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We consider a linear regression model for which we assume that some of the observed variables are irrelevant for the prediction. Including the wrong variables in the statistical model can either lead to the problem of having too little information to properly estimate the statistic of interest, or having too much information and consequently describing fictitious connections. This thesis considers discrete optimization to conduct a variable selection. In light of this, the subset selection regression method is analyzed. The approach gained a lot of interest in recent years due to its promising predictive performance. A major challenge associated with the subset selection regression is the computational difficulty. In this thesis, we propose several improvements for the efficiency of the method. Novel bounds on the coefficients of the subset selection regression are developed, which help to tighten the relaxation of the associated mixed-integer program, which relies on a Big-M formulation. Moreover, a novel mixed-integer linear formulation for the subset selection regression based on a bilevel optimization reformulation is proposed. Finally, it is shown that the perspective formulation of the subset selection regression is equivalent to a state-of-the-art binary formulation. We use this insight to develop novel bounds for the subset selection regression problem, which show to be highly effective in combination with the proposed linear formulation.
In the second part of this thesis, we examine the statistical conception of the subset selection regression and conclude that it is misaligned with its intention. The subset selection regression uses the training error to decide on which variables to select. The approach conducts the validation on the training data, which oftentimes is not a good estimate of the prediction error. Hence, it requires a predetermined cardinality bound. Instead, we propose to select variables with respect to the cross-validation value. The process is formulated as a mixed-integer program with the sparsity becoming subject of the optimization. Usually, a cross-validation is used to select the best model out of a few options. With the proposed program the best model out of all possible models is selected. Since the cross-validation is a much better estimate of the prediction error, the model can select the best sparsity itself.
The thesis is concluded with an extensive simulation study which provides evidence that discrete optimization can be used to produce highly valuable predictive models with the cross-validation subset selection regression almost always producing the best results.

Harvesting of silage maize in late autumn on waterlogged soils may result in several ecological problems such as soil compaction and may subsequently be a major threat to soil fertility in Europe. It was hypothesized that perennial energy crops might reduce the vulnerability for soil compaction through earlier harvest dates and improved soil stability. However, the performance of such crops to be grown on soil that are periodically waterlogged and implications for soil chemical and microbial properties are currently an open issue. Within the framework of a two-year pot experiment we investigated the potential of the cup plant (Silphium perfoliatum L.), Jerusalem artichoke (Helianthus tuberosus), giant knotweed (Fallopia japonicum X bohemica), tall wheatgrass (Agropyron elongatum), and reed canary grass (Phalaris arundinacea) for cultivation under periodically waterlogged soil conditions during the winter half year and implications for soil chemical and biological properties. Examined perennial energy crops coped with periodical waterlogging and showed yields 50% to 150% higher than in the control which was never faced with waterlogging. Root formation was similar in waterlogged and non-waterlogged soil layers. Soil chemical and microbial properties clearly responded to different soil moisture treatments. For example, dehydrogenase activity was two to four times higher in the periodically waterlogged treatment compared to the control. Despite waterlogging, aerobic microbial activity was significantly elevated indicating morphological and metabolic adaptation of the perennial crops to withstand waterlogged conditions. Thus, our results reveal first evidence of a site-adapted biomass production on periodical waterlogged soils through the cultivation of perennial energy crops and for intense plant microbe interactions.

A satellite-based climatology of wind-induced surface temperature anomalies for the Antarctic
(2019)

It is well-known that katabatic winds can be detected as warm signatures in the surface temperature over the slopes of the Antarctic ice sheets. For appropriate synoptic forcing and/or topographic channeling, katabatic surges occur, which result in warm signatures also over adjacent ice shelves. Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) data are used to detect warm signatures over the Antarctic for the winter periods 2002–2017. In addition, high-resolution (5 km) regional climate model data is used for the years of 2002 to 2016. We present a case study and a climatology of wind-induced IST anomalies for the Ross Ice Shelf and the eastern Weddell Sea. The IST anomaly distributions show maxima around 10–15K for the slopes, but values of more than 25K are also found. Katabatic surges represent a strong climatological signal with a mean warm anomaly of more than 5K on more than 120 days per winter for the Byrd Glacier and the Nimrod Glacier on the Ross Ice Shelf. The mean anomaly for the Brunt Ice Shelf is weaker, and exceeds 5K on about 70 days per winter. Model simulations of the IST are compared to the MODIS IST, and show a very good agreement. The model data show that the near-surface stability is a better measure for the response to the wind than the IST itself.

Abstract: Thermal infrared (TIR) multi-/hyperspectral and sun-induced fluorescence (SIF) approaches together with classic solar-reflective (visible, near-, and shortwave infrared reflectance (VNIR)/SWIR) hyperspectral remote sensing form the latest state-of-the-art techniques for the detection of crop water stress. Each of these three domains requires dedicated sensor technology currently in place for ground and airborne applications and either have satellite concepts under development (e.g., HySPIRI/SBG (Surface Biology and Geology), Sentinel-8, HiTeSEM in the TIR) or are subject to satellite missions recently launched or scheduled within the next years (i.e., EnMAP and PRISMA (PRecursore IperSpettrale della Missione Applicativa, launched on March 2019) in the VNIR/SWIR, Fluorescence Explorer (FLEX) in the SIF). Identification of plant water stress or drought is of utmost importance to guarantee global water and food supply. Therefore, knowledge of crop water status over large farmland areas bears large potential for optimizing agricultural water use. As plant responses to water stress are numerous and complex, their physiological consequences affect the electromagnetic signal in different spectral domains. This review paper summarizes the importance of water stress-related applications and the plant responses to water stress, followed by a concise review of water-stress detection through remote sensing, focusing on TIR without neglecting the comparison to other spectral domains (i.e., VNIR/SWIR and SIF) and multi-sensor approaches. Current and planned sensors at ground, airborne, and satellite level for the TIR as well as a selection of commonly used indices and approaches for water-stress detection using the main multi-/hyperspectral remote sensing imaging techniques are reviewed. Several important challenges are discussed that occur when using spectral emissivity, temperature-based indices, and physically-based approaches for water-stress detection in the TIR spectral domain. Furthermore, challenges with data processing and the perspectives for future satellite missions in the TIR are critically examined. In conclusion, information from multi-/hyperspectral TIR together with those from VNIR/SWIR and SIF sensors within a multi-sensor approach can provide profound insights to actual plant (water) status and the rationale of physiological and biochemical changes. Synergistic sensor use will open new avenues for scientists to study plant functioning and the response to environmental stress in a wide range of ecosystems.

Background
In light of the current biodiversity crisis, DNA barcoding is developing into an essential tool to quantify state shifts in global ecosystems. Current barcoding protocols often rely on short amplicon sequences, which yield accurate identification of biological entities in a community but provide limited phylogenetic resolution across broad taxonomic scales. However, the phylogenetic structure of communities is an essential component of biodiversity. Consequently, a barcoding approach is required that unites robust taxonomic assignment power and high phylogenetic utility. A possible solution is offered by sequencing long ribosomal DNA (rDNA) amplicons on the MinION platform (Oxford Nanopore Technologies).
Findings
Using a dataset of various animal and plant species, with a focus on arthropods, we assemble a pipeline for long rDNA barcode analysis and introduce a new software (MiniBar) to demultiplex dual indexed Nanopore reads. We find excellent phylogenetic and taxonomic resolution offered by long rDNA sequences across broad taxonomic scales. We highlight the simplicity of our approach by field barcoding with a miniaturized, mobile laboratory in a remote rainforest. We also test the utility of long rDNA amplicons for analysis of community diversity through metabarcoding and find that they recover highly skewed diversity estimates.
Conclusions
Sequencing dual indexed, long rDNA amplicons on the MinION platform is a straightforward, cost-effective, portable, and universal approach for eukaryote DNA barcoding. Although bulk community analyses using long-amplicon approaches may introduce biases, the long rDNA amplicons approach signifies a powerful tool for enabling the accurate recovery of taxonomic and phylogenetic diversity across biological communities.

