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In many applications one is faced with the problem of inferring some functional relation between input and output variables from given data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., spam labels) is a major goal of machine learning. Many learning methods assume that these training data are governed by the same distribution as the test data which the predictive model will be exposed to at application time. That assumption is violated when the test data are generated in response to the presence of a predictive model. This becomes apparent, for instance, in the above example of email spam filtering. Here, email service providers employ spam filters and spam senders engineer campaign templates such as to achieve a high rate of successful deliveries despite any filters. Most of the existing work casts such situations as learning robust models which are unsusceptible against small changes of the data generation process. The models are constructed under the worst-case assumption that these changes are performed such to produce the highest possible adverse effect on the performance of the predictive model. However, this approach is not capable to realistically model the true dependency between the model-building process and the process of generating future data. We therefore establish the concept of prediction games: We model the interaction between a learner, who builds the predictive model, and a data generator, who controls the process of data generation, as an one-shot game. The game-theoretic framework enables us to explicitly model the players' interests, their possible actions, their level of knowledge about each other, and the order at which they decide for an action. We model the players' interests as minimizing their own cost function which both depend on both players' actions. The learner's action is to choose the model parameters and the data generator's action is to perturbate the training data which reflects the modification of the data generation process with respect to the past data. We extensively study three instances of prediction games which differ regarding the order in which the players decide for their action. We first assume that both player choose their actions simultaneously, that is, without the knowledge of their opponent's decision. We identify conditions under which this Nash prediction game has a meaningful solution, that is, a unique Nash equilibrium, and derive algorithms that find the equilibrial prediction model. As a second case, we consider a data generator who is potentially fully informed about the move of the learner. This setting establishes a Stackelberg competition. We derive a relaxed optimization criterion to determine the solution of this game and show that this Stackelberg prediction game generalizes existing prediction models. Finally, we study the setting where the learner observes the data generator's action, that is, the (unlabeled) test data, before building the predictive model. As the test data and the training data may be governed by differing probability distributions, this scenario reduces to learning under covariate shift. We derive a new integrated as well as a two-stage method to account for this data set shift. In case studies on email spam filtering we empirically explore properties of all derived models as well as several existing baseline methods. We show that spam filters resulting from the Nash prediction game as well as the Stackelberg prediction game in the majority of cases outperform other existing baseline methods.
Education in knowledge society is challenged with a lot of problems in particular the interaction between the teacher and learner in social networking software as a key factor affects the learners’ learning and satisfaction (Prammanee, 2005) where “to teach is to communicate, to communicate is to interact, to interact is to learn” (Hefzallah, 2004, p. 48). Analyzing the relation between teacher-learner interaction from a side and learning outcome and learners’ satisfaction from the other side, some basic problems regarding a new learning culture using social networking software are discussed. Most of the educational institutions pay a lot of attentions to the equipments and emerging Information and Communication Technologies (ICTs) in learning situations. They try to incorporate ICT into their institutions as teaching and learning environments. They do this because they expect that by doing so they will improve the outcome of the learning process. Despite this, the learning outcome as reported in most studies is very limited, because the expectations of self-directed learning are much higher than the reality. Findings from an empirical study (investigating the role of teacher-learner interaction through new digital media wiki in higher education and learning outcome and learner’s satisfaction) are presented recommendations about the necessity of pedagogical interactions in support of teaching and learning activities in wiki courses in order to improve the learning outcome. Conclusions show the necessity for significant changes in the approach of vocational teacher training programs of online teachers in order to meet the requirements of new digital media in coherence with a new learning culture. These changes have to address collaborative instead of individual learning and ICT wiki as a tool for knowledge construction instead of a tool for gathering information.
Cargo transport by molecular motors is ubiquitous in all eukaryotic cells and is typically driven cooperatively by several molecular motors, which may belong to one or several motor species like kinesin, dynein or myosin. These motor proteins transport cargos such as RNAs, protein complexes or organelles along filaments, from which they unbind after a finite run length. Understanding how these motors interact and how their movements are coordinated and regulated is a central and challenging problem in studies of intracellular transport. In this thesis, we describe a general theoretical framework for the analysis of such transport processes, which enables us to explain the behavior of intracellular cargos based on the transport properties of individual motors and their interactions. Motivated by recent in vitro experiments, we address two different modes of transport: unidirectional transport by two identical motors and cooperative transport by actively walking and passively diffusing motors. The case of cargo transport by two identical motors involves an elastic coupling between the motors that can reduce the motors’ velocity and/or the binding time to the filament. We show that this elastic coupling leads, in general, to four distinct transport regimes. In addition to a weak coupling regime, kinesin and dynein motors are found to exhibit a strong coupling and an enhanced unbinding regime, whereas myosin motors are predicted to attain a reduced velocity regime. All of these regimes, which we derive both by analytical calculations and by general time scale arguments, can be explored experimentally by varying the elastic coupling strength. In addition, using the time scale arguments, we explain why previous studies came to different conclusions about the effect and relevance of motor-motor interference. In this way, our theory provides a general and unifying framework for understanding the dynamical behavior of two elastically coupled molecular motors. The second mode of transport studied in this thesis is cargo transport by actively pulling and passively diffusing motors. Although these passive motors do not participate in active transport, they strongly enhance the overall cargo run length. When an active motor unbinds, the cargo is still tethered to the filament by the passive motors, giving the unbound motor the chance to rebind and continue its active walk. We develop a stochastic description for such cooperative behavior and explicitly derive the enhanced run length for a cargo transported by one actively pulling and one passively diffusing motor. We generalize our description to the case of several pulling and diffusing motors and find an exponential increase of the run length with the number of involved motors.
One of the most exciting predictions of Einstein's theory of gravitation that have not yet been proven experimentally by a direct detection are gravitational waves. These are tiny distortions of the spacetime itself, and a world-wide effort to directly measure them for the first time with a network of large-scale laser interferometers is currently ongoing and expected to provide positive results within this decade. One potential source of measurable gravitational waves is the inspiral and merger of two compact objects, such as binary black holes. Successfully finding their signature in the noise-dominated data of the detectors crucially relies on accurate predictions of what we are looking for. In this thesis, we present a detailed study of how the most complete waveform templates can be constructed by combining the results from (A) analytical expansions within the post-Newtonian framework and (B) numerical simulations of the full relativistic dynamics. We analyze various strategies to construct complete hybrid waveforms that consist of a post-Newtonian inspiral part matched to numerical-relativity data. We elaborate on exsisting approaches for nonspinning systems by extending the accessible parameter space and introducing an alternative scheme based in the Fourier domain. Our methods can now be readily applied to multiple spherical-harmonic modes and precessing systems. In addition to that, we analyze in detail the accuracy of hybrid waveforms with the goal to quantify how numerous sources of error in the approximation techniques affect the application of such templates in real gravitational-wave searches. This is of major importance for the future construction of improved models, but also for the correct interpretation of gravitational-wave observations that are made utilizing any complete waveform family. In particular, we comprehensively discuss how long the numerical-relativity contribution to the signal has to be in order to make the resulting hybrids accurate enough, and for currently feasible simulation lengths we assess the physics one can potentially do with template-based searches.
