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This dissertation consists of five self-contained essays, addressing different aspects of career choices, especially the choice of entrepreneurship, under risk and ambiguity. In Chapter 2, the first essay develops an occupational choice model with boundedly rational agents, who lack information, receive noisy feedback, and are restricted in their decisions by their personality, to analyze and explain puzzling empirical evidence on entrepreneurial decision processes. In the second essay, in Chapter 3, I contribute to the literature on entrepreneurial choice by constructing a general career choice model on the basis of the assumption that outcomes are partially ambiguous. The third essay, in Chapter 4, theoretically and empirically analyzes the impact of media on career choices, where information on entrepreneurship provided by the media is treated as an informational shock affecting prior beliefs. The fourth essay, presented in Chapter 5, contains an empirical analysis of the effects of cyclical macro variables (GDP and unemployment) on innovative start-ups in Germany. In the fifth, and last, essay in Chapter 6, we examine whether information on personality is useful for advice, using the example of career advice.
The Himalayan arc stretches >2500 km from east to west at the southern edge of the Tibetan Plateau, representing one of the most important Cenozoic continent-continent collisional orogens. Internal deformation processes and climatic factors, which drive weathering, denudation, and transport, influence the growth and erosion of the orogen. During glacial times wet-based glaciers sculpted the mountain range and left overdeepend and U-shaped valleys, which were backfilled during interglacial times with paraglacial sediments over several cycles. These sediments partially still remain within the valleys because of insufficient evacuation capabilities into the foreland. Climatic processes overlay long-term tectonic processes responsible for uplift and exhumation caused by convergence. Possible processes accommodating convergence within the orogenic wedge along the main Himalayan faults, which divide the range into four major lithologic units, are debated. In this context, the identification of processes shaping the Earth’s surface on short- and on long-term are crucial to understand the growth of the orogen and implications for landscape development in various sectors along the arc. This thesis focuses on both surface and tectonic processes that shape the landscape in the western Indian Himalaya since late Miocene.
In my first study, I dated well-preserved glacially polished bedrock on high-elevated ridges and valley walls in the upper of the Chandra Valley the by means of 10Be terrestrial cosmogenic radionuclides (TCN). I used these ages and mapped glacial features to reconstruct the extent and timing of Pleistocene glaciation at the southern front of the Himalaya. I was able to reconstruct an extensive valley glacier of ~200 km length and >1000 m thickness. Deglaciation of the Chandra Valley glacier started subsequently to insolation increase on the Northern Hemisphere and thus responded to temperature increase. I showed that the timing this deglaciation onset was coeval with retreat of further midlatitude glaciers on the Northern and Southern Hemispheres. These comparisons also showed that the post-LGM deglaciation very rapid, occurred within a few thousand years, and was nearly finished prior to the Bølling/Allerød interstadial.
A second study (co-authorship) investigates how glacial advances and retreats in high mountain environments impact the landscape. By 10Be TCN dating and geomorphic mapping, we obtained maximal length and height of the Siachen Glacier within the Nubra Valley. Today the Shyok and Nubra confluence is backfilled with sedimentary deposits, which are attributed to the valley blocking of the Siachen Glacier 900 m above the present day river level. A glacial dam of the Siachen Glacier blocked the Shyok River and lead to the evolution of a more than 20 km long lake. Fluvial and lacustrine deposits in the valley document alternating draining and filling cycles of the lake dammed by the Siachen Glacier. In this study, we can show that glacial incision was outpacing fluvial incision.
In the third study, which spans the million-year timescale, I focus on exhumation and erosion within the Chandra and Beas valleys. In this study the position and discussed possible reasons of rapidly exhuming rocks, several 100-km away from one of the main Himalayan faults (MFT) using Apatite Fission Track (AFT) thermochronometry. The newly gained AFT ages indicate rapid exhumation and confirm earlier studies in the Chandra Valley. I assume that the rapid exhumation is most likely related to uplift over subsurface structures. I tested this hypothesis by combining further low-temperature thermochronometers from areas east and west of my study area. By comparing two transects, each parallel to the Beas/Chandra Valley transect, I demonstrate similarities in the exhumation pattern to transects across the Sutlej region, and strong dissimilarities in the transect crossing the Dhauladar Range. I conclude that the belt of rapid exhumation terminates at the western end of the Kullu-Rampur window. Therewith, I corroborate earlier studies suggesting changes in exhumation behavior in the western Himalaya. Furthermore, I discussed several causes responsible for the pronounced change in exhumation patterns along strike: 1) the role of inherited pre-collisional features such as the Proterozoic sedimentary cover of the Indian basement, former ridges and geological structures, and 2) the variability of convergence rates along the Himalayan arc due to an increased oblique component towards the syntaxis.
The combination of field observations (geological and geomorphological mapping) and methods to constrain short- and long-term processes (10Be, AFT) help to understand the role of the individual contributors to exhumation and erosion in the western Indian Himalaya. With the results of this thesis, I emphasize the importance of glacial and tectonic processes in shaping the landscape by driving exhumation and erosion in the studied areas.
Die Kernfrage der vorliegenden Arbeit lautet: Sichert die Schuldenbremse die fiskalische Nachhaltigkeit in Deutschland? Zur Beantwortung dieser Frage wird zunächst untersucht, welche Vor-Wirkungen die Einführung der Schuldenbremse im Zeitraum 2010-16 auf die deutschen Bundesländer zeitigte. Dafür wurden die beobachtete Konsolidierungsleistung und der 2009 bestehende Konsolidierungsanreiz bzw. –druck der Bundesländer mit Hilfe einer eigens zu diesem Zweck entwickelten Scorecard evaluiert. Mittels multipler Regressionsanalyse wurde dann analysiert, wie die Faktoren der Scorecard die Konsolidierungsleistung der Bun- desländer beeinflussen. Dabei wurde festgestellt, dass beinahe 90% der Variation, durch die unabhängigen Variablen Haushaltslage, Schuldenlast, Einnahmenwachstum und Pensionslast erklärt werden und der Schuldenbremse bei der Konsolidierungsepisode 2009-2016 eher eine untergeordnete Rolle zugefallen sein dürfte. Anschließend wurde mithilfe der in 65 Expertinneninterviews gesammelten Daten analysiert, welche Grenzen der neuen Fiskalregel in ihrem Wirken gesetzt sind, bzw. welche Risiken zukünftig die Einhaltung der Schuldenbremse erschweren oder verhindern könnten: Kommunalverschuldung, FEUs, Eventualverpflichtungen in Form von Bürgschaften für Finanzinstitute und Pensionsverpflichtungen. Die häufig geäußerten Kritikpunkte, die Schuldenbremse sei eine Konjunktur- und Investitionsbremse werden ebenfalls überprüft und zurückgewiesen. Schließlich werden potentielle zukünftige Entwicklungen hinsichtlich der Schuldenbremse und der öffentlichen Verwaltung in Deutschland sowie der Konsolidierungsbemühungen der Länder erörtert.
