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Membrane adhesion is a fundamental biological process in which membranes are attached to neighboring membranes or surfaces. Membrane adhesion emerges from a complex interplay between the binding of membrane-anchored receptors/ligands and the membrane properties. In this work, we study membrane adhesion mediated by lipid-anchored saccharides using microsecond-long full-atomistic molecular dynamics simulations. Motivated by neutron scattering experiments on membrane adhesion via lipid-anchored saccharides, we investigate the role of LeX, Lac1, and Lac2 saccharides and membrane fluctuations in membrane adhesion.
We study the binding of saccharides in three different systems: for saccharides in water, for saccharides anchored to essentially planar membranes at fixed separations, and for saccharides anchored to apposing fluctuating membranes. Our simulations of two saccharides in water indicate that the saccharides engage in weak interactions to form dimers. We find that the binding occurs in a continuum of bound states instead of a certain number of well-defined bound structures, which we term as "diffuse binding".
The binding of saccharides anchored to essentially planar membranes strongly depends on separation of the membranes, which is fixed in our simulation system. We show that the binding constants for trans-interactions of two lipid-anchored saccharides monotonically decrease with increasing separation. Saccharides anchored to the same membrane leaflet engage in cis-interactions with binding constants comparable to the trans-binding constants at the smallest membrane separations. The interplay of cis- and trans-binding can be investigated in simulation systems with many lipid-anchored saccharides. For Lac2, our simulation results indicate a positive cooperativity of trans- and cis-binding. In this cooperative binding the trans-binding constant is enhanced by the cis-interactions. For LeX, in contrast, we observe no cooperativity between trans- and cis-binding. In addition, we determine the forces generated by trans-binding of lipid-anchored saccharides in planar membranes from the binding-induced deviations of the lipid-anchors. We find that the forces acting on trans-bound saccharides increase with increasing membrane separation to values of the order of 10 pN.
The binding of saccharides anchored to the fluctuating membranes results from an interplay between the binding properties of the lipid-anchored saccharides and membrane fluctuations. Our simulations, which have the same average separation of the membranes as obtained from the neutron scattering experiments, yield a binding constant larger than in planar membranes with the same separation. This result demonstrates that membrane fluctuations play an important role at average membrane separations which are seemingly too large for effective binding. We further show that the probability distribution of the local separation can be well approximated by a Gaussian distribution. We calculate the relative membrane roughness and show that our results are in good agreement with the roughness values reported from the neutron scattering experiments.
Domestication syndrome has resulted in the large loss of genetic variation of crop plants. Because of such genetic loss, productivity of various beneficial secondary (specialized) metabolites that protect against abiotic/biotic stresses, has been narrowed in many domesticated crops. Many key regulators or structural genes of secondary metabolic pathways in the domesticated as well as wild tomatoes are still largely unknown. In recent studies, metabolic quantitative trait loci (mQTL) analysis using the population of introgression lines (ILs), each containing a single introgression from Solanum pennellii (wild tomato) in the genetic background of domesticated tomato (M82, Solanum lycopersicum), has been used for investigation of metabolic regulation and key genes involved in both primary and secondary metabolism. In this thesis, three research projects, i) understanding of metabolic linkage between branched chain amino acids (BCAAs) and secondary metabolism using antisense lines of BCAAs metabolic genes, ii) investigation of novel key genes involved in tomato secondary metabolism and fruit ripening, iii) mapping of drought stress responsive mQTLs in tomato, are presented and discussed. In the first part, metabolic linkage between leucine and secondary metabolism is investigated by analyzing antisense lines of four key genes (ketol-acid reductoisomerase, KARI; dihydroxy-acid dehydratase, DHAD; isopropylmalate dehydratase, IPMD and branched chain aminotransferases1, BCAT1) found previously in mQTL of leucine contents. Obtained results indicate that KARI might be a rate limiting enzyme for iC5 acyl-sucrose synthesis in young leaf but not in red ripe fruits. By integrating obtained results with previous reports, inductive metabolic linkage between BCAAs and other secondary metabolic pathways at DHAD transcriptional levels in fruit is proposed. In the second part, candidate genes that are involved in secondary metabolism and fruit ripening in tomato were found by the approach of expression quantitative trait loci (eQTL) analysis. To predict functions of those candidate genes, functional validation by virus induced gene silencing and transient overexpression were performed. Results obtained by analyzing T0 overexpression and artificial miRNA lines for some of those candidates confirm their predicted functions, for example involved in fruit ripening (WD40, Solyc04g005020) and iC5 acyl-sucrose synthesis (P450, Solyc03g111940). In the third part, mapping of drought stress responsive mQTLs was performed using 57 S. pennellii ILs population. Evaluation of genetic architecture of mQTL analysis resulted in identifying drought responsive ILs (11-2, 8-3-1, 10-1-1 and 3-1). Location of well characterized regulators in these ILs helped to filter potential new key genes involved in drought stress tolerance. Obtained results suggests us our approaches could be viable for narrowing down potential candidates involved in creating interspecific variation in secondary metabolite content and at the level of fruit ripening.
In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces.
In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius.
Each version of the clustering algorithm has its own use case that we show in the thesis.
In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data.
The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.
Continuous insight into biological processes has led to the development of large-scale, mechanistic systems biology models of pharmacologically relevant networks. While these models are typically designed to study the impact of diverse stimuli or perturbations on multiple system variables, the focus in pharmacological research is often on a specific input, e.g., the dose of a drug, and a specific output related to the drug effect or response in terms of some surrogate marker.
To study a chosen input-output pair, the complexity of the interactions as well as the size of the models hinders easy access and understanding of the details of the input-output relationship.
