This working paper outlines analytical pathways that could contribute to deepening the understanding of water inequalities in cities of the Global South. It brings together the status quo of research on water inequalities in Accra, the capital of Ghana, and studies on Environmental Justice. In doing so, it argues for the need to analytically distinguish between the terms ‘(in)equality’ and ‘(in)justice’. Studying everyday water practices and per- spectives on water (in)justice of different stakeholders would be a suitable entry point for an in-depth ethnographic study that analytically separates water inequalities and water injustices but considers their interlinkages. The working paper is based on a literature review conducted in 2015 in the scope of the WaterPower project.

Behavioural traces from interactions with digital technologies are diverse and abundant. Yet, their capacity for theory-driven research is still to be constituted. In the present cumulative dissertation project, I deliberate the caveats and potentials of digital behavioural trace data in behavioural and social science research. One use case is online radicalisation research. The three studies included, set out to discern the state-of-the-art of methods and constructs employed in radicalization research, at the intersection of traditional methods and digital behavioural trace data. Firstly, I display, based on a systematic literature review of empirical work, the prevalence of digital behavioural trace data across different research strands and discern determinants and outcomes of radicalisation constructs. Secondly, I extract, based on this literature review, hypotheses and constructs and integrate them to a framework from network theory. This graph of hypotheses, in turn, makes the relative importance of theoretical considerations explicit. One implication of visualising the assumptions in the field is to systematise bottlenecks for the analysis of digital behavioural trace data and to provide the grounds for the genesis of new hypotheses. Thirdly, I provide a proof-of-concept for incorporating a theoretical framework from conspiracy theory research (as a specific form of radicalisation) and digital behavioural traces. I argue for marrying theoretical assumptions derived from temporal signals of posting behaviour and semantic meaning from textual content that rests on a framework from evolutionary psychology. In the light of these findings, I conclude by discussing important potential biases at different stages in the research cycle and practical implications.

Objective Our study investigated body image representations in female patients with anorexia nervosa and healthy controls using a size estimation with pictures of their own body. We also explored a method to reduce body image distortions through right hemispheric activation. Method Pictures of participants’ own bodies were shown on the left or right visual fields for 130 ms after presentation of neutral, positive, or negative word primes, which could be self-relevant or not, with the task of classifying the picture as “thinner than”, “equal to”, or “fatter than” one’s own body. Subsequently, activation of the left- or right hemispheric through right- or left-hand muscle contractions for 3 min., respectively. Finally, participants completed the size estimation task again. Results The distorted “fatter than” body image was found only in patients and only when a picture of their own body appeared on the right visual field (left hemisphere) and was preceded by negative self-relevant words. This distorted perception of the patients’ body image was reduced after left-hand muscle contractions (right hemispheric activation). Discussion To reduce body image distortions it is advisable to find methods that help anorexia nervosa patients to increase their self-esteem. The body image distortions were ameliorated after right hemispheric activation. A related method to prevent distorted body-image representations in these patients may be Eye Movement Desensitization and Reprocessing (EMDR) therapy.

In bilevel optimization, some of the variables of an optimization problem have to be an optimal solution to another nested optimization problem. This specific structure renders bilevel optimization a powerful tool for modeling hierarchical decision-making processes, which arise in various real-world applications such as in critical infrastructure defense, transportation, or energy. Due to their nested structure, however, bilevel problems are also inherently hard to solve—both in theory and in practice. Further challenges arise if, e.g., bilevel problems under uncertainty are considered. In this dissertation, we address different types of uncertainties in bilevel optimization using techniques from robust optimization. We study mixed-integer linear bilevel problems with lower-level objective uncertainty, which we tackle using the notion of Gamma-robustness. We present two exact branch-and-cut approaches to solve these Gamma-robust bilevel problems, along with cuts tailored to the important class of monotone interdiction problems. Given the overall hardness of the considered problems, we additionally propose heuristic approaches for mixed-integer, linear, and Gamma-robust bilevel problems. The latter rely on solving a linear number of deterministic bilevel problems so that no problem-specific tailoring is required. We assess the performance of both the exact and the heuristic approaches through extensive computational studies. In addition, we study the problem of determining optimal tolls in a traffic network in which the network users hedge against uncertain travel costs in a robust way. The overall toll-setting problem can be seen as a single-leader multi-follower problem with multiple robustified followers. We model this setting as a mathematical problem with equilibrium constraints, for which we present a mixed-integer, nonlinear, and nonconvex reformulation that can be tackled using state-of-the-art general-purpose solvers. We further illustrate the impact of considering robustified followers on the toll-setting policies through a case study. Finally, we highlight that the sources of uncertainty in bilevel optimization are much richer compared to single-level optimization. To this end, we study two aspects related to so-called decision uncertainty. First, we propose a strictly robust approach in which the follower hedges against erroneous observations of the leader's decision. Second, we consider an exemplary bilevel problem with a continuous but nonconvex lower level in which algorithmic necessities prevent the follower from making a globally optimal decision in an exact sense. The example illustrates that even very small deviations in the follower's decision may lead to arbitrarily large discrepancies between exact and computationally obtained bilevel solutions.

