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Institut
- Institut für Biochemie und Biologie (48)
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This thesis investigates the processing and representation of (ir-)regularity in inflectional verb morphology in German and English. The focus lies on the predictions from models of morphological processing about the production of subtypes of irregular verbs which are usually subsumed under the category `irregular verbs'. Thus, this dissertation presents three journal articles investigating the language production of healthy speakers and speakers with agrammatic aphasia in order to fill a gap both for the availability of language production data and systematically tested patterns of irregularity. The second Chapter set out to investigate whether regularity of a verb or its phonological complexity (measured in number of phonemes) better predict the production accuracies of German speakers with agrammatic aphasia. While regular verbs were significantly more often correct than mixed and irregular verbs, production accuracies of irregular and mixed verbs for impaired participants did not differ. Thus, no influence of phonological complexity was observed. Chapter 3 aimed at teasing apart the influence of stem changes and affix type on the production accuracies of English speaking individuals with agrammatic aphasia. The analyses revealed that the presence of stem changes but not the type of affix had a significant effect on the production accuracies. Moreover, as four different verb types were tested, results showed that production accuracies did not conform to a regular-irregular distinction but that accuracies differed by the degree of regularity. In Chapter 4, long-lag primed picture naming design was used to study if the differences found in the production accuracies of Chapter 3 were also associated with differences in production latencies of non-brain damaged speakers. A morphological priming effect was found, however, in neither experiment the effect differed of the three verb types tested. In addition to standard frequentist analysis, Bayesian analysis were performed. In this way the absence of a difference of the morphological priming effect between verb types was interpreted as actual evidence for the lack of such a difference. Hence, this thesis presents diverging results on the production of subtypes of irregular verbs in healthy and impaired adult speakers. However, at the same time these results provided evidence that the conventional regular-irregular distinction is not adequate for testing models of morphological processing.
Cellular membranes constantly experience remodeling, as exemplified by morphological changes during endo- and exocytosis. Regulation of membrane morphology is essential for these processes. In this work, we attempt to establish a regulation path based on the use of photoswitches exhibiting conformational changes in model membranes, namely, giant unilamellar vesicles (GUVs). The mechanism of the changes in the GUVs’ morphology caused by isomerization of the photosensitive molecules has been previously explored but still remains elusive. We examine the morphological reshaping of GUVs in the presence of the photoswitch o-tetrafluoroazobenzene (F-azo) and show that the mechanism behind the resulting morphological changes involves both an increase in the membrane area and generation of a positive spontaneous curvature. First, we characterize the partitioning of F-azo in a single-component membrane using both experimental and computational approaches. The partition coefficient calculated from molecular dynamic simulations agrees with experimental data obtained with size-exclusion chromatography. Then, we implement the approach of vesicle electrodeformation in order to assess the increase in the membrane area, which is observed as a result of the conformational change of F-azo. Finally, the local and the effective membrane spontaneous curvatures were estimated from the observed shapes of vesicles exhibiting outward budding. We then extend the application of the F-azo to multicomponent lipid membranes, which exhibit a coexistence of domains in different liquid phases due to a miscibility gap between the lipids. We perform initial experiments to investigate whether F-azo can be employed to modulate the lateral lipid packing and organization. We observe either complete mixing of the domains or the appearing of disordered domains within the domains of more ordered phase. The type of behavior observed in response to the photoisomerization of F-azo was dependent on the used lipid composition. We believe that the findings introduced here will have an impact in understanding and controlling both lipid phase modulation and regulation of the membrane morphology in membrane systems.
Lignin valorization
(2017)
The topic of this project is the use of lignin as alternative source of aromatic building blocks and oligomers to fossil feedstocks. Lignin is known as the most abundant aromatic polymer in nature and is isolated from the lignocellulosic component of plants by different possible extraction treatments. Both the biomass source and the extraction method affect the structure of the isolated lignin, therefore influencing its further application. Lignin was extracted from beech wood by two different hydrothermal alkaline treatments, which use NaOH and Ba(OH)2 as base and by an acid-catalyzed organosolv process. Moreover, lignin was isolated from bamboo, beech wood and coconut by soda treatment of the biomasses. A comparison of the structural features of such isolated lignins was performed through the use of a wide range of analytical methods. Alkaline lignins resulted in a better candidate as carbon precursor and macromonomers for the synthesis of polymer than organosolv lignin. In fact, alkaline lignins showed higher residual mass after carbonization and higher content of the reactive hydroxy functionalities. In contrast, the lignin source turned out to slightly affect the lignin hydroxyl content.
