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Institute
- Extern (201) (remove)
The potential increase in frequency and magnitude of extreme floods is currently discussed in terms of global warming and the intensification of the hydrological cycle. The profound knowledge of past natural variability of floods is of utmost importance in order to assess flood risk for the future. Since instrumental flood series cover only the last ~150 years, other approaches to reconstruct historical and pre-historical flood events are needed. Annually laminated (varved) lake sediments are meaningful natural geoarchives because they provide continuous records of environmental changes > 10000 years down to a seasonal resolution. Since lake basins additionally act as natural sediment traps, the riverine sediment supply, which is preserved as detrital event layers in the lake sediments, can be used as a proxy for extreme discharge events. Within my thesis I examined a ~ 8.50 m long sedimentary record from the pre-Alpine Lake Mondsee (Northeast European Alps), which covered the last 7000 years. This sediment record consists of calcite varves and intercalated detrital layers, which range in thickness from 0.05 to 32 mm. Detrital layer deposition was analysed by a combined method of microfacies analysis via thin sections, Scanning Electron Microscopy (SEM), μX-ray fluorescence (μXRF) scanning and magnetic susceptibility. This approach allows characterizing individual detrital event layers and assigning a corresponding input mechanism and catchment. Based on varve counting and controlled by 14C age dates, the main goals of this thesis are (i) to identify seasonal runoff processes, which lead to significant sediment supply from the catchment into the lake basin and (ii) to investigate flood frequency under changing climate boundary conditions. This thesis follows a line of different time slices, presenting an integrative approach linking instrumental and historical flood data from Lake Mondsee in order to evaluate the flood record inferred from Lake Mondsee sediments. The investigation of eleven short cores covering the last 100 years reveals the abundance of 12 detrital layers. Therein, two types of detrital layers are distinguished by grain size, geochemical composition and distribution pattern within the lake basin. Detrital layers, which are enriched in siliciclastic and dolomitic material, reveal sediment supply from the Flysch sediments and Northern Calcareous Alps into the lake basin. These layers are thicker in the northern lake basin (0.1-3.9 mm) and thinner in the southern lake basin (0.05-1.6 mm). Detrital layers, which are enriched in dolomitic components forming graded detrital layers (turbidites), indicate the provenance from the Northern Calcareous Alps. These layers are generally thicker (0.65-32 mm) and are solely recorded within the southern lake basin. In comparison with instrumental data, thicker graded layers result from local debris flow events in summer, whereas thin layers are deposited during regional flood events in spring/summer. Extreme summer floods as reported from flood layer deposition are principally caused by cyclonic activity from the Mediterranean Sea, e.g. July 1954, July 1997 and August 2002. During the last two millennia, Lake Mondsee sediments reveal two significant flood intervals with decadal-scale flood episodes, during the Dark Ages Cold Period (DACP) and the transition from the Medieval Climate Anomaly (MCA) into the Little Ice Age (LIA) suggesting a linkage of transition to climate cooling and summer flood recurrences in the Northeastern Alps. In contrast, intermediate or decreased flood episodes appeared during the MWP and the LIA. This indicates a non-straightforward relationship between temperature and flood recurrence, suggesting higher cyclonic activity during climate transition in the Northeast Alps. The 7000-year flood chronology reveals 47 debris flows and 269 floods, with increased flood activity shifting around 3500 and 1500 varve yr BP (varve yr BP = varve years before present, before present = AD 1950). This significant increase in flood activity shows a coincidence with millennial-scale climate cooling that is reported from main Alpine glacier advances and lower tree lines in the European Alps since about 3300 cal. yr BP (calibrated years before present). Despite relatively low flood occurrence prior to 1500 varve yr BP, floods at Lake Mondsee could have also influenced human life in early Neolithic lake dwellings (5750-4750 cal. yr BP). While the first lake dwellings were constructed on wetlands, the later lake dwellings were built on piles in the water suggesting an early flood risk adaptation of humans and/or a general change of the Late Neolithic Culture of lake-dwellers because of socio-economic reasons. However, a direct relationship between the final abandonment of the lake dwellings and higher flood frequencies is not evidenced.
The last years have been affected by Covid-19 and the international emergency mecha-nism to deal with health-related threats. The effects of this period manifested differ-ently worldwide, depending on matters such as international relations, national policies, power dynamics etc. Additionally, the impact of this time will likely have long-term effects which are yet to be known. This paper gives a critical overview of the Public Health Emergency of International Concern (PHEIC) mechanism in the context of Covid-19. It does so by explaining the legal framework for states of emergency, specifically in the context of a PHEIC, while considering its restrictions and limitations on human rights. It further outlines issues in the manifestation of global protections and limitations on human rights during Covid-19. Lastly, considering the likelihood of future PHEICs and the known systemic obstructions, this paper offers ways to im-prove this mechanism from a holistic, non-zero-sum perspective.
What are the consequences of unemployment and precarious employment for individuals' health in Europe? What are the moderating factors that may offset (or increase) the health consequences of labor-market risks? How do the effects of these risks vary across different contexts, which differ in their institutional and cultural settings? Does gender, regarded as a social structure, play a role, and how? To answer these questions is the aim of my cumulative thesis. This study aims to advance our knowledge about the health consequences that unemployment and precariousness cause over the life course. In particular, I investigate how several moderating factors, such as gender, the family, and the broader cultural and institutional context, may offset or increase the impact of employment instability and insecurity on individual health.
In my first paper, 'The buffering role of the family in the relationship between job loss and self-perceived health: Longitudinal results from Europe, 2004-2011', I and my co-authors measure the causal effect of job loss on health and the role of the family and welfare states (regimes) as moderating factors. Using EU-SILC longitudinal data (2004-2011), we estimate the probability of experiencing 'bad health' following a transition to unemployment by applying linear probability models and undertake separate analyses for men and women. Firstly, we measure whether changes in the independent variable 'job loss' lead to changes in the dependent variable 'self-rated health' for men and women separately. Then, by adding into the model different interaction terms, we measure the moderating effect of the family, both in terms of emotional and economic support, and how much it varies across different welfare regimes. As an identification strategy, we first implement static fixed-effect panel models, which control for time-varying observables and indirect health selection—i.e., constant unobserved heterogeneity. Secondly, to control for reverse causality and path dependency, we implement dynamic fixed-effect panel models, adding a lagged dependent variable to the model.
We explore the role of the family by focusing on close ties within households: we consider the presence of a stable partner and his/her working status as a source of social and economic support. According to previous literature, having a partner should reduce the stress from adverse events, thanks to the symbolic and emotional dimensions that such a relationship entails, regardless of any economic benefits. Our results, however, suggest that benefits linked to the presence of a (female) partner also come from the financial stability that (s)he can provide in terms of a second income. Furthermore, we find partners' employment to be at least as important as the mere presence of the partner in reducing the negative effect of job loss on the individual's health by maintaining the household's standard of living and decreasing economic strain on the family. Our results are in line with previous research, which has highlighted that some people cope better than others with adverse life circumstances, and the support provided by the family is a crucial resource in that regard.
We also reported an important interaction between the family and the welfare state in moderating the health consequences of unemployment, showing how the compensation effect of the family varies across welfare regimes. The family plays a decisive role in cushioning the adverse consequences of labor market risks in Southern and Eastern welfare states, characterized by less developed social protection systems and –especially the Southern – high level of familialism.
The first paper also found important gender differences concerning job loss, family and welfare effects. Of particular interest is the evidence suggesting that health selection works differently for men and women, playing a more prominent role for women than for men in explaining the relationship between job loss and self-perceived health. The second paper, 'Gender roles and selection mechanisms across contexts: A comparative analysis of the relationship between unemployment, self-perceived health, and gender.' investigates more in-depth the gender differential in health driven by unemployment.
Being a highly contested issue in literature, we aim to study whether men are more penalized than women or the other way around and the mechanisms that may explain the gender difference. To do that, we rely on two theoretical arguments: the availability of alternative roles and social selection. The first argument builds on the idea that men and women may compensate for the detrimental health consequences of unemployment through the commitment to 'alternative roles,' which can provide for the resources needed to fulfill people's socially constructed needs. Notably, the availability of alternative options depends on the different positions that men and women have in society.
Further, we merge the availability of the 'alternative roles' argument with the health selection argument. We assume that health selection could be contingent on people's social position as defined by gender and, thus, explain the gender differential in the relationship between unemployment and health. Ill people might be less reluctant to fall or remain (i.e., self-select) in unemployment if they have alternative roles. In Western societies, women generally have more alternative roles than men and thus more discretion in their labor market attachment. Therefore, health selection should be stronger for them, explaining why unemployment is less menace for women than for their male counterparts.
Finally, relying on the idea of different gender regimes, we extended these arguments to comparison across contexts. For example, in contexts where being a caregiver is assumed to be women's traditional and primary roles and the primary breadwinner role is reserved to men, unemployment is less stigmatized, and taking up alternative roles is more socially accepted for women than for men (Hp.1). Accordingly, social (self)selection should be stronger for women than for men in traditional contexts, where, in the case of ill-health, the separation from work is eased by the availability of alternative roles (Hp.2).
By focusing on contexts that are representative of different gender regimes, we implement a multiple-step comparative approach. Firstly, by using EU-SILC longitudinal data (2004-2015), our analysis tests gender roles and selection mechanisms for Sweden and Italy, representing radically different gender regimes, thus providing institutional and cultural variation. Then, we limit institutional heterogeneity by focusing on Germany and comparing East- and West-Germany and older and younger cohorts—for West-Germany (SOEP data 1995-2017). Next, to assess the differential impact of unemployment for men and women, we compared (unemployed and employed) men with (unemployed and employed) women. To do so, we calculate predicted probabilities and average marginal effect from two distinct random-effects probit models. Our first step is estimating random-effects models that assess the association between unemployment and self-perceived health, controlling for observable characteristics. In the second step, our fully adjusted model controls for both direct and indirect selection. We do this using dynamic correlated random-effects (CRE) models. Further, based on the fully adjusted model, we test our hypotheses on alternative roles (Hp.1) by comparing several contexts – models are estimated separately for each context. For this hypothesis, we pool men and women and include an interaction term between unemployment and gender, which has the advantage to allow for directly testing whether gender differences in the effect of unemployment exist and are statistically significant. Finally, we test the role of selection mechanisms (Hp.2), using the KHB method to compare coefficients across nested nonlinear models. Specifically, we test the role of selection for the relationship between unemployment and health by comparing the partially-adjusted and fully-adjusted models. To allow selection mechanisms to operate differently between genders, we estimate separate models for men and women.
We found support to our first hypotheses—the context where people are embedded structures the relationship between unemployment, health, and gender. We found no gendered effect of unemployment on health in the egalitarian context of Sweden. Conversely, in the traditional context of Italy, we observed substantive and statistically significant gender differences in the effect of unemployment on bad health, with women suffering less than men. We found the same pattern for comparing East and West Germany and younger and older cohorts in West Germany.
On the contrary, our results did not support our theoretical argument on social selection. We found that in Sweden, women are more selected out of employment than men. In contrast, in Italy, health selection does not seem to be the primary mechanism behind the gender differential—Italian men and women seem to be selected out of employment to the same extent. Namely, we do not find any evidence that health selection is stronger for women in more traditional countries (Hp2), despite the fact that the institutional and the cultural context would offer them a more comprehensive range of 'alternative roles' relative to men. Moreover, our second hypothesis is also rejected in the second and third comparisons, where the cross-country heterogeneity is reduced to maximize cultural differences within the same institutional context. Further research that addresses selection into inactivity is needed to evaluate the interplay between selection and social roles across gender regimes.
While the health consequences of unemployment have been on the research agenda for a pretty long time, the interest in precarious employment—defined as the linking of the vulnerable worker to work that is characterized by uncertainty and insecurity concerning pay, the stability of the work arrangement, limited access to social benefits, and statutory protections—has emerged only later. Since the 80s, scholars from different disciplines have raised concerns about the social consequences of de-standardization of employment relationships. However, while work has become undoubtedly more precarious, very little is known about its causal effect on individual health and the role of gender as a moderator. These questions are at the core of my third paper : 'Bad job, bad health? A longitudinal analysis of the interaction between precariousness, gender and self-perceived health in Germany'. Herein, I investigate the multidimensional nature of precarious employment and its causal effect on health, particularly focusing on gender differences.
With this paper, I aim at overcoming three major shortcomings of earlier studies: The first one regards the cross-sectional nature of data that prevents the authors from ruling out unobserved heterogeneity as a mechanism for the association between precarious employment and health. Indeed, several unmeasured individual characteristics—such as cognitive abilities—may confound the relationship between precarious work and health, leading to biased results. Secondly, only a few studies have directly addressed the role of gender in shaping the relationship. Moreover, available results on the gender differential are mixed and inconsistent: some found precarious employment being more detrimental for women's health, while others found no gender differences or stronger negative association for men. Finally, previous attempts to an empirical translation of the employment precariousness (EP) concept have not always been coherent with their theoretical framework. EP is usually assumed to be a multidimensional and continuous phenomenon; it is characterized by different dimensions of insecurity that may overlap in the same job and lead to different "degrees of precariousness." However, researchers have predominantly focused on one-dimensional indicators—e.g., temporary employment, subjective job insecurity—to measure EP and study the association with health. Besides the fact that this approach partially grasps the phenomenon's complexity, the major problem is the inconsistency of evidence that it has produced. Indeed, this line of inquiry generally reveals an ambiguous picture, with some studies finding substantial adverse effects of temporary over permanent employment, while others report only minor differences.
To measure the (causal) effect of precarious work on self-rated health and its variation by gender, I focus on Germany and use four waves from SOEP data (2003, 2007, 2011, and 2015). Germany is a suitable context for my study. Indeed, since the 1980s, the labor market and welfare system have been restructured in many ways to increase the German economy's competitiveness in the global market. As a result, the (standard) employment relationship has been de-standardized: non-standard and atypical employment arrangements—i.e., part-time work, fixed-term contracts, mini-jobs, and work agencies—have increased over time while wages have lowered, even among workers with standard work. In addition, the power of unions has also fallen over the last three decades, leaving a large share of workers without collective protection. Because of this process of de-standardization, the link between wage employment and strong social rights has eroded, making workers more powerless and more vulnerable to labor market risks than in the past. EP refers to this uneven distribution of power in the employment relationship, which can be detrimental to workers' health. Indeed, by affecting individuals' access to power and other resources, EP puts precarious workers at risk of experiencing health shocks and influences their ability to gain and accumulate health advantages (Hp.1).
Further, the focus on Germany allows me to investigate my second research question on the gender differential. Germany is usually regarded as a traditionalist gender regime: a context characterized by a configuration of roles. Here, being a caregiver is assumed to be women's primary role, whereas the primary breadwinner role is reserved for men. Although many signs of progress have been made over the last decades towards a greater equalization of opportunities and more egalitarianism, the breadwinner model has barely changed towards a modified version. Thus, women usually take on the double role of workers (the so-called secondary earner) and caregivers, and men still devote most of their time to paid work activities. Moreover, the overall upward trend towards more egalitarian gender ideologies has leveled off over the last decades, moving notably towards more traditional gender ideologies.
In this setting, two alternative hypotheses are possible. Firstly, I assume that the negative relationship between EP and health is stronger for women than for men. This is because women are systematically more disadvantaged than men in the public and private spheres of life, having less access to formal and informal sources of power. These gender-related power asymmetries may interact with EP-related power asymmetries resulting in a stronger effect of EP on women's health than on men's health (Hp.2).
An alternative way of looking at the gender differential is to consider the interaction that precariousness might have with men's and women's gender identities. According to this view, the negative relationship between EP and health is weaker for women than for men (Hp.2a). In a society with a gendered division of labor and a strong link between masculine identities and stable and well-rewarded job—i.e., a job that confers the role of primary family provider—a male worker with precarious employment might violate the traditional male gender role. Men in precarious jobs may perceive themselves (and by others) as possessing a socially undesirable characteristic, which conflicts with the stereotypical idea of themselves as the male breadwinner. Engaging in behaviors that contradict stereotypical gender identity may decrease self-esteem and foster feelings of inferiority, helplessness, and jealousy, leading to poor health.
I develop a new indicator of EP that empirically translates a definition of EP as a multidimensional and continuous phenomenon. I assume that EP is a latent construct composed of seven dimensions of insecurity chosen according to the theory and previous empirical research: Income insecurity, social insecurity, legal insecurity, employment insecurity, working-time insecurity, representation insecurity, worker's vulnerability. The seven dimensions are proxied by eight indicators available in the four waves of the SOEP dataset. The EP composite indicator is obtained by performing a multiple correspondence analysis (MCA) on the eight indicators. This approach aims to construct a summary scale in which all dimensions contribute jointly to the measured experience of precariousness and its health impact.
Further, the relationship between EP and 'general self-perceived health' is estimated by applying ordered probit random-effects estimators and calculating average marginal effect (further AME). Then, to control for unobserved heterogeneity, I implement correlated random-effects models that add to the model the within-individual means of the time-varying independent variables. To test the significance of the gender differential, I add an interaction term between EP and gender in the fully adjusted model in the pooled sample.
My correlated random-effects models showed EP's negative and substantial 'effect' on self-perceived health for both men and women. Although nonsignificant, the evidence seems in line with previous cross-sectional literature. It supports the hypothesis that employment precariousness could be detrimental to workers' health. Further, my results showed the crucial role of unobserved heterogeneity in shaping the health consequences of precarious employment. This is particularly important as evidence accumulates, yet it is still mostly descriptive.
Moreover, my results revealed a substantial difference among men and women in the relationship between EP and health: when EP increases, the risk of experiencing poor health increases much more for men than for women. This evidence falsifies previous theory according to whom the gender differential is contingent on the structurally disadvantaged position of women in western societies. In contrast, they seem to confirm the idea that men in precarious work could experience role conflict to a larger extent than women, as their self-standard is supposed to be the stereotypical breadwinner worker with a good and well-rewarded job. Finally, results from the multiple correspondence analysis contribute to the methodological debate on precariousness, showing that a multidimensional and continuous indicator can express a latent variable of EP.
All in all, complementarities are revealed in the results of unemployment and employment precariousness, which have two implications: Policy-makers need to be aware that the total costs of unemployment and precariousness go far beyond the economic and material realm penetrating other fundamental life domains such as individual health. Moreover, they need to balance the trade-off between protecting adequately unemployed people and fostering high-quality employment in reaction to the highlighted market pressures. In this sense, the further development of a (universalistic) welfare state certainly helps mitigate the adverse health effects of unemployment and, therefore, the future costs of both individuals' health and welfare spending. In addition, the presence of a working partner is crucial for reducing the health consequences of employment instability. Therefore, policies aiming to increase female labor market participation should be promoted, especially in those contexts where the welfare state is less developed.
Moreover, my results support the significance of taking account of a gender perspective in health research. The findings of the three articles show that job loss, unemployment, and precarious employment, in general, have adverse effects on men's health but less or absent consequences for women's health. Indeed, this suggests the importance of labor and health policies that consider and further distinguish the specific needs of the male and female labor force in Europe. Nevertheless, a further implication emerges: the health consequences of employment instability and de-standardization need to be investigated in light of the gender arrangements and the transforming gender relationships in specific cultural and institutional contexts. My results indeed seem to suggest that women's health advantage may be a transitory phenomenon, contingent on the predominant gendered institutional and cultural context. As the structural difference between men's and women's position in society is eroded, egalitarianism becomes the dominant normative status, so will probably be the gender difference in the health consequences of job loss and precariousness. Therefore, while gender equality in opportunities and roles is a desirable aspect for contemporary societies and a political goal that cannot be postponed further, this thesis raises a further and maybe more crucial question: What kind of equality should be pursued to provide men and women with both good life quality and equal chances in the public and private spheres? In this sense, I believe that social and labor policies aiming to reduce gender inequality in society should focus on improving women's integration into the labor market, implementing policies targeting men, and facilitating their involvement in the private sphere of life. Equal redistribution of social roles could activate a crucial transformation of gender roles and the cultural models that sustain and still legitimate gender inequality in Western societies.
The large literature that aims to find evidence of climate migration delivers mixed findings. This meta-regression analysis i) summarizes direct links between adverse climatic events and migration, ii) maps patterns of climate migration, and iii) explains the variation in outcomes. Using a set of limited dependent variable models, we meta-analyze thus-far the most comprehensive sample of 3,625 estimates from 116 original studies and produce novel insights on climate migration. We find that extremely high temperatures and drying conditions increase migration. We do not find a significant effect of sudden-onset events. Climate migration is most likely to emerge due to contemporaneous events, to originate in rural areas and to take place in middle-income countries, internally, to cities. The likelihood to become trapped in affected areas is higher for women and in low-income countries, particularly in Africa. We uniquely quantify how pitfalls typical for the broader empirical climate impact literature affect climate migration findings. We also find evidence of different publication biases.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
Access to digital finance
(2024)
Financing entrepreneurship spurs innovation and economic growth. Digital financial platforms that crowdfund equity for entrepreneurs have emerged globally, yet they remain poorly understood. We model equity crowdfunding in terms of the relationship between the number of investors and the amount of money raised per pitch. We examine heterogeneity in the average amount raised per pitch that is associated with differences across three countries and seven platforms. Using a novel dataset of successful fundraising on the most prominent platforms in the UK, Germany, and the USA, we find the underlying relationship between the number of investors and the amount of money raised for entrepreneurs is loglinear, with a coefficient less than one and concave to the origin. We identify significant variation in the average amount invested in each pitch across countries and platforms. Our findings have implications for market actors as well as regulators who set competitive frameworks.
This Thesis puts its focus on the physics of neutron stars and its description with methods of numerical relativity. In the first step, a new numerical framework the Whisky2D code will be developed, which solves the relativistic equations of hydrodynamics in axisymmetry. Therefore we consider an improved formulation of the conserved form of these equations. The second part will use the new code to investigate the critical behaviour of two colliding neutron stars. Considering the analogy to phase transitions in statistical physics, we will investigate the evolution of the entropy of the neutron stars during the whole process. A better understanding of the evolution of thermodynamical quantities, like the entropy in critical process, should provide deeper understanding of thermodynamics in relativity. More specifically, we have written the Whisky2D code, which solves the general-relativistic hydrodynamics equations in a flux-conservative form and in cylindrical coordinates. This of course brings in 1/r singular terms, where r is the radial cylindrical coordinate, which must be dealt with appropriately. In the above-referenced works, the flux operator is expanded and the 1/r terms, not containing derivatives, are moved to the right-hand-side of the equation (the source term), so that the left hand side assumes a form identical to the one of the three-dimensional (3D) Cartesian formulation. We call this the standard formulation. Another possibility is not to split the flux operator and to redefine the conserved variables, via a multiplication by r. We call this the new formulation. The new equations are solved with the same methods as in the Cartesian case. From a mathematical point of view, one would not expect differences between the two ways of writing the differential operator, but, of course, a difference is present at the numerical level. Our tests show that the new formulation yields results with a global truncation error which is one or more orders of magnitude smaller than those of alternative and commonly used formulations. The second part of the Thesis uses the new code for investigations of critical phenomena in general relativity. In particular, we consider the head-on-collision of two neutron stars in a region of the parameter space where two final states a new stable neutron star or a black hole, lay close to each other. In 1993, Choptuik considered one-parameter families of solutions, S[P], of the Einstein-Klein-Gordon equations for a massless scalar field in spherical symmetry, such that for every P > P⋆, S[P] contains a black hole and for every P < P⋆, S[P] is a solution not containing singularities. He studied numerically the behavior of S[P] as P → P⋆ and found that the critical solution, S[P⋆], is universal, in the sense that it is approached by all nearly-critical solutions regardless of the particular family of initial data considered. All these phenomena have the common property that, as P approaches P⋆, S[P] approaches a universal solution S[P⋆] and that all the physical quantities of S[P] depend only on |P − P⋆|. The first study of critical phenomena concerning the head-on collision of NSs was carried out by Jin and Suen in 2007. In particular, they considered a series of families of equal-mass NSs, modeled with an ideal-gas EOS, boosted towards each other and varied the mass of the stars, their separation, velocity and the polytropic index in the EOS. In this way they could observe a critical phenomenon of type I near the threshold of black-hole formation, with the putative solution being a nonlinearly oscillating star. In a successive work, they performed similar simulations but considering the head-on collision of Gaussian distributions of matter. Also in this case they found the appearance of type-I critical behaviour, but also performed a perturbative analysis of the initial distributions of matter and of the merged object. Because of the considerable difference found in the eigenfrequencies in the two cases, they concluded that the critical solution does not represent a system near equilibrium and in particular not a perturbed Tolmann-Oppenheimer-Volkoff (TOV) solution. In this Thesis we study the dynamics of the head-on collision of two equal-mass NSs using a setup which is as similar as possible to the one considered above. While we confirm that the merged object exhibits a type-I critical behaviour, we also argue against the conclusion that the critical solution cannot be described in terms of equilibrium solution. Indeed, we show that, in analogy with what is found in, the critical solution is effectively a perturbed unstable solution of the TOV equations. Our analysis also considers fine-structure of the scaling relation of type-I critical phenomena and we show that it exhibits oscillations in a similar way to the one studied in the context of scalar-field critical collapse.