There is no longer any doubt about the general effectiveness of psychotherapy. However, up to 40% of patients do not respond to treatment. Despite efforts to develop new treatments, overall effectiveness has not improved. Consequently, practice-oriented research has emerged to make research results more relevant to practitioners. Within this context, patient-focused research (PFR) focuses on the question of whether a particular treatment works for a specific patient. Finally, PFR gave rise to the precision mental health research movement that is trying to tailor treatments to individual patients by making data-driven and algorithm-based predictions. These predictions are intended to support therapists in their clinical decisions, such as the selection of treatment strategies and adaptation of treatment. The present work summarizes three studies that aim to generate different prediction models for treatment personalization that can be applied to practice. The goal of Study I was to develop a model for dropout prediction using data assessed prior to the first session (N = 2543). The usefulness of various machine learning (ML) algorithms and ensembles was assessed. The best model was an ensemble utilizing random forest and nearest neighbor modeling. It significantly outperformed generalized linear modeling, correctly identifying 63.4% of all cases and uncovering seven key predictors. The findings illustrated the potential of ML to enhance dropout predictions, but also highlighted that not all ML algorithms are equally suitable for this purpose. Study II utilized Study I’s findings to enhance the prediction of dropout rates. Data from the initial two sessions and observer ratings of therapist interventions and skills were employed to develop a model using an elastic net (EN) algorithm. The findings demonstrated that the model was significantly more effective at predicting dropout when using observer ratings with a Cohen’s d of up to .65 and more effective than the model in Study I, despite the smaller sample (N = 259). These results indicated that generating models could be improved by employing various data sources, which provide better foundations for model development. Finally, Study III generated a model to predict therapy outcome after a sudden gain (SG) in order to identify crucial predictors of the upward spiral. EN was used to generate the model using data from 794 cases that experienced a SG. A control group of the same size was also used to quantify and relativize the identified predictors by their general influence on therapy outcomes. The results indicated that there are seven key predictors that have varying effect sizes on therapy outcome, with Cohen's d ranging from 1.08 to 12.48. The findings suggested that a directive approach is more likely to lead to better outcomes after an SG, and that alliance ruptures can be effectively compensated for. However, these effects were reversed in the control group. The results of the three studies are discussed regarding their usefulness to support clinical decision-making and their implications for the implementation of precision mental health.

Striving for sustainable development by combating climate change and creating a more social world is one of the most pressing issues of our time. Growing legal requirements and customer expectations require also Mittelstand firms to address sustainability issues such as climate change. This dissertation contributes to a better understanding of sustainability in the Mittelstand context by examining different Mittelstand actors and the three dimensions of sustainability - social, economic, and environmental sustainability - in four quantitative studies. The first two studies focus on the social relevance and economic performance of hidden champions, a niche market leading subgroup of Mittelstand firms. At the regional level, the impact of 1,645 hidden champions located in Germany on various dimensions of regional development is examined. A higher concentration of hidden champions has a positive effect on regional employment, median income, and patents. At the firm level, analyses of a panel dataset of 4,677 German manufacturing firms, including 617 hidden champions, show that the latter have a higher return on assets than other Mittelstand firms. The following two chapters deal with environmental strategies and thus contribute to the exploration of the environmental dimension of sustainability. First, the consideration of climate aspects in investment decisions is compared using survey data from 468 European venture capital and private equity investors. While private equity firms respond to external stakeholders and portfolio performance and pursue an active ownership strategy, venture capital firms are motivated by product differentiation and make impact investments. Finally, based on survey data from 443 medium-sized manufacturing firms in Germany, 54% of which are family-owned, the impact of stakeholder pressures on their decarbonization strategies is analyzed. A distinction is made between symbolic (compensation of CO₂-emissions) and substantive decarbonization strategies (reduction of CO₂-emissions). Stakeholder pressures lead to a proactive pursuit of decarbonization strategies, with internal and external stakeholders varying in their influence on symbolic and substantial decarbonization strategies, and the relationship influenced by family ownership.

This study focuses on the representation of British South Asian identities in contemporary British audiovisual media. It attempts to answer the question, whether these identities are represented as hybrid, heterogeneous and ambivalent, or whether these contemporary representations follow in the tradition of colonial and postcolonial racialism. Racialised depictions of British South Asians have been the norm not only in the colonial but also in the postcolonial era until the rise of the Black British movement, whose successes have been also acknowledged in the field of representation. However these achievements have to be scrutinized again, especially in the context of the post 9/11 world, rising Islamophobia, and new forms of institutionalized discrimination on the basis of religion. Since the majority of British Muslims are of South Asian origin, this study tries to answer the question whether the marker of religious origin is racial belonging, i.e. skin colour, and old stereotypes associated with the racialised representation are being perpetuated into current depictions through an examination of the varied genre of popular audio visual media texts.

