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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.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
Localisation of deformation is a ubiquitous feature in continental rift dynamics and observed across drastically different time and length scales. This thesis comprises one experimental and two numerical modelling studies investigating strain localisation in (1) a ductile shear zone induced by a material heterogeneity and (2) in an active continental rift setting. The studies are related by the fact that the weakening mechanisms on the crystallographic and grain size scale enable bulk rock weakening, which fundamentally enables the formation of shear zones, continental rifts and hence plate tectonics. Aiming to investigate the controlling mechanisms on initiation and evolution of a shear zone, the torsion experiments of the experimental study were conducted in a Patterson type apparatus with strong Carrara marble cylinders with a weak, planar Solnhofen limestone inclusion. Using state-of-the-art numerical modelling software, the torsion experiments were simulated to answer questions regarding localisation procedure like stress distribution or the impact of rheological weakening. 2D numerical models were also employed to integrate geophysical and geological data to explain characteristic tectonic evolution of the Southern and Central Kenya Rift. Key elements of the numerical tools are a randomized initial strain distribution and the usage of strain softening. During the torsion experiments, deformation begins to localise at the limestone inclusion tips in a process zone, which propagates into the marble matrix with increasing deformation until a ductile shear zone is established. Minor indicators for coexisting brittle deformation are found close to the inclusion tip and presumed to slightly facilitate strain localisation besides the dominant ductile deformation processes. The 2D numerical model of the torsion experiment successfully predicts local stress concentration and strain rate amplification ahead of the inclusion in first order agreement with the experimental results. A simple linear parametrization of strain weaking enables high accuracy reproduction of phenomenological aspects of the observed weakening. The torsion experiments suggest that loading conditions do not affect strain localisation during high temperature deformation of multiphase material with high viscosity contrasts. A numerical simulation can provide a way of analysing the process zone evolution virtually and extend the examinable frame. Furthermore, the nested structure and anastomosing shape of an ultramylonite band was mimicked with an additional second softening step. Rheological weakening is necessary to establish a shear zone in a strong matrix around a weak inclusion and for ultramylonite formation.
Such strain weakening laws are also incorporated into the numerical models of the
Southern and Central Kenya Rift that capture the characteristic tectonic evolution. A three-stage early rift evolution is suggested that starts with (1) the accommodation of strain by a single border fault and flexure of the hanging-wall crust, after which (2) faulting in the hanging-wall and the basin centre increases before (3) the early-stage asymmetry is lost and basinward localisation of deformation occurs. Along-strike variability of rifts can be produced by modifying the initial random noise distribution. In summary, the three studies address selected aspects of the broad range of mechanisms and processes that fundamentally enable the deformation of rock and govern the localisation patterns across the scales. In addition to the aforementioned results, the first and second manuscripts combined, demonstrate a procedure to find new or improve on existing numerical formulations for specific rheologies and their dynamic weakening. These formulations are essential in addressing rock deformation from the grain to the global scale. As within the third study of this thesis, where geodynamic controls on the evolution of a rift were examined and acquired by the integration of geological and geophysical data into a numerical model.
The protein fraction, important for coffee cup quality, is modified during post-harvest treatment prior to roasting. Proteins may interact with phenolic compounds, which constitute the major metabolites of coffee, where the processing affects these interactions. This allows the hypothesis that the proteins are denatured and modified via enzymatic and/or redox activation steps. The present study was initiated to encompass changes in the protein fraction. The investigations were limited to major storage protein of green coffee beans. Fourteen Coffea arabica samples from various processing methods and countries were used. Different extraction protocols were compared to maintain the status quo of the protein modification. The extracts contained about 4–8 µg of chlorogenic acid derivatives per mg of extracted protein. High-resolution chromatography with multiple reaction monitoring was used to detect lysine modifications in the coffee protein. Marker peptides were allocated for the storage protein of the coffee beans. Among these, the modified peptides K.FFLANGPQQGGK.E and R.LGGK.T of the α-chain and R.ITTVNSQK.I and K.VFDDEVK.Q of β-chain were detected. Results showed a significant increase (p < 0.05) of modified peptides from wet processed green beans as compared to the dry ones. The present study contributes to a better understanding of the influence of the different processing methods on protein quality and its role in the scope of coffee cup quality and aroma. View Full-Text
The development of novel programmable materials aiming to control friction in real-time holds potential to facilitate innovative lubrication solutions for reducing wear and energy losses. This work describes the integration of light-responsiveness into two lubricating materials, silicon oils and polymer brush surfaces.