The concept of hydrologic connectivity summarizes all flow processes that link separate regions of a landscape. As such, it is a central theme in the field of catchment hydrology, with influence on neighboring disciplines such as ecology and geomorphology. It is widely acknowledged to be an important key in understanding the response behavior of a catchment and has at the same time inspired research on internal processes over a broad range of scales. From this process-hydrological point of view, hydrological connectivity is the conceptual framework to link local observations across space and scales.
This is the context in which the four studies this thesis comprises of were conducted. The focus was on structures and their spatial organization as important control on preferential subsurface flow. Each experiment covered a part of the conceptualized flow path from hillslopes to the stream: soil profile, hillslope, riparian zone, and stream.
For each study site, the most characteristic structures of the investigated domain and scale, such as slope deposits and peat layers were identified based on preliminary or previous investigations or literature reviews. Additionally, further structural data was collected and topographical analyses were carried out. Flow processes were observed either based on response observations (soil moisture changes or discharge patterns) or direct measurement (advective heat transport). Based on these data, the flow-relevance of the characteristic structures was evaluated, especially with regard to hillslope to stream connectivity.
Results of the four studies revealed a clear relationship between characteristic spatial structures and the hydrological behavior of the catchment. Especially the spatial distribution of structures throughout the study domain and their interconnectedness were crucial for the establishment of preferential flow paths and their relevance for large-scale processes. Plot and hillslope-scale irrigation experiments showed that the macropores of a heterogeneous, skeletal soil enabled preferential flow paths at the scale of centimeters through the otherwise unsaturated soil. These flow paths connected throughout the soil column and across the hillslope and facilitated substantial amounts of vertical and lateral flow through periglacial slope deposits.
In the riparian zone of the same headwater catchment, the connectivity between hillslopes and stream was controlled by topography and the dualism between characteristic subsurface structures and the geomorphological heterogeneity of the stream channel. At the small scale (1 m to 10 m) highest gains always occurred at steps along the longitudinal streambed profile, which also controlled discharge patterns at the large scale (100 m) during base flow conditions (number of steps per section). During medium and high flow conditions, however, the impact of topography and parafluvial flow through riparian zone structures prevailed and dominated the large-scale response patterns.
In the streambed of a lowland river, low permeability peat layers affected the connectivity between surface water and groundwater, but also between surface water and the hyporheic zone. The crucial factor was not the permeability of the streambed itself, but rather the spatial arrangement of flow-impeding peat layers, causing increased vertical flow through narrow “windows” in contrast to predominantly lateral flow in extended areas of high hydraulic conductivity sediments.
These results show that the spatial organization of structures was an important control for hydrological processes at all scales and study areas. In a final step, the observations from different scales and catchment elements were put in relation and compared. The main focus was on the theoretical analysis of the scale hierarchies of structures and processes and the direction of causal dependencies in this context. Based on the resulting hierarchical structure, a conceptual framework was developed which is capable of representing the system’s complexity while allowing for adequate simplifications.
The resulting concept of the parabolic scale series is based on the insight that flow processes in the terrestrial part of the catchment (soil and hillslopes) converge. This means that small-scale processes assemble and form large-scale processes and responses. Processes in the riparian zone and the streambed, however, are not well represented by the idea of convergence. Here, the large-scale catchment signal arrives and is modified by structures in the riparian zone, stream morphology, and the small-scale interactions between surface water and groundwater. Flow paths diverge and processes can better be represented by proceeding from large scales to smaller ones. The catchment-scale representation of processes and structures is thus the conceptual link between terrestrial hillslope processes and processes in the riparian corridor.
Natural extreme events are an integral part of nature on planet earth. Usually these events are only considered hazardous to humans, in case they are exposed. In this case, however, natural hazards can have devastating impacts on human societies. Especially hydro-meteorological hazards have a high damage potential in form of e.g. riverine and pluvial floods, winter storms, hurricanes and tornadoes, which can occur all over the globe. Along with an increasingly warm climate also an increase in extreme weather which potentially triggers natural hazards can be expected. Yet, not only changing natural systems, but also changing societal systems contribute to an increasing risk associated with these hazards. These can comprise increasing exposure and possibly also increasing vulnerability to the impacts of natural events. Thus, appropriate risk management is required to adapt all parts of society to existing and upcoming risks at various spatial scales. One essential part of risk management is the risk assessment including the estimation of the economic impacts. However, reliable methods for the estimation of economic impacts due to hydro-meteorological hazards are still missing. Therefore, this thesis deals with the question of how the reliability of hazard damage estimates can be improved, represented and propagated across all spatial scales. This question is investigated using the specific example of economic impacts to companies as a result of riverine floods in Germany.
Flood damage models aim to describe the damage processes during a given flood event. In other words they describe the vulnerability of a specific object to a flood. The models can be based on empirical data sets collected after flood events. In this thesis tree-based models trained with survey data are used for the estimation of direct economic flood impacts on the objects. It is found that these machine learning models, in conjunction with increasing sizes of data sets used to derive the models, outperform state-of-the-art damage models. However, despite the performance improvements induced by using multiple variables and more data points, large prediction errors remain at the object level. The occurrence of the high errors was explained by a further investigation using distributions derived from tree-based models. The investigation showed that direct economic impacts to individual objects cannot be modeled by a normal distribution. Yet, most state-of-the-art approaches assume a normal distribution and take mean values as point estimators. Subsequently, the predictions are unlikely values within the distributions resulting in high errors. At larger spatial scales more objects are considered for the damage estimation. This leads to a better fit of the damage estimates to a normal distribution. Consequently, also the performance of the point estimators get better, although large errors can still occur due to the variance of the normal distribution. It is recommended to use distributions instead of point estimates in order to represent the reliability of damage estimates.
In addition current approaches also mostly ignore the uncertainty associated with the characteristics of the hazard and the exposed objects. For a given flood event e.g. the estimation of the water level at a certain building is prone to uncertainties. Current approaches define exposed objects mostly by the use of land use data sets. These data sets often show inconsistencies, which introduce additional uncertainties. Furthermore, state-of-the-art approaches also imply problems of missing consistency when predicting the damage at different spatial scales. This is due to the use of different types of exposure data sets for model derivation and application. In order to face these issues a novel object-based method was developed in this thesis. The method enables a seamless estimation of hydro-meteorological hazard damage across spatial scales including uncertainty quantification. The application and validation of the method resulted in plausible estimations at all spatial scales without overestimating the uncertainty.