The glucocorticoid (GC) cortisol, main mediator of the hypothalamic-pituitary-adrenal axis, has many implications in metabolism, stress response and the immune system. GC function is mediated mainly via the glucocorticoid receptor (GR) which binds as a transcription factor to glucocorticoid response elements (GREs). GCs are strong immunosuppressants and used to treat inflammatory and autoimmune diseases. Long-term usage can lead to several irreversible side effects which make improved understanding indispensable and warrant the adaptation of current drugs. Several large scale gene expression studies have been performed to gain insight into GC signalling. Nevertheless, studies at the proteomic level have not yet been made. The effects of cortisol on monocytes and macrophages were studied in the THP-1 cell line using 2D fluorescence difference gel electrophoresis (2D DIGE) combined with MALDI-TOF mass spectrometry. More than 50 cortisol-modulated proteins were identified which belonged to five functional groups: cytoskeleton, chaperones, immune response, metabolism, and transcription/translation. Multiple GREs were found in the promoters of their corresponding genes (+10 kb/-0.2 kb promoter regions including all alternative promoters available within the Database for Transcription Start Sites (DBTSS)). High quality GREs were observed mainly in cortisol modulated genes, corroborating the proteomics results. Differential regulation of selected immune response related proteins were confirmed by qPCR and immuno-blotting. All immune response related proteins (MX1, IFIT3, SYWC, STAT3, PMSE2, PRS7) which were induced by LPS were suppressed by cortisol and belong mainly to classical interferon target genes. Mx1 has been selected for detailed expression analysis since new isoforms have been identified by proteomics. FKBP51, known to be induced by cortisol, was identified as the strongest differentially expressed protein and contained the highest number of strict GREs. Genomic analysis of five alternative FKBP5 promoter regions suggested GC inducibility of all transcripts. 2D DIGE combined with 2D immunoblotting revealed the existence of several previously unknown FKBP51 isoforms, possibly resulting from these transcripts. Additionally multiple post-translational modifications were found, which could lead to different subcellular localization in monocytes and macrophages as seen by confocal microscopy. Similar results were obtained for the different cellular subsets of human peripheral blood mononuclear cells (PBMCs). FKBP51 was found to be constitutively phosphorylated with up to 8 phosphosites in CD19+ B lymphocytes. Differential Co-immunoprecipitation for cytoplasm and nucleus allowed us to identify new potential interaction partners. Nuclear FKBP51 was found to interact with myosin 9, whereas cytosolic FKBP51 with TRIM21 (synonym: Ro52, Sjögren`s syndrome antigen). The GR has been found to interact with THOC4 and YB1, two proteins implicated in mRNA processing and transcriptional regulation. We also applied proteomics to study rapid non-genomic effects of acute stress in a rat model. The nuclear proteome of the thymus was investigated after 15 min restraint stress and compared to the non-stressed control. Most of the identified proteins were transcriptional regulators found to be enriched in the nucleus probably to assist gene expression in an appropriate manner. The proteomic approach allowed us to further understand the cortisol mediated response in monocytes/macrophages. We identified several new target proteins, but we also found new protein variants and post-translational modifications which need further investigation. Detailed study of FKBP51 and GR indicated a complex regulation network which opened a new field of research. We identified new variants of the anti-viral response protein MX1, displaying differential expression and phosphorylation in the cellular compartments. Further, proteomics allowed us to follow the very early effects of acute stress, which happen prior to gene expression. The nuclear thymocyte proteome of restraint stressed rats revealed an active preparation for subsequent gene expression. Proteomics was successfully applied to study differential protein expression, to identify new protein variants and phosphorylation events as well as to follow translocation. New aspects for future research in the field of cortisol-mediated immune modulation have been added.

This work addresses the algorithmic tractability of hard combinatorial problems. Basically, we are considering \NP-hard problems. For those problems we can not find a polynomial time algorithm. Several algorithmic approaches already exist which deal with this dilemma. Among them we find (randomized) approximation algorithms and heuristics. Even though in practice they often work in reasonable time they usually do not return an optimal solution. If we constrain optimality then there are only two methods which suffice for this purpose: exponential time algorithms and parameterized algorithms. In the first approach we seek to design algorithms consuming exponentially many steps who are more clever than some trivial algorithm (who simply enumerates all solution candidates). Typically, the naive enumerative approach yields an algorithm with run time $\Oh^*(2^n)$. So, the general task is to construct algorithms obeying a run time of the form $\Oh^*(c^n)$ where $c<2$. The second approach considers an additional parameter $k$ besides the input size $n$. This parameter should provide more information about the problem and cover a typical characteristic. The standard parameterization is to see $k$ as an upper (lower, resp.) bound on the solution size in case of a minimization (maximization, resp.) problem. Then a parameterized algorithm should solve the problem in time $f(k)\cdot n^\beta$ where $\beta$ is a constant and $f$ is independent of $n$. In principle this method aims to restrict the combinatorial difficulty of the problem to the parameter $k$ (if possible). The basic hypothesis is that $k$ is small with respect to the overall input size. In both fields a frequent standard technique is the design of branching algorithms. These algorithms solve the problem by traversing the solution space in a clever way. They frequently select an entity of the input and create two new subproblems, one where this entity is considered as part of the future solution and another one where it is excluded from it. Then in both cases by fixing this entity possibly other entities will be fixed. If so then the traversed number of possible solution is smaller than the whole solution space. The visited solutions can be arranged like a search tree. To estimate the run time of such algorithms there is need for a method to obtain tight upper bounds on the size of the search trees. In the field of exponential time algorithms a powerful technique called Measure&Conquer has been developed for this purpose. It has been applied successfully to many problems, especially to problems where other algorithmic attacks could not break the trivial run time upper bound. On the other hand in the field of parameterized algorithms Measure&Conquer is almost not known. This piece of work will present examples where this technique can be used in this field. It also will point out what differences have to be made in order to successfully apply the technique. Further, exponential time algorithms for hard problems where Measure&Conquer is applied are presented. Another aspect is that a formalization (and generalization) of the notion of a search tree is given. It is shown that for certain problems such a formalization is extremely useful.

