1 cal ka BP) of detrital influx indicating extreme hydrological events in the past. Regional comparison for this time slice indicates a possible extended “break-monsoon like” mode for the monsoon that favors enhanced precipitation over the Tibetan plateau, Himalayas and their foothills. My studies on surface sediments from Lonar lake helped to identify environmentally sensitive proxies which could also be used to interpret palaeodata obtained from a ca. 10m long core raised from the lake in 2008. The core encompasses the entire Holocene and is the first well dated (by 14C) archive from the core monsoon zone of central India. My identification of authigenic evaporite gaylussite crystals within the core sediments provided evidence of exceptionally drier conditions during 4.7-3.9 and 2.0-0.5 cal ka BP. Additionally, isotopic investigations on these crystals provided information on eutrophication, stratification, and carbon cycling processes in the lake.
The African weakly electric fish genus Campylomormyrus includes 15 described species mostly native to the Congo River and its tributaries. They are considered sympatric species, because their distribution area overlaps. These species generate species-specific electric organ discharges (EODs) varying in waveform characteristics, including duration, polarity, and phase number. They exhibit also pronounced divergence in their snout, i.e. the length, thickness, and curvature. The diversifications in these two phenotypical traits (EOD and snout) have been proposed as key factors promoting adaptive radiation in Campylomormyrus. The role of EODs as a pre-zygotic isolation mechanism driving sympatric speciation by promoting assortative mating has been examined using behavioral, genetical, and histological approaches. However, the evolutionary effects of the snout morphology and its link to species divergence have not been closely examined. Hence, the main objective of this study is to investigate the effect of snout morphology diversification and its correlated EOD to better understand their sympatric speciation and evolutionary drivers. Moreover, I aim to utilize the intragenus and intergenus hybrids of Campylomormyrus to better understand trait divergence as well as underlying molecular/genetic mechanisms involved in the radiation scenario. To this end, I utilized three different approaches: feeding behavior analysis, diet assessment, and geometric morphometrics analysis. I performed feeding behavior experiments to evaluate the concept of the phenotype-environment correlation by testing whether Campylomormyrus species show substrate preferences. The behavioral experiments showed that the short snout species exhibits preference to sandy substrate, the long snout species prefers a stone substrate, and the species with intermediate snout size does not exhibit any substrate preference. The experiments suggest that the diverse feeding apparatus in the genus Campylomormyrus may have evolved in adaptation to their microhabitats. I also performed diet assessments of sympatric Campylomormyrus species and a sister genus species (Gnathonemus petersii) with markedly different snout morphologies and EOD using NGS-based DNA metabarcoding of their stomach contents. The diet of each species was documented showing that aquatic insects such as dipterans, coleopterans and trichopterans represent the major diet component. The results showed also that all species are able to exploit diverse food niches in their habitats. However, comparing the diet overlap indices showed that different snout morphologies and the associated divergence in the EOD translated into different prey spectra. These results further support the idea that the EOD could be a ‘magic trait’ triggering both adaptation and reproductive isolation. Geometric morphometrics method was also used to compare the phenotypical shape traits of the F1 intragenus (Campylomormyrus) and intergenus (Campylomormyrus species and Gnathonemus petersii) hybrids relative to their parents. The hybrids of these species were well separated based on the morphological traits, however the hybrid phenotypic traits were closer to the short-snouted species. In addition, the likelihood that the short snout expressed in the hybrids increases with increasing the genetic distance of the parental species. The results confirmed that additive effects produce intermediate phenotypes in F1-hybrids. It seems, therefore, that morphological shape traits in hybrids, unlike the physiological traits, were not expressed straightforward.
In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces.
In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius.
Each version of the clustering algorithm has its own use case that we show in the thesis.
In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data.
The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.
The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
This text is a contribution to the research on the worldwide success of evangelical Christianity and offers a new perspective on the relationship between late modern capitalism and evangelicalism. For this purpose, the utilization of affect and emotion in evangelicalism towards the mobilization of its members will be examined in order to find out what similarities to their employment in late modern capitalism can be found. Different examples from within the evangelical spectrum will be analyzed as affective economies in order to elaborate how affective mobilization is crucial for evangelicalism’s worldwide success. Pivotal point of this text is the exploration of how evangelicalism is able to activate the voluntary commitment of its members, financiers, and missionaries. Gathered here are examples where both spheres—evangelicalism and late modern capitalism—overlap and reciprocate, followed by a theoretical exploration of how the findings presented support a view of evangelicalism as an inner-worldly narcissism that contributes to an assumed re-enchantment of the world.
Galaxies are among the most complex systems that can currently be modelled with a computer. A realistic simulation must take into account cosmology and gravitation as well as effects of plasma, nuclear, and particle physics that occur on very different time, length, and energy scales. The Milky Way is the ideal test bench for such simulations, because we can observe millions of its individual stars whose kinematics and chemical composition are records of the evolution of our Galaxy. Thanks to the advent of multi-object spectroscopic surveys, we can systematically study stellar populations in a much larger volume of the Milky Way. While the wealth of new data will certainly revolutionise our picture of the formation and evolution of our Galaxy and galaxies in general, the big-data era of Galactic astronomy also confronts us with new observational, theoretical, and computational challenges.
This thesis aims at finding new observational constraints to test Milky-Way models, primarily based on infra-red spectroscopy from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) and asteroseismic data from the CoRoT mission. We compare our findings with chemical-evolution models and more sophisticated chemodynamical simulations. In particular we use the new powerful technique of combining asteroseismic and spectroscopic observations that allows us to test the time dimension of such models for the first time. With CoRoT and APOGEE (CoRoGEE) we can infer much more precise ages for distant field red-giant stars, opening up a new window for Galactic archaeology.
Another important aspect of this work is the forward-simulation approach that we pursued when interpreting these complex datasets and comparing them to chemodynamical models.
The first part of the thesis contains the first chemodynamical study conducted with the APOGEE survey. Our sample comprises more than 20,000 red-giant stars located within 6 kpc from the Sun, and thus greatly enlarges the Galactic volume covered with high-resolution spectroscopic observations. Because APOGEE is much less affected by interstellar dust extinction, the sample covers the disc regions very close to the Galactic plane that are typically avoided by optical surveys. This allows us to investigate the chemo-kinematic properties of the Milky Way's thin disc outside the solar vicinity. We measure, for the first time with high-resolution data, the radial metallicity gradient of the disc as a function of distance from the Galactic plane, demonstrating that the gradient flattens and even changes its sign for mid-plane distances greater than 1 kpc.
