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Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. In response to specific environmental stresses the cell activates several stress-specific molecules such as sigma factors. They reversibly bind the RNA polymerase to form the so-called holoenzyme and direct it towards the appropriate stress response genes. In exponentially growing E. coli cells, the majority of the transcriptional activity is carried out by the housekeeping sigma factor, while stress responses are often under the control of alternative sigma factors. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross talk between genes or gene classes via the sharing of expression machinery. To quantitatively analyze the contribution of sigma factor competition to global changes in gene expression, we develop a thermodynamic model that describes binding between sigma factors and core RNAP at equilibrium, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components.
Association of housekeeping sigma factor to RNAP is generally favored by its abundance and higher binding affinity to the core. In order to promote transcription by alternative sigma subunits, the bacterial cell modulates the transcriptional efficiency in a reversible manner through several strategies such as anti-sigma factors, 6S RNA and generally any kind of transcriptional regulators (e.g. activators or inhibitors). By shifting the outcome of sigma factor competition for the core, these modulators bias the transcriptional program of the cell. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. We observe that transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected.
Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross talk effects and raising the question of how their in vitro measure is relevant in the cell. We also estimate that sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors, and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program and gives new insights into RNAP partitioning in the cell.
An important goal in biotechnology and (bio-) medical research is the isolation of single cells from a heterogeneous cell population. These specialised cells are of great interest for bioproduction, diagnostics, drug development, (cancer) therapy and research. To tackle emerging questions, an ever finer differentiation between target cells and non-target cells is required. This precise differentiation is a challenge for a growing number of available methods.
Since the physiological properties of the cells are closely linked to their morphology, it is beneficial to include their appearance in the sorting decision. For established methods, this represents a non addressable parameter, requiring new methods for the identification and isolation of target cells. Consequently, a variety of new flow-based methods have been developed and presented in recent years utilising 2D imaging data to identify target cells within a sample. As these methods aim for high throughput, the devices developed typically require highly complex fluid handling techniques, making them expensive while offering limited image quality.
In this work, a new continuous flow system for image-based cell sorting was developed that uses dielectrophoresis to precisely handle cells in a microchannel. Dielectrophoretic forces are exerted by inhomogeneous alternating electric fields on polarisable particles (here: cells). In the present system, the electric fields can be switched on and off precisely and quickly by a signal generator. In addition to the resulting simple and effective cell handling, the system is characterised by the outstanding quality of the image data generated and its compatibility with standard microscopes. These aspects result in low complexity, making it both affordable and user-friendly.
With the developed cell sorting system, cells could be sorted reliably and efficiently according to their cytosolic staining as well as morphological properties at different optical magnifications. The achieved purity of the target cell population was up to 95% and about 85% of the sorted cells could be recovered from the system. Good agreement was achieved between the results obtained and theoretical considerations. The achieved throughput of the system was up to 12,000 cells per hour. Cell viability studies indicated a high biocompatibility of the system.
The results presented demonstrate the potential of image-based cell sorting using dielectrophoresis. The outstanding image quality and highly precise yet gentle handling of the cells set the system apart from other technologies. This results in enormous potential for processing valuable and sensitive cell samples.
For the elucidation of the dynamics of signal transduction processes that are induced by cellular interactions, defined events along the signal transduction cascade and subsequent activation steps have to be analyzed and then also correlated with each other. This cannot be achieved by ensemble measurements because averaging biological data ignores the variability in timing and response patterns of individual cells and leads to highly blurred results. Instead, only a multi-parameter analysis at a single-cell level is able to exploit the information that is crucially needed for deducing the signaling pathways involved. The aim of this work was to develop a process line that allows the initiation of cell-cell or cell-particle interactions while at the same time the induced cellular reactions can be analyzed at various stages along the signal transduction cascade and correlated with each other. As this approach requires the gentle management of individually addressable cells, a dielectrophoresis (DEP)-based microfluidic system was employed that provides the manipulation of microscale objects with very high spatiotemporal precision and without the need of contacting the cell membrane. The system offers a high potential for automation and parallelization. This is essential for achieving a high level of robustness and reproducibility, which are key requirements in order to qualify this approach for a biomedical application. As an example process for intercellular communication, T cell activation has been chosen. The activation of the single T cells was triggered by contacting them individually with microbeads that were coated with antibodies directed against specific cell surface proteins, like the T cell receptor-associated kinase CD3 and the costimulatory molecule CD28 (CD; cluster of differentiation). The stimulation of the cells with the functionalized beads led to a rapid rise of their cytosolic Ca2+ concentration which was analyzed by a dual-wavelength ratiometric fluorescence measurement of the Ca2+-sensitive dye Fura-2. After Ca2+ imaging, the cells were isolated individually from the microfluidic system and cultivated further. Cell division and expression of the marker molecule CD69 as a late activation event of great significance were analyzed the following day and correlated with the previously recorded Ca2+ traces for each individual cell. It turned out such that the temporal profile of the Ca2+ traces between both activated and non-activated cells as well as dividing and non-dividing cells differed significantly. This shows that the pattern of Ca2+ signals in T cells can provide early information about a later reaction of the cell. As isolated cells are highly delicate objects, a precondition for these experiments was the successful adaptation of the system to maintain the vitality of single cells during and after manipulation. In this context, the influences of the microfluidic environment as well as the applied electric fields on the vitality of the cells and the cytosolic Ca2+ concentration as crucially important physiological parameters were thoroughly investigated. While a short-term DEP manipulation did not affect the vitality of the cells, they showed irregular Ca2+ transients upon exposure to the DEP field only. The rate and the strength of these Ca2+ signals depended on exposure time, electric field strength and field frequency. By minimizing their occurrence rate, experimental conditions were identified that caused the least interference with the physiology of the cell. The possibility to precisely control the exact time point of stimulus application, to simultaneously analyze short-term reactions and to correlate them with later events of the signal transduction cascade on the level of individual cells makes this approach unique among previously described applications and offers new possibilities to unravel the mechanisms underlying intercellular communication.
With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation.
Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly.
The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design.
As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation.
The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments.
Recognizing, understanding, and responding to quantities are considerable skills for human beings. We can easily communicate quantities, and we are extremely efficient in adapting our behavior to numerical related tasks. One usual task is to compare quantities. We also use symbols like digits in numerical-related tasks. To solve tasks including digits, we must to rely on our previously learned internal number representations.
This thesis elaborates on the process of number comparison with the use of noisy mental representations of numbers, the interaction of number and size representations and how we use mental number representations strategically. For this, three studies were carried out.
In the first study, participants had to decide which of two presented digits was numerically larger. They had to respond with a saccade in the direction of the anticipated answer. Using only a small set of meaningfully interpretable parameters, a variant of random walk models is described that accounts for response time, error rate, and variance of response time for the full matrix of 72 digit pairs. In addition, the used random walk model predicts a numerical distance effect even for error response times and this effect clearly occurs in the observed data. In relation to corresponding correct answers error responses were systematically faster. However, different from standard assumptions often made in random walk models, this account required that the distributions of step sizes of the induced random walks be asymmetric to account for this asymmetry between correct and incorrect responses.