Acquiring Syntactic Variability: The Production of Wh-Questions in Children and Adults Speaking Akan
(2020)
This paper investigates the predictions of the Derivational Complexity Hypothesis by studying the acquisition of wh-questions in 4- and 5-year-old Akan-speaking children in an experimental approach using an elicited production and an elicited imitation task. Akan has two types of wh-question structures (wh-in-situ and wh-ex-situ questions), which allows an investigation of children’s acquisition of these two question structures and their preferences for one or the other. Our results show that adults prefer to use wh-ex-situ questions over wh-in-situ questions. The results from the children show that both age groups have the two question structures in their linguistic repertoire. However, they differ in their preferences in usage in the elicited production task: while the 5-year-olds preferred the wh-in-situ structure over the wh-ex-situ structure, the 4-year-olds showed a selective preference for the wh-in-situ structure in who-questions. These findings suggest a developmental change in wh-question preferences in Akan-learning children between 4 and 5 years of age with a so far unobserved u-shaped developmental pattern. In the elicited imitation task, all groups showed a strong tendency to maintain the structure of in-situ and ex-situ questions in repeating grammatical questions. When repairing ungrammatical ex-situ questions, structural changes to grammatical in-situ questions were hardly observed but the insertion of missing morphemes while keeping the ex-situ structure. Together, our findings provide only partial support for the Derivational Complexity Hypothesis.
Business process management experiences a large uptake by the industry, and process models play an important role in the analysis and improvement of processes. While an increasing number of staff becomes involved in actual modeling practice, it is crucial to assure model quality and homogeneity along with providing suitable aids for creating models. In this paper we consider the problem of offering recommendations to the user during the act of modeling. Our key contribution is a concept for defining and identifying so-called action patterns - chunks of actions often appearing together in business processes. In particular, we specify action patterns and demonstrate how they can be identified from existing process model repositories using association rule mining techniques. Action patterns can then be used to suggest additional actions for a process model. Our approach is challenged by applying it to the collection of process models from the SAP Reference Model.
Advancing charge selective contacts for efficient monolithic perovskite-silicon tandem solar cells
(2019)
Hybrid organic-inorganic perovskites are one of the most promising material classes for photovoltaic energy conversion. In solar cells, the perovskite absorber is sandwiched between n- and p-type contact layers which selectively transport electrons and holes to the cell’s cathode and anode, respectively. This thesis aims to advance contact layers in perovskite solar cells and unravel the impact of interface and contact properties on the device performance. Further, the contact materials are applied in monolithic perovskite-silicon heterojunction (SHJ) tandem solar cells, which can overcome the single junction efficiency limits and attract increasing attention. Therefore, all contact layers must be highly transparent to foster light harvesting in the tandem solar cell design. Besides, the SHJ device restricts processing temperatures for the selective contacts to below 200°C.
A comparative study of various electron selective contact materials, all processed below 180°C, in n-i-p type perovskite solar cells highlights that selective contacts and their interfaces to the absorber govern the overall device performance. Combining fullerenes and metal-oxides in a TiO2/PC60BM (phenyl-C60-butyric acid methyl ester) double-layer contact allows to merge good charge extraction with minimized interface recombination. The layer sequence thereby achieved high stabilized solar cell performances up to 18.0% and negligible current-voltage hysteresis, an otherwise pronounced phenomenon in this device design. Double-layer structures are therefore emphasized as a general concept to establish efficient and highly selective contacts.
Based on this success, the concept to combine desired properties of different materials is transferred to the p-type contact. Here, a mixture of the small molecule Spiro-OMeTAD [2,2’,7,7’-tetrakis(N,N-di-p-methoxyphenylamine)-9,9’-spirobifluoren] and the doped polymer PEDOT [poly(3,4-ethylenedioxythiophene)] is presented as a novel hole selective contact. PEDOT thereby remarkably suppresses charge recombination at the perovskite surface, allowing an increase of quasi-Fermi level splitting in the absorber. Further, the addition of Spiro-OMeTAD into the PEDOT layer is shown to enhance charge extraction at the interface and allow high efficiencies up to 16.8%.
Finally, the knowledge on contact properties is applied to monolithic perovskite-SHJ tandem solar cells. The main goal is to optimize the top contact stack of doped Spiro-OMeTAD/molybdenum oxide(MoOx)/ITO towards higher transparency by two different routes. First, fine-tuning of the ITO deposition to mitigate chemical reduction of MoOx and increase the transmittance of MoOx/ITO stacks by 25%. Second, replacing Spiro-OMeTAD with the alternative hole transport materials PEDOT/Spiro-OMeTAD mixtures, CuSCN or PTAA [poly(triaryl amine)]. Experimental results determine layer thickness constrains and validate optical simulations, which subsequently allow to realistically estimate the respective tandem device performances. As a result, PTAA represents the most promising replacement for Spiro-OMeTAD, with a projected increase of the optimum tandem device efficiency for the herein used architecture by 2.9% relative to 26.5% absolute. The results also reveal general guidelines for further performance gains of the technology.
We prove in this paper an existence result for infinite-dimensional stationary interactive Brownian diffusions. The interaction is supposed to be small in the norm ||.||∞ but otherwise is very general, being possibly non-regular and non-Markovian. Our method consists in using the characterization of such diffusions as space-time Gibbs fields so that we construct them by space-time cluster expansions in the small coupling parameter.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
Antarctic glacier forfields are extreme environments and pioneer sites for ecological succession. The Antarctic continent shows microbial community development as a natural laboratory because of its special environment, geographic isolation and little anthropogenic influence. Increasing temperatures due to global warming lead to enhanced deglaciation processes in cold-affected habitats and new terrain is becoming exposed to soil formation and accessible for microbial colonisation. This study aims to understand the structure and development of glacier forefield bacterial communities, especially how soil parameters impact the microorganisms and how those are adapted to the extreme conditions of the habitat. To this effect, a combination of cultivation experiments, molecular, geophysical and geochemical analysis was applied to examine two glacier forfields of the Larsemann Hills, East Antarctica. Culture-independent molecular tools such as terminal restriction length polymorphism (T-RFLP), clone libraries and quantitative real-time PCR (qPCR) were used to determine bacterial diversity and distribution. Cultivation of yet unknown species was carried out to get insights in the physiology and adaptation of the microorganisms. Adaptation strategies of the microorganisms were studied by determining changes of the cell membrane phospholipid fatty acid (PLFA) inventory of an isolated bacterium in response to temperature and pH fluctuations and by measuring enzyme activity at low temperature in environmental soil samples. The two studied glacier forefields are extreme habitats characterised by low temperatures, low water availability and small oligotrophic nutrient pools and represent sites of different bacterial succession in relation to soil parameters. The investigated sites showed microbial succession at an early step of soil formation near the ice tongue in comparison to closely located but rather older and more developed soil from the forefield. At the early step the succession is influenced by a deglaciation-dependent areal shift of soil parameters followed by a variable and prevalently depth-related distribution of the soil parameters that is driven by the extreme Antarctic conditions. The dominant taxa in the glacier forefields are Actinobacteria, Acidobacteria, Proteobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi. The connection of soil characteristics with bacterial community structure showed that soil parameter and soil formation along the glacier forefield influence the distribution of certain phyla. In the early step of succession the relative undifferentiated bacterial diversity reflects the undifferentiated soil development and has a high potential to shift according to past and present environmental conditions. With progressing development environmental constraints such as water or carbon limitation have a greater influence. Adapting the culturing conditions to the cold and oligotrophic environment, the number of culturable heterotrophic bacteria reached up to 108 colony forming units per gram soil and 148 isolates were obtained. Two new psychrotolerant bacteria, Herbaspirillum psychrotolerans PB1T and Chryseobacterium frigidisoli PB4T, were characterised in detail and described as novel species in the family of Oxalobacteraceae and Flavobacteriaceae, respectively. The isolates are able to grow at low temperatures tolerating temperature fluctuations and they are not specialised to a certain substrate, therefore they are well-adapted to the cold and oligotrophic environment. The adaptation strategies of the microorganisms were analysed in environmental samples and cultures focussing on extracellular enzyme activity at low temperature and PLFA analyses. Extracellular phosphatases (pH 11 and pH 6.5), β-glucosidase, invertase and urease activity were detected in the glacier forefield soils at low temperature (14°C) catalysing the conversion of various compounds providing necessary substrates and may further play a role in the soil formation and total carbon turnover of the habitat. The PLFA analysis of the newly isolated species C. frigidisoli showed that the cold-adapted strain develops different strategies to maintain the cell membrane function under changing environmental conditions by altering the PLFA inventory at different temperatures and pH values. A newly discovered fatty acid, which was not found in any other microorganism so far, significantly increased at decreasing temperature and low pH and thus plays an important role in the adaption of C. frigidisoli. This work gives insights into the diversity, distribution and adaptation mechanisms of microbial communities in oligotrophic cold-affected soils and shows that Antarctic glacier forefields are suitable model systems to study bacterial colonisation in connection to soil formation.
Microswimmers, i.e. swimmers of micron size experiencing low Reynolds numbers, have received a great deal of attention in the last years, since many applications are envisioned in medicine and bioremediation. A promising field is the one of magnetic swimmers, since magnetism is biocom-patible and could be used to direct or actuate the swimmers. This thesis studies two examples of magnetic microswimmers from a physics point of view.
The first system to be studied are magnetic cells, which can be magnetic biohybrids (a swimming cell coupled with a magnetic synthetic component) or magnetotactic bacteria (naturally occurring bacteria that produce an intracellular chain of magnetic crystals). A magnetic cell can passively interact with external magnetic fields, which can be used for direction. The aim of the thesis is to understand how magnetic cells couple this magnetic interaction to their swimming strategies, mainly how they combine it with chemotaxis (the ability to sense external gradient of chemical species and to bias their walk on these gradients). In particular, one open question addresses the advantage given by these magnetic interactions for the magnetotactic bacteria in a natural environment, such as porous sediments. In the thesis, a modified Active Brownian Particle model is used to perform simulations and to reproduce experimental data for different systems such as bacteria swimming in the bulk, in a capillary or in confined geometries. I will show that magnetic fields speed up chemotaxis under special conditions, depending on parameters such as their swimming strategy (run-and-tumble or run-and-reverse), aerotactic strategy (axial or polar), and magnetic fields (intensities and orientations), but it can also hinder bacterial chemotaxis depending on the system.
The second example of magnetic microswimmer are rigid magnetic propellers such as helices or random-shaped propellers. These propellers are actuated and directed by an external rotating magnetic field. One open question is how shape and magnetic properties influence the propeller behavior; the goal of this research field is to design the best propeller for a given situation. The aim of the thesis is to propose a simulation method to reproduce the behavior of experimentally-realized propellers and to determine their magnetic properties. The hydrodynamic simulations are based on the use of the mobility matrix. As main result, I propose a method to match the experimental data, while showing that not only shape but also the magnetic properties influence the propellers swimming characteristics.
In biological cells, the long-range intracellular traffic is powered by molecular motors which transport various cargos along microtubule filaments. The microtubules possess an intrinsic direction, having a 'plus' and a 'minus' end. Some molecular motors such as cytoplasmic dynein walk to the minus end, while others such as conventional kinesin walk to the plus end. Cells typically have an isopolar microtubule network. This is most pronounced in neuronal axons or fungal hyphae. In these long and thin tubular protrusions, the microtubules are arranged parallel to the tube axis with the minus ends pointing to the cell body and the plus ends pointing to the tip. In such a tubular compartment, transport by only one motor type leads to 'motor traffic jams'. Kinesin-driven cargos accumulate at the tip, while dynein-driven cargos accumulate near the cell body. We identify the relevant length scales and characterize the jamming behaviour in these tube geometries by using both Monte Carlo simulations and analytical calculations. A possible solution to this jamming problem is to transport cargos with a team of plus and a team of minus motors simultaneously, so that they can travel bidirectionally, as observed in cells. The presumably simplest mechanism for such bidirectional transport is provided by a 'tug-of-war' between the two motor teams which is governed by mechanical motor interactions only. We develop a stochastic tug-of-war model and study it with numerical and analytical calculations. We find a surprisingly complex cooperative motility behaviour. We compare our results to the available experimental data, which we reproduce qualitatively and quantitatively.
A numerical bifurcation analysis of the electrically driven plane sheet pinch is presented. The electrical conductivity varies across the sheet such as to allow instability of the quiescent basic state at some critical Hartmann number. The most unstable perturbation is the two-dimensional tearing mode. Restricting the whole problem to two spatial dimensions, this mode is followed up to a time-asymptotic steady state, which proves to be sensitive to three-dimensional perturbations even close to the point where the primary instability sets in. A comprehensive three-dimensional stability analysis of the two-dimensional steady tearing-mode state is performed by varying parameters of the sheet pinch. The instability with respect to three-dimensional perturbations is suppressed by a sufficiently strong magnetic field in the invariant direction of the equilibrium. For a special choice of the system parameters, the unstably perturbed state is followed up in its nonlinear evolution and is found to approach a three-dimensional steady state.
Business process management aims at capturing, understanding, and improving work in organizations. The central artifacts are process models, which serve different purposes. Detailed process models are used to analyze concrete working procedures, while high-level models show, for instance, handovers between departments. To provide different views on process models, business process model abstraction has emerged. While several approaches have been proposed, a number of abstraction use case that are both relevant for industry and scientifically challenging are yet to be addressed. In this paper we systematically develop, classify, and consolidate different use cases for business process model abstraction. The reported work is based on a study with BPM users in the health insurance sector and validated with a BPM consultancy company and a large BPM vendor. The identified fifteen abstraction use cases reflect the industry demand. The related work on business process model abstraction is evaluated against the use cases, which leads to a research agenda.
Basaltic fissure eruptions, such as on Hawai'i or on Iceland, are thought to be driven by the lateral propagation of feeder dikes and graben subsidence. Associated solid earth processes, such as deformation and structural development, are well studied by means of geophysical and geodetic technologies. The eruptions themselves, lava fountaining and venting dynamics, in turn, have been much less investigated due to hazardous access, local dimension, fast processes, and resulting poor data availability.
This thesis provides a detailed quantitative understanding of the shape and dynamics of lava fountains and the morphological changes at their respective eruption sites. For this purpose, I apply image processing techniques, including drones and fixed installed cameras, to the sequence of frames of video records from two well-known fissure eruptions in Hawai'i and Iceland. This way I extract the dimensions of multiple lava fountains, visible in all frames. By putting these results together and considering the acquisition times of the frames I quantify the variations in height, width and eruption velocity of the lava fountains. Then I analyse these time-series in both time and frequency domains and investigate the similarities and correlations between adjacent lava fountains. Following this procedure, I am able to link the dynamics of the individual lava fountains to physical parameters of the magma transport in the feeder dyke of the fountains.
The first case study in this thesis focuses on the March 2011 Pu'u'O'o eruption, Hawai'i, where a continuous pulsating behaviour at all eight lava fountains has been observed. The lava fountains, even those from different parts of the fissure that are closely connected, show a similar frequency content and eruption behaviour. The regular pattern in the heights of lava fountain suggests a controlling process within the magma feeder system like a hydraulic connection in the underlying dyke, affecting or even controlling the pulsating behaviour.
The second case study addresses the 2014-2015 Holuhraun fissure eruption, Iceland. In this case, the feeder dyke is highlighted by the surface expressions of graben-like structures and fault systems. At the eruption site, the activity decreases from a continuous line of fire of ~60 vents to a limited number of lava fountains. This can be explained by preferred upwards magma movements through vertical structures of the pre-eruptive morphology. Seismic tremors during the eruption reveal vent opening at the surface and/or pressure changes in the feeder dyke. The evolving topography of the cinder cones during the eruption interacts with the lava fountain behaviour. Local variations in the lava fountain height and width are controlled by the conduit diameter, the depth of the lava pond and the shape of the crater. Modelling of the fountain heights shows that long-term eruption behaviour is controlled mainly by pressure changes in the feeder dyke.
This research consists of six chapters with four papers, including two first author and two co-author papers. It establishes a new method to analyse lava fountain dynamics by video monitoring. The comparison with the seismicity, geomorphologic and structural expressions of fissure eruptions shows a complex relationship between focussed flow through dykes, the morphology of the cinder cones, and the lava fountain dynamics at the vents of a fissure eruption.
Solar photocatalysis is the one of leading concepts of research in the current paradigm of sustainable chemical industry. For actual practical implementation of sunlight-driven catalytic processes in organic synthesis, a cheap, efficient, versatile and robust heterogeneous catalyst is necessary. Carbon nitrides are a class of organic semiconductors who are known to fulfill these requirements.
First, current state of solar photocatalysis in economy, industry and lab research is overviewed, outlining EU project funding, prospective synthetic and reforming bulk processes, small scale solar organic chemistry, and existing reactor designs and prototypes, concluding feasibility of the approach.
Then, the photocatalytic aerobic cleavage of oximes to corresponding aldehydes and ketones by anionic poly(heptazine imide) carbon nitride is discussed. The reaction provides a feasible method of deprotection and formation of carbonyl compounds from nitrosation products and serves as a convenient model to study chromoselectivity and photophysics of energy transfer in heterogeneous photocatalysis.
Afterwards, the ability of mesoporous graphitic carbon nitride to conduct proton-coupled electron transfer was utilized for the direct oxygenation of 1,3-oxazolidin-2-ones to corresponding 1,3-oxazlidine-2,4-diones. This reaction provides an easier access to a key scaffold of diverse types of drugs and agrochemicals.
Finally, a series of novel carbon nitrides based on poly(triazine imide) and poly(heptazine imide) structure was synthesized from cyanamide and potassium rhodizonate. These catalysts demonstrated a good performance in a set of photocatalytic benchmark reactions, including aerobic oxidation, dual nickel photoredox catalysis, hydrogen peroxide evolution and chromoselective transformation of organosulfur precursors.
Concluding, the scope of carbon nitride utilization for net-oxidative and net-neutral photocatalytic processes was expanded, and a new tunable platform for catalyst synthesis was discovered.
Recent years witnessed a vast advent of stalagmites as palaeoclimate archives. The multitude of geochemical and physical proxies and a promise of a precise and accurate age model greatly appeal to palaeoclimatologists. Although substantial progress was made in speleothem-based palaeoclimate research and despite high-resolution records from low-latitudinal regions, proving that palaeo-environmental changes can be archived on sub-annual to millennial time scales our comprehension of climate dynamics is still fragmentary. This is in particular true for the summer monsoon system on the Indian subcontinent. The Indian summer monsoon (ISM) is an integral part of the intertropical convergence zone (ITCZ). As this rainfall belt migrates northward during boreal summer, it brings monsoonal rainfall. ISM strength depends however on a variety of factors, including snow cover in Central Asia and oceanic conditions in the Indic and Pacific. Presently, many of the factors influencing the ISM are known, though their exact forcing mechanism and mutual relations remain ambiguous. Attempts to make an accurate prediction of rainfall intensity and frequency and drought recurrence, which is extremely important for South Asian countries, resemble a puzzle game; all interaction need to fall into the right place to obtain a complete picture. My thesis aims to create a faithful picture of climate change in India, covering the last 11,000 ka. NE India represents a key region for the Bay of Bengal (BoB) branch of the ISM, as it is here where the monsoon splits into a northwestward and a northeastward directed arm. The Meghalaya Plateau is the first barrier for northward moving air masses and receives excessive summer rainfall, while the winter season is very dry. The proximity of Meghalaya to the Tibetan Plateau on the one hand and the BoB on the other hand make the study area a key location for investigating the interaction between different forcings that governs the ISM. A basis for the interpretation of palaeoclimate records, and a first important outcome of my thesis is a conceptual model which explains the observed pattern of seasonal changes in stable isotopes (d18O and d2H) in rainfall. I show that although in tropical and subtropical regions the amount effect is commonly called to explain strongly depleted isotope values during enhanced rainfall, alone it cannot account for observed rainwater isotope variability in Meghalaya. Monitoring of rainwater isotopes shows no expected negative correlation between precipitation amount and d18O of rainfall. In turn I find evidence that the runoff from high elevations carries an inherited isotopic signature into the BoB, where during the ISM season the freshwater builds a strongly depleted plume on top of the marine water. The vapor originating from this plume is likely to memorize' and transmit further very negative d18O values. The lack of data does not allow for quantication of this plume effect' on isotopes in rainfall over Meghalaya but I suggest that it varies on seasonal to millennial timescales, depending on the runoff amount and source characteristics. The focal point of my thesis is the extraction of climatic signals archived in stalagmites from NE India. High uranium concentration in the stalagmites ensured excellent age control required for successful high-resolution climate reconstructions. Stable isotope (d18O and d13C) and grey-scale data allow unprecedented insights into millennial to seasonal dynamics of the summer and winter monsoon in NE India. ISM strength (i. e. rainfall amount) is recorded in changes in d18Ostalagmites. The d13C signal, reflecting drip rate changes, renders a powerful proxy for dry season conditions, and shows similarities to temperature-related changes on the Tibetan Plateau. A sub-annual grey-scale profile supports a concept of lower drip rate and slower stalagmite growth during dry conditions. During the Holocene, ISM followed a millennial-scale decrease of insolation, with decadal to centennial failures resulting from atmospheric changes. The period of maximum rainfall and enhanced seasonality corresponds to the Holocene Thermal Optimum observed in Europe. After a phase of rather stable conditions, 4.5 kyr ago, the strengthening ENSO system dominated the ISM. Strong El Nino events weakened the ISM, especially when in concert with positive Indian Ocean dipole events. The strongest droughts of the last 11 kyr are recorded during the past 2 kyr. Using the advantage of a well-dated stalagmite record at hand I tested the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to detect sub-annual to sub-decadal changes in element concentrations in stalagmites. The development of a large ablation cell allows for ablating sample slabs of up to 22 cm total length. Each analyzed element is a potential proxy for different climatic parameters. Combining my previous results with the LAICP- MS-generated data shows that element concentration depends not only on rainfall amount and associated leaching from the soil. Additional factors, like biological activity and hydrogeochemical conditions in the soil and vadose zone can eventually affect the element content in drip water and in stalagmites. I present a theoretical conceptual model for my study site to explain how climatic signals can be transmitted and archived in stalagmite carbonate. Further, I establish a first 1500 year long element record, reconstructing rainfall variability. Additionally, I hypothesize that volcanic eruptions, producing large amounts of sulfuric acid, can influence soil acidity and hence element mobilization.
In this work, binding interactions between biomolecules were analyzed by a technique that is based on electrically controllable DNA nanolevers. The technique was applied to virus-receptor interactions for the first time. As receptors, primarily peptides on DNA nanostructures and antibodies were utilized. The DNA nanostructures were integrated into the measurement technique and enabled the presentation of the peptides in a controllable geometrical order. The number of peptides could be varied to be compatible to the binding sites of the viral surface proteins.
Influenza A virus served as a model system, on which the general measurability was demonstrated. Variations of the receptor peptide, the surface ligand density, the measurement temperature and the virus subtypes showed the sensitivity and applicability of the technology. Additionally, the immobilization of virus particles enabled the measurement of differences in oligovalent binding of DNA-peptide nanostructures to the viral proteins in their native environment.
When the coronavirus pandemic broke out in 2020, work on binding interactions of a peptide from the hACE2 receptor and the spike protein of the SARS-CoV-2 virus revealed that oligovalent binding can be quantified in the switchSENSE technology. It could also be shown that small changes in the amino acid sequence of the spike protein resulted in complete loss of binding. Interactions of the peptide and inactivated virus material as well as pseudo virus particles could be measured. Additionally, the switchSENSE technology was utilized to rank six antibodies for their binding affinity towards the nucleocapsid protein of SARS-CoV-2 for the development of a rapid antigen test device.
The technique was furthermore employed to show binding of a non-enveloped virus (adenovirus) and a virus-like particle (norovirus-like particle) to antibodies. Apart from binding interactions, the use of DNA origami levers with a length of around 50 nm enabled the switching of virus material. This proved that the technology is also able to size objects with a hydrodynamic diameter larger than 14 nm.
A theoretical work on diffusion and reaction-limited binding interactions revealed that the technique and the chosen parameters enable the determination of binding rate constants in the reaction-limited regime.
Overall, the applicability of the switchSENSE technique to virus-receptor binding interactions could be demonstrated on multiple examples. While there are challenges that remain, the setup enables the determination of affinities between viruses and receptors in their native environment. Especially the possibilities regarding the quantification of oligo- and multivalent binding interactions could be presented.
The Milky Way is only one out of billions of galaxies in the universe. However, it is a special galaxy because it allows to explore the main mechanisms involved in its evolution and formation history by unpicking the system star-by-star. Especially, the chemical fingerprints of its stars provide clues and evidence of past events in the Galaxy’s lifetime. These information help not only to decipher the current structure and building blocks of the Milky Way, but to learn more about the general formation process of galaxies.
In the past decade a multitude of stellar spectroscopic Galactic surveys have scanned millions of stars far beyond the rim of the solar neighbourhood. The obtained spectroscopic information provide unprecedented insights to the chemo-dynamics of the Milky Way. In addition analytic models and numerical simulations of the Milky Way provide necessary descriptions and predictions suited for comparison with observations in order to decode the physical properties that underlie the complex system of the Galaxy.
In the thesis various approaches are taken to connect modern theoretical modelling of galaxy formation and evolution with observations from Galactic stellar surveys. With its focus on the chemo-kinematics of the Galactic disk this work aims to determine new observational constraints on the formation of the Milky Way providing also proper comparisons with two different models. These are the population synthesis model TRILEGAL based on analytical distribution functions, which aims to simulate the number and distribution of stars in the Milky Way and its different components, and a hybrid model (MCM) that combines an N-body simulation of a Milky Way like galaxy in the cosmological framework with a semi-analytic chemical evolution model for the Milky Way. The major observational data sets in use come from two surveys, namely the “Radial Velocity Experiment” (RAVE) and the “Sloan Extension for Galactic Understanding and Exploration” (SEGUE).