One of the most common lignin modifications is its deconstruction to obtain aromatic molecules, which can be used as starting materials for the synthesis of fine chemicals. Lignin deconstruction leads to a complex mixture of aromatic molecules. A gas chromatographic analytical method was developed to characterize the mixture of products obtained by lignin deconstruction via heterogeneous catalytic hydrogenolysis. The analytical protocol allowed the quantification of three main groups of molecules by means of calibration curves, internal standard and a preliminary silylation step of the sample. The analytical method was used to study the influence of the hydrogenolysis catalyst, temperature and system (flow and batch reactor) on the yield and selectivity of the aromatic compounds.
Lignin extracted from beech wood by a hydrothermal process using Ba(OH)2 as base, was functionalized by aromatic nitration in order to add nitrogen functionalities. The final goal was the synthesis of a nitrogen doped carbon. Nitrated lignin was reduced to the amino form in order to compare the influence of different nitrogen functionalities on the porosity of the final carbon. The carbons were obtained by ionothermal treatment of the precursors in the presence of the eutectic salt mixture KCl/ZnCl2 Such synthesized carbons showed micro-, macro- and mesoporosity and were tested for their electrocatalytic activity towards the oxygen reduction reaction. Mesoporous carbon derived from nitro lignin displayed the highest electrocatalytic activity.
Lignins isolated from coconut, beech wood and bamboo were used as macromonomers for the synthesis of biobased polyesters. A condensation reaction was performed between lignin and a hyper branched poly(ester-amine), previously obtained by condensation of triethanolamine and adipic acid. The influence of the lignin source and content on the thermochemical and mechanical properties of the final material was investigated. The prepolymer showed adhesive properties towards aluminum and its shear strength was therefore measured. The gluing properties of such synthesized glues turned out to be independent from the lignin source but affected by the amount of lignin in the final material.
This work shows that, although still at a laboratory scale, the valorization of lignin can overcome the critical issues of lignin´s structure variability and complexity.
Lithospheric plates move over the low viscosity asthenosphere balancing several forces. The driving forces include basal shear stress exerted by mantle convection and plate boundary forces such as slab pull and ridge push, whereas the resisting forces include inter-plate friction, trench resistance, and cratonic root resistance. These generate plate motions, the lithospheric stress field and dynamic topography which are observed with different geophysical methods. The orientation and tectonic regime of the observed crustal/lithospheric stress field further contribute to our knowledge of different deformation processes occurring within the Earth's crust and lithosphere. Using numerical models previous studies were able to identify major forces generating stresses in the crust and lithosphere which also contribute to the formation of topography as well as driving lithospheric plates. They showed that the first-order stress pattern explaining about 80\,\% of the stress field originates from a balance of forces acting at the base of the moving lithospheric plates due to convective flow in the underlying mantle. The remaining second-order stress pattern is due to lateral density variations in the crust and lithosphere in regions of pronounced topography and high gravitational potential, such as the Himalayas and mid-ocean ridges. By linking global lithosphere dynamics to deep mantle flow this study seeks to evaluate the influence of shallow and deep density heterogenities on plate motions, lithospheric stress field and dynamic topography using the geoid as a major constraint for mantle rheology. We use the global 3D lithosphere-asthenosphere model SLIM3D with visco-elasto-plastic rheology coupled at 300 km depth to a spectral model of mantle flow. The complexity of the lithosphere-asthenosphere component allows for the simulation of power-law rheology with creep parameters accounting for both diffusion and dislocation creep within the uppermost 300 km.
First we investigate the influence of intra-plate friction and asthenospheric viscosity on present-day plate motions. Previous modelling studies have suggested that small friction coefficients (µ < 0.1, yield stress ~ 100 MPa) can lead to plate tectonics in models of mantle convection. Here we show that, in order to match present-day plate motions and net rotation, the frictional parameter must be less than 0.05. We are able to obtain a good fit with the magnitude and orientation of observed plate velocities (NUVEL-1A) in a no-net-rotation (NNR) reference frame with µ < 0.04 and minimum asthenosphere viscosity ~ 5*10e19 Pas to 10e20 Pas. Our estimates of net rotation (NR) of the lithosphere suggest that amplitudes ~ 0.1-0.2 °/Ma, similar to most observation-based estimates, can be obtained with asthenosphere viscosity cutoff values of ~ 10e19 Pas to 5*10e19 Pas and friction coefficient µ < 0.05.