A huge number of clinical studies and meta-analyses have shown that psychotherapy is effective on average. However, not every patient profits from psychotherapy and some patients even deteriorate in treatment. Due to this result and the restricted generalization of clinical studies to clinical practice, a more patient-focused research strategy has emerged. The question whether a particular treatment works for an individual case is the focus of this paradigm. The use of repeated assessments and the feedback of this information to therapists is a major ingredient of patient-focused research. Improving patient outcomes and reducing dropout rates by the use of psychometric feedback seems to be a promising path. Therapists seem to differ in the degree to which they make use of and profit from such feedback systems. This dissertation aims to better understand therapist differences in the context of patient-focused research and the impact of therapists on psychotherapy. Three different studies are included, which focus on different aspects within the field:
Study I (Chapter 5) investigated how therapists use psychometric feedback in their work with patients and how much therapists differ in their usage. Data from 72 therapists treating 648 patients were analyzed. It could be shown that therapists used the psychometric feedback for most of their patients. Substantial variance in the use of feedback (between 27% and 52%) was attributable to therapists. Therapists were more likely to use feedback when they reported being satisfied with the graphical information they received. The results therefore indicated that not only patient characteristics or treatment progress affected the use of feedback.
Study II (Chapter 6) picked up on the idea of analyzing systematic differences in therapists and applied it to the criterion of premature treatment termination (dropout). To answer the question whether therapist effects occur in terms of patients’ dropout rates, data from 707 patients treated by 66 therapists were investigated. It was shown that approximately six percent of variance in dropout rates could be attributed to therapists, even when initial impairment was controlled for. Other predictors of dropout were initial impairment, sex, education, personality styles, and treatment expectations.
Study III (Chapter 7) extends the dissertation by investigating the impact of a transfer from one therapist to another within ongoing treatments. Data from 124 patients who agreed to and experienced a transfer during their treatment were analyzed. A significant drop in patient-rated as well as therapist-rated alliance levels could be observed after a transfer. On average, there seemed to be no difficulties establishing a good therapeutic alliance with the new therapist, although differences between patients were observed. There was no increase in symptom severity due to therapy transfer. Various predictors of alliance and symptom development after transfer were investigated. Impacts on clinical practice were discussed.
Results of the three studies are discussed and general conclusions are drawn. Implications for future research as well as their utility for clinical practice and decision-making are presented.

In this thesis, we consider the solution of high-dimensional optimization problems with an underlying low-rank tensor structure. Due to the exponentially increasing computational complexity in the number of dimensions—the so-called curse of dimensionality—they present a considerable computational challenge and become infeasible even for moderate problem sizes.
Multilinear algebra and tensor numerical methods have a wide range of applications in the fields of data science and scientific computing. Due to the typically large problem sizes in practical settings, efficient methods, which exploit low-rank structures, are essential. In this thesis, we consider an application each in both of these fields.
Tensor completion, or imputation of unknown values in partially known multiway data is an important problem, which appears in statistics, mathematical imaging science and data science. Under the assumption of redundancy in the underlying data, this is a well-defined problem and methods of mathematical optimization can be applied to it.
Due to the fact that tensors of fixed rank form a Riemannian submanifold of the ambient high-dimensional tensor space, Riemannian optimization is a natural framework for these problems, which is both mathematically rigorous and computationally efficient.
We present a novel Riemannian trust-region scheme, which compares favourably with the state of the art on selected application cases and outperforms known methods on some test problems.
Optimization problems governed by partial differential equations form an area of scientific computing which has applications in a variety of areas, ranging from physics to financial mathematics. Due to the inherent high dimensionality of optimization problems arising from discretized differential equations, these problems present computational challenges, especially in the case of three or more dimensions. An even more challenging class of optimization problems has operators of integral instead of differential type in the constraint. These operators are nonlocal, and therefore lead to large, dense discrete systems of equations. We present a novel solution method, based on separation of spatial dimensions and provably low-rank approximation of the nonlocal operator. Our
approach allows the solution of multidimensional problems with a complexity which is only slightly larger than linear in the univariate grid size; this improves the state of the art for a particular test problem problem by at least two orders of magnitude.

Because EU water quality policy can result in infrastructure creation or adaptation at the local level across member states, compliance cases are worth examining critically from a sustainable spatial planning perspective. In this study, the 2000 EU Water Framework Directive’s (WFD) reach to local implementation efforts in average towns and cities is shown through the case study of nonconforming household wastewater infrastructure in the German state of Rhineland Palatinate. Seeing wastewater as a socio-technical infrastructure, we ask how the WFD implementation can be understood in the context of local infrastructure development, sustainability, and spatial planning concepts. In particular, this study examines what compliance meant for the centralization or decentralization of local wastewater infrastructure systems—and the sustainability implications for cities
from those choices.

When do anorexic patients perceive their body as too fat? Aggravating and ameliorating factors
(2019)

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.

Background: Increasing exposure to engineered inorganic nanoparticles takes actually place in both terrestric and aquatic ecosystems worldwide. Although we already know harmful effects of AgNP on the soil bacterial community, information about the impact of the factors functionalization, concentration, exposure time, and soil texture on the AgNP effect expression are still rare. Hence, in this study, three soils of different grain size were exposed for up to 90 days to bare and functionalized AgNP in concentrations ranging from 0.01 to 1.00 mg/kg soil dry weight. Effects on soil microbial community were quantified by various biological parameters, including 16S rRNA gene, photometric, and fluorescence analyses.
Results: Multivariate data analysis revealed significant effects of AgNP exposure for all factors and factor combinations investigated. Analysis of individual factors (silver species, concentration, exposure time, soil texture) in the unifactorial ANOVA explained the largest part of the variance compared to the error variance. In depth analysis of factor combinations revealed even better explanation of variance. For the biological parameters assessed in this study, the matching of soil texture and silver species, and the matching of soil texture and exposure time were the two most relevant factor combinations. The factor AgNP concentration contributed to a lower extent to the effect expression compared to silver species, exposure time and physico–chemical composition of soil.
Conclusions: The factors functionalization, concentration, exposure time, and soil texture significantly impacted the effect expression of AgNP on the soil microbial community. Especially long-term exposure scenarios are strongly needed for the reliable environmental impact assessment of AgNP exposure in various soil types.

Academic achievement is a central outcome in educational research, both in and outside higher education, has direct effects on individual’s professional and financial prospects and a high individual and public return on investment. Theories comprise cognitive as well as non-cognitive influences on achievement. Two examples frequently investigated in empirical research are knowledge (as a cognitive determinant) and stress (as a non-cognitive determinant) of achievement. However, knowledge and stress are not stable, what raises questions as to how temporal dynamics in knowledge on the one hand and stress on the other contribute to achievement. To study these contributions in the present doctoral dissertation, I used meta-analysis, latent profile transition analysis, and latent state-trait analysis. The results support the idea of knowledge acquisition as a cumulative and long-term process that forms the basis for academic achievement and conceptual change as an important mechanism for the acquisition of knowledge in higher education. Moreover, the findings suggest that students’ stress experiences in higher education are subject to stable, trait-like influences, as well as situational and/or interactional, state-like influences which are differentially related to achievement and health. The results imply that investigating the causal networks between knowledge, stress, and academic achievement is a promising strategy for better understanding academic achievement in higher education. For this purpose, future studies should use longitudinal designs, randomized controlled trials, and meta-analytical techniques. Potential practical applications include taking account of students’ prior knowledge in higher education teaching and decreasing stress among higher education students.