The objective of this thesis is the development of a mathematical approach, in specific a model reduction technique, that allows (i) to quantify the importance of the different state variables for a given input-output relationship, and (ii) to reduce the dynamics to its essential features -- allowing for a physiological interpretation of state variables as well as parameter estimation in the statistical analysis of clinical data. We develop a model reduction technique using a control theoretic setting by first defining a novel type of time-limited controllability and observability gramians for nonlinear systems. We then show the superiority of the time-limited generalised gramians for nonlinear systems in the context of balanced truncation for a benchmark system from control theory.
The concept of time-limited controllability and observability gramians is subsequently used to introduce a state and time-dependent quantity called the input-response (ir) index that quantifies the importance of state variables for a given input-response relationship at a particular time.
We subsequently link our approach to sensitivity analysis, thus, enabling for the first time the use of sensitivity coefficients for state space reduction. The sensitivity based ir-indices are given as a product of two sensitivity coefficients. This allows not only for a computational more efficient calculation but also for a clear distinction of the extent to which the input impacts a state variable and the extent to which a state variable impacts the output.
The ir-indices give insight into the coordinated action of specific state variables for a chosen input-response relationship.
Our developed model reduction technique results in reduced models that still allow for a mechanistic interpretation in terms of the quantities/state variables of the original system, which is a key requirement in the field of systems pharmacology and systems biology and distinguished the reduced models from so-called empirical drug effect models. The ir-indices are explicitly defined with respect to a reference trajectory and thereby dependent on the initial state (this is an important feature of the measure). This is demonstrated for an example from the field of systems pharmacology, showing that the reduced models are very informative in their ability to detect (genetic) deficiencies in certain physiological entities. Comparing our novel model reduction technique to the already existing techniques shows its superiority.
The novel input-response index as a measure of the importance of state variables provides a powerful tool for understanding the complex dynamics of large-scale systems in the context of a specific drug-response relationship. Furthermore, the indices provide a means for a very efficient model order reduction and, thus, an important step towards translating insight from biological processes incorporated in detailed systems pharmacology models into the population analysis of clinical data.
The North China Plain (NCP) is one of the most productive and intensive agricultural regions in China. High doses of mineral nitrogen (N) fertiliser, often combined with flood irrigation, are applied, resulting in N surplus, groundwater depletion and environmental pollution. The objectives of this thesis were to use the HERMES model to simulate the N cycle in winter wheat (Triticum aestivum L.)–summer maize (Zea mays L.) double crop rotations and show the performance of the HERMES model, of the new ammonia volatilisation sub-module and of the new nitrification inhibition tool in the NCP. Further objectives were to assess the models potential to save N and water on plot and county scale, as well as on short and long-term. Additionally, improved management strategies with the help of a model-based nitrogen fertiliser recommendation (NFR) and adapted irrigation, should be found.
Results showed that the HERMES model performed well under growing conditions of the NCP and was able to describe the relevant processes related to soil–plant interactions concerning N and water during a 2.5 year field experiment. No differences in grain yield between the real-time model-based NFR and the other treatments of the experiments on plot scale in Quzhou County could be found. Simulations with increasing amounts of irrigation resulted in significantly higher N leaching, higher N requirements of the NFR and reduced yields. Thus, conventional flood irrigation as currently practised by the farmers bears great uncertainties and exact irrigation amounts should be known for future simulation studies. In the best-practice scenario simulation on plot-scale, N input and N leaching, but also irrigation water could be reduced strongly within 2 years. Thus, the model-based NFR in combination with adapted irrigation had the highest potential to reduce nitrate leaching, compared to farmers practice and mineral N (Nmin)-reduced treatments. Also the calibrated and validated ammonia volatilisation sub-module of the HERMES model worked well under the climatic and soil conditions of northern China. Simple ammonia volatilisation approaches gave also satisfying results compared to process-oriented approaches. During the simulation with Ammonium sulphate Nitrate with nitrification inhibitor (ASNDMPP) ammonia volatilisation was higher than in the simulation without nitrification inhibitor, while the result for nitrate leaching was the opposite. Although nitrification worked well in the model, nitrification-born nitrous oxide emissions should be considered in future. Results of the simulated annual long-term (31 years) N losses in whole Quzhou County in Hebei Province were 296.8 kg N ha−1 under common farmers practice treatment and 101.7 kg N ha−1 under optimised treatment including NFR and automated irrigation (OPTai). Spatial differences in simulated N losses throughout Quzhou County, could only be found due to different N inputs. Simulations of an optimised treatment, could save on average more than 260 kg N ha−1a−1 from fertiliser input and 190 kg N ha−1a−1 from N losses and around 115.7 mm a−1 of water, compared to farmers practice. These long-term simulation results showed lower N and water saving potential, compared to short-term simulations and underline the necessity of long-term simulations to overcome the effect of high initial N stocks in soil.
Additionally, the OPTai worked best on clay loam soil except for a high simulated denitrification loss, while the simulations using farmers practice irrigation could not match the actual water needs resulting in yield decline, especially for winter wheat. Thus, a precise adaption of management to actual weather conditions and plant growth needs is necessary for future simulations. However, the optimised treatments did not seem to be able to maintain the soil organic matter pools, even with full crop residue input. Extra organic inputs seem to be required to maintain soil quality in the optimised treatments.
HERMES is a relatively simple model, with regard to data input requirements, to simulate the N cycle. It can offer interpretation of management options on plot, on county and regional scale for extension and research staff. Also in combination with other N and water saving methods the model promises to be a useful tool.