The second part of the study investigates further constraints on shallow and deep mantle heterogeneities causing plate motion by predicting lithosphere stress field and topography and validating with observations. Lithosphere stresses and dynamic topography are computed using the modelling setup and rheological parameters for prescribed plate motions. We validate our results with the World Stress Map 2016 (WSM2016) and the observed residual topography. Here we tested a number of upper mantle thermal-density structures. The one used to calculate plate motions is considered the reference thermal-density structure. This model is derived from a heat flow model combined with a sea floor age model. In addition we used three different thermal-density structures derived from global S-wave velocity models to show the influence of lateral density heterogeneities in the upper 300 km on model predictions. A large portion of the total dynamic force generating stresses in the crust/lithosphere has its origin in the deep mantle, while topography is largely influenced by shallow heterogeneities. For example, there is hardly any difference between the stress orientation patterns predicted with and without consideration of the heterogeneities in the upper mantle density structure across North America, Australia, and North Africa. However, the crust is dominant in areas of high altitude for the stress orientation compared to the all deep mantle contribution.
This study explores the sensitivity of all the considered surface observables with regards to model parameters providing insights into the influence of the asthenosphere and plate boundary rheology on plate motion as we test various thermal-density structures to predict stresses and topography.
Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles.
Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations.
Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years.
Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect.
Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication.
Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified.
Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk.
Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures.
Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes.
The ionosphere, which is strongly influenced by the Sun, is known to be also affected by meteorological processes. These processes, despite having their origin in the troposphere and stratosphere, interact with the upper atmosphere. Such an interaction between atmospheric layers is known as vertical coupling. During geomagnetically quiet times, when near-Earth space is not under the influence of solar storms, these processes become important drivers for ionospheric variability. Studying the link between these processes in the lower atmosphere and the ionospheric variability is important for our understanding of fundamental mechanisms in ionospheric and meteorological research.
A prominent example of vertical coupling between the stratosphere and the ionosphere are the so-called stratospheric sudden warming (SSW) events that occur usually during northern winters and result in an increase in the polar stratospheric temperature and a reversal of the circumpolar winds. While the phenomenon of SSW is confined to the northern polar stratosphere, its influence on the ionosphere can be observed even at equatorial latitudes. During SSW events, the connection between the polar stratosphere and the equatorial ionosphere is believed to be through the modulation of global atmospheric tides. These tides are fundamental for the ionospheric E-region wind dynamo that generates electric fields and currents in the ionosphere. Observations of ionospheric currents indicate a large enhancement of the semidiurnal lunar tide in response to SSW events. Thus, the semidiurnal lunar tide becomes an important driver of ionospheric variability during SSW events.
In this thesis, the ionospheric effect of SSW events is investigated in the equatorial region, where a narrow but an intense E-region current known as the equatorial electrojet (EEJ) flows above the dip equator during the daytime. The day-to-day variability of the EEJ can be determined from magnetic field records at geomagnetic observatories close to the dip equator. Such magnetic data are available for several decades and allows to investigate the impact of SSW events on the EEJ and, even more importantly, helps in understanding the effects of SSW events on the equatorial ionosphere. An excellent long-term record of the geomagnetic field at the equator from 1922 onwards is available for the observatory Huancayo in Peru and is extensively utilized in this study.
The central subject of this thesis is the investigation of lunar tides in the EEJ during SSW events by analyzing long time series. This is done by estimating the lunar tidal amplitude in the EEJ from the magnetic records at Huancayo and by comparing them to measurements of the polar stratospheric wind and temperature, which led to the identification of the known SSW events from 1952 onwards. One goal of this thesis is to identify SSW events that predate 1952. To this end, superposed epoch analysis (SEA) is employed to establish a relationship between the lunar tidal power and the wind and temperature conditions in the lower atmosphere. A threshold value for the lunar tidal power is identified that is discriminative for the known SSW events. This threshold is then used to identify lunar tidal enhancements, which are indicative for any historic SSW events prior to 1952. It can be shown, that the number of lunar tidal enhancements and thus the occurrence frequency of historic SSW events between 1926 and 1952 is similar to the occurrence frequency of the known SSW events from 1952 onwards.