Furthermore, we detect a gap between the high- and low-[$\alpha$/Fe] sequences in the chemical-abundance diagram (associated with the thin and thick disc) that unlike in previous surveys can hardly be explained by selection effects. Using 6D kinematic information, we also present chemical-abundance diagrams cleaned from stars on kinematically hot orbits. The data allow us to confirm without doubt that the scale length of the (chemically-defined) thick disc is significantly shorter than that of the thin disc.
In the second part, we present our results of the first combination of asteroseismic and spectroscopic data in the context of Galactic Archaeology. We analyse APOGEE follow-up observations of 606 solar-like oscillating red giants in two CoRoT fields close to the Galactic plane. These stars cover a large radial range of the Galactic disc (4.5 kpc $\lesssim R_{\rm Gal}\lesssim15$ kpc) and a large age baseline (0.5 Gyr $\lesssim \tau\lesssim$ 13 Gyr), allowing us to study the age- and radius-dependence of the [$\alpha$/Fe] vs. [Fe/H] distributions. We find that the age distribution of the high-[$\alpha$/Fe] sequence appears to be broader than expected from a monolithically-formed old thick disc that stopped to form stars 10 Gyr ago. In particular, we discover a significant population of apparently young, [$\alpha$/Fe]-rich stars in the CoRoGEE data whose existence cannot be explained by standard chemical-evolution models. These peculiar stars are much more abundant in the inner CoRoT field LRc01 than in the outer-disc field LRc01, suggesting that at least part of this population has a chemical-evolution rather than a stellar-evolution origin, possibly due to a peculiar chemical-enrichment history of the inner disc. We also find that strong radial migration is needed to explain the abundance of super-metal-rich stars in the outer disc.
Finally, we use the CoRoGEE sample to study the time evolution of the radial metallicity gradient in the thin disc, an observable that has been the subject of observational and theoretical debate for more than 20 years. By dividing the CoRoGEE dataset into six age bins, performing a careful statistical analysis of the radial [Fe/H], [O/H], and [Mg/Fe] distributions, and accounting for the biases introduced by the observation strategy, we obtain reliable gradient measurements. The slope of the radial [Fe/H] gradient of the young red-giant population ($-0.058\pm0.008$ [stat.] $\pm0.003$ [syst.] dex/kpc) is consistent with recent Cepheid data. For the age range of $1-4$ Gyr, the gradient steepens slightly ($-0.066\pm0.007\pm0.002$ dex/kpc), before flattening again to reach a value of $\sim-0.03$ dex/kpc for stars with ages between 6 and 10 Gyr. This age dependence of the [Fe/H] gradient can be explained by a nearly constant negative [Fe/H] gradient of $\sim-0.07$ dex/kpc in the interstellar medium over the past 10 Gyr, together with stellar heating and migration. Radial migration also offers a new explanation for the puzzling observation that intermediate-age open clusters in the solar vicinity (unlike field stars) tend to have higher metallicities than their younger counterparts. We suggest that non-migrating clusters are more likely to be kinematically disrupted, which creates a bias towards high-metallicity migrators from the inner disc and may even steepen the intermediate-age cluster abundance gradient.
Adsorption layers of soluble surfactants enable and govern a variety of phenomena in surface and colloidal sciences, such as foams. The ability of a surfactant solution to form wet foam lamellae is governed by the surface dilatational rheology. Only systems having a non-vanishing imaginary part in their surface dilatational modulus, E, are able to form wet foams. The aim of this thesis is to illuminate the dissipative processes that give rise to the imaginary part of the modulus. There are two controversial models discussed in the literature. The reorientation model assumes that the surfactants adsorb in two distinct states, differing in their orientation. This model is able to describe the frequency dependence of the modulus E. However, it assumes reorientation dynamics in the millisecond time regime. In order to assess this model, we designed a SHG pump-probe experiment that addresses the orientation dynamics. Results obtained reveal that the orientation dynamics occur in the picosecond time regime, being in strong contradiction with the two states model. The second model regards the interface as an interphase. The adsorption layer consists of a topmost monolayer and an adjacent sublayer. The dissipative process is due to the molecular exchange between both layers. The assessment of this model required the design of an experiment that discriminates between the surface compositional term and the sublayer contribution. Such an experiment has been successfully designed and results on elastic and viscoelastic surfactant provided evidence for the correctness of the model. Because of its inherent surface specificity, surface SHG is a powerful analytical tool that can be used to gain information on molecular dynamics and reorganization of soluble surfactants. They are central elements of both experiments. However, they impose several structural elements of the model system. During the course of this thesis, a proper model system has been identified and characterized. The combination of several linear and nonlinear optical techniques, allowed for a detailed picture of the interfacial architecture of these surfactants.
With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation.
Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly.
The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design.
As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation.
The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments.
A systems biological approach towards the molecular basis of heterosis in Arabidopsis thaliana
(2011)
Heterosis is defined as the superiority in performance of heterozygous genotypes compared to their corresponding genetically different homozygous parents. This phenomenon is already known since the beginning of the last century and it has been widely used in plant breeding, but the underlying genetic and molecular mechanisms are not well understood. In this work, a systems biological approach based on molecular network structures is proposed to contribute to the understanding of heterosis. Hybrids are likely to contain additional regulatory possibilities compared to their homozygous parents and, therefore, they may be able to correctly respond to a higher number of environmental challenges, which leads to a higher adaptability and, thus, the heterosis phenomenon. In the network hypothesis for heterosis, presented in this work, more regulatory interactions are expected in the molecular networks of the hybrids compared to the homozygous parents. Partial correlations were used to assess this difference in the global interaction structure of regulatory networks between the hybrids and the homozygous genotypes. This network hypothesis for heterosis was tested on metabolite profiles as well as gene expression data of the two parental Arabidopsis thaliana accessions C24 and Col-0 and their reciprocal crosses. These plants are known to show a heterosis effect in their biomass phenotype. The hypothesis was confirmed for mid-parent and best-parent heterosis for either hybrid of our experimental metabolite as well as gene expression data. It was shown that this result is influenced by the used cutoffs during the analyses. Too strict filtering resulted in sets of metabolites and genes for which the network hypothesis for heterosis does not hold true for either hybrid regarding mid-parent as well as best-parent heterosis. In an over-representation analysis, the genes that show the largest heterosis effects according to our network hypothesis were compared to genes of heterotic quantitative trait loci (QTL) regions. Separately for either hybrid regarding mid-parent as well as best-parent heterosis, a significantly larger overlap between the resulting gene lists of the two different approaches towards biomass heterosis was detected than expected by chance. This suggests that each heterotic QTL region contains many genes influencing biomass heterosis in the early development of Arabidopsis thaliana. Furthermore, this integrative analysis led to a confinement and an increased confidence in the group of candidate genes for biomass heterosis in Arabidopsis thaliana identified by both approaches.