Furthermore, the presented model provides a well-defined framework to investigate the nature and scale (e.g., linear vs. logarithmic) of the mapping of numerical magnitude onto its internal representation. In comparison of the fits of proposed models with linear and logarithmic mapping, the logarithmic mapping is suggested to be prioritized.
Finally, we discuss how our findings can help interpret complex findings (e.g., conflicting speed vs. accuracy trends) in applied studies that use number comparison as a well-established diagnostic tool. Furthermore, a novel oculomotoric effect is reported, namely the saccadic overschoot effect. The participants responded by saccadic eye movements and the amplitude of these saccadic responses decreases with numerical distance.
For the second study, an experimental design was developed that allows us to apply the signal detection theory to a task where participants had to decide whether a presented digit was physically smaller or larger. A remaining question is, whether the benefit in (numerical magnitude – physical size) congruent conditions is related to a better perception than in incongruent conditions. Alternatively, the number-size congruency effect is mediated by response biases due to numbers magnitude. The signal detection theory is a perfect tool to distinguish between these two alternatives. It describes two parameters, namely sensitivity and response bias. Changes in the sensitivity are related to the actual task performance due to real differences in perception processes whereas changes in the response bias simply reflect strategic implications as a stronger preparation (activation) of an anticipated answer. Our results clearly demonstrate that the number-size congruency effect cannot be reduced to mere response bias effects, and that genuine sensitivity gains for congruent number-size pairings contribute to the number-size congruency effect.
Third, participants had to perform a SNARC task – deciding whether a presented digit was odd or even. Local transition probability of irrelevant attributes (magnitude) was varied while local transition probability of relevant attributes (parity) and global probability occurrence of each stimulus were kept constantly. Participants were quite sensitive in recognizing the underlying local transition probability of irrelevant attributes. A gain in performance was observed for actual repetitions of the irrelevant attribute in relation to changes of the irrelevant attribute in high repetition conditions compared to low repetition conditions. One interpretation of these findings is that information about the irrelevant attribute (magnitude) in the previous trial is used as an informative precue, so that participants can prepare early processing stages in the current trial, with the corresponding benefits and costs typical of standard cueing studies.
Finally, the results reported in this thesis are discussed in relation to recent studies in numerical cognition.
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.
Nowadays, graph data models are employed, when relationships between entities have to be stored and are in the scope of queries. For each entity, this graph data model locally stores relationships to adjacent entities. Users employ graph queries to query and modify these entities and relationships. These graph queries employ graph patterns to lookup all subgraphs in the graph data that satisfy certain graph structures. These subgraphs are called graph pattern matches. However, this graph pattern matching is NP-complete for subgraph isomorphism. Thus, graph queries can suffer a long response time, when the number of entities and relationships in the graph data or the graph patterns increases.
One possibility to improve the graph query performance is to employ graph views that keep ready graph pattern matches for complex graph queries for later retrieval. However, these graph views must be maintained by means of an incremental graph pattern matching to keep them consistent with the graph data from which they are derived, when the graph data changes. This maintenance adds subgraphs that satisfy a graph pattern to the graph views and removes subgraphs that do not satisfy a graph pattern anymore from the graph views.
Current approaches for incremental graph pattern matching employ Rete networks. Rete networks are discrimination networks that enumerate and maintain all graph pattern matches of certain graph queries by employing a network of condition tests, which implement partial graph patterns that together constitute the overall graph query. Each condition test stores all subgraphs that satisfy the partial graph pattern. Thus, Rete networks suffer high memory consumptions, because they store a large number of partial graph pattern matches. But, especially these partial graph pattern matches enable Rete networks to update the stored graph pattern matches efficiently, because the network maintenance exploits the already stored partial graph pattern matches to find new graph pattern matches. However, other kinds of discrimination networks exist that can perform better in time and space than Rete networks. Currently, these other kinds of networks are not used for incremental graph pattern matching.
This thesis employs generalized discrimination networks for incremental graph pattern matching. These discrimination networks permit a generalized network structure of condition tests to enable users to steer the trade-off between memory consumption and execution time for the incremental graph pattern matching. For that purpose, this thesis contributes a modeling language for the effective definition of generalized discrimination networks. Furthermore, this thesis contributes an efficient and scalable incremental maintenance algorithm, which updates the (partial) graph pattern matches that are stored by each condition test. Moreover, this thesis provides a modeling evaluation, which shows that the proposed modeling language enables the effective modeling of generalized discrimination networks. Furthermore, this thesis provides a performance evaluation, which shows that a) the incremental maintenance algorithm scales, when the graph data becomes large, and b) the generalized discrimination network structures can outperform Rete network structures in time and space at the same time for incremental graph pattern matching.
This work analyzes the saving and consumption behavior of agents faced with the possibility of unemployment in a dynamic and stochastic life cycle model. The intertemporal optimization is based on Dynamic Programming with a backward recursion algorithm. The implemented uncertainty is not based on income shocks as it is done in traditional life cycle models but uses Markov probabilities where the probability for the next employment status of the agent depends on the current status. The utility function used is a CRRA function (constant relative risk aversion), combined with a CES function (constant elasticity of substitution) and has several consumption goods, a subsistence level, money and a bequest function.