The growing energy demand of the modern economies leads to the increased consumption of fossil fuels in form of coal, oil, and natural gases, as the mains sources. The combustion of these carbon-based fossil fuels is inevitably producing greenhouse gases, especially CO2. Approaches to tackle the CO2 problem are to capture it from the combustion sources or directly from air, as well as to avoid CO2 production in energy consuming sources (e.g., in the refrigeration sector). In the former, relatively low CO2 concentrations and competitive adsorption of other gases is often leading to low CO2 capacities and selectivities. In both approaches, the interaction of gas molecules with porous materials plays a key role. Porous carbon materials possess unique properties including electric conductivity, tunable porosity, as well as thermal and chemical stability. Nevertheless, pristine carbon materials offer weak polarity and thus low CO2 affinity. This can be overcome by nitrogen doping, which enhances the affinity of carbon materials towards acidic or polar guest molecules (e.g., CO2, H2O, or NH3). In contrast to heteroatom-free materials, such carbon materials are in most cases “noble”, that is, they oxidize other matter rather than being oxidized due to the very positive working potential of their electrons. The challenging task here is to achieve homogenous distribution of significant nitrogen content with similar bonding motives throughout the carbon framework and a uniform pore size/distribution to maximize host-guest interactions. The aim of this thesis is the development of novel synthesis pathways towards nitrogen-doped nanoporous noble carbon materials with precise design on a molecular level and understanding of their structure-related performance in energy and environmental applications, namely gas adsorption and electrochemical energy storage.
A template-free synthesis approach towards nitrogen-doped noble microporous carbon materials with high pyrazinic nitrogen content and C2N-type stoichiometry was established via thermal condensation of a hexaazatriphenylene derivative. The materials exhibited high uptake of guest molecules, such as H2O and CO2 at low concentrations, as well as moderate CO2/N2 selectivities. In the following step, the CO2/N2 selectivity was enhanced towards molecular sieving of CO2 via kinetic size exclusion of N2. The precise control over the condensation degree, and thus, atomic construction and porosity of the resulting materials led to remarkable CO2/N2 selectivities, CO2 capacities, and heat of CO2 adsorption. The ultrahydrophilic nature of the pore walls and the narrow microporosity of these carbon materials served as ideal basis for the investigation of interface effects with more polar guest molecules than CO2, namely H2O and NH3.
H2O vapor physisorption measurements, as well as NH3-temperature programmed desorption and thermal response measurements showed exceptionally high affinity towards H2O vapor and NH3 gas. Another series of nitrogen-doped carbon materials was synthesized by direct condensation of a pyrazine-fused conjugated microporous polymer and their structure-related performance in electrochemical energy storage, namely as anode materials for sodium-ion battery, was investigated.
All in all, the findings in this thesis exemplify the value of molecularly designed nitrogen-doped carbon materials with remarkable heteroatom content implemented as well-defined structure motives. The simultaneous adjustment of the porosity renders these materials suitable candidates for fundamental studies about the interactions between nitrogen-doped carbon materials and different guest species.
Supercapacitors are electrochemical energy storage devices with rapid charge/discharge rate and long cycle life. Their biggest challenge is the inferior energy density compared to other electrochemical energy storage devices such as batteries. Being the most widely spread type of supercapacitors, electrochemical double-layer capacitors (EDLCs) store energy by electrosorption of electrolyte ions on the surface of charged electrodes. As a more recent development, Na-ion capacitors (NICs) are expected to be a more promising tactic to tackle the inferior energy density due to their higher-capacity electrodes and larger operating voltage. The charges are simultaneously stored by ion adsorption on the capacitive-type cathode surface and via faradic process in the battery-type anode, respectively. Porous carbon electrodes are of great importance in these devices, but the paramount problems are the facile synthetic routes for high-performance carbons and the lack of fundamental understanding of the energy storage mechanisms. Therefore, the aim of the present dissertation is to develop novel synthetic methods for (nitrogen-doped) porous carbon materials with superior performance, and to reveal a deeper understanding energy storage mechanisms of EDLCs and NICs.
The first part introduces a novel synthetic method towards hierarchical ordered meso-microporous carbon electrode materials for EDLCs. The large amount of micropores and highly ordered mesopores endow abundant sites for charge storage and efficient electrolyte transport, respectively, giving rise to superior EDLC performance in different electrolytes. More importantly, the controversial energy storage mechanism of EDLCs employing ionic liquid (IL) electrolytes is investigated by employing a series of porous model carbons as electrodes. The results not only allow to conclude on the relations between the porosity and ion transport dynamics, but also deliver deeper insights into the energy storage mechanism of IL-based EDLCs which is different from the one usually dominating in solvent-based electrolytes leading to compression double-layers.
The other part focuses on anodes of NICs, where novel synthesis of nitrogen-rich porous carbon electrodes and their sodium storage mechanism are investigated. Free-standing fibrous nitrogen-doped carbon materials are synthesized by electrospinning using the nitrogen-rich monomer (hexaazatriphenylene-hexacarbonitrile, C18N12) as the precursor followed by condensation at high temperature. These fibers provide superior capacity and desirable charge/discharge rate for sodium storage. This work also allows insights into the sodium storage mechanism in nitrogen-doped carbons. Based on this mechanism, further optimization is done by designing a composite material composed of nitrogen-rich carbon nanoparticles embedded in conductive carbon matrix for a better charge/discharge rate. The energy density of the assembled NICs significantly prevails that of common EDLCs while maintaining the high power density and long cycle life.