With the advent of highthroughput sequencing (HTS), profiling immunoglobulin (IG) repertoires has become an essential part of immunological research. The dissection of IG repertoires promises to transform our understanding of the adaptive immune system dynamics. Advances in sequencing technology now also allow the use of the Ion Torrent Personal Genome Machine (PGM) to cover the full length of IG mRNA transcripts. The applications of this benchtop scale HTS platform range from identification of new therapeutic antibodies to the deconvolution of malignant B cell tumors. In the context of this thesis, the usability of the PGM is assessed to investigate the IG heavy chain (IGH) repertoires of animal models. First, an innovate bioinformatics approach is presented to identify antigendriven IGH sequences from bulk sequenced bone marrow samples of transgenic humanized rats, expressing a human IG repertoire (OmniRatTM). We show, that these rats mount a convergent IGH CDR3 response towards measles virus hemagglutinin protein and tetanus toxoid, with high similarity to human counterparts. In the future, databases could contain all IGH CDR3 sequences with known specificity to mine IG repertoire datasets for past antigen exposures, ultimately reconstructing the immunological history of an individual. Second, a unique molecular identifier (UID) based HTS approach and network property analysis is used to characterize the CLLlike CD5+ B cell expansion of A20BKO mice overexpressing a natural short splice variant of the CYLD gene (A20BKOsCYLDBOE). We could determine, that in these mice, overexpression of sCYLD leads to unmutated subvariant of CLL (UCLL). Furthermore, we found that this short splice variant is also seen in human CLL patients highlighting it as important target for future investigations. Third, the UID based HTS approach is improved by adapting it to the PGM sequencing technology and applying a custommade data processing pipeline including the ImMunoGeneTics (IMGT) database error detection. Like this, we were able to obtain correct IGH sequences with over 99.5% confidence and correct CDR3 sequences with over 99.9% confidence. Taken together, the results, protocols and sample processing strategies described in this thesis will improve the usability of animal models and the Ion Torrent PGM HTS platform in the field if IG repertoire research.

External capital plays an important role in financing entrepreneurial ventures, due to limited internal capital sources. An important external capital provider for entrepreneurial ventures are venture capitalists (VCs). VCs worldwide are often confronted with thousands of proposals of entrepreneurial ventures per year and must choose among all of these companies in which to invest. Not only do VCs finance companies at their early stages, but they also finance entrepreneurial companies in their later stages, when companies have secured their first market success. That is why this dissertation focuses on the decision-making behavior of VCs when investing in later-stage ventures. This dissertation uses both qualitative as well as quantitative research methods in order to provide answer to how the decision-making behavior of VCs that invest in later-stage ventures can be described.
Based on qualitative interviews with 19 investment professionals, the first insight gained is that for different stages of venture development, different decision criteria are applied. This is attributed to different risks and goals of ventures at different stages, as well as the different types of information available. These decision criteria in the context of later-stage ventures contrast with results from studies that focus on early-stage ventures. Later-stage ventures possess meaningful information on financials (revenue growth and profitability), the established business model, and existing external investors that is not available for early-stage ventures and therefore constitute new decision criteria for this specific context.
Following this identification of the most relevant decision criteria for investors in the context of later-stage ventures, a conjoint study with 749 participants was carried out to understand the relative importance of decision criteria. The results showed that investors attribute the highest importance to 1) revenue growth, (2) value-added of products/services for customers, and (3) management team track record, demonstrating differences when compared to decision-making studies in the context of early-stage ventures.
Not only do the characteristics of a venture influence the decision to invest, additional indirect factors, such as individual characteristics or characteristics of the investment firm, can influence individual decisions. Relying on cognitive theory, this study investigated the influence of various individual characteristics on screening decisions and found that both investment experience and entrepreneurial experience have an influence on individual decision-making behavior. This study also examined whether goals, incentive structures, resources, and governance of the investment firm influence decision making in the context of later-stage ventures. This study particularly investigated two distinct types of investment firms, family offices and corporate venture capital funds (CVC), which have unique structures, goals, and incentive systems. Additional quantitative analysis showed that family offices put less focus on high-growth firms and whether reputable investors are present. They tend to focus more on the profitability of a later-stage venture in the initial screening. The analysis showed that CVCs place greater importance on product and business model characteristics than other investors. CVCs also favor later-stage ventures with lower revenue growth rates, indicating a preference for less risky investments. The results provide various insights for theory and practice.

Many combinatorial optimization problems on finite graphs can be formulated as conic convex programs, e.g. the stable set problem, the maximum clique problem or the maximum cut problem. Especially NP-hard problems can be written as copositive programs. In this case the complexity is moved entirely into the copositivity constraint.
Copositive programming is a quite new topic in optimization. It deals with optimization over the so-called copositive cone, a superset of the positive semidefinite cone, where the quadratic form x^T Ax has to be nonnegative for only the nonnegative vectors x. Its dual cone is the cone of completely positive matrices, which includes all matrices that can be decomposed as a sum of nonnegative symmetric vector-vector-products.
The related optimization problems are linear programs with matrix variables and cone constraints.
However, some optimization problems can be formulated as combinatorial problems on infinite graphs. For example, the kissing number problem can be formulated as a stable set problem on a circle.
In this thesis we will discuss how the theory of copositive optimization can be lifted up to infinite dimension. For some special cases we will give applications in combinatorial optimization.

This doctoral thesis examines intergenerational knowledge, its antecedents as well as how participation in intergenerational knowledge transfer is related to the performance evaluation of employees. To answer these questions, this doctoral thesis builds on a literature review and quantitative research methods. A systematic literature study shows that empirical evidence on intergenerational knowledge transfer is limited. Building on prior literature, effects of various antecedents at the interpersonal and organizational level regarding their effects on intergenerational and intragenerational knowledge transfer are postulated. By questioning 444 trainees and trainers, this doctoral thesis also demonstrates that interpersonal antecedents impact how trainees participate in intergenerational knowledge transfer with their trainers. Thereby, the results of this study provide support that interpersonal antecedents are relevant for intergenerational knowledge transfer, yet, also emphasize the implications attached to the assigned roles in knowledge transfer (i.e., whether one is a trainee or trainer). Moreover, the results of an experimental vignette study reveal that participation in intergenerational knowledge transfer is linked to the performance evaluation of employees, yet, is susceptible to whether the employee is sharing or seeking knowledge. Overall, this doctoral thesis provides insights into this topic by covering a multitude of antecedents of intergenerational knowledge transfer, as well as how participation in intergenerational knowledge transfer may be associated with the performance evaluation of employees.

Die räumliche Entwicklung von Städten und Regionen wird durch Trends wie Klimawandel, demographische Veränderungen und Strukturwandel beeinflusst, welche nicht an Verwaltungsgrenzen aufhören, sondern die Entwicklung großflächiger Gebiete bestimmen. Außerdem weisen Grenzräume häufig funktionale und thematische Verflechtungen auf, die über die nationalen Grenzen hinweg bestehen. Damit verbunden sind ein regelmäßiger Austausch und Abhängigkeiten zwischen Grenzräumen und deren Bewohnern. Daher ist die Koordination der grenzüberschreitenden Raumentwicklung entscheidend für eine zukunftsorientierte und nachhaltige räumliche Entwicklung. Aufgrund seiner hohen Bedeutung wird dieses Thema von europäischen Wissenschaftlern in der ersten Ausgabe der Themenhefte Borders in Perspective aus verschiedenen Perspektiven beleuchtet.

Salivary alpha-amylase (sAA) influences the perception of taste and texture, features both relevant in acquiring food liking and, with time, food preference. However, no studies have yet investigated the relationship between basal activity levels of sAA and food preference. We collected saliva from 57 volunteers (63% women) who we assessed in terms of their preference for different food items. These items were grouped into four categories according to their nutritional properties: high in starch, high in sugar, high glycaemic index, and high glycaemic load. Anthropometric markers of cardiovascular risk were also calculated. Our findings suggest that sAA influences food
preference and body composition in women. Regression analysis showed that basal sAA activity is inversely associated with subjective but not self-reported behavioural preference for foods high in sugar. Additionally, sAA and subjective preference are associated with anthropometric markers of cardiovascular risk. We believe that this pilot study points to this enzyme as an interesting candidate to consider among the physiological factors that modulate eating behaviour.