Non-mycorrhizal fungal endophytes are able to colonize internally roots without causing visible disease symptoms establishing neutral or mutualistic associations with plants. These fungi known as non-clavicipitaceous endophytes have a broad host range of monocot and eudicot plants and are highly diverse. Some of them promote plant growth and confer increased abiotic-stress tolerance and disease resistance. According to such possible effects on host plants, it was aimed to isolate and to characterize native fungal root endophytes from tomato (Lycopersicon esculentum Mill.) and to analyze their effects on plant development, plant resistance and fruit yield and quality together with the model endophyte Piriformospora indica. Fifty one new fungal strains were isolated from desinfected tomato roots of four different crop sites in Colombia. These isolates were roughly characterized and fourteen potential endophytes were further analyzed concerning their taxonomy, their root colonization capacity and their impact on plant growth. Sequencing of the ITS region from the ribosomal RNA gene cluster and in-depth morphological characterisation revealed that they correspond to different phylogenetic groups among the phylum Ascomycota. Nine different morphotypes were described including six dark septate endophytes (DSE) that did not correspond to the Phialocephala group. Detailed confocal microscopy analysis showed various colonization patterns of the endophytes inside the roots ranging from epidermal penetration to hyphal growth through the cortex. Tomato pot experiments under glass house conditions showed that they differentially affect plant growth depending on colonization time and inoculum concentration. Three new isolates (two unknown fungal endophyte DSE48, DSE49 and one identified as Leptodontidium orchidicola) with neutral or positiv effects were selected and tested in several experiments for their influence on vegetative growth, fruit yield and quality and their ability to diminish the impact of the pathogen Verticillium dahliae on tomato plants. Although plant growth promotion by all three fungi was observed in young plants, vegetative growth parameters were not affected after 22 weeks of cultivation except a reproducible increase of root diameter by the endophyte DSE49. Additionally, L. orchidicola increased biomass and glucose content of tomato fruits, but only at an early date of harvest and at a certain level of root colonization. Concerning bioprotective effects, the endophytes DSE49 and L. orchidicola decreased significantly disease symptoms caused by the pathogen V. dahliae, but only at a low dosis of the pathogen. In order to analyze, if the model root endophytic fungus Piriformospora indica could be suitable for application in production systems, its impact on tomato was evaluated. Similarly to the new fungal isolates, significant differences for vegetative growth parameters were only observable in young plants and, but protection against V. dahliae could be seen in one experiment also at high dosage of the pathogen. As the DSE L. orchidicola, P. indica increased the number and biomass of marketable tomatoes only at the beginning of fruit setting, but this did not lead to a significant higher total yield. If the effects on growth are due to a better nutrition of the plant with mineral element was analyzed in barley in comparison to the arbuscular mycorrhizal fungus Glomus mosseae. While the mycorrhizal fungus increased nitrogen and phosphate uptake of the plant, no such effect was observed for P. indica. In summary this work shows that many different fungal endophytes can be also isolated from roots of crops and, that these isolates can have positive effects on early plant development. This does, however, not lead to an increase in total yield or in improvement of fruit quality of tomatoes under greenhouse conditions.
Carbohydrate recognition is a ubiquitous principle underlying many fundamental biological processes like fertilization, embryogenesis and viral infections. But how carbohydrate specificity and affinity induce a molecular event is not well understood. One of these examples is bacteriophage P22 that binds and infects three distinct Salmonella enterica (S.) hosts. It recognizes and depolymerizes repetitive carbohydrate structures of O antigen in its host´s outer membrane lipopolysaccharide molecule. This is mediated by tailspikes, mainly β helical appendages on phage P22 short non contractile tail apparatus (podovirus). The O antigen of all three Salmonella enterica hosts is built from tetrasaccharide repeating units consisting of an identical main chain with a distinguished 3,6 dideoxyhexose substituent that is crucial for P22 tailspike recognition: tyvelose in S. Enteritidis, abequose in S. Typhimurium and paratose in S. Paratyphi. In the first study the complexes of P22 tailspike with its host’s O antigen octasaccharide were characterized. S. Paratyphi octasaccharide binds less tightly (ΔΔG≈7 kJ/mol) to the tailspike than the other two hosts. Crystal structure analysis of P22 tailspike co crystallized with S. Paratyphi octasaccharides revealed different interactions than those observed before in tailspike complexes with S. Enteritidis and S. Typhimurium octasaccharides. These different interactions occur due to a structural rearrangement in the S. Paratyphi octasaccharide. It results in an unfavorable glycosidic bond Φ/Ψ angle combination that also had occurred when the S. Paratyphi octasaccharide conformation was analyzed in an aprotic environment. Contributions of individual protein surface contacts to binding affinity were analyzed showing that conserved structural waters mediate specific recognition of all three different Salmonella host O antigens. Although different O antigen structures possess distinct binding behavior on the tailspike surface, all are recognized and infected by phage P22. Hence, in a second study, binding measurements revealed that multivalent O antigen was able to bind with high avidity to P22 tailspike. Dissociation rates of the polymer were three times slower than for an octasaccharide fragment pointing towards high affinity for O antigen polysaccharide. Furthermore, when phage P22 was incubated with lipopolysaccharide aggregates before plating on S. Typhimurium cells, P22 infectivity became significantly reduced. Therefore, in a third study, the function of carbohydrate recognition on the infection process was characterized. It was shown that large S. Typhimurium lipopolysaccharide aggregates triggered DNA release from the phage capsid in vitro. This provides evidence that phage P22 does not use a second receptor on the Salmonella surface for infection. P22 tailspike binding and cleavage activity modulate DNA egress from the phage capsid. DNA release occurred more slowly when the phage possessed mutant tailspikes with less hydrolytic activity and was not induced if lipopolysaccharides contained tailspike shortened O antigen polymer. Furthermore, the onset of DNA release was delayed by tailspikes with reduced binding affinity. The results suggest a model for P22 infection induced by carbohydrate recognition: tailspikes position the phage on Salmonella enterica and their hydrolytic activity forces a central structural protein of the phage assembly, the plug protein, onto the host´s membrane surface. Upon membrane contact, a conformational change has to occur in the assembly to eject DNA and pilot proteins from the phage to establish infection. Earlier studies had investigated DNA ejection in vitro solely for viruses with long non contractile tails (siphovirus) recognizing protein receptors. Podovirus P22 in this work was therefore the first example for a short tailed phage with an LPS recognition organelle that can trigger DNA ejection in vitro. However, O antigen binding and cleaving tailspikes are widely distributed in the phage biosphere, for example in siphovirus 9NA. Crystal structure analysis of 9NA tailspike revealed a complete similar fold to P22 tailspike although they only share 36 % sequence identity. Moreover, 9NA tailspike possesses similar enzyme activity towards S. Typhimurium O antigen within conserved amino acids. These are responsible for a DNA ejection process from siphovirus 9NA triggered by lipopolysaccharide aggregates. 9NA expelled its DNA 30 times faster than podovirus P22 although the associated conformational change is controlled with a similar high activation barrier. The difference in DNA ejection velocity mirrors different tail morphologies and their efficiency to translate a carbohydrate recognition signal into action.