This thesis contains several theoretical studies on optomechanical systems, i.e. physical devices where mechanical degrees of freedom are coupled with optical cavity modes. This optomechanical interaction, mediated by radiation pressure, can be exploited for cooling and controlling mechanical resonators in a quantum regime. The goal of this thesis is to propose several new ideas for preparing meso- scopic mechanical systems (of the order of 10^15 atoms) into highly non-classical states. In particular we have shown new methods for preparing optomechani-cal pure states, squeezed states and entangled states. At the same time, proce-dures for experimentally detecting these quantum effects have been proposed. In particular, a quantitative measure of non classicality has been defined in terms of the negativity of phase space quasi-distributions. An operational al- gorithm for experimentally estimating the non-classicality of quantum states has been proposed and successfully applied in a quantum optics experiment. The research has been performed with relatively advanced mathematical tools related to differential equations with periodic coefficients, classical and quantum Bochner’s theorems and semidefinite programming. Nevertheless the physics of the problems and the experimental feasibility of the results have been the main priorities.
Complex networks have been successfully employed to represent different levels of biological systems, ranging from gene regulation to protein-protein interactions and metabolism. Network-based research has mainly focused on identifying unifying structural properties, including small average path length, large clustering coefficient, heavy-tail degree distribution, and hierarchical organization, viewed as requirements for efficient and robust system architectures. Existing studies estimate the significance of network properties using a generic randomization scheme - a Markov-chain switching algorithm - which generates unrealistic reactions in metabolic networks, as it does not account for the physical principles underlying metabolism. Therefore, it is unclear whether the properties identified with this generic approach are related to the functions of metabolic networks. Within this doctoral thesis, I have developed an algorithm for mass-balanced randomization of metabolic networks, which runs in polynomial time and samples networks almost uniformly at random. The properties of biological systems result from two fundamental origins: ubiquitous physical principles and a complex history of evolutionary pressure. The latter determines the cellular functions and abilities required for an organism’s survival. Consequently, the functionally important properties of biological systems result from evolutionary pressure. By employing randomization under physical constraints, the salient structural properties, i.e., the smallworld property, degree distributions, and biosynthetic capabilities of six metabolic networks from all kingdoms of life are shown to be independent of physical constraints, and thus likely to be related to evolution and functional organization of metabolism. This stands in stark contrast to the results obtained from the commonly applied switching algorithm. In addition, a novel network property is devised to quantify the importance of reactions by simulating the impact of their knockout. The relevance of the identified reactions is verified by the findings of existing experimental studies demonstrating the severity of the respective knockouts. The results suggest that the novel property may be used to determine the reactions important for viability of organisms. Next, the algorithm is employed to analyze the dependence between mass balance and thermodynamic properties of Escherichia coli metabolism. The thermodynamic landscape in the vicinity of the metabolic network reveals two regimes of randomized networks: those with thermodynamically favorable reactions, similar to the original network, and those with less favorable reactions. The results suggest that there is an intrinsic dependency between thermodynamic favorability and evolutionary optimization. The method is further extended to optimizing metabolic pathways by introducing novel chemically feasibly reactions. The results suggest that, in three organisms of biotechnological importance, introduction of the identified reactions may allow for optimizing their growth. The approach is general and allows identifying chemical reactions which modulate the performance with respect to any given objective function, such as the production of valuable compounds or the targeted suppression of pathway activity. These theoretical developments can find applications in metabolic engineering or disease treatment. The developed randomization method proposes a novel approach to measuring the significance of biological network properties, and establishes a connection between large-scale approaches and biological function. The results may provide important insights into the functional principles of metabolic networks, and open up new possibilities for their engineering.
Since available phosphate (Pi) resources in soil are limited, symbiotic interactions between plant roots and arbuscular mycorrhizal (AM) fungi are a widespread strategy to improve plant phosphate nutrition. The repression of AM symbiosis by a high plant Pi-status indicates a link between Pi homeostasis signalling and AM symbiosis development. This assumption is supported by the systemic induction of several microRNA399 (miR399) primary transcripts in shoots and a simultaneous accumulation of mature miR399 in roots of mycorrhizal plants. However, the physiological role of this miR399 expression pattern is still elusive and offers the question whether other miRNAs are also involved in AM symbiosis. Therefore, a deep sequencing approach was applied to investigate miRNA-mediated posttranscriptional gene regulation in M. truncatula mycorrhizal roots. Degradome analysis revealed that 185 transcripts were cleaved by miRNAs, of which the majority encoded transcription factors and disease resistance genes, suggesting a tight control of transcriptional reprogramming and a downregulation of defence responses by several miRNAs in mycorrhizal roots. Interestingly, 45 of the miRNA-cleaved transcripts showed a significant differentially regulated between mycorrhizal and non-mycorrhizal roots. In addition, key components of the Pi homeostasis signalling pathway were analyzed concerning their expression during AM symbiosis development. MtPhr1 overexpression and time course expression data suggested a strong interrelation between the components of the PHR1-miR399-PHO2 signalling pathway and AM symbiosis, predominantly during later stages of symbiosis. In situ hybridizations confirmed accumulation of mature miR399 in the phloem and in arbuscule-containing cortex cells of mycorrhizal roots. Moreover, a novel target of the miR399 family, named as MtPt8, was identified by the above mentioned degradome analysis. MtPt8 encodes a Pi-transporter exclusively transcribed in mycorrhizal roots and its promoter activity was restricted to arbuscule-containing cells. At a low Pi-status, MtPt8 transcript abundance inversely correlated with a mature miR399 expression pattern. Increased MtPt8 transcript levels were accompanied by elevated symbiotic Pi-uptake efficiency, indicating its impact on balancing plant and fungal Pi-acquisition. In conclusion, this study provides evidence for a direct link of the regulatory mechanisms of plant Pi-homeostasis and AM symbiosis at a cell-specific level. The results of this study, especially the interaction of miR399 and MtPt8 provide a fundamental step for future studies of plant-microbe-interactions with regard to agricultural and ecological aspects.
