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In our fast-changing world, human-machine interfaces (HMIs) are of ever-increasing importance. Among the most ubiquitous examples are touchscreens that most people are familiar with from their smartphones. The quality of such an HMI can be improved by adding haptic feedback-an imitation of using mechanical buttons-to the touchscreen. Thin-film actuators on the basis of electro-mechanically active polymers (EAPs), with the electroactive material sandwiched between two compliant electrodes, offer a promising technology for haptic surfaces. In thin-film technology, the thickness and the number of stacked layers of the electroactive dielectric are key parameters for tuning a system. Therefore, we have experimentally investigated the influence of the thickness of a single EAP layer on the electrical and the electro-mechanical performance of the transducer. In order to achieve high electro-mechanical actuator outputs, we have employed relaxor-ferroelectric ter-fluoropolymers that can be screen-printed. By means of a model-based approach, we have also directly compared single- and multi-layer actuators, thus providing guidelines for optimized transducer configurations with respect to the system requirements of haptic applications for which the operation frequency is of particular importance.
This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.
Despite the importance of rhizosphere properties for water flow from soil to roots, there is limited quantitative information on the distribution of water in the rhizosphere of plants.
Here, we used neutron tomography to quantify and visualize the water content in the rhizosphere of the plant species chickpea (Cicer arietinum), white lupin (Lupinus albus), and maize (Zea mays) 12 d after planting.
We clearly observed increasing soil water contents (h) towards the root surface for all three plant species, as opposed to the usual assumption of decreasing water content. This was true for tap roots and lateral roots of both upper and lower parts of the root system. Furthermore, water gradients around the lower part of the roots were smaller and extended further into bulk soil compared with the upper part, where the gradients in water content were steeper.
Incorporating the hydraulic conductivity and water retention parameters of the rhizosphere into our model, we could simulate the gradual changes of h towards the root surface, in agreement with the observations. The modelling result suggests that roots in their rhizosphere may modify the hydraulic properties of soil in a way that improves uptake under dry conditions.
The Andes are a ~7000 km long N-S trending mountain range developed along the South American western continental margin. Driven by the subduction of the oceanic Nazca plate beneath the continental South American plate, the formation of the northern and central parts of the orogen is a type case for a non-collisional orogeny. In the southern Central Andes (SCA, 29°S-39°S), the oceanic plate changes the subduction angle between 33°S and 35°S from almost horizontal (< 5° dip) in the north to a steeper angle (~30° dip) in the south. This sector of the Andes also displays remarkable along- and across- strike variations of the tectonic deformation patterns. These include a systematic decrease of topographic elevation, of crustal shortening and foreland and orogenic width, as well as an alternation of the foreland deformation style between thick-skinned and thin-skinned recorded along- and across the strike of the subduction zone. Moreover, the SCA are a very seismically active region. The continental plate is characterized by a relatively shallow seismicity (< 30 km depth) which is mainly focussed at the transition from the orogen to the lowland areas of the foreland and the forearc; in contrast, deeper seismicity occurs below the interiors of the northern foreland. Additionally, frequent seismicity is also recorded in the shallow parts of the oceanic plate and in a sector of the flat slab segment between 31°S and 33°S. The observed spatial heterogeneity in tectonic and seismic deformation in the SCA has been attributed to multiple causes, including variations in sediment thickness, the presence of inherited structures and changes in the subduction angle of the oceanic slab. However, there is no study that inquired the relationship between the long-term rheological configuration of the SCA and the spatial deformation patterns. Moreover, the effects of the density and thickness configuration of the continental plate and of variations in the slab dip angle in the rheological state of the lithosphere have been not thoroughly investigated yet. Since rheology depends on composition, pressure and temperature, a detailed characterization of the compositional, structural and thermal fields of the lithosphere is needed. Therefore, by using multiple geophysical approaches and data sources, I constructed the following 3D models of the SCA lithosphere: (i) a seismically-constrained structural and density model that was tested against the gravity field; (ii) a thermal model integrating the conversion of mantle shear-wave velocities to temperature with steady-state conductive calculations in the uppermost lithosphere (< 50 km depth), validated by temperature and heat-flow measurements; and (iii) a rheological model of the long-term lithospheric strength using as input the previously-generated models.
The results of this dissertation indicate that the present-day thermal and rheological fields of the SCA are controlled by different mechanisms at different depths. At shallow depths (< 50 km), the thermomechanical field is modulated by the heterogeneous composition of the continental lithosphere. The overprint of the oceanic slab is detectable where the oceanic plate is shallow (< 85 km depth) and the radiogenic crust is thin, resulting in overall lower temperatures and higher strength compared to regions where the slab is steep and the radiogenic crust is thick. At depths > 50 km, largest temperatures variations occur where the descending slab is detected, which implies that the deep thermal field is mainly affected by the slab dip geometry.