Potato is the 4th most important food crop in the world. Especially in tropical and sub-tropical potato production, drought is a yield limiting factor. Potato is sensitive to water stress. Potato yield loss under water stress could be reduced by using tolerant varieties and adjusted agronomic practices. Direct selection for yield under water-stressed conditions requires long selection cycles. Thus, identification of markers for marker-assisted selection may speed up breeding. The objective of this thesis is to identify morphological markers for drought tolerance by continuously monitoring plant growth and canopy temperature with an automatic phenotyping system.
The phenotyping was performed in drought-stress experiments that were conducted in population A with 64 genotypes and population B with 21 genotypes in the screenhouse in 2015 and 2016 (population A) and in 2017 and 2018 (population B). Drought tolerance was quantified as deviation of the relative tuber starch yield from the experimental median (DRYM) and parent median (DRYMp). Relative tuber starch yield is starch yield under drought stress relative to the average starch yield of the respective cultivar under control conditions in the same experiment. The specific DRYM value was calculated based on the yield data of the same experiment or the global DRYM that was calculated from yield data derived from data combined over yeas of respective population or across multiple experiments including VALDIS and TROST experiments (2011-2016).
Analysis of variance found a significant effect of genotype on DRYM indicating that the tolerance variation required for marker identification was given in both populations.
Canopy growth was monitored continuously six times a day over five to ten weeks by a laser scanner system and yielded information on leaf area, plant height and leaf angle for population A and additionally on leaf inclination and light penetration depth for population B. Canopy temperature was measured 48 times a day over six to seven weeks by infrared thermometry in population B. From the continuous IRT surface temperature data set, the canopy temperature for each plant was selected by matching the time stamp of the IRT data with laser scanner data.
Mean, maximum, range and growth rate values were calculated from continuous laser scanner measurements of respective canopy parameters. Among the canopy parameters, the maximum and mean values in long-term stress conditions showed better correlation with DRYM values calculated in the same experiment than growth rate and diurnal range values. Therefore, drought tolerance index prediction was done from maximum and mean values of canopy parameters.
The tolerance index in specific experiment condition was linearly predicted by simple regression model from different single canopy parameters under long-term stress condition in population A (2016) and population B (2017 and 2018). Among the canopy parameters maximum light penetration depth (2017), mean leaf angle (2017, 2018, and 2016), mean leaf inclination or mean canopy temperature depression (2017 and 2018), maximum plant height (2017) were selected as tolerance predictors. However, no single parameters were sufficient to predict DRYM. Therefore, several independent parameters were integrated in a multiple regression model.
In multiple regression model, specific experiment DRYM values in population A was predicted from mean leaf angle (2016). In population B, specific tolerance could be predicted from maximum light penetration depth and mean leaf inclination (2017) and mean leaf inclination (2018) or mean canopy temperature depression and mean leaf angle (2018).
In data combined over season of population A, the multiple linear regression model selected maximum plant height and mean leaf angle as tolerance predictor. In Population B, mean leaf inclination was selected as tolerance predictor. However, in population A, the variation explained by the final model was too low.
Furthermore, the average tolerances respective to parent median (2011-2018) across FGH plants or all plants (FGH and field) were predicted from maximum plant height (population A) and maximum plant height and mean leaf inclination (population B). Altogether, canopy parameters could be used as markers for drought tolerance. Therefore, water stress breeding in potato could be speed up through using leaf inclination, light penetration depth, plant height and canopy temperature depression as markers for drought tolerance, especially in long-term stress conditions.
Subsea permafrost is perennially cryotic earth material that lies offshore. Most submarine permafrost is relict terrestrial permafrost beneath the Arctic shelf seas, was inundated after the last glaciation, and has been warming and thawing ever since. It is a reservoir and confining layer for gas hydrates and has the potential to release greenhouse gases and affect global climate change. Furthermore, subsea permafrost thaw destabilizes coastal infrastructure. While numerous studies focus on its distribution and rate of thaw over glacial timescales, these studies have not been brought together and examined in their entirety to assess rates of thaw beneath the Arctic Ocean. In addition, there is still a large gap in our understanding of sub-aquatic permafrost processes on finer spatial and temporal scales. The degradation rate of subsea permafrost is influenced by the initial conditions upon submergence. Terrestrial permafrost that has already undergone warming, partial thawing or loss of ground ice may react differently to inundation by seawater compared to previously undisturbed ice-rich permafrost. Heat conduction models are sufficient to model the thaw of thick subsea permafrost from the bottom, but few studies have included salt diffusion for top-down chemical degradation in shallow waters characterized by mean annual cryotic conditions on the seabed. Simulating salt transport is critical for assessing degradation rates for recently inundated permafrost, which may accelerate in response to warming shelf waters, a lengthening open water season, and faster coastal erosion rates. In the nearshore zone, degradation rates are also controlled by seasonal processes like bedfast ice, brine injection, seasonal freezing under floating ice conditions and warm freshwater discharge from large rivers. The interplay of all these variables is complex and needs further research. To fill this knowledge gap, this thesis investigates sub-aquatic permafrost along the southern coast of the Bykovsky Peninsula in eastern Siberia. Sediment cores and ground temperature profiles were collected at a freshwater thermokarst lake and two thermokarst lagoons in 2017. At this site, the coastline is retreating, and seawater is inundating various types of permafrost: sections of ice-rich Pleistocene permafrost (Yedoma) cliffs at the coastline alternate with lagoons and lower elevation previously thawed and refrozen permafrost basins (Alases). Electrical resistivity surveys with floating electrodes were carried out to map ice-bearing permafrost and taliks (unfrozen zones in the permafrost, usually formed beneath lakes) along the diverse coastline and in the lagoons. Combined with the borehole data, the electrical resistivity results permit estimation of contemporary ice-bearing permafrost characteristics, distribution, and occasionally, thickness. To conceptualize possible geomorphological and marine evolutionary pathways to the formation of the observed layering, numerical models were applied. The developed model incorporates salt diffusion and seasonal dynamics at the seabed, including bedfast ice. Even along coastlines with mean annual non-cryotic boundary conditions like the Bykovsky Peninsula, the modelling results show that salt diffusion minimizes seasonal freezing of the seabed, leading to faster degradation rates compared to models without salt diffusion. Seasonal processes are also important for thermokarst lake to lagoon transitions because lagoons can generate cold hypersaline conditions underneath the ice cover. My research suggests that ice-bearing permafrost can form in a coastal lagoon environment, even under floating ice. Alas basins, however, may degrade more than twice as fast as Yedoma permafrost in the first several decades of inundation. In addition to a lower ice content compared to Yedoma permafrost, Alas basins may be pre-conditioned with salt from adjacent lagoons. Considering the widespread distribution of thermokarst in the Arctic, its integration into geophysical models and offshore surveys is important to quantify and understand subsea permafrost degradation and aggradation. Through numerical modelling, fieldwork, and a circum-Arctic review of subsea permafrost literature, this thesis provides new insights into sub-aquatic permafrost evolution in saline coastal environments.