In the first approach the chemo-kinematic properties of the thin and thick disk of the Galaxy as traced by a selection of about 20000 SEGUE G-dwarf stars are directly compared to the predictions by the MCM model. As a necessary condition for this, SEGUE's selection function and its survey volume are evaluated in detail to correct the spectroscopic observations for their survey specific selection biases. Also, based on a Bayesian method spectro-photometric distances with uncertainties below 15% are computed for the selection of SEGUE G-dwarfs that are studied up to a distance of 3 kpc from the Sun.
For the second approach two synthetic versions of the SEGUE survey are generated based on the above models. The obtained synthetic stellar catalogues are then used to create mock samples best resembling the compiled sample of observed SEGUE G-dwarfs. Generally, mock samples are not only ideal to compare predictions from various models. They also allow validation of the models' quality and improvement as with this work could be especially achieved for TRILEGAL. While TRILEGAL reproduces the statistical properties of the thin and thick disk as seen in the observations, the MCM model has shown to be more suitable in reproducing many chemo-kinematic correlations as revealed by the SEGUE stars. However, evidence has been found that the MCM model may be missing a stellar component with the properties of the thick disk that the observations clearly show. While the SEGUE stars do indicate a thin-thick dichotomy of the stellar Galactic disk in agreement with other spectroscopic stellar studies, no sign for a distinct metal-poor disk is seen in the MCM model.
Usually stellar spectroscopic surveys are limited to a certain volume around the Sun covering different regions of the Galaxy’s disk. This often prevents to obtain a global view on the chemo-dynamics of the Galactic disk. Hence, a suitable combination of stellar samples from independent surveys is not only useful for the verification of results but it also helps to complete the picture of the Milky Way. Therefore, the thesis closes with a comparison of the SEGUE G-dwarfs and a sample of RAVE giants. The comparison reveals that the chemo-kinematic relations agree in disk regions where the samples of both surveys show a similar number of stars. For those parts of the survey volumes where one of the surveys lacks statistics they beautifully complement each other. This demonstrates that the comparison of theoretical models on the one side, and the combined observational data gathered by multiple surveys on the other side, are key ingredients to understand and disentangle the structure and formation history of the Milky Way.
In the living cell, the organization of the complex internal structure relies to a large extent on molecular motors. Molecular motors are proteins that are able to convert chemical energy from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Being about 10 to 100 nanometers in size, the molecules act on a length scale, for which thermal collisions have a considerable impact onto their motion. In this way, they constitute paradigmatic examples of thermodynamic machines out of equilibrium. This study develops a theoretical description for the energy conversion by the molecular motor myosin V, using many different aspects of theoretical physics. Myosin V has been studied extensively in both bulk and single molecule experiments. Its stepping velocity has been characterized as a function of external control parameters such as nucleotide concentration and applied forces. In addition, numerous kinetic rates involved in the enzymatic reaction of the molecule have been determined. For forces that exceed the stall force of the motor, myosin V exhibits a 'ratcheting' behaviour: For loads in the direction of forward stepping, the velocity depends on the concentration of ATP, while for backward loads there is no such influence. Based on the chemical states of the motor, we construct a general network theory that incorporates experimental observations about the stepping behaviour of myosin V. The motor's motion is captured through the network description supplemented by a Markov process to describe the motor dynamics. This approach has the advantage of directly addressing the chemical kinetics of the molecule, and treating the mechanical and chemical processes on equal grounds. We utilize constraints arising from nonequilibrium thermodynamics to determine motor parameters and demonstrate that the motor behaviour is governed by several chemomechanical motor cycles. In addition, we investigate the functional dependence of stepping rates on force by deducing the motor's response to external loads via an appropriate Fokker-Planck equation. For substall forces, the dominant pathway of the motor network is profoundly different from the one for superstall forces, which leads to a stepping behaviour that is in agreement with the experimental observations. The extension of our analysis to Markov processes with absorbing boundaries allows for the calculation of the motor's dwell time distributions. These reveal aspects of the coordination of the motor's heads and contain direct information about the backsteps of the motor. Our theory provides a unified description for the myosin V motor as studied in single motor experiments.
Chloroplasts as bioreactors : high-yield production of active bacteriolytic protein antibiotics
(2008)
Plants, more precisely their chloroplasts with their bacterial-like expression machinery inherited from their cyanobacterial ancestors, can potentially offer a cheap expression system for proteinaceous pharmaceuticals. This system would be easily scalable and provides appropriate safety due to chloroplasts maternal inheritance. In this work, it was shown that three phage lytic enzymes (Pal, Cpl-1 and PlyGBS) could be successfully expressed at very high levels and with high stability in tobacco chloroplasts. PlyGBS expression reached an amount of foreign protein accumulation (> 70% TSP) that has never been obtained before. Although the high expression levels of PlyGBS caused a pale green phenotype with retarded growth, presumably due to exhaustion of plastid protein synthesis capacity, development and seed production were not impaired under greenhouse conditions. Since Pal and Cpl-1 showed toxic effects when expressed in E. coli, a special plastid transformation vector (pTox) was constructed to allow DNA amplification in bacteria. The construction of the pTox transformation vector allowing a recombinase-mediated deletion of an E. coli transcription block in the chloroplast, leading to an increase of foreign protein accumulation to up to 40% of TSP for Pal and 20% of TSP for Cpl-1. High dose-dependent bactericidal efficiency was shown for all three plant-derived lytic enzymes using their pathogenic target bacteria S. pyogenes and S. pneumoniae. Confirmation of specificity was obtained for the endotoxic proteins Pal and Cpl-1 by application to E. coli cultures. These results establish tobacco chloroplasts as a new cost-efficient and convenient production platform for phage lytic enzymes and address the greatest obstacle for clinical application. The present study is the first report of lysin production in a non-bacterial system. The properties of chloroplast-produced lysins described in this work, their stability, high accumulation rate and biological activity make them highly attractive candidates for future antibiotics.
Die Anpassung von Sektoren an veränderte klimatische Bedingungen erfordert ein Verständnis von regionalen Vulnerabilitäten. Vulnerabilität ist als Funktion von Sensitivität und Exposition, welche potentielle Auswirkungen des Klimawandels darstellen, und der Anpassungsfähigkeit von Systemen definiert. Vulnerabilitätsstudien, die diese Komponenten quantifizieren, sind zu einem wichtigen Werkzeug in der Klimawissenschaft geworden. Allerdings besteht von der wissenschaftlichen Perspektive aus gesehen Uneinigkeit darüber, wie diese Definition in Studien umgesetzt werden soll. Ausdiesem Konflikt ergeben sich viele Herausforderungen, vor allem bezüglich der Quantifizierung und Aggregierung der einzelnen Komponenten und deren angemessenen Komplexitätsniveaus. Die vorliegende Dissertation hat daher zum Ziel die Anwendbarkeit des Vulnerabilitätskonzepts voranzubringen, indem es in eine systematische Struktur übersetzt wird. Dies beinhaltet alle Komponenten und schlägt für jede Klimaauswirkung (z.B. Sturzfluten) eine Beschreibung des vulnerablen Systems vor (z.B. Siedlungen), welches direkt mit einer bestimmten Richtung eines relevanten klimatischen Stimulus in Verbindung gebracht wird (z.B. stärkere Auswirkungen bei Zunahme der Starkregentage). Bezüglich der herausfordernden Prozedur der Aggregierung werden zwei alternative Methoden, die einen sektorübergreifenden Überblick ermöglichen, vorgestellt und deren Vor- und Nachteile diskutiert. Anschließend wird die entwickelte Struktur einer Vulnerabilitätsstudie mittels eines indikatorbasierten und deduktiven Ansatzes beispielhaft für Gemeinden in Nordrhein-Westfalen in Deutschland angewandt. Eine Übertragbarkeit auf andere Regionen ist dennoch möglich. Die Quantifizierung für die Gemeinden stützt sich dabei auf Informationen aus der Literatur. Da für viele Sektoren keine geeigneten Indikatoren vorhanden waren, werden in dieser Arbeit neue Indikatoren entwickelt und angewandt, beispielsweise für den Forst- oder Gesundheitssektor. Allerdings stellen fehlende empirische Daten bezüglich relevanter Schwellenwerte eine Lücke dar, beispielsweise welche Stärke von Klimaänderungen eine signifikante Auswirkung hervorruft. Dies führt dazu, dass die Studie nur relative Aussagen zum Grad der Vulnerabilität jeder Gemeinde im Vergleich zum Rest des Bundeslandes machen kann. Um diese Lücke zu füllen, wird für den Forstsektor beispielhaft die heutige und zukünftige Sturmwurfgefahr von Wäldern berechnet. Zu diesem Zweck werden die Eigenschaften der Wälder mit empirischen Schadensdaten eines vergangenen Sturmereignisses in Verbindung gebracht. Der sich daraus ergebende Sensitivitätswert wird anschließend mit den Windverhältnissen verknüpft. Sektorübergreifende Vulnerabilitätsstudien erfordern beträchtliche Ressourcen, was oft deren Anwendbarkeit erschwert. In einem nächsten Schritt wird daher das Potential einer Vereinfachung der Komplexität anhand zweier sektoraler Beispiele untersucht. Um das Auftreten von Waldbränden vorherzusagen, stehen zahlreiche meteorologische Indices zur Verfügung, welche eine Spannbreite unterschiedlicher Komplexitäten aufweisen. Bezüglich der Anzahl monatlicher Waldbrände weist die relative Luftfeuchtigkeit für die meisten deutschen Bundesländer eine bessere Vorhersagekraft als komplexere Indices auf. Dies ist er Fall, obgleich sie selbst als Eingangsvariable für die komplexeren Indices verwendet wird. Mit Hilfe dieses einzelnen meteorologischen Faktors kann also die Waldbrandgefahr in deutschen Region ausreichend genau ausgedrückt werden, was die Ressourceneffizienz von Studien erhöht. Die Methodenkomplexität wird auf ähnliche Weise hinsichtlich der Anwendung des ökohydrologischen Modells SWIM für die Region Brandenburg untersucht. Die interannuellen Bodenwasserwerte, welche durch dieses Modell simuliert werden, können nur unzureichend durch ein einfacheres statistisches Modell, welches auf denselben Eingangsdaten aufbaut, abgebildet werden. Innerhalb eines Zeithorizonts von Jahrzehnten, kann der statistische Ansatz jedoch das Bodenwasser zufriedenstellend abbilden und zeigt eine Dominanz der Bodeneigenschaft Feldkapazität. Dies deutet darauf hin, dass die Komplexität im Hinblick auf die Anzahl der Eingangsvariablen für langfristige Berechnungen reduziert werden kann. Allerdings sind die Aussagen durch fehlende beobachtete Bodenwasserwerte zur Validierung beschränkt. Die vorliegenden Studien zur Vulnerabilität und ihren Komponenten haben gezeigt, dass eine Anwendung noch immer wissenschaftlich herausfordernd ist. Folgt man der hier verwendeten Vulnerabilitätsdefinition, treten zahlreiche Probleme bei der Implementierung in regionalen Studien auf. Mit dieser Dissertation wurden Fortschritte bezüglich der aufgezeigten Lücken bisheriger Studien erzielt, indem eine systematische Struktur für die Beschreibung und Aggregierung von Vulnerabilitätskomponenten erarbeitet wurde. Hierfür wurden mehrere Ansätze diskutiert, die jedoch Vor- und Nachteile besitzen. Diese sollten vor der Anwendung von zukünftigen Studien daher ebenfalls sorgfältig abgewogen werden. Darüber hinaus hat sich gezeigt, dass ein Potential besteht einige Ansätze zu vereinfachen, jedoch sind hierfür weitere Untersuchungen nötig. Insgesamt konnte die Dissertation die Anwendung von Vulnerabilitätsstudien als Werkzeug zur Unterstützung von Anpassungsmaßnahmen stärken.
Being living systems unable to adjust their location to changing environmental conditions, plants display homeostatic networks that have evolved to maintain transition metal levels in a very narrow concentration range in order to avoid either deficiency or toxicity. Hence, plants possess a broad repertoire of mechanisms for the cellular uptake, compartmentation and efflux, as well as for the chelation of transition metal ions. A small number of plants are hypertolerant to one or a few specific transition metals. Some metal tolerant plants are also able to hyperaccumulate metal ions. The Brassicaceae family member Arabidopis halleri ssp. halleri (L.) O´KANE and AL´SHEHBAZ is a hyperaccumulator of zinc (Zn), and it is closely related to the non-hypertolerant and non-hyperaccumulating model plant Arabidopsis thaliana (L.) HEYNHOLD. The close relationship renders A. halleri a promising emerging model plant for the comparative investigation of the molecular mechanisms behind hypertolerance and hyperaccumulation. Among several potential candidate genes that are probably involved in mediating the zinc-hypertolerant and zinc-hyperaccumulating trait is AhHMA3. The AhHMA3 gene is highly similar to AtHMA3 (AGI number: At4g30120) in A. thaliana, and its encoded protein belongs to the P-type IB ATPase family of integral membrane transporter proteins that transport transition metals. In contrast to the low AtHMA3 transcript levels in A. thaliana, the gene was found to be constitutively highly expressed across different Zn treatments in A. halleri, especially in shoots. In this study, the cloning and characterisation of the HMA3 gene and its promoter from Arabidopsis halleri (L.) O´KANE and AL´SHEHBAZ and Arabidopsis thaliana (L.) HEYNHOLD is described. Heterologously expressed AhHMA3 mediated enhanced tolerance to Zn and to a much lesser degree to cadmium (Cd) but not to cobalt (Co) in metal-sensitive mutant strains of budding yeast. It is demonstrated that the genome of A. halleri contains at least four copies of AhHMA3, AhHMA3-1 to AhHMA3-4. A copy-specific real-time RT-PCR indicated that an AhHMA3-1 related gene copy is the source of the constitutively high transcript level in A. halleri and not a gene copy similar to AhHMA3-2 or AhHMA3-4. In accordance with the enhanced AtHMA3mRNA transcript level in A. thaliana roots, an AtHMA3 promoter-GUS gene construct mediated GUS activity predominantly in the vascular tissues of roots and not in shoots. However, the observed AhHMA3-1 and AhHMA3-2 promoter-mediated GUS activity in A. thaliana or A. halleri plants did not reflect the constitutively high expression of AhHMA3 in shoots of A. halleri. It is suggested that other factors e. g. characteristic sequence inserts within the first intron of AhHMA3-1 might enable a constitutively high expression. Moreover, the unknown promoter of the AhHMA3-3 gene copy could be the source of the constitutively high AhHMA3 transcript levels in A. halleri. In that case, the AhHMA3-3 sequence is predicted to be highly homologous to AhHMA3-1. The lack of solid localisation data for the AhHMA3 protein prevents a clear functional assignment. The provided data suggest several possible functions of the AhHMA3 protein: Like AtHMA2 and AtHMA4 it might be localised to the plasma membrane and could contribute to the efficient translocation of Zn from root to shoot and/or to the cell-to-cell distribution of Zn in the shoot. If localised to the vacuolar membrane, then a role in maintaining a low cytoplasmic zinc concentration by vacuolar zinc sequestration is possible. In addition, AhHMA3 might be involved in the delivery of zinc ions to trichomes and mesophyll leaf cells that are major zinc storage sites in A. halleri.
Stellar winds play an important role for the evolution of massive stars and their cosmic environment. Multiple lines of evidence, coming from spectroscopy, polarimetry, variability, stellar ejecta, and hydrodynamic modeling, suggest that stellar winds are non-stationary and inhomogeneous. This is referred to as 'wind clumping'. The urgent need to understand this phenomenon is boosted by its far-reaching implications. Most importantly, all techniques to derive empirical mass-loss rates are more or less corrupted by wind clumping. Consequently, mass-loss rates are extremely uncertain. Within their range of uncertainty, completely different scenarios for the evolution of massive stars are obtained. Settling these questions for Galactic OB, LBV and Wolf-Rayet stars is prerequisite to understanding stellar clusters and galaxies, or predicting the properties of first-generation stars. In order to develop a consistent picture and understanding of clumped stellar winds, an international workshop on 'Clumping in Hot Star Winds' was held in Potsdam, Germany, from 18. - 22. June 2007. About 60 participants, comprising almost all leading experts in the field, gathered for one week of extensive exchange and discussion. The Scientific Organizing Committee (SOC) included John Brown (Glasgow), Joseph Cassinelli (Madison), Paul Crowther (Sheffield), Alex Fullerton (Baltimore), Wolf-Rainer Hamann (Potsdam, chair), Anthony Moffat (Montreal), Stan Owocki (Newark), and Joachim Puls (Munich). These proceedings contain the invited and contributed talks presented at the workshop, and document the extensive discussions.
The natural abundance of Coiled Coil (CC) motifs in cytoskeleton and extracellular matrix proteins suggests that CCs play an important role as passive (structural) and active (regulatory) mechanical building blocks. CCs are self-assembled superhelical structures consisting of 2-7 α-helices. Self-assembly is driven by hydrophobic and ionic interactions, while the helix propensity of the individual helices contributes additional stability to the structure. As a direct result of this simple sequence-structure relationship, CCs serve as templates for protein design and sequences with a pre-defined thermodynamic stability have been synthesized de novo. Despite this quickly increasing knowledge and the vast number of possible CC applications, the mechanical function of CCs has been largely overlooked and little is known about how different CC design parameters determine the mechanical stability of CCs. Once available, this knowledge will open up new applications for CCs as nanomechanical building blocks, e.g. in biomaterials and nanobiotechnology.
With the goal of shedding light on the sequence-structure-mechanics relationship of CCs, a well-characterized heterodimeric CC was utilized as a model system. The sequence of this model system was systematically modified to investigate how different design parameters affect the CC response when the force is applied to opposing termini in a shear geometry or separated in a zipper-like fashion from the same termini (unzip geometry). The force was applied using an atomic force microscope set-up and dynamic single-molecule force spectroscopy was performed to determine the rupture forces and energy landscape properties of the CC heterodimers under study. Using force as a denaturant, CC chain separation is initiated by helix uncoiling from the force application points. In the shear geometry, this allows uncoiling-assisted sliding parallel to the force vector or dissociation perpendicular to the force vector. Both competing processes involve the opening of stabilizing hydrophobic (and ionic) interactions. Also in the unzip geometry, helix uncoiling precedes the rupture of hydrophobic contacts.
In a first series of experiments, the focus was placed on canonical modifications in the hydrophobic core and the helix propensity. Using the shear geometry, it was shown that both a reduced core packing and helix propensity lower the thermodynamic and mechanical stability of the CC; however, with different effects on the energy landscape of the system. A less tightly packed hydrophobic core increases the distance to the transition state, with only a small effect on the barrier height. This originates from a more dynamic and less tightly packed core, which provides more degrees of freedom to respond to the applied force in the direction of the force vector. In contrast, a reduced helix propensity decreases both the distance to the transition state and the barrier height. The helices are ‘easier’ to unfold and the remaining structure is less thermodynamically stable so that dissociation perpendicular to the force axis can occur at smaller deformations.
Having elucidated how canonical sequence modifications influence CC mechanics, the pulling geometry was investigated in the next step. Using one and the same sequence, the force application points were exchanged and two different shear and one unzipping geometry were compared. It was shown that the pulling geometry determines the mechanical stability of the CC. Different rupture forces were observed in the different shear as well as in the unzipping geometries, suggesting that chain separation follows different pathways on the energy landscape. Whereas the difference between CC shearing and unzipping was anticipated and has also been observed for other biological structures, the observed difference for the two shear geometries was less expected. It can be explained with the structural asymmetry of the CC heterodimer. It is proposed that the direction of the α-helices, the different local helix propensities and the position of a polar asparagine in the hydrophobic core are responsible for the observed difference in the chain separation pathways. In combination, these factors are considered to influence the interplay between processes parallel and perpendicular to the force axis.
To obtain more detailed insights into the role of helix stability, helical turns were reinforced locally using artificial constraints in the form of covalent and dynamic ‘staples’. A covalent staple bridges to adjacent helical turns, thus protecting them against uncoiling. The staple was inserted directly at the point of force application in one helix or in the same terminus of the other helix, which did not experience the force directly. It was shown that preventing helix uncoiling at the point of force application reduces the distance to the transition state while slightly increasing the barrier height. This confirms that helix uncoiling is critically important for CC chain separation. When inserted into the second helix, this stabilizing effect is transferred across the hydrophobic core and protects the force-loaded turns against uncoiling. If both helices were stapled, no additional increase in mechanical stability was observed. When replacing the covalent staple with a dynamic metal-coordination bond, a smaller decrease in the distance to the transition was observed, suggesting that the staple opens up while the CC is under load.
Using fluorinated amino acids as another type of non-natural modification, it was investigated how the enhanced hydrophobicity and the altered packing at the interface influences CC mechanics. The fluorinated amino acid was inserted into one central heptad of one or both α-helices. It was shown that this substitution destabilized the CC thermodynamically and mechanically. Specifically, the barrier height was decreased and the distance to the transition state increased. This suggests that a possible stabilizing effect of the increased hydrophobicity is overruled by a disturbed packing, which originates from a bad fit of the fluorinated amino acid into the local environment. This in turn increases the flexibility at the interface, as also observed for the hydrophobic core substitution described above. In combination, this confirms that the arrangement of the hydrophobic side chains is an additional crucial factor determining the mechanical stability of CCs.
In conclusion, this work shows that knowledge of the thermodynamic stability alone is not sufficient to predict the mechanical stability of CCs. It is the interplay between helix propensity and hydrophobic core packing that defines the sequence-structure-mechanics relationship. In combination, both parameters determine the relative contribution of processes parallel and perpendicular to the force axis, i.e. helix uncoiling and uncoiling-assisted sliding as well as dissociation. This new mechanistic knowledge provides insight into the mechanical function of CCs in tissues and opens up the road for designing CCs with pre-defined mechanical properties. The library of mechanically characterized CCs developed in this work is a powerful starting point for a wide spectrum of applications, ranging from molecular force sensors to mechanosensitive crosslinks in protein nanostructures and synthetic extracellular matrix mimics.
The global climate crisis is significantly contributing to changing ecosystems, loss of biodiversity and is putting numerous species on the verge of extinction. In principle, many species are able to adapt to changing conditions or shift their habitats to more suitable regions. However, change is progressing faster than some species can adjust, or potential adaptation is blocked and disrupted by direct and indirect human action. Unsustainable anthropogenic land use in particular is one of the driving factors, besides global heating, for these ecologically critical developments. Precisely because land use is anthropogenic, it is also a factor that could be quickly and immediately corrected by human action.
In this thesis, I therefore assess the impact of three climate change scenarios of increasing intensity in combination with differently scheduled mowing regimes on the long-term development and dispersal success of insects in Northwest German grasslands. The large marsh grasshopper (LMG, Stethophyma grossum, Linné 1758) is used as a species of reference for the analyses. It inhabits wet meadows and marshes and has a limited, yet fairly good ability to disperse. Mowing and climate conditions affect the development and mortality of the LMG differently depending on its life stage.
The specifically developed simulation model HiLEG (High-resolution Large Environmental
Gradient) serves as a tool for investigating and projecting viability and dispersal success under different climate conditions and land use scenarios. It is a spatially explicit, stage- and cohort-based model that can be individually configured to represent the life cycle and characteristics of terrestrial insect species, as well as high-resolution environmental data and the occurrence of external disturbances. HiLEG is a freely available and adjustable software that can be used to support conservation planning in cultivated grasslands.
In the three case studies of this thesis, I explore various aspects related to the structure of simulation models per se, their importance in conservation planning in general, and insights regarding the LMG in particular. It became apparent that the detailed resolution of model processes and components is crucial to project the long-term effect of spatially and temporally confined events. Taking into account conservation measures at the regional level has further proven relevant, especially in light of the climate crisis. I found that the LMG is benefiting from global warming in principle, but continues to be constrained by harmful mowing regimes. Land use measures could, however, be adapted in such a way that they allow the expansion and establishment of the LMG without overly affecting agricultural yields.
Overall, simulation models like HiLEG can make an important contribution and add value
to conservation planning and policy-making. Properly used, simulation results shed light
on aspects that might be overlooked by subjective judgment and the experience of individual stakeholders. Even though it is in the nature of models that they are subject to limitations and only represent fragments of reality, this should not keep stakeholders from using them, as long as these limitations are clearly communicated. Similar to HiLEG, models could further be designed in such a way that not only the parameterization can be adjusted as required, but also the implementation itself can be improved and changed as desired. This openness and flexibility should become more widespread in the development of simulation models.