In the context of cosmological structure formation sheets, filaments and eventually halos form due to gravitational instabilities. It is noteworthy, that at all times, the majority of the baryons in the universe does not reside in the dense halos but in the filaments and the sheets of the intergalactic medium. While at higher redshifts of z > 2, these baryons can be detected via the absorption of light (originating from more distant sources) by neutral hydrogen at temperatures of T ~ 10^4 K (the Lyman-alpha forest), at lower redshifts only about 20 % can be found in this state. The remain (about 50 to 70 % of the total baryons mass) is unaccounted for by observational means. Numerical simulations predict that these missing baryons could reside in the filaments and sheets of the cosmic web at high temperatures of T = 10^4.5 - 10^7 K, but only at low to intermediate densities, and constitutes the warm-hot intergalactic medium (WHIM). The high temperatures of the WHIM are caused by the formation of shocks and the subsequent shock-heating of the gas. This results in a high degree of ionization and renders the reliable detection of the WHIM a challenging task. Recent high-resolution hydrodynamical simulations indicate that, at redshifts of z ~ 2, filaments are able to provide very massive galaxies with a significant amount of cool gas at temperatures of T ~ 10^4 K. This could have an important impact on the star-formation in those galaxies. It is therefore of principle importance to investigate the particular hydro- and thermodynamical conditions of these large filament structures. Density and temperature profiles, and velocity fields, are expected to leave their special imprint on spectroscopic observations. A potential multiphase structure may act as tracer in observational studies of the WHIM. In the context of cold streams, it is important to explore the processes, which regulate the amount of gas transported by the streams. This includes the time evolution of filaments, as well as possible quenching mechanisms. In this context, the halo mass range in which cold stream accretion occurs is of particular interest. In order to address these questions, we perform particular hydrodynamical simulations of very high resolution, and investigate the formation and evolution of prototype structures representing the typical filaments and sheets of the WHIM. We start with a comprehensive study of the one-dimensional collapse of a sinusoidal density perturbation (pancake formation) and examine the influence of radiative cooling, heating due to an UV background, thermal conduction, and the effect of small-scale perturbations given by the cosmological power spectrum. We use a set of simulations, parametrized by the wave length of the initial perturbation L. For L ~ 2 Mpc/h the collapse leads to shock-confined structures. As a result of radiative cooling and of heating due to an UV background, a relatively cold and dense core forms. With increasing L the core becomes denser and more concentrated. Thermal conduction enhances this trend and may lead to an evaporation of the core at very large L ~ 30 Mpc/h. When extending our simulations into three dimensions, instead of a pancake structure, we obtain a configuration consisting of well-defined sheets, filaments, and a gaseous halo. For L > 4 Mpc/h filaments form, which are fully confined by an accretion shock. As with the one-dimensional pancakes, they exhibit an isothermal core. Thus, our results confirm a multiphase structure, which may generate particular spectral tracers. We find that, after its formation, the core becomes shielded against further infall of gas onto the filament, and its mass content decreases with time. In the vicinity of the halo, the filament's core can be attributed to the cold streams found in other studies. We show, that the basic structure of these cold streams exists from the very beginning of the collapse process. Further on, the cross section of the streams is constricted by the outwards moving accretion shock of the halo. Thermal conduction leads to a complete evaporation of the cold stream for L > 6 Mpc/h. This corresponds to halos with a total mass higher than M_halo = 10^13 M_sun, and predicts that in more massive halos star-formation can not be sustained by cold streams. Far away from the gaseous halo, the temperature gradients in the filament are not sufficiently strong for thermal conduction to be effective.
With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found.
The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack.
Dark matter, DM, has not yet been directly observed, but it has a very solid theoretical basis. There are observations that provide indirect evidence, like galactic rotation curves that show that the galaxies are rotating too fast to keep their constituent parts, and galaxy clusters that bends the light coming from behind-lying galaxies more than expected with respect to the mass that can be calculated from what can be visibly seen. These observations, among many others, can be explained with theories that include DM. The missing piece is to detect something that can exclusively be explained by DM. Direct observation in a particle accelerator is one way and indirect detection using telescopes is another. This thesis is focused on the latter method.
The Very Energetic Radiation Imaging Telescope Array System, V ERITAS, is a telescope array that detects Cherenkov radiation. Theory predicts that DM particles annihilate into, e.g., a γγ pair and create a distinctive energy spectrum when detected by such telescopes, e.i., a monoenergetic line at the same energy as the particle mass. This so called ”smoking-gun” signature is sought with a sliding window line search within the sub-range ∼ 0.3 − 10 TeV of the VERITAS energy range, ∼ 0.01 − 30 TeV.
Standard analysis within the VERITAS collaboration uses Hillas analysis and look-up tables, acquired by analysing particle simulations, to calculate the energy of the particle causing the Cherenkov shower. In this thesis, an improved analysis method has been used. Modelling each shower as a 3Dgaussian should increase the energy recreation quality. Five dwarf spheroidal galaxies were chosen as targets with a total of ∼ 224 hours of data. The targets were analysed individually and stacked. Particle simulations were based on two simulation packages, CARE and GrISU.
Improvements have been made to the energy resolution and bias correction, up to a few percent each, in comparison to standard analysis. Nevertheless, no line with a relevant significance has been detected. The most promising line is at an energy of ∼ 422 GeV with an upper limit cross section of 8.10 · 10^−24 cm^3 s^−1 and a significance of ∼ 2.73 σ, before trials correction and ∼ 1.56 σ after. Upper limit cross sections have also been calculated for the γγ annihilation process and four other outcomes. The limits are in line with current limits using other methods, from ∼ 8.56 · 10^−26 − 6.61 · 10^−23 cm^3s^−1. Future larger telescope arrays, like the upcoming Cherenkov Telescope Array, CTA, will provide better results with the help of this analysis method.
The aim of this dissertation was to conduct a larger-scale cross-linguistic empirical investigation of similarity-based interference effects in sentence comprehension.
Interference studies can offer valuable insights into the mechanisms that are involved in long-distance dependency completion.
Many studies have investigated similarity-based interference effects, showing that syntactic and semantic information are employed during long-distance dependency formation (e.g., Arnett & Wagers, 2017; Cunnings & Sturt, 2018; Van Dyke, 2007, Van Dyke & Lewis, 2003; Van Dyke & McElree, 2011). Nevertheless, there are some important open questions in the interference literature that are critical to our understanding of the constraints involved in dependency resolution.
The first research question concerns the relative timing of syntactic and semantic interference in online sentence comprehension. Only few interference studies have investigated this question, and, to date, there is not enough data to draw conclusions with regard to their time course (Van Dyke, 2007; Van Dyke & McElree, 2011).
Our first cross-linguistic study explores the relative timing of syntactic and semantic interference in two eye-tracking reading experiments that implement the study design used in Van Dyke (2007). The first experiment tests English sentences. The second, larger-sample experiment investigates the two interference types in German.
Overall, the data suggest that syntactic and semantic interference can arise simultaneously during retrieval.
The second research question concerns a special case of semantic interference: We investigate whether cue-based retrieval interference can be caused by semantically similar items which are not embedded in a syntactic structure.
This second interference study builds on a landmark study by Van Dyke & McElree (2006). The study design used in their study is unique in that it is able to pin down the source of interference as a consequence of cue overload during retrieval, when semantic retrieval cues do not uniquely match the retrieval target. Unlike most other interference studies, this design is able to rule out encoding interference as an alternative explanation. Encoding accounts postulate that it is not cue overload at the retrieval site but the erroneous encoding of similar linguistic items in memory that leads to interference (Lewandowsky et al., 2008; Oberauer & Kliegl, 2006). While Van Dyke & McElree (2006) reported cue-based retrieval interference from sentence-external distractors, the evidence for this effect was weak. A subsequent study did not show interference of this type (Van Dyke et al., 2014). Given these inconclusive findings, further research is necessary to investigate semantic cue-based retrieval interference.
The second study in this dissertation provides a larger-scale cross-linguistic investigation of cue-based retrieval interference from sentence-external items. Three larger-sample eye-tracking studies in English, German, and Russian tested cue-based interference in the online processing of filler-gap dependencies. This study further extends the previous research by investigating interference in each language under varying task demands (Logačev & Vasishth, 2016; Swets et al., 2008).