Next to the classic SSW definition, the concept of polar vortex weakening (PVW) is utilized in this thesis. PVW is defined for higher latitudes and altitudes (≈ 40km) than the classical SSW definition (≈ 32km). The correlation between the timing and magnitude of lunar tidal enhancements in the EEJ and the timing and magnitude of PVW is found to be better than for the classic SSW definition. This suggests that the lunar tidal enhancements in the EEJ are closely linked to the state of the middle atmosphere.
Geomagnetic observatories located in different longitudes at the dip equator allow investigating the longitudinally dependent variability of the EEJ during SSW events. For this purpose, the lunar tidal enhancements in the EEJ are determined for the Peruvian and Indian sectors during the major SSW events of the years 2006 and 2009. It is found that the lunar tidal amplitude shows similar enhancements in the Peruvian sector during both SSW events, while the enhancements are notably different for the two events in the Indian sector.
In summary, this thesis shows that lunar tidal enhancements in the EEJ are indeed correlated to the occurrence of SSW events and they should be considered a prominent driver of low latitude ionospheric variability. Secondly, lunar tidal enhancements are found to be longitudinally variable. This suggests that regional effects, such as ionospheric conductivity and the geometry and strength of the geomagnetic field, also play an important role and have to be considered when investigating the mechanisms behind vertical coupling.
Proteins are molecules that are essential for life and carry out an enormous number of functions in organisms. To this end, they change their conformation and bind to other molecules. However, the interplay between conformational change and binding is not fully understood. In this work, this interplay is investigated with molecular dynamics (MD) simulations of the protein-peptide system Mdm2-PMI and by analysis of data from relaxation experiments.
The central task it to uncover the binding mechanism, which is described by the sequence of (partial) binding events and conformational change events including their probabilities. In the simplest case, the binding mechanism is described by a two-step model: binding followed by conformational change or conformational change followed by binding. In the general case, longer sequences with multiple conformational changes and partial binding events are possible as well as parallel pathways that differ in their sequences of events. The theory of Markov state models (MSMs) provides the theoretical framework in which all these cases can be modeled. For this purpose, MSMs are estimated in this work from MD data, and rate equation models, which are related to MSMs, are inferred from experimental relaxation data.
The MD simulation and Markov modeling of the PMI-Mdm2 system shows that PMI and Mdm2 can bind via multiple pathways. A main result of this work is a dissociation rate on the order of one event per second, which was calculated using Markov modeling and is in agreement with experiment. So far, dissociation rates and transition rates of this magnitude have only been calculated with methods that speed up transitions by acting with time-dependent, external forces on the binding partners. The simulation technique developed in this work, in contrast, allows the estimation of dissociation rates from the combination of free energy calculation and direct MD simulation of the fast binding process. Two new statistical estimators TRAM and TRAMMBAR are developed to estimate a MSM from the joint data of both simulation types.
In addition, a new analysis technique for time-series data from chemical relaxation experiments is developed in this work. It allows to identify one of the above-mentioned two-step mechanisms as the mechanism that underlays the data. The new method is valid for a broader range of concentrations than previous methods and therefore allows to choose the concentrations such that the mechanism can be uniquely identified. It is successfully tested with data for the binding of recoverin to a rhodopsin kinase peptide.
Hintergrund: Die Untersuchung von Ernährungsmustern als komplementärer Ansatz zu der Untersuchung einzelner Lebensmittel nimmt stetig zu. Generell können drei verschiedene Ansätze unterschieden werden um Ernährungsmuster herzuleiten: A priori Indizes, welche das Wissen über gesundheitsförderliche und –schädliche Eigenschaften eines Lebensmittels für einen gewissen Endpunkt nutzen; A posteriori (exploratorische) Ernährungsmuster, welche die populationsspezifischen vorliegenden Daten ohne eine vorangegangene Hypothese nutzen; gemischte Methoden, die das Wissen über bestimmte Nährstoffe oder Biomarker, welche in der Krankheitsentstehung eine Rolle spielen, nutzen und mit einer exploratorischen Methode kombinieren um krankheitsrelevante Ernährungsmuster zu generieren. Vorangegangene systematische Übersichtsarbeiten, welche die Evidenz der Assoziation zwischen Ernährungsmustern und Diabetes mellitus Typ 2 zusammenfassten, waren entweder beschränkt auf eine Mustermethode oder kombinierten die Muster verschiedener Methoden, ohne die Zusammensetzung der Ernährungsmuster zu berücksichtigen.