The present thesis is devoted to a construction which defies generalisations about the prototypical English noun phrase (NP) to such an extent that it has been termed the Big Mess Construction (Berman 1974). As illustrated by the examples in (1) and (2), the NPs under study involve premodifying adjective phrases (APs) which precede the determiner (always realised in the form of the indefinite article a(n)) rather than following it. (1) NoS had not been hijacked – that was too strong a word. (BNC: CHU 1766) (2) He was prepared for a battle if the porter turned out to be as difficult a customer as his wife. (BNC: CJX 1755) Previous research on the construction is largely limited to contributions from the realms of theoretical syntax and a number of cursory accounts in reference grammars. No comprehensive investigation of its realisations and uses has as yet been conducted. My thesis fills this gap by means of an exhaustive analysis of the construction on the basis of authentic language data retrieved from the British National Corpus (BNC). The corpus-based approach allows me to examine not only the possible but also the most typical uses of the construction. Moreover, while previous work has almost exclusively focused on the formal realisations of the construction, I investigate both its forms and functions. It is demonstrated that, while the construction is remarkably flexible as concerns its possible realisations, its use is governed by probabilistic constraints. For example, some items occur much more frequently inside the degree item slot than others (as, too and so stand out for their particularly high frequency). Contrary to what is assumed in most previous descriptions, the slot is not restricted in its realisation to a fixed number of items. Rather than representing a specialised structure, the construction is furthermore shown to be distributed over a wide range of possible text types and syntactic functions. On the other hand, it is found to be much less typical of spontaneous conversation than of written language; Big Mess NPs further display a strong preference for the function of subject complement. Investigations of the internal structural complexity of the construction indicate that its obligatory components can optionally be enriched by a remarkably wide range of optional (if infrequent) elements. In an additional analysis of the realisations of the obligatory but lexically variable slots (head noun and head of AP), the construction is highlighted to represent a productive pattern. With the help of the methods of Collexeme Analysis (Stefanowitsch and Gries 2003) and Co-varying Collexeme Analysis (Gries and Stefanowitsch 2004b, Stefanowitsch and Gries 2005), the two slots are, however, revealed to be strongly associated with general nouns and ‘evaluative’ and ‘dimension’ adjectives, respectively. On the basis of an inspection of the most typical adjective-noun combinations, I identify the prototypical semantics of the Big Mess Construction. The analyses of the constructional functions centre on two distinct functional areas. First, I investigate Bolinger’s (1972) hypothesis that the construction fulfils functions in line with the Principle of Rhythmic Alternation (e.g. Selkirk 1984: 11, Schlüter 2005). It is established that rhythmic preferences co-determine the use of the construction to some extent, but that they clearly do not suffice to explain the phenomenon under study. In a next step, the discourse-pragmatic functions of the construction are scrutinised. Big Mess NPs are demonstrated to perform distinct information-structural functions in that the non-canonical position of the AP serves to highlight focal information (compare De Mönnink 2000: 134-35). Additionally, the construction is shown to place emphasis on acts of evaluation. I conclude the construction to represent a contrastive focus construction. My investigations of the formal and functional characteristics of Big Mess NPs each include analyses which compare individual versions of the construction to one another (e.g. the As Big a Mess, Too Big a Mess and So Big a Mess Constructions). It is revealed that the versions are united by a shared core of properties while differing from one another at more abstract levels of description. The question of the status of the constructional versions as separate constructions further receives special emphasis as part of a discussion in which I integrate my results into the framework of usage-based Construction Grammar (e.g. Goldberg 1995, 2006).

N-acetylation by N-acetyltransferase 1 (NAT1) is an important biotransformation pathway of the human skin and it is involved in the deactivation of the arylamine and well-known contact allergen para-phenylenediamine (PPD). Here, NAT1 expression and activity were analyzed in antigen presenting cells (monocyte-derived dendritic cells, MoDCs, a model for epidermal Langerhans cells) and human keratinocytes. The latter were used to study exogenous and endogenous NAT1 activity modulations. Within this thesis, MoDCs were found to express metabolically active NAT1. Activities were between 23.4 and 26.6 nmol/mg/min and thus comparable to peripheral blood mononuclear cells. These data suggest that epidermal Langerhans cells contribute to the cutaneous N-acetylation capacity. Keratinocytes, which are known for their efficient N-acetylation, were analyzed in a comparative study using primary keratinocytes (NHEK) and different shipments of the immortalized keratinocyte cell line HaCaT, in order to investigate the ability of the cell line to model epidermal biotransformation. N-acetylation of the substrate para-aminobenzoic acid (PABA) was 3.4-fold higher in HaCaT compared to NHEK and varied between the HaCaT shipments (range 12.0"44.5 nmol/mg/min). Since B[a]P induced cytochrome p450 1 (CYP1) activities were also higher in HaCaT compared to NHEK, the cell line can be considered as an in vitro tool to qualitatively model epidermal metabolism, regarding NAT1 and CYP1. The HaCaT shipment with the highest NAT1 activity showed only minimal reduction of cell viability after treatment with PPD and was subsequently used to study interactions between NAT1 and PPD in keratinocytes. Treatment with PPD induced expression of cyclooxygenases (COX) in HaCaT, but in parallel, PPD N-acetylation was found to saturate with increasing PPD concentration. This saturation explains the presence of the PPD induced COX induction despite the high N-acetylation capacities. A detailed analysis of the effect of PPD on NAT1 revealed that the saturation of PPD N-acetylation was caused by a PPD-induced decrease of NAT1 activity. This inhibition was found in HaCaT as well as in primary keratinocytes after treatment with PPD and PABA. Regarding the mechanism, reduced NAT1 protein level and unaffected NAT1 mRNA expression after PPD treatment adduced clear evidences for substrate-dependent NAT1 downregulation. These results expand the existing knowledge about substrate-dependent NAT1 downregulation to human epithelial skin cells and demonstrate that NAT1 activity in keratinocytes can be modulated by exogenous factors. Further analysis of HaCaT cells from different shipments revealed an accelerated progression through the cell cycle in HaCaT cells with high NAT1 activities. These findings suggest an association between NAT1 and proliferation in keratinocytes as it has been proposed earlier for tumor cells. In conclusion, N-acetylation capacity of MoDCs as well as keratinocytes contribute to the overall N-acetylation capacity of human skin. NAT1 activity of keratinocytes and consequently the detoxification capacities of human skin can be modulated by the presence of exogenous NAT1 substrates and endogenous by the cell proliferation status of keratinocytes.