The concept of hydrologic connectivity summarizes all flow processes that link separate regions of a landscape. As such, it is a central theme in the field of catchment hydrology, with influence on neighboring disciplines such as ecology and geomorphology. It is widely acknowledged to be an important key in understanding the response behavior of a catchment and has at the same time inspired research on internal processes over a broad range of scales. From this process-hydrological point of view, hydrological connectivity is the conceptual framework to link local observations across space and scales.
This is the context in which the four studies this thesis comprises of were conducted. The focus was on structures and their spatial organization as important control on preferential subsurface flow. Each experiment covered a part of the conceptualized flow path from hillslopes to the stream: soil profile, hillslope, riparian zone, and stream.
For each study site, the most characteristic structures of the investigated domain and scale, such as slope deposits and peat layers were identified based on preliminary or previous investigations or literature reviews. Additionally, further structural data was collected and topographical analyses were carried out. Flow processes were observed either based on response observations (soil moisture changes or discharge patterns) or direct measurement (advective heat transport). Based on these data, the flow-relevance of the characteristic structures was evaluated, especially with regard to hillslope to stream connectivity.
Results of the four studies revealed a clear relationship between characteristic spatial structures and the hydrological behavior of the catchment. Especially the spatial distribution of structures throughout the study domain and their interconnectedness were crucial for the establishment of preferential flow paths and their relevance for large-scale processes. Plot and hillslope-scale irrigation experiments showed that the macropores of a heterogeneous, skeletal soil enabled preferential flow paths at the scale of centimeters through the otherwise unsaturated soil. These flow paths connected throughout the soil column and across the hillslope and facilitated substantial amounts of vertical and lateral flow through periglacial slope deposits.
In the riparian zone of the same headwater catchment, the connectivity between hillslopes and stream was controlled by topography and the dualism between characteristic subsurface structures and the geomorphological heterogeneity of the stream channel. At the small scale (1 m to 10 m) highest gains always occurred at steps along the longitudinal streambed profile, which also controlled discharge patterns at the large scale (100 m) during base flow conditions (number of steps per section). During medium and high flow conditions, however, the impact of topography and parafluvial flow through riparian zone structures prevailed and dominated the large-scale response patterns.
In the streambed of a lowland river, low permeability peat layers affected the connectivity between surface water and groundwater, but also between surface water and the hyporheic zone. The crucial factor was not the permeability of the streambed itself, but rather the spatial arrangement of flow-impeding peat layers, causing increased vertical flow through narrow “windows” in contrast to predominantly lateral flow in extended areas of high hydraulic conductivity sediments.
These results show that the spatial organization of structures was an important control for hydrological processes at all scales and study areas. In a final step, the observations from different scales and catchment elements were put in relation and compared. The main focus was on the theoretical analysis of the scale hierarchies of structures and processes and the direction of causal dependencies in this context. Based on the resulting hierarchical structure, a conceptual framework was developed which is capable of representing the system’s complexity while allowing for adequate simplifications.
The resulting concept of the parabolic scale series is based on the insight that flow processes in the terrestrial part of the catchment (soil and hillslopes) converge. This means that small-scale processes assemble and form large-scale processes and responses. Processes in the riparian zone and the streambed, however, are not well represented by the idea of convergence. Here, the large-scale catchment signal arrives and is modified by structures in the riparian zone, stream morphology, and the small-scale interactions between surface water and groundwater. Flow paths diverge and processes can better be represented by proceeding from large scales to smaller ones. The catchment-scale representation of processes and structures is thus the conceptual link between terrestrial hillslope processes and processes in the riparian corridor.
Data assimilation has been an active area of research in recent years, owing to its wide utility. At the core of data assimilation are filtering, prediction, and smoothing procedures. Filtering entails incorporation of measurements' information into the model to gain more insight into a given state governed by a noisy state space model. Most natural laws are governed by time-continuous nonlinear models. For the most part, the knowledge available about a model is incomplete; and hence uncertainties are approximated by means of probabilities. Time-continuous filtering, therefore, holds promise for wider usefulness, for it offers a means of combining noisy measurements with imperfect model to provide more insight on a given state.
The solution to time-continuous nonlinear Gaussian filtering problem is provided for by the Kushner-Stratonovich equation. Unfortunately, the Kushner-Stratonovich equation lacks a closed-form solution. Moreover, the numerical approximations based on Taylor expansion above third order are fraught with computational complications. For this reason, numerical methods based on Monte Carlo methods have been resorted to. Chief among these methods are sequential Monte-Carlo methods (or particle filters), for they allow for online assimilation of data. Particle filters are not without challenges: they suffer from particle degeneracy, sample impoverishment, and computational costs arising from resampling.
The goal of this thesis is to:— i) Review the derivation of Kushner-Stratonovich equation from first principles and its extant numerical approximation methods, ii) Study the feedback particle filters as a way of avoiding resampling in particle filters, iii) Study joint state and parameter estimation in time-continuous settings, iv) Apply the notions studied to linear hyperbolic stochastic differential equations.