Ziel: Das Ziel dieser Dissertation war eine umfassende Untersuchung der Assoziation von Ernährungsmustern mit Diabetes mellitus Typ 2. Das erste Teilprojekt zielte auf die Erstellung einer systematischen Übersichtsarbeit von prospektiven Studien ab, unter der Berücksichtigung der verschiedenen Methoden zur Herleitung von Ernährungsmustern in der meta-analytischen Zusammenfassung, was in vorangegangen Übersichtsarbeiten eine Limitation darstellte. Das zweite Teilprojekt hatte die Untersuchung der Assoziation mit Diabetes mellitus Typ 2 von exploratorischen Ernährungsmustern, welche mit der Hauptkomponentenanalyse in einer multi-zentrischen europäischen Fall-Kohorten Studie hergeleitet wurden, zum Ziel. Des Weiteren wurde der eingeschränkten Anwendbarkeit von exploratorischen Mustern in anderen Studienpopulationen mit Methoden der Replikation dieser Ernährungsmuster begegnet.
Methoden: Im ersten Teilprojekt wurde eine systematische Literatursuche in den Datenbanken MEDLINE und Web of Science vorgenommen, sowie ein dreistufiger Screeningprozess. Die identifizierten Studien wurden nach den jeweiligen Methoden zur Erstellung von Ernährungsmustern zusammengefasst und Meta-Analysen nur für diejenigen Ernährungsmuster mit vergleichbarer Zusammensetzung vorgenommen. Im zweiten Teilprojekt wurden länderspezifische Ernährungsmuster mittels Hauptkomponentenanalyse aus 36 standardisierten Lebensmittelgruppen hergeleitet. Die Assoziation mit Diabetes mellitus Typ 2 Risiko wurde mit verschieden adjustierten Cox Regressionsmodellen zur Berechnung von Hazardratenverhältnissen untersucht. Die Ernährungsmuster, welche eine signifikante Assoziation mit dem Diabetesrisiko aufzeigten, wurden anschließend über alle Länder in der EPIC-InterAct Studie repliziert: Entweder wurden Summenscores ungewichteter standardisierter Lebensmittelgruppen berechnet (wenn die Korrelation mit dem originalen Ernährungsmuster r ≥ 0.90 war) oder Summenscores der Produkte von standardisierten Scoringkoeffizienten mit standardisierten Lebensmittelgruppen (wenn die Korrelation mit dem originalen Ernährungsmuster r < 0.90). Die resultierenden Scores wurden standardisiert nach der Verteilung der gesamten EPIC-InterAct Subkohorte, dann in jedem Land angewendet und die Assoziation mit Diabetes mellitus Typ 2 anhand der Cox Regressionsmodelle berechnet. Anschließend wurden Meta-Analysen zur Berechnung der gepoolten Schätzer durchgeführt.
Ergebnisse: Im ersten Teilprojekt ergab die Literatursuche 48 Artikel, welche 16 Kohorten umfassten. Die Einhaltung der Mediterranen Diät (relatives Risiko (RR) für den Vergleich der extremen Quantile: 0,87; 95%-Konfidenzintervall (KI): 0,82, 0,93), der DASH Diät (RR: 0,81; 95%-KI: 0,72, 0,92) und des Alternative Healthy Eating Index (AHEI) (RR: 0,79; 95%-KI: 0,69, 0,90) war mit einer signifikanten Reduzierung des Diabetesrisikos assoziiert. Exploratorische Ernährungsmuster, charakterisiert durch rotes und verarbeitetes Fleisch, prozessiertes Getreide, hochfette Milchprodukte, Eier und frittierte Produkte, waren positiv mit dem Diabetesrisiko assoziiert (RR: 1,44; 95%-KI: 1,27, 1,62), während Ernährungs-muster, charakterisiert durch Gemüse, Hülsenfrüchte, Obst, Geflügel und Fisch, invers mit dem Diabetesrisiko assoziiert waren (RR: 0,84; 95%-KI: 0,77, 0,91). Ernährungsmuster, welche mit reduzierter Rangregression hergeleitet wurden und charakterisiert waren durch eine hohe Aufnahme von prozessiertem Getreide, zuckergesüßten Getränken und verarbeitetem Fleisch und einen niedrigen Weinkonsum, waren alle signifikant mit dem Diabetesrisiko assoziiert. Im zweiten Teilprojekt konnten zwei wesentliche Ernährungsmuster in jedem Land mit der Hauptkomponentenanalyse hergeleitet werden. Ein Ernährungsmuster, welches in Frankreich hergeleitet wurde und charakterisiert war durch Nüsse, andere Früchte, verarbeitetes Fleisch, Fisch, Eier, Kuchen und Kekse, Kaffee und andere alkoholische Getränke, war signifikant assoziiert mit einem erniedrigten Diabetesrisiko. Drei andere Ernährungsmuster, hergeleitet in Spanien, Norfolk und Oxford, welche sich erheblich in ihrer Zusammensetzung unterschieden, waren mit einem erhöhten Diabetesrisiko assoziiert. Keine der Replikationen dieser vier Ernährungsmuster konnte die signifikante Assoziation mit Diabetes mellitus Typ 2 über andere Länder bestätigen.