The Central Andes host large reserves of base and precious metals. The region represented, in 2017, an important part of the worldwide mining activity. Three principal types of deposits have been identified and studied: 1) porphyry type deposits extending from central Chile and Argentina to Bolivia, and Northern Peru, 2) iron oxide-copper-gold (IOCG) deposits, extending from central Peru to central Chile, and 3) epithermal tin polymetallic deposits extending from Southern Peru to Northern Argentina, which compose a large part of the deposits of the Bolivian Tin Belt (BTB). Deposits in the BTB can be divided into two major types: (1) tin-tungsten-zinc pluton-related polymetallic deposits, and (2) tin-silver-lead-zinc epithermal polymetallic vein deposits.
Mina Pirquitas is a tin-silver-lead-zinc epithermal polymetallic vein deposit, located in north-west Argentina, that used to be one of the most important tin-silver producing mine of the country. It was interpreted to be part of the BTB and it shares similar mineral associations with southern pluton related BTB epithermal deposits. Two major mineralization events related to three pulses of magmatic fluids mixed with meteoric water have been identified. The first event can be divided in two stages: 1) stage I-1 with quartz, pyrite, and cassiterite precipitating from fluids between 233 and 370 °C and salinity between 0 and 7.5 wt%, corresponding to a first pulse of fluids, and 2) stage I-2 with sphalerite and tin-silver-lead-antimony sulfosalts precipitating from fluids between 213 and 274 °C with salinity up to 10.6 wt%, corresponding to a new pulse of magmatic fluids in the hydrothermal system. The mineralization event II deposited the richest silver ores at Pirquitas. Event II fluids temperatures and salinities range between 190 and 252 °C and between 0.9 and 4.3 wt% respectively. This corresponds to the waning supply of magmatic fluids. Noble gas isotopic compositions and concentrations in ore-hosted fluid inclusions demonstrate a significant contribution of magmatic fluids to the Pirquitas mineralization although no intrusive rocks are exposed in the mine area.
Lead and sulfur isotopic measurements on ore minerals show that Pirquitas shares a similar signature with southern pluton related polymetallic deposits in the BTB. Furthermore, the major part of the sulfur isotopic values of sulfide and sulfosalt minerals from Pirquitas ranges in the field for sulfur derived from igneous rocks. This suggests that the main contribution of sulfur to the hydrothermal system at Pirquitas is likely to be magma-derived. The precise age of the deposit is still unknown but the results of wolframite dating of 2.9 ± 9.1 Ma and local structural observations suggest that the late mineralization event is younger than 12 Ma.
Predation drives coexistence, evolution and population dynamics of species in food webs, and has strong impacts on related ecosystem functions (e.g. primary production). The effect of predation on these processes largely depends on the trade-offs between functional traits in the predator and prey community. Trade-offs between defence against predation and competitive ability, for example, allow for prey speciation and predator-mediated coexistence of prey species with different strategies (defended or competitive), which may stabilize the overall food web dynamics. While the importance of such trade-offs for coexistence is widely known, we lack an understanding and the empirical evidence of how the variety of differently shaped trade-offs at multiple trophic levels affect biodiversity, trait adaptation and biomass dynamics in food webs. Such mechanistic understanding is crucial for predictions and management decisions that aim to maintain biodiversity and the capability of communities to adapt to environmental change ensuring their persistence.
In this dissertation, after a general introduction to predator-prey interactions and tradeoffs, I first focus on trade-offs in the prey between qualitatively different types of defence (e.g. camouflage or escape behaviour) and their costs. I show that these different types lead to different patterns of predator-mediated coexistence and population dynamics, by using a simple predator-prey model. In a second step, I elaborate quantitative aspects of trade-offs and demonstrates that the shape of the trade-off curve in combination with trait-fitness relationships strongly affects competition among different prey types: Either specialized species with extreme trait combinations (undefended or completely defended) coexist, or a species with an intermediate defence level dominates. The developed theory on trade-off shapes and coexistence is kept general, allowing for applications apart from defence-competitiveness trade-offs. Thirdly, I tested the theory on trade-off shapes on a long-term field data set of phytoplankton from Lake Constance. The measured concave trade-off between defence and growth governs seasonal trait changes of phytoplankton in response to an altering grazing pressure by zooplankton, and affects the maintenance of trait variation in the community. In a fourth step, I analyse the interplay of different tradeoffs at multiple trophic levels with plankton data of Lake Constance and a corresponding tritrophic food web model. The results show that the trait and biomass dynamics of the different three trophic levels are interrelated in a trophic biomass-trait cascade, leading to unintuitive patterns of trait changes that are reversed in comparison to predictions from bitrophic systems. Finally, in the general discussion, I extract main ideas on trade-offs in multitrophic systems, develop a graphical theory on trade-off-based coexistence, discuss the interplay of intra- and interspecific trade-offs, and end with a management-oriented view on the results of the dissertation, describing how food webs may respond to future global changes, given their trade-offs.
The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes.
Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988–2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research.
This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/–2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/–4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram.
To conclude, these three stages–from GLOF detection, to analysing their frequency and estimating regional GLOF hazard–provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.
Interactions and feedbacks between tectonics, climate, and upper plate architecture control basin geometry, relief, and depositional systems. The Andes is part of a longlived continental margin characterized by multiple tectonic cycles which have strongly modified the Andean upper plate architecture. In the Andean retroarc, spatiotemporal variations in the structure of the upper plate and tectonic regimes have resulted in marked along-strike variations in basin geometry, stratigraphy, deformational style, and mountain belt morphology. These along-strike variations include high-elevation plateaus (Altiplano and Puna) associated with a thin-skin fold-and-thrust-belt and thick-skin deformation in broken foreland basins such as the Santa Barbara system and the Sierras Pampeanas. At the confluence of the Puna Plateau, the Santa Barbara system and the Sierras Pampeanas, major along-strike changes in upper plate architecture, mountain belt morphology, basement exhumation, and deformation style can be recognized. I have used a source to sink approach to unravel the spatiotemporal tectonic evolution of the Andean retroarc between 26 and 28°S. I obtained a large low-temperature thermochronology data set from basement units which includes apatite fission track, apatite U-Th-Sm/He, and zircon U-Th/He (ZHe) cooling ages. Stratigraphic descriptions of Miocene units were temporally constrained by U-Pb LA-ICP-MS zircon ages from interbedded pyroclastic material.