The interconnection between Itô integrals and stochastic partial differential equations and those of Stratonovich is introduced in anticipation of feedback particle filters. With these ideas and motivated by the variants of ensemble Kalman-Bucy filters founded on the structure of the innovation process, a feedback particle filter with randomly perturbed innovation is proposed. Moreover, feedback particle filters based on coupling of prediction and analysis measures are proposed. They register a better performance than the bootstrap particle filter at lower ensemble sizes.
We study joint state and parameter estimation, both by means of extended state spaces and by use of dual filters. Feedback particle filters seem to perform well in both cases. Finally, we apply joint state and parameter estimation in the advection and wave equation, whose velocity is spatially varying. Two methods are employed: Metropolis Hastings with filter likelihood and a dual filter comprising of Kalman-Bucy filter and ensemble Kalman-Bucy filter. The former performs better than the latter.
Polyelectrolyte multilayer capsules as controlled permeability vehicles and catalyst carriers
(2003)
Gravitational-wave (GW) astrophysics is a field in full blossom. Since the landmark detection of GWs from a binary black hole on September 14th 2015, fifty-two compact-object binaries have been reported by the LIGO-Virgo collaboration. Such events carry astrophysical and cosmological information ranging from an understanding of how black holes and neutron stars are formed, what neutron stars are composed of, how the Universe expands, and allow testing general relativity in the highly-dynamical strong-field regime. It is the goal of GW astrophysics to extract such information as accurately as possible. Yet, this is only possible if the tools and technology used to detect and analyze GWs are advanced enough. A key aspect of GW searches are waveform models, which encapsulate our best predictions for the gravitational radiation under a certain set of parameters, and that need to be cross-correlated with data to extract GW signals. Waveforms must be very accurate to avoid missing important physics in the data, which might be the key to answer the fundamental questions of GW astrophysics. The continuous improvements of the current LIGO-Virgo detectors, the development of next-generation ground-based detectors such as the Einstein Telescope or the Cosmic Explorer, as well as the development of the Laser Interferometer Space Antenna (LISA), demand accurate waveform models. While available models are enough to capture the low spins, comparable-mass binaries routinely detected in LIGO-Virgo searches, those for sources from both current and next-generation ground-based and spaceborne detectors must be accurate enough to detect binaries with large spins and asymmetry in the masses. Moreover, the thousands of sources that we expect to detect with future detectors demand accurate waveforms to mitigate biases in the estimation of signals’ parameters due to the presence of a foreground of many sources that overlap in the frequency band. This is recognized as one of the biggest challenges for the analysis of future-detectors’ data, since biases might hinder the extraction of important astrophysical and cosmological information from future detectors’ data. In the first part of this thesis, we discuss how to improve waveform models for binaries with high spins and asymmetry in the masses. In the second, we present the first generic metrics that have been proposed to predict biases in the presence of a foreground of many overlapping signals in GW data.
For the first task, we will focus on several classes of analytical techniques. Current models for LIGO and Virgo studies are based on the post-Newtonian (PN, weak-field, small velocities) approximation that is most natural for the bound orbits that are routinely detected in GW searches. However, two other approximations have risen in prominence, the post-Minkowskian (PM, weak- field only) approximation natural for unbound (scattering) orbits and the small-mass-ratio (SMR) approximation typical of binaries in which the mass of one body is much bigger than the other. These are most appropriate to binaries with high asymmetry in the masses that challenge current waveform models. Moreover, they allow one to “cover” regions of the parameter space of coalescing binaries, thereby improving the interpolation (and faithfulness) of waveform models. The analytical approximations to the relativistic two-body problem can synergically be included within the effective-one-body (EOB) formalism, in which the two-body information from each approximation can be recast into an effective problem of a mass orbiting a deformed Schwarzschild (or Kerr) black hole. The hope is that the resultant models can cover both the low-spin comparable-mass binaries that are routinely detected, and the ones that challenge current models. The first part of this thesis is dedicated to a study about how to best incorporate information from the PN, PM, SMR and EOB approaches in a synergistic way. We also discuss how accurate the resulting waveforms are, as compared against numerical-relativity (NR) simulations. We begin by comparing PM models, whether alone or recast in the EOB framework, against PN models and NR simulations. We will show that PM information has the potential to improve currently-employed models for LIGO and Virgo, especially if recast within the EOB formalism. This is very important, as the PM approximation comes with a host of new computational techniques from particle physics to exploit. Then, we show how a combination of PM and SMR approximations can be employed to access previously-unknown PN orders, deriving the third subleading PN dynamics for spin-orbit and (aligned) spin1-spin2 couplings. Such new results can then be included in the EOB models currently used in GW searches and parameter estimation studies, thereby improving them when the binaries have high spins. Finally, we build an EOB model for quasi-circular nonspinning binaries based on the SMR approximation (rather than the PN one as usually done). We show how this is done in detail without incurring in the divergences that had affected previous attempts, and compare the resultant model against NR simulations. We find that the SMR approximation is an excellent approximation for all (quasi-circular nonspinning) binaries, including both the equal-mass binaries that are routinely detected in GW searches and the ones with highly asymmetric masses. In particular, the SMR-based models compare much better than the PN models, suggesting that SMR-informed EOB models might be the key to model binaries in the future. In the second task of this thesis, we work within the linear-signal ap- proximation and describe generic metrics to predict inference biases on the parameters of a GW source of interest in the presence of confusion noise from unfitted foregrounds and from residuals of other signals that have been incorrectly fitted out. We illustrate the formalism with simple (yet realistic) LISA sources, and demonstrate its validity against Monte-Carlo simulations. The metrics we describe pave the way for more realistic studies to quantify the biases with future ground-based and spaceborne detectors.
Changing the perspective sometimes offers completely new insights to an already well-known phenomenon. Exercising behavior, defined as planned, structured and repeated bodily movements with the intention to maintain or increase the physical fitness (Caspersen, Powell, & Christenson, 1985), can be thought of as such a well-known phenomenon that has been in the scientific focus for many decades (Dishman & O’Connor, 2005). Within these decades a perspective that assumes rational and controlled evaluations as the basis for decision making, was predominantly used to understand why some people engage in physical activity and others do not (Ekkekakis & Zenko, 2015).