The Arctic is a particularly sensitive area with respect to climate change due to the high surface albedo of snow and ice and the extreme radiative conditions. Clouds and aerosols as parts of the Arctic atmosphere play an important role in the radiation budget, which is, as yet, poorly quantified and understood. The LIDAR (Light Detection And Ranging) measurements presented in this PhD thesis contribute with continuous altitude resolved aerosol profiles to the understanding of occurrence and characteristics of aerosol layers above Ny-Ålesund, Spitsbergen. The attention was turned to the analysis of periods with high aerosol load. As the Arctic spring troposphere exhibits maximum aerosol optical depths (AODs) each year, March and April of both the years 2007 and 2009 were analyzed. Furthermore, stratospheric aerosol layers of volcanic origin were analyzed for several months, subsequently to the eruptions of the Kasatochi and Sarychev volcanoes in summer 2008 and 2009, respectively. The Koldewey Aerosol Raman LIDAR (KARL) is an instrument for the active remote sensing of atmospheric parameters using pulsed laser radiation. It is operated at the AWIPEV research base and was fundamentally upgraded within the framework of this PhD project. It is now equipped with a new telescope mirror and new detection optics, which facilitate atmospheric profiling from 450m above sea level up to the mid-stratosphere. KARL provides highly resolved profiles of the scattering characteristics of aerosol and cloud particles (backscattering, extinction and depolarization) as well as water vapor profiles within the lower troposphere. Combination of KARL data with data from other instruments on site, namely radiosondes, sun photometer, Micro Pulse LIDAR, and tethersonde system, resulted in a comprehensive data set of scattering phenomena in the Arctic atmosphere. The two spring periods March and April 2007 and 2009 were at first analyzed based on meteorological parameters, like local temperature and relative humidity profiles as well as large scale pressure patterns and air mass origin regions. Here, it was not possible to find a clear correlation between enhanced AOD and air mass origin. However, in a comparison of two cloud free periods in March 2007 and April 2009, large AOD values in 2009 coincided with air mass transport through the central Arctic. This suggests the occurrence of aerosol transformation processes during the aerosol transport to Ny-Ålesund. Measurements on 4 April 2009 revealed maximum AOD values of up to 0.12 and aerosol size distributions changing with altitude. This and other performed case studies suggest the differentiation between three aerosol event types and their origin: Vertically limited aerosol layers in dry air, highly variable hygroscopic boundary layer aerosols and enhanced aerosol load across wide portions of the troposphere. For the spring period 2007, the available KARL data were statistically analyzed using a characterization scheme, which is based on optical characteristics of the scattering particles. The scheme was validated using several case studies. Volcanic eruptions in the northern hemisphere in August 2008 and June 2009 arose the opportunity to analyze volcanic aerosol layers within the stratosphere. The rate of stratospheric AOD change was similar within both years with maximum values above 0.1 about three to five weeks after the respective eruption. In both years, the stratospheric AOD persisted at higher rates than usual until the measurements were stopped in late September due to technical reasons. In 2008, up to three aerosol layers were detected, the layer structure in 2009 was characterized by up to six distinct and thin layers which smeared out to one broad layer after about two months. The lowermost aerosol layer was continuously detected at the tropopause altitude. Three case studies were performed, all revealed rather large indices of refraction of m = (1.53–1.55) - 0.02i, suggesting the presence of an absorbing carbonaceous component. The particle radius, derived with inversion calculations, was also similar in both years with values ranging from 0.16 to 0.19 μm. However, in 2009, a second mode in the size distribution was detected at about 0.5 μm. The long term measurements with the Koldewey Aerosol Raman LIDAR in Ny-Ålesund provide the opportunity to study Arctic aerosols in the troposphere and the stratosphere not only in case studies but on longer time scales. In this PhD thesis, both, tropospheric aerosols in the Arctic spring and stratospheric aerosols following volcanic eruptions have been described qualitatively and quantitatively. Case studies and comparative studies with data of other instruments on site allowed for the analysis of microphysical aerosol characteristics and their temporal evolution.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.
Localisation of deformation is a ubiquitous feature in continental rift dynamics and observed across drastically different time and length scales. This thesis comprises one experimental and two numerical modelling studies investigating strain localisation in (1) a ductile shear zone induced by a material heterogeneity and (2) in an active continental rift setting. The studies are related by the fact that the weakening mechanisms on the crystallographic and grain size scale enable bulk rock weakening, which fundamentally enables the formation of shear zones, continental rifts and hence plate tectonics. Aiming to investigate the controlling mechanisms on initiation and evolution of a shear zone, the torsion experiments of the experimental study were conducted in a Patterson type apparatus with strong Carrara marble cylinders with a weak, planar Solnhofen limestone inclusion. Using state-of-the-art numerical modelling software, the torsion experiments were simulated to answer questions regarding localisation procedure like stress distribution or the impact of rheological weakening. 2D numerical models were also employed to integrate geophysical and geological data to explain characteristic tectonic evolution of the Southern and Central Kenya Rift. Key elements of the numerical tools are a randomized initial strain distribution and the usage of strain softening. During the torsion experiments, deformation begins to localise at the limestone inclusion tips in a process zone, which propagates into the marble matrix with increasing deformation until a ductile shear zone is established. Minor indicators for coexisting brittle deformation are found close to the inclusion tip and presumed to slightly facilitate strain localisation besides the dominant ductile deformation processes. The 2D numerical model of the torsion experiment successfully predicts local stress concentration and strain rate amplification ahead of the inclusion in first order agreement with the experimental results. A simple linear parametrization of strain weaking enables high accuracy reproduction of phenomenological aspects of the observed weakening. The torsion experiments suggest that loading conditions do not affect strain localisation during high temperature deformation of multiphase material with high viscosity contrasts. A numerical simulation can provide a way of analysing the process zone evolution virtually and extend the examinable frame. Furthermore, the nested structure and anastomosing shape of an ultramylonite band was mimicked with an additional second softening step. Rheological weakening is necessary to establish a shear zone in a strong matrix around a weak inclusion and for ultramylonite formation.
Such strain weakening laws are also incorporated into the numerical models of the
Southern and Central Kenya Rift that capture the characteristic tectonic evolution. A three-stage early rift evolution is suggested that starts with (1) the accommodation of strain by a single border fault and flexure of the hanging-wall crust, after which (2) faulting in the hanging-wall and the basin centre increases before (3) the early-stage asymmetry is lost and basinward localisation of deformation occurs. Along-strike variability of rifts can be produced by modifying the initial random noise distribution. In summary, the three studies address selected aspects of the broad range of mechanisms and processes that fundamentally enable the deformation of rock and govern the localisation patterns across the scales. In addition to the aforementioned results, the first and second manuscripts combined, demonstrate a procedure to find new or improve on existing numerical formulations for specific rheologies and their dynamic weakening. These formulations are essential in addressing rock deformation from the grain to the global scale. As within the third study of this thesis, where geodynamic controls on the evolution of a rift were examined and acquired by the integration of geological and geophysical data into a numerical model.
In my doctoral thesis, I examine continuous gravity measurements for monitoring of the geothermal site at Þeistareykir in North Iceland. With the help of high-precision superconducting gravity meters (iGravs), I investigate underground mass changes that are caused by operation of the geothermal power plant (i.e. by extraction of hot water and reinjection of cold water). The overall goal of this research project is to make a statement about the sustainable use of the geothermal reservoir, from which also the Icelandic energy supplier and power plant operator Landsvirkjun should benefit.
As a first step, for investigating the performance and measurement stability of the gravity meters, in summer 2017, I performed comparative measurements at the gravimetric observatory J9 in Strasbourg. From the three-month gravity time series, I examined calibration, noise and drift behaviour of the iGravs in comparison to stable long-term time series of the observatory superconducting gravity meters. After preparatory work in Iceland (setup of gravity stations, additional measuring equipment and infrastructure, discussions with Landsvirkjun and meetings with the Icelandic partner institute ISOR), gravity monitoring at Þeistareykir was started in December 2017. With the help of the iGrav records of the initial 18 months after start of measurements, I carried out the same investigations (on calibration, noise and drift behaviour) as in J9 to understand how the transport of the superconducting gravity meters to Iceland may influence instrumental parameters.
In the further course of this work, I focus on modelling and reduction of local gravity contributions at Þeistareykir. These comprise additional mass changes due to rain, snowfall and vertical surface displacements that superimpose onto the geothermal signal of the gravity measurements. For this purpose, I used data sets from additional monitoring sensors that are installed at each gravity station and adapted scripts for hydro-gravitational modelling. The third part of my thesis targets geothermal signals in the gravity measurements.
Together with my PhD colleague Nolwenn Portier from France, I carried out additional gravity measurements with a Scintrex CG5 gravity meter at 26 measuring points within the geothermal field in the summers of 2017, 2018 and 2019. These annual time-lapse gravity measurements are intended to increase the spatial coverage of gravity data from the three continuous monitoring stations to the entire geothermal field. The combination of CG5 and iGrav observations, as well as annual reference measurements with an FG5 absolute gravity meter represent the hybrid gravimetric monitoring method for Þeistareykir. Comparison of the gravimetric data to local borehole measurements (of groundwater levels, geothermal extraction and injection rates) is used to relate the observed gravity changes to the actually extracted (and reinjected) geothermal fluids. An approach to explain the observed gravity signals by means of forward modelling of the geothermal production rate is presented at the end of the third (hybrid gravimetric) study. Further modelling with the help of the processed gravity data is planned by Landsvirkjun. In addition, the experience from time-lapse and continuous gravity monitoring will be used for future gravity measurements at the Krafla geothermal field 22 km south-east of Þeistareykir.
The complex hierarchical structure of bone undergoes a lifelong remodeling process, where it adapts to mechanical needs. Hereby, bone resorption by osteoclasts and bone formation by osteoblasts have to be balanced to sustain a healthy and stable organ. Osteocytes orchestrate this interplay by sensing mechanical strains and translating them into biochemical signals. The osteocytes are located in lacunae and are connected to one another and other bone cells via cell processes through small channels, the canaliculi. Lacunae and canaliculi form a network (LCN) of extracellular spaces that is able to transport ions and enables cell-to-cell communication. Osteocytes might also contribute to mineral homeostasis by direct interactions with the surrounding matrix. If the LCN is acting as a transport system, this should be reflected in the mineralization pattern. The central hypothesis of this thesis is that osteocytes are actively changing their material environment. Characterization methods of material science are used to achieve the aim of detecting traces of this interaction between osteocytes and the extracellular matrix. First, healthy murine bones were characterized. The properties analyzed were then compared with three murine model systems: 1) a loading model, where a bone of the mouse was loaded during its life time; 2) a healing model, where a bone of the mouse was cut to induce a healing response; and 3) a disease model, where the Fbn1 gene is dysfunctional causing defects in the formation of the extracellular tissue.
The measurement strategy included routines that make it possible to analyze the organization of the LCN and the material components (i.e., the organic collagen matrix and the mineral particles) in the same bone volumes and compare the spatial distribution of different data sets. The three-dimensional network architecture of the LCN is visualized by confocal laser scanning microscopy (CLSM) after rhodamine staining and is then subsequently quantified. The calcium content is determined via quantitative backscattered electron imaging (qBEI), while small- and wide-angle X-ray scattering (SAXS and WAXS) are employed to determine the thickness and length of local mineral particles.
First, tibiae cortices of healthy mice were characterized to investigate how changes in LCN architecture can be attributed to interactions of osteocytes with the surrounding bone matrix. The tibial mid-shaft cross-sections showed two main regions, consisting of a band with unordered LCN surrounded by a region with ordered LCN. The unordered region is a remnant of early bone formation and exhibited short and thin mineral particles. The surrounding, more aligned bone showed ordered and dense LCN as well as thicker and longer mineral particles. The calcium content was unchanged between the two regions.
In the mouse loading model, the left tibia underwent two weeks of mechanical stimulation, which results in increased bone formation and decreased resorption in skeletally mature mice. Here the specific research question addressed was how do bone material characteristics change at (re)modeling sites? The new bone formed in response to mechanical stimulation showed similar properties in terms of the mineral particles, like the ordered calcium region but lower calcium content compared to the right, non-loaded control bone of the same mice. There was a clear, recognizable border between mature and newly formed bone. Nevertheless, some canaliculi went through this border connecting the LCN of mature and newly formed bone.
Additionally, the question should be answered whether the LCN topology and the bone matrix material properties adapt to loading. Although, mechanically stimulated bones did not show differences in calcium content compared to controls, different correlations were found between the local LCN density and the local Ca content depending on whether the bone was loaded or not. These results suggest that the LCN may serve as a mineral reservoir.
For the healing model, the femurs of mice underwent an osteotomy, stabilized with an external fixator and were allowed to heal for 21 days. Thus, the spatial variations in the LCN topology with mineral properties within different tissue types and their interfaces, namely calcified cartilage, bony callus and cortex, could be simultaneously visualized and compared in this model. All tissue types showed structural differences across multiple length scales. Calcium content increased and became more homogeneous from calcified cartilage to bony callus to lamellar cortical bone. The degree of LCN organization increased as well, while the lacunae became smaller, as did the lacunar density between these different tissue types that make up the callus. In the calcified cartilage, the mineral particles were short and thin. The newly formed callus exhibited thicker mineral particles, which still had a low degree of orientation. While most of the callus had a woven-like structure, it also served as a scaffold for more lamellar tissue at the edges. The lamelar bone callus showed thinner mineral particles, but a higher degree of alignment in both, mineral particles and the LCN. The cortex showed the highest values for mineral length, thickness and degree of orientation. At the same time, the lacunae number density was 34% lower and the lacunar volume 40% smaller compared to bony callus. The transition zone between cortical and callus regions showed a continuous convergence of bone mineral properties and lacunae shape. Although only a few canaliculi connected callus and the cortical region, this indicates that communication between osteocytes of both tissues should be possible. The presented correlations between LCN architecture and mineral properties across tissue types may suggest that osteocytes have an active role in mineralization processes of healing.
A mouse model for the disease marfan syndrome, which includes a genetic defect in the fibrillin-1 gene, was investigated. In humans, Marfan syndrome is characterized by a range of clinical symptoms such as long bone overgrowth, loose joints, reduced bone mineral density, compromised bone microarchitecture, and increased fracture rates. Thus, fibrillin-1 seems to play a role in the skeletal homeostasis. Therefore, the present work studied how marfan syndrome alters LCN architecture and the surrounding bone matrix. The mice with marfan syndrome showed longer tibiae than their healthy littermates from an age of seven weeks onwards. In contrast, the cortical development appeared retarded, which was observed across all measured characteristics, i. e. lower endocortical bone formation, looser and less organized lacuno-canalicular network, less collagen orientation, thinner and shorter mineral particles.
In each of the three model systems, this study found that changes in the LCN architecture spatially correlated with bone matrix material parameters. While not knowing the exact mechanism, these results provide indications that osteocytes can actively manipulate a mineral reservoir located around the canaliculi to make a quickly accessible contribution to mineral homeostasis. However, this interaction is most likely not one-sided, but could be understood as an interplay between osteocytes and extra-cellular matrix, since the bone matrix contains biochemical signaling molecules (e.g. non-collagenous proteins) that can change osteocyte behavior. Bone (re)modeling can therefore not only be understood as a method for removing defects or adapting to external mechanical stimuli, but also for increasing the efficiency of possible osteocyte-mineral interactions during bone homeostasis. With these findings, it seems reasonable to consider osteocytes as a target for drug development related to bone diseases that cause changes in bone composition and mechanical properties. It will most likely require the combined effort of materials scientists, cell biologists, and molecular biologists to gain a deeper understanding of how bone cells respond to their material environment.
The origin and structure of magnetic fields in the Galaxy are largely unknown. What is known is that they are essential for several astrophysical processes, in particular the propagation of cosmic rays. Our ability to describe the propagation of cosmic rays through the Galaxy is severely limited by the lack of observational data needed to probe the structure of the Galactic magnetic field on many different length scales. This is particularly true for modelling the propagation of cosmic rays into the Galactic halo, where our knowledge of the magnetic field is particularly poor.
In the last decade, observations of the Galactic halo in different frequency regimes have revealed the existence of out-of-plane bubble emission in the Galactic halo. In gamma rays these bubbles have been termed Fermi bubbles with a radial extent of ≈ 3 kpc and an azimuthal height of ≈ 6 kpc. The radio counterparts of the Fermi bubbles were seen by both the S-PASS telescopes and the Planck satellite, and showed a clear spatial overlap. The X-ray counterparts of the Fermi bubbles were named eROSITA bubbles after the eROSITA satellite, with a radial width of ≈ 7 kpc and an azimuthal height of ≈ 14 kpc. Taken together, these observations suggest the presence of large extended Galactic Halo Bubbles (GHB) and have stimulated interest in exploring the less explored Galactic halo.
In this thesis, a new toy model (GHB model) for the magnetic field and non-thermal electron distribution in the Galactic halo has been proposed. The new toy model has been used to produce polarised synchrotron emission sky maps. Chi-square analysis was used to compare the synthetic skymaps with the Planck 30 GHz polarised skymaps. The obtained constraints on the strength and azimuthal height were found to be in agreement with the S-PASS radio observations.
The upper, lower and best-fit values obtained from the above chi-squared analysis were used to generate three separate toy models. These three models were used to propagate ultra-high energy cosmic rays. This study was carried out for two potential sources, Centaurus A and NGC 253, to produce magnification maps and arrival direction skymaps. The simulated arrival direction skymaps were found to be consistent with the hotspots of Centaurus A and NGC 253 as seen in the observed arrival direction skymaps provided by the Pierre Auger Observatory (PAO).
The turbulent magnetic field component of the GHB model was also used to investigate the extragalactic dipole suppression seen by PAO. UHECRs with an extragalactic dipole were forward-tracked through the turbulent GHB model at different field strengths. The suppression in the dipole due to the varying diffusion coefficient from the simulations was noted. The results could also be compared with an analytical analogy of electrostatics. The simulations of the extragalactic dipole suppression were in agreement with similar studies carried out for galactic cosmic rays.
Data dependencies, or integrity constraints, are used to improve the quality of a database schema, to optimize queries, and to ensure consistency in a database. In the last years conditional dependencies have been introduced to analyze and improve data quality. In short, a conditional dependency is a dependency with a limited scope defined by conditions over one or more attributes. Only the matching part of the instance must adhere to the dependency. In this paper we focus on conditional inclusion dependencies (CINDs). We generalize the definition of CINDs, distinguishing covering and completeness conditions. We present a new use case for such CINDs showing their value for solving complex data quality tasks. Further, we define quality measures for conditions inspired by precision and recall. We propose efficient algorithms that identify covering and completeness conditions conforming to given quality thresholds. Our algorithms choose not only the condition values but also the condition attributes automatically. Finally, we show that our approach efficiently provides meaningful and helpful results for our use case.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
Fluvial systems are one of the major features shaping a landscape. They adjust to the prevailing tectonic and climatic setting and therefore are very sensitive markers of changes in these systems. If their response to tectonic and climatic forcing is quantified and if the climatic signal is excluded, it is possible to derive a local deformation history. Here, we investigate fluvial terraces and erosional surfaces in the southern Chilean forearc to assess a long-term geomorphic and hence tectonic evolution. Remote sensing and field studies of the Nahuelbuta Range show that the long-term deformation of the Chilean forearc is manifested by breaks in topography, sequences of differentially uplifted marine, alluvial and strath terraces as well as tectonically modified river courses and drainage basins. We used SRTM-90-data as basic elevation information for extracting and delineating drainage networks. We calculated hypsometric curves as an indicator for basin uplift, stream-length gradient indices to identify stream segments with anomalous slopes, and longitudinal river profiles as well as DS-plots to identify knickpoints and other anomalies. In addition, we investigated topography with elevation-slope graphs, profiles, and DEMs to reveal erosional surfaces. During the first field trip we already measured palaeoflow directions, performed pebble counting and sampled the fluvial terraces in order to apply cosmogenic nuclide dating (<sup>10Be, <sup>26Al) as well as provenance analyses. Our preliminary analysis of the Coastal Cordillera indicates a clear segmentation between the northern and southern parts of the Nahuelbuta Range. The Lanalhue Fault, a NW-SE striking fault zone oblique to the plate boundary, defines the segment boundary. Furthermore, we find a complex drainage re-organisation including a drainage reversal and wind gap on the divide between the Tirúa and Pellahuén basins east of the town Tirúa. The coastal basins lost most of their Andean sediment supply areas that existed in Tertiary and in part during early Pleistocene time. Between the Bío-Bío and Imperial rivers no Andean river is recently capable to traverse the Coastal Cordillera, suggesting ongoing Quaternary uplift of the entire range. From the spatial distribution of geomorphic surfaces in this region two uplift signals may be derived: (1) a long-term differential uplift process, active since the Miocene and possibly caused by underplating of subducted trench sediments, (2) a younger, local uplift affecting only the northern part of the Nahuelbuta Range that may be caused by the interaction of the forearc with the subduction of the Mocha Fracture Zone at the latitude of the Arauco peninsula. Our approach thus provides results in our attempt to decipher the characteristics of forearc development of active convergent margins using long-term geomorphic indicators. Furthermore, it is expected that our ongoing assessment will constrain repeatedly active zones of deformation. <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Dermal Delivery of the High-Molecular-Weight Drug Tacrolimus by Means of Polyglycerol-Based Nanogels
(2019)
Polyglycerol-based thermoresponsive nanogels (tNGs) have been shown to have excellent skin hydration properties and to be valuable delivery systems for sustained release of drugs into skin. In this study, we compared the skin penetration of tacrolimus formulated in tNGs with a commercial 0.1% tacrolimus ointment. The penetration of the drug was investigated in ex vivo abdominal and breast skin, while different methods for skin barrier disruption were investigated to improve skin permeability or simulate inflammatory conditions with compromised skin barrier. The amount of penetrated tacrolimus was measured in skin extracts by liquid chromatography tandem-mass spectrometry (LC-MS/MS), whereas the inflammatory markers IL-6 and IL-8 were detected by enzyme-linked immunosorbent assay (ELISA). Higher amounts of tacrolimus penetrated in breast as compared to abdominal skin or in barrier-disrupted as compared to intact skin, confirming that the stratum corneum is the main barrier for tacrolimus skin penetration. The anti-proliferative effect of the penetrated drug was measured in skin tissue/Jurkat cells co-cultures. Interestingly, tNGs exhibited similar anti-proliferative effects as the 0.1% tacrolimus ointment. We conclude that polyglycerol-based nanogels represent an interesting alternative to paraffin-based formulations for the treatment of inflammatory skin conditions.
While a growing body of literature finds positive impacts of Start-Up Subsidies (SUS) on labor market outcomes of participants, little is known about how the design of these programs shapes their effectiveness and hence how to improve policy. As experimental variation in program design is unavailable, we exploit the 2011 reform of the current German SUS program for the unemployed which strengthened case-workers’ discretionary power, increased entry requirements and reduced monetary support. We estimate the impact of the reform on the program’s effectiveness using samples of participants and non-participants from before and after the reform. To control for time-constant unobserved heterogeneity as well as differential selection patterns based on observable characteristics over time, we combine Difference-in-Differences with inverse probability weighting using covariate balancing propensity scores. Holding participants’ observed characteristics as well as macroeconomic conditions constant, the results suggest that the reform was successful in raising employment effects on average. As these findings may be contaminated by changes in selection patterns based on unobserved characteristics, we assess our results using simulation-based sensitivity analyses and find that our estimates are highly robust to changes in unobserved characteristics. Hence, the reform most likely had a positive impact on the effectiveness of the program, suggesting that increasing entry requirements and reducing support in-creased the program’s impacts while reducing the cost per participant.
The Voyager 2 Photopolarimeter experiment has yielded the highest resolved data of Saturn's rings, exhibiting a wide variety of features. The B-ring region between 105000 km and 110000 km distance from Saturn has been investigated. It has a high matter density and contains no significance features visible by eye. Analysis with statistical methods has let us to the detection of two significant events. These features are correlated with the inner 3:2 resonances of the F-ring shepherd satellites Pandora and Prometheus, and may be evidence of large ring paricles caught in the corotation resonances.
It is desirable to reduce the potential threats that result from the variability of nature, such as droughts or heat waves that lead to food shortage, or the other extreme, floods that lead to severe damage. To prevent such catastrophic events, it is necessary to understand, and to be capable of characterising, nature's variability. Typically one aims to describe the underlying dynamics of geophysical records with differential equations. There are, however, situations where this does not support the objectives, or is not feasible, e.g., when little is known about the system, or it is too complex for the model parameters to be identified. In such situations it is beneficial to regard certain influences as random, and describe them with stochastic processes. In this thesis I focus on such a description with linear stochastic processes of the FARIMA type and concentrate on the detection of long-range dependence. Long-range dependent processes show an algebraic (i.e. slow) decay of the autocorrelation function. Detection of the latter is important with respect to, e.g. trend tests and uncertainty analysis. Aiming to provide a reliable and powerful strategy for the detection of long-range dependence, I suggest a way of addressing the problem which is somewhat different from standard approaches. Commonly used methods are based either on investigating the asymptotic behaviour (e.g., log-periodogram regression), or on finding a suitable potentially long-range dependent model (e.g., FARIMA[p,d,q]) and test the fractional difference parameter d for compatibility with zero. Here, I suggest to rephrase the problem as a model selection task, i.e.comparing the most suitable long-range dependent and the most suitable short-range dependent model. Approaching the task this way requires a) a suitable class of long-range and short-range dependent models along with suitable means for parameter estimation and b) a reliable model selection strategy, capable of discriminating also non-nested models. With the flexible FARIMA model class together with the Whittle estimator the first requirement is fulfilled. Standard model selection strategies, e.g., the likelihood-ratio test, is for a comparison of non-nested models frequently not powerful enough. Thus, I suggest to extend this strategy with a simulation based model selection approach suitable for such a direct comparison. The approach follows the procedure of a statistical test, with the likelihood-ratio as the test statistic. Its distribution is obtained via simulations using the two models under consideration. For two simple models and different parameter values, I investigate the reliability of p-value and power estimates obtained from the simulated distributions. The result turned out to be dependent on the model parameters. However, in many cases the estimates allow an adequate model selection to be established. An important feature of this approach is that it immediately reveals the ability or inability to discriminate between the two models under consideration. Two applications, a trend detection problem in temperature records and an uncertainty analysis for flood return level estimation, accentuate the importance of having reliable methods at hand for the detection of long-range dependence. In the case of trend detection, falsely concluding long-range dependence implies an underestimation of a trend and possibly leads to a delay of measures needed to take in order to counteract the trend. Ignoring long-range dependence, although present, leads to an underestimation of confidence intervals and thus to an unjustified belief in safety, as it is the case for the return level uncertainty analysis. A reliable detection of long-range dependence is thus highly relevant in practical applications. Examples related to extreme value analysis are not limited to hydrological applications. The increased uncertainty of return level estimates is a potentially problem for all records from autocorrelated processes, an interesting examples in this respect is the assessment of the maximum strength of wind gusts, which is important for designing wind turbines. The detection of long-range dependence is also a relevant problem in the exploration of financial market volatility. With rephrasing the detection problem as a model selection task and suggesting refined methods for model comparison, this thesis contributes to the discussion on and development of methods for the detection of long-range dependence.