Mainly newly available data sets containing individual buildings make the application of the method possible as they allow for the identification of flood affected objects by overlaying the data sets with water masks. However, the identification of affected objects with two different water masks revealed huge differences in the number of identified objects. Thus, more effort is needed for their identification, since the number of objects affected determines the order of magnitude of the economic flood impacts to a large extent.
In general the method represents the uncertainties associated with the three components of risk namely hazard, exposure and vulnerability, in form of probability distributions. The object-based approach enables a consistent propagation of these uncertainties in space. Aside from the propagation of damage estimates and their uncertainties across spatial scales, a propagation between models estimating direct and indirect economic impacts was demonstrated. This enables the inclusion of uncertainties associated with the direct economic impacts within the estimation of the indirect economic impacts. Consequently, the modeling procedure facilitates the representation of the reliability of estimated total economic impacts. The representation of the estimates' reliability prevents reasoning based on a false certainty, which might be attributed to point estimates. Therefore, the developed approach facilitates a meaningful flood risk management and adaptation planning.
The successful post-event application and the representation of the uncertainties qualifies the method also for the use for future risk assessments. Thus, the developed method enables the representation of the assumptions made for the future risk assessments, which is crucial information for future risk management. This is an important step forward, since the representation of reliability associated with all components of risk is currently lacking in all state-of-the-art methods assessing future risk.
In conclusion, the use of object-based methods giving results in the form of distributions instead of point estimations is recommended. The improvement of the model performance by the means of multi-variable models and additional data points is possible, but small. Uncertainties associated with all components of damage estimation should be included and represented within the results. Furthermore, the findings of the thesis suggest that, at larger scales, the influence of the uncertainty associated with the vulnerability is smaller than those associated with the hazard and exposure. This leads to the conclusion that for an increased reliability of flood damage estimations and risk assessments, the improvement and active inclusion of hazard and exposure, including their uncertainties, is needed in addition to the improvements of the models describing the vulnerability of the objects.
The continuously increasing pollution of aquatic environments with microplastics (plastic particles < 5 mm) is a global problem with potential implications for organisms of all trophic levels. For microorganisms, trillions of these floating microplastics particles represent a huge surface area for colonization. Due to the very low biodegradability, microplastics remain years to centuries in the environment and can be transported over thousands of kilometers together with the attached organisms. Since also pathogenic, invasive, or otherwise harmful species could be spread this way, it is essential to study microplastics-associated communities.
For this doctoral thesis, eukaryotic communities were analyzed for the first time on microplastics in brackish environments and compared to communities in the surrounding water and on the natural substrate wood. With Illumina MiSeq high-throughput sequencing, more than 500 different eukaryotic taxa were detected on the microplastics samples. Among them were various green algae, dinoflagellates, ciliates, fungi, fungal-like protists and small metazoans such as nematodes and rotifers. The most abundant organisms was a dinoflagellate of the genus Pfiesteria, which could include fish pathogenic and bloom forming toxigenic species. Network analyses revealed that there were numerous interaction possibilities among prokaryotes and eukaryotes in microplastics biofilms. Eukaryotic community compositions on microplastics differed significantly from those on wood and in water, and compositions were additionally distinct among the sampling locations. Furthermore, the biodiversity was clearly lower on microplastics in comparison to the diversity on wood or in the surrounding water.
In another experiment, a situation was simulated in which treated wastewater containing microplastics was introduced into a freshwater lake. With increasing microplastics concentrations, the resulting bacterial communities became more similar to those from the treated wastewater. Moreover, the abundance of integrase I increased together with rising concentrations of microplastics. Integrase I is often used as a marker for anthropogenic environmental pollution and is further linked to genes conferring, e.g., antibiotic resistance.
This dissertation gives detailed insights into the complexity of prokaryotic and eukaryotic communities on microplastics in brackish and freshwater systems. Even though microplastics provide novel microhabitats for various microbes, they might also transport toxigenic, pathogenic, antibiotic-resistant or parasitic organisms; meaning their colonization can pose potential threats to humans and the environment. Finally, this thesis explains the urgent need for more research as well as for strategies to minimize the global microplastic pollution.
Plastic pollution is ubiquitous on the planet since several millions of tons of plastic waste enter aquatic ecosystems each year. Furthermore, the amount of plastic produced is expected to increase exponentially shortly. The heterogeneity of materials, additives and physical characteristics of plastics are typical of these emerging contaminants and affect their environmental fate in marine and freshwaters. Consequently, plastics can be found in the water column, sediments or littoral habitats of all aquatic ecosystems. Most of this plastic debris will fragment as a product of physical, chemical and biological forces, producing particles of small size. These particles (< 5mm) are known as “microplastics” (MP). Given their high surface-to-volume ratio, MP stimulate biofouling and the formation of biofilms in aquatic systems.
As a result of their unique structure and composition, the microbial communities in MP biofilms are referred to as the “Plastisphere.” While there is increasing data regarding the distinctive composition and structure of the microbial communities that form part of the plastisphere, scarce information exists regarding the activity of microorganisms in MP biofilms. This surface-attached lifestyle is often associated with the increase in horizontal gene transfer (HGT) among bacteria. Therefore, this type of microbial activity represents a relevant function worth to be analyzed in MP biofilms. The horizontal exchange of mobile genetic elements (MGEs) is an essential feature of bacteria. It accounts for the rapid evolution of these prokaryotes and their adaptation to a wide variety of environments. The process of HGT is also crucial for spreading antibiotic resistance and for the evolution of pathogens, as many MGEs are known to contain antibiotic resistance genes (ARGs) and genetic determinants of pathogenicity.
In general, the research presented in this Ph.D. thesis focuses on the analysis of HGT and heterotrophic activity in MP biofilms in aquatic ecosystems. The primary objective was to analyze the potential of gene exchange between MP bacterial communities vs. that of the surrounding water, including bacteria from natural aggregates. Moreover, the thesis addressed the potential of MP biofilms for the proliferation of biohazardous bacteria and MGEs from wastewater treatment plants (WWTPs) and associated with antibiotic resistance. Finally, it seeks to prove if the physiological profile of MP biofilms under different limnological conditions is divergent from that of the water communities. Accordingly, the thesis is composed of three independent studies published in peer-reviewed journals. The two laboratory studies were performed using both model and environmental microbial communities. In the field experiment, natural communities from freshwater ecosystems were examined.
In Chapter I, the inflow of treated wastewater into a temperate lake was simulated with a concentration gradient of MP particles. The effects of MP on the microbial community structure and the occurrence of integrase 1 (int 1) were followed. The int 1 is a marker associated with mobile genetic elements and known as a proxy for anthropogenic effects on the spread of antimicrobial resistance genes. During the experiment, the abundance of int1 increased in the plastisphere with increasing MP particle concentration, but not in the surrounding water. In addition, the microbial community on MP was more similar to the original wastewater community with increasing microplastic concentrations. Our results show that microplastic particles indeed promote persistence of standard indicators of microbial anthropogenic pollution in natural waters.