The trophic niche is a life trait that identifies the consumer’s position in a local food web. Several factors, such as ontogeny, competitive ability and resource availability contribute in shaping species trophic niches. To date, information on the diet of European Hydromantes salamanders are only available for a limited number of species, no dietary studies have involved more than one species of the genus at a time, and there are limited evidences on how multiple factors interact in determining diet variation. In this study we examined the diet of multiple populations of six out of the eight European cave salamanders, providing the first data on the diet for five of them. In addition, we assessed whether these closely related generalist species show similar diet and, for each species, we tested whether season, age class or sex influence the number and the type of prey consumed. Stomach condition (empty/full) and the number of prey consumed were strongly related to seasonality and to the activity level of individuals. Empty stomachs were more frequent in autumn, in individuals far from cave entrance and in juveniles. Diet composition was significantly different among species. Hydromantes imperialis and H. supramontis were the most generalist species; H. flavus and H. sarrabusensis fed mostly on Hymenoptera and Coleoptera Staphylinidae, while H. genei and H. ambrosii mostly consumed Arachnida and Endopterygota larvae. Furthermore, we detected seasonal shifts of diet in the majority of the species examined. Conversely, within each species, we did not find diet differences between females, males and juveniles. Although being assumed to have very similar dietary habits, here Hydromantes species were shown to be characterized by a high divergence in diet composition and in the stomach condition of individuals.

Sample surveys are a widely used and cost effective tool to gain information about a population under consideration. Nowadays, there is an increasing demand not only for information on the population level but also on the level of subpopulations. For some of these subpopulations of interest, however, very small subsample sizes might occur such that the application of traditional estimation methods is not expedient. In order to provide reliable information also for those so called small areas, small area estimation (SAE) methods combine auxiliary information and the sample data via a statistical model.
The present thesis deals, among other aspects, with the development of highly flexible and close to reality small area models. For this purpose, the penalized spline method is adequately modified which allows to determine the model parameters via the solution of an unconstrained optimization problem. Due to this optimization framework, the incorporation of shape constraints into the modeling process is achieved in terms of additional linear inequality constraints on the optimization problem. This results in small area estimators that allow for both the utilization of the penalized spline method as a highly flexible modeling technique and the incorporation of arbitrary shape constraints on the underlying P-spline function.
In order to incorporate multiple covariates, a tensor product approach is employed to extend the penalized spline method to multiple input variables. This leads to high-dimensional optimization problems for which naive solution algorithms yield an unjustifiable complexity in terms of runtime and in terms of memory requirements. By exploiting the underlying tensor nature, the present thesis provides adequate computationally efficient solution algorithms for the considered optimization problems and the related memory efficient, i.e. matrix-free, implementations. The crucial point thereby is the (repetitive) application of a matrix-free conjugated gradient method, whose runtime is drastically reduced by a matrx-free multigrid preconditioner.

This study examines to what extent a banking crisis and the ensuing potential liquidity shortage affect corporate cash holdings. Specifically, how do firms adjust their liquidity management prior to and during a banking crisis when they are restricted in their financing options? These restrictions might not result from firm-specific characteristics but also incorporate the effects of certain regulatory requirements. I analyse the real effects of indicators of a potential crisis and the occurrence of a crisis event on corporate cash holdings for both unregulated and regulated firms from 31 different countries. In contrast to existing studies, I perform this analysis on the basis of a long observation period (1997 to 2014 respectively 2003 to 2014) using multiple crisis indicators (early warning signals) and multiple crisis events. For regulated firms, this study makes use of a unique sample of country-specific regulatory information, which is collected by hand for 15 countries and converted into an ordinal scale based on the severity of the regulation. Regulated firms are selected from a single industry: Real Estate Investment Trusts. These firms invest in real estate properties and let these properties to third parties. Real Estate Investment Trusts that comply with the aforementioned regulations are exempt from income taxation and are punished for a breach, which makes this industry particularly interesting for the analysis of capital structure decisions.
The results for regulated and unregulated firms are mostly inconclusive. I find no convincing evidence that the degree of regulation affects the level of cash holdings for regulated firms before and during a banking crisis. For unregulated firms, I find strong evidence that financially constrained firms have higher cash holdings than unconstrained firms. Further, there is no real evidence that either financially constrained firms or unconstrained firms increase their cash holdings when observing an early warning signal. In case of a banking crisis, the results differ for univariate tests and in panel regressions. In the univariate setting, I find evidence that both types of firms hold higher levels of cash during a banking crisis. In panel regressions, the effect is only evident for financially unconstrained firms from the US, and when controlling for financial stress, it is also apparent for financially constrained US firms. For firms from Europe, the results are predominantly inconclusive. For banking crises that are preceded by an early warning signal, there is only evidence for an increase in cash holdings for unconstrained US firms when controlling for financial stress.

In the present study a non-motion-stabilized scanning Doppler lidar was operated on board of RV Polarstern in the Arctic (June 2014) and Antarctic (December 2015– January 2016). This is the first time that such a system measured on an icebreaker in the Antarctic. A method for a motion correction of the data in the post-processing is presented.
The wind calculation is based on vertical azimuth display (VAD) scans with eight directions that pass a quality control. Additionally a method for an empirical signal-tonoise ratio (SNR) threshold is presented, which can be calculated for individual measurement set-ups. Lidar wind profiles are compared to total of about 120 radiosonde profiles and also to wind measurements of the ship.
The performance of the lidar measurements in comparison with radio soundings generally shows small root mean square deviation (bias) for wind speed of around 1ms-1(0.1ms-1) and for wind direction of around 10 (1). The post-processing of the non-motion-stabilized data shows comparably high quality to studies with motion-stabilized systems.
Two case studies show that a flexible change in SNR threshold can be beneficial for special situations. Further the studies reveal that short-lived low-level jets in the atmospheric boundary layer can be captured by lidar measurements with a high temporal resolution in contrast to routine radio soundings. The present study shows that a non-motionstabilized Doppler lidar can be operated successfully on an
icebreaker. It presents a processing chain including quality control tests and error quantification, which is useful for further measurement campaigns.

In the context of accelerated global socio-environmental change, the Water-Energy-Food Nexus has received increasing attention within science and international politics by promoting integrated resource governance. This study explores the scientific nexus debates from a discourse analytical perspective to reveal knowledge and power relations as well as geographical settings of nexus research. We also investigate approaches to socio-nature relations that influence nexus research and subsequent political implications. Our findings suggest that the leading nexus discourse is dominated by natural scientific perspectives and a neo-Malthusian framing of environmental challenges. Accordingly, the promoted cross-sectoral nexus approach to resource governance emphasizes efficiency, security, future sustainability, and poverty reduction. Water, energy, and food are conceived as global trade goods that require close monitoring, management and control, to be achieved via quantitative assessments and technological interventions. Within the less visible discourse, social scientific perspectives engage with the social, political, and normative elements of the Water-Energy-Food Nexus. These perspectives criticize the dominant nexus representation for itsmanagerial, neoliberal, and utilitarian approach to resource governance. The managerial framing is critiqued for masking power relations and social inequalities, while alternative framings acknowledge the political nature of resource governance and socio-nature relations. The spatial dimensions of the nexus debate are also discussed. Notably, the nexus is largely shaped by western knowledge, yet applied mainly in specific regions of the Global South. In order for the nexus to achieve integrative solutions for sustainability, the debate needs to overcome its current discursive and spatial separations. To this end, we need to engage more closely with alternative nexus discourses, embrace epistemic pluralism and encourage multi-perspective debates about the socio-nature relations we actually intend to promote.