Theory of mRNA degradation
(2012)
One of the central themes of biology is to understand how individual cells achieve a high fidelity in gene expression. Each cell needs to ensure accurate protein levels for its proper functioning and its capability to proliferate. Therefore, complex regulatory mechanisms have evolved in order to render the expression of each gene dependent on the expression level of (all) other genes. Regulation can occur at different stages within the framework of the central dogma of molecular biology. One very effective and relatively direct mechanism concerns the regulation of the stability of mRNAs. All organisms have evolved diverse and powerful mechanisms to achieve this. In order to better comprehend the regulation in living cells, biochemists have studied specific degradation mechanisms in detail. In addition to that, modern high-throughput techniques allow to obtain quantitative data on a global scale by parallel analysis of the decay patterns of many different mRNAs from different genes. In previous studies, the interpretation of these mRNA decay experiments relied on a simple theoretical description based on an exponential decay. However, this does not account for the complexity of the responsible mechanisms and, as a consequence, the exponential decay is often not in agreement with the experimental decay patterns. We have developed an improved and more general theory of mRNA degradation which provides a general framework of mRNA expression and allows describing specific degradation mechanisms. We have made an attempt to provide detailed models for the regulation in different organisms. In the yeast S. cerevisiae, different degradation pathways are known to compete and furthermore most of them rely on the biochemical modification of mRNA molecules. In bacteria such as E. coli, degradation proceeds primarily endonucleolytically, i.e. it is governed by the initial cleavage within the coding region. In addition, it is often coupled to the level of maturity and the size of the polysome of an mRNA. Both for S. cerevisiae and E. coli, our descriptions lead to a considerable improvement of the interpretation of experimental data. The general outcome is that the degradation of mRNA must be described by an age-dependent degradation rate, which can be interpreted as a consequence of molecular aging of mRNAs. Within our theory, we find adequate ways to address this much debated topic from a theoretical perspective. The improvements of the understanding of mRNA degradation can be readily applied to further comprehend the mRNA expression under different internal or environmental conditions such as after the induction of transcription or stress application. Also, the role of mRNA decay can be assessed in the context of translation and protein synthesis. The ultimate goal in understanding gene regulation mediated by mRNA stability will be to identify the relevance and biological function of different mechanisms. Once more quantitative data will become available, our description allows to elaborate the role of each mechanism by devising a suitable model.
Climate is the principal driving force of hydrological extremes like floods and attributing generating mechanisms is an essential prerequisite for understanding past, present, and future flood variability. Successively enhanced radiative forcing under global warming enhances atmospheric water-holding capacity and is expected to increase the likelihood of strong floods. In addition, natural climate variability affects the frequency and magnitude of these events on annual to millennial time-scales. Particularly in the mid-latitudes of the Northern Hemisphere, correlations between meteorological variables and hydrological indices suggest significant effects of changing climate boundary conditions on floods. To date, however, understanding of flood responses to changing climate boundary conditions is limited due to the scarcity of hydrological data in space and time. Exploring paleoclimate archives like annually laminated (varved) lake sediments allows to fill this gap in knowledge offering precise dated time-series of flood variability for millennia. During river floods, detrital catchment material is eroded and transported in suspension by fluid turbulence into downstream lakes. In the water body the transport capacity of the inflowing turbidity current successively diminishes leading to the deposition of detrital layers on the lake floor. Intercalated into annual laminations these detrital layers can be dated down to seasonal resolution. Microfacies analyses and X-ray fluorescence scanning (µ-XRF) at 200 µm resolution were conducted on the varved Mid- to Late Holocene interval of two sediment profiles from pre-alpine Lake Ammersee (southern Germany) located in a proximal (AS10prox) and distal (AS10dist) position towards the main tributary River Ammer. To shed light on sediment distribution within the lake, particular emphasis was (1) the detection of intercalated detrital layers and their micro-sedimentological features, and (2) intra-basin correlation of these deposits. Detrital layers were dated down to the season by microscopic varve counting and determination of the microstratigraphic position within a varve. The resulting chronology is verified by accelerator mass spectrometry (AMS) 14C dating of 14 terrestrial plant macrofossils. Since ~5500 varve years before present (vyr BP), in total 1573 detrital layers were detected in either one or both of the investigated sediment profiles. Based on their microfacies, geochemistry, and proximal-distal deposition pattern, detrital layers were interpreted as River Ammer flood deposits. Calibration of the flood layer record using instrumental daily River Ammer runoff data from AD 1926 to 1999 proves the flood layer succession to represent a significant time-series of major River Ammer floods in spring and summer, the flood season in the Ammersee region. Flood layer frequency trends are in agreement with decadal variations of the East Atlantic-Western Russia (EA-WR) atmospheric pattern back to 200 yr BP (end of the used atmospheric data) and solar activity back to 5500 vyr BP. Enhanced flood frequency corresponds to the negative EA-WR phase and reduced solar activity. These common links point to a central role of varying large-scale atmospheric circulation over Europe for flood frequency in the Ammersee region and suggest that these atmospheric variations, in turn, are likely modified by solar variability during the past 5500 years. Furthermore, the flood layer record indicates three shifts in mean layer thickness and frequency of different manifestation in both sediment profiles at ~5500, ~2800, and ~500 vyr BP. Combining information from both sediment profiles enabled to interpret these shifts in terms of stepwise increases in mean flood intensity. Likely triggers of these shifts are gradual reduction of Northern Hemisphere orbital summer forcing and long-term solar activity minima. Hypothesized atmospheric response to this forcing is hemispheric cooling that enhances equator-to-pole temperature gradients and potential energy in the troposphere. This energy is transferred into stronger westerly cyclones, more extreme precipitation, and intensified floods at Lake Ammersee. Interpretation of flood layer frequency and thickness data in combination with reanalysis models and time-series analysis allowed to reconstruct the flood history and to decipher flood triggering climate mechanisms in the Ammersee region throughout the past 5500 years. Flood frequency and intensity are not stationary, but influenced by multi-causal climate forcing of large-scale atmospheric modes on time-scales from years to millennia. These results challenge future projections that propose an increase in floods when Earth warms based only on the assumption of an enhanced hydrological cycle.
The field of machine learning studies algorithms that infer predictive models from data. Predictive models are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a predictive model, it is crucial to know the model’s approximate performance. To evaluate performance, a set of labeled test instances is required that is drawn from the distribution the model will be exposed to at application time. In many practical scenarios, unlabeled test instances are readily available, but the process of labeling them can be a time- and cost-intensive task and may involve a human expert. This thesis addresses the problem of evaluating a given predictive model accurately with minimal labeling effort. We study an active model evaluation process that selects certain instances of the data according to an instrumental sampling distribution and queries their labels. We derive sampling distributions that minimize estimation error with respect to different performance measures such as error rate, mean squared error, and F-measures. An analysis of the distribution that governs the estimator leads to confidence intervals, which indicate how precise the error estimation is. Labeling costs may vary across different instances depending on certain characteristics of the data. For instance, documents differ in their length, comprehensibility, and technical requirements; these attributes affect the time a human labeler needs to judge relevance or to assign topics. To address this, the sampling distribution is extended to incorporate instance-specific costs. We empirically study conditions under which the active evaluation processes are more accurate than a standard estimate that draws equally many instances from the test distribution. We also address the problem of comparing the risks of two predictive models. The standard approach would be to draw instances according to the test distribution, label the selected instances, and apply statistical tests to identify significant differences. Drawing instances according to an instrumental distribution affects the power of a statistical test. We derive a sampling procedure that maximizes test power when used to select instances, and thereby minimizes the likelihood of choosing the inferior model. Furthermore, we investigate the task of comparing several alternative models; the objective of an evaluation could be to rank the models according to the risk that they incur or to identify the model with lowest risk. An experimental study shows that the active procedure leads to higher test power than the standard test in many application domains. Finally, we study the problem of evaluating the performance of ranking functions, which are used for example for web search. In practice, ranking performance is estimated by applying a given ranking model to a representative set of test queries and manually assessing the relevance of all retrieved items for each query. We apply the concepts of active evaluation and active comparison to ranking functions and derive optimal sampling distributions for the commonly used performance measures Discounted Cumulative Gain and Expected Reciprocal Rank. Experiments on web search engine data illustrate significant reductions in labeling costs.