Modeled ZHe ages suggest that the basement of the study area was exhumed during the Famatinian orogeny (550-450 Ma), followed by a period of relative tectonic quiescence during the Paleozoic and the Triassic. The basement experienced horst exhumation during the Cretaceous development of the Salta rift. After initial exhumation, deposition of thick Cretaceous syn-rift strata caused reheating of several basement blocks within the Santa Barbara system. During the Eocene-Oligocene, the Andean compressional setting was responsible for the exhumation of several disconnected basement blocks. These exhumed blocks were separated by areas of low relief, in which humid climate and low erosion rates facilitated the development of etchplains on the crystalline basement. The exhumed basement blocks formed an Eocene to Oligocene broken foreland basin in the back-bulge depozone of the Andean foreland. During the Early Miocene, foreland basin strata filled up the preexisting Paleogene topography. The basement blocks in lower relief positions were reheated; associated geothermal gradients were higher than 25°C/km. Miocene volcanism was responsible for lateral variations on the amount of reheating along the Campo-Arenal basin. Around 12 Ma, a new deformational phase modified the drainage network and fragmented the lacustrine system. As deformation and rock uplift continued, the easily eroded sedimentary cover was efficiently removed and reworked by an ephemeral fluvial system, preventing the development of significant relief. After ~6 Ma, the low erodibility of the basement blocks which began to be exposed caused relief increase, leading to the development of stable fluvial systems. Progressive relief development modified atmospheric circulation, creating a rainfall gradient. After 3 Ma, orographic rainfall and high relief lead to the development of proximal fluvial-gravitational depositional systems in the surrounding basins.
Sinkholes and depressions are typical landforms of karst regions. They pose a considerable natural hazard to infrastructure, agriculture, economy and human life in affected areas worldwide. The physio-chemical processes of sinkholes and depression formation are manifold, ranging from dissolution and material erosion in the subsurface to mechanical subsidence/failure of the overburden. This thesis addresses the mechanisms leading to the development of sinkholes and depressions by using complementary methods: remote sensing, distinct element modelling and near-surface geophysics.
In the first part, detailed information about the (hydro)-geological background, ground structures, morphologies and spatio-temporal development of sinkholes and depressions at a very active karst area at the Dead Sea are derived from satellite image analysis, photogrammetry and geologic field surveys. There, clusters of an increasing number of sinkholes have been developing since the 1980s within large-scale depressions and are distributed over different kinds of surface materials: clayey mud, sandy-gravel alluvium and lacustrine evaporites (salt). The morphology of sinkholes differs depending in which material they form: Sinkholes in sandy-gravel alluvium and salt are generally deeper and narrower than sinkholes in the interbedded evaporite and mud deposits. From repeated aerial surveys, collapse precursory features like small-scale subsidence, individual holes and cracks are identified in all materials. The analysis sheds light on the ongoing hazardous subsidence process, which is driven by the base-level fall of the Dead Sea and by the dynamic formation of subsurface water channels.
In the second part of this thesis, a novel, 2D distinct element geomechanical modelling approach with the software PFC2D-V5 to simulating individual and multiple cavity growth and sinkhole and large-scale depression development is presented. The approach involves a stepwise material removal technique in void spaces of arbitrarily shaped geometries and is benchmarked by analytical and boundary element method solutions for circular cavities. Simulated compression and tension tests are used to calibrate model parameters with bulk rock properties for the materials of the field site. The simulations show that cavity and sinkhole evolution is controlled by material strength of both overburden and cavity host material, the depth and relative speed of the cavity growth and the developed stress pattern in the subsurface. Major findings are: (1) A progressively deepening differential subrosion with variable growth speed yields a more fragmented stress pattern with stress interaction between the cavities. It favours multiple sinkhole collapses and nesting within large-scale depressions. (2) Low-strength materials do not support large cavities in the material removal zone, and subsidence is mainly characterised by gradual sagging into the material removal zone with synclinal bending. (3) High-strength materials support large cavity formation, leading to sinkhole formation by sudden collapse of the overburden. (4) Large-scale depression formation happens either by coalescence of collapsing holes, block-wise brittle failure, or gradual sagging and lateral widening.
The distinct element based approach is compared to results from remote sensing and geophysics at the field site. The numerical simulation outcomes are generally in good agreement with derived morphometrics, documented surface and subsurface structures as well as seismic velocities. Complementary findings on the subrosion process are provided from electric and seismic measurements in the area.
Based on the novel combination of methods in this thesis, a generic model of karst landform evolution with focus on sinkhole and depression formation is developed. A deepening subrosion system related to preferential flow paths evolves and creates void spaces and subsurface conduits. This subsequently leads to hazardous subsidence, and the formation of sinkholes within large-scale depressions. Finally, a monitoring system for shallow natural hazard phenomena consisting of geodetic and geophysical observations is proposed for similarly affected areas.