In Chapter II, the experiments aimed to compare the permissiveness of aquatic bacteria towards model antibiotic resistance plasmid pKJK5, between communities that form biofilms on MP vs. those that are free-living. The frequency of plasmid transfer in bacteria associated with MP was higher when compared to bacteria that are free-living or in natural aggregates. Moreover, comparison increased gene exchange occurred in a broad range of phylogenetically-diverse bacteria. The results indicate a different activity of HGT in MP biofilms, which could affect the ecology of aquatic microbial communities on a global scale and the spread of antibiotic resistance.
Finally, in Chapter III, physiological measurements were performed to assess whether microorganisms on MP had a different functional diversity from those in water. General heterotrophic activity such as oxygen consumption was compared in microcosm assays with and without MP, while diversity and richness of heterotrophic activities were calculated by using Biolog® EcoPlates. Three lakes with different nutrient statuses presented differences in MP-associated biomass build up. Functional diversity profiles of MP biofilms in all lakes differed from those of the communities in the surrounding water, but only in the oligo-mesotrophic lake MP biofilms had a higher functional richness compared to the ambient water. The results support that MP surfaces act as new niches for aquatic microorganisms and can affect global carbon dynamics of pelagic environments.
Overall, the experimental works presented in Chapters I and II support a scenario where MP pollution affects HGT dynamics among aquatic bacteria. Among the consequences of this alteration is an increase in the mobilization and transfer efficiency of ARGs. Moreover, it supposes that changes in HGT can affect the evolution of bacteria and the processing of organic matter, leading to different catabolic profiles such as demonstrated in Chapter III. The results are discussed in the context of the fate and magnitude of plastic pollution and the importance of HGT for bacterial evolution and the microbial loop, i.e., at the base of aquatic food webs. The thesis supports a relevant role of MP biofilm communities for the changes observed in the aquatic microbiome as a product of intense human intervention.
Microbial processing of organic matter (OM) in the freshwater biosphere is a key component of global biogeochemical cycles. Freshwaters receive and process valuable amounts of leaf OM from their terrestrial landscape. These terrestrial subsidies provide an essential source of energy and nutrients to the aquatic environment as a function of heterotrophic processing by fungi and bacteria. Particularly in freshwaters with low in-situ primary production from algae (microalgae, cyanobacteria), microbial turnover of leaf OM significantly contributes to the productivity and functioning of freshwater ecosystems and not least their contribution to global carbon cycling.
Based on differences in their chemical composition, it is believed that leaf OM is less bioavailable to microbial heterotrophs than OM photosynthetically produced by algae. Especially particulate leaf OM, consisting predominantly of structurally complex and aromatic polymers, is assumed highly resistant to enzymatic breakdown by microbial heterotrophs. However, recent research has demonstrated that OM produced by algae promotes the heterotrophic breakdown of leaf OM in aquatic ecosystems, with profound consequences for the metabolism of leaf carbon (C) within microbial food webs. In my thesis, I aimed at investigating the underlying mechanisms of this so called priming effect of algal OM on the use of leaf C in natural microbial communities, focusing on fungi and bacteria.
The works of my thesis underline that algal OM provides highly bioavailable compounds to the microbial community that are quickly assimilated by bacteria (Paper II). The substrate composition of OM pools determines the proportion of fungi and bacteria within the microbial community (Paper I). Thereby, the fraction of algae OM in the aquatic OM pool stimulates the activity and hence contribution of bacterial communities to leaf C turnover by providing an essential energy and nutrient source for the assimilation of the structural complex leaf OM substrate. On the contrary, the assimilation of algal OM remains limited for fungal communities as a function of nutrient competition between fungi and bacteria (Paper I, II). In addition, results provide evidence that environmental conditions determine the strength of interactions between microalgae and heterotrophic bacteria during leaf OM decomposition (Paper I, III). However, the stimulatory effect of algal photoautotrophic activities on leaf C turnover remained significant even under highly dynamic environmental conditions, highlighting their functional role for ecosystem processes (Paper III).
The results of my thesis provide insights into the mechanisms by which algae affect the microbial turnover of leaf C in freshwaters. This in turn contributes to a better understanding of the function of algae in freshwater biogeochemical cycles, especially with regard to their interaction with the heterotrophic community.
Die deutsche Berufsausbildung hat in den vergangenen Jahren stark an Zuspruch verloren. Dies trifft insbesondere auch auf die duale kaufmännische Berufsausbildung zu. Galt sie vor einigen Jahren noch als ein möglicher Ausbildungsweg für leistungsstarke Schüler/-innen, präferieren diese heute zum großen Teil das Studium. Die wachsende Anzahl an Studienabbrechern belegt jedoch, dass dadurch auch Potenzial verloren geht, weil sich Jugendliche mit dem Studium für einen Ausbildungsweg entscheiden, der für sie nicht geeignet ist. Bisherige Bemühungen zur Etablierung alternativer Bildungswege wie zum Beispiel Berufsakademien weisen zwar Erfolge auf, basieren jedoch auf einem Konzept, das sich ausschließlich am Bedarf der Wirtschaft orientiert. Es ist jedoch die Überzeugung der Autorin, dass neue innovative Bildungswege auch die Bedürfnisse und Vorstellungen derjenigen berücksichtigen müssen, für die sie entworfen werden. Denn die Generation der heutigen Jugendlichen zeichnet sich dadurch aus, dass sie ein anderes Wertekonzept als ihre Vorgängergenerationen aufweist. Die Dissertation entwickelt daher ein Modell einer wirtschaftsorientierten Ausbildung, welches sich aus unterschiedlichen motivationstheoretischen Elementen ableitet und zugleich die Werte der Generation der heutigen Jugend-lichen berücksichtigt. Es umfasst sowohl die Anreiz-Beitrags-Theorie nach Barnard als auch die Inhalts-Erwartungstheorie nach Vroom. Zudem liegt ein Hauptaugenmerk dieser Arbeit auf der Anpassung der Zwei-Faktoren-Theorie nach Herzberg auf die heutige Zeit.