Schlussfolgerung: Aus der systematischen Übersichtsarbeit ließ sich schlussfolgern, dass Ernährungsweisen gemäß der Mediterranen Diät, DASH und AHEI ein starkes Potenzial zur Prävention von Diabetes mellitus Typ 2 zu haben, obwohl sie sich in einigen Komponenten unterscheiden. Exploratorische Ernährungsmuster wurden basierend auf konkordanten Lebensmitteln gruppiert und waren signifikant mit dem Diabetesrisiko assoziiert, auch wenn die Untersuchungen einzelner Lebensmittel eher begrenzte Evidenz für einen Zusammenhang aufwiesen. Trotzdem bleiben sie populationsspezifische Beobachtungen. Das wurde auch in dem zweiten Teilprojekt unterstrichen, als länderspezifische Ernährungsmuster generiert wurden und keines der Ernährungsmuster, welches signifikant mit dem Diabetesrisiko assoziiert war, durch Simplifizierung oder Replikation der Musterstruktur des Originalmusters über alle Länder bestätigt werden konnte. Für drei RRR-Muster konnten konsistente positive Assoziationen mit dem Diabetesrisiko über verschiedene Studienpopulationen beobachtet werden.
The timing and location of the two largest earthquakes of the 21st century (Sumatra, 2004 and Tohoku 2011, events) greatly surprised the scientific community, indicating that the deformation processes that precede and follow great megathrust earthquakes remain enigmatic. During these phases before and after the earthquake a combination of multi-scale complex processes are acting simultaneously: Stresses built up by long-term tectonic motions are modified by sudden jerky deformations during earthquakes, before being restored by multiple ensuing relaxation processes.
This thesis details a cross-scale thermomechanical model developed with the aim of simulating the entire subduction process from earthquake (1 minute) to million years’ time scale, excluding only rupture propagation. The model employs elasticity, non-linear transient viscous rheology, and rate-and-state friction. It generates spontaneous earthquake sequences, and, by using an adaptive time-step algorithm, recreates the deformation process as observed naturally over single and multiple seismic cycles. The model is thoroughly tested by comparing results to those from known high- resolution solutions of generic modeling setups widely used in modeling of rupture propagation. It is demonstrated, that while not modeling rupture propagation explicitly, the modeling procedure correctly recognizes the appearance of instability (earthquake) and correctly simulates the cumulative slip at a fault during great earthquake by means of a quasi-dynamic approximation.
A set of 2D models is used to study the effects of non-linear transient rheology on the postseismic processes following great earthquakes. Our models predict that the viscosity in the mantle wedge drops by 3 to 4 orders of magnitude during a great earthquake with magnitude above 9. This drop in viscosity results in spatial scales and timings of the relaxation processes following the earthquakes that are significantly different to previous estimates. These models replicate centuries long seismic cycles exhibited by the greatest earthquakes (like the Great Chile 1960 Earthquake) and are consistent with the major features of postseismic surface displacements recorded after the Great Tohoku Earthquake.