Today about 24 Million people worldwide suffer from dementia, Alzheimer’s Disease accounts for approximately 50-60% of all dementia cases. As the prevalence of dementia grows with increasing age Alzheimer’s Disease becomes more and more of an issue for society as the proportion of elderly people increases from year to year. It is well established, that the amino acid glutamate - quantitatively being the most important neurotransmitter in the central nervous system (CNS) - may reach toxic concentrations if not cleared from the synaptic cleft into which it is released during transmittance of action potentials. In Alzheimer’s Disease there is strong evidence for a generally impaired glutamate uptake system which in turn is thought to result in toxic levels of the amino acid with the potential to kill off neurons. The excitatory amino acid transporter 1 (EAAT1) belongs to the family of Na+-dependent glutamate transporter and accounts together with EAAT2 for most of the glutamate uptake in the CNS. In this project a new splice variant of EAAT1, skipping exon 3 was detected in human brain samples and subsequently called EAAT1Δ3, this being the second splice variant found after the recent detection of EAAT1Δ9. A method was developed to quantify the transcript of EAAT1 wt, EAAT1Δ3 and EAAT1Δ9 by means of real-time PCR. Samples were taken from different brain areas of a set of control and AD cases. The areas chosen for examination are affected differently in Alzheimer’s Disease, this was used an internal control for the experiments done in this project as to determine whether any effect observed is specific for AD, i.e. AD affected areas or is generally seen in all areas examined. The results of this project show that EAAT1Δ3 is transcribed in very low copy numbers making up a proportion of 0.15% of EAAT1 wt whereas EAAT1Δ9 is transcribed in a considerably large proportion of EAAT1 wt of 26.6%. It was moreover found that all EAAT1 variants are transcribed at significantly lower rates (P<0.0001) in AD cases, supporting the theory that EAAT1 protein expression is reduced to a point where glutamate uptake normally mediated by this transporter is impaired. This in turn is thought to result in toxic levels glutamate accounting for neuronal loss in the disease. No area-dependent effects were found, suggesting that the reduction of EAAT1 transcription is rather a result of an underlying general mechanism present in AD. Further research will have to be done to assess the degree of EAAT1 expression in AD and whether those future findings match with the result of this project.
Cargo transport by molecular motors is ubiquitous in all eukaryotic cells and is typically driven cooperatively by several molecular motors, which may belong to one or several motor species like kinesin, dynein or myosin. These motor proteins transport cargos such as RNAs, protein complexes or organelles along filaments, from which they unbind after a finite run length. Understanding how these motors interact and how their movements are coordinated and regulated is a central and challenging problem in studies of intracellular transport. In this thesis, we describe a general theoretical framework for the analysis of such transport processes, which enables us to explain the behavior of intracellular cargos based on the transport properties of individual motors and their interactions. Motivated by recent in vitro experiments, we address two different modes of transport: unidirectional transport by two identical motors and cooperative transport by actively walking and passively diffusing motors. The case of cargo transport by two identical motors involves an elastic coupling between the motors that can reduce the motors’ velocity and/or the binding time to the filament. We show that this elastic coupling leads, in general, to four distinct transport regimes. In addition to a weak coupling regime, kinesin and dynein motors are found to exhibit a strong coupling and an enhanced unbinding regime, whereas myosin motors are predicted to attain a reduced velocity regime. All of these regimes, which we derive both by analytical calculations and by general time scale arguments, can be explored experimentally by varying the elastic coupling strength. In addition, using the time scale arguments, we explain why previous studies came to different conclusions about the effect and relevance of motor-motor interference. In this way, our theory provides a general and unifying framework for understanding the dynamical behavior of two elastically coupled molecular motors. The second mode of transport studied in this thesis is cargo transport by actively pulling and passively diffusing motors. Although these passive motors do not participate in active transport, they strongly enhance the overall cargo run length. When an active motor unbinds, the cargo is still tethered to the filament by the passive motors, giving the unbound motor the chance to rebind and continue its active walk. We develop a stochastic description for such cooperative behavior and explicitly derive the enhanced run length for a cargo transported by one actively pulling and one passively diffusing motor. We generalize our description to the case of several pulling and diffusing motors and find an exponential increase of the run length with the number of involved motors.
The widespread usage of products containing volatile organic compounds (VOC) has lead to a general human exposure to these chemicals in work places or homes being suspected to contribute to the growing incidence of environmental diseases. Since the causal molecular mechanisms for the development of these disorders are not completely understood, the overall objective of this thesis was to investigate VOC-mediated molecular effects on human lung cells in vitro at VOC concentrations comparable to exposure scenarios below current occupational limits. Although differential expression of single proteins in response to VOCs has been reported, effects on complex protein networks (proteome) have not been investigated. However, this information is indispensable when trying to ascertain a mechanism for VOC action on the cellular level and establishing preventive strategies. For this study, the alveolar epithelial cell line A549 has been used. This cell line, cultured in a two-phase (air/liquid) model allows the most direct exposure and had been successfully applied for the analysis of inflammatory effects in response to VOCs. Mass spectrometric identification of 266 protein spots provided the first proteomic map of A549 cell line to this extent that may foster future work with this frequently used cellular model. The distribution of three typical air contaminants, monochlorobenzene (CB), styrene and 1,2 dichlorobenzene (1,2-DCB), between gas and liquid phase of the exposure model has been analyzed by gas chromatography. The obtained VOC partitioning was in agreement with available literature data. Subsequently the adapted in vitro system has been successfully employed to characterize the effects of the aromatic compound styrene on the proteome of A549 cells (Chapter 4). Initially, the cell toxicity has been assessed in order to ensure that most of the concentrations used in the following proteomic approach were not cytotoxic. Significant changes in abundance and phosphorylation in the total soluble protein fraction of A549 cells have been detected following styrene exposure. All proteins have been identified using mass spectrometry and the main cellular functions have been assigned. Validation experiments on protein and transcript level confirmed the results of the 2-DE experiments. From the results, two main cellular pathways have been identified that were induced by styrene: the cellular oxidative stress response combined with moderate pro-apoptotic signaling. Measurement of cellular reactive oxygen species (ROS) as well as the styrene-mediated induction of oxidative stress marker proteins confirmed the hypothesis of oxidative stress as the main molecular response mechanism. Finally, adducts of cellular proteins with the reactive styrene metabolite styrene 7,8 oxide (SO) have been identified. Especially the SO-adducts observed at both the reactive centers of thioredoxin reductase 1, which is a key element in the control of the cellular redox state, may be involved in styrene-induced ROS formation and apoptosis. A similar proteomic approach has been carried out with the halobenzenes CB and 1,2-DCB (Chapter 5). In accordance with previous findings, cell toxicity assessment showed enhanced toxicity compared to the one caused by styrene. Significant changes in abundance and phosphorylation of total soluble proteins of A549 cells have been detected following exposure to subtoxic concentrations of CB and 1,2-DCB. All proteins have been identified using mass spectrometry and the main cellular functions have been assigned. As for the styrene experiment, the results indicated two main pathways to be affected in the presence of chlorinated benzenes, cell death signaling and oxidative stress response. The strong induction of pro-apoptotic signaling has been confirmed for both treatments by detection of the cleavage of caspase 3. Likewise, the induction of redox-sensitive protein species could be correlated to an increased cellular level of ROS observed following CB treatment. Finally, common mechanisms in the cellular response to aromatic VOCs have been investigated (Chapter 6). A similar number (4.6-6.9%) of all quantified protein spots showed differential expression (p<0.05) following cell exposure to styrene, CB or 1,2-DCB. However, not more than three protein spots showed significant regulation in the same direction for all three volatile compounds: voltage-dependent anion-selective channel protein 2, peroxiredoxin 1 and elongation factor 2. However, all of these proteins are important molecular targets in stress- and cell death-related signaling pathways.
We investigate whether political ideology has an observable effect on decarbonization ambition, renewable power aims, and preferences for power system balancing technologies in four European countries. Based on the Energy Logics framework, we identify ideologically different transition strategies (state-centered, market-centered, grassroots-centered) contained in government policies and opposition party programs valid in 2019. We compare these policies and programs with citizen poll data. We find that ideology has a small effect: governments and political parties across the spectrum have similar, and relatively ambitious, decarbonization and renewables targets. This mirrors citizens' strong support for ambitious action regardless of their ideological self-description. However, whereas political positions on phasing out fossil fuel power are clear across the policy space, positions on phasing in new flexibility options to balance intermittent renewables are vague or non-existent. As parties and citizens agree on strong climate and renewable power aims, the policy ambition is likely to remain high, even if governments change.
Dryland vulnerability : typical patterns and dynamics in support of vulnerability reduction efforts
(2011)
The pronounced constraints on ecosystem functioning and human livelihoods in drylands are frequently exacerbated by natural and socio-economic stresses, including weather extremes and inequitable trade conditions. Therefore, a better understanding of the relation between these stresses and the socio-ecological systems is important for advancing dryland development. The concept of vulnerability as applied in this dissertation describes this relation as encompassing the exposure to climate, market and other stresses as well as the sensitivity of the systems to these stresses and their capacity to adapt. With regard to the interest in improving environmental and living conditions in drylands, this dissertation aims at a meaningful generalisation of heterogeneous vulnerability situations. A pattern recognition approach based on clustering revealed typical vulnerability-creating mechanisms at global and local scales. One study presents the first analysis of dryland vulnerability with global coverage at a sub-national resolution. The cluster analysis resulted in seven typical patterns of vulnerability according to quantitative indication of poverty, water stress, soil degradation, natural agro-constraints and isolation. Independent case studies served to validate the identified patterns and to prove the transferability of vulnerability-reducing approaches. Due to their worldwide coverage, the global results allow the evaluation of a specific system’s vulnerability in its wider context, even in poorly-documented areas. Moreover, climate vulnerability of smallholders was investigated with regard to their food security in the Peruvian Altiplano. Four typical groups of households were identified in this local dryland context using indicators for harvest failure risk, agricultural resources, education and non-agricultural income. An elaborate validation relying on independently acquired information demonstrated the clear correlation between weather-related damages and the identified clusters. It also showed that household-specific causes of vulnerability were consistent with the mechanisms implied by the corresponding patterns. The synthesis of the local study provides valuable insights into the tailoring of interventions that reflect the heterogeneity within the social group of smallholders. The conditions necessary to identify typical vulnerability patterns were summarised in five methodological steps. They aim to motivate and to facilitate the application of the selected pattern recognition approach in future vulnerability analyses. The five steps outline the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. The precise definition of the hypotheses is essential to appropriately quantify the basic processes as well as to consistently interpret, validate and rank the clusters. In particular, the five steps reflect scale-dependent opportunities, such as the outcome-oriented aspect of validation in the local study. Furthermore, the clusters identified in Northeast Brazil were assessed in the light of important endogenous processes in the smallholder systems which dominate this region. In order to capture these processes, a qualitative dynamic model was developed using generalised rules of labour allocation, yield extraction, budget constitution and the dynamics of natural and technological resources. The model resulted in a cyclic trajectory encompassing four states with differing degree of criticality. The joint assessment revealed aggravating conditions in major parts of the study region due to the overuse of natural resources and the potential for impoverishment. The changes in vulnerability-creating mechanisms identified in Northeast Brazil are well-suited to informing local adjustments to large-scale intervention programmes, such as “Avança Brasil”. Overall, the categorisation of a limited number of typical patterns and dynamics presents an efficient approach to improving our understanding of dryland vulnerability. Appropriate decision-making for sustainable dryland development through vulnerability reduction can be significantly enhanced by pattern-specific entry points combined with insights into changing hotspots of vulnerability and the transferability of successful adaptation strategies.
In this paper, we consider families of time Markov fields (or reciprocal classes) which have the same bridges as a Brownian diffusion. We characterize each class as the set of solutions of an integration by parts formula on the space of continuous paths C[0; 1]; R-d) Our techniques provide a characterization of gradient diffusions by a duality formula and, in case of reversibility, a generalization of a result of Kolmogorov.
In the arable soil landscape of hummocky ground moraines, an erosion-affected spatial differentiation of soils can be observed. Man-made erosion leads to soil profile modifications along slopes with changed solum thickness and modified properties of soil horizons due to water erosion in combination with tillage operations. Soil erosion creates, thereby, spatial patterns of soil properties (e.g., texture and organic matter content) and differences in crop development. However, little is known about the manner in which water fluxes are affected by soil-crop interactions depending on contrasting properties of differently-developed soil horizons and how water fluxes influence the carbon transport in an eroded landscape. To identify such feedbacks between erosion-induced soil profile modifications and the 1D-water and solute balance, high-precision weighing lysimeters equipped with a wide range of sensor technique were filled with undisturbed soil monoliths that differed in the degree of past soil erosion. Furthermore, lysimeter effluent concentrations were analyzed for dissolved carbon fractions in bi-weekly intervals.
The water balance components measured by high precision lysimeters varied from the most eroded to the less eroded monolith up to 83 % (deep drainage) primarily caused due to varying amounts of precipitation and evapotranspiration for a 3-years period. Here, interactions between crop development and contrasting rainfall interception by above ground biomass could explain differences in water balance components. Concentrations of dissolved carbon in soil water samples were relatively constant in time, suggesting carbon leaching was mainly affected by water fluxes in this observation period. For the lysimeter-based water balance analysis, a filtering scheme was developed considering temporal autocorrelation. The minute-based autocorrelation analysis of mass changes from lysimeter time series revealed characteristic autocorrelation lengths ranging from 23 to 76 minutes. Thereby, temporal autocorrelation provided an optimal approximation of precipitation quantities. However, the high temporal resolution in lysimeter time series is restricted by the lengths of autocorrelation.
Erosion-induced but also gradual changes in soil properties were reflected by dynamics of soil water retention properties in the lysimeter soils. Short-term and long-term hysteretic water retention data suggested seasonal wettability problems of soils increasingly limited rewetting of previously dried pore regions. Differences in water retention were assigned to soil tillage operations and the erosion history at different slope positions. The threedimensional spatial pattern of soil types that result from erosional soil profile modifications were also reflected in differences of crop root development at different landscape positions. Contrasting root densities revealed positive relations of root and aboveground plant characteristics. Differences in the spatially-distributed root growth between different eroded soil types provided indications that root development was affected by the erosion-induced soil evolution processes.
Overall, the current thesis corroborated the hypothesis that erosion-induced soil profile modifications affect the soil water balance, carbon leaching and soil hydraulic properties, but also the crop root system is influenced by erosion-induced spatial patterns of soil properties in the arable hummocky post glacial soil landscape. The results will help to improve model predictions of water and solute movement in arable soils and to understand interactions between soil erosion and carbon pathways regarding sink-or-source terms in landscapes.
Data obtained from foreign data sources often come with only superficial structural information, such as relation names and attribute names. Other types of metadata that are important for effective integration and meaningful querying of such data sets are missing. In particular, relationships among attributes, such as foreign keys, are crucial metadata for understanding the structure of an unknown database. The discovery of such relationships is difficult, because in principle for each pair of attributes in the database each pair of data values must be compared. A precondition for a foreign key is an inclusion dependency (IND) between the key and the foreign key attributes. We present with Spider an algorithm that efficiently finds all INDs in a given relational database. It leverages the sorting facilities of DBMS but performs the actual comparisons outside of the database to save computation. Spider analyzes very large databases up to an order of magnitude faster than previous approaches. We also evaluate in detail the effectiveness of several heuristics to reduce the number of necessary comparisons. Furthermore, we generalize Spider to find composite INDs covering multiple attributes, and partial INDs, which are true INDs for all but a certain number of values. This last type is particularly relevant when integrating dirty data as is often the case in the life sciences domain - our driving motivation.
To achieve a sustainable energy economy, it is necessary to turn back on the combustion of fossil fuels as a means of energy production and switch to renewable sources. However, their temporal availability does not match societal consumption needs, meaning that renewably generated energy must be stored in its main generation times and allocated during peak consumption periods. Electrochemical energy storage (EES) in general is well suited due to its infrastructural independence and scalability. The lithium ion battery (LIB) takes a special place, among EES systems due to its energy density and efficiency, but the scarcity and uneven geological occurrence of minerals and ores vital for many cell components, and hence the high and fluctuating costs will decelerate its further distribution.
The sodium ion battery (SIB) is a promising successor to LIB technology, as the fundamental setup and cell chemistry is similar in the two systems. Yet, the most widespread negative electrode material in LIBs, graphite, cannot be used in SIBs, as it cannot store sufficient amounts of sodium at reasonable potentials. Hence, another carbon allotrope, non-graphitizing or hard carbon (HC) is used in SIBs. This material consists of turbostratically disordered, curved graphene layers, forming regions of graphitic stacking and zones of deviating layers, so-called internal or closed pores.
The structural features of HC have a substantial impact of the charge-potential curve exhibited by the carbon when it is used as the negative electrode in an SIB. At defects and edges an adsorption-like mechanism of sodium storage is prevalent, causing a sloping voltage curve, ill-suited for the practical application in SIBs, whereas a constant voltage plateau of relatively high capacities is found immediately after the sloping region, which recent research attributed to the deposition of quasimetallic sodium into the closed pores of HC.
Literature on the general mechanism of sodium storage in HCs and especially the role of the closed pore is abundant, but the influence of the pore geometry and chemical nature of the HC on the low-potential sodium deposition is yet in an early stage. Therefore, the scope of this thesis is to investigate these relationships using suitable synthetic and characterization methods. Materials of precisely known morphology, porosity, and chemical structure are prepared in clear distinction to commonly obtained ones and their impact on the sodium storage characteristics is observed. Electrochemical impedance spectroscopy in combination with distribution of relaxation times analysis is further established as a technique to study the sodium storage process, in addition to classical direct current techniques, and an equivalent circuit model is proposed to qualitatively describe the HC sodiation mechanism, based on the recorded data. The obtained knowledge is used to develop a method for the preparation of closed porous and non-porous materials from open porous ones, proving not only the necessity of closed pores for efficient sodium storage, but also providing a method for effective pore closure and hence the increase of the sodium storage capacity and efficiency of carbon materials.
The insights obtained and methods developed within this work hence not only contribute to the better understanding of the sodium storage mechanism in carbon materials of SIBs, but can also serve as guidance for the design of efficient electrode materials.
Our dynamic Sun manifests its activity by different phenomena: from the 11-year cyclic sunspot pattern to the unpredictable and violent explosions in the case of solar flares. During flares, a huge amount of the stored magnetic energy is suddenly released and a substantial part of this energy is carried by the energetic electrons, considered to be the source of the nonthermal radio and X-ray radiation. One of the most important and still open question in solar physics is how the electrons are accelerated up to high energies within (the observed in the radio emission) short time scales. Because the acceleration site is extremely small in spatial extent as well (compared to the solar radius), the electron acceleration is regarded as a local process. The search for localized wave structures in the solar corona that are able to accelerate electrons together with the theoretical and numerical description of the conditions and requirements for this process, is the aim of the dissertation. Two models of electron acceleration in the solar corona are proposed in the dissertation: I. Electron acceleration due to the solar jet interaction with the background coronal plasma (the jet--plasma interaction) A jet is formed when the newly reconnected and highly curved magnetic field lines are relaxed by shooting plasma away from the reconnection site. Such jets, as observed in soft X-rays with the Yohkoh satellite, are spatially and temporally associated with beams of nonthermal electrons (in terms of the so-called type III metric radio bursts) propagating through the corona. A model that attempts to give an explanation for such observational facts is developed here. Initially, the interaction of such jets with the background plasma leads to an (ion-acoustic) instability associated with growing of electrostatic fluctuations in time for certain range of the jet initial velocity. During this process, any test electron that happen to feel this electrostatic wave field is drawn to co-move with the wave, gaining energy from it. When the jet speed has a value greater or lower than the one, required by the instability range, such wave excitation cannot be sustained and the process of electron energization (acceleration and/or heating) ceases. Hence, the electrons can propagate further in the corona and be detected as type III radio burst, for example. II. Electron acceleration due to attached whistler waves in the upstream region of coronal shocks (the electron--whistler--shock interaction) Coronal shocks are also able to accelerate electrons, as observed by the so-called type II metric radio bursts (the radio signature of a shock wave in the corona). From in-situ observations in space, e.g., at shocks related to co-rotating interaction regions, it is known that nonthermal electrons are produced preferably at shocks with attached whistler wave packets in their upstream regions. Motivated by these observations and assuming that the physical processes at shocks are the same in the corona as in the interplanetary medium, a new model of electron acceleration at coronal shocks is presented in the dissertation, where the electrons are accelerated by their interaction with such whistlers. The protons inflowing toward the shock are reflected there by nearly conserving their magnetic moment, so that they get a substantial velocity gain in the case of a quasi-perpendicular shock geometry, i.e, the angle between the shock normal and the upstream magnetic field is in the range 50--80 degrees. The so-accelerated protons are able to excite whistler waves in a certain frequency range in the upstream region. When these whistlers (comprising the localized wave structure in this case) are formed, only the incoming electrons are now able to interact resonantly with them. But only a part of these electrons fulfill the the electron--whistler wave resonance condition. Due to such resonant interaction (i.e., of these electrons with the whistlers), the electrons are accelerated in the electric and magnetic wave field within just several whistler periods. While gaining energy from the whistler wave field, the electrons reach the shock front and, subsequently, a major part of them are reflected back into the upstream region, since the shock accompanied with a jump of the magnetic field acts as a magnetic mirror. Co-moving with the whistlers now, the reflected electrons are out of resonance and hence can propagate undisturbed into the far upstream region, where they are detected in terms of type II metric radio bursts. In summary, the kinetic energy of protons is transfered into electrons by the action of localized wave structures in both cases, i.e., at jets outflowing from the magnetic reconnection site and at shock waves in the corona.
The self-employed faced strong income losses during the Covid-19 pandemic. Many governments introduced programs to financially support the self-employed during the pandemic, including Germany. The German Ministry for Economic Affairs announced a €50bn emergency-aid program in March 2020, offering one-off lump-sum payments of up to €15,000 to those facing substantial revenue declines. By reassuring the self- employed that the government ‘would not let them down’ during the crisis, the program had also the important aim of motivating the self-employed to get through the crisis. We investigate whether the program affected the confidence of the self-employed to survive the crisis using real-time online-survey data comprising more than 20,000 observations. We employ propensity score matching, making use of a rich set of variables that influence the subjective survival probability as main outcome measure. We observe that this program had significant effects, with the subjective survival probability of the self- employed being moderately increased. We reveal important effect heterogeneities with respect to education, industries, and speed of payment. Notably, positive effects only occur among those self-employed whose application was processed quickly. This suggests stress-induced waiting costs due to the uncertainty associated with the administrative processing and the overall pandemic situation. Our findings have policy implications for the design of support programs, while also contributing to the literature on the instruments and effects of entrepreneurship policy interventions in crisis situations.
Plate tectonics describes the movement of rigid plates at the surface of the Earth as well as their complex deformation at three types of plate boundaries: 1) divergent boundaries such as rift zones and mid-ocean ridges, 2) strike-slip boundaries where plates grind past each other, such as the San Andreas Fault, and 3) convergent boundaries that form large mountain ranges like the Andes. The generally narrow deformation zones that bound the plates exhibit complex strain patterns that evolve through time. During this evolution, plate boundary deformation is driven by tectonic forces arising from Earth’s deep interior and from within the lithosphere, but also by surface processes, which erode topographic highs and deposit the resulting sediment into regions of low elevation. Through the combination of these factors, the surface of the Earth evolves in a highly dynamic way with several feedback mechanisms. At divergent boundaries, for example, tensional stresses thin the lithosphere, forcing uplift and subsequent erosion of rift flanks, which creates a sediment source. Meanwhile, the rift center subsides and becomes a topographic low where sediments accumulate. This mass transfer from foot- to hanging wall plays an important role during rifting, as it prolongs the activity of individual normal faults. When rifting continues, continents are eventually split apart, exhuming Earth’s mantle and creating new oceanic crust. Because of the complex interplay between deep tectonic forces that shape plate boundaries and mass redistribution at the Earth’s surface, it is vital to understand feedbacks between the two domains and how they shape our planet.
In this study I aim to provide insight on two primary questions: 1) How do divergent and strike-slip plate boundaries evolve? 2) How is this evolution, on a large temporal scale and a smaller structural scale, affected by the alteration of the surface through erosion and deposition? This is done in three chapters that examine the evolution of divergent and strike-slip plate boundaries using numerical models. Chapter 2 takes a detailed look at the evolution of rift systems using two-dimensional models. Specifically, I extract faults from a range of rift models and correlate them through time to examine how fault networks evolve in space and time. By implementing a two-way coupling between the geodynamic code ASPECT and landscape evolution code FastScape, I investigate how the fault network and rift evolution are influenced by the system’s erosional efficiency, which represents many factors like lithology or climate. In Chapter 3, I examine rift evolution from a three-dimensional perspective. In this chapter I study linkage modes for offset rifts to determine when fast-rotating plate-boundary structures known as continental microplates form. Chapter 4 uses the two-way numerical coupling between tectonics and landscape evolution to investigate how a strike-slip boundary responds to large sediment loads, and whether this is sufficient to form an entirely new type of flexural strike-slip basin.
Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.
Controlling interactions in synthetic polymers as precisely as in proteins would have a strong impact on polymer science. Advanced structural and functional control can lead to rational design of, integrated nano- and microstructures. To achieve this, properties of monomer sequence defined oligopeptides were exploited. Through their incorporation as monodisperse segments into synthetic polymers we learned in recent four years how to program the structure formation of polymers, to adjust and exploit interactions in such polymers, to control inorganic-organic interfaces in fiber composites and induce structure in Biomacromolecules like DNA for biomedical applications.
Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vegetation phenology. This thesis explores the diversity and utility of dense TerraSAR-X (TSX) X-Band time series for monitoring ice-rich riverbank erosion, snowmelt, and phenology of Arctic vegetation at long-term study sites in the central Lena Delta, Russia and on Qikiqtaruk (Herschel Island), Canada. In the thesis the following three research questions are addressed:
• Is TSX time series capable of monitoring the dynamics of rapid permafrost degradation in ice-rich permafrost on an intra-seasonal scale and can these datasets in combination with climate data identify the climatic drivers of permafrost degradation?
• Can multi-pass and multi-polarized TSX time series adequately monitor seasonal snow cover and snowmelt in small Arctic catchments and how does it perform compared to optical satellite data and field-based measurements?
• Do TSX time series reflect the phenology of Arctic vegetation and how does the recorded signal compare to in-situ greenness data from RGB time-lapse camera data and vegetation height from field surveys?
To answer the research questions three years of TSX backscatter data from 2013 to 2015 for the Lena Delta study site and from 2015 to 2017 for the Qikiqtaruk study site were used in quantitative and qualitative analysis complimentary with optical satellite data and in-situ time-lapse imagery.
The dynamics of intra-seasonal ice-rich riverbank erosion in the central Lena Delta, Russia were quantified using TSX backscatter data at 2.4 m spatial resolution in HH polarization and validated with 0.5 m spatial resolution optical satellite data and field-based time-lapse camera data. Cliff top lines were automatically extracted from TSX intensity images using threshold-based segmentation and vectorization and combined in a geoinformation system with manually digitized cliff top lines from the optical satellite data and rates of erosion extracted from time-lapse cameras. The results suggest that the cliff top eroded at a constant rate throughout the entire erosional season. Linear mixed models confirmed that erosion was coupled with air temperature and precipitation at an annual scale, seasonal fluctuations did not influence 22-day erosion rates. The results highlight the potential of HH polarized X-Band backscatter data for high temporal resolution monitoring of rapid permafrost degradation.
The distinct signature of wet snow in backscatter intensity images of TSX data was exploited to generate wet snow cover extent (SCE) maps on Qikiqtaruk at high temporal resolution. TSX SCE showed high similarity to Landsat 8-derived SCE when using cross-polarized VH data. Fractional snow cover (FSC) time series were extracted from TSX and optical SCE and compared to FSC estimations from in-situ time-lapse imagery. The TSX products showed strong agreement with the in-situ data and significantly improved the temporal resolution compared to the Landsat 8 time series. The final combined FSC time series revealed two topography-dependent snowmelt patterns that corresponded to in-situ measurements. Additionally TSX was able to detect snow patches longer in the season than Landsat 8, underlining the advantage of TSX for detection of old snow. The TSX-derived snow information provided valuable insights into snowmelt dynamics on Qikiqtaruk previously not available.
The sensitivity of TSX to vegetation structure associated with phenological changes was explored on Qikiqtaruk. Backscatter and coherence time series were compared to greenness data extracted from in-situ digital time-lapse cameras and detailed vegetation parameters on 30 areas of interest. Supporting previous results, vegetation height corresponded to backscatter intensity in co-polarized HH/VV at an incidence angle of 31°. The dry, tall shrub dominated ecological class showed increasing backscatter with increasing greenness when using the cross polarized VH/HH channel at 32° incidence angle. This is likely driven by volume scattering of emerging and expanding leaves. Ecological classes with more prostrate vegetation and higher bare ground contributions showed decreasing backscatter trends over the growing season in the co-polarized VV/HH channels likely a result of surface drying instead of a vegetation structure signal. The results from shrub dominated areas are promising and provide a complementary data source for high temporal monitoring of vegetation phenology.
Overall this thesis demonstrates that dense time series of TSX with optical remote sensing and in-situ time-lapse data are complementary and can be used to monitor rapid and seasonal processes in Arctic landscapes at high spatial and temporal resolution.
There are two common approaches to implement a virtual machine (VM) for a dynamic object-oriented language. On the one hand, it can be implemented in a C-like language for best performance and maximum control over the resulting executable. On the other hand, it can be implemented in a language such as Java that allows for higher-level abstractions. These abstractions, such as proper object-oriented modularization, automatic memory management, or interfaces, are missing in C-like languages but they can simplify the implementation of prevalent but complex concepts in VMs, such as garbage collectors (GCs) or just-in-time compilers (JITs). Yet, the implementation of a dynamic object-oriented language in Java eventually results in two VMs on top of each other (double stack), which impedes performance. For statically typed languages, the Maxine VM solves this problem; it is written in Java but can be executed without a Java virtual machine (JVM). However, it is currently not possible to execute dynamic object-oriented languages in Maxine. This work presents an approach to bringing object models and execution models of dynamic object-oriented languages to the Maxine VM and the application of this approach to Squeak/Smalltalk. The representation of objects in and the execution of dynamic object-oriented languages pose certain challenges to the Maxine VM that lacks certain variation points necessary to enable an effortless and straightforward implementation of dynamic object-oriented languages' execution models. The implementation of Squeak/Smalltalk in Maxine as a feasibility study is to unveil such missing variation points.
Metals are often used in environments that are conducive to corrosion, which leads to a reduction in their mechanical properties and durability. Coatings are applied to corrosion-prone metals such as aluminum alloys to inhibit the destructive surface process of corrosion in a passive or active way. Standard anticorrosive coatings function as a physical barrier between the material and the corrosive environment and provide passive protection only when intact. In contrast, active protection prevents or slows down corrosion even when the main barrier is damaged. The most effective industrially used active corrosion inhibition for aluminum alloys is provided by chromate conversion coatings. However, their toxicity and worldwide restriction provoke an urgent need for finding environmentally friendly corrosion preventing systems. A promising approach to replace the toxic chromate coatings is to embed particles containing nontoxic inhibitor in a passive coating matrix. This work presents the development and optimization of effective anticorrosive coatings for the industrially important aluminum alloy, AA2024-T3 using this approach. The protective coatings were prepared by dispersing mesoporous silica containers, loaded with the nontoxic corrosion inhibitor 2-mercaptobenzothiazole, in a passive sol-gel (SiOx/ZrOx) or organic water-based layer. Two types of porous silica containers with different sizes (d ≈ 80 and 700 nm, respectively) were investigated. The studied robust containers exhibit high surface area (≈ 1000 m² g-1), narrow pore size distribution (dpore ≈ 3 nm) and large pore volume (≈ 1 mL g-1) as determined by N2 sorption measurements. These properties favored the subsequent adsorption and storage of a relatively large amount of inhibitor as well as its release in response to pH changes induced by the corrosion process. The concentration, position and size of the embedded containers were varied to ascertain the optimum conditions for overall anticorrosion performance. Attaining high anticorrosion efficiency was found to require a compromise between delivering an optimal amount of corrosion inhibitor and preserving the coating barrier properties. This study broadens the knowledge about the main factors influencing the coating anticorrosion efficiency and assists the development of optimum active anticorrosive coatings doped with inhibitor loaded containers.
Earthquake modeling is the key to a profound understanding of a rupture. Its kinematics or dynamics are derived from advanced rupture models that allow, for example, to reconstruct the direction and velocity of the rupture front or the evolving slip distribution behind the rupture front. Such models are often parameterized by a lattice of interacting sub-faults with many degrees of freedom, where, for example, the time history of the slip and rake on each sub-fault are inverted. To avoid overfitting or other numerical instabilities during a finite-fault estimation, most models are stabilized by geometric rather than physical constraints such as smoothing.
As a basis for the inversion approach of this study, we build on a new pseudo-dynamic rupture model (PDR) with only a few free parameters and a simple geometry as a physics-based solution of an earthquake rupture. The PDR derives the instantaneous slip from a given stress drop on the fault plane, with boundary conditions on the developing crack surface guaranteed at all times via a boundary element approach. As a side product, the source time function on each point on the rupture plane is not constraint and develops by itself without additional parametrization. The code was made publicly available as part of the Pyrocko and Grond Python packages. The approach was compared with conventional modeling for different earthquakes. For example, for the Mw 7.1 2016 Kumamoto, Japan, earthquake, the effects of geometric changes in the rupture surface on the slip and slip rate distributions could be reproduced by simply projecting stress vectors. For the Mw 7.5 2018 Palu, Indonesia, strike-slip earthquake, we also modelled rupture propagation using the 2D Eikonal equation and assuming a linear relationship between rupture and shear wave velocity. This allowed us to give a deeper and faster propagating rupture front and the resulting upward refraction as a new possible explanation for the apparent supershear observed at the Earth's surface.
The thesis investigates three aspects of earthquake inversion using PDR: (1) to test whether implementing a simplified rupture model with few parameters into a probabilistic Bayesian scheme without constraining geometric parameters is feasible, and whether this leads to fast and robust results that can be used for subsequent fast information systems (e.g., ground motion predictions). (2) To investigate whether combining broadband and strong-motion seismic records together with near-field ground deformation data improves the reliability of estimated rupture models in a Bayesian inversion. (3) To investigate whether a complex rupture can be represented by the inversion of multiple PDR sources and for what type of earthquakes this is recommended.
I developed the PDR inversion approach and applied the joint data inversions to two seismic sequences in different tectonic settings. Using multiple frequency bands and a multiple source inversion approach, I captured the multi-modal behaviour of the Mw 8.2 2021 South Sandwich subduction earthquake with a large, curved and slow rupturing shallow earthquake bounded by two faster and deeper smaller events. I could cross-validate the results with other methods, i.e., P-wave energy back-projection, a clustering analysis of aftershocks and a simple tsunami forward model.
The joint analysis of ground deformation and seismic data within a multiple source inversion also shed light on an earthquake triplet, which occurred in July 2022 in SE Iran. From the inversion and aftershock relocalization, I found indications for a vertical separation between the shallower mainshocks within the sedimentary cover and deeper aftershocks at the sediment-basement interface. The vertical offset could be caused by the ductile response of the evident salt layer to stress perturbations from the mainshocks.
The applications highlight the versatility of the simple PDR in probabilistic seismic source inversion capturing features of rather different, complex earthquakes. Limitations, as the evident focus on the major slip patches of the rupture are discussed as well as differences to other finite fault modeling methods.
The concepts of food deficit, hunger, undernourishment and food security are discussed. Axioms and indices for the assessment of nutrition of individuals and groups are suggested. Furthermore a measure for food aid donor performance is developed and applied to a sample of bilateral and multilateral donors providing food aid for African countries.
We demonstrate how the incentives of firms that partially own their suppliers or customers to foreclose rivals depend on how the partial owner can extract profits from the target (tunneling). Compared to a fully vertically integrated firm, a partial owner may obtain only a share of the target’s profit but influence the target’s strategy significantly. We show that the incentives for customer and input foreclosure can be higher, equal, or even lower with partial ownership than with a vertical merger, depending on how the protection of minority shareholders and transfer price regulations affect the scope for profit extraction.
Steep mountain channels are an important component of the fluvial system. On geological timescales, they shape mountain belts and counteract tectonic uplift by erosion. Their channels are strongly coupled to hillslopes and they are often the main source of sediment transported downstream to low-gradient rivers and to alluvial fans, where commonly settlements in mountainous areas are located. Hence, mountain streams are the cause for one of the main natural hazards in these regions. Due to climate change and a pronounced populating of mountainous regions the attention given to this threat is even growing. Although quantitative studies on sediment transport have significantly advanced our knowledge on measuring and calibration techniques we still lack studies of the processes within mountain catchments. Studies examining the mechanisms of energy and mass exchange on small temporal and spatial scales in steep streams remain sparse in comparison to low-gradient alluvial channels.
In the beginning of this doctoral project, a vast amount of experience and knowledge of a steep stream in the Swiss Prealps had to be consolidated in order to shape the principal aim of this research effort. It became obvious, that observations from within the catchment are underrepresented in comparison to experiments performed at the catchment’s outlet measuring fluxes and the effects of the transported material. To counteract this imbalance, an examination of mass fluxes within the catchment on the process scale was intended. Hence, this thesis is heavily based on direct field observations, which are generally rare in these environments in quantity and quality. The first objective was to investigate the coupling of the channel with surrounding hillslopes, the major sources of sediment. This research, which involved the monitoring of the channel and adjacent hillslopes, revealed that alluvial channel steps play a key role in coupling of channel and hillslopes. The observations showed that hillslope stability is strongly associated with the step presence and an understanding of step morphology and stability is therefore crucial in understanding sediment mobilization. This finding refined the way we think about the sediment dynamics in steep channels and motivated continued research of the step dynamics. However, soon it became obvious that the technological basis for developing field tests and analyzing the high resolution geometry measured in the field was not available. Moreover, for many geometrical quantities in mountain channels definitions and a clear scientific standard was not available. For example, these streams are characterized by a high spatial variability of the channel banks, preventing straightforward calculations of the channel width without a defined reference. Thus, the second and inevitable part of this thesis became the development and evaluation of scientific tools in order to investigate the geometrical content of the study reach thoroughly. The developed framework allowed the derivation of various metrics of step and channel geometry which facilitated research on the a large data set of observations of channel steps. In the third part, innovative, physically-based metrics have been developed and compared to current knowledge on step formation, suggested in the literature. With this analyses it could be demonstrated that the formation of channel steps follow a wide range of hydraulic controls. Due to the wide range of tested parameters channel steps observed in a natural stream were attributed to different mechanisms of step formation, including those based on jamming and those based on key-stones. This study extended our knowledge on step formation in a steep stream and harmonized different, often time seen as competing, processes of step formation. This study was based on observations collected at one point in time. In the fourth part of this project, the findings of the snap-shot observations were extended in the temporal dimension and the derived concepts have been utilized to investigate reach-scale step patterns in response to large, exceptional flood events. The preliminary results of this work based on the long-term analyses of 7 years of long profile surveys showed that the previously observed channel-hillslope mechanism is the responsible for the short-term response of step formation.
The findings of the long-term analyses of step patterns drew a bow to the initial observations of a channel-hillslope system which allowed to join the dots in the dynamics of steep stream. Thus, in this thesis a broad approach has been chosen to gain insights into the complex system of steep mountain rivers. The effort includes in situ field observations (article I), the development of quantitative scientific tools (article II), the reach-scale analyses of step-pool morphology (article III) and its temporal evolution (article IV). With this work our view on the processes within the catchment has been advanced towards a better mechanistic understanding of these fluvial system relevant to improve applied scientific work.
Functional nanoporous carbon-based materials derived from oxocarbon-metal coordination complexes
(2017)
Nanoporous carbon based materials are of particular interest for both science and industry due to their exceptional properties such as a large surface area, high pore volume, high electroconductivity as well as high chemical and thermal stability. Benefiting from these advantageous properties, nanoporous carbons proved to be useful in various energy and environment related applications including energy storage and conversion, catalysis, gas sorption and separation technologies. The synthesis of nanoporous carbons classically involves thermal carbonization of the carbon precursors (e.g. phenolic resins, polyacrylonitrile, poly(vinyl alcohol) etc.) followed by an activation step and/or it makes use of classical hard or soft templates to obtain well-defined porous structures. However, these synthesis strategies are complicated and costly; and make use of hazardous chemicals, hindering their application for large-scale production. Furthermore, control over the carbon materials properties is challenging owing to the relatively unpredictable processes at the high carbonization temperatures.
In the present thesis, nanoporous carbon based materials are prepared by the direct heat treatment of crystalline precursor materials with pre-defined properties. This synthesis strategy does not require any additional carbon sources or classical hard- or soft templates. The highly stable and porous crystalline precursors are based on coordination compounds of the squarate and croconate ions with various divalent metal ions including Zn2+, Cu2+, Ni2+, and Co2+, respectively. Here, the structural properties of the crystals can be controlled by the choice of appropriate synthesis conditions such as the crystal aging temperature, the ligand/metal molar ratio, the metal ion, and the organic ligand system. In this context, the coordination of the squarate ions to Zn2+ yields porous 3D cube crystalline particles. The morphology of the cubes can be tuned from densely packed cubes with a smooth surface to cubes with intriguing micrometer-sized openings and voids which evolve on the centers of the low index faces as the crystal aging temperature is raised. By varying the molar ratio, the particle shape can be changed from truncated cubes to perfect cubes with right-angled edges.
These crystalline precursors can be easily transformed into the respective carbon based materials by heat treatment at elevated temperatures in a nitrogen atmosphere followed by a facile washing step. The resulting carbons are obtained in good yields and possess a hierarchical pore structure with well-organized and interconnected micro-, meso- and macropores. Moreover, high surface areas and large pore volumes of up to 1957 m2 g-1 and 2.31 cm3 g-1 are achieved, respectively, whereby the macroscopic structure of the precursors is preserved throughout the whole synthesis procedure.
Owing to these advantageous properties, the resulting carbon based materials represent promising supercapacitor electrode materials for energy storage applications. This is exemplarily demonstrated by employing the 3D hierarchical porous carbon cubes derived from squarate-zinc coordination compounds as electrode material showing a specific capacitance of 133 F g-1 in H2SO4 at a scan rate of 5 mV s-1 and retaining 67% of this specific capacitance when the scan rate is increased to 200 mV s-1.
In a further application, the porous carbon cubes derived from squarate-zinc coordination compounds are used as high surface area support material and decorated with nickel nanoparticles via an incipient wetness impregnation. The resulting composite material combines a high surface area, a hierarchical pore structure with high functionality and well-accessible pores. Moreover, owing to their regular micro-cube shape, they allow for a good packing of a fixed-bed flow reactor along with high column efficiency and a minimized pressure drop throughout the packed reactor. Therefore, the composite is employed as heterogeneous catalyst in the selective hydrogenation of 5-hydroxymethylfurfural to 2,5-dimethylfuran showing good catalytic performance and overcoming the conventional problem of column blocking.
Thinking about the rational design of 3D carbon geometries, the functions and properties of the resulting carbon-based materials can be further expanded by the rational introduction of heteroatoms (e.g. N, B, S, P, etc.) into the carbon structures in order to alter properties such as wettability, surface polarity as well as the electrochemical landscape. In this context, the use of crystalline materials based on oxocarbon-metal ion complexes can open a platform of highly functional materials for all processes that involve surface processes.
An exhaustive and disjoint decomposition of social choice situations is derived in a general set theoretical framework using the new tools of the Lifted Pareto relation on the power set of social states representing a pre-choice comparison of choice option sets. The main result is the classification of social choice situations which include three types of social choice problems. First, we usually observe the common incompleteness of the Pareto relation. Second, a kind of non-compactness problem of a choice set of social states can be generated. Finally, both can be combined. The first problem root can be regarded as natural everyday dilemma of social choice theory whereas the second may probably be much more due to modeling technique implications. The distinction is enabled at a very general set theoretical level. Hence, the derived classification of social choice situations is applicable on almost every relevant economic model.
Salt deposits offer a variety of usage types. These include the mining of rock salt and potash salt as important raw materials, the storage of energy in man-made underground caverns, and the disposal of hazardous substances in former mines. The most serious risk with any of these usage types comes from the contact with groundwater or surface water. It causes an uncontrolled dissolution of salt rock, which in the worst case can result in the flooding or collapse of underground facilities. Especially along potash seams, cavernous structures can spread quickly, because potash salts show a much higher solubility than rock salt. However, as their chemical behavior is quite complex, previous models do not account for these highly soluble interlayers. Therefore, the objective of the present thesis is to describe the evolution of cavernous structures along potash seams in space and time in order to improve hazard mitigation during the utilization of salt deposits.
The formation of cavernous structures represents an interplay of chemical and hydraulic processes. Hence, the first step is to systematically investigate the dissolution and precipitation reactions that occur when water and potash salt come into contact. For this purpose, a geochemical reaction model is used. The results show that the minerals are only partially dissolved, resulting in a porous sponge like structure. With the saturation of the solution increasing, various secondary minerals are formed, whose number and type depend on the original rock composition. Field data confirm a correlation between the degree of saturation and the distance from the center of the cavern, where solution is entering. Subsequently, the reaction model is coupled with a flow and transport code and supplemented by a novel approach called ‘interchange’. The latter enables the exchange of solution and rock between areas of different porosity and mineralogy, and thus ultimately the growth of the cavernous structure. By means of several scenario analyses, cavern shape, growth rate and mineralogy are systematically investigated, taking also heterogeneous potash seams into account. The results show that basically four different cases can be distinguished, with mixed forms being a frequent occurrence in nature. The classification scheme is based on the dimensionless numbers Péclet and Damköhler, and allows for a first assessment of the hazard potential. In future, the model can be applied to any field case, using measurement data for calibration.
The presented research work provides a reactive transport model that is able to spatially and temporally characterize the propagation of cavernous structures along potash seams for the first time. Furthermore, it allows to determine thickness and composition of transition zones between cavern center and unaffected salt rock. The latter is particularly important in potash mining, so that natural cavernous structures can be located at an early stage and the risk of mine flooding can thus be reduced. The models may also contribute to an improved hazard prevention in the construction of storage caverns and the disposal of hazardous waste in salt deposits. Predictions regarding the characteristics and evolution of cavernous structures enable a better assessment of potential hazards, such as integrity or stability loss, as well as of suitable mitigation measures.
In this paper, we study the effect of exogenous global crop price changes on migration from agricultural and non-agricultural households in Sub-Saharan Africa. We show that, similar to the effect of positive local weather shocks, the effect of a locally-relevant global crop price increase on household out-migration depends on the initial household wealth. Higher international producer prices relax the budget constraint of poor agricultural households and facilitate migration. The order of magnitude of a standardized price effect is approx. one third of the standardized effect of a local weather shock. Unlike positive weather shocks, which mostly facilitate internal rural-urban migration, positive income shocks through rising producer prices only increase migration to neighboring African countries, likely due to the simultaneous decrease in real income in nearby urban areas. Finally, we show that while higher producer prices induce conflict, conflict does not play a role for the household decision to send a member as a labor migrant.
Indonesia is one of the countries most prone to natural hazards. Complex interaction of several tectonic plates with high relative velocities leads to approximately two earthquakes with magnitude Mw>7 every year, being more than 15% of the events worldwide. Earthquakes with magnitude above 9 happen far more infrequently, but with catastrophic effects. The most severe consequences thereby arise from tsunamis triggered by these subduction-related earthquakes, as the Sumatra-Andaman event in 2004 showed. In order to enable efficient tsunami early warning, which includes the estimation of wave heights and arrival times, it is necessary to combine different types of real-time sensor data with numerical models of earthquake sources and tsunami propagation. This thesis was created as a result of the GITEWS project (German Indonesian Tsunami Early Warning System). It is based on five research papers and manuscripts. Main project-related task was the development of a database containing realistic earthquake scenarios for the Sunda Arc. This database provides initial conditions for tsunami propagation modeling used by the simulation system at the early warning center. An accurate discretization of the subduction geometry, consisting of 25x150 subfaults was constructed based on seismic data. Green’s functions, representing the deformational response to unit dip- and strike slip at the subfaults, were computed using a layered half-space approach. Different scaling relations for earthquake dimensions and slip distribution were implemented. Another project-related task was the further development of the ‘GPS-shield’ concept. It consists of a constellation of near field GPS-receivers, which are shown to be very valuable for tsunami early warning. The major part of this thesis is related to the geophysical interpretation of GPS data. Coseismic surface displacements caused by the 2004 Sumatra earthquake are inverted for slip at the fault. The effect of different Earth layer models is tested, favoring continental structure. The possibility of splay faulting is considered and shown to be a secondary order effect in respect to tsunamigenity for this event. Tsunami models based on source inversions are compared to satellite radar altimetry observations. Postseismic GPS time series are used to test a wide parameter range of uni- and biviscous rheological models of the asthenosphere. Steady-state Maxwell rheology is shown to be incompatible with near-field GPS data, unless large afterslip, amounting to more than 10% of the coseismic moment is assumed. In contrast, transient Burgers rheology is in agreement with data without the need for large aseismic afterslip. Comparison to postseismic geoid observation by the GRACE satellites reveals that even with afterslip, the model implementing Maxwell rheology results in amplitudes being too small, and thus supports a biviscous asthenosphere. A simple approach based on the assumption of quasi-static deformation propagation is introduced and proposed for inversion of coseismic near-field GPS time series. Application of this approach to observations from the 2004 Sumatra event fails to quantitatively reconstruct the rupture propagation, since a priori conditions are not fulfilled in this case. However, synthetic tests reveal the feasibility of such an approach for fast estimation of rupturing properties.