Empirisch basiert die Dissertation auf einem dreistufigen Untersuchungsdesign. Die erste Stufe umfasst eine quantitative Befragung von insgesamt 459 Abiturienten/-innen und 100 Studierenden. In der zweiten Stufe wurden 10 Studieren-de und 12 Abiturienten/-innen qualitativ befragt. Eine Validierung der Ergebnis-se erfolgte in der dritten Stufe mittels Experteninterviews. Das Ziel der empirischen Untersuchung bestand in der Überprüfung von vier Hypothesen als Basis zur Modellableitung:
Hypothese H1 - Flexibilität erhöht die Attraktivität einer wirtschaftsorientierten Ausbildung: Der Faktor Flexibilität wurde als ein relevanter Motivator für die Wahl eines Ausbildungsweges identifiziert. Jugendliche wollen sich heutzutage nicht sofort bzw. nicht zu früh festlegen müssen.
Hypothese H2 - Auslandsaufenthalte erhöhen die Attraktivität einer wirtschaftsorientierten Ausbildung: Es wurde bestätigt, dass Auslandsaufenthalte die Attraktivität einer wirtschaftsorientierten Ausbildung steigert, es besteht jedoch eine Reihe von Barrieren, die Jugendliche (obwohl sie den grundsätzlichen Vor-teil sehen) davon abhalten, einen Auslandsaufenthalt für sich selbst in Betracht zu ziehen.
Hypothese H3 - Das Aufzeigen einer Karriereperspektive erhöht die Attraktivität einer wirtschaftsorientierten Ausbildung: Für die Generation der heutigen Jugendlichen steht bezüglich der Wahl ihres Ausbildungsweges die Aussicht auf eine Tätigkeit im Vordergrund, die ein gesichertes Einkommen und somit ein gutes Leben ermöglicht und zudem aus ihrer Sicht eine gewisse Sinnhaftigkeit hat. Führungspositionen, in denen auch höhere Verantwortung übernommen wird, strebt nur eine Minderheit an.
Hypothese H4 - Zusätzliche monetäre Anreize erhöhen die Attraktivität einer wirtschaftsorientierten Ausbildung: Vergütungsbestandteile werden grundsätzlich nicht abgelehnt (das wäre auch irrational), haben jedoch auch nicht die Anreizfunktion, die ihr auf Basis der Voruntersuchung im Rahmen dieser Arbeit hätte unterstellt werden können. Für die Entscheidungsfindung bezüglich eines Ausbildungsweges spielen sie nur eine untergeordnete Rolle. Dennoch trägt die Vergütung zur Attraktivität eines Ausbildungsweges bei.
Basierend auf den zuvor genannten Ergebnissen wurde das Modell einer wirtschaftsorientieren Ausbildung abgeleitet, das sowohl horizontal als auch vertikal flexibel ist. Horizontale Flexibilität ist dadurch gegeben, dass innerhalb eines Ausbildungsjahres unterschiedliche Unternehmen und Branchen kennengelernt werden (Jahr 1 und Jahr 2). Eine Spezialisierung erfolgt erst in den späteren Ausbildungsjahren. Durch die Möglichkeit, nach jedem Ausbildungsjahr mit einem Abschluss ins Berufsleben zu wechseln und die Ausbildung gegebenenfalls zu einem späteren Zeitpunkt fortzusetzen, ist auch eine vertikale Flexibilität gegeben. Zudem bietet das Modell Studienabbrechern/-innen die Möglichkeit, im Ausbildungsjahr 2 bzw. 3 in die Ausbildung einzusteigen. Im Jahr 2 und/oder Jahr 3 sind Auslandsaufenthalte integriert. Diese werden fakultativ an-geboten. Bereits ab dem Jahr 1 besteht die Möglichkeit, Vorbereitungskurse zu belegen. Der hohen Bedeutung der Karriereperspektive wird im abgeleiteten Modell auf mehreren Ebenen Rechnung getragen. So werden nach jedem Ausbildungsjahr anerkannte Abschlüsse erreicht. Während diese in den Jahren 1 und 2 mit IHK-Abschlüssen gleichzusetzen sind, beginnen ab Jahr 3 die akademischen Graduierungen (Jahr 3 Bachelor, Jahr 4 Master). Die Vergütung wird Bestandteil einer wirtschaftsorientierten Ausbildung, wobei ihre Höhe mit Dauer der Ausbildung zunimmt.
Da mit der Einführung des Modells einer wirtschaftsorientierten Ausbildung die Überwindung von institutionellen Paradigmen und Schranken verbunden sind, erfolgte im Rahmen des Ausblicks der Arbeit eine weitere Expertenbefragung bezüglich seiner Umsetzbarkeit. Es setzt eine Beweglichkeit von institutioneller Seite voraus (hierbei insbesondere auch von den Kammern), die von der Mehr-zahl der Experten derzeit skeptisch gesehen wird. Die konzeptionelle Ausgestaltung findet grundsätzlichen Zuspruch, wobei in einigen Details, zum Beispiel in der Dauer der Ausbildung, noch Klärungsbedarf besteht.
Grundsätzlich schließen sich die Experten/-innen der Meinung der Autorin an, dass ein Sinneswandel in der deutschen Ausbildungslandschaft gewünscht und gefordert wird. Dies betrifft insbesondere auch den kaufmännischen Bereich. Diese Arbeit liefert mit dem Modell der wirtschaftsorientierten Ausbildung einen wichtigen Beitrag zur Diskussion über neue Ausbildungswege.
Global climate change is one of the greatest challenges of the 21st century, with influence on the environment, societies, politics and economies. The (semi-)arid areas of Southern Africa already suffer from water scarcity. There is a great variety of ongoing research related to global climate history but important questions on regional differences still exist.
In southern African regions terrestrial climate archives are rare, which makes paleoclimate studies challenging. Based on the assumption that continental pans (sabkhas) represent a suitable geo-archive for the climate history, two different pans were studied in the southern and western Kalahari Desert. A combined approach of molecular biological and biogeochemical analyses is utilized to investigate the diversity and abundance of microorganisms and to trace temporal and spatial changes in paleoprecipitation in arid environments. The present PhD thesis demonstrates the applicability of pan sediments as a late Quaternary geo-archive based on microbial signature lipid biomarkers, such as archaeol, branched and isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) as well as phospholipid fatty acids (PLFA). The microbial signatures contained in the sediment provide information on the current or past microbial community from the Last Glacial Maximum to the recent epoch, the Holocene. The results are discussed in the context of regional climate evolution in southwestern Africa. The seasonal shift of the Innertropical Convergence Zone (ITCZ) along the equator influences the distribution of precipitation- and climate zones. The different expansion of the winter- and summer rainfall zones in southern Africa was confirmed by the frequency of certain microbial biomarkers. A period of increased precipitation in the south-western Kalahari could be described as a result of the extension of the winter rainfall zone during the last glacial maximum (21 ± 2 ka). Instead a period of increased paleoprecipitation in the western Kalahari was indicated during the Late Glacial to Holocene transition. This was possibly caused by a southwestern shift in the position of the summer rainfall zone associated to the southward movement of the ITCZ.