A basic assumption of standard small area models is that the statistic of interest can be modelled through a linear mixed model with common model parameters for all areas in the study. The model can then be used to stabilize estimation. In some applications, however, there may be different subgroups of areas, with specific relationships between the response variable and auxiliary information. In this case, using a distinct model for each subgroup would be more appropriate than employing one model for all observations. If no suitable natural clustering variable exists, finite mixture regression models may represent a solution that „lets the data decide“ how to partition areas into subgroups. In this framework, a set of two or more different models is specified, and the estimation of subgroup-specific model parameters is performed simultaneously to estimating subgroup identity, or the probability of subgroup identity, for each area. Finite mixture models thus offer a fexible approach to accounting for unobserved heterogeneity. Therefore, in this thesis, finite mixtures of small area models are proposed to account for the existence of latent subgroups of areas in small area estimation. More specifically, it is assumed that the statistic of interest is appropriately modelled by a mixture of K linear mixed models. Both mixtures of standard unit-level and standard area-level models are considered as special cases. The estimation of mixing proportions, area-specific probabilities of subgroup identity and the K sets of model parameters via the EM algorithm for mixtures of mixed models is described. Eventually, a finite mixture small area estimator is formulated as a weighted mean of predictions from model 1 to K, with weights given by the area-specific probabilities of subgroup identity.

Acute social and physical stress interact to influence social behavior: the role of social anxiety
(2018)

Stress is proven to have detrimental effects on physical and mental health. Due to different tasks and study designs, the direct consequences of acute stress have been found to be wide-reaching: while some studies report prosocial effects, others report increases in antisocial behavior, still others report no effect. To control for specific effects of different stressors and to consider the role of social anxiety in stress-related social behavior, we investigated the effects of social versus physical stress on behavior in male participants possessing different levels of social anxiety. In a randomized, controlled two by two design we investigated the impact of social and physical stress on behavior in healthy young men. We found significant influences on various subjective increases in stress by physical and social stress, but no interaction effect. Cortisol was significantly increased by physical stress, and the heart rate was modulated by physical and social stress as well as their combination. Social anxiety modulated the subjective stress response but not the cortisol or heart rate response. With respect to behavior, our results show that social and physical stress interacted to modulate trust, trustworthiness, and sharing. While social stress and physical stress alone reduced prosocial behavior, a combination of the two stressor modalities could restore prosociality. Social stress alone reduced nonsocial risk behavior regardless of physical stress. Social anxiety was associated with higher subjective stress responses and higher levels of trust. As a consequence, future studies will need to investigate further various stressors and clarify their effects on social behavior in health and social anxiety disorders.

The forward effect of testing refers to the finding that retrieval practice of previously studied information increases retention of subsequently studied other information. It has recently been hypothesized that the forward effect (partly) reflects the result of a reset-of-encoding (ROE) process. The proposal is that encoding efficacy decreases with an increase in study material, but testing of previously studied information resets the encoding process and makes the encoding of the subsequently studied information as effective as the encoding of the previously studied information. The goal of the present study was to verify the ROE hypothesis on an item level basis. An experiment is reported that examined the effects of testing in comparison to restudy on items’ serial position curves. Participants studied three lists of items in each condition. In the testing condition, participants were tested immediately on non-target lists 1 and 2, whereas in the restudy condition, they restudied lists 1 and 2. In both conditions, participants were tested immediately on target list 3. Influences of condition and items’ serial learning position on list 3 recall were analyzed. The results showed the forward effect of testing and furthermore that this effect varies with items’ serial list position. Early target list items at list primacy positions showed a larger enhancement effect than middle and late target list items at non-primacy positions. The results are consistent with the ROE hypothesis on an item level basis. The generalizability of the ROE hypothesis across different experimental tasks, like the list-method directed-forgetting task, is discussed.

Background: The growing production and use of engineered AgNP in industry and private households make increasing concentrations of AgNP in the environment unavoidable. Although we already know the harmful effects of AgNP on pivotal bacterial driven soil functions, information about the impact of silver nanoparticles (AgNP) on the soil bacterial community structure is rare. Hence, the aim of this study was to reveal the long-term effects of AgNP on major soil bacterial phyla in a loamy soil. The study was conducted as a laboratory incubation experiment over a period of 1 year using a loamy soil and AgNP concentrations ranging from 0.01 to 1 mg AgNP/kg soil. Effects were quantified using the taxon-specific 16S rRNA qPCR.
Results: The short-term exposure of AgNP at environmentally relevant concentration of 0.01 mg AgNP/kg caused significant positive effects on Acidobacteria (44.0%), Actinobacteria (21.1%) and Bacteroidetes (14.6%), whereas beta-Proteobacteria population was minimized by 14.2% relative to the control (p ≤ 0.05). After 1 year of exposure to 0.01 mg AgNP/kg diminished Acidobacteria (p = 0.007), Bacteroidetes (p = 0.005) and beta-Proteobacteria (p = 0.000) by 14.5, 10.1 and 13.9%, respectively. Actino- and alpha-Proteobacteria were statistically unaffected by AgNP treatments after 1-year exposure. Furthermore, a statistically significant regression and correlation analysis between silver toxicity and exposure time confirmed loamy soils as a sink for silver nanoparticles and their concomitant silver ions.
Conclusions: Even very low concentrations of AgNP may cause disadvantages for the autotrophic ammonia oxidation (nitrification), the organic carbon transformation and the chitin degradation in soils by exerting harmful effects on the liable bacterial phyla.

Species can show strong variation of local abundance across their ranges. Recent analyses suggested that variation in abundance can be related to environmental suitability, as the highest abundances are often observed in populations living in the most suitable areas. However, there is limited information on the mechanisms through which variation in environmental suitability determines abundance. We analysed populations of the microendemic salamander Hydromantes flavus, and tested several hypotheses on potential relationships linking environmental suitability to population parameters. For multiple populations across the whole species range, we assessed suitability using species distribution models, and measured density, activity level, food intake and body condition index. In high-suitability sites, the density of salamanders was up to 30-times higher than in the least suitable ones. Variation in activity levels and population performance can explain such variation of abundance. In high-suitability sites, salamanders were active close to the surface, and showed a low frequency of empty stomachs. Furthermore, when taking into account seasonal variation, body condition was better in the most suitable sites. Our results show that the strong relationship between environmental suitability and population abundance can be mediated by the variation of parameters strongly linked to individual performance and fitness.