The outcomes of this thesis suggests that long-term thermomechanical state of the lithosphere influences the spatial distribution of seismic deformation. Most of the seismicity within the continental plate occurs above the modelled transition from brittle to ductile conditions. Additionally, there is a spatial correlation between the location of these events and the transition from the mechanically strong domains of the forearc and foreland to the weak domain of the orogen. In contrast, seismicity within the oceanic plate is also detected where long-term ductile conditions are expected. I therefore analysed the possible influence of additional mechanisms triggering these earthquakes, including the compaction of sediments in the subduction interface and dehydration reactions in the slab. To that aim, I carried out a qualitative analysis of the state of hydration in the mantle using the ratio between compressional- and shear-wave velocity (vp/vs ratio) from a previous seismic tomography. The results from this analysis indicate that the majority of the seismicity spatially correlates with hydrated areas of the slab and overlying continental mantle, with the exception of the cluster within the flat slab segment. In this region, earthquakes are likely triggered by flexural processes where the slab changes from a flat to a steep subduction angle.
First-order variations in the observed tectonic patterns also seem to be influenced by the thermomechanical configuration of the lithosphere. The mechanically strong domains of the forearc and foreland, due to their resistance to deformation, display smaller amounts of shortening than the relatively weak orogenic domain. In addition, the structural and thermomechanical characteristics modelled in this dissertation confirm previous analyses from geodynamic models pointing to the control of the observed heterogeneities in the orogen and foreland deformation style. These characteristics include the lithospheric and crustal thickness, the presence of weak sediments and the variations in gravitational potential energy.
Specific conditions occur in the cold and strong northern foreland, which is characterized by active seismicity and thick-skinned structures, although the modelled crustal strength exceeds the typical values of externally-applied tectonic stresses. The additional mechanisms that could explain the strain localization in a region that should resist deformation are: (i) increased tectonic forces coming from the steepening of the slab and (ii) enhanced weakening along inherited structures from pre-Andean deformation events. Finally, the thermomechanical conditions of this sector of the foreland could be a key factor influencing the preservation of the flat subduction angle at these latitudes of the SCA.
We systematically explore the effect of calibration data length on the performance of a conceptual hydrological model, GR4H, in comparison to two Artificial Neural Network (ANN) architectures: Long Short-Term Memory Networks (LSTM) and Gated Recurrent Units (GRU), which have just recently been introduced to the field of hydrology. We implemented a case study for six river basins across the contiguous United States, with 25 years of meteorological and discharge data. Nine years were reserved for independent validation; two years were used as a warm-up period, one year for each of the calibration and validation periods, respectively; from the remaining 14 years, we sampled increasing amounts of data for model calibration, and found pronounced differences in model performance. While GR4H required less data to converge, LSTM and GRU caught up at a remarkable rate, considering their number of parameters. Also, LSTM and GRU exhibited the higher calibration instability in comparison to GR4H. These findings confirm the potential of modern deep-learning architectures in rainfall runoff modelling, but also highlight the noticeable differences between them in regard to the effect of calibration data length.
Predator-prey interactions provide central links in food webs. These interaction are directly or indirectly impacted by a number of factors. These factors range from physiological characteristics of individual organisms, over specifics of their interaction to impacts of the environment. They may generate the potential for the application of different strategies by predators and prey. Within this thesis, I modelled predator-prey interactions and investigated a broad range of different factors driving the application of certain strategies, that affect the individuals or their populations. In doing so, I focused on phytoplankton-zooplankton systems as established model systems of predator-prey interactions.
At the level of predator physiology I proposed, and partly confirmed, adaptations to fluctuating availability of co-limiting nutrients as beneficial strategies. These may allow to store ingested nutrients or to regulate the effort put into nutrient assimilation. We found that these two strategies are beneficial at different fluctuation frequencies of the nutrients, but may positively interact at intermediate frequencies. The corresponding experiments supported our model results. We found that the temporal structure of nutrient fluctuations indeed has strong effects on the juvenile somatic growth rate of {\itshape Daphnia}.
Predator colimitation by energy and essential biochemical nutrients gave rise to another physiological strategy. High-quality prey species may render themselves indispensable in a scenario of predator-mediated coexistence by being the only source of essential biochemical nutrients, such as cholesterol. Thereby, the high-quality prey may even compensate for a lacking defense and ensure its persistence in competition with other more defended prey species.
We found a similar effect in a model where algae and bacteria compete for nutrients. Now, being the only source of a compound that is required by the competitor (bacteria) prevented the competitive exclusion of the algae. In this case, the essential compounds were the organic carbon provided by the algae. Here again, being indispensable served as a prey strategy that ensured its coexistence.