Furthermore, for the first time this study characterizes the bacterial and archaeal life based on 16S rRNA gene high-throughput sequencing in continental pan sediments and provides an insight into the recent microbial community structure. Near-surface processes play an important role for the modern microbial ecosystem in the pans. Water availability as well as salinity might determine the abundance and composition of the microbial communities. The microbial community of pan sediments is dominated by halophilic and dry-adapted archaea and bacteria. Frequently occurring microorganisms such as, Halobacteriaceae, Bacillus and Gemmatimonadetes are described in more detail in this study.
Today, more than half of the world’s population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe.
To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing.
Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands.
Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household’s resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk.
While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response.
These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household’s risk awareness, while the degree of loss is mainly explained by impact variables.
Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine.
The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate.
Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building’s structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions.
The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment.
In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high.
Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons:
First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses.
Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated.
This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.
Systems biology aims at investigating biological systems in its entirety by gathering and analyzing large-scale data sets about the underlying components. Computational systems biology approaches use these large-scale data sets to create models at different scales and cellular levels. In addition, it is concerned with generating and testing hypotheses about biological processes. However, such approaches are inevitably leading to computational challenges due to the high dimensionality of the data and the differences in the dimension of data from different cellular layers.
This thesis focuses on the investigation and development of computational approaches to analyze metabolite profiles in the context of cellular networks. This leads to determining what aspects of the network functionality are reflected in the metabolite levels. With these methods at hand, this thesis aims to answer three questions: (1) how observability of biological systems is manifested in metabolite profiles and if it can be used for phenotypical comparisons; (2) how to identify couplings of reaction rates from metabolic profiles alone; and (3) which regulatory mechanism that affect metabolite levels can be distinguished by integrating transcriptomics and metabolomics read-outs.
I showed that sensor metabolites, identified by an approach from observability theory, are more correlated to each other than non-sensors. The greater correlations between sensor metabolites were detected both with publicly available metabolite profiles and synthetic data simulated from a medium-scale kinetic model. I demonstrated through robustness analysis that correlation was due to the position of the sensor metabolites in the network and persisted irrespectively of the experimental conditions. Sensor metabolites are therefore potential candidates for phenotypical comparisons between conditions through targeted metabolic analysis.
Furthermore, I demonstrated that the coupling of metabolic reaction rates can be investigated from a purely data-driven perspective, assuming that metabolic reactions can be described by mass action kinetics. Employing metabolite profiles from domesticated and wild wheat and tomato species, I showed that the process of domestication is associated with a loss of regulatory control on the level of reaction rate coupling. I also found that the same metabolic pathways in Arabidopsis thaliana and Escherichia coli exhibit differences in the number of reaction rate couplings.
I designed a novel method for the identification and categorization of transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approach determines the partial correlation of metabolites with control by the principal components of the transcript levels. The principle components contain the majority of the transcriptomic information allowing to partial out the effect of the transcriptional layer from the metabolite profiles. Depending whether the correlation between metabolites persists upon controlling for the effect of the transcriptional layer, the approach allows us to group metabolite pairs into being associated due to post-transcriptional or transcriptional regulation, respectively. I showed that the classification of metabolite pairs into those that are associated due to transcriptional or post-transcriptional regulation are in agreement with existing literature and findings from a Bayesian inference approach.
The approaches developed, implemented, and investigated in this thesis open novel ways to jointly study metabolomics and transcriptomics data as well as to place metabolic profiles in the network context. The results from these approaches have the potential to provide further insights into the regulatory machinery in a biological system.
Magnetotellurics (MT) is a geophysical method that is able to image the electrical conductivity structure of the subsurface by recording time series of natural electromagnetic (EM) field variations. During the data processing these time series are divided into small segments and for each segment spectral values are computed which are typically averaged in a statistical manner to obtain MT transfer functions. Unfortunately, the presence of man-made EM noise sources often deteriorates a significant amount of the recorded time series resulting in disturbed transfer functions. Many advanced processing techniques, e.g. robust statistics, pre-stack data selection or remote reference, have been developed to tackle this problem. The first two techniques reduce the amount of outliers and noise in the data whereas the latter approach removes noise by using data from another MT station. However, especially in populated regions the data processing is still quite challenging even with these approaches. In this thesis, I present two novel pre-stack data confinement and selection criteria for the detection of outliers and noise affected data based on (i) a distance measure of each data segment with regard to the entire sample distribution and (ii) the evaluation of the magnetic polarisation direction of all segments. The first criterion is able to remove data points that scatter around the desired MT distribution and furthermore it can, under some circumstances, even reject complete data cluster originating from noise sources. The second criterion eliminates data points caused by a strongly polarised magnetic signal. Both criteria have been successfully applied to many stations with different noise contaminations showing that they can significantly improve the transfer function estimation. The novel criteria were used to evaluate a MT data set from the Eastern Karoo Basin in South Africa. The corresponding field experiment is part of an extensive research programme to collect information of the current e.g. geological setting in this region prior to a potential shale gas exploitation. The aim was to investigate whether a three-dimensional (3D) inversion of the newly measured data fosters a more realistic mapping of physical properties of the target horizon. For this purpose, a comprehensive 3D model was derived by using all available data. In a second step, I analysed parameters of the target horizon, e.g. its conductivity, that are proxies for physical properties such as thermal maturity and porosity.
The climate is a complex dynamical system involving interactions and feedbacks among different processes at multiple temporal and spatial scales. Although numerous studies have attempted to understand the climate system, nonetheless, the studies investigating the multiscale characteristics of the climate are scarce. Further, the present set of techniques are limited in their ability to unravel the multi-scale variability of the climate system. It is completely plausible that extreme events and abrupt transitions, which are of great interest to climate community, are resultant of interactions among processes operating at multi-scale. For instance, storms, weather patterns, seasonal irregularities such as El Niño, floods and droughts, and decades-long climate variations can be better understood and even predicted by quantifying their multi-scale dynamics. This makes a strong argument to unravel the interaction and patterns of climatic processes at different scales. With this background, the thesis aims at developing measures to understand and quantify multi-scale interactions within the climate system.
In the first part of the thesis, I proposed two new methods, viz, multi-scale event synchronization (MSES) and wavelet multi-scale correlation (WMC) to capture the scale-specific features present in the climatic processes. The proposed methods were tested on various synthetic and real-world time series in order to check their applicability and replicability. The results indicate that both methods (WMC and MSES) are able to capture scale-specific associations that exist between processes at different time scales in a more detailed manner as compared to the traditional single scale counterparts.
In the second part of the thesis, the proposed multi-scale similarity measures were used in constructing climate networks to investigate the evolution of spatial connections within climatic processes at multiple timescales. The proposed methods WMC and MSES, together with complex network were applied to two different datasets.