Dual-process theories (Ekkekakis & Zenko, 2015; Payne & Gawronski, 2010) provide another perspective, that is not exclusively influenced by rational reasoning. These theories differentiate two different processes that guide behavior “depending on whether they operate automatically or in a controlled fashion“ (Gawronski & Creighton, 2012, p. 282). Following this line of thought, exercise behavior is not solely influenced by thoughtful deliberations (e.g. concluding that exercising is healthy) but also by spontaneous affective reactions (e.g. disliking being sweaty while exercising). The theoretical frameworks of dual-process models are not new in psychology (Chaiken & Trope, 1999) and have already been used for the explanation of numerous behaviors (e.g. Hofmann, Friese, & Wiers, 2008; Huijding, de Jong, Wiers, & Verkooijen, 2005). However, they have only rarely been used for the explanation of exercise behavior (e.g. Bluemke, Brand, Schweizer, & Kahlert, 2010; Conroy, Hyde, Doerksen, & Ribeiro, 2010; Hyde, Doerksen, Ribeiro, & Conroy, 2010). The assumption of two dissimilar behavior influencing processes, differs fundamentally from previous theories and thus from the research that has been conducted in the last decades in exercise psychology. Research mainly concentrated on predictors of the controlled processes and addressed the identified predictors in exercise interventions (Ekkekakis & Zenko, 2015; Hagger, Chatzisarantis, & Biddle, 2002).
Predictors arising from the described automatic processes, for example automatic evaluations for exercising (AEE), have been neglected in exercise psychology for many years. Until now, only a few researchers investigated the influence of these AEE for exercising behavior (Bluemke et al., 2010; Brand & Schweizer, 2015; Markland, Hall, Duncan, & Simatovic, 2015). Marginally more researchers focused on the impact of AEE for physical activity behavior (Calitri, Lowe, Eves, & Bennett, 2009; Conroy et al., 2010; Hyde et al., 2010; Hyde, Elavsky, Doerksen, & Conroy, 2012). The extant studies mainly focused on the quality of AEE and the associated quantity of exercise (exercise much or little; Bluemke et al., 2010; Calitri et al., 2009; Conroy et al., 2010; Hyde et al., 2012). In sum, there is still a dramatic lack of empirical knowledge, when applying dual-process theories to exercising behavior, even though these theories have proven to be successful in explaining behavior in many other health-relevant domains like eating, drinking or smoking behavior (e.g. Hofmann et al., 2008).
The main goal of the present dissertation was to collect empirical evidence for the influence of AEE on exercise behavior and to expand the so far exclusively correlational studies by experimentally controlled studies. By doing so, the ongoing debate on a paradigm shift from controlled and deliberative influences of exercise behavior towards approaches that consider automatic and affective influences (Ekkekakis & Zenko, 2015) should be encouraged. All three conducted publications are embedded in dual-process theorizing (Gawronski & Bodenhausen, 2006, 2014; Strack & Deutsch, 2004). These theories offer a theoretical framework that could integrate the established controlled variables of exercise behavior explanation and additionally consider automatic factors for exercise behavior like AEE.
Taken together, the empirical findings collected suggest that AEE play an important and diverse role for exercise behavior. They represent exercise setting preferences, are a cause for short-term exercise decisions and are decisive for long-term exercise adherence. Adding to the few already present studies in this field, the influence of (positive) AEE for exercise behavior was confirmed in all three presented publications. Even though the available set of studies needs to be extended in prospectively studies, first steps towards a more complete picture have been taken. Closing with the beginning of the synopsis: I think that time is right for a change of perspectives! This means a careful extension of the present theories with controlled evaluations explaining exercise behavior. Dual-process theories including controlled and automatic evaluations could provide such a basis for future research endeavors in exercise psychology.
The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data.
The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient.
The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.
Polymer optical fibers (POFs) are a rather new tool for high-speed data transfer by modulated light. They allow the transport of high amounts of data over distances up to about 100 m without be influenced by external electromagnetic fields. Due to organic chemical nature of POFs, they are sensitive to the climate of their environment and therefore the optical fiber properties are as well. Hence, the optical stability is a key issue for long-term applications of POFs. The causes for a loss of optical transmission due to climatic exposures (aging/degradation) are researched by means of chemical analytical tools such as chemiluminescence (CL) and Fourier transform infrared (FTIR) spectroscopy for five different (with respect to manufacturers) step-index multimode PMMA based POFs and for seven different climatic conditions. Three of the five POF samples are studied more in detail to realize the effects of individual parameters and for forecasting longterm optical stability by short-term exposure tests. At first, the unexposed POF components (core, cladding, and bare POF as combination of core and cladding) are characterized with respect to important physical and chemical properties. The glass transition temperature Tg, and the melting temperature Tm are in the region of 120 °C to 140 °C, the molecular weight (Mw) of cores is in the order of 105 g mol-1. POFs are found to have different chemical compositions of their claddings as could be detected by FTIR, but identical compositions of their cores. Two of the POFs are exposed as cables (core, cladding and jacket) for about 3300 hours to the climate 92 °C / 95 % relative humidity (RH) resulting in a different transmission decrease. Investigating the related unexposed and exposed bare POFs for degradation using CL, FTIR, thermogravimetry (TG), UV/visible transmittance and gel permeation chromatography (GPC) suggest that claddings of POFs are more affected than cores. Probably the observed loss of transmission is mainly due to increased light absorption and imperfections at the core-cladding boundary caused by a large degradation of claddings. Hence, it is highly possible that the optical transmission stability of POFs is governed mainly by the thermo-oxidative stability of the cladding and minor of the core. Three bare POFs (core and cladding only) are exposed for different duration of exposure time (30 hours to 4500 hours) to 92 °C / 95 %RH, 92 °C / 50 %RH, 50 °C / 95 %RH, 90 °C / low humidity, 100 °C / low humidity, 110 °C / low humidity and 120 °C / low humidity. In these climates their transmission variations are found to be different from each other, too. The outcomes strongly inform that under high temperature and high humid climates physical changes such as volume expansion, are the main sources for the loss of optical transmission. Also, the optical transmission stability of POFs is found to be dependent on chemical compositions of claddings. Under high temperature and low humid conditions, a loss of transmission at the early stages of the exposure is mainly caused by physical changes, presumable by corecladding interface imperfections. For the later stages of exposures it is proposed to an additional increase of light absorption by core and cladding owes to degradation. Optical simulation results obtained parallel by Mr. L. Jankowski (a PhD student of BAM) are found to confirm these results. For bare POFs, too, the optical stability of POFs seems to depend on their thermo-oxidative stability. Some short-term exposure tests are conducted to realize influences of individual climatic parameters on the transmission property of POFs. It is found that at stationary high temperature and variable humidity conditions POFs display to a certain amount a reversible transmission loss due to physically absorbed water. But in the case of varying temperature and constant high humidity such reversibility is hardly noticeable. However, at room temperature and varying humidity, POFs display fully reversible transmission loss. The whole research described above has to be regarded as a starting point for further investigations. The restricted distribution of fundamental POF data by the manufacturers and the time consuming aging by climatic exposures restrict the results more or less to the samples, investigated here. Significant general statements require for example additional information concerning the variation of POF properties due to production. Nevertheless the tests, described here, have the capability for approximating and forecasting the long-term optical transmission stability of POFs. -------------- Auch im Druck erschienen: Appajaiah, Anilkumar: Climatic stability of polymer optical fibers (POF) / Anilkumar Appajaiah. - Bremerhaven : Wirtschaftsverl. NW, Verl. für neue Wiss., 2005. - Getr. Zählung [ca. 175 S.]. : Ill., graph. Darst. - (BAM-Dissertationsreihe ; 9) ISBN 3-86509-302-7
Back pain is a problem in adolescent athletes affecting postural control which is an important requirement for physical and daily activities whether under static or dynamic conditions. One leg stance and star excursion balance postural control tests are effective in measuring static and dynamic postural control respectively. These tests have been used in individuals with back pain, athletes and non-athletes without first establishing their reliabilities. In addition to this, there is no published literature investigating dynamic posture in adolescent athletes with back pain using the star excursion balance test. Therefore, the aim of the thesis was to assess deficit in postural control in adolescent athletes with and without back pain using static (one leg stance test) and dynamic postural (SEBT) control tests.