Overall, we see some very modest support for proactive cue-based retrieval interference in English. Unexpectedly, this was observed only under a low task demand. In German and Russian, there is some evidence against the interference effect. It is possible that interference is attenuated in languages with richer case marking.
In sum, the cross-linguistic experiments on the time course of syntactic and semantic interference from sentence-internal distractors support existing evidence of syntactic and semantic interference during sentence comprehension. Our data further show that both types of interference effects can arise simultaneously. Our cross-linguistic experiments investigating semantic cue-based retrieval interference from sentence-external distractors suggest that this type of interference may arise only in specific linguistic contexts.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR.
In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid.
This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses.
The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies.
All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research.
As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations.
Companies develop process models to explicitly describe their business operations. In the same time, business operations, business processes, must adhere to various types of compliance requirements. Regulations, e.g., Sarbanes Oxley Act of 2002, internal policies, best practices are just a few sources of compliance requirements. In some cases, non-adherence to compliance requirements makes the organization subject to legal punishment. In other cases, non-adherence to compliance leads to loss of competitive advantage and thus loss of market share. Unlike the classical domain-independent behavioral correctness of business processes, compliance requirements are domain-specific. Moreover, compliance requirements change over time. New requirements might appear due to change in laws and adoption of new policies. Compliance requirements are offered or enforced by different entities that have different objectives behind these requirements. Finally, compliance requirements might affect different aspects of business processes, e.g., control flow and data flow. As a result, it is infeasible to hard-code compliance checks in tools. Rather, a repeatable process of modeling compliance rules and checking them against business processes automatically is needed. This thesis provides a formal approach to support process design-time compliance checking. Using visual patterns, it is possible to model compliance requirements concerning control flow, data flow and conditional flow rules. Each pattern is mapped into a temporal logic formula. The thesis addresses the problem of consistency checking among various compliance requirements, as they might stem from divergent sources. Also, the thesis contributes to automatically check compliance requirements against process models using model checking. We show that extra domain knowledge, other than expressed in compliance rules, is needed to reach correct decisions. In case of violations, we are able to provide a useful feedback to the user. The feedback is in the form of parts of the process model whose execution causes the violation. In some cases, our approach is capable of providing automated remedy of the violation.
Situated in an active tectonic region, Santiago de Chile, the country´s capital with more than six million inhabitants, faces tremendous earthquake hazard. Macroseismic data for the 1985 Valparaiso and the 2010 Maule events show large variations in the distribution of damage to buildings within short distances indicating strong influence of local sediments and the shape of the sediment-bedrock interface on ground motion. Therefore, a temporary seismic network was installed in the urban area for recording earthquake activity, and a study was carried out aiming to estimate site amplification derived from earthquake data and ambient noise. The analysis of earthquake data shows significant dependence on the local geological structure with regards to amplitude and duration. Moreover, the analysis of noise spectral ratios shows that they can provide a lower bound in amplitude for site amplification and, since no variability in terms of time and amplitude is observed, that it is possible to map the fundamental resonance frequency of the soil for a 26 km x 12 km area in the northern part of the Santiago de Chile basin. By inverting the noise spectral rations, local shear wave velocity profiles could be derived under the constraint of the thickness of the sedimentary cover which had previously been determined by gravimetric measurements. The resulting 3D model was derived by interpolation between the single shear wave velocity profiles and shows locally good agreement with the few existing velocity profile data, but allows the entire area, as well as deeper parts of the basin, to be represented in greater detail. The wealth of available data allowed further to check if any correlation between the shear wave velocity in the uppermost 30 m (vs30) and the slope of topography, a new technique recently proposed by Wald and Allen (2007), exists on a local scale. While one lithology might provide a greater scatter in the velocity values for the investigated area, almost no correlation between topographic gradient and calculated vs30 exists, whereas a better link is found between vs30 and the local geology. When comparing the vs30 distribution with the MSK intensities for the 1985 Valparaiso event it becomes clear that high intensities are found where the expected vs30 values are low and over a thick sedimentary cover. Although this evidence cannot be generalized for all possible earthquakes, it indicates the influence of site effects modifying the ground motion when earthquakes occur well outside of the Santiago basin. Using the attained knowledge on the basin characteristics, simulations of strong ground motion within the Santiago Metropolitan area were carried out by means of the spectral element technique. The simulation of a regional event, which has also been recorded by a dense network installed in the city of Santiago for recording aftershock activity following the 27 February 2010 Maule earthquake, shows that the model is capable to realistically calculate ground motion in terms of amplitude, duration, and frequency and, moreover, that the surface topography and the shape of the sediment bedrock interface strongly modify ground motion in the Santiago basin. An examination on the dependency of ground motion on the hypocenter location for a hypothetical event occurring along the active San Ramón fault, which is crossing the eastern outskirts of the city, shows that the unfavorable interaction between fault rupture, radiation mechanism, and complex geological conditions in the near-field may give rise to large values of peak ground velocity and therefore considerably increase the level of seismic risk for Santiago de Chile.
The aim of this doctoral thesis was to establish a technique for the analysis of biomolecules with infrared matrix-assisted laser dispersion (IR-MALDI) ion mobility (IM) spectrometry. The main components of the work were the characterization of the IR-MALDI process, the development and characterization of different ion mobility spectrometers, the use of IR-MALDI-IM spectrometry as a robust, standalone spectrometer and the development of a collision cross-section estimation approach for peptides based on molecular dynamics and thermodynamic reweighting.
First, the IR-MALDI source was studied with atmospheric pressure ion mobility spectrometry and shadowgraphy. It consisted of a metal capillary, at the tip of which a self-renewing droplet of analyte solution was met by an IR laser beam. A relationship between peak shape, ion desolvation, diffusion and extraction pulse delay time (pulse delay) was established. First order desolvation kinetics were observed and related to peak broadening by diffusion, both influenced by the pulse delay. The transport mechanisms in IR-MALDI were then studied by relating different laser impact positions on the droplet surface to the corresponding ion mobility spectra. Two different transport mechanisms were determined: phase explosion due to the laser pulse and electrical transport due to delayed ion extraction. The velocity of the ions stemming from the phase explosion was then measured by ion mobility and shadowgraphy at different time scales and distances from the source capillary, showing an initially very high but rapidly decaying velocity. Finally, the anatomy of the dispersion plume was observed in detail with shadowgraphy and general conclusions over the process were drawn.
Understanding the IR-MALDI process enabled the optimization of the different IM spectrometers at atmospheric and reduced pressure (AP and RP, respectively). At reduced pressure, both an AP and an RP IR-MALDI source were used. The influence of the pulsed ion extraction parameters (pulse delay, width and amplitude) on peak shape, resolution and area was systematically studied in both AP and RP IM spectrometers and discussed in the context of the IR-MALDI process. Under RP conditions, the influence of the closing field and of the pressure was also examined for both AP and RP sources. For the AP ionization RP IM spectrometer, the influence of the inlet field (IF) in the source region was also examined. All of these studies led to the determination of the optimal analytical parameters as well as to a better understanding of the initial ion cloud anatomy.