Statistical matching offers a way to broaden the scope of analysis without increasing respondent burden and costs. These would result from conducting a new survey or adding variables to an existing one. Statistical matching aims at combining two datasets A and B referring to the same target population in order to analyse variables, say Y and Z, together, that initially were not jointly observed. The matching is performed based on matching variables X that correspond to common variables present in both datasets A and B. Furthermore, Y is only observed in B and Z is only observed in A. To overcome the fact that no joint information on X, Y and Z is available, statistical matching procedures have to rely on suitable assumptions. Therefore, to yield a theoretical foundation for statistical matching, most procedures rely on the conditional independence assumption (CIA), i.e. given X, Y is independent of Z. The goal of this thesis is to encompass both the statistical matching process and the analysis of the matched dataset. More specifically, the aim is to estimate a linear regression model for Z given Y and possibly other covariates in data A. Since the validity of the assumptions underlying the matching process determine the validity of the obtained matched file, the accuracy of statistical inference is determined by the suitability of the assumptions. By putting the focus on these assumptions, this work proposes a systematic categorisation of approaches to statistical matching by relying on graphical representations in form of directed acyclic graphs. These graphs are particularly useful in representing dependencies and independencies which are at the heart of the statistical matching problem. The proposed categorisation distinguishes between (a) joint modelling of the matching and the analysis (integrated approach), and (b) matching subsequently followed by statistical analysis of the matched dataset (classical approach). Whereas the classical approach relies on the CIA, implementations of the integrated approach are only valid if they converge, i.e. if the specified models are identifiable and, in the case of MCMC implementations, if the algorithm converges to a proper distribution. In this thesis an implementation of the integrated approach is proposed, where the imputation step and the estimation step are jointly modelled through a fully Bayesian MCMC estimation. It is based on a linear regression model for Z given Y and accounts for both a linear regression model and a random effects model for Y. Furthermore, it yields its validity when the instrumental variable assumption (IVA) holds. The IVA corresponds to: (a) Z is independent of a subset X’ of X given Y and X*, where X* = X\X’ and (b) Y is correlated with X’ given X*. The proof, that the joint Bayesian modelling of both the model for Z and the model for Y through an MCMC simulation converges to a proper distribution is provided in this thesis. In a first model-based simulation study, the proposed integrated Bayesian procedure is assessed with regard to the data situation, convergence issues, and underlying assumptions. Special interest lies in the investigation of the interplay of the Y and the Z model within the imputation process. It turns out that failure scenarios can be distinguished by comparing the CIA and the IVA in the completely observed dataset. Finally, both approaches to statistical matching, i.e. the classical approach and the integrated approach, are subject to an extensive comparison in (1) a model-based simulation study and (2) a simulation study based on the AMELIA dataset, which is an openly available very large synthetic dataset and, by construction, similar to the EU-SILC survey. As an additional integrated approach, a Bayesian additive regression trees (BART) model is considered for modelling Y. These integrated procedures are compared to the classical approach represented by predictive mean matching in the form of multiple imputations by chained equation. Suitably chosen, the first simulation framework offers the possibility to clarify aspects related to the underlying assumptions by comparing the IVA and the CIA and by evaluating the impact of the matching variables. Thus, within this simulation study two related aspects are of special interest: the assumptions underlying each method and the incorporation of additional matching variables. The simulation on the AMELIA dataset offers a close-to-reality framework with the advantage of knowing the whole setting, i.e. the whole data X, Y and Z. Special interest lies in investigating assumptions through adding and excluding auxiliary variables in order to enhance conditional independence and assess the sensitivity of the methods to this issue. Furthermore, the benefit of having an overlap of units in data A and B for which information on X, Y, Z is available is investigated. It turns out that the integrated approach yields better results than the classical approach when the CIA clearly does not hold. Moreover, even when the classical approach obtains unbiased results for the regression coefficient of Y in the model for Z, it is the method relying on BART that over all coefficients performs best. Concluding, this work constitutes a major contribution to the clarification of assumptions essential to any statistical matching procedure. By introducing graphical models to identify existing approaches to statistical matching combined with the subsequent analysis of the matched dataset, it offers an extensive overview, categorisation and extension of theory and application. Furthermore, in a setting where none of the assumptions are testable (since X, Y and Z are not observed together), the integrated approach is a valuable asset by offering an alternative to the CIA.

In a case of robbery, some people actually use violence to steal - but others may supply information or weapons, make the plans, act as lookouts, provide transport. Certainly the actual robbers are guilty - but what of the others? How does Hong Kong's version of the common law answer this question now? How should the question be answered in the future?

Spatially explicit information about forest cover is fundamental for operational forest management and forest monitoring. Although open-satellite-based earth observation data in a spatially high resolution (i.e., Sentinel-2, ≤10 m) can cover some information needs, spatially very high-resolution imagery (i.e., aerial imagery, ≤2 m) is needed to generate maps at a scale suitable for regional and local applications. In this study, we present the development, implementation, and evaluation of a Geographic Object-Based Image Analysis (GEOBIA) framework to stratify forests (needleleaved, broadleaved, non-forest) in Luxembourg. The framework is exclusively based on open data and free and open-source geospatial software. Although aerial imagery is used to derive image objects with a 0.05 ha minimum size, Sentinel-2 scenes of 2020 are the basis for random forest classifications in different single-date and multi-temporal feature setups. These setups are compared with each other and used to evaluate the framework against classifications based on features derived from aerial imagery. The highest overall accuracies (89.3%) have been achieved with classification on a Sentinel-2-based vegetation index time series (n = 8). Similar accuracies have been achieved with classification based on two (88.9%) or three (89.1%) Sentinel-2 scenes in the greening phase of broadleaved forests. A classification based on color infrared aerial imagery and derived texture measures only achieved an accuracy of 74.5%. The integration of the texture measures into the Sentinel-2-based classification did not improve its accuracy. Our results indicate that high resolution image objects can successfully be stratified based on lower spatial resolution Sentinel-2 single-date and multi-temporal features, and that those setups outperform classifications based on aerial imagery only. The conceptual framework of spatially high-resolution image objects enriched with features from lower resolution imagery facilitates the delivery of frequent and reliable updates due to higher spectral and temporal resolution. The framework additionally holds the potential to derive additional information layers (i.e., forest disturbance) as derivatives of the features attached to the image objects, thus providing up-to-date information on the state of observed forests.