The latter scenario also gave rise to the application of the two metabolic strategies of autotrophy and heterotrophy by algae and bacteria, respectively. We found that their coexistence allowed the recycling of resources in a microbial loop that would otherwise be lost. Instead, these resources were made available to higher trophic levels, increasing the trophic transfer efficiency in food webs.
The predation process comprises the next higher level of factors shaping the predator-prey interaction, besides these factors that originated from the functioning or composition of individuals. Here, I focused on defensive mechanisms and investigated multiple scenarios of static or adaptive combinations of prey defense and predator offense. I confirmed and extended earlier reports on the coexistence-promoting effects of partially lower palatability of the prey community. When bacteria and algae are coexisting, a higher palatability of bacteria may increase the average predator biomass, with the side effect of making the population dynamics more regular. This may facilitate experimental investigations and interpretations. If defense and offense are adaptive, this allows organisms to maximize their growth rate. Besides this fitness-enhancing effect, I found that co-adaptation may provide the predator-prey system with the flexibility to buffer external perturbations.
On top of these rather internal factors, environmental drivers also affect predator-prey interactions. I showed that environmental nutrient fluctuations may create a spatio-temporal resource heterogeneity that selects for different predator strategies. I hypothesized that this might favour either storage or acclimation specialists, depending on the frequency of the environmental fluctuations.
We found that many of these factors promote the coexistence of different strategies and may therefore support and sustain biodiversity. Thus, they might be relevant for the maintenance of crucial ecosystem functions that also affect us humans. Besides this, the richness of factors that impact predator-prey interactions might explain why so many species, especially in the planktonic regime, are able to coexist.
Semiaride Gebiete sind hauptsächlich durch geringe Wasserressourcen gekennzeichnet und unterliegen häufig dem Risiko der Wasserknappheit. In diesen Gebieten ist die Wasserbereitstellung für Bewässerung und Trinkwasserversorgung stark von der oberflächlichen Speicherung in Stauseen abhängig, deren Wasserverfügbarkeit nachteilig durch Sedimentablagerung beeinflusst wird. Zur Wiedergabe des komplexen Sedimentablagerungsverhaltens in Stauseen von semiariden Gebieten und die Auswirkungen von Sedimentmanagementmaßnahmen wird ein Sedimentationsmodell entwickelt und mit dem WASA-SED Modell gekoppelt, das für die Modellierung der Abflussbildung und des Sedimenttransportes in Einzugsgebieten geeignet ist. Das Sedimentationsmodell beinhaltet zwei Ansätze, die unter der Berücksichtigung verschiedener Stauseengrößenklassen und Datenverfügbarkeit eingesetzt werden können. Für die Stauseen mit verfügbaren Informationen über ihre geometrischen Eigenschaften (wie Stauseetopographie und Höhe-Fläche-Volumen-Beziehung) und weitere Kenngrößen wie Ablagerungsmächtigkeit, Korngrößenverteilung und Sedimentdichte, kann ein detaillierter Modellansatz für die Sedimentablagerung verwendet werden. Wo diese Informationen nicht verfügbar sind, wird auf einen vereinfachten Ansatz zurückgegriffen. Der detaillierte Modellansatz ermöglicht die Betrachtung von Ablagerungsmustern im Stausee und Einschätzungen über die Effektivität von Sedimentmanagementmaßnahmen hinsichtlich der Sedimententlastung. Dieser Ansatz beruht auf der Simulation des Sedimenttransportes entlang eines Stauseelängsprofils. Für die Berechnung des Sedimenttransfers wird der Stauseekörper in einer Folge von Querprofilen repräsentiert. Der Sedimenttransport wird dabei korngrößenspezifisch entsprechend der Transportkapazität berechnet. Dafür stehen vier verschiedenen Sedimenttransportgleichungen zur Verfügung. Der vereinfachte Modellansatz ist für die Simulation des Sedimenttransfers in Gebieten mit hoher Stauseedichte geeignet, jedoch können weder Sedimentmanagementmaßnahmen noch die räumliche Verteilung der Ablagerungen berücksichtigt werden. Dafür werden die Stauseen in Abhängigkeit von ihrer Größe und Position in kleine und strategische Stauseen unterteilt. Dabei sind strategische Stausseen solche mit mittlerem bis großem Volumen sowie einer Lage im Hauptgerinne oder solche mit sonstiger besonderer Bedeutung. Kleine Stauseen hingegen befinden sich an den Nebenflüssen und werden im Modell in aggregierter Form durch ihre Einteilung in Stauseegrößenklassen repräsentiert. Ein Kaskadenverfahren wird für den Wasser- und Sedimentlauf zwischen den Stauseeklassen verwendet. Dabei werden für jede Stauseeklasse der Wasser- sowie Sedimenthaushalt für einen hypothetischen repräsentativen Stausee mit mittleren Eigenschaften berechnet. Die Sedimentaufnahme und die