The analytical performance of the spectrometer was then studied. Limits of detection (LOD) and linear ranges were determined under static and pulsed ion injection conditions and interpreted in the context of the IR-MALDI mechanism. Applications in the separation of simple mixtures were also illustrated, demonstrating good isomer separation capabilities and the advantages of singly charged peaks. The possibility to couple high performance liquid chromatography (HPLC) to IR-MALDI-IM spectrometry was also demonstrated. Finally, the reduced pressure spectrometer was used to study the effect of high reduced field strength on the mobility of polyatomic ions in polyatomic gases.
The last focus point was on the study of peptide ions. A dataset obtained with electrospray IM spectrometry was characterized and used for the calibration of a collision cross-section (CCS) determination method based on molecular dynamics (MD) simulations at high temperature. Instead of producing candidate structures which are evaluated one by one, this semi-automated method uses the simulation as a whole to determine a single average collision cross-section value by reweighting the CCS of a few representative structures. The method was compared to the intrinsic size parameter (ISP) method and to experimental results. Additional MD data obtained from the simulations was also used to further analyze the peptides and understand the experimental results, an advantage with regard to the ISP method. Finally, the CCS of peptide ions analyzed by IR-MALDI were also evaluated with both ISP and MD methods and the results compared to experiment, resulting in a first validation of the MD method. Thus, this thesis brings together the soft ionization technique that is IR-MALDI, which produces mostly singly charged peaks, with ion mobility spectrometry, which can distinguish between isomers, and a collision cross-section determination method which also provides structural information on the analyte at hand.
Data stream processing systems (DSPSs) are a key enabler to integrate continuously generated data, such as sensor measurements, into enterprise applications. DSPSs allow to steadily analyze information from data streams, e.g., to monitor manufacturing processes and enable fast reactions to anomalous behavior. Moreover, DSPSs continuously filter, sample, and aggregate incoming streams of data, which reduces the data size, and thus data storage costs.
The growing volumes of generated data have increased the demand for high-performance DSPSs, leading to a higher interest in these systems and to the development of new DSPSs. While having more DSPSs is favorable for users as it allows choosing the system that satisfies their requirements the most, it also introduces the challenge of identifying the most suitable DSPS regarding current needs as well as future demands. Having a solution to this challenge is important because replacements of DSPSs require the costly re-writing of applications if no abstraction layer is used for application development. However, quantifying performance differences between DSPSs is a difficult task. Existing benchmarks fail to integrate all core functionalities of DSPSs and lack tool support, which hinders objective result comparisons. Moreover, no current benchmark covers the combination of streaming data with existing structured business data, which is particularly relevant for companies.
This thesis proposes a performance benchmark for enterprise stream processing called ESPBench. With enterprise stream processing, we refer to the combination of streaming and structured business data. Our benchmark design represents real-world scenarios and allows for an objective result comparison as well as scaling of data. The defined benchmark query set covers all core functionalities of DSPSs. The benchmark toolkit automates the entire benchmark process and provides important features, such as query result validation and a configurable data ingestion rate.
To validate ESPBench and to ease the use of the benchmark, we propose an example implementation of the ESPBench queries leveraging the Apache Beam software development kit (SDK). The Apache Beam SDK is an abstraction layer designed for developing stream processing applications that is applied in academia as well as enterprise contexts. It allows to run the defined applications on any of the supported DSPSs. The performance impact of Apache Beam is studied in this dissertation as well. The results show that there is a significant influence that differs among DSPSs and stream processing applications. For validating ESPBench, we use the example implementation of the ESPBench queries developed using the Apache Beam SDK. We benchmark the implemented queries executed on three modern DSPSs: Apache Flink, Apache Spark Streaming, and Hazelcast Jet. The results of the study prove the functioning of ESPBench and its toolkit. ESPBench is capable of quantifying performance characteristics of DSPSs and of unveiling differences among systems.
The benchmark proposed in this thesis covers all requirements to be applied in enterprise stream processing settings, and thus represents an improvement over the current state-of-the-art.
The emerging threat of antibiotic-resistant bacteria has become a global challenge in the last decades, leading to a rising demand for alternative treatments for bacterial infections. One approach is to target the bacterial cell envelope, making understanding its biophysical properties crucial. Specifically, bacteriophages use the bacterial envelope as an entry point to initiate infection, and they are considered important building blocks of new antibiotic strategies against drug-resistant bacteria.. Depending on the structure of the cell wall, bacteria are classified as Gram-negative and Gram-positive. Gram-negative bacteria are equipped with a complex cell envelope composed of two lipid membranes enclosing a rigid peptidoglycan layer. The synthesis machinery of the Gram-negative cell envelope is the target of antimicrobial agents, including new physical sanitizing procedures addressing the outer membrane (OM). It is therefore very important to study the biophysical properties of the Gram-negative bacterial cell envelope. The high complexity of the Gram-negative OM sets the demand for a model system in which the contribution of individual components can be evaluated separately. In this respect, giant unilamellar vesicles (GUVs) are promising membrane systems to study membrane properties while controlling parameters such as membrane composition and surrounding medium conditions.
The aim of this work was to develop methods and approaches for the preparation and characterization of a GUV-based membrane model that mimics the OM of the Gram-negative cell envelope. A major component of the OM is the lipopolysaccharide (LPS) on the outside of the OM heterobilayer. The vesicle model was designed to contain LPS in the outer leaflet and lipids in the inner leaflet. Furthermore, the interaction of the prepared LPS-GUVs with bacteriophages was tested. LPS containing GUVs were prepared by adapting the inverted emulsion technique to meet the challenging properties of LPS, namely their high self-aggregation rate in aqueous solutions. Notably, an additional emulsification step together with the adaption of solution conditions was employed to asymmetrically incorporate LPS containing long polysaccharide chains into the artificial membranes. GUV membrane asymmetry was verified with a fluorescence quenching assay. Since the necessary precautions for handling the quenching agent sodium dithionite are often underestimated and poorly described, important parameters were tested and identified to obtain a stable and reproducible assay. In the context of varied LPS incorporation, a microscopy-based technique was introduced to determine the LPS content on individual GUVs and to directly compare vesicle properties and LPS coverage. Diffusion coefficient measurements in the obtained GUVs showed that increasing LPS concentrations in the membranes resulted in decreased diffusivity.
Employing LPS-GUVs we could demonstrate that a Salmonella bacteriophage bound with high specificity to its LPS receptor when presented at the GUV surface, and that the number of bound bacteriophages scaled with the amount of presented LPS receptor. In addition to binding, the bacteriophages were able to eject their DNA into the vesicle lumen. LPS-GUVs thus provide a starting platform for bottom-up approaches for the generation of more complex membranes, in which the effects of individual components on the membrane properties and the interaction with antimicrobial agents such as bacteriophages could be explored.