The potential increase in frequency and magnitude of extreme floods is currently discussed in terms of global warming and the intensification of the hydrological cycle. The profound knowledge of past natural variability of floods is of utmost importance in order to assess flood risk for the future. Since instrumental flood series cover only the last ~150 years, other approaches to reconstruct historical and pre-historical flood events are needed. Annually laminated (varved) lake sediments are meaningful natural geoarchives because they provide continuous records of environmental changes > 10000 years down to a seasonal resolution. Since lake basins additionally act as natural sediment traps, the riverine sediment supply, which is preserved as detrital event layers in the lake sediments, can be used as a proxy for extreme discharge events. Within my thesis I examined a ~ 8.50 m long sedimentary record from the pre-Alpine Lake Mondsee (Northeast European Alps), which covered the last 7000 years. This sediment record consists of calcite varves and intercalated detrital layers, which range in thickness from 0.05 to 32 mm. Detrital layer deposition was analysed by a combined method of microfacies analysis via thin sections, Scanning Electron Microscopy (SEM), μX-ray fluorescence (μXRF) scanning and magnetic susceptibility. This approach allows characterizing individual detrital event layers and assigning a corresponding input mechanism and catchment. Based on varve counting and controlled by 14C age dates, the main goals of this thesis are (i) to identify seasonal runoff processes, which lead to significant sediment supply from the catchment into the lake basin and (ii) to investigate flood frequency under changing climate boundary conditions. This thesis follows a line of different time slices, presenting an integrative approach linking instrumental and historical flood data from Lake Mondsee in order to evaluate the flood record inferred from Lake Mondsee sediments. The investigation of eleven short cores covering the last 100 years reveals the abundance of 12 detrital layers. Therein, two types of detrital layers are distinguished by grain size, geochemical composition and distribution pattern within the lake basin. Detrital layers, which are enriched in siliciclastic and dolomitic material, reveal sediment supply from the Flysch sediments and Northern Calcareous Alps into the lake basin. These layers are thicker in the northern lake basin (0.1-3.9 mm) and thinner in the southern lake basin (0.05-1.6 mm). Detrital layers, which are enriched in dolomitic components forming graded detrital layers (turbidites), indicate the provenance from the Northern Calcareous Alps. These layers are generally thicker (0.65-32 mm) and are solely recorded within the southern lake basin. In comparison with instrumental data, thicker graded layers result from local debris flow events in summer, whereas thin layers are deposited during regional flood events in spring/summer. Extreme summer floods as reported from flood layer deposition are principally caused by cyclonic activity from the Mediterranean Sea, e.g. July 1954, July 1997 and August 2002. During the last two millennia, Lake Mondsee sediments reveal two significant flood intervals with decadal-scale flood episodes, during the Dark Ages Cold Period (DACP) and the transition from the Medieval Climate Anomaly (MCA) into the Little Ice Age (LIA) suggesting a linkage of transition to climate cooling and summer flood recurrences in the Northeastern Alps. In contrast, intermediate or decreased flood episodes appeared during the MWP and the LIA. This indicates a non-straightforward relationship between temperature and flood recurrence, suggesting higher cyclonic activity during climate transition in the Northeast Alps. The 7000-year flood chronology reveals 47 debris flows and 269 floods, with increased flood activity shifting around 3500 and 1500 varve yr BP (varve yr BP = varve years before present, before present = AD 1950). This significant increase in flood activity shows a coincidence with millennial-scale climate cooling that is reported from main Alpine glacier advances and lower tree lines in the European Alps since about 3300 cal. yr BP (calibrated years before present). Despite relatively low flood occurrence prior to 1500 varve yr BP, floods at Lake Mondsee could have also influenced human life in early Neolithic lake dwellings (5750-4750 cal. yr BP). While the first lake dwellings were constructed on wetlands, the later lake dwellings were built on piles in the water suggesting an early flood risk adaptation of humans and/or a general change of the Late Neolithic Culture of lake-dwellers because of socio-economic reasons. However, a direct relationship between the final abandonment of the lake dwellings and higher flood frequencies is not evidenced.
A discrete analogue of the Witten Laplacian on the n-dimensional integer lattice is considered. After rescaling of the operator and the lattice size we analyze the tunnel effect between different wells, providing sharp asymptotics of the low-lying spectrum. Our proof, inspired by work of B. Helffer, M. Klein and F. Nier in continuous setting, is based on the construction of a discrete Witten complex and a semiclassical analysis of the corresponding discrete Witten Laplacian on 1-forms. The result can be reformulated in terms of metastable Markov processes on the lattice.