The first part focusses on the assessment on 9-anthracene ester-terminated polydimethylsiloxanes (PDMS-A) and, in particular, on the variability of rheological properties and the implications that arise with UV-light as external trigger. The applied rheometer setup contains an UV-transparent quartz-plate, which enables radiation and simultaneous measurement of the dynamic moduli. UV-A radiation (354 nm) triggers the cycloaddition reaction between the terminal functionalities of linear PDMS, resulting in chain extension. The newly-formed anthracene dimers cleave by UV-C radiation (254 nm) or at elevated temperatures (T > 130 °C). The sequential UV-A radiation and thermal reprogramming over three cycles demonstrate high conversions and reproducible programming of rheological properties. In contrast, the photochemical back reaction by UV-C is incomplete and can only partially restore the initial rheological properties. The dynamic moduli increase with each cycle in photochemical programming, presumably resulting from a chain segment re-arrangement as a result of the repeated partial photocleavage and subsequent chain length-dependent dimerization. In addition, long periods of radiation cause photooxidative degradation, which damages photo-responsive functions and consequently reduces the programming range. The absence of oxygen, however, reduces undesired side reactions. Anthracene-functionalized PDMS and native PDMS mix depending on the anthracene ester content and chain length, respectively, and allow fine-tuning of programmable rheological properties. The work shows the influence of mixing conditions during the photoprogramming step on the rheological properties, indicating that material property gradients induced by light attenuation along the beam have to be considered. Accordingly, thin lubricant films are suggested as potential application for light-programmable silicon fluids.
The second part compares strategies for the grafting of spiropyran (SP) containing copolymer brushes from Si wafers and evaluates the light-responsiveness of the surfaces. Pre-experiments on the kinetics of the thermally initiated RAFT copolymerization of 2-hydroxyethyl acrylate (HEA) and spiropyran acrylate (SPA) in solution show, first, a strong retardation by SP and, second, the dependence of SPA polymerization on light. Surprisingly, the copolymerization of SPA is inhibited in the dark. These findings contribute to improve the synthesis of polar, spiropyran-containing copolymers. The comparison between initiator systems for the grafting-from approach indicates PET-RAFT superior to thermally initiated RAFT, suggesting a more efficient initiation of surface-bound CTA by light. Surface-initiated polymerization via PET-RAFT with an initiator system of EosinY (EoY) and ascorbic acid (AscA) facilitates copolymer synthesis from HEA and 5-25 mol% SPA. The resulting polymer film with a thickness of a few nanometers was detected by atomic force microscopy (AFM) and ellipsometry. Water contact angle (CA) measurements demonstrate photo-switchable surface polarity, which is attributed to the photoisomerization between non-polar spiropyran and zwitterionic merocyanine isomer. Furthermore, the obtained spiropyran brushes show potential for further studies on light-programmable properties. In this context, it would be interesting to investigate whether swollen spiropyran-containing polymers change their configuration and thus their film thickness under the influence of light. In addition, further experiments using an AFM or microtribometer should evaluate whether light-programmable solvation enables a change in frictional properties between polymer brush surfaces.
The echo chamber model describes the development of groups in heterogeneous social networks. By heterogeneous social network we mean a set of individuals, each of whom represents exactly one opinion. The existing relationships between individuals can then be represented by a graph. The echo chamber model is a time-discrete model which, like a board game, is played in rounds. In each round, an existing relationship is randomly and uniformly selected from the network and the two connected individuals interact. If the opinions of the individuals involved are sufficiently similar, they continue to move closer together in their opinions, whereas in the case of opinions that are too far apart, they break off their relationship and one of the individuals seeks a new relationship. In this paper we examine the building blocks of this model. We start from the observation that changes in the structure of relationships in the network can be described by a system of interacting particles in a more abstract space.