Stiftungsunternehmen sind Unternehmen, die sich ganz oder teilweise im Eigentum einer gemeinnützigen oder privaten Stiftung befinden. Die Anzahl an Stiftungsunternehmen in Deutschland ist in den letzten Jahren deutlich gestiegen. Bekannte deutsche Unternehmen wie Aldi, Bosch, Bertelsmann, LIDL oder Würth befinden sich im Eigentum von Stiftungen. Einige von ihnen, wie beispielsweise Fresenius, ZF Friedrichshafen oder Zeiss, sind sogar an der Börse notiert. Die Mehrzahl der Stiftungsunternehmen entsteht dadurch, dass Unternehmensgründer oder Unternehmerfamilien ihr Unternehmen in eine Stiftung einbringen, anstatt es zu vererben oder zu verkaufen.
Die Motive hierfür sind vielfältig und können familiäre Gründe (z. B. Kinderlosigkeit, Vermeidung von Familienstreit), unternehmensbezogene Gründe (z. B. Möglichkeit der langfristigen Planung durch stabile Eigentümerstruktur) und steuerliche Gründe (Vermeidung oder Reduzierung der Erbschaftssteuer) haben oder sind durch die Person des Gründers motiviert (Möglichkeit, das Unternehmen auch nach dem eigenen Tod über die Stiftung noch weiterhin zu prägen). Aufgrund der Tatsache, dass Stiftungsunternehmen zumeist aus Familienunternehmen hervorgehen, wird in der Forschung häufig nicht zwischen Familien- und Stiftungsunternehmen differenziert. Aus diesem Grund werden in dieser Dissertation zu Beginn anhand des Drei-Kreis-Modells für Familienunternehmen die Unterschiede zwischen Stiftungs- und Familienunternehmen dargestellt. Die Ergebnisse zeigen, dass nur eine sehr geringe Anzahl von Stiftungsunternehmen eine große Ähnlichkeit zu klassischen Familienunternehmen aufweist. Die meisten Stiftungsunternehmen unterscheiden sich zum Teil sehr stark von Familienunternehmen. Diese Ergebnisse verdeutlichen, dass Stiftungsunternehmen als separates Forschungsfeld betrachtet werden sollten.
Da innerhalb der Gruppe der Stiftungsunternehmen ebenfalls eine starke Heterogenität herrscht, werden im Anschluss Performanceunterschiede innerhalb der Gruppe der Stiftungsunternehmen untersucht. Hierzu wurden die Daten von 142 deutschen Stiftungsunternehmen für die Jahre 2006-2016 erhoben und mittels einer lineareren Regression ausgewertet. Die Ergebnisse zeigen, dass zwischen den verschiedenen Typen signifikante Unterschiede herrschen. Unternehmen, die von einer gemeinnützigen Stiftung gehalten werden, weisen eine signifikant schlechtere Performance auf, als Unternehmen die eine private Stiftung als Shareholder haben.
Im nächsten Schritt wird die Gruppe der börsennotierten Stiftungsunternehmen untersucht. Mittels einer Ereignisstudie wird getestet, wie sich die Stiftung als Eigentümer eines börsennotierten Unternehmens auf den Shareholder Value auswirkt. Die Ergebnisse zeigen, dass eine Anteilsverringerung einer Stiftung einen positiven Einfluss auf den Shareholder Value hat. Stiftungen werden vom Kapitalmarkt dementsprechend negativ bewertet. Aufgrund der divergierenden Ziele von Stiftung und Unternehmen birgt die Verbindung zwischen Stiftung und Unternehmen potentielle Konflikte und Herausforderungen für die beteiligten Personen. Mittels eines qualitativen explorativen Ansatzes, wird basierend auf Interviews, ein Modell entwickelt, welches die potentiellen Konflikte in Stiftungsunternehmen anhand des Beispiels der Doppelstiftung aufzeigt.
Im letzten Schritt werden Handlungsempfehlungen in Form eines Entwurfs für einen Corporate Governance Kodex erarbeitet, die (potentiellen) Stifterinnen und Stiftern helfen sollen, mögliche Konflikte entweder zu vermeiden oder bereits bestehende Probleme zu lösen.
Die Ergebnisse dieser Dissertation sind relevant für Theorie und Praxis. Aus theoretischer Sicht liegt der Wert dieser Untersuchungen darin, dass Forscher künftig besser zwischen Stiftungs- und Familienunternehmen unterscheiden können. Zudem bringt diese Arbeit den aktuellen Forschungsstand zum Thema Stiftungsunternehmen weiter. Außerdem bietet diese Dissertation insbesondere potentiellen Stiftern einen Überblick über die verschiedenen Ausgestaltungsmöglichkeiten und die Vor- und Nachteile, die diese Konstruktionen mit sich bringen. Die Handlungsempfehlungen ermöglichen es Stiftern, vorab potentielle Gefahren erkennen zu können und diese zu umgehen.

The changing views on the evolutionary relationships of extant Salamandridae (Amphibia: Urodela)
(2018)

The phylogenetic relationships among members of the family Salamandridae have been repeatedly investigated over the last 90 years, with changing character and taxon sampling. We review the changing composition and the phylogenetic position of salamandrid genera and species groups and add a new phylogeny based exclusively on sequences of nuclear genes. Salamandrina often changed its position depending on the characters used. It was included several times in a clade together with the primitive newts (Echinotriton, Pleurodeles, Tylototriton) due to their seemingly ancestral morphology. The latter were often inferred as a monophyletic clade. Respective monophyly was almost consistently established in all molecular studies for true salamanders (Chioglossa, Lyciasalamandra, Mertensiella, Salamandra), modern Asian newts (Cynops, Laotriton, Pachytriton, Paramesotriton) and modern New World newts (Notophthalmus, Taricha). Reciprocal non-monophyly has been established through molecular studies for the European mountain newts (Calotriton, Euproctus) and the modern European newts (Ichthyosaura, Lissotriton, Neurergus, Ommatotriton, Triturus) since Calotriton was identified as the sister lineage of Triturus. In pre-molecular studies, their respective monophyly had almost always been assumed, mainly because a complex courtship behaviour shared by their respective members. Our nuclear tree is nearly identical to a mito-genomic tree, with all but one node being highly supported. The major difference concerns the position of Calotriton, which is no longer nested within the modern European newts. This has implications for the evolution of courtship behaviour of European newts. Within modern European newts, Ichthyosaura and Lissotriton changed their position compared to the mito-genomic tree. Previous molecular trees based on seemingly large nuclear data sets, but analysed together with mitochondrial data, did not reveal monophyly of modern European newts since taxon sampling and nuclear gene coverage was too poor to obtain conclusive results. We therefore conclude that mitochondrial and nuclear data should be analysed on their own.

Reptiles belong to a taxonomic group characterized by increasing worldwide population declines. However, it has not been until comparatively recent years that public interest in these taxa has increased, and conservation measures are starting to show results. While many factors contribute to these declines, environmental pollution, especially in form of pesticides, has seen a strong increase in the last few decades, and is nowadays considered a main driver for reptile diversity loss. In light of the above, and given that reptiles are extremely underrepresented in ecotoxicological studies regarding the effects of plant protection products, this thesis aims at studying the impacts of pesticide exposure in reptiles, by using the Common wall lizard (Podarcis muralis) as model species. In a first approach, I evaluated the risk of pesticide exposure for reptile species within the European Union, as a means to detect species with above average exposure probabilities and to detect especially sensitive reptile orders. While helpful to detect species at risk, a risk evaluation is only the first step towards addressing this problem. It is thus indispensable to identify effects of pesticide exposure in wildlife. For this, the use of enzymatic biomarkers has become a popular method to study sub-individual responses, and gain information regarding the mode of action of chemicals. However, current methodologies are very invasive. Thus, in a second step, I explored the use of buccal swabs as a minimally invasive method to detect changes in enzymatic biomarker activity in reptiles, as an indicator for pesticide uptake and effects at the sub-individual level. Finally, the last part of this thesis focuses on field data regarding pesticide exposure and its effects on reptile wildlife. Here, a method to determine pesticide residues in food items of the Common wall lizard was established, as a means to generate data for future dietary risk assessments. Subsequently, a field study was conducted with the aim to describe actual effects of pesticide exposure on reptile populations at different levels.

The Harmonic Faber Operator
(2018)