This study follows the debate in comparative public administration research on the role of advisory arrangements in central governments. The aim of this study is to explain the mechanisms by which these actors gain their alleged role in government decision-making. Hence, it analyses advisory arrangements that are proactively involved in executive decision-making and may compete with the permanent bureaucracy by offering policy advice to political executives. The study argues that these advisory arrangements influence government policy-making by "institutional politics", i.e. by shaping the institutional underpinnings to govern or rather the "rules of the executive game" in order to strengthen their own position or that of their clients. The theoretical argument of this study follows the neo-institutionalist turn in organization theory and defines institutional politics as gradual institutionalization processes between institutions and organizational actors. It applies a broader definition of institutions as sets of regulative, normative and cognitive pillars. Following the "power-distributional approach" such gradual institutionalization processes are influenced by structure-oriented characteristics, i.e. the nature of the objects of institutional politics, in particular the freedom of interpretation in their application, as well as the distinct constraints of the institutional context. In addition, institutional politics are influenced by agency-oriented characteristics, i.e. the ambitions of actors to act as "would-be change agents". These two explanatory dimensions result in four ideal-typical mechanisms of institutional politics: layering, displacement, drift, and conversion, which correspond to four ideal-types of would-be change agents. The study examines the ambitions of advisory arrangements in institutional politics in an exploratory manner, the relevance of the institutional context is analyzed via expectation hypotheses on the effects of four institutional context features that are regarded as relevant in the scholarly debate: (1) the party composition of governments, (2) the structuring principles in cabinet, (3) the administrative tradition, and (4) the formal politicization of the ministerial bureaucracy. The study follows a "most similar systems design" and conducts qualitative case studies on the role of advisory arrangements at the center of German and British governments, i.e. the Prime Minister’s Office and the Ministry of Finance, for a longer period (1969/1970-2005). Three time periods are scrutinized per country; the British case studies examine the role of advisory arrangements at the Cabinet Office, the Prime Minister's Office, and the Ministry of Finance under Prime Ministers Heath (1970-74), Thatcher (1979-87) and Blair (1997-2005). The German case studies study the role of advisory arrangements at the Federal Chancellery and the Federal Ministry of Finance during the Brandt government (1969-74), the Kohl government (1982-1987) and the Schröder government (1998-2005). For the empirical analysis, the results of a document analysis and the findings of 75 semi-structured expert interviews have been triangulated. The comparative analysis reveals different patterns of institutional politics. The German advisory arrangements engaged initially in displacement but turned soon towards layering and drift, i.e. after an initial displacement of the pre-existing institutional underpinnings to govern they laid increasingly new elements onto existing ones and took the non-deliberative decision to neglect the adaption of existing rules of the executive game towards changing environmental demands. The British advisory arrangements were mostly involved in displacement and conversion, despite occasional layering, i.e. they displaced the pre-existing institutional underpinnings to govern with new rules of the executive game and transformed and realigned them, sometimes also layering new elements onto pre-existing ones. The structure- and agency-oriented characteristics explain these patterns of institutional politics. First, the study shows that the institutional context limits the institutional politics in Germany and facilitates the institutional politics in the UK. Second, the freedom of interpreting the application of institutional targets is relevant and could be observed via the different ambitions of advisory arrangements across countries and over time, confirming, third, that the interests of such would-be change agents are likewise important to understand the patterns of institutional politics. The study concludes that the role of advisory arrangements in government policy-making rests not only upon their policy-related, party-political or media-advisory role for political executives, but especially upon their activities in institutional politics, resulting in distinct institutional constraints on all actors in government policy-making – including their own role in these processes.
Tensorial spacetime geometries carrying predictive, interpretable and quantizable matter dynamics
(2012)
Which tensor fields G on a smooth manifold M can serve as a spacetime structure? In the first part of this thesis, it is found that only a severely restricted class of tensor fields can provide classical spacetime geometries, namely those that can carry predictive, interpretable and quantizable matter dynamics. The obvious dependence of this characterization of admissible tensorial spacetime geometries on specific matter is not a weakness, but rather presents an insight: it was Maxwell theory that justified Einstein to promote Lorentzian manifolds to the status of a spacetime geometry. Any matter that does not mimick the structure of Maxwell theory, will force us to choose another geometry on which the matter dynamics of interest are predictive, interpretable and quantizable. These three physical conditions on matter impose three corresponding algebraic conditions on the totally symmetric contravariant coefficient tensor field P that determines the principal symbol of the matter field equations in terms of the geometric tensor G: the tensor field P must be hyperbolic, time-orientable and energy-distinguishing. Remarkably, these physically necessary conditions on the geometry are mathematically already sufficient to realize all kinematical constructions familiar from Lorentzian geometry, for precisely the same structural reasons. This we were able to show employing a subtle interplay of convex analysis, the theory of partial differential equations and real algebraic geometry. In the second part of this thesis, we then explore general properties of any hyperbolic, time-orientable and energy-distinguishing tensorial geometry. Physically most important are the construction of freely falling non-rotating laboratories, the appearance of admissible modified dispersion relations to particular observers, and the identification of a mechanism that explains why massive particles that are faster than some massless particles can radiate off energy until they are slower than all massless particles in any hyperbolic, time-orientable and energy-distinguishing geometry. In the third part of the thesis, we explore how tensorial spacetime geometries fare when one wants to quantize particles and fields on them. This study is motivated, in part, in order to provide the tools to calculate the rate at which superluminal particles radiate off energy to become infraluminal, as explained above. Remarkably, it is again the three geometric conditions of hyperbolicity, time-orientability and energy-distinguishability that allow the quantization of general linear electrodynamics on an area metric spacetime and the quantization of massive point particles obeying any admissible dispersion relation. We explore the issue of field equations of all possible derivative order in rather systematic fashion, and prove a practically most useful theorem that determines Dirac algebras allowing the reduction of derivative orders. The final part of the thesis presents the sketch of a truly remarkable result that was obtained building on the work of the present thesis. Particularly based on the subtle duality maps between momenta and velocities in general tensorial spacetimes, it could be shown that gravitational dynamics for hyperbolic, time-orientable and energy distinguishable geometries need not be postulated, but the formidable physical problem of their construction can be reduced to a mere mathematical task: the solution of a system of homogeneous linear partial differential equations. This far-reaching physical result on modified gravity theories is a direct, but difficult to derive, outcome of the findings in the present thesis. Throughout the thesis, the abstract theory is illustrated through instructive examples.
This thesis aims at a better mechanistic understanding of animal communities. Therefore, an allometry- and individual-based model has been developed which was used to simulate mammal and bird communities in heterogeneous landscapes, and to to better understand their response to landscape changes (habitat loss and fragmentation).
This thesis is focussed on the electronic properties of the new material class named topological insulators. Spin and angle resolved photoelectron spectroscopy have been applied to reveal several unique properties of the surface state of these materials. The first part of this thesis introduces the methodical background of these quite established experimental techniques.
In the following chapter, the theoretical concept of topological insulators is introduced. Starting from the prominent example of the quantum Hall effect, the application of topological invariants to classify material systems is illuminated. It is explained how, in presence of time reversal symmetry, which is broken in the quantum Hall phase, strong spin orbit coupling can drive a system into a topologically non trivial phase. The prediction of the spin quantum Hall effect in two dimensional insulators an the generalization to the three dimensional case of topological insulators is reviewed together with the first experimental realization of a three dimensional topological insulator in the Bi1-xSbx alloys given in the literature.
The experimental part starts with the introduction of the Bi2X3 (X=Se, Te) family of materials. Recent theoretical predictions and experimental findings on the bulk and surface electronic structure of these materials are introduced in close discussion to our own experimental results. Furthermore, it is revealed, that the topological surface state of Bi2Te3 shares its orbital symmetry with the bulk valence band and the observation of a temperature induced shift of the chemical potential is to a high probability unmasked as a doping effect due to residual gas adsorption.
The surface state of Bi2Te3 is found to be highly spin polarized with a polarization value of about 70% in a macroscopic area, while in Bi2Se3 the polarization appears reduced, not exceeding 50%. We, however, argue that the polarization is most likely only extrinsically limited in terms of the finite angular resolution and the lacking detectability of the out of plane component of the electron spin. A further argument is based on the reduced surface quality of the single crystals after cleavage and, for Bi2Se3 a sensitivity of the electronic structure to photon exposure.