Korngrößenverteilung des abgegebenen Sediments werden mit dem Überlaufanteil-Ansatz berechnet. In dieser Studie werden drei Modellanwendungen vorgestellt: • Für den 92,2 Mio.m³-großen Barasona-Stausee (Vorland der Zentralpyrenäen, Aragon, Spanien) wird die Modellierung der Sedimentablagerung mit dem detaillierten Modellansatz vorgenommen. Die Kalibrierung dafür wurde in zwei Schritten durchgeführt, um Änderungen im Stauseemanagement Rechnung zu tragen. Die ModellValidierung wird schließlich für eine andere Simulationsperiode vorgenommen. Dabei wird ersichtlich, dass die Prozesse der Sedimentablagerung gut durch das Modell wiedergegeben werden. • Das Modell wird auf das 933 km²-große Benguê-Einzugsgebiet, das sich im semiariden Nordosten Brasiliens befindet, angewendet. Dieses Einzugsgebiet ist durch eine hohe Dichte an kleinen Stauseen, charakterisiert, die fast 45% des Gebietes umfasst, wofür jedoch wenige Messdaten verfügbar sind. Deshalb werden der Wasser- und Sedimenttransport mit dem vereinfachten Modellansatz berechnet. Dabei werden drei Konfigurationen des Kaskadenverfahrens getestet. • Die Modellanwendung erfolgt erneut für den Barasona-Stausee bezüglich der Effektivität der Sedimentmanagementmaßnahmen. Eine Kostenanalyse ermöglicht die Auswahl geeigneter Maßnahmen für den Stausee. Dadurch wird eine Beurteilung der verschiedenen Sedimentmanagementstrategien ermöglicht. Im Allgemeinen unterliegen die Simulationsergebnisse großen Unsicherheiten, teilweise wegen der geringen Datenverfügbarkeit, andererseits durch die Unsicherheiten in der Modellstruktur zur korrekten Wiedergabe der Sedimentablagerungsprozesse.
Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However, in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here, we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapunos catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (>13.3mm30min(-1)) however show large differences between the versions with and without macropores. These model results compared with measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore, preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events. Copyright (c) 2013 John Wiley & Sons, Ltd.
Monoclonal antibodies (mAbs) are an innovative group of drugs with increasing clinical importance in oncology, combining high specificity with generally low toxicity. There are, however, numerous challenges associated with the development of mAbs as therapeutics. Mechanistic understanding of factors that govern the pharmacokinetics (PK) of mAbs is critical for drug development and the optimisation of effective therapies; in particular, adequate dosing strategies can improve patient quality life and lower drug cost. Physiologically-based PK (PBPK) models offer a physiological and mechanistic framework, which is of advantage in the context of animal to human extrapolation. Unlike for small molecule drugs, however, there is no consensus on how to model mAb disposition in a PBPK context. Current PBPK models for mAb PK hugely vary in their representation of physiology and parameterisation. Their complexity poses a challenge for their applications, e.g., translating knowledge from animal species to humans.
In this thesis, we developed and validated a consensus PBPK model for mAb disposition taking into account recent insights into mAb distribution (antibody biodistribution coefficients and interstitial immunoglobulin G (IgG) pharmacokinetics) to predict tissue PK across several pre-clinical species and humans based on plasma data only. The model allows to a priori predict target-independent (unspecific) mAb disposition processes as well as mAb disposition in concentration ranges, for which the unspecific clearance (CL) dominates target-mediated CL processes. This is often the case for mAb therapies at steady state dosing.
The consensus PBPK model was then used and refined to address two important problems:
1) Immunodeficient mice are crucial models to evaluate mAb efficacy in cancer therapy. Protection from elimination by binding to the neonatal Fc receptor is known to be a major pathway influencing the unspecific CL of both, endogenous and therapeutic IgG. The concentration of endogenous IgG, however, is reduced in immunodeficient mouse models, and this effect on unspecific mAb CL is unknown, yet of great importance for the extrapolation to human in the context of mAb cancer therapy.
2) The distribution of mAbs into solid tumours is of great interest. To comprehensively investigate mAb distribution within tumour tissue and its implications for therapeutic efficacy, we extended the consensus PBPK model by a detailed tumour distribution model incorporating a cell-level model for mAb-target interaction. We studied the impact of variations in tumour microenvironment on therapeutic efficacy and explored the plausibility of different mechanisms of action in mAb cancer therapy.
The mathematical findings and observed phenomena shed new light on therapeutic utility and dosing regimens in mAb cancer treatment.