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 scientific drilling campaign PALEOVAN was conducted in the summer of 2010 and was part of the international continental drilling programme (ICDP). The main goal of the campaign was the recovery of a sensitive climate archive in the East of Anatolia. Lacustrine deposits underneath the lake floor of ‘Lake Van’ constitute this archive. The drilled core material was recovered from two locations: the Ahlat Ridge and the Northern Basin. A composite core was constructed from cored material of seven parallel boreholes at the Ahlat Ridge and covers an almost complete lacustrine history of Lake Van. The composite record offered sensitive climate proxies such as variations of total organic carbon, K/Ca ratios, or a relative abundance of arboreal pollen. These proxies revealed patterns that are similar to climate proxy variations from Greenland ice cores. Climate variations in Greenland ice cores have been dated by modelling the timing of orbital forces to affect the climate. Volatiles from melted ice aliquots are often taken as high-resolution proxies and provide a base for fitting the according temporal models.
The ICDP PALEOVAN scientific team fitted proxy data from the lacustrine drilling record to ice core data and constructed an age model. Embedded volcaniclastic layers had to be dated radiometrically in order to provide independent age constraints to the climate-stratigraphic age model. Solving this task by an application of the 40Ar/39Ar method was the main objective of this thesis. Earlier efforts to apply the 40Ar/39Ar dating resulted in inaccuracies that could not be explained satisfactorily.
The absence of K-rich feldspars in suitable tephra layers implied that feldspar crystals needed to be 500 μm in size minimum, in order to apply single-crystal 40Ar/39Ar dating. Some of the samples did not contain any of these grain sizes or only very few crystals of that size. In order to overcome this problem this study applied a combined single-crystal and multi-crystal approach with different crystal fractions from the same sample. The preferred method of a stepwise heating analysis of an aliquot of feldspar crystals has been applied to three samples. The Na-rich crystals and their young geological age required 20 mg of inclusion-free, non-corroded feldspars. Small sample volumes (usually 25 % aliquots of 5 cm3 of sample material – a spoon full of tephra) and the widespread presence of melt-inclusion led to the application of combined single- and multigrain total fusion analyses. 40Ar/39Ar analyses on single crystals have the advantage of being able to monitor the presence of excess 40Ar and detrital or xenocrystic contamination in the samples. Multigrain analyses may hide the effects from these obstacles. The results from the multigrain analyses are therefore discussed with respect to the findings from the respective cogenetic single crystal ages. Some of the samples in this study were dated by 40Ar/39Ar on feldspars on multigrain separates and (if available) in combination with only a few single crystals. 40Ar/39Ar ages from two of the samples deviated statistically from the age model. All other samples resulted in identical ages. The deviations displayed older ages than those obtained from the age model. t-Tests compared radiometric ages with available age control points from various proxies and from the relative paleointensity of the earth magnetic field within a stratigraphic range of ± 10 m. Concordant age control points from different relative chronometers indicated that deviations are a result of erroneous 40Ar/39Ar ages. The thesis argues two potential reasons for these ages: (1) the irregular appearance of 40Ar from rare melt- and fluid- inclusions and (2) the contamination of the samples with older crystals due to a rapid combination of assimilation and ejection.
Another aliquot of feldspar crystals that underwent separation for the application of 40Ar/39Ar dating was investigated for geochemical inhomogeneities. Magmatic zoning is ubiquitous in the volcaniclastic feldspar crystals. Four different types of magmatic zoning were detected. The zoning types are compositional zoning (C-type zoning), pseudo-oscillatory zoning of trace ele- ment concentrations (PO-type zoning), chaotic and patchy zoning of major and trace element concentrations (R-type zoning) and concentric zoning of trace elements (CC-type zoning). Sam- ples that deviated in 40Ar/39Ar ages showed C-type zoning, R-type zoning or a mix of different types of zoning (C-type and PO-type). Feldspars showing PO-type zoning typically represent the smallest grain size fractions in the samples. The constant major element compositions of these crystals are interpreted to represent the latest stages in the compositional evolution of feldspars in a peralkaline melt. PO-type crystals contain less melt- inclusions than other zoning types and are rarely corroded. This thesis concludes that feldspars that show PO-type zoning are most promising chronometers for the 40Ar/39Ar method, if samples provide mixed zoning types of Quaternary anorthoclase feldspars.
Five samples were dated by applying the 40Ar/39Ar method to volcanic glass. High fractions of atmospheric Ar (typically > 98%) significantly hampered the precision of the 40Ar/39Ar ages and resulted in rough age estimates that widely overlap the age model. Ar isotopes indicated that the glasses bore a chorine-rich Ar-end member. The chlorine-derived 38Ar indicated chlorine-rich fluid-inclusions or the hydration of the volcanic glass shards. This indication strengthened the evidence that irregularly distributed melt-inclusions and thus irregular distributed excess 40Ar influenced the problematic feldspar 40Ar/39Ar ages. Whether a connection between a corrected initial 40Ar/36Ar ratio from glasses to the 40Ar/36Ar ratios from pore waters exists remains unclear.
This thesis offers another age model, which is similarly based on the interpolation of the temporal tie points from geophysical and climate-stratigraphic data. The model used a PCHIP- interpolation (piecewise cubic hermite interpolating polynomial) whereas the older age model used a spline-interpolation. Samples that match in ages from 40Ar/39Ar dating of feldspars with the earlier published age model were additionally assigned with an age from the PCHIP- interpolation. These modelled ages allowed a recalculation of the Alder Creek sanidine mineral standard. The climate-stratigraphic calibration of an 40Ar/39Ar mineral standard proved that the age versus depth interpolations from PAELOVAN drilling cores were accurate, and that the applied chronometers recorded the temporal evolution of Lake Van synchronously.
Petrochemical discrimination of the sampled volcaniclastic material is also given in this thesis. 41 from 57 sampled volcaniclastic layers indicate Nemrut as their provenance. Criteria that served for the provenance assignment are provided and reviewed critically. Detailed correlations of selected PALEOVAN volcaniclastics to onshore samples that were described in detail by earlier studies are also discussed. The sampled volcaniclastics dominantly have a thickness of < 40 cm and have been ejected by small to medium sized eruptions. Onshore deposits from these types of eruptions are potentially eroded due to predominant strong winds on Nemrut and Süphan slopes. An exact correlation with the data presented here is therefore equivocal or not possible at all.