We probe the robustness of the topological surface state in Bi2X3 against surface impurities in Chapter 5. This robustness is provided through the protection by the time reversal symmetry. Silver, deposited on the (111) surface of Bi2Se3 leads to a strong electron doping but the surface state is observed up to a deposited Ag mass equivalent to one atomic monolayer. The opposite sign of doping, i.e., hole-like, is observed by exposing oxygen to Bi2Te3. But while the n-type shift of Ag on Bi2Se3 appears to be more or less rigid, O2 is lifting the Dirac point of the topological surface state in Bi2Te3 out of the valence band minimum at $\Gamma$. After increasing the oxygen dose further, it is possible to shift the Dirac point to the Fermi level, while the valence band stays well beyond. The effect is found reversible, by warming up the samples which is interpreted in terms of physisorption of O2.
For magnetic impurities, i.e., Fe, we find a similar behavior as for the case of Ag in both Bi2Se3 and Bi2Te3. However, in that case the robustness is unexpected, since magnetic impurities are capable to break time reversal symmetry which should introduce a gap in the surface state at the Dirac point which in turn removes the protection. We argue, that the fact that the surface state shows no gap must be attributed to a missing magnetization of the Fe overlayer. In Bi2Te3 we are able to observe the surface state for deposited iron mass equivalents in the monolayer regime. Furthermore, we gain control over the sign of doping through the sample temperature during deposition.
Chapter6 is devoted to the lifetime broadening of the photoemission signal from the topological surface states of Bi2Se3 and Bi2Te3. It is revealed that the hexagonal warping of the surface state in Bi2Te3 introduces an anisotropy for electrons traveling along the two distinct high symmetry directions of the surface Brillouin zone, i.e., $\Gamma$K and $\Gamma$M. We show that the phonon coupling strength to the surface electrons in Bi2Te3 is in nice agreement with the theoretical prediction but, nevertheless, higher than one may expect. We argue that the electron-phonon coupling is one of the main contributions to the decay of photoholes but the relatively small size of the Fermi surface limits the number of phonon modes that may scatter off electrons. This effect is manifested in the energy dependence of the imaginary part of the electron self energy of the surface state which shows a decay to higher binding energies in contrast to the monotonic increase proportional to E$^2$ in the Fermi liquid theory due to electron-electron interaction.
Furthermore, the effect of the surface impurities of Chapter 5 on the quasiparticle life- times is investigated. We find that Fe impurities have a much stronger influence on the lifetimes as compared to Ag. Moreover, we find that the influence is stronger independently of the sign of the doping. We argue that this observation suggests a minor contribution of the warping on increased scattering rates in contrast to current belief. This is additionally confirmed by the observation that the scattering rates increase further with increasing silver amount while the doping stays constant and by the fact that clean Bi2Se3 and Bi2Te3 show very similar scattering rates regardless of the much stronger warping in Bi2Te3.
In the last chapter we report on a strong circular dichroism in the angle distribution of the photoemission signal of the surface state of Bi2Te3. We show that the color pattern obtained by calculating the difference between photoemission intensities measured with opposite photon helicity reflects the pattern expected for the spin polarization. However, we find a strong influence on strength and even sign of the effect when varying the photon energy. The sign change is qualitatively confirmed by means of one-step photoemission calculations conducted by our collaborators from the LMU München, while the calculated spin polarization is found to be independent of the excitation energy. Experiment and theory together unambiguously uncover the dichroism in these systems as a final state effect and the question in the title of the chapter has to be negated: Circular dichroism in the angle distribution is not a new spin sensitive technique.
Porous materials (e.g. zeolites, activated carbon, etc.) have found various applications in industry, such as the use as sorbents, catalyst supports and membranes for separation processes. Recently, much attention has been focused on synthesizing porous polymer materials. A vast amount of tailor-made polymeric systems with tunable properties has been investigated. Very often, however, the starting substances for these polymers are of petrochemical origin, and the processes are all in all not sustainable. Moreover, the new polymers have challenged existing characterizing methodologies. These have to be further developed to address the upcoming demands of the novel materials. Some standard techniques for the analysis of porous substances like nitrogen sorption at 77 K do not seem to be sufficient to answer all arising questions about the microstructure of such materials. In this thesis, microporous polymers from an abundant natural resource, betulin, will be presented. Betulin is a large-scale byproduct of the wood industry, and its content in birch bark can reach 30 wt.%. Based on its rigid structure, polymer networks with intrinsic microporosity could be synthesized and characterized. Apart from standard nitrogen and carbon dioxide sorption at 77 K and 273 K, respectively, gas sorption has been examined not only with various gases (hydrogen and argon) but also at various temperatures. Additional techniques such as X-ray scattering and xenon NMR have been utilized to enable insight into the microporous structure of the material. Starting from insoluble polymer networks with promising gas selectivities, soluble polyesters have been synthesized and processed to a cast film. Such materials are feasible for membrane applications in gas separation. Betulin as a starting compound for polyester synthesis has aided to prepare, and for the first time to thoroughly analyse a microporous polyester with respect to its pores and microstructure. It was established that nitrogen adsorption at 87 K can be a better method to solve the microstructure of the material. In addition to that, other betulin-based polymers such as polyurethanes and polyethylene glycol bioconjugates are presented. Altogether, it has been shown that as an abundant natural resource betulin is a suitable and cheap starting compound for some polymers with various potential applications.