Digitalisation in industry – also called “Industry 4.0” – is seen by numerous actors as an opportunity to reduce the environmental impact of the industrial sector. The scientific assessments of the effects of digitalisation in industry on environmental sustainability, however, are ambivalent. This cumulative dissertation uses three empirical studies to examine the expected and observed effects of digitalisation in industry on environmental sustainability. The aim of this dissertation is to identify opportunities and risks of digitalisation at different system levels and to derive options for action in politics and industry for a more sustainable design of digitalisation in industry. I use an interdisciplinary, socio-technical approach and look at selected countries of the Global South (Study 1) and the example of China (all studies). In the first study (section 2, joint work with Marcel Matthess), I use qualitative content analysis to examine digital and industrial policies from seven different countries in Africa and Asia for expectations regarding the impact of digitalisation on sustainability and compare these with the potentials of digitalisation for sustainability in the respective country contexts. The analysis reveals that the documents express a wide range of vague expectations that relate more to positive indirect impacts of information and communication technology (ICT) use, such as improved energy efficiency and resource management, and less to negative direct impacts of ICT, such as electricity consumption through ICT. In the second study (section 3, joint work with Marcel Matthess, Grischa Beier and Bing Xue), I conduct and analyse interviews with 18 industry representatives of the electronics industry from Europe, Japan and China on digitalisation measures in supply chains using qualitative content analysis. I find that while there are positive expectations regarding the effects of digital technologies on supply chain sustainability, their actual use and observable effects are still limited. Interview partners can only provide few examples from their own companies which show that sustainability goals have already been pursued through digitalisation of the supply chain or where sustainability effects, such as resource savings, have been demonstrably achieved. In the third study (section 4, joint work with Peter Neuhäusler, Melissa Dachrodt and Marcel Matthess), I conduct an econometric panel data analysis. I examine the relationship between the degree of Industry 4.0, energy consumption and energy intensity in ten manufacturing sectors in China between 2006 and 2019. The results suggest that overall, there is no significant relationship between the degree of Industry 4.0 and energy consumption or energy intensity in manufacturing sectors in China. However, differences can be found in subgroups of sectors. I find a negative correlation of Industry 4.0 and energy intensity in highly digitalised sectors, indicating an efficiency-enhancing effect of Industry 4.0 in these sectors. On the other hand, there is a positive correlation of Industry 4.0 and energy consumption for sectors with low energy consumption, which could be explained by the fact that digitalisation, such as the automation of previously mainly labour-intensive sectors, requires energy and also induces growth effects. In the discussion section (section 6) of this dissertation, I use the classification scheme of the three levels macro, meso and micro, as well as of direct and indirect environmental effects to classify the empirical observations into opportunities and risks, for example, with regard to the probability of rebound effects of digitalisation at the three levels. I link the investigated actor perspectives (policy makers, industry representatives), statistical data and additional literature across the system levels and consider political economy aspects to suggest fields of action for more sustainable (digitalised) industries. The dissertation thus makes two overarching contributions to the academic and societal discourse. First, my three empirical studies expand the limited state of research at the interface between digitalisation in industry and sustainability, especially by considering selected countries in the Global South and the example of China. Secondly, exploring the topic through data and methods from different disciplinary contexts and taking a socio-technical point of view, enables an analysis of (path) dependencies, uncertainties, and interactions in the socio-technical system across different system levels, which have often not been sufficiently considered in previous studies. The dissertation thus aims to create a scientifically and practically relevant knowledge basis for a value-guided, sustainability-oriented design of digitalisation in industry.
Biofilms are complex living materials that form as bacteria get embedded in a matrix of self-produced protein and polysaccharide fibres. The formation of a network of extracellular biopolymer fibres contributes to the cohesion of the biofilm by promoting cell-cell attachment and by mediating biofilm-substrate interactions. This sessile mode of bacteria growth has been well studied by microbiologists to prevent the detrimental effects of biofilms in medical and industrial settings. Indeed, biofilms are associated with increased antibiotic resistance in bacterial infections, and they can also cause clogging of pipelines or promote bio-corrosion. However, biofilms also gained interest from biophysics due to their ability to form complex morphological patterns during growth. Recently, the emerging field of engineered living materials investigates biofilm mechanical properties at multiple length scales and leverages the tools of synthetic biology to tune the functions of their constitutive biopolymers.
This doctoral thesis aims at clarifying how the morphogenesis of Escherichia coli (E. coli) biofilms is influenced by their growth dynamics and mechanical properties. To address this question, I used methods from cell mechanics and materials science. I first studied how biological activity in biofilms gives rise to non-uniform growth patterns. In a second study, I investigated how E. coli biofilm morphogenesis and its mechanical properties adapt to an environmental stimulus, namely the water content of their substrate. Finally, I estimated how the mechanical properties of E. coli biofilms are altered when the bacteria express different extracellular biopolymers.
On nutritive hydrogels, micron-sized E. coli cells can build centimetre-large biofilms. During this process, bacterial proliferation and matrix production introduce mechanical stresses in the biofilm, which release through the formation of macroscopic wrinkles and delaminated buckles. To relate these biological and mechanical phenomena, I used time-lapse fluorescence imaging to track cell and matrix surface densities through the early and late stages of E. coli biofilm growth. Colocalization of high cell and matrix densities at the periphery precede the onset of mechanical instabilities at this annular region. Early growth is detected at this outer annulus, which was analysed by adding fluorescent microspheres to the bacterial inoculum. But only when high rates of matrix production are present in the biofilm centre, does overall biofilm spreading initiate along the solid-air interface. By tracking larger fluorescent particles for a long time, I could distinguish several kinematic stages of E. coli biofilm expansion and observed a transition from non-linear to linear velocity profiles, which precedes the emergence of wrinkles at the biofilm periphery. Decomposing particle velocities to their radial and circumferential components revealed a last kinematic stage, where biofilm movement is mostly directed towards the radial delaminated buckles, which verticalize. The resulting compressive strains computed in these regions were observed to substantially deform the underlying agar substrates. The co-localization of higher cell and matrix densities towards an annular region and the succession of several kinematic stages are thus expected to promote the emergence of mechanical instabilities at the biofilm periphery. These experimental findings are predicted to advance future modelling approaches of biofilm morphogenesis.
E. coli biofilm morphogenesis is further anticipated to depend on external stimuli from the environment. To clarify how the water could be used to tune biofilm material properties, we quantified E. coli biofilm growth, wrinkling dynamics and rigidity as a function of the water content of the nutritive substrates. Time-lapse microscopy and computational image analysis revealed that substrates with high water content promote biofilm spreading kinetics, while substrates with low water content promote biofilm wrinkling. The wrinkles observed on biofilm cross-sections appeared more bent on substrates with high water content, while they tended to be more vertical on substrates with low water content. Both wet and dry biomass, accumulated over 4 days of culture, were larger in biofilms cultured on substrates with high water content, despite extra porosity within the matrix layer. Finally, the micro-indentation analysis revealed that substrates with low water content supported the formation of stiffer biofilms. This study shows that E. coli biofilms respond to the water content of their substrate, which might be used for tuning their material properties in view of further applications.
Biofilm material properties further depend on the composition and structure of the matrix of extracellular proteins and polysaccharides. In particular, E. coli biofilms were suggested to present tissue-like elasticity due to a dense fibre network consisting of amyloid curli and phosphoethanolamine-modified cellulose. To understand the contribution of these components to the emergent mechanical properties of E. coli biofilms, we performed micro-indentation on biofilms grown from bacteria of several strains. Besides showing higher dry masses, larger spreading diameters and slightly reduced water contents, biofilms expressing both main matrix components also presented high rigidities in the range of several hundred kPa, similar to biofilms containing only curli fibres. In contrast, a lack of amyloid curli fibres provides much higher adhesive energies and more viscoelastic fluid-like material behaviour. Therefore, the combination of amyloid curli and phosphoethanolamine-modified cellulose fibres implies the formation of a composite material whereby the amyloid curli fibres provide rigidity to E. coli biofilms, whereas the phosphoethanolamine-modified cellulose rather acts as a glue. These findings motivate further studies involving purified versions of these protein and polysaccharide components to better understand how their interactions benefit biofilm functions.
All three studies depict different aspects of biofilm morphogenesis, which are interrelated. The first work reveals the correlation between non-uniform biological activities and the emergence of mechanical instabilities in the biofilm. The second work acknowledges the adaptive nature of E. coli biofilm morphogenesis and its mechanical properties to an environmental stimulus, namely water. Finally, the last study reveals the complementary role of the individual matrix components in the formation of a stable biofilm material, which not only forms complex morphologies but also functions as a protective shield for the bacteria it contains. Our experimental findings on E. coli biofilm morphogenesis and their mechanical properties can have further implications for fundamental and applied biofilm research fields.
We investigate numerically the appearance of heteroclinic behavior in a three-dimensional, buoyancy-driven fluid layer with stress-free top and bottom boundaries, a square horizontal periodicity with a small aspect ratio, and rotation at low to moderate rates about a vertical axis. The Prandtl number is 6.8. If the rotation is not too slow, the skewed-varicose instability leads from stationary rolls to a stationary mixed-mode solution, which in turn loses stability to a heteroclinic cycle formed by unstable roll states and connections between them. The unstable eigenvectors of these roll states are also of the skewed-varicose or mixed-mode type and in some parameter regions skewed-varicose like shearing oscillations as well as square patterns are involved in the cycle. Always present weak noise leads to irregular horizontal translations of the convection pattern and makes the dynamics chaotic, which is verified by calculating Lyapunov exponents. In the nonrotating case, the primary rolls lose, depending on the aspect ratio, stability to traveling waves or a stationary square pattern. We also study the symmetries of the solutions at the intermittent fixed points in the heteroclinic cycle.
The papers in this volume were presented at the workshop Heterogeneity in Linguistic Databases', which took place on July 9, 2004 at the University of Potsdam. The workshop was organized by project D1: Linguistic Database for Information Structure: Annotation and Retrieval', a member project of the SFB 632, a collaborative research center entitled Information Structure: the Linguistic Means for Structuring Utterances, Sentences and Texts'. The workshop brought together both developers and users of linguistic databases from a number of research projects which work on an empirical basis, all of which have to cope with different sorts of heterogeneity: primary linguistic data and annotated information may be heterogeneous, as well as the data structures representing them. The first four papers (by Wagner, Schmidt, Lüdeling, and Witt) address aspects of heterogeneous data from the point of view of database developers; the remaining three papers (by Meyer, Smith, and Teich/Fankhauser) focus on data exploitation by the users.
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.
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
In light of climate change mitigation efforts, revenues from climate policies are growing, with no consensus yet on how they should be used. Potential efficiency gains from reducing distortionary taxes and the distributional implications of different revenue recycling schemes are currently debated. To account for households heterogeneity and dynamic trade-offs, we study the macroeconomic and welfare performance of different revenue recycling schemes using an Environmental Two-Agent New-Keynesian model, calibrated on the German economy. We find that, in the long run, welfare gains are higher when revenues are used to reduce distortionary taxes on capital, but this comes at the cost of higher inequality: while all households prefer labor income tax reductions to lump-sum transfers, only financially unconstrained households are better off when reducing taxes on capital income. Interestingly, we find that over the transition period relevant to meet short-medium run climate targets, labor income tax cuts are the most efficient and equitable instrument.
Hydraulic-driven fractures play a key role in subsurface energy technologies across several scales. By injecting fluid at high hydraulic pressure into rock with intrinsic low permeability, in-situ stress field and fracture development pattern can be characterised as well as rock permeability can be enhanced. Hydraulic fracturing is a commercial standard procedure for enhanced oil and gas production of rock reservoirs with low permeability in petroleum industry. However, in EGS utilization, a major geological concern is the unsolicited generation of earthquakes due to fault reactivation, referred to as induced seismicity, with a magnitude large enough to be felt on the surface or to damage facilities and buildings. Furthermore, reliable interpretation of hydraulic fracturing tests for stress measurement is a great challenge for the energy technologies. Therefore, in this cumulative doctoral thesis the following research questions are investigated. (1): How do hydraulic fractures grow in hard rock at various scales?; (2): Which parameters control hydraulic fracturing and hydro-mechanical coupling?; and (3): How can hydraulic fracturing in hard rock be modelled?
In the laboratory scale study, several laboratory hydraulic fracturing experiments are investigated numerically using Irazu2D that were performed on intact cubic Pocheon granite samples from South Korea applying different injection protocols. The goal of the laboratory experiments is to test the concept of cyclic soft stimulation which may enable sustainable permeability enhancement (Publication 1).
In the borehole scale study, hydraulic fracturing tests are reported that were performed in boreholes located in central Hungary to determine the in-situ stress for a geological site investigation. At depth of about 540 m, the recorded pressure versus time curves in mica schist with low dip angle foliation show atypical evolution. In order to provide explanation for this observation, a series of discrete element computations using Particle Flow Code 2D are performed (Publication 2).
In the reservoir scale study, the hydro-mechanical behaviour of fractured crystalline rock due to one of the five hydraulic stimulations at the Pohang Enhanced Geothermal site in South Korea is studied. Fluid pressure perturbation at faults of several hundred-meter lengths during hydraulic stimulation is simulated using FracMan (Publication 3).
The doctoral research shows that the resulting hydraulic fracturing geometry will depend “locally”, i.e. at the length scale of representative elementary volume (REV) and below that (sub-REV), on the geometry and strength of natural fractures, and “globally”, i.e. at super-REV domain volume, on far-field stresses. Regarding hydro-mechanical coupling, it is suggested to define separate coupling relationship for intact rock mass and natural fractures. Furthermore, the relative importance of parameters affecting the magnitude of formation breakdown pressure, a parameter characterising hydro-mechanical coupling, is defined. It can be also concluded that there is a clear gap between the capacity of the simulation software and the complexity of the studied problems. Therefore, the computational time of the simulation of complex hydraulic fracture geometries must be reduced while maintaining high fidelity simulation results. This can be achieved either by extending the computational resources via parallelization techniques or using time scaling techniques. The ongoing development of used numerical models focuses on tackling these methodological challenges.
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation
(2019)
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed:
• Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases?
• How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations?
• How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization?
To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis Program (EnMAP) satellite reflectance spectra from ground-based reflectance spectra as well as simulations of EnMAP imagery from aerial hyperspectral imagery were also obtained.
Results showed that canopy-level spectral variability within and between vegetation communities differed by phenological phase. The late season was identified as the most discriminative for identifying many dominant vegetation communities using both ground-based and simulated hyperspectral reflectance spectra. This was due to an overall reduction in spectral variability and comparable or greater differences in spectral reflectance between vegetation communities in the visible near infrared spectrum.
Red, green, and blue (RGB) indices extracted from nadir digital photographs and pigment-driven vegetation indices extracted from ground-based spectral measurements showed strong significant relationships. RGB indices also showed moderate relationships with chlorophyll and carotenoid pigment concentrations. The observed relationships with the broadband RGB channels of the digital camera indicate that vegetation colour strongly influences the response of pigment-driven spectral indices and digital cameras can track the seasonal development and degradation of photosynthetic pigments.
Spatial aggregation of hyperspectral data from the ground to airborne, to simulated satel-lite scale was influenced by non-photosynthetic components as demonstrated by the distinct shift of the red edge to shorter wavelengths. Correspondence between spectral reflectance at the three scales was highest in the red spectrum and lowest in the near infra-red. By artificially mixing litter spectra at different proportions to ground-based spectra, correspondence with aerial and satellite spectra increased. Greater proportions of litter were required to achieve correspondence at the satellite scale.
Overall this thesis found that integrating multiple temporal, spectral, and spatial data is necessary to monitor the complexity and heterogeneity of Arctic tundra ecosystems. The identification of spectrally similar vegetation communities can be optimized using non-peak season hyperspectral data leading to more detailed identification of vegetation communities. The results also highlight the power of vegetation colour to link ground-based and satellite data. Finally, a detailed characterization non-photosynthetic ecosystem components is crucial for accurate interpretation of vegetation signals at landscape scales.
Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool “E.V.A.” is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.
Enhanced geothermal systems (EGS) are considered a cornerstone of future sustainable energy production. In such systems, high-pressure fluid injections break the rock to provide pathways for water to circulate in and heat up. This approach inherently induces small seismic events that, in rare cases, are felt or can even cause damage. Controlling and reducing the seismic impact of EGS is crucial for a broader public acceptance. To evaluate the applicability of hydraulic fracturing (HF) in EGS and to improve the understanding of fracturing processes and the hydromechanical relation to induced seismicity, six in-situ, meter-scale HF experiments with different injection schemes were performed under controlled conditions in crystalline rock in a depth of 410 m at the Äspö Hard Rock Laboratory (Sweden).
I developed a semi-automated, full-waveform-based detection, classification, and location workflow to extract and characterize the acoustic emission (AE) activity from the continuous recordings of 11 piezoelectric AE sensors. Based on the resulting catalog of 20,000 AEs, with rupture sizes of cm to dm, I mapped and characterized the fracture growth in great detail. The injection using a novel cyclic injection scheme (HF3) had a lower seismic impact than the conventional injections. HF3 induced fewer AEs with a reduced maximum magnitude and significantly larger b-values, implying a decreased number of large events relative to the number of small ones. Furthermore, HF3 showed an increased fracture complexity with multiple fractures or a fracture network. In contrast, the conventional injections developed single, planar fracture zones (Publication 1).
An independent, complementary approach based on a comparison of modeled and observed tilt exploits transient long-period signals recorded at the horizontal components of two broad-band seismometers a few tens of meters apart from the injections. It validated the efficient creation of hydraulic fractures and verified the AE-based fracture geometries. The innovative joint analysis of AEs and tilt signals revealed different phases of the fracturing process, including the (re-)opening, growth, and aftergrowth of fractures, and provided evidence for the reactivation of a preexisting fault in one of the experiments (Publication 2). A newly developed network-based waveform-similarity analysis applied to the massive AE activity supports the latter finding.
To validate whether the reduction of the seismic impact as observed for the cyclic injection schemes during the Äspö mine-scale experiments is transferable to other scales, I additionally calculated energy budgets for injection experiments from previously conducted laboratory tests and from a field application. Across all three scales, the cyclic injections reduce the seismic impact, as depicted by smaller maximum magnitudes, larger b-values, and decreased injection efficiencies (Publication 3).
The trace gases CO2 and CH4 pertain to the most relevant greenhouse gases and are important exchange fluxes of the global carbon (C) cycle. Their atmospheric quantity increased significantly as a result of the intensification of anthropogenic activities, such as especially land-use and land-use change, since the mid of the 18th century. To mitigate global climate change and ensure food security, land-use systems need to be developed, which favor reduced trace gas emissions and a sustainable soil carbon management. This requires the accurate and precise quantification of the influence of land-use and land-use change on CO2 and CH4 emissions. A common method to determine the trace gas dynamics and C sink or source function of a particular ecosystem is the closed chamber method. This method is often used assuming that accuracy and precision are high enough to determine differences in C gas emissions for e.g., treatment comparisons or different ecosystem components.
However, the broad range of different chamber designs, related operational procedures and data-processing strategies which are described in the scientific literature contribute to the overall uncertainty of closed chamber-based emission estimates. Hence, the outcomes of meta-analyses are limited, since these methodical differences hamper the comparability between studies. Thus, a standardization of closed chamber data acquisition and processing is much-needed.
Within this thesis, a set of case studies were performed to: (I) develop standardized routines for an unbiased data acquisition and processing, with the aim of providing traceable, reproducible and comparable closed chamber based C emission estimates; (II) validate those routines by comparing C emissions derived using closed chambers with independent C emission estimates; and (III) reveal processes driving the spatio-temporal dynamics of C emissions by developing (data processing based) flux separation approaches.
The case studies showed: (I) the importance to test chamber designs under field conditions for an appropriate sealing integrity and to ensure an unbiased flux measurement. Compared to the sealing integrity, the use of a pressure vent and fan was of minor importance, affecting mainly measurement precision; (II) that the developed standardized data processing routines proved to be a powerful and flexible tool to estimate C gas emissions and that this tool can be successfully applied on a broad range of flux data sets from very different ecosystem; (III) that automatic chamber measurements display temporal dynamics of CO2 and CH4 fluxes very well and most importantly, that they accurately detect small-scale spatial differences in the development of soil C when validated against repeated soil inventories; and (IV) that a simple algorithm to separate CH4 fluxes into ebullition and diffusion improves the identification of environmental drivers, which allows for an accurate gap-filling of measured CH4 fluxes.
Overall, the proposed standardized data acquisition and processing routines strongly improved the detection accuracy and precision of source/sink patterns of gaseous C emissions. Hence, future studies, which consider the recommended improvements, will deliver valuable new data and insights to broaden our understanding of spatio-temporal C gas dynamics, their particular environmental drivers and underlying processes.
We consider a system of infinitely many hard balls in R<sup>d undergoing Brownian motions and submitted to a smooth pair potential. It is modelized by an infinite-dimensional stochastic differential equation with a local time term. We prove that the set of all equilibrium measures, solution of a detailed balance equation, coincides with the set of canonical Gibbs measures associated to the hard core potential added to the smooth interaction potential.
The International Conference on Informatics in Schools: Situation, Evolution and Perspectives – ISSEP – is a forum for researchers and practitioners in the area of Informatics education, both in primary and secondary schools. It provides an opportunity for educators to reflect upon the goals and objectives of this subject, its curricula and various teaching/learning paradigms and topics, possible connections to everyday life and various ways of establishing Informatics Education in schools. This conference also cares about teaching/learning materials, various forms of assessment, traditional and innovative educational research designs, Informatics’ contribution to the preparation of children for the 21st century, motivating competitions, projects and activities supporting informatics education in school.
The increasing demand for energy in the current technological era and the recent political decisions about giving up on nuclear energy diverted humanity to focus on alternative environmentally friendly energy sources like solar energy. Although silicon solar cells are the product of a matured technology, the search for highly efficient and easily applicable materials is still ongoing. These properties made the efficiency of halide perovskites comparable with silicon solar cells for single junctions within a decade of research. However, the downside of halide perovskites are poor stability and lead toxicity for the most stable ones.
On the other hand, chalcogenide perovskites are one of the most promising absorber materials for the photovoltaic market, due to their elemental abundance and chemical stability against moisture and oxygen. In the search of the ultimate solar absorber material, combining the good optoelectronic properties of halide perovskites with the stability of chalcogenides could be the promising candidate.
Thus, this work investigates new techniques for the synthesis and design of these novel chalcogenide perovskites, that contain transition metals as cations, e.g., BaZrS3, BaHfS3, EuZrS3, EuHfS3 and SrHfS3. There are two stages in the deposition techniques of this study: In the first stage, the binary compounds are deposited via a solution processing method. In the second stage, the deposited materials are annealed in a chalcogenide atmosphere to form the perovskite structure by using solid-state reactions.
The research also focuses on the optimization of a generalized recipe for a molecular ink to deposit precursors of chalcogenide perovskites with different binaries. The implementation of the precursor sulfurization resulted in either binaries without perovskite formation or distorted perovskite structures, whereas some of these materials are reported in the literature as they are more favorable in the needle-like non-perovskite configuration.
Lastly, there are two categories for the evaluation of the produced materials: The first category is about the determination of the physical properties of the deposited layer, e.g., crystal structure, secondary phase formation, impurities, etc. For the second category, optoelectronic properties are measured and compared to an ideal absorber layer, e.g., band gap, conductivity, surface photovoltage, etc.
Interdisciplinary studies on information structure : ISIS ; working papers of the SFB 632. - Vol. 1
(2004)
Contents: A1: Phonology and syntax of focussing and topicalisation: Gisbert Fanselow: Cyclic Phonology–Syntax-Interaction: Movement to First Position in German Caroline Féry and Laura Herbst: German Sentence Accent Revisited Shinichiro Ishihara: Prosody by Phase: Evidence from Focus Intonation–Wh-scope Correspondence in Japanese A2: Quantification and information structure: Cornelia Endriss and Stefan Hinterwimmer: The Influence of Tense in Adverbial Quantification A3: Rhetorical Structure in Spoken Language: Modeling of Global Prosodic Parameters: Ekaterina Jasinskaja, Jörg Mayer and David Schlangen: Discourse Structure and Information Structure: Interfaces and Prosodic Realization B2: Focussing in African Tchadic languages: Katharina Hartmann and Malte Zimmermann: Focus Strategies in Chadic: The Case of Tangale Revisited D1: Linguistic database for information structure: Annotation and retrieval: Stefanie Dipper, Michael Götze, Manfred Stede and Tillmann Wegst: ANNIS: A Linguistic Database for Exploring Information Structure
Earth's climate varies continuously across space and time, but humankind has witnessed only a small snapshot of its entire history, and instrumentally documented it for a mere 200 years. Our knowledge of past climate changes is therefore almost exclusively based on indirect proxy data, i.e. on indicators which are sensitive to changes in climatic variables and stored in environmental archives. Extracting the data from these archives allows retrieval of the information from earlier times. Obtaining accurate proxy information is a key means to test model predictions of the past climate, and only after such validation can the models be used to reliably forecast future changes in our warming world. The polar ice sheets of Greenland and Antarctica are one major climate archive, which record information about local air temperatures by means of the isotopic composition of the water molecules embedded in the ice. However, this temperature proxy is, as any indirect climate data, not a perfect recorder of past climatic variations. Apart from local air temperatures, a multitude of other processes affect the mean and variability of the isotopic data, which hinders their direct interpretation in terms of climate variations. This applies especially to regions with little annual accumulation of snow, such as the Antarctic Plateau. While these areas in principle allow for the extraction of isotope records reaching far back in time, a strong corruption of the temperature signal originally encoded in the isotopic data of the snow is expected. This dissertation uses observational isotope data from Antarctica, focussing especially on the East Antarctic low-accumulation area around the Kohnen Station ice-core drilling site, together with statistical and physical methods, to improve our understanding of the spatial and temporal isotope variability across different scales, and thus to enhance the applicability of the proxy for estimating past temperature variability. The presented results lead to a quantitative explanation of the local-scale (1–500 m) spatial variability in the form of a statistical noise model, and reveal the main source of the temporal variability to be the mixture of a climatic seasonal cycle in temperature and the effect of diffusional smoothing acting on temporally uncorrelated noise. These findings put significant limits on the representativity of single isotope records in terms of local air temperature, and impact the interpretation of apparent cyclicalities in the records. Furthermore, to extend the analyses to larger scales, the timescale-dependency of observed Holocene isotope variability is studied. This offers a deeper understanding of the nature of the variations, and is crucial for unravelling the embedded true temperature variability over a wide range of timescales.