Deviating feldspar 40Ar/39Ar ages can possibly be explained by inherited 40Ar from feldspar xenocrysts contaminating the samples. In order to test this hypothesis diffusion couples of Ba were investigated in compositionally zoned feldspar crystals. The diffusive behaviour of Ba in feldspar is known, and gradients in the changing concentrations allowed for the calculation of the duration of the crystal’s magmatic development since the formation of the zoning interface. Durations were compared with degassing scenarios that model the Ar-loss during assimilation and subsequent ejection of the xenocrystals. Diffusive equilibration of the contrasting Ba concentrations is assumed to generate maximum durations as the gradient could have been developed in several growth and heating stages. The modelling does not show any indication of an involvement of inherited 40Ar in any of the deviating samples. However, the analytical set-up represents the lower limit of the required spatial resolution. Therefore, it cannot be excluded that the degassing modelling relies on a significant overestimation of the maximum duration of the magmatic history. Nevertheless, the modelling of xenocrystal degassing evidences that the irregular incorporation of excess 40Ar by melt- and fluid inclusions represents the most critical problem that needs to be overcome in dating volcaniclastic feldspars from the PALEOVAN drill cores. This thesis provides the complete background in generating and presenting 40Ar/39Ar ages that are compared to age data from a climate-stratigraphic model. Deviations are identified statistically and then discussed in order to find explanations from the age model and/or from 40Ar/39Ar geochronology. Most of the PALEOVAN stratigraphy provides several chronometers that have been proven for their synchronicity. Lacustrine deposits from Lake Van represent a key archive for reconstructing climate evolution in the eastern Mediterranean and in the Near East. The PALEOVAN record offers a climate-stratigraphic age model with a remarkable accuracy and resolution.
Hepcidin-25 (Hep-25) plays a crucial role in the control of iron homeostasis. Since the dysfunction of the hepcidin pathway leads to multiple diseases as a result of iron imbalance, hepcidin represents a potential target for the diagnosis and treatment of disorders of iron metabolism. Despite intense research in the last decade targeted at developing a selective immunoassay for iron disorder diagnosis and treatment and better understanding the ferroportin-hepcidin interaction, questions remain. The key to resolving these underlying questions is acquiring exact knowledge of the 3D structure of native Hep-25. Since it was determined that the N-terminus, which is responsible for the bioactivity of Hep-25, contains a small Cu(II)-binding site known as the ATCUN motif, it was assumed that the Hep-25-Cu(II) complex is the native, bioactive form of the hepcidin. This structure has thus far not been elucidated in detail. Owing to the lack of structural information on metal-bound Hep-25, little is known about its possible biological role in iron metabolism. Therefore, this work is focused on structurally characterizing the metal-bound Hep-25 by NMR spectroscopy and molecular dynamics simulations. For the present work, a protocol was developed to prepare and purify properly folded Hep-25 in high quantities. In order to overcome the low solubility of Hep-25 at neutral pH, we introduced the C-terminal DEDEDE solubility tag. The metal binding was investigated through a series of NMR spectroscopic experiments to identify the most affected amino acids that mediate metal coordination. Based on the obtained NMR data, a structural calculation was performed in order to generate a model structure of the Hep-25-Ni(II) complex. The DEDEDE tag was excluded from the structural calculation due to a lack of NMR restraints. The dynamic nature and fast exchange of some of the amide protons with solvent reduced the overall number of NMR restraints needed for a high-quality structure. The NMR data revealed that the 20 Cterminal Hep-25 amino acids experienced no significant conformational changes, compared to published results, as a result of a pH change from pH 3 to pH 7 and metal binding. A 3D model of the Hep-25-Ni(II) complex was constructed from NMR data recorded for the hexapeptideNi(II) complex and Hep-25-DEDEDE-Ni(II) complex in combination with the fixed conformation of 19 C-terminal amino acids. The NMR data of the Hep-25-DEDEDE-Ni(II) complex indicates that the ATCUN motif moves independently from the rest of the structure. The 3D model structure of the metal-bound Hep-25 allows for future works to elucidate hepcidin’s interaction with its receptor ferroportin and should serve as a starting point for the development of antibodies with improved selectivity.
3D from 2D touch
(2013)
While interaction with computers used to be dominated by mice and keyboards, new types of sensors now allow users to interact through touch, speech, or using their whole body in 3D space. These new interaction modalities are often referred to as "natural user interfaces" or "NUIs." While 2D NUIs have experienced major success on billions of mobile touch devices sold, 3D NUI systems have so far been unable to deliver a mobile form factor, mainly due to their use of cameras. The fact that cameras require a certain distance from the capture volume has prevented 3D NUI systems from reaching the flat form factor mobile users expect. In this dissertation, we address this issue by sensing 3D input using flat 2D sensors. The systems we present observe the input from 3D objects as 2D imprints upon physical contact. By sampling these imprints at very high resolutions, we obtain the objects' textures. In some cases, a texture uniquely identifies a biometric feature, such as the user's fingerprint. In other cases, an imprint stems from the user's clothing, such as when walking on multitouch floors. By analyzing from which part of the 3D object the 2D imprint results, we reconstruct the object's pose in 3D space. While our main contribution is a general approach to sensing 3D input on 2D sensors upon physical contact, we also demonstrate three applications of our approach. (1) We present high-accuracy touch devices that allow users to reliably touch targets that are a third of the size of those on current touch devices. We show that different users and 3D finger poses systematically affect touch sensing, which current devices perceive as random input noise. We introduce a model for touch that compensates for this systematic effect by deriving the 3D finger pose and the user's identity from each touch imprint. We then investigate this systematic effect in detail and explore how users conceptually touch targets. Our findings indicate that users aim by aligning visual features of their fingers with the target. We present a visual model for touch input that eliminates virtually all systematic effects on touch accuracy. (2) From each touch, we identify users biometrically by analyzing their fingerprints. Our prototype Fiberio integrates fingerprint scanning and a display into the same flat surface, solving a long-standing problem in human-computer interaction: secure authentication on touchscreens. Sensing 3D input and authenticating users upon touch allows Fiberio to implement a variety of applications that traditionally require the bulky setups of current 3D NUI systems. (3) To demonstrate the versatility of 3D reconstruction on larger touch surfaces, we present a high-resolution pressure-sensitive floor that resolves the texture of objects upon touch. Using the same principles as before, our system GravitySpace analyzes all imprints and identifies users based on their shoe soles, detects furniture, and enables accurate touch input using feet. By classifying all imprints, GravitySpace detects the users' body parts that are in contact with the floor and then reconstructs their 3D body poses using inverse kinematics. GravitySpace thus enables a range of applications for future 3D NUI systems based on a flat sensor, such as smart rooms in future homes. We conclude this dissertation by projecting into the future of mobile devices. Focusing on the mobility aspect of our work, we explore how NUI devices may one day augment users directly in the form of implanted devices.
Shape change is a fundamental process occurring in biological tissues during embryonic development and regeneration of tissues and organs. This process is regulated by cells that are constrained within a complex environment of biochemical and physical cues. The spatial constraint due to geometry has a determining role on tissue mechanics and the spatial distribution of force patterns that, in turn, influences the organization of the tissue structure. An understanding of the underlying principles of tissue organization may have wide consequences for the understanding of healing processes and the development of organs and, as such, is of fundamental interest for the tissue engineering community.