Plasmonic metal nanostructures can be tuned to efficiently interact with light, converting the photons into energetic charge carriers and heat. Therefore, the plasmonic nanoparticles such as gold and silver nanoparticles act as nano-reactors, where the molecules attached to their surfaces benefit from the enhanced electromagnetic field along with the generated energetic charge carriers and heat for possible chemical transformations. Hence, plasmonic chemistry presents metal nanoparticles as a unique playground for chemical reactions on the nanoscale remotely controlled by light. However, defining the elementary concepts behind these reactions represents the main challenge for understanding their mechanism in the context of the plasmonically assisted chemistry.
Surface-enhanced Raman scattering (SERS) is a powerful technique employing the plasmon-enhanced electromagnetic field, which can be used for probing the vibrational modes of molecules adsorbed on plasmonic nanoparticles. In this cumulative dissertation, I use SERS to probe the dimerization reaction of 4-nitrothiophenol (4-NTP) as a model example of plasmonic chemistry. I first demonstrate that plasmonic nanostructures such as gold nanotriangles and nanoflowers have a high SERS efficiency, as evidenced by probing the vibrations of the rhodamine dye R6G and the 4-nitrothiophenol 4-NTP. The high signal enhancement enabled the measurements of SERS spectra with a short acquisition time, which allows monitoring the kinetics of chemical reactions in real time.
To get insight into the reaction mechanism, several time-dependent SERS measurements of the 4-NTP have been performed under different laser and temperature conditions. Analysis of the results within a mechanistic framework has shown that the plasmonic heating significantly enhances the reaction rate, while the reaction is probably initiated by the energetic electrons. The reaction was shown to be intensity-dependent, where a certain light intensity is required to drive the reaction. Finally, first attempts to scale up the plasmonic catalysis have been performed showing the necessity to achieve the reaction threshold intensity. Meanwhile, the induced heat needs to quickly dissipate from the reaction substrate, since otherwise the reactants and the reaction platform melt. This study might open the way for further work seeking the possibilities to quickly dissipate the plasmonic heat generated during the reaction and therefore, scaling up the plasmonic catalysis.
This dissertation is concerned with the relation between qualitative phonological organization in the form of syllabic structure and continuous phonetics, that is, the spatial and temporal dimensions of vocal tract action that express syllabic structure. The main claim of the dissertation is twofold. First, we argue that syllabic organization exerts multiple effects on the spatio-temporal properties of the segments that partake in that organization. That is, there is no unique or privileged exponent of syllabic organization. Rather, syllabic organization is expressed in a pleiotropy of phonetic indices. Second, we claim that a better understanding of the relation between qualitative phonological organization and continuous phonetics is reached when one considers how the string of segments (over which the nature of the phonological organization is assessed) responds to perturbations (scaling of phonetic variables) of localized properties (such as durations) within that string. Specifically, variation in phonetic variables and more specifically prosodic variation is a crucial key to understanding the nature of the link between (phonological) syllabic organization and the phonetic spatio-temporal manifestation of that organization. The effects of prosodic variation on segmental properties and on the overlap between the segments, we argue, offer the right pathway to discover patterns related to syllabic organization. In our approach, to uncover evidence for global organization, the sequence of segments partaking in that organization as well as properties of these segments or their relations with one another must be somehow locally varied. The consequences of such variation on the rest of the sequence can then be used to unveil the span of organization. When local perturbations to segments or relations between adjacent segments have effects that ripple through the rest of the sequence, this is evidence that organization is global. If instead local perturbations stay local with no consequences for the rest of the whole, this indicates that organization is local.
Due to its bioavailability and (bio)degradability, poly(lactide) (PLA) is an interesting polymer that is already being used as packaging material, surgical seam, and drug delivery system. Dependent on various parameters such as polymer composition, amphiphilicity, sample preparation, and the enantiomeric purity of lactide, PLA in an amphiphilic block copolymer can affect the self-assembly behavior dramatically. However, sizes and shapes of aggregates have a critical effect on the interactions between biological and drug delivery systems, where the general understanding of these polymers and their ability to influence self-assembly is of significant interest in science.
The first part of this thesis describes the synthesis and study of a series of linear poly(L-lactide) (PLLA) and poly(D-lactide) (PDLA)-based amphiphilic block copolymers with varying PLA (hydrophobic), and poly(ethylene glycol) (PEG) (hydrophilic) chain lengths and different block copolymer sequences (PEG-PLA and PLA-PEG). The PEG-PLA block copolymers were synthesized by ring-opening polymerization of lactide initiated by a PEG-OH macroinitiator. In contrast, the PLA-PEG block copolymers were produced by a Steglich-esterification of modified PLA with PEG-OH.
The aqueous self-assembly at room temperature of the enantiomerically pure PLLA-based block copolymers and their stereocomplexed mixtures was investigated by dynamic light scattering (DLS), transmission electron microscopy (TEM), wide-angle X-ray diffraction (WAXD), and differential scanning calorimetry (DSC). Spherical micelles and worm-like structures were produced, whereby the obtained self-assembled morphologies were affected by the lactide weight fraction in the block copolymer and self-assembly time. The formation of worm-like structures increases with decreasing PLA-chain length and arises from spherical micelles, which become colloidally unstable and undergo an epitaxial fusion with other micelles. As shown by DSC experiments, the crystallinity of the corresponding PLA blocks increases within the self-assembly time. However, the stereocomplexed self-assembled structures behave differently from the parent polymers and result in irregular-shaped clusters of spherical micelles. Additionally, time-dependent self-assembly experiments showed a transformation, from already self-assembled morphologies of different shapes to more compact micelles upon stereocomplexation.