The 2D models are also applied to study key factors controlling maximum magnitudes of earthquakes in subduction zones. Even though methods of instrumentally observing earthquakes at subduction zones have rapidly improved in recent decades, the characteristic recurrence interval of giant earthquakes (Mw>8.5) is much larger than the currently available observational record and therefore the necessary conditions for giant earthquakes are not clear. Statistical studies have recognized the importance of the slab shape and its surface roughness, state of the strain of the upper plate and thickness of sediments filling the trenches. In this thesis we attempt to explain these observations and to identify key controlling parameters. We test a set of 2D models representing great earthquake seismic cycles at known subduction zones with various known geometries, megathrust friction coefficients, and convergence rates implemented. We found that low-angle subduction (large effect) and thick sediments in the subduction channel (smaller effect) are the fundamental necessary conditions for generating giant earthquakes, while the change of subduction velocity from 10 to 3.5 cm/yr has a lower effect. Modeling results also suggest that having thick sediments in the subduction channel causes low static friction, resulting in neutral or slightly compressive deformation in the overriding plate for low-angle subduction zones. These modeling results agree well with observations for the largest earthquakes. The model predicts the largest possible earthquakes for subduction zones of given dipping angles. The predicted maximum magnitudes exactly threshold magnitudes of all known giant earthquakes of 20th and 21st centuries.
The clear limitation of most of the models developed in the thesis is their 2D nature. Development of 3D models with comparable resolution and complexity will require significant advances in numerical techniques. Nevertheless, we conducted a series of low-resolution 3D models to study the interaction between two large asperities at a subduction interface separated by an aseismic gap of varying width. The novelty of the model is that it considers behavior of the asperities during multiple seismic cycles. As expected, models show that an aseismic gap with a narrow width could not prevent rupture propagation from one asperity to another, and that rupture always crosses the entire model. When the gap becomes too wide, asperities do not interact anymore and rupture independently. However, an interesting mode of interaction was observed in the model with an intermediate width of the aseismic gap: In this model the asperities began to stably rupture in anti-phase following multiple seismic cycles. These 3D modeling results, while insightful, must be considered preliminary because of the limitations in resolution.
The technique developed in this thesis for cross-scale modeling of seismic cycles can be used to study the effects of multiple seismic cycles on the long-term deformation of the upper plate. The technique can be also extended to the case of continental transform faults and for the advanced 3D modeling of specific subduction zones. This will require further development of numerical techniques and adaptation of the existing advanced highly scalable parallel codes like LAMEM and ASPECT.
For several decades, researchers have tried to explain how speakers of more than one language (multilinguals) manage to keep their languages separate and to switch from one language to the other depending on the context. This ability of multilingual speakers to use the intended language, while avoiding interference from the other language(s) has recently been termed “language control”.
A multitude of studies showed that when bilinguals process one language, the other language is also activated and might compete for selection. According to the most influential model of language control developed over the last two decades, competition from the non-intended language is solved via inhibition. In particular, the Inhibitory Control (IC) model proposed by Green (1998) puts forward that the amount of inhibition applied to the non-relevant language depends on its dominance, in that the stronger the language the greater the strength of inhibition applied to it. Within this account, the cost required to reactivate a previously inhibited language depends on the amount of inhibition previously exerted on it, that is, reactivation costs are greater for a stronger compared to a weaker language. In a nutshell, according to the IC model, language control is determined by language dominance.
The goal of the present dissertation is to investigate the extent to which language control in multilinguals is affected by language dominance and whether and how other factors might influence this process. Three main factors are considered in this work: (i) the time speakers have to prepare for a certain language or PREPARATION TIME, (ii) the type of languages involved in the interactional context or LANGUAGE TYPOLOGY, and (iii) the PROCESSING MODALITY, that is, whether the way languages are controlled differs between reception and production.
The results obtained in the four manuscripts, either published or in revision, indicate that language dominance alone does not suffice to explain language switching patterns. In particular, the present thesis shows that language control is profoundly affected by each of the three variables described above. More generally, the findings obtained in the present dissertation indicate that language control in multilingual speakers is a much more dynamic system than previously believed and is not exclusively determined by language dominance, as predicted by the IC model (Green, 1998).