This thesis aims to further our understanding of how the collective behaviour of cells is influenced by the 3D geometry of the environment. Previous research studying the role of geometry on tissue growth has mainly focused either on flat surfaces or on substrates where at least one of the principal curvatures is zero. In the present work, tissue growth from MC3T3-E1 pre-osteoblasts was investigated on surfaces of controlled mean curvature.
One key aspect of this thesis was the development of substrates of controlled mean curvature and their visualization in 3D. It was demonstrated that substrates of controlled mean curvature suitable for cell culture can be fabricated using liquid polymers and surface tension effects.
Using these substrates, it was shown that the mean surface curvature has a strong impact on the rate of tissue growth and on the organization of the tissue structure. It was thereby not only demonstrated that the amount of tissue produced (i.e. growth rates) by the cells depends on the mean curvature of the substrate but also that the tissue surface behaves like a viscous fluid with an equilibrium shape governed by the Laplace-Young-law. It was observed that more tissue was formed on highly concave surfaces compared to flat or convex surfaces.
Motivated by these observations, an analytical model was developed, where the rate of tissue growth is a function of the mean curvature, which could successfully describe the growth kinetics. This model was also able to reproduce the growth kinetics of previous experiments where tissues have been cultured in straight-sided prismatic pores.
A second part of this thesis focuses on the tissue structure, which influences the mechanical properties of the mature bone tissue. Since the extracellular matrix is produced by the cells, the cell orientation has a strong impact on the direction of the tissue fibres. In addition, it was recently shown that some cell types exhibit collective alignment similar to liquid crystals.
Based on this observation, a computational model of self-propelled active particles was developed to explore in an abstract manner how the collective behaviour of cells is influenced by 3D curvature. It was demonstrated that the 3D curvature has a strong impact on the self-organization of active particles and gives, therefore, first insights into the principles of self-organization of cells on curved surfaces.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
The Earth’s shallow subsurface with sedimentary cover acts as a waveguide to any incoming wavefield. Within the framework of my thesis, I focused on the characterization of this shallow subsurface within tens to few hundreds of meters of sediment cover. I imaged the seismic 1D shear wave velocity (and possibly the 1D compressional wave velocity). This information is not only required for any seismic risk assessment, geotechnical engineering or microzonation activities, but also for exploration and global seismology where site effects are often neglected in seismic waveform modeling.
First, the conventional frequency-wavenumber (f - k) technique is used to derive the dispersion characteristic of the propagating surface waves recorded using distinct arrays of seismometers in 1D and 2D configurations. Further, the cross-correlation technique is applied to seismic array data to estimate the Green’s function between receivers pairs combination assuming one is the source and the other the receiver. With the consideration of a 1D media, the estimated cross-correlation Green’s functions are sorted with interstation distance in a virtual 1D active seismic experiment. The f - k technique is then used to estimate the dispersion curves. This integrated analysis is important for the interpretation of a large bandwidth of the phase velocity dispersion curves and therefore improving the resolution of the estimated 1D Vs profile.
Second, the new theoretical approach based on the Diffuse Field Assumption (DFA) is used for the interpretation of the observed microtremors H/V spectral ratio. The theory is further extended in this research work to include not only the interpretation of the H/V measured at the surface, but also the H/V measured at depths and in marine environments. A modeling and inversion of synthetic H/V spectral ratio curves on simple predefined geological structures shows an almost perfect recovery of the model parameters (mainly Vs and to a lesser extent Vp). These results are obtained after information from a receiver at depth has been considered in the inversion.
Finally, the Rayleigh wave phase velocity information, estimated from array data, and the H/V(z, f) spectral ratio, estimated from a single station data, are combined and inverted for the velocity profile information. Obtained results indicate an improved depth resolution in comparison to estimations using the phase velocity dispersion curves only. The overall estimated sediment thickness is comparable to estimations obtained by inverting the full micortremor H/V spectral ratio.
Participation has become an orthodoxy in the field of development, an essential element of projects and programmes. This book analyses participation in development interventions as an institutionalised expectation – a rationalized myth – and examines how organisations on different levels of government process it. At least two different objectives of participation are appropriate and legitimate for international organisations in the field: the empowerment of local beneficiaries and the achievement of programme goals. Both integrate participatory forums into the organisational logic of development interventions. Local administrations react to the institutionalised expectation with means-ends decoupling, where participatory forums are implemented superficially but de facto remain marginalised in local administrative processes and activities. The book furthermore provides a thick description of the organisationality of participation in development interventions. Participatory forums are shown to be a form of partial organisation. They establish an order in the relationship between administrations and citizens through the introduction of rules and the creation of a defined membership. At the same time, this order is found to be fragile and subject to criticism and negotiation.
Nanostructured inorganic materials are routinely synthesized by the use of templates. Depending on the synthesis conditions of the product material, either “soft” or “hard” templates can be applied. For sol-gel processes, usually “soft” templating techniques are employed, while “hard” templates are used for high temperature synthesis pathways. In classical templating approaches, the template has the unique role of structure directing agent, in the sense that it is not participating to the chemical formation of the resulting material. This work investigates a new templating pathway to nanostructured materials, where the template is also a reagent in the formation of the final material. This concept is described as “reactive templating” and opens a synthetic path toward materials which cannot be synthesised on a nanometre scale by classical templating approaches. Metal nitrides are such kind of materials. They are usually produced by the conversion of metals or metal oxides in ammonia flow at high temperature (T > 1000°C), which make the application of classical templating techniques difficult. Graphitic carbon nitride, g-C3N4, despite its fundamental and theoretical importance, is probably one of the most promising materials to complement carbon in material science and many efforts are put in the synthesis of this material. A simple polyaddition/elimination reaction path at high temperature (T = 550°C) allows the polymerisation of cyanamide toward graphitic carbon nitride solids. By hard templating, using nanostructured silica or aluminium oxide as nanotemplates, a variety of nanostructured graphitic carbon nitrides such as nanorods, nanotubes, meso- and macroporous powders could be obtained by nanocasting or nanocoating. Due to the special semi-conducting properties of the graphitic carbon nitride matrix, the nanostructured graphitic carbon nitrides show unexpected catalytic activity for the activation of benzene in Friedel-Crafts type reactions, making this material an interesting metal free catalyst. Furthermore, due to the chemical composition of g-C3N4 and the fact that it is totally decomposed at temperatures between 600°C and 800°C even under inert atmosphere, g-C3N4 was shown to be a good nitrogen donor for the synthesis of early transition metal nitrides at high temperatures. Thus using the nanostructured carbon nitrides as “reactive templates” or “nanoreactors”, various metal nitride nanostructures, such as nanoparticles and porous frameworks could be obtained at high temperature. In this approach the carbon nitride nanostructure played both the role of the nitrogen source and of the exotemplate, imprinting its size and shape to the resulting metal nitride nanostructure.