The forensic application of phonetics relies on individuality in speech. In the forensic domain, individual patterns of verbal and paraverbal behavior are of interest which are readily available, measurable, consistent, and robust to disguise and to telephone transmission. This contribution is written from the perspective of the forensic phonetic practitioner and seeks to establish a more comprehensive concept of disfluency than previous studies have. A taxonomy of possible variables forming part of what can be termed disfluency behavior is outlined. It includes the “classical” fillers, but extends well beyond these, covering, among others, additional types of fillers as well as prolongations, but also the way in which fillers are combined with pauses. In the empirical section, the materials collected for an earlier study are re-examined and subjected to two different statistical procedures in an attempt to approach the issue of individuality. Recordings consist of several minutes of spontaneous speech by eight speakers on three different occasions. Beyond the established set of hesitation markers, additional aspects of disfluency behavior which fulfill the criteria outlined above are included in the analysis. The proportion of various types of disfluency markers is determined. Both statistical approaches suggest that these speakers can be distinguished at a level far above chance using the disfluency data. At the same time, the results show that it is difficult to pin down a single measure which characterizes the disfluency behavior of an individual speaker. The forensic implications of these findings are discussed.

The temporal stability of psychological test scores is one prerequisite for their practical usability. This is especially true for intelligence test scores. In educational contexts, high stakes decisions with long-term consequences, such as placement in special education programs, are often based on intelligence test results. There are four different types of temporal stability: mean-level change, individual-level change, differential continuity, and ipsative continuity. We present statistical methods for investigating each type of stability. Where necessary, the methods were adapted for the specific challenges posed by intelligence research (e.g., controlling for general intelligence in lower order test scores). We provide step-by-step guidance for the application of the statistical methods and apply them to a real data set of 114 gifted students tested twice with a test-retest interval of 6 months. • Four different types of stability need to be investigated for a full picture of temporal stability in psychological research • Selection and adaption of the methods for the use in intelligence research • Complete protocol of the implementation

In the present thesis, a theoretical framework for the analysis of spatial queues is developed. Spatial queues are a generalization of the classical concept of queues as they provide the possibility of assigning properties to the users. These properties may influence the queueing process, but may also be of interest for themselves. As a field of application, mobile communication networks are modeled by spatial queues in order to demonstrate the advantage of including user properties into the queueing model. In this application, the property of main interest is the user's position in the network. After a short introduction, the second chapter contains an examination of the class of Markov-additive jump processes, including expressions for the transition probabilities and the expectation as well as laws of large numbers. Chapter 3 contains the definition and analysis of the central concept of spatial Markovian arrival processes (shortly: SMAPs) as a special case of Markov-additive jump processes, but also as a natural generalization from the well-known concept of BMAPs. In chapters 4 and 5, SMAPs serve as arrival streams for the analyzed periodic SMAP/M/c/c and SMAP/G/infinity queues, respectively. These types of queues find application as models or planning tools for mobile communication networks. The analysis of these queues involves new methods such that even for the special cases of BMAP inputs (i.e. non-spatial queues) new results are obtained. In chapter 6, a procedure for statistical parameter estimation is proposed along with its numerical results. The thesis is concluded by an appendix which collects necessary results from the theories of Markov jump processes and stochastic point fields. For special classes of Markov jump processes, new results have been obtained, too.

Magnet Resonance Imaging (MRI) and Electroencephalography (EEG) are tools used to investigate the functioning of the working brain in both humans and animal studies. Both methods are increasingly combined in separate or simultaneous measurements under the assumption to benefit from their individual strength while compensating their particular weaknesses. However, little attention has been paid to how statistical analyses strategies can influence the information that can be retrieved from a combined EEG fMRI study. Two independent studies in healthy student volunteers were conducted in the context of emotion research to demonstrate two approaches of combining MRI and EEG data of the same participants. The first study (N = 20) applied a visual search paradigm and found that in both measurements the assumed effects were absent by not statistically combining their results. The second study (N = 12) applied a novelty P300 paradigm and found that only the statistical combination of MRI and EEG measurements was able to disentangle the functional effects of brain areas involved in emotion processing. In conclusion, the observed results demonstrate that there are added benefits of statistically combining EEG-fMRI data acquisitions by assessing both the inferential statistical structure and the intra-individual correlations of the EEG and fMRI signal.

This working paper examines the concept of metabolism and its potential as a critical analytical lens to study the contemporary city from a political perspective. The paper illustrates how the metabolism concept has been used historically, both as a metaphor to describe the technological, social, political and economic dimensions of human-environment relations, and as a concrete analytical tool to quantify and better understand how flows of matter and energy shape the territorial and spatial configurations of cityscapes. Drawing on the example of the urban water metabolism of the Greater Accra Metropolitan Area (GAMA), it is argued that contemporary approaches to metabolic analysis should be extended in two ways to increase the integrative potential of the urban water metabolism concept. On the one hand, the paper demonstrates that a political ecology approach is particularly well-suited to illuminate the contested production of urban environments and move beyond a narrow technical, managerial and state- centric focus in research on urban metabolic relations. On the other hand, the paper advocates for an approach to metabolic analysis that views the urban environment not simply as a relatively static exteriority that is produced by dynamic flows of matter, energy and information, but rather as a dynamic, nested and co-evolutionary network of complex biosocial and material relations, which in itself shapes how various metabolisms interact across scales. The paper then concludes by briefly discussing how a combination of metabolic analysis and political ecology research can inform urban water governance. In sum, the paper emphasizes the need for metabolic analysis to remain open to a plurality of different knowledge forms and perspectives, and to remain attentive to the inherently political nature of material and technological phenomena in order to allow for mutually beneficial exchanges between various scholarly communities.