These reflections lead to the definition of a new abstract graph that encompasses all possible relational configurations of the social network. This provides us with the geometric understanding necessary to analyse the dynamic components of the echo chamber model in Part III. As a first step, in Part 7, we leave aside the opinions of the inidividuals and assume that the position of the edges changes with each move as described above, in order to obtain a basic understanding of the underlying dynamics. Using Markov chain theory, we find upper bounds on the speed of convergence of an associated Markov chain to its unique stationary distribution and show that there are mutually identifiable networks that are not apparent in the dynamics under analysis, in the sense that the stationary distribution of the associated Markov chain gives equal weight to these networks.
In the reversible cases, we focus in particular on the explicit form of the stationary distribution as well as on the lower bounds of the Cheeger constant to describe the convergence speed.
The final result of Section 8, based on absorbing Markov chains, shows that in a reduced version of the echo chamber model, a hierarchical structure of the number of conflicting relations can be identified.
We can use this structure to determine an upper bound on the expected absorption time, using a quasi-stationary distribution. This hierarchy of structure also provides a bridge to classical theories of pure death processes. We conclude by showing how future research can exploit this link and by discussing the importance of the results as building blocks for a full theoretical understanding of the echo chamber model. Finally, Part IV presents a published paper on the birth-death process with partial catastrophe. The paper is based on the explicit calculation of the first moment of a catastrophe. This first part is entirely based on an analytical approach to second degree recurrences with linear coefficients. The convergence to 0 of the resulting sequence as well as the speed of convergence are proved. On the other hand, the determination of the upper bounds of the expected value of the population size as well as its variance and the difference between the determined upper bound and the actual value of the expected value. For these results we use almost exclusively the theory of ordinary nonlinear differential equations.
Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
Plate tectonics describes the movement of rigid plates at the surface of the Earth as well as their complex deformation at three types of plate boundaries: 1) divergent boundaries such as rift zones and mid-ocean ridges, 2) strike-slip boundaries where plates grind past each other, such as the San Andreas Fault, and 3) convergent boundaries that form large mountain ranges like the Andes. The generally narrow deformation zones that bound the plates exhibit complex strain patterns that evolve through time. During this evolution, plate boundary deformation is driven by tectonic forces arising from Earth’s deep interior and from within the lithosphere, but also by surface processes, which erode topographic highs and deposit the resulting sediment into regions of low elevation. Through the combination of these factors, the surface of the Earth evolves in a highly dynamic way with several feedback mechanisms. At divergent boundaries, for example, tensional stresses thin the lithosphere, forcing uplift and subsequent erosion of rift flanks, which creates a sediment source. Meanwhile, the rift center subsides and becomes a topographic low where sediments accumulate. This mass transfer from foot- to hanging wall plays an important role during rifting, as it prolongs the activity of individual normal faults. When rifting continues, continents are eventually split apart, exhuming Earth’s mantle and creating new oceanic crust. Because of the complex interplay between deep tectonic forces that shape plate boundaries and mass redistribution at the Earth’s surface, it is vital to understand feedbacks between the two domains and how they shape our planet.
In this study I aim to provide insight on two primary questions: 1) How do divergent and strike-slip plate boundaries evolve? 2) How is this evolution, on a large temporal scale and a smaller structural scale, affected by the alteration of the surface through erosion and deposition? This is done in three chapters that examine the evolution of divergent and strike-slip plate boundaries using numerical models. Chapter 2 takes a detailed look at the evolution of rift systems using two-dimensional models. Specifically, I extract faults from a range of rift models and correlate them through time to examine how fault networks evolve in space and time. By implementing a two-way coupling between the geodynamic code ASPECT and landscape evolution code FastScape, I investigate how the fault network and rift evolution are influenced by the system’s erosional efficiency, which represents many factors like lithology or climate. In Chapter 3, I examine rift evolution from a three-dimensional perspective. In this chapter I study linkage modes for offset rifts to determine when fast-rotating plate-boundary structures known as continental microplates form. Chapter 4 uses the two-way numerical coupling between tectonics and landscape evolution to investigate how a strike-slip boundary responds to large sediment loads, and whether this is sufficient to form an entirely new type of flexural strike-slip basin.