The present thesis is to be brought into line with the current need for alternative and sustainable approaches toward energy management and materials design. In this context, carbon in particular has become the material of choice in many fields such as energy conversion and storage. Herein, three main topics are covered: 1)An alternative synthesis strategy toward highly porous functional carbons with tunable porosity using ordinary salts as porogen (denoted as “salt templating”) 2)The one-pot synthesis of porous metal nitride containing functional carbon composites 3)The combination of both approaches, enabling the generation of highly porous composites with finely tunable properties All approaches have in common that they are based on the utilization of ionic liquids, salts which are liquid below 100 °C, as precursors. Just recently, ionic liquids were shown to be versatile precursors for the generation of heteroatom-doped carbons since the liquid state and a negligible vapor pressure are highly advantageous properties. However, in most cases the products do not possess any porosity which is essential for many applications. In the first part, “salt templating”, the utilization of salts as diverse and sustainable porogens, is introduced. Exemplarily shown for ionic liquid derived nitrogen- and nitrogen-boron-co-doped carbons, the control of the porosity and morphology on the nanometer scale by salt templating is presented. The studies within this thesis were conducted with the ionic liquids 1-Butyl-3-methyl-pyridinium dicyanamide (Bmp-dca), 1-Ethyl-3-methyl-imidazolium dicyanamide (Emim-dca) and 1 Ethyl 3-methyl-imidazolium tetracyanoborate (Emim-tcb). The materials are generated through thermal treatment of precursor mixtures containing one of the ionic liquids and a porogen salt. By simple removal of the non-carbonizable template salt with water, functional graphitic carbons with pore sizes ranging from micro- to mesoporous and surface areas up to 2000 m2g-1 are obtained. The carbon morphologies, which presumably originate from different onsets of demixing, mainly depend on the nature of the porogen salt whereas the nature of the ionic liquid plays a minor role. Thus, a structural effect of the porogen salt rather than activation can be assumed. This offers an alternative to conventional activation and templating methods, enabling to avoid multiple-step and energy-consuming synthesis pathways as well as employment of hazardous chemicals for the template removal. The composition of the carbons can be altered via the heat-treatment procedure, thus at lower synthesis temperatures rather polymeric carbonaceous materials with a high degree of functional groups and high surface areas are accessible. First results suggest the suitability of the materials for CO2 utilization. In order to further illustrate the potential of ionic liquids as carbon precursors and to expand the class of carbons which can be obtained, the ionic liquid 1-Ethyl-3-methyl-imidazolium thiocyanate (Emim-scn) is introduced for the generation of nitrogen-sulfur-co-doped carbons in combination with the already studied ionic liquids Bmp-dca and Emim-dca. Here, the salt templating approach should also be applicable eventually further illustrating the potential of salt templating, too. In the second part, a one-pot and template-free synthesis approach toward inherently porous metal nitride nanoparticle containing nitrogen-doped carbon composites is presented. Since ionic liquids also offer outstanding solubility properties, the materials can be generated through the carbonization of homogeneous solutions of an ionic liquid acting as nitrogen as well as carbon source and the respective metal precursor. The metal content and surface area are easily tunable via the initial metal precursor amount. Furthermore, it is also possible to synthesize composites with ternary nitride nanoparticles whose composition is adjustable by the metal ratio in the precursor solution. Finally, both approaches are combined into salt templating of the one-pot composites. This opens the way to the one-step synthesis of composites with tunable composition, particle size as well as precisely controllable porosity and morphology. Thereby, common synthesis strategies where the product composition is often negatively affected by the template removal procedure can be avoided. The composites are further shown to be suitable as electrodes for supercapacitors. Here, different properties such as porosity, metal content and particle size are investigated and discussed with respect to their influence on the energy storage performance. Because a variety of ionic liquids, metal precursors and salts can be combined and a simple closed-loop process including salt recycling is imaginable, the approaches present a promising platform toward sustainable materials design.
The underlying motivation for the work carried out for this thesis was the growing need for more sustainable technologies. The aim was to synthesize a “palette” of functional nanomaterials using the established technique of hydrothermal carbonization (HTC). The incredible diversity of HTC was demonstrated together with small but steady advances in how HTC can be manipulated to tailor material properties for specific applications. Two main strategies were used to modify the materials obtained by HTC of glucose, a model precursor representing biomass. The first approach was the introduction of heteroatoms, or “doping” of the carbon framework. Sulfur was for the first time introduced as a dopant in hydrothermal carbon. The synthesis of sulfur and sulfur/nitrogen doped microspheres was presented whereby it was shown that the binding state of sulfur could be influenced by varying the type of sulfur source. Pyrolysis may additionally be used to tune the heteroatom binding states which move to more stable motifs with increasing pyrolysis temperature. Importantly, the presence of aromatic binding states in the as synthesized hydrothermal carbon allows for higher heteroatom retention levels after pyrolysis and hence more efficient use of dopant sources. In this regard, HTC may be considered as an “intermediate” step in the formation of conductive heteroatom doped carbon. To assess the novel hydrothermal carbons in terms of their potential for electrochemical applications, materials with defined nano-architectures and high surface areas were synthesized via templated, as well as template-free routes. Sulfur and/or nitrogen doped carbon hollow spheres (CHS) were synthesized using a polystyrene hard templating approach and doped carbon aerogels (CA) were synthesized using either the albumin directed or borax-mediated hydrothermal carbonization of glucose. Electrochemical testing showed that S/N dual doped CHS and aerogels derived via the albumin approach exhibited superior catalytic performance compared to solely nitrogen or sulfur doped counterparts in the oxygen reduction reaction (ORR) relevant to fuel cells. Using the borax mediated aerogel formation, nitrogen content and surface area could be tuned and a carbon aerogel was engineered to maximize electrochemical performance. The obtained sample exhibited drastically improved current densities compared to a platinum catalyst (but lower onset potential), as well as excellent long term stability. In the second approach HTC was carried out at elevated temperatures (550 °C) and pressure (50 bar), corresponding to the superheated vapor regime (htHTC). It was demonstrated that the carbon materials obtained via htHTC are distinct from those obtained via ltHTC and subsequent pyrolysis at 550 °C. No difference in htHTC-derived material properties could be observed between pentoses and hexoses. The material obtained from a polysaccharide exhibited a slightly lower degree of carbonization but was otherwise similar to the monosaccharide derived samples. It was shown that in addition to thermally induced carbonization at 550 °C, the SHV environment exhibits a catalytic effect on the carbonization process. The resulting materials are chemically inert (i.e. they contain a negligible amount of reactive functional groups) and possess low surface area and electronic conductivity which distinguishes them from carbon obtained from pyrolysis. Compared to the materials presented in the previous chapters on chemical modifications of hydrothermal carbon, this makes them ill-suited candidates for electronic applications like lithium ion batteries or electrocatalysts. However, htHTC derived materials could be interesting for applications that require chemical inertness but do not require specific electronic properties. The final section of this thesis therefore revisited the latex hard templating approach to synthesize carbon hollow spheres using htHTC. However, by using htHTC it was possible to carry out template removal in situ because the second heating step at 550 °C was above the polystyrene latex decomposition temperature. Preliminary tests showed that the CHS could be dispersed in an aqueous polystyrene latex without monomer penetrating into the hollow sphere voids. This leaves the stagnant air inside the CHS intact which in turn is promising for their application in heat and sound insulating coatings. Overall the work carried out in this thesis represents a noteworthy development in demonstrating the great potential of sustainable carbon materials.