In the second part of this thesis, with the objective to influence the self-assembly of PLA-based block copolymers and its stereocomplexes, poly(methyl phosphonate) (PMeP) and poly(isopropyl phosphonate) (PiPrP) were produced by ring-opening polymerization to implement an alternative to the hydrophilic block PEG. Although, the 1,8 diazabicyclo[5.4.0]unde 7 ene (DBU) or 1,5,7 triazabicyclo[4.4.0]dec-5-ene (TBD) mediated synthesis of the corresponding poly(alkyl phosphonate)s was successful, however, not so the polymerization of copolymers with PLA-based precursors (PLA-homo polymers, and PEG-PLA block copolymers). Transesterification, obtained by 1H-NMR spectroscopy, between the poly(phosphonate)- and PLA block caused a high-field shifted peak split of the methine proton in the PLA polymer chain, with split intensities depending on the used catalyst (DBU for PMeP, and TBD for PiPrP polymerization). An additional prepared block copolymer PiPrP-PLLA that wasn’t affected in its polymer sequence was finally used for self-assembly experiments with PLA-PEG and PEG-PLA mixing.
This work provides a comprehensive study of the self-assembly behavior of PLA-based block copolymers influenced by various parameters such as polymer block lengths, self-assembly time, and stereocomplexation of block copolymer mixtures.
Back pain is a problem in adolescent athletes affecting postural control which is an important requirement for physical and daily activities whether under static or dynamic conditions. One leg stance and star excursion balance postural control tests are effective in measuring static and dynamic postural control respectively. These tests have been used in individuals with back pain, athletes and non-athletes without first establishing their reliabilities. In addition to this, there is no published literature investigating dynamic posture in adolescent athletes with back pain using the star excursion balance test. Therefore, the aim of the thesis was to assess deficit in postural control in adolescent athletes with and without back pain using static (one leg stance test) and dynamic postural (SEBT) control tests.
Adolescent athletes with and without back pain participated in the study. Static and dynamic postural control tests were performed using one leg stance and SEBT respectively. The reproducibility of both tests was established. Afterwards, it was determined whether there was an association between static and dynamic posture using the measure of displacement of the centre pressure and reach distance respectively. Finally, it was investigated whether there was a difference in postural control in adolescent athletes with and without back pain using the one leg stance test and the SEBT.
Fair to excellent reliabilities was recorded for the static (one leg stance) and dynamic (star excursion balance) postural control tests in the subjects of interest. No association was found between variables of the static and dynamic tests for the adolescent athletes with and without back pain. Also, no statistically significant difference was obtained between adolescent athletics with and without back pain using the static and dynamic postural control test.
One leg stance test and SEBT can be used as measures of postural control in adolescent athletes with and without back pain. Although static and dynamic postural control might be related, adolescent athletes with and without back pain might be using different mechanisms in controlling their static and dynamic posture. Consequently, static and dynamic postural control in adolescent athletes with back pain was not different from those without back pain. These outcome measures might not be challenging enough to detect deficit in postural control in our study group of interest.
The current thesis examined how second language (L2) speakers of German predict upcoming input during language processing. Early research has shown that the predictive abilities of L2 speakers relative to L1 speakers are limited, resulting in the proposal of the Reduced Ability to Generate Expectations (RAGE) hypothesis. Considering that prediction is assumed to facilitate language processing in L1 speakers and probably plays a role in language learning, the assumption that L1/L2 differences can be explained in terms of different processing mechanisms is a particularly interesting approach. However, results from more recent studies on the predictive processing abilities of L2 speakers have indicated that the claim of the RAGE hypothesis is too broad and that prediction in L2 speakers could be selectively limited. In the current thesis, the RAGE hypothesis was systematically put to the test.
In this thesis, German L1 and highly proficient late L2 learners of German with Russian as L1 were tested on their predictive use of one or more information sources that exist as cues to sentence interpretation in both languages, to test for selective limits. The results showed that, in line with previous findings, L2 speakers can use the lexical-semantics of verbs to predict the upcoming noun. Here the level of prediction was more systematically controlled for than in previous studies by using verbs that restrict the selection of upcoming nouns to the semantic category animate or inanimate. Hence, prediction in L2 processing is possible. At the same time, this experiment showed that the L2 group was slower/less certain than the L1 group. Unlike previous studies, the experiment on case marking demonstrated that L2 speakers can use this morphosyntactic cue for prediction. Here, the use of case marking was tested by manipulating the word order (Dat > Acc vs. Acc > Dat) in double object constructions after a ditransitive verb. Both the L1 and the L2 group showed a difference between the two word order conditions that emerged within the critical time window for an anticipatory effect, indicating their sensitivity towards case. However, the results for the post-critical time window pointed to a higher uncertainty in the L2 group, who needed more time to integrate incoming information and were more affected by the word order variation than the L1 group, indicating that they relied more on surface-level information. A different cue weighting was also found in the experiment testing whether participants predict upcoming reference based on implicit causality information. Here, an additional child L1 group was tested, who had a lower memory capacity than the adult L2 group, as confirmed by a digit span task conducted with both learner groups. Whereas the children were only slightly delayed compared to the adult L1 group and showed the same effect of condition, the L2 speakers showed an over-reliance on surface-level information (first-mention/subjecthood). Hence, the pattern observed resulted more likely from L1/L2 differences than from resource deficits.
The reviewed studies and the experiments conducted show that L2 prediction is affected by a range of factors. While some of the factors can be attributed to more individual differences (e.g., language similarity, slower processing) and can be interpreted by L2 processing accounts assuming that L1 and L2 processing are basically the same, certain limits are better explained by accounts that assume more substantial L1/L2 differences. Crucially, the experimental results demonstrate that the RAGE hypothesis should be refined: Although prediction as a fast-operating mechanism is likely to be affected in L2 speakers, there is no indication that prediction is the dominant source of L1/L2 differences. The results rather demonstrate that L2 speakers show a different weighting of cues and rely more on semantic and surface-level information to predict as well as to integrate incoming information.