Underground coal gasification (UCG) has the potential to increase worldwide coal reserves by developing coal resources, currently not economically extractable by conventional mining methods. For that purpose, coal is combusted in situ to produce a high-calorific synthesis gas with different end-use options, including electricity generation as well as production of fuels and chemical feedstock. Apart from the high economic potentials, UCG may induce site‐specific environmental impacts, including ground surface subsidence and pollutant migration of UCG by-products into shallow freshwater aquifers. Sustainable and efficient UCG operation requires a thorough understanding of the coupled thermal, hydraulic and mechanical processes, occurring in the UCG reactor vicinity. The development and infrastructure costs of UCG trials are very high; therefore, numerical simulations of coupled processes in UCG are essential for the assessment of potential environmental impacts. Therefore, the aim of the present study is to assess UCG-induced permeability changes, potential hydraulic short circuit formation and non-isothermal multiphase fluid flow dynamics by means of coupled numerical simulations. Simulation results on permeability changes in the UCG reactor vicinity demonstrate that temperature-dependent thermo-mechanical parameters have to be considered in near-field assessments, only. Hence, far-field simulations do not become inaccurate, but benefit from increased computational efficiency when thermo-mechanical parameters are maintained constant. Simulations on potential hydraulic short circuit formation between single UCG reactors at regional-scale emphasize that geologic faults may induce hydraulic connections, and thus compromise efficient UCG operation. In this context, the steam jacket surrounding high-temperature UCG reactors plays a vital role in avoiding UCG by-products escaping into freshwater aquifers and in minimizing energy consumption by formation fluid evaporation. A steam jacket emerges in the close reactor vicinity due to phase transition of formation water and is a non-isothermal flow phenomenon. Considering this complex multiphase flow behavior, an innovative conceptual modeling approach, validated against field data, enables the quantification and prediction of UCG reactor water balances. The findings of this doctoral thesis provide an important basis for integration of thermo-hydro-mechanical simulations in UCG, required for the assessment and mitigation of its potential environmental impacts as well as optimization of its efficiency.
Natural and potentially hazardous events occur on the Earth’s surface every day. The most destructive of these processes must be monitored, because they may cause loss of lives, infrastructure, and natural resources, or have a negative effect on the environment. A variety of remote sensing technologies allow the recoding of data to detect these processes in the first place, partly based on the diagnostic landforms that they form. To perform this effectively, automatic methods are desirable.
Universal detection of natural hazards is challenging due to their differences in spatial impacts, timing and longevity of consequences, and the spatial resolution of remote-sensing data. Previous studies have reported that topographic metrics such as roughness, which can be captured from digital elevation data, can reveal landforms diagnostic of natural hazards, such as gullies, dunes, lava fields, landslides and snow avalanches, as these landforms tend to be more heterogeneous than the surrounding landscape. A single roughness metric is often limited in such detections; however, a more complex approach that exploits the spatial relation and the location of objects, such as object-based image analysis (OBIA), is desirable.
In this thesis, I propose a topographic roughness measure derived from an airborne laser scanning (ALS) digital terrain model (DTM) and discuss its performance in detecting landforms principally diagnostic of natural hazards. I further develop OBIA-based algorithms for the detection of snow avalanches using near-infrared (NIR) aerial images, and the size (changes) of mountain lakes using LANDSAT satellite images. I quantitatively test and document how the level of difficulty in detecting these very challenging landforms depends on the input data resolution, the derivatives that could be evaluated from images and DTMs, the size, shape and complexity of landforms, and the capabilities of obtaining the information in the data. I demonstrate that surface roughness is a promising metric for detecting different landforms in diverse environments, and that OBIA assists significantly in detecting parts of lakes and snow avalanches that may not be correctly assigned by applying only the thresholding of spectral properties of data and their derivatives.
The curvature-based surface roughness parameter allows the detection of gullies, dunes, lava fields and landslides with a user’s accuracy of 0.63, 0.21, 0.53, and 0.45, respectively. The OBIA algorithms for detecting lakes and snow avalanches obtained user’s accuracy of 0.98, and 0.78, respectively. Most of the analysed landforms constituted only a small part of the entire dataset, and therefore the user’s accuracy is the most appropriate performance measure that should be given in a such classification, because it tells how many automatically-extracted pixels in fact represent the object that one wants to classify, and its calculation does not take the second (background) class into account. One advantage of the proposed roughness parameter is that it allows the extraction of the heterogeneity of the surface without the need for data detrending. The OBIA approach is novel in that it allows the classification of lakes regardless of the physical state of their water, and also allows the separation of frozen lakes from glaciers that have very similar water indices used in purely optical remote sensing applications. The algorithm proposed for snow avalanches allows the detection of release zones, tracks, and deposition zones by verifying the snow heterogeneity based on a roughness metric evaluated from a water index, and by analysing the local relation of segments with their neighbouring objects. This algorithm contains few steps, which allows for the simultaneous classification of avalanches that occur on diverse mountain slopes and differ in size and shape.
This thesis contributes to natural hazard research as it provides automatic solutions to tracking six different landforms that are diagnostic of natural hazards over large regions. This is a step toward delineating areas susceptible to the processes producing these landforms and the improvement of hazard maps.