The need to reduce humankind reliance on fossil fuels by exploiting sustainably the planet renewable resources is a major driving force determining the focus of modern material research. For this reason great interest is nowadays focused on finding alternatives to fossil fuels derived products/materials. For the short term the most promising substitute is undoubtedly biomass, since it is the only renewable and sustainable alternative to fossil fuels as carbon source. As a consequence efforts, aimed at finding new synthetic approaches to convert biomass and its derivatives into carbon-based materials, are constantly increasing. In this regard, hydrothermal carbonisation (HTC) has shown to be an effective means of conversion of biomass-derived precursors into functional carbon materials. However the attempts to convert raw biomass, in particular lignocellulosic one, directly into such products have certainly been rarer. Unlocking the direct use of these raw materials as carbon precursors would definitely be beneficial in terms of HTC sustainability. For this reason, in this thesis the HTC of carbohydrate and protein-rich biomass was systematically investigated, in order to obtain more insights on the potentials of this thermochemical processing technique in relation to the production of functional carbon materials from crude biomass. First a detailed investigation on the HTC conversion mechanism of lignocellulosic biomass and its single components (i.e. cellulose, lignin) was developed based on a comparison with glucose HTC, which was adopted as a reference model. In the glucose case it was demonstrated that varying the HTC temperature allowed tuning the chemical structure of the synthesised carbon materials from a highly cross-linked furan-based structure (T = 180oC) to a carbon framework composed of polyaromatic arene-like domains. When cellulose or lignocellulosic biomass was used as carbon precursor, the furan rich structure could not be isolated at any of the investigated processing conditions. These evidences were indicative of a different HTC conversion mechanism for cellulose, involving reactions that are commonly observed during pyrolytic processes. The evolution of glucose-derived HTC carbon chemical structure upon pyrolysis was also investigated. These studies revealed that upon heat treatment (Investigated temperatures 350 – 900 oC) the furan-based structure was progressively converted into highly curved aromatic pre-graphenic domains. This thermal degradation process was observed to produce an increasingly more hydrophobic surface and considerable microporosity within the HTC carbon structure. In order to introduce porosity in the HTC carbons derived from lignocellulosic biomass, KOH chemical activation was investigated as an HTC post-synthesis functionalisation step. These studies demonstrated that HTC carbons are excellent precursors for the production of highly microporous activated carbons (ACs) and that the porosity development upon KOH chemical activation is dependent on the chemical structure of the HTC carbon, tuned by employing different HTC temperatures. Preliminary testing of the ACs for CO2 capture or high pressure CH4 storage yielded very promising results, since the measured uptakes of both adsorbates (i.e. CO2 and CH4) were comparable to top-performing and commercially available adsorbents, usually employed for these end-applications. The combined use of HTC and KOH chemical activation was also employed to produce highly microporous N-doped ACs from microalgae. The hydrothermal treatment of the microalgae substrate was observed to cause the depletion of the protein and carbohydrate fractions and the near complete loss (i.e. 90%) of the microalgae N-content, as liquid hydrolysis/degradation products. The obtained carbonaceous product showed a predominantly aliphatic character indicating the presence of alkyl chains presumably derived from the lipid fractions. Addition of glucose to the initial reaction mixture was found out to be extremely beneficial, because it allowed the fixation of a higher N amount, in the algae derived HTC carbons (i.e. 60%), and the attainment of higher product yields (50%). Both positive effects were attributed to Maillard type cascade reactions taking place between the monosaccharides and the microalgae derived liquid hydrolysis/degradation products, which were in this way recovered from the liquid phase. KOH chemical activation of the microalgae/glucose mixture derived HTC carbons produced highly microporous N-doped carbons. Although the activation process led to a major reduction of the N-content, the retained N-amount in the ACs was still considerable. These features render these materials ideal candidates for supercapacitors electrodes, since they provide extremely high surface areas, for the formation of electric double-layer, coupled to abundant heteroatom doping (i.e. N and O) necessary to obtain a pseudocapacitance contribution.
Eye movements are a powerful tool to examine cognitive processes. However, in most paradigms little is known about the dynamics present in sequences of saccades and fixations. In particular, the control of fixation durations has been widely neglected in most tasks. As a notable exception, both spatial and temporal aspects of eye-movement control have been thoroughly investigated during reading. There, the scientific discourse was dominated by three controversies, (i), the role of oculomotor vs. cognitive processing on eye-movement control, (ii) the serial vs. parallel processing of words, and, (iii), the control of fixation durations. The main purpose of this thesis was to investigate eye movements in tasks that require sequences of fixations and saccades. While reading phenomena served as a starting point, we examined eye guidance in non-reading tasks with the aim to identify general principles of eye-movement control. In addition, the investigation of eye movements in non-reading tasks helped refine our knowledge about eye-movement control during reading. Our approach included the investigation of eye movements in non-reading experiments as well as the evaluation and development of computational models. I present three main results : First, oculomotor phenomena during reading can also be observed in non-reading tasks (Chapter 2 & 4). Oculomotor processes determine the fixation position within an object. The fixation position, in turn, modulates both the next saccade target and the current fixation duration. Second, predicitions of eye-movement models based on sequential attention shifts were falsified (Chapter 3). In fact, our results suggest that distributed processing of multiple objects forms the basis of eye-movement control. Third, fixation durations are under asymmetric control (Chapter 4). While increasing processing demands immediately prolong fixation durations, decreasing processing demands reduce fixation durations only with a temporal delay. We propose a computational model ICAT to account for asymmetric control. In this model, an autonomous timer initiates saccades after random time intervals independent of ongoing processing. However, processing demands that are higher than expected inhibit the execution of the next saccade and, thereby, prolong the current fixation. On the other hand, lower processing demands will not affect the duration before the next saccade is executed. Since the autonomous timer adjusts to expected processing demands from fixation to fixation, a decrease in processing demands may lead to a temporally delayed reduction of fixation durations. In an extended version of ICAT, we evaluated its performance while simulating both temporal and spatial aspects of eye-movement control. The eye-movement phenomena investigated in this thesis have now been observed in a number of different tasks, which suggests that they represent general principles of eye guidance. I propose that distributed processing of the visual input forms the basis of eye-movement control, while fixation durations are controlled by the principles outlined in ICAT. In addition, oculomotor control contributes considerably to the variability observed in eye movements. Interpretations for the relation between eye movements and cognition strongly benefit from a precise understanding of this interplay.
Thermal and quantum fluctuations of the electromagnetic near field of atoms and macroscopic bodies play a key role in quantum electrodynamics (QED), as in the Lamb shift. They lead, e.g., to atomic level shifts, dispersion interactions (Van der Waals-Casimir-Polder interactions), and state broadening (Purcell effect) because the field is subject to boundary conditions. Such effects can be observed with high precision on the mesoscopic scale which can be accessed in micro-electro-mechanical systems (MEMS) and solid-state-based magnetic microtraps for cold atoms (‘atom chips’). A quantum field theory of atoms (molecules) and photons is adapted to nonequilibrium situations. Atoms and photons are described as fully quantized while macroscopic bodies can be included in terms of classical reflection amplitudes, similar to the scattering approach of cavity QED. The formalism is applied to the study of nonequilibrium two-body potentials. We then investigate the impact of the material properties of metals on the electromagnetic surface noise, with applications to atomic trapping in atom-chip setups and quantum computing, and on the magnetic dipole contribution to the Van der Waals-Casimir-Polder potential in and out of thermal equilibrium. In both cases, the particular properties of superconductors are of high interest. Surface-mode contributions, which dominate the near-field fluctuations, are discussed in the context of the (partial) dynamic atomic dressing after a rapid change of a system parameter and in the Casimir interaction between two conducting plates, where nonequilibrium configurations can give rise to repulsion.