The visualization of relational data is at the heart of information visualization. The prevalence of visual representations for this kind of data is based on many real world examples spread over many application domains: protein-protein interaction networks in the field of bioinformatics, hyperlinked documents in the World Wide Web, call graphs in software systems, or co-author networks are just four instances of a rich source of relational datasets. The most common visual metaphor for this kind of data is definitely the node-link approach, which typically suffers from visual clutter caused by many edge crossings. Many sophisticated algorithms have been developed to layout a graph efficiently and with respect to a list of aesthetic graph drawing criteria. Relations between objects normally change over time. Visualizing the dynamics means an additional challenge for graph visualization researchers. Applying the same layout algorithms for static graphs to intermediate states of dynamic graphs may also be a strategy to compute layouts for an animated graph sequence that shows the dynamics. The major drawback of this approach is the high cognitive effort for a viewer of the animation to preserve his mental map. To tackle this problem, a sophisticated layout algorithm has to inspect the whole graph sequence and compute a layout with as little changes as possible between subsequent graphs. The main contribution and ultimate goal of this thesis is the visualization of dynamic compound weighted multi directed graphs as a static image that targets at visual clutter reduction and at mental map preservation. To achieve this goal, we use a radial space-filling visual metaphor to represent the dynamics in relational data. As a side effect the obtained pictures are very aesthetically appealing. In this thesis we firstly describe static graph visualizations for rule sets obtained by extracting knowledge from software archives under version control. In a different work we apply animated node-link diagrams to code-developer relationships to show the dynamics in software systems. An underestimated visualization paradigm is the radial representation of data. Though this kind of data has a long history back to centuries-old statistical graphics, only little efforts have been done to fully explore the benefits of this paradigm. We evaluated a Cartesian and a radial counterpart of a visualization technique for visually encoding transaction sequences and dynamic compound digraphs with both an eyetracking and an online study. We found some interesting phenomena apart from the fact that also laymen in graph theory can understand the novel approach in a short time and apply it to datasets. The thesis is concluded by an aesthetic dimensions framework for dynamic graph drawing, future work, and currently open issues.

Surveys play a major role in studying social and behavioral phenomena that are difficult to observe. Survey data provide insights into the determinants and consequences of human behavior and social interactions. Many domains rely on high quality survey data for decision making and policy implementation including politics, health, business, and the social sciences. Given a certain research question in a specific context, finding the most appropriate survey design to ensure data quality and keep fieldwork costs low at the same time is a difficult task. The aim of examining survey research methodology is to provide the best evidence to estimate the costs and errors of different survey design options. The goal of this thesis is to support and optimize the accumulation and sustainable use of evidence in survey methodology in four steps: (1) Identifying the gaps in meta-analytic evidence in survey methodology by a systematic review of the existing evidence along the dimensions of a central framework in the field (2) Filling in these gaps with two meta-analyses in the field of survey methodology, one on response rates in psychological online surveys, the other on panel conditioning effects for sensitive items (3) Assessing the robustness and sufficiency of the results of the two meta-analyses (4) Proposing a publication format for the accumulation and dissemination of metaanalytic evidence

People are increasingly concerned about how meat affects the environment, human health, and animal welfare, yet eating and enjoying meat remains a norm. Unsurprisingly, many people are ambivalent about meat—evaluating it as both positive and negative. Here, we propose that meat-related conflict is multidimensional and depends on people’s dietary group: Omnivores’ felt ambivalence relates to multiple negative associations that oppose a predominantly positive attitude towards meat, and veg*ans’ ambivalence relates to various positive associations that oppose a predominantly negative attitude. A qualitative study (N = 235; German) revealed that omnivores and veg*ans experience meat-related ambivalence due to associations with animals, sociability, sustainability, health, and sensory experiences. To quantify felt ambivalence in these domains, we developed the Meat Ambivalence Questionnaire (MAQ). We validated the MAQ in four pre-registered studies using self-report and behavioral data (N = 3,485; German, UK, representative US). Both omnivores and veg*ans reported meat-related ambivalence, but with differences across domains and their consequences for meat consumption. Specifically, ambivalence was associated with less meat consumption in omnivores (especially sensory-/animal-based ambivalence) and more meat consumption in veg*ans (especially sensory-/socially-based ambivalence). Network analyses shed further light on the nomological net of the MAQ while controlling for a comprehensive set of determinants of meat consumption. By introducing the MAQ, we hope to provide researchers with a tool to better understand how ambivalence accompanies behavior change and maintenance.