In the first application, climate networks based on WMC were constructed for the univariate global sea surface temperature (SST) data to identify and visualize the SSTs patterns that develop very similarly over time and distinguish them from those that have long-range teleconnections to other ocean regions. Further investigations of climate networks on different timescales revealed (i) various high variability and co-variability regions, and (ii) short and long-range teleconnection regions with varying spatial distance. The outcomes of the study not only re-confirmed the existing knowledge on the link between SST patterns like El Niño Southern Oscillation and the Pacific Decadal Oscillation, but also suggested new insights into the characteristics and origins of long-range teleconnections.
In the second application, I used the developed non-linear MSES similarity measure to quantify the multivariate teleconnections between extreme Indian precipitation and climatic patterns with the highest relevance for Indian sub-continent. The results confirmed significant non-linear influences that were not well captured by the traditional methods. Further, there was a substantial variation in the strength and nature of teleconnection across India, and across time scales.
Overall, the results from investigations conducted in the thesis strongly highlight the need for considering the multi-scale aspects in climatic processes, and the proposed methods provide robust framework for quantifying the multi-scale characteristics.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Kolorektalkrebs (CRC) ist die dritthäufigste Tumorerkrankung weltweit. Neben dem Alter spielt auch die Ernährung eine wichtige Rolle bei der Entstehung der Krankheit. Eine vermutlich krebspräventive Wirkung wird dabei dem Spurenelement Selen zugeschrieben, das fast ausschließlich über Lebensmittel aufgenommen wird. So hängt beispielsweise ein niedriger Selenstatus mit dem Risiko, im Laufe des Lebens an CRC zu erkranken, zusammen. Seine Funktionen vermittelt Selen dabei überwiegend durch Selenoproteine, in denen es in Form von Selenocystein eingebaut wird. Zu den bisher am besten untersuchten Selenoproteinen mit möglicher Funktion während CRC zählen die Glutathionperoxidasen (GPXen). Die Mitglieder dieser Familie tragen aufgrund ihrer Hydroperoxid-reduzierenden Eigenschaften entscheidend zum Schutz der Zellen vor oxidativem Stress bei. Dies kann je nach Art und Stadium des Tumors entweder krebshemmend oder -fördernd wirken, da auch transformierte Zellen von dieser Schutzfunktion profitieren.
In dieser Arbeit wurde die GPX2 in HT29-Darmkrebszellen mithilfe stabil-transfizierter shRNA herunterreguliert, um die Funktion des Enzyms vor allem in Hinblick auf regulierte Signalwege zu untersuchen. Ein Knockdowns (KD) der strukturell ähnlichen GPX1 kam ebenfalls zum Einsatz, um gezielt Isoform-spezifische Funktionen unterscheiden zu können. Anhand eines PCR-Arrays wurden Signalwege identifiziert, die auf einen Einfluss der beiden Proteine im Zellwachstum hindeuteten. Anschließende Untersuchungen ließen auf einen verminderten Differenzierungsstatus in den GPX1- und GPX2-KDs aufgrund einer geringeren Aktivität der Alkalischen Phosphatase schließen. Zudem war die Zellviabilität im Neutralrot-Assay (NRU) bei Fehlen der GPX1 bzw. GPX2 im Vergleich zur Kontrolle reduziert. Die Ergebnisse des PCR-Arrays, und speziell für die GPX2 frühere Untersuchungen der Arbeitsgruppe, wiesen weiterhin auf eine Rolle der beiden Proteine in der entzündungsgetriebenen Karzinogenese hin. Daher wurden auch mögliche Interaktionen mit dem NFκB-Signalweg analysiert. Eine Stimulation der Zellen mit dem proinflammatorischen Zytokin IL1β ging mit einer verstärkten Aktivierung der MAP-Kinasen ERK1/2 in den Zellen mit GPX1- bzw. GPX2-KD einher. Die gleichzeitige Behandlung mit dem Antioxidans NAC führte nicht zur Rücknahme der Effekte in den KDs, sodass möglicherweise nicht nur die antioxidativen Eigenschaften der Enzyme bei der Interaktion mit diesen Signalwegsproteinen relevant sind.
Weiterhin wurden Analysen zum Substratspektrum der GPX2 in HCT116-Zellen mit einer Überexpression des Proteins durchgeführt. Dabei zeigte sich mittels NRU-Assay und DNA-Laddering, dass die GPX2 besonders vor den proapoptotischen Effekten einer Behandlung mit den Lipidhydroperoxiden HPODE und HPETE schützt.
Im Gegensatz zur GPX2 lässt sich Selenoprotein H (SELENOH) stärker durch die alimentäre Selenzufuhr beeinflussen. Einer möglichen Nutzung als Biomarker oder gar als Ansatzpunkt bei der Prävention bzw. Behandlung von CRC steht allerdings unvollständiges Wissen über die Funktion des Proteins gegenüber. Zur genaueren Charakterisierung von SELENOH wurden daher stabil-transfizierte KD-Klone in HT29- und Caco2-Zellen hergestellt und zunächst auf ihre Tumorigenität untersucht.
Zellen mit SELENOH-KD bildeten mehr und größere Kolonien im Soft Agar und zeigten ein erhöhtes Proliferations- und Migrationspotenzial im Vergleich zur Kontrolle.
Ein Xenograft in Nacktmäusen resultierte zudem in einer stärkeren Tumorbildung nach Injektion von KD-Zellen. Untersuchungen zur Beteiligung von SELENOH an der Zellzyklusregulation deuten auf eine hemmende Rolle des Proteins in der G1/S-Phase hin.
Die weiterhin beobachtete Hochregulation von SELENOH in humanen Adenokarzinomen und präkanzerösem Mausgewebe lässt sich möglicherweise mit der postulierten Schutzfunktion vor oxidativen Zell- und DNA-Schäden erklären. In gesunden Darmepithelzellen war das Protein vorrangig am Kryptengrund lokalisiert, was zu einer potenziellen Rolle während der gastrointestinalen Differenzierung passt.
In the thesis there are constructed new quantizations for pseudo-differential boundary value problems (BVPs) on manifolds with edge. The shape of operators comes from Boutet de Monvel’s calculus which exists on smooth manifolds with boundary. The singular case, here with edge and boundary, is much more complicated. The present approach simplifies the operator-valued symbolic structures by using suitable Mellin quantizations on infinite stretched model cones of wedges with boundary. The Mellin symbols themselves are, modulo smoothing ones, with asymptotics, holomorphic in the complex Mellin covariable. One of the main results is the construction of parametrices of elliptic elements in the corresponding operator algebra, including elliptic edge conditions.