We investigate the effect of the COVID-19 pandemic on self-employed people’s mental health. Using representative longitudinal survey data from Germany, we reveal differential effects by gender: whereas self-employed women experienced a substantial deterioration in their mental health, self-employed men displayed no significant changes up to early 2021. Financial losses are important in explaining these differences. In addition, we find larger mental health responses among self-employed women who were directly affected by government-imposed restrictions and bore an increased childcare burden due to school and daycare closures. We also find that self-employed individuals who are more resilient coped better with the crisis.
In light of climate change mitigation efforts, revenues from climate policies are growing, with no consensus yet on how they should be used. Potential efficiency gains from reducing distortionary taxes and the distributional implications of different revenue recycling schemes are currently debated. To account for households heterogeneity and dynamic trade-offs, we study the macroeconomic and welfare performance of different revenue recycling schemes using an Environmental Two-Agent New-Keynesian model, calibrated on the German economy. We find that, in the long run, welfare gains are higher when revenues are used to reduce distortionary taxes on capital, but this comes at the cost of higher inequality: while all households prefer labor income tax reductions to lump-sum transfers, only financially unconstrained households are better off when reducing taxes on capital income. Interestingly, we find that over the transition period relevant to meet short-medium run climate targets, labor income tax cuts are the most efficient and equitable instrument.
Salt deposits offer a variety of usage types. These include the mining of rock salt and potash salt as important raw materials, the storage of energy in man-made underground caverns, and the disposal of hazardous substances in former mines. The most serious risk with any of these usage types comes from the contact with groundwater or surface water. It causes an uncontrolled dissolution of salt rock, which in the worst case can result in the flooding or collapse of underground facilities. Especially along potash seams, cavernous structures can spread quickly, because potash salts show a much higher solubility than rock salt. However, as their chemical behavior is quite complex, previous models do not account for these highly soluble interlayers. Therefore, the objective of the present thesis is to describe the evolution of cavernous structures along potash seams in space and time in order to improve hazard mitigation during the utilization of salt deposits.
The formation of cavernous structures represents an interplay of chemical and hydraulic processes. Hence, the first step is to systematically investigate the dissolution and precipitation reactions that occur when water and potash salt come into contact. For this purpose, a geochemical reaction model is used. The results show that the minerals are only partially dissolved, resulting in a porous sponge like structure. With the saturation of the solution increasing, various secondary minerals are formed, whose number and type depend on the original rock composition. Field data confirm a correlation between the degree of saturation and the distance from the center of the cavern, where solution is entering. Subsequently, the reaction model is coupled with a flow and transport code and supplemented by a novel approach called ‘interchange’. The latter enables the exchange of solution and rock between areas of different porosity and mineralogy, and thus ultimately the growth of the cavernous structure. By means of several scenario analyses, cavern shape, growth rate and mineralogy are systematically investigated, taking also heterogeneous potash seams into account. The results show that basically four different cases can be distinguished, with mixed forms being a frequent occurrence in nature. The classification scheme is based on the dimensionless numbers Péclet and Damköhler, and allows for a first assessment of the hazard potential. In future, the model can be applied to any field case, using measurement data for calibration.
The presented research work provides a reactive transport model that is able to spatially and temporally characterize the propagation of cavernous structures along potash seams for the first time. Furthermore, it allows to determine thickness and composition of transition zones between cavern center and unaffected salt rock. The latter is particularly important in potash mining, so that natural cavernous structures can be located at an early stage and the risk of mine flooding can thus be reduced. The models may also contribute to an improved hazard prevention in the construction of storage caverns and the disposal of hazardous waste in salt deposits. Predictions regarding the characteristics and evolution of cavernous structures enable a better assessment of potential hazards, such as integrity or stability loss, as well as of suitable mitigation measures.
»Plus outre« – immer weiter
(2022)
The key to reduce the energy required for specific transformations in a selective manner is the employment of a catalyst, a very small molecular platform that decides which type of energy to use. The field of photocatalysis exploits light energy to shape one type of molecules into others, more valuable and useful.