Adolescent athletes with and without back pain participated in the study. Static and dynamic postural control tests were performed using one leg stance and SEBT respectively. The reproducibility of both tests was established. Afterwards, it was determined whether there was an association between static and dynamic posture using the measure of displacement of the centre pressure and reach distance respectively. Finally, it was investigated whether there was a difference in postural control in adolescent athletes with and without back pain using the one leg stance test and the SEBT.
Fair to excellent reliabilities was recorded for the static (one leg stance) and dynamic (star excursion balance) postural control tests in the subjects of interest. No association was found between variables of the static and dynamic tests for the adolescent athletes with and without back pain. Also, no statistically significant difference was obtained between adolescent athletics with and without back pain using the static and dynamic postural control test.
One leg stance test and SEBT can be used as measures of postural control in adolescent athletes with and without back pain. Although static and dynamic postural control might be related, adolescent athletes with and without back pain might be using different mechanisms in controlling their static and dynamic posture. Consequently, static and dynamic postural control in adolescent athletes with back pain was not different from those without back pain. These outcome measures might not be challenging enough to detect deficit in postural control in our study group of interest.
The central melanin-concentrating hormone (MCH) system has been intensively studied for its involvement in the regulation of feeding behaviour and body weight regulation. The importance of the neuropeptide MCH in the control of energy balance has been underlined by MCH knock out and Melanin-concentrating hormone receptor subtype 1 (MCHR-1) knock-out animals. The anorectic and anti-obesity effects of selective MCHR-1 antagonists have confirmed the notion that pharmacological blockade of MCHR-1 is a potential therapeutic approach for obesity. First aim of this work is to study the neurochemical “equipment” of MCHR-1 immunoreactive neurons by double-labelling immunohistochemistry within the rat hypothalamus. Of special interest is the neuroanatomical identification of other hypothalamic neuropeptides that are co-distributed with MCHR-1. A second part of this study deals with the examination of neuronal activation patterns after pharmacological or physiological, feeding-related stimuli and was introduced to further understand central regulatory mechanisms of the MCH system. In the first part of work, I wanted to neurochemically characterize MCHR-1 immunoreactive neurons in the rat hypothalamus for colocalisation with neuropeptides of interest. Therefore I performed an immunohistochemical colocalisation study using a specific antibody against MCHR-1 in combination with antibodies against hypothalamic neuropeptides. I showed that MCHR-1 immunoreactivity (IR) was co-localised with orexin A in the lateral hypothalamus, and with adrenocorticotropic hormone and neuropeptide Y in the arcuate nucleus. Additionally, MCHR-1 IR was co-localised with the neuropeptides vasopressin and oxytocin in magnocellular neurons of the supraoptic and paraventricular hypothalamic nucleus and corticotrophin releasing hormone in the parvocellular division of the paraventricular hypothalamic nucleus. Moreover, for the first time MCHR-1 immunoreactivity was found in both the adenohypophyseal and neurohypophyseal part of the rat pituitary. These results provide the neurochemical basis for previously described potential physiological actions of MCH at its target receptor. In particular, the MCHR-1 may be involved not only in food intake regulation, but also in other physiological actions such as fluid regulation, reproduction and stress response, possibly through here examined neuropeptides. Central activation patterns induced by pharmacological or physiological stimulation can be mapped using c-Fos immunohistochemistry. In the first experimental design, central administration (icv) of MCH in the rat brain resulted in acute and significant increase of food and water intake, but this animal treatment did not induce a specific c-Fos induction pattern in hypothalamic nuclei. In contrast, sub-chronic application of MCHR-1 antagonist promoted a significant decrease in food- and water intake during an eight day treatment period. A qualitative analysis of c-Fos immunohistochemistry of sections derived from MCHR-1 antagonist treated animals showed a specific neuronal activation in the paraventricular nucleus, the supraoptic nucleus and the dorsomedial hypothalamus. These results could be substantiated by quantitative evaluation of an automated, software-supported analysis of the c-Fos signal. Additionally, I examined the activation pattern of rats in a restricted feeding schedule (RFS) to identify pathways involved in hunger and satiety. Animals were trained for 9 days to feed during a three hour period. On the last day, food restricted animals was also allowed to feed for the three hours, while food deprived (FD) animals did not receive food. Mapping of neuronal activation showed a clear difference between stareved (FD) and satiated (FR) rats. FD animals showed significant induction of c-Fos in forebrain regions, several hypothalamic nuclei, amygdaloid thalamus and FR animals in the supraoptic nucleus and the paraventricular nucleus of the hypothalamus, and the nucleus of the solitary tract. In the lateral hypothalamus of FD rats, c-Fos IR showed strong colocalisation for Orexin A, but no co-staining for MCH immunoreactivity. However, a large number of c-Fos IR neurons within activated regions of FD and FR animals was co-localised with MCHR-1 within selected regions. To conclude, the experimental set-up of scheduled feeding can be used to induce a specific hunger or satiety activation pattern within the rat brain. My results show a differential activation by hunger signals of MCH neurons and furthermore, demonstrates that MCHR-1 expressing neurons may be essential parts of downstream processing of physiological feeding/hunger stimuli. In the final part of my work, the relevance of here presented studies is discussed with respect to possible introduction of MCHR-1 antagonists as drug candidates for the treatment of obesity.