In a changing world facing several direct or indirect anthropogenic challenges the freshwater resources are endangered in quantity and quality. An excessive supply of nutrients, for example, can cause disproportional phytoplankton development and oxygen deficits in large rivers, leading to failure of the aims requested by the Water Framework Directive (WFD). Such problems can be observed in many European river catchments including the Elbe basin, and effective measures for improving water quality status are highly appreciated.
In water resources management and protection, modelling tools can help to understand the dominant nutrient processes and to identify the main sources of nutrient pollution in a watershed. They can be effective instruments for impact assessments investigating the effects of changing climate or socio-economic conditions on the status of surface water bodies, and for testing the usefulness of possible protection measures. Due to the high number of interrelated processes, ecohydrological model approaches containing water quality components are more complex than the pure hydrological ones, and their setup and calibration require more efforts. Such models, including the Soil and Water Integrated Model (SWIM), still need some further development and improvement.
Therefore, this cumulative dissertation focuses on two main objectives: 1) the approach-related objectives aiming in the SWIM model improvement and further development regarding nutrient (nitrogen and phosphorus) process description, and 2) the application-related objectives in meso- to large-scale Elbe river basins to support adaptive river basin management in view of possible future changes. The dissertation is based on five scientific papers published in international journals and dealing with these research questions.
Several adaptations were implemented in the model code to improve the representation of nutrient processes including a simple wetland approach, an extended by ammonium nitrogen cycle in the soils, as well as a detailed in-stream module, simulating algal growth, nutrient transformation processes and oxygen conditions in the river reaches, mainly driven by water temperature and light. Although this new approaches created a highly complex ecohydrological model with a large number of additional calibration parameters and rising uncertainty, the calibration and validation of the SWIM model enhanced by the new approaches in selected subcatchment and the entire Elbe river basin delivered satisfactory to good model results in terms of criteria of fit. Thus, the calibrated and validated model provided a sound base for the assessment of possible future changes and impacts in climate, land use and management in the Elbe river (sub)basin(s).
The new enhanced modelling approach improved the applicability of the SWIM model for the WFD related research questions, where the ability to consider biological water quality components (such as phytoplankton) is important. It additionally enhanced its ability to simulate the behaviour of nutrients coming mainly from point sources (e.g. phosphate phosphorus). Scenario results can be used by decision makers and stakeholders to find and understand future challenges and possible adaptation measures in the Elbe river basin.
Gamma-ray astronomy has proven to provide unique insights into cosmic-ray accelerators in the past few decades. By combining information at the highest photon energies with the entire electromagnetic spectrum in multi-wavelength studies, detailed knowledge of non-thermal particle populations in astronomical objects and systems has been gained: Many individual classes of gamma-ray sources could be identified inside our galaxy and outside of it. Different sources were found to exhibit a wide range of temporal evolution, ranging from seconds to stable behaviours over many years of observations. With the dawn of both neutrino- and gravitational wave astronomy, additional messengers have come into play over the last years. This development presents the advent of multi-messenger astronomy: a novel approach not only to search for sources of cosmic rays, but for astronomy in general.
In this thesis, both traditional multi-wavelength studies and multi-messenger studies will be presented. They were carried out with the H.E.S.S. experiment, an imaging air Cherenkov telescope array located in the Khomas Highland of Namibia. H.E.S.S. has entered its second phase in 2012 with the addition of a large, fifth telescope. While the initial array was limited to the study of gamma-rays with energies above 100 GeV, the new instrument allows to access gamma-rays with energies down to a few tens of GeV. Strengths of the multi-wavelength approach will be demonstrated at the example of the galaxy NGC253, which is undergoing an episode of enhanced star-formation. The gamma-ray emission will be discussed in light of all the information on this system available from radio, infrared and X-rays. These wavelengths reveal detailed information on the population of supernova remnants, which are suspected cosmic-ray accelerators. A broad-band gamma-ray spectrum is derived from H.E.S.S. and Fermi-LAT data. The improved analysis of H.E.S.S. data provides a measurement which is no longer dominated by systematic uncertainties. The long-term behaviour of cosmic rays in the starburst galaxy NGC253 is finally characterised.
In contrast to the long time-scale evolution of a starburst galaxy, multi-messenger studies are especially intriguing when shorter time-scales are being probed. A prime example of a short time-scale transient are Gamma Ray Bursts. The efforts to understand this phenomenon effectively founded the branch of gamma-ray astronomy. The multi-messenger approach allows for the study of illusive phenomena such as Gamma Ray Bursts and other transients using electromagnetic radiation, neutrinos, cosmic rays and gravitational waves contemporaneously. With contemporaneous observations getting more important just recently, the execution of such observation campaigns still presents a big challenge due to the different limitations and strengths of the infrastructures.
An alert system for transient phenomena has been developed over the course of this thesis for H.E.S.S. It aims to address many follow-up challenges in order to maximise the science return of the new large telescope, which is able to repoint much faster than the initial four telescopes. The system allows for fully automated observations based on scientific alerts from any wavelength or messenger and allows H.E.S.S. to participate in multi-messenger campaigns. Utilising this new system, many interesting multi-messenger observation campaigns have been performed. Several highlight observations with H.E.S.S. are analysed, presented and discussed in this work. Among them are observations of Gamma Ray Bursts with low latency and low energy threshold, the follow-up of a neutrino candidate in spatial coincidence with a flaring active galactic nucleus and of the merger of two neutron stars, which was revealed by the coincidence of gravitational waves and a Gamma-Ray Burst.
Modern gamma-ray telescopes, provide the main stream of data for astrophysicists in quest of detecting the sources of gamma rays such as active galactic nuclei (AGN). Many blazars have been detected with gamma-ray telescopes such as HESS, VERITAS, MAGIC and Fermi satellite as sources of gamma-rays with the energy E ≥ 100 GeV. These very-high-energy photons interact with extragalactic background light (EBL) producing ultra-relativistic electron-positron pairs. Observations with Fermi-LAT indicate that the GeV gamma-ray flux from some blazars is lower than that predicted from the full electromagnetic cascade. The pairs can induce electrostatic and electromagnetic instabilities. In this case, wave-particle interactions can reduce the energy of the pairs. Therefore, the collective plasma effects can also substantially suppress the GeV-band gamma-ray emission affecting as well the IGMF constraints. Using Particle in cell (PIC) simulations, we have revisited the issue of plasma instabilities induced by electron-positron beams in the fully ionized intergalactic medium. This problem is related to pair beams produced by TeV radiation of blazars. The main objective of our study is to clarify the feedback of the beam-driven instabilities on the pairs. The present dissertation provides new results regarding the plasma instabilities from blazar induced pair beams interacting with intergalactic medium. This clarifies the relevance of plasma instabilities and improves our understanding of blazars.