P. K. Suetin points out in the beginning of his monograph "Faber
Polynomials and Faber Series" that Faber polynomials play an important
role in modern approximation theory of a complex variable as they
are used in representing analytic functions in simply connected domains,
and many theorems on approximation of analytic functions are proved
with their help [50].
In 1903, the Faber polynomials were firstly discovered by G. Faber. It was Faber's aim to find a generalisation of Taylor
series of holomorphic functions in the open unit disc D
in the following way. As any holomorphic function in D
has a Taylor series representation
f(z)=\sum_{\nu=0}^{\infty}a_{\nu}z^{\nu} (z\in\D)
converging locally uniformly inside D, for a simply connected
domain G, Faber wanted to determine a system of polynomials (Q_n)
such that each function f being holomorphic in G can be expanded
into a series
f=\sum_{\nu=0}^{\infty}b_{\nu}Q_{\nu}
converging locally uniformly inside G. Having this goal in mind,
Faber considered simply connected domains bounded by an analytic Jordan
curve. He constructed a system of polynomials (F_n)
with this property. These polynomials F_n were named after him
as Faber polynomials. In the preface of [50],
a detailed summary of results concerning Faber polynomials and results
obtained by the aid of them is given.
An important application of Faber polynomials is e.g. the transfer
of known assertions concerning polynomial approximation of functions
belonging to the disc algebra to results of the approximation of functions
being continuous on a compact continuum K which contains at least
two points and has a connected complement and being holomorphic in
the interior of K. In this field, the Faber operator
denoted by T turns out to be a powerful tool (for
an introduction, see e.g. D. Gaier's monograph). It
assigns a polynomial of degree at most n given in the monomial
basis \sum_{\nu=0}^{n}a_{\nu}z^{\nu} with a polynomial of degree
at most n given in the basis of Faber polynomials \sum_{\nu=0}^{n}a_{\nu}F_{\nu}.
If the Faber operator is continuous with respect to the uniform norms,
it has a unique continuous extension to an operator mapping the disc
algebra onto the space of functions being continuous on the whole
compact continuum and holomorphic in its interior. For all f being
element of the disc algebra and all polynomials P, via the obvious
estimate for the uniform norms
||T(f)-T(P)||<= ||T|| ||f-P||,
it can be seen that the original task of approximating F=T(f)
by polynomials is reduced to the polynomial approximation of the function
f. Therefore, the question arises under which conditions the Faber
operator is continuous and surjective. A fundamental result in this
regard was established by J. M. Anderson and J. Clunie who showed
that if the compact continuum is bounded by a rectifiable Jordan curve
with bounded boundary rotation and free from cusps, then the Faber
operator with respect to the uniform norms is a topological isomorphism.
Now, let f be a harmonic function in D.
Similar as above, we find that f has a uniquely determined representation
f=\sum_{\nu=-\infty}^{\infty}a_{\nu}p_{\nu}
converging locally uniformly inside D where p_{n}(z)=z^{n}
for n\in\N_{0} and p_{-n}(z)=\overline{z}^{n}
for n\in\N}. One may ask whether there is an analogue for
harmonic functions on simply connected domains G. Indeed, for a
domain G bounded by an analytic Jordan curve, the conjecture that
each function f being harmonic in G has a uniquely determined
representation
f=\sum_{\nu=-\infty}^{\infty}b_{\nu}F_{\nu}
where F_{-n}(z)=\overline{F_{n}(z\)} for n\inN,
converging locally uniformly inside G, holds true.
Let now K be a compact continuum containing at least two points
and having a connected complement. A main component of this thesis
will be the examination of the harmonic Faber operator mapping a harmonic
polynomial given in the basis of the harmonic monomials \sum_{\nu=-n}^{n}a_{\nu}p_{\nu}
to a harmonic polynomial given as \sum_{\nu=-n}^{n}a_{\nu}F_{\nu}.
If this operator, which is based on an idea of J. Müller,
is continuous with respect to the uniform norms, it has a unique continuous
extension to an operator mapping the functions being continuous on
\partial\D onto the continuous functions on K being
harmonic in the interior of K. Harmonic Faber polynomials and the
harmonic Faber operator will be the objects accompanying us throughout
our whole discussion.
After having given an overview about notations and certain tools we
will use in our consideration in the first chapter, we begin our studies
with an introduction to the Faber operator and the harmonic Faber
operator. We start modestly and consider domains bounded by an analytic
Jordan curve. In Section 2, as a first
result, we will show that, for such a domain G, the harmonic Faber
operator has a unique continuous extension to an operator mapping
the space of the harmonic functions in D onto the space
of the harmonic functions in G, and moreover, the harmonic Faber
operator is an isomorphism with respect to the topologies of locally
uniform convergence. In the further sections of this chapter, we illumine
the behaviour of the (harmonic) Faber operator on certain function
spaces.
In the third chapter, we leave the situation of compact continua bounded
by an analytic Jordan curve. Instead we consider closures of domains
bounded by Jordan curves having a Dini continuous curvature. With
the aid of the concept of compact operators and the Fredholm alternative,
we are able to show that the harmonic Faber operator is a topological
isomorphism.
Since, in particular, the main result of the third chapter holds true
for closures K of domains bounded by analytic Jordan curves, we
can make use of it to obtain new results concerning the approximation
of functions being continuous on K and harmonic in the interior
of K by harmonic polynomials. To do so, we develop techniques applied
by L. Frerick and J. Müller in [11] and adjust them to
our setting. So, we can transfer results about the classic Faber operator
to the harmonic Faber operator.
In the last chapter, we will use the theory of harmonic Faber polynomials
to solve certain Dirichlet problems in the complex plane. We pursue
two different approaches: First, with a similar philosophy as in [50],
we develop a procedure to compute the coefficients of a series \sum_{\nu=-\infty}^{\infty}c_{\nu}F_{\nu}
converging uniformly to the solution of a given Dirichlet problem.
Later, we will point out how semi-infinite programming with harmonic
Faber polynomials as ansatz functions can be used to get an approximate
solution of a given Dirichlet problem. We cover both approaches first
from a theoretical point of view before we have a focus on the numerical
implementation of concrete examples. As application of the numerical
computations, we considerably obtain visualisations of the concerned
Dirichlet problems rounding out our discussion about the harmonic
Faber polynomials and the harmonic Faber operator.

Optimal Control of Partial Integro-Differential Equations and Analysis of the Gaussian Kernel
(2018)

An important field of applied mathematics is the simulation of complex financial, mechanical, chemical, physical or medical processes with mathematical models. In addition to the pure modeling of the processes, the simultaneous optimization of an objective function by changing the model parameters is often the actual goal. Models in fields such as finance, biology or medicine benefit from this optimization step.
While many processes can be modeled using an ordinary differential equation (ODE), partial differential equations (PDEs) are needed to optimize heat conduction and flow characteristics, spreading of tumor cells in tissue as well as option prices. A partial integro-differential equation (PIDE) is a parital differential equation involving an integral operator, e.g., the convolution of the unknown function with a given kernel function. PIDEs occur for example in models that simulate adhesive forces between cells or option prices with jumps.
In each of the two parts of this thesis, a certain PIDE is the main object of interest. In the first part, we study a semilinear PIDE-constrained optimal control problem with the aim to derive necessary optimality conditions. In the second, we analyze a linear PIDE that includes the convolution of the unknown function with the Gaussian kernel.

Early life adversity (ELA) poses a high risk for developing major health problems in adulthood including cardiovascular and infectious diseases and mental illness. However, the fact that ELA-associated disorders first become manifest many years after exposure raises questions about the mechanisms underlying their etiology. This thesis focuses on the impact of ELA on startle reflexivity, physiological stress reactivity and immunology in adulthood.
The first experiment investigated the impact of parental divorce on affective processing. A special block design of the affective startle modulation paradigm revealed blunted startle responsiveness during presentation of aversive stimuli in participants with experience of parental divorce. Nurture context potentiated startle in these participants suggesting that visual cues of childhood-related content activates protective behavioral responses. The findings provide evidence for the view that parental divorce leads to altered processing of affective context information in early adulthood.
A second investigation was conducted to examine the link between aging of the immune system and long-term consequences of ELA. In a cohort of healthy young adults, who were institutionalized early in life and subsequently adopted, higher levels of T cell senescence were observed compared to parent-reared controls. Furthermore, the results suggest that ELA increases the risk of cytomegalovirus infection in early childhood, thereby mediating the effect of ELA on T cell-specific immunosenescence.
The third study addresses the effect of ELA on stress reactivity. An extended version of the Cold Pressor Test combined with a cognitive challenging task revealed blunted endocrine response in adults with a history of adoption while cardiovascular stress reactivity was similar to control participants. This pattern of response separation may best be explained by selective enhancement of central feedback-sensitivity to glucocorticoids resulting from ELA, in spite of preserved cardiovascular/autonomic stress reactivity.