A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics.
Organic semiconductors are a promising class of materials. Their special properties are the particularly good absorption, low weight and easy processing into thin films. Therefore, intense research has been devoted to the realization of thin film organic solar cells (OPVs). Because of the low dielectric constant of organic semiconductors, primary excitations (excitons) are strongly bound and a type II heterojunction needs to be introduced to split these excitations into free charges. Therefore, most organic solar cells consist of at least an electron donor and electron acceptor material. For such donor acceptor systems mainly three states are relevant; the photoexcited exciton on the donor or acceptor material, the charge transfer state at the donor-acceptor interface and the charge separated state of a free electron and hole. The interplay between these states significantly determines the efficiency of organic solar cells. Due to the high absorption and the low charge carrier mobilities, the active layers are usually thin but also, exciton dissociation and free charge formation proceeds rapidely, which makes the study of carrier dynamics highly challenging.
Therefore, the focus of this work was first to install new experimental setups for the investigation of the charge carrier dynamics in complete devices with superior sensitivity and time resolution and, second, to apply these methods to prototypical photovoltaic materials to address specific questions in the field of organic and hybrid photovoltaics.
Regarding the first goal, a new setup combining transient absorption spectroscopy (TAS) and time delayed collection field (TDCF) was designed and installed in Potsdam. An important part of this work concerned the improvement of the electronic components with respect to time resolution and sensitivity. To this end, a highly sensitive amplifier for driving and detecting the device response in TDCF was developed. This system was then applied to selected organic and hybrid model systems with a particular focus on the understanding of the loss mechanisms that limit the fill factor and short circuit current of organic solar cells.
The first model system was a hybrid photovoltaic material comprising inorganic quantum dots decorated with organic ligands. Measurements with TDCF revealed fast free carrier recombination, in part assisted by traps, while bias-assisted charge extraction measurements showed high mobility. The measured parameters then served as input for a successful description of the device performance with an analytical model.
With a further improvement of the instrumentation, a second topic was the detailed analysis of non-geminate recombination in a disordered polymer:fullerene blend where an important question was the effect of disorder on the carrier dynamics. The measurements revealed that early time highly mobile charges undergo fast non-geminate recombination at the contacts, causing an apparent field dependence of free charge generation in TDCF experiments if not conducted properly. On the other hand, recombination the later time scale was determined by dispersive recombination in the bulk of the active layer, showing the characteristics of carrier dynamics in an exponential density of state distribution. Importantly, the comparison with steady state recombination data suggested a very weak impact of non-thermalized carriers on the recombination properties of the solar cells under application relevant illumination conditions.
Finally, temperature and field dependent studies of free charge generation were performed on three donor-acceptor combinations, with two donor polymers of the same material family blended with two different fullerene acceptor molecules. These particular material combinations were chosen to analyze the influence of the energetic and morphology of the blend on the efficiency of charge generation. To this end, activation energies for photocurrent generation were accurately determined for a wide range of excitation energies. The results prove that the formation of free charge is via thermalized charge transfer states and does not involve hot exciton splitting. Surprisingly, activation energies were of the order of thermal energy at room temperature. This led to the important conclusion that organic solar cells perform well not because of predominate high energy pathways but because the thermalized CT states are weakly bound. In addition, a model is introduced to interconnect the dissociation efficiency of the charge transfer state with its recombination observable with photoluminescence, which rules out a previously proposed two-pool model for free charge formation and recombination. Finally, based on the results, proposals for the further development of organic solar cells are formulated.
In light of the debate on the consequences of competitive contracting out of traditionally public services, this research compares two mechanisms used to allocate funds in development cooperation—direct awarding and competitive contracting out—aiming to identify their potential advantages and disadvantages.
The agency theory is applied within the framework of rational-choice institutionalism to study the institutional arrangements that surround two different money allocation mechanisms, identify the incentives they create for the behavior of individual actors in the field, and examine how these then transfer into measurable differences in managerial quality of development aid projects. In this work, project management quality is seen as an important determinant of the overall project success.
For data-gathering purposes, the German development agency, the Gesellschaft für Internationale Zusammenarbeit (GIZ), is used due to its unique way of work. Whereas the majority of projects receive funds via direct-award mechanism, there is a commercial department, GIZ International Services (GIZ IS) that has to compete for project funds.
The data concerning project management practices on the GIZ and GIZ IS projects was gathered via a web-based, self-administered survey of project team leaders. Principal component analysis was applied to reduce the dimensionality of the independent variable to total of five components of project management. Furthermore, multiple regression analysis identified the differences between the separate components on these two project types. Enriched by qualitative data gathered via interviews, this thesis offers insights into everyday managerial practices in development cooperation and identifies the advantages and disadvantages of the two allocation mechanisms.
The thesis first reiterates the responsibility of donors and implementers for overall aid effectiveness. It shows that the mechanism of competitive contracting out leads to better oversight and control of implementers, fosters deeper cooperation between the implementers and beneficiaries, and has a potential to strengthen ownership of recipient countries. On the other hand, it shows that the evaluation quality does not tremendously benefit from the competitive allocation mechanism and that the quality of the component knowledge management and learning is better when direct-award mechanisms are used. This raises questions about the lacking possibilities of actors in the field to learn about past mistakes and incorporate the finings into the future interventions, which is one of the fundamental issues of aid effectiveness. Finally, the findings show immense deficiencies in regard to oversight and control of individual projects in German development cooperation.