The NAC transcription factor (TF) JUNGBRUNNEN1 (JUB1) is an important negative regulator of plant senescence, as well as of gibberellic acid (GA) and brassinosteroid (BR) biosynthesis in Arabidopsis thaliana. Overexpression of JUB1 promotes longevity and enhances tolerance to drought and other abiotic stresses. A similar role of JUB1 has been observed in other plant species, including tomato and banana. Our data show that JUB1 overexpressors (JUB1-OXs) accumulate higher levels of proline than WT plants under control conditions, during the onset of drought stress, and thereafter. We identified that overexpression of JUB1 induces key proline biosynthesis and suppresses key proline degradation genes. Furthermore, bZIP63, the transcription factor involved in proline metabolism, was identified as a novel downstream target of JUB1 by Yeast One-Hybrid (Y1H) analysis and Chromatin immunoprecipitation (ChIP). However, based on Electrophoretic Mobility Shift Assay (EMSA), direct binding of JUB1 to bZIP63 could not be confirmed. Our data indicate that JUB1-OX plants exhibit reduced stomatal conductance under control conditions. However, selective overexpression of JUB1 in guard cells did not improve drought stress tolerance in Arabidopsis. Moreover, the drought-tolerant phenotype of JUB1 overexpressors does not solely depend on the transcriptional control of the DREB2A gene. Thus, our data suggest that JUB1 confers tolerance to drought stress by regulating multiple components. Until today, none of the previous studies on JUB1´s regulatory network focused on identifying protein-protein interactions. We, therefore, performed a yeast two-hybrid screen (Y2H) which identified several protein interactors of JUB1, two of which are the calcium-binding proteins CaM1 and CaM4. Both proteins interact with JUB1 in the nucleus of Arabidopsis protoplasts. Moreover, JUB1 is expressed with CaM1 and CaM4 under the same conditions. Since CaM1.1 and CaM4.1 encode proteins with identical amino acid sequences, all further experiments were performed with constructs involving the CaM4 coding sequence. Our data show that JUB1 harbors multiple CaM-binding sites, which are localized in both the N-terminal and C-terminal regions of the protein. One of the CaM-binding sites, localized in the DNA-binding domain of JUB1, was identified as a functional CaM-binding site since its mutation strongly reduced the binding of CaM4 to JUB1. Furthermore, JUB1 transactivates expression of the stress-related gene DREB2A in mesophyll cells; this effect is significantly reduced when the calcium-binding protein CaM4 is expressed as well. Overexpression of both genes in Arabidopsis results in early senescence observed through lower chlorophyll content and an enhanced expression of senescence-associated genes (SAGs) when compared with single JUB1 overexpressors. Our data also show that JUB1 and CaM4 proteins interact in senescent leaves, which have increased Ca2+ levels when compared to young leaves. Collectively, our data indicate that JUB1 activity towards its downstream targets is fine-tuned by calcium-binding proteins during leaf senescence.
KEYCIT 2014
(2015)
In our rapidly changing world it is increasingly important not only to be an expert in a chosen field of study but also to be able to respond to developments, master new approaches to solving problems, and fulfil changing requirements in the modern world and in the job market. In response to these needs key competencies in understanding, developing and using new digital technologies are being brought into focus in school and university programmes. The IFIP TC3 conference "KEYCIT – Key Competences in Informatics and ICT (KEYCIT 2014)" was held at the University of Potsdam in Germany from July 1st to 4th, 2014 and addressed the combination of key competencies, Informatics and ICT in detail. The conference was organized into strands focusing on secondary education, university education and teacher education (organized by IFIP WGs 3.1 and 3.3) and provided a forum to present and to discuss research, case studies, positions, and national perspectives in this field.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
Sediment records of three European lakes were investigated in order to reconstruct the regional climate development during the Lateglacial and Holocene, to investigate the response of local ecosystems to climatic fluctuations and human impact and to relate regional peculiarities of past climate development to climatic changes on a larger spatial scale. The Lake Hańcza (NE Poland) sediment record was studied with a focus on reconstructing the early Holocene climate development and identifying possible differences to Western Europe. Following the initial Holocene climatic improvement, a further climatic improvement occurred between 10 000 and 9000 cal. a BP. Apparently, relatively cold and dry climate conditions persisted in NE Poland during the first ca. 1500 years of the Holocene, most likely due to a specific regional atmospheric circulation pattern. Prevailing anticyclonic circulation linked to a high-pressure cell above the remaining Scandinavian Ice Sheet (SIS) might have blocked the eastward propagation of warm and moist Westerlies and thus attenuated the early Holocene climatic amelioration in this region until the final decay of the SIS, a pattern different from climate development in Western Europe. The Lateglacial sediment record of Lake Mondsee (Upper Austria) was investigated in order to study the regional climate development and the environmental response to rapid climatic fluctuations. While the temperature rise and environmental response at the onset of the Holocene took place quasi-synchronously, major leads and lags in proxy responses characterize the onset of the Lateglacial Interstadial. In particular, the spread of coniferous woodlands and the reduction of detrital flux lagged the initial Lateglacial warming by ca. 500–750 years. Major cooling at the onset of the Younger Dryas took place synchronously with a change in vegetation, while the increase of detrital matter flux was delayed by about 150–300 years. Complex proxy responses are also detected for short-term Lateglacial climatic fluctuations. In summary, periods of abrupt climatic changes are characterized by complex and temporally variable proxy responses, mainly controlled by ecosystem inertia and the environmental preconditions. A second study on the Lake Mondsee sediment record focused on two small-scale climate deteriorations around 8200 and 9100 cal. a BP, which have been triggered by freshwater discharges to the North Atlantic, causing a shutdown of the Atlantic meridional overturning circulation (MOC). Combining microscopic varve counting and AMS 14C dating yielded a precise duration estimate (ca. 150 years) and absolute dating of the 8.2 ka cold event, both being in good agreement with results from other palaeoclimate records. Moreover, a sudden temperature overshoot after the 8.2 ka cold event was identified, also seen in other proxy records around the North Atlantic. This was most likely caused by enhanced resumption of the MOC, which also initiated substantial shifts of oceanic and atmospheric front systems. Although there is also evidence from other proxy records for pronounced recovery of the MOC and atmospheric circulation changes after the 9.1 ka cold event, no temperature overshoot is seen in the Lake Mondsee record, indicating the complex behaviour of the global climate system. The Holocene sediment record of Lake Iseo (northern Italy) was studied to shed light on regional earthquake activity and the influence of climate variability and anthropogenic impact on catchment erosion and detrital flux into the lake. Frequent small-scale detrital layers within the sediments reflect allochthonous sediment supply by extreme surface runoff events. During the early to mid-Holocene, increased detrital flux coincides with periods of cold and wet climate conditions, thus apparently being mainly controlled by climate variability. In contrast, intervals of high detrital flux during the late Holocene partly also correlate with phases of increased human impact, reflecting the complex influences on catchment erosion processes. Five large-scale event layers within the sediments, which are composed of mass-wasting deposits and turbidites, are supposed to have been triggered by strong local earthquakes. While the uppermost of these event layers is assigned to a documented adjacent earthquake in AD 1222, the four other layers are supposed to be related to previously undocumented prehistorical earthquakes.
The development of novel programmable materials aiming to control friction in real-time holds potential to facilitate innovative lubrication solutions for reducing wear and energy losses. This work describes the integration of light-responsiveness into two lubricating materials, silicon oils and polymer brush surfaces.
The first part focusses on the assessment on 9-anthracene ester-terminated polydimethylsiloxanes (PDMS-A) and, in particular, on the variability of rheological properties and the implications that arise with UV-light as external trigger. The applied rheometer setup contains an UV-transparent quartz-plate, which enables radiation and simultaneous measurement of the dynamic moduli. UV-A radiation (354 nm) triggers the cycloaddition reaction between the terminal functionalities of linear PDMS, resulting in chain extension. The newly-formed anthracene dimers cleave by UV-C radiation (254 nm) or at elevated temperatures (T > 130 °C). The sequential UV-A radiation and thermal reprogramming over three cycles demonstrate high conversions and reproducible programming of rheological properties. In contrast, the photochemical back reaction by UV-C is incomplete and can only partially restore the initial rheological properties. The dynamic moduli increase with each cycle in photochemical programming, presumably resulting from a chain segment re-arrangement as a result of the repeated partial photocleavage and subsequent chain length-dependent dimerization. In addition, long periods of radiation cause photooxidative degradation, which damages photo-responsive functions and consequently reduces the programming range. The absence of oxygen, however, reduces undesired side reactions. Anthracene-functionalized PDMS and native PDMS mix depending on the anthracene ester content and chain length, respectively, and allow fine-tuning of programmable rheological properties. The work shows the influence of mixing conditions during the photoprogramming step on the rheological properties, indicating that material property gradients induced by light attenuation along the beam have to be considered. Accordingly, thin lubricant films are suggested as potential application for light-programmable silicon fluids.
The second part compares strategies for the grafting of spiropyran (SP) containing copolymer brushes from Si wafers and evaluates the light-responsiveness of the surfaces. Pre-experiments on the kinetics of the thermally initiated RAFT copolymerization of 2-hydroxyethyl acrylate (HEA) and spiropyran acrylate (SPA) in solution show, first, a strong retardation by SP and, second, the dependence of SPA polymerization on light. Surprisingly, the copolymerization of SPA is inhibited in the dark. These findings contribute to improve the synthesis of polar, spiropyran-containing copolymers. The comparison between initiator systems for the grafting-from approach indicates PET-RAFT superior to thermally initiated RAFT, suggesting a more efficient initiation of surface-bound CTA by light. Surface-initiated polymerization via PET-RAFT with an initiator system of EosinY (EoY) and ascorbic acid (AscA) facilitates copolymer synthesis from HEA and 5-25 mol% SPA. The resulting polymer film with a thickness of a few nanometers was detected by atomic force microscopy (AFM) and ellipsometry. Water contact angle (CA) measurements demonstrate photo-switchable surface polarity, which is attributed to the photoisomerization between non-polar spiropyran and zwitterionic merocyanine isomer. Furthermore, the obtained spiropyran brushes show potential for further studies on light-programmable properties. In this context, it would be interesting to investigate whether swollen spiropyran-containing polymers change their configuration and thus their film thickness under the influence of light. In addition, further experiments using an AFM or microtribometer should evaluate whether light-programmable solvation enables a change in frictional properties between polymer brush surfaces.
In the context of ecological risk assessment of chemicals, individual-based population models hold great potential to increase the ecological realism of current regulatory risk assessment procedures. However, developing and parameterizing such models is time-consuming and often ad hoc. Using standardized, tested submodels of individual organisms would make individual-based modelling more efficient and coherent. In this thesis, I explored whether Dynamic Energy Budget (DEB) theory is suitable for being used as a standard submodel in individual-based models, both for ecological risk assessment and theoretical population ecology. First, I developed a generic implementation of DEB theory in an individual-based modeling (IBM) context: DEB-IBM. Using the DEB-IBM framework I tested the ability of the DEB theory to predict population-level dynamics from the properties of individuals. We used Daphnia magna as a model species, where data at the individual level was available to parameterize the model, and population-level predictions were compared against independent data from controlled population experiments. We found that DEB theory successfully predicted population growth rates and peak densities of experimental Daphnia populations in multiple experimental settings, but failed to capture the decline phase, when the available food per Daphnia was low. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detecting gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. In addition to theoretical explorations, we tested the potential of DEB theory combined with IBMs to extrapolate effects of chemical stress from the individual to population level. For this we used information at the individual level on the effect of 3,4-dichloroanailine on Daphnia. The individual data suggested direct effects on reproduction but no significant effects on growth. Assuming such direct effects on reproduction, the model was able to accurately predict the population response to increasing concentrations of 3,4-dichloroaniline. We conclude that DEB theory combined with IBMs holds great potential for standardized ecological risk assessment based on ecological models.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
Strategic uncertainty is the uncertainty that players face with respect to the purposeful behavior of other players in an interactive decision situation. Our paper develops a new method for measuring strategic-uncertainty attitudes and distinguishing them from risk and ambiguity attitudes. We vary the source of uncertainty (whether strategic or not) across conditions in a ceteris paribus manner. We elicit certainty equivalents of participating in two strategic 2x2 games (a stag-hunt and a market-entry game) as well as certainty equivalents of related lotteries that yield the same possible payoffs with exogenously given probabilities (risk) and lotteries with unknown probabilities (ambiguity). We provide a structural model of uncertainty attitudes that allows us to measure a preference for or an aversion against the source of uncertainty, as well as optimism or pessimism regarding the desired outcome. We document systematic attitudes towards strategic uncertainty that vary across contexts. Under strategic complementarity [substitutability], the majority of participants tend to be pessimistic [optimistic] regarding the desired outcome. However, preferences for the source of uncertainty are distributed around zero.
The Arctic plays a key role in Earth’s climate system as global warming is predicted to be most pronounced at high latitudes and because one third of the global carbon pool is stored in ecosystems of the northern latitudes. In order to improve our understanding of the present and future carbon dynamics in climate sensitive permafrost ecosystems, the present study concentrates on investigations of microbial controls of methane fluxes, on the activity and structure of the involved microbial communities, and on their response to changing environmental conditions. For this purpose an integrated research strategy was applied, which connects trace gas flux measurements to soil ecological characterisation of permafrost habitats and molecular ecological analyses of microbial populations. Furthermore, methanogenic archaea isolated from Siberian permafrost have been used as potential keystone organisms for studying and assessing life under extreme living conditions. Long-term studies on methane fluxes were carried out since 1998. These studies revealed considerable seasonal and spatial variations of methane emissions for the different landscape units ranging from 0 to 362 mg m-2 d-1. For the overall balance of methane emissions from the entire delta, the first land cover classification based on Landsat images was performed and applied for an upscaling of the methane flux data sets. The regionally weighted mean daily methane emissions of the Lena Delta (10 mg m-2 d-1) are only one fifth of the values calculated for other Arctic tundra environments. The calculated annual methane emission of the Lena Delta amounts to about 0.03 Tg. The low methane emission rates obtained in this study are the result of the used remotely sensed high-resolution data basis, which provides a more realistic estimation of the real methane emissions on a regional scale. Soil temperature and near soil surface atmospheric turbulence were identified as the driving parameters of methane emissions. A flux model based on these variables explained variations of the methane budget corresponding to continuous processes of microbial methane production and oxidation, and gas diffusion through soil and plants reasonably well. The results show that the Lena Delta contributes significantly to the global methane balance because of its extensive wetland areas. The microbiological investigations showed that permafrost soils are colonized by high numbers of microorganisms. The total biomass is comparable to temperate soil ecosystems. Activities of methanogens and methanotrophs differed significantly in their rates and distribution patterns along both the vertical profiles and the different investigated soils. The methane production rates varied between 0.3 and 38.9 nmol h-1 g-1, while the methane oxidation ranged from 0.2 to 7.0 nmol h-1 g-1. Phylogenetic analyses of methanogenic communities revealed a distinct diversity of methanogens affiliated to Methanomicrobiaceae, Methanosarcinaceae and Methanosaetaceae, which partly form four specific permafrost clusters. The results demonstrate the close relationship between methane fluxes and the fundamental microbiological processes in permafrost soils. The microorganisms do not only survive in their extreme habitat but also can be metabolic active under in situ conditions. It was shown that a slight increase of the temperature can lead to a substantial increase in methanogenic activity within perennially frozen deposits. In case of degradation, this would lead to an extensive expansion of the methane deposits with their subsequent impacts on total methane budget. Further studies on the stress response of methanogenic archaea, especially Methanosarcina SMA-21, isolated from Siberian permafrost, revealed an unexpected resistance of the microorganisms against unfavourable living conditions. A better adaptation to environmental stress was observed at 4 °C compared to 28 °C. For the first time it could be demonstrated that methanogenic archaea from terrestrial permafrost even survived simulated Martian conditions. The results show that permafrost methanogens are more resistant than methanogens from non-permafrost environments under Mars-like climate conditions. Microorganisms comparable to methanogens from terrestrial permafrost can be seen as one of the most likely candidates for life on Mars due to their physiological potential and metabolic specificity.
Contents: 1. Introduction 2. Migration and Assimilation – Theoretical Approaches 2.1 Meaning and Definition of the Terms Migration and Migrant 2.2 Milton M. Gordon – Sub Processes of Assimilation 2.3 Hartmut Esser - Acculturation, Integration, and Assimilation 2.4 The Concept of Integration and Assimilation 2.5 Straight–line Assimilation and its Implications 2.6 Segmented Assimilation and its Implications 3. Social Inequality and Welfare – Theoretical Approaches 3.1 Dimensions of Inequality 3.2 Welfare Regimes and Social Inequality 3.3 Migration, Assimilation and Inequality 4. Research Design 4.1 Research Question and General Proceeding 4.2 Sample and Data Base 4.3 Operationalisation and Indicators 5. Migration, Welfare and Inequality in Three European Countries 6. Empirical Results 6.1 Performance of Migrants Compared With Natives 6.2 Different Trajectories of Assimilation 6.3 Trajectories of Segmented Assimilation and their Determinants 6.4 Policies, Attitudes and Assimilation – An Aggregate Analysis 6.5 Summary – What Determines the Performance of Migrants? 7. Discussion of Empirical Results in Terms of Theoretical Approaches 7.1 The Situation of Migrants in Three European Countries 7.2 Assessment of the Trajectories of Assimilation 8. Conclusion – Future Prospects of Migration in Europe
This dissertation aimed to determine differential expressed miRNAs in the context of chronic pain in polyneuropathy. For this purpose, patients with chronic painful polyneuropathy were compared with age matched healthy patients. Taken together, all miRNA pre library preparation quality controls were successful and none of the samples was identified as an outlier or excluded for library preparation. Pre sequencing quality control showed that library preparation worked for all samples as well as that all samples were free of adapter dimers after BluePippin size selection and reached the minimum molarity for further processing. Thus, all samples were subjected to sequencing. The sequencing control parameters were in their optimal range and resulted in valid sequencing results with strong sample to sample correlation for all samples. The resulting FASTQ file of each miRNA library was analyzed and used to perform a differential expression analysis. The differentially expressed and filtered miRNAs were subjected to miRDB to perform a target prediction. Three of those four miRNAs were downregulated: hsa-miR-3135b, hsa-miR-584-5p and hsa-miR-12136, while one was upregulated: hsa-miR-550a-3p. miRNA target prediction showed that chronic pain in polyneuropathy might be the result of a combination of miRNA mediated high blood flow/pressure and neural activity dysregulations/disbalances. Thus, leading to the promising conclusion that these four miRNAs could serve as potential biomarkers for the diagnosis of chronic pain in polyneuropathy.
Since TRPV1 seems to be one of the major contributors of nociception and is associated with neuropathic pain, the influence of PKA phosphorylated ARMS on the sensitivity of TRPV1 as well as the part of AKAP79 during PKA phosphorylation of ARMS was characterized. Therefore, possible PKA-sites in the sequence of ARMS were identified. This revealed five canonical PKA-sites: S882, T903, S1251/52, S1439/40 and S1526/27. The single PKA-site mutants of ARMS revealed that PKA-mediated ARMS phosphorylation seems not to influence the interaction rate of TRPV1/ARMS. While phosphorylation of ARMST903 does not increase the interaction rate with TRPV1, ARMSS1526/27 is probably not phosphorylated and leads to an increased interaction rate. The calcium flux measurements indicated that the higher the interaction rate of TRPV1/ARMS, the lower the EC50 for capsaicin of TRPV1, independent of the PKA phosphorylation status of ARMS. In addition, the western blot analysis confirmed the previously observed TRPV1/ARMS interaction. More importantly, AKAP79 seems to be involved in the TRPV1/ARMS/PKA signaling complex. To overcome the problem of ARMS-mediated TRPV1 sensitization by interaction, ARMS was silenced by shRNA. ARMS silencing resulted in a restored TRPV1 desensitization without affecting the TRPV1 expression and therefore could be used as new topical therapeutic analgesic alternative to stop ARMS mediated TRPV1 sensitization.
One type of internal diachronic change that has been extensively studied for spoken languages is grammaticalization whereby lexical elements develop into free or bound grammatical elements. Based on a wealth of spoken languages, a large amount of prototypical grammaticalization pathways has been identified. Moreover, it has been shown that desemanticization, decategorialization, and phonetic erosion are typical characteristics of grammaticalization processes. Not surprisingly, grammaticalization is also responsible for diachronic change in sign languages. Drawing data from a fair number of sign languages, we show that grammaticalization in visual-gestural languages – as far as the development from lexical to grammatical element is concerned – follows the same developmental pathways as in spoken languages. That is, the proposed pathways are modalityindependent. Besides these intriguing parallels, however, sign languages have the possibility of developing grammatical markers from manual and non-manual co-speech gestures. We will discuss various instances of grammaticalized gestures and we will also briefly address the issue of the modality-specificity of this phenomenon.
Extreme flooding displaces an average of 12 million people every year. Marginalized populations in low-income countries are in particular at high risk, but also industrialized countries are susceptible to displacement and its inherent societal impacts. The risk of being displaced results from a complex interaction of flood hazard, population exposed in the floodplains, and socio-economic vulnerability. Ongoing global warming changes the intensity, frequency, and duration of flood hazards, undermining existing protection measures. Meanwhile, settlements in attractive yet hazardous flood-prone areas have led to a higher degree of population exposure. Finally, the vulnerability to displacement is altered by demographic and social change, shifting economic power, urbanization, and technological development. These risk components have been investigated intensively in the context of loss of life and economic damage, however, only little is known about the risk of displacement under global change.
This thesis aims to improve our understanding of flood-induced displacement risk under global climate change and socio-economic change. This objective is tackled by addressing the following three research questions. First, by focusing on the choice of input data, how well can a global flood modeling chain reproduce flood hazards of historic events that lead to displacement? Second, what are the socio-economic characteristics that shape the vulnerability to displacement? Finally, to what degree has climate change potentially contributed to recent flood-induced displacement events?
To answer the first question, a global flood modeling chain is evaluated by comparing simulated flood extent with satellite-derived inundation information for eight major flood events. A focus is set on the sensitivity to different combinations of the underlying climate reanalysis datasets and global hydrological models which serve as an input for the global hydraulic model. An evaluation scheme of performance scores shows that simulated flood extent is mostly overestimated without the consideration of flood protection and only for a few events dependent on the choice of global hydrological models. Results are more sensitive to the underlying climate forcing, with two datasets differing substantially from a third one. In contrast, the incorporation of flood protection standards results in an underestimation of flood extent, pointing to potential deficiencies in the protection level estimates or the flood frequency distribution within the modeling chain.
Following the analysis of a physical flood hazard model, the socio-economic drivers of vulnerability to displacement are investigated in the next step. For this purpose, a satellite- based, global collection of flood footprints is linked with two disaster inventories to match societal impacts with the corresponding flood hazard. For each event the number of affected population, assets, and critical infrastructure, as well as socio-economic indicators are computed. The resulting datasets are made publicly available and contain 335 displacement events and 695 mortality/damage events. Based on this new data product, event-specific displacement vulnerabilities are determined and multiple (national) dependencies with the socio-economic predictors are derived. The results suggest that economic prosperity only partially shapes vulnerability to displacement; urbanization, infant mortality rate, the share of elderly, population density and critical infrastructure exhibit a stronger functional relationship, suggesting that higher levels of development are generally associated with lower vulnerability.
Besides examining the contextual drivers of vulnerability, the role of climate change in the context of human displacement is also being explored. An impact attribution approach is applied on the example of Cyclone Idai and associated extreme coastal flooding in Mozambique. A combination of coastal flood modeling and satellite imagery is used to construct factual and counterfactual flood events. This storyline-type attribution method allows investigating the isolated or combined effects of sea level rise and the intensification of cyclone wind speeds on coastal flooding. The results suggest that displacement risk has increased by 3.1 to 3.5% due to the total effects of climate change on coastal flooding, with the effects of increasing wind speed being the dominant factor.
In conclusion, this thesis highlights the potentials and challenges of modeling flood- induced displacement risk. While this work explores the sensitivity of global flood modeling to the choice of input data, new questions arise on how to effectively improve the reproduction of flood return periods and the representation of protection levels. It is also demonstrated that disentangling displacement vulnerabilities is feasible, with the results providing useful information for risk assessments, effective humanitarian aid, and disaster relief. The impact attribution study is a first step in assessing the effects of global warming on displacement risk, leading to new research challenges, e.g., coupling fluvial and coastal flood models or the attribution of other hazard types and displacement events. This thesis is one of the first to address flood-induced displacement risk from a global perspective. The findings motivate for further development of the global flood modeling chain to improve our understanding of displacement vulnerability and the effects of global warming.