Although it has been demonstrated that nociceptive processing can be modulated by heterotopically and concurrently applied noxious stimuli, the nature of brain processes involved in this percept modulation in healthy subjects remains elusive. Using functional magnetic resonance imaging (fMRI) we investigated the effect of noxious counter-stimulation on pain processing. FMRI scans (1.5 T; block-design) were performed in 34 healthy subjects (median age: 23.5 years; range: 20-31 yrs.) during combined and single application (duration: 15 s; ISI=36 s incl. 6 s rating time) of noxious interdigital-web pinching (intensity range: 6-15 N) and contact-heat (45-49 -°C) presented in pseudo-randomized order during two runs separated by approx. 15 min with individually adjusted equi-intense stimuli. In order to control for attention artifacts, subjects were instructed to maintain their focus either on the mechanical or on the thermal pain stimulus. Changes in subjective pain intensity were computed as percent differences (∆%) in pain ratings between single and heterotopic stimulation for both fMRI runs, resulting in two subgroups showing a relative pain increase (subgroup P-IN, N=10) vs. decrease (subgroup P-DE, N=12). Second level and Region of Interest analysis conducted for both subgroups separately revealed that during heterotopic noxious counter-stimulation, subjects with relative pain decrease showed stronger and more widespread brain activations compared to subjects with relative pain increase in pain processing regions as well as a fronto-parietal network. Median-split regression analyses revealed a modulatory effect of prefrontal activation on connectivity between the thalamus and midbrain/pons, supporting the proposed involvement of prefrontal cortex regions in pain modulation. Furthermore, the mid-sagittal size of the total corpus callosum and five of its subareas were measured from the in vivo magnetic resonance imaging (MRI) recordings. A significantly larger relative truncus size (P=.04) was identified in participants reporting a relative decrease of subjective pain intensity during counter-stimulation, when compared to subjects experiencing a relative pain increase. The above subgroup differences observed in functional and structural imaging data are discussed with consideration of potential differences in cognitive and emotional aspects of pain modulation.

The work of Japanese-German writer Yoko Tawada (Tawada Yōko) stands out as an example of ‘in-between’ writing. Instead of simply ‘translating’ Japanese into German and vice versa, Tawada blends both languages and cultures, often self-reflexively. As a result, poetic in-between spaces emerge, in which creative work, cultural translation, and social criticism can take place. The texts also construct in-between spaces on a formal level. For instance, the verse novels “Kasa no shitai to watashi no tsuma” (『傘の死体とわたしの妻』, 2006) and “Ein Balkonplatz für flüchtige Abende” (2016) feature both narrative progression and poetic devices (vivid imagery, association, and wordplay), defying categorization either as volumes of poetry or as novels. In addition, the in-between space of genres becomes visible in Tawada’s self-translations, which often amount to rewritings and lead to a change in genre – travel essay to novella, novel to drama, or poem to prose text. An example of this genre-transcending bilingualism as entryway to an in-between space are the texts „Die Orangerie“ (1997) and “Orenji-en nite” (「オレンジ園にて」, 1997/1998), which initially appear as a poem and its (apparently) prose translation. However, a number of textual peculiarities of both pieces point to the mutual influences between versions. Thus, I read all four examples as hybrid forms of poetry, which perform the mixing of genres, languages, and cultures that occurs in today’s world. In their cultural hybridity especially, the poems point to underlying social issues of homo- and xenophobia.

Aggression is one of the most researched topics in psychology. This is understandable, since aggression behavior does a lot of harm to individuals and groups. A lot is known already about the biology of aggression, but one system that seems to be of vital importance in animals has largely been overlooked: the hypothalamic-pituitary-adrenal (HPA) axis. Menno Kruk and Jószef Haller and their research teams developed rodent models of adaptive, normal, and abnormal aggressive behavior. They found the acute HPA axis (re)activity, but also chronic basal levels to be causally relevant in the elicitation and escalation of aggressive behavior. As a mediating variable, changes in the processing of relevant social information is proposed, although this could not be tested in animals. In humans, not a lot of research has been done, but there is evidence for both the association between acute and basal cortisol levels in (abnormal) aggression. However, not many of these studies have been experimental of nature. rnrnOur aim was to add to the understanding of both basal chronic levels of HPA axis activity, as well as acute levels in the formation of aggressive behavior. Therefore, we did two experiments, both with healthy student samples. In both studies we induced aggression with a well validated paradigm from social psychology: the Taylor Aggression Paradigm. Half of the subjects, however, only went through a non-provoking control condition. We measured trait basal levels of HPA axis activity on three days prior. We took several cortisol samples before, during, and after the task. After the induction of aggression, we measured the behavioral and electrophysiological brain response to relevant social stimuli, i.e., emotional facial expressions embedded in an emotional Stroop task. In the second study, we pharmacologically manipulated cortisol levels 60min before the beginning of the experiment. To do that, half of the subjects were administered 20mg of hydrocortisone, which elevates circulating cortisol levels (cortisol group), the other half was administered a placebo (placebo group). Results showed that acute HPA axis activity is indeed relevant for aggressive behavior. We found in Study 1 a difference in cortisol levels after the aggression induction in the provoked group compared to the non-provoked group (i.e., a heightened reactivity of the HPA axis). However, this could not be replicated in Study 2. Furthermore, the pharmacological elevation of cortisol levels led to an increase in aggressive behavior in women compared to the placebo group. There were no effects in men, so that while men were significantly more aggressive than women in the placebo group, they were equally aggressive in the cortisol group. Furthermore, there was an interaction of cortisol treatment with block of the Taylor Aggression Paradigm, in that the cortisol group was significantly more aggressive in the third block of the task. Concerning basal HPA axis activity, we found an effect on aggressive behavior in both studies, albeit more consistently in women and in the provoked and non-provoked groups. However, the effect was not apparent in the cortisol group. After the aggressive encounter, information processing patterns were changed in the provoked compared to the non-provoked group for all facial expressions, especially anger. These results indicate that the HPA axis plays an important role in the formation of aggressive behavior in humans, as well. Importantly, different changes within the system, be it basal or acute, are associated with the same outcome in this task. More studies are needed, however, to better understand the role that each plays in different kinds of aggressive behavior, and the role information processing plays as a possible mediating variable. This extensive knowledge is necessary for better behavioral interventions.