However, many challenges arise in this field, for example, catalysts employed usually are based on metal derivatives, which abundance is limited, they cannot be recycled and are expensive. Therefore, carbon nitrides materials are used in this work to expand horizons in the field of photocatalysis.
Carbon nitrides are organic materials, which can act as recyclable, cheap, non-toxic, heterogeneous photocatalysts. In this thesis, they have been exploited for the development of new catalytic methods, and shaped to develop new types of processes.
Indeed, they enabled the creation of a new photocatalytic synthetic strategy, the dichloromethylation of enones by dichloromethyl radical generated in situ from chloroform, a novel route for the making of building blocks to be used for the productions of active pharmaceutical compounds.
Then, the ductility of these materials allowed to shape carbon nitride into coating for lab vials, EPR capillaries, and a cell of a flow reactor showing the great potential of such flexible technology in photocatalysis.
Afterwards, their ability to store charges has been exploited in the reduction of organic substrates under dark conditions, gaining new insights regarding multisite proton coupled electron transfer processes.
Furthermore, the combination of carbon nitrides with flavins allowed the development of composite materials with improved photocatalytic activity in the CO2 photoreduction.
Concluding, carbon nitrides are a versatile class of photoactive materials, which may help to unveil further scientific discoveries and to develop a more sustainable future.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
Carbon dioxide removal (CDR) moves atmospheric carbon to geological or land-based sinks. In a first-best setting, the optimal use of CDR is achieved by a removal subsidy that equals the optimal carbon tax and marginal damages. We derive second-best subsidies for CDR when no global carbon price exists but a national government implements a unilateral climate policy. We find that the optimal carbon tax differs from an optimal CDR subsidy because of carbon leakage, terms-of-trade and fossil resource rent dynamics. First, the optimal removal subsidy tends to be larger than the carbon tax because of lower supply-side leakage on fossil resource markets. Second, terms-of-trade effects exacerbate this wedge for net resource exporters, implying even larger removal subsidies. Third, the optimal removal subsidy may fall below the carbon tax for resource-poor countries when marginal environmental damages are small.
Transitional Justice
(2022)
This publication deals with the topic of transitional justice. In six case studies, the authors link theoretical and practical implications in order to develop some innovative approaches. Their proposals might help to deal more effectively with the transition of societies, legal orders and political systems.
Young academics from various backgrounds provide fresh insights and demonstrate the relevance of the topic. The chapters analyse transitions and conflicts in Sierra Leone, Argentina, Nicaragua, Nepal, and South Sudan as well as Germany’s colonial genocide in Namibia. Thus, the book provides the reader with new insights and contributes to the ongoing debate about transitional justice.
Subsidizing the geographical mobility of unemployed workers may improve welfare by relaxing their financial constraints and allowing them to find jobs in more prosperous regions. We exploit regional variation in the promotion of mobility programs along administrative borders of German employment agency districts to investigate the causal effect of offering such financial incentives on the job search behavior and labor market integration of unemployed workers. We show that promoting mobility – as intended – causes job seekers to increase their search radius, apply for and accept distant jobs. At the same time, local job search is reduced with adverse consequences for reemployment and earnings. These unintended negative effects are provoked by spatial search frictions. Overall, the unconditional provision of mobility programs harms the welfare of unemployed job seekers.
The COVID-19 pandemic created the largest experiment in working from home. We study how persistent telework may change energy and transport consumption and costs in Germany to assess the distributional and environmental implications when working from home will stick. Based on data from the German Microcensus and available classifications of working-from-home feasibility for different occupations, we calculate the change in energy consumption and travel to work when 15% of employees work full time from home. Our findings suggest that telework translates into an annual increase in heating energy expenditure of 110 euros per worker and a decrease in transport expenditure of 840 euros per worker. All income groups would gain from telework but high-income workers gain twice as much as low-income workers. The value of time saving is between 1.3 and 6 times greater than the savings from reduced travel costs and almost 9 times higher for high-income workers than low-income workers. The direct effects on CO₂ emissions due to reduced car commuting amount to 4.5 millions tons of CO₂, representing around 3 percent of carbon emissions in the transport sector.