The dissertation deals with methods to improve design-based and model-assisted estimation techniques for surveys in a finite population framework. The focus is on the development of the statistical methodology as well as their implementation by means of tailor-made numerical optimization strategies. In that regard, the developed methods aim at computing statistics for several potentially conflicting variables of interest at aggregated and disaggregated levels of the population on the basis of one single survey. The work can be divided into two main research questions, which are briefly explained in the following sections.
First, an optimal multivariate allocation method is developed taking into account several stratification levels. This approach results in a multi-objective optimization problem due to the simultaneous consideration of several variables of interest. In preparation for the numerical solution, several scalarization and standardization techniques are presented, which represent the different preferences of potential users. In addition, it is shown that by solving the problem scalarized with a weighted sum for all combinations of weights, the entire Pareto frontier of the original problem can be generated. By exploiting the special structure of the problem, the scalarized problems can be efficiently solved by a semismooth Newton method. In order to apply this numerical method to other scalarization techniques as well, an alternative approach is suggested, which traces the problem back to the weighted sum case. To address regional estimation quality requirements at multiple stratification levels, the potential use of upper bounds for regional variances is integrated into the method. In addition to restrictions on regional estimates, the method enables the consideration of box-constraints for the stratum-specific sample sizes, allowing minimum and maximum stratum-specific sampling fractions to be defined.
In addition to the allocation method, a generalized calibration method is developed, which is supposed to achieve coherent and efficient estimates at different stratification levels. The developed calibration method takes into account a very large number of benchmarks at different stratification levels, which may be obtained from different sources such as registers, paradata or other surveys using different estimation techniques. In order to incorporate the heterogeneous quality and the multitude of benchmarks, a relaxation of selected benchmarks is proposed. In that regard, predefined tolerances are assigned to problematic benchmarks at low aggregation levels in order to avoid an exact fulfillment. In addition, the generalized calibration method allows the use of box-constraints for the correction weights in order to avoid an extremely high variation of the weights. Furthermore, a variance estimation by means of a rescaling bootstrap is presented.
Both developed methods are analyzed and compared with existing methods in extensive simulation studies on the basis of a realistic synthetic data set of all households in Germany. Due to the similar requirements and objectives, both methods can be successively applied to a single survey in order to combine their efficiency advantages. In addition, both methods can be solved in a time-efficient manner using very comparable optimization approaches. These are based on transformations of the optimality conditions. The dimension of the resulting system of equations is ultimately independent of the dimension of the original problem, which enables the application even for very large problem instances.

The economic growth theory analyses which factors affect economic growth
and tries to analyze how it can last. A popular neoclassical growth model
is the Ramsey-Cass-Koopmans model, which aims to determine how much
of its income a nation or an economy should save in order to maximize its
welfare.
In this thesis, we present and analyze an extended capital accumulation equation of a spatial version of the Ramsey model, balancing diffusive and agglomerative effects. We model the capital mobility in space via a nonlocal
diffusion operator which allows for jumps of the capital stock from one lo-
cation to an other. Moreover, this operator smooths out heterogeneities in
the factor distributions slower, which generated a more realistic behavior of
capital flows. In addition to that, we introduce an endogenous productivity-
production operator which depends on time and on the capital distribution
in space. This operator models the technological progress of the economy.
The resulting mathematical model is an optimal control problem under a
semilinear parabolic integro-differential equation with initial and volume constraints, which are a nonlocal analog to local boundary conditions, and box-constraints on the state and the control variables. In this thesis, we consider
this problem on a bounded and unbounded spatial domain, in both cases with
a finite time horizon. We derive existence results of weak solutions for the
capital accumulation equations in both settings and we proof the existence
of a Ramsey equilibrium in the unbounded case. Moreover, we solve the
optimal control problem numerically and discuss the results in the economic
context.

This dissertation is dedicated to the analysis of the stabilty of portfolio risk and the impact of European regulation introducing risk based classifications for investment funds.
The first paper examines the relationship between portfolio size and the stability of mutual fund risk measures, presenting evidence for economies of scale in risk management. In a unique sample of 338 fund portfolios we find that the volatility of risk numbers decreases for larger funds. This finding holds for dispersion as well as tail risk measures. Further analyses across asset classes provide evidence for the robustness of the effect for balanced and fixed income portfolios. However, a size effect did not emerge for equity funds, suggesting that equity fund managers simply scale their strategy up as they grow. Analyses conducted on the differences in risk stability between tail risk measures and volatilities reveal that smaller funds show higher discrepancies in that respect. In contrast to the majority of prior studies on the basis of ex-post time series risk numbers, this study contributes to the literature by using ex-ante risk numbers based on the actual assets and de facto portfolio data.
The second paper examines the influence of European legislation regarding risk classification of mutual funds. We conduct analyses on a set of worldwide equity indices and find that a strategy based on the long term volatility as it is imposed by the Synthetic Risk Reward Indicator (SRRI) would lead to substantial variations in exposures ranging from short phases of very high leverage to long periods of under investments that would be required to keep the risk classes. In some cases, funds will be forced to migrate to higher risk classes due to limited means to reduce volatilities after crises events. In other cases they might have to migrate to lower risk classes or increase their leverage to ridiculous amounts. Overall, we find if the SRRI creates a binding mechanism for fund managers, it will create substantial interference with the core investment strategy and may incur substantial deviations from it. Fruthermore due to the forced migrations the SRRI degenerates to a passive indicator.
The third paper examines the impact of this volatility based fund classification on portfolio performance. Using historical data on equity indices we find initially that a strategy based on long term portfolio volatility, as it is imposed by the Synthetic Risk Reward Indicator (SRRI), yields better Sharpe Ratios (SRs) and Buy and Hold Returns (BHRs) for the investment strategies matching the risk classes. Accounting for the Fama-French factors reveals no significant alphas for the vast majority of the strategies. In our simulation study where volatility was modelled through a GJR(1,1) - model we find no significant difference in mean returns, but significantly lower SRs for the volatility based strategies. These results were confirmed in robustness checks using alternative models and timeframes. Overall we present evidence which suggests that neither the higher leverage induced by the SRRI nor the potential protection in downside markets does pay off on a risk adjusted basis.

The implicit power motive is one of the most researched motives in motivational
psychology—at least in adults. Children have rarely been subject to investigation and there
are virtually no results on behavioral and affective correlates of the implicit power motive in
children. As behavior and affect are important components of conceptual validation, the
empirical data in this dissertation focused on identifying three correlates, namely resource
control behavior (study 1), power stress (study 2), and persuasive behavior (study 3). In each
study, the implicit power motive was measured via the Picture Story Exercise, using an
adapted version for children. Children across samples were between 4 and 11 years old.
Results from study 1 and 2 showed that children’s power-related behavior corresponded with
evidence from adult samples: children with a high implicit power motive secure attractive
resources and show negative reactions to a thwarted attempt to exert influence. Study 3
contradicted existing evidence with adults in that children’s persuasive behavior was not
associated with nonverbal, but with verbal strategies of persuasion. Despite this inconsistency,
these results are, together with the validation of a child-friendly Picture Story Exercise
version, an important step into further investigating and confirming the concept of the implicit
power motive and how to measure it in children.

A matrix A is called completely positive if there exists an entrywise nonnegative matrix B such that A = BB^T. These matrices can be used to obtain convex reformulations of for example nonconvex quadratic or combinatorial problems. One of the main problems with completely positive matrices is checking whether a given matrix is completely positive. This is known to be NP-hard in general. rnrnFor a given matrix completely positive matrix A, it is nontrivial to find a cp-factorization A=BB^T with nonnegative B since this factorization would provide a certificate for the matrix to be completely positive. But this factorization is not only important for the membership to the completely positive cone, it can also be used to recover the solution of the underlying quadratic or combinatorial problem.rnrnIn addition, it is not a priori known how many columns are necessary to generate a cp-factorization for the given matrix. The minimal possible number of columns is called the cp-rank of A and so far it is still an open question how to derive the cp-rank for a given matrix. Some facts on completely positive matrices and the cp-rank will be given in Chapter 2.rnrnMoreover, in Chapter 6, we will see a factorization algorithm, which, for a given completely positive matrix A and a suitable starting point, computes the nonnegative factorization A=BB^T. The algorithm therefore returns a certificate for the matrix to be completely positive. As introduced in Chapter 3, the fundamental idea of the factorization algorithm is to start from an initial square factorization which is not necessarily entrywise nonnegative, and extend this factorization to a matrix for which the number of columns is greater than or equal to the cp-rank of A. Then it is the goal to transform this generated factorization into a cp-factorization.rnrnThis problem can be formulated as a nonconvex feasibility problem, as shown in Section 4.1, and solved by a method which is based on alternating projections, as proven in Chapter 6.rnrnOn the topic of alternating projections, a survey will be given in Chapter 5. Here we will see how to apply this technique to several types of sets like subspaces, convex sets, manifolds and semialgebraic sets. Furthermore, we will see some known facts on the convergence rate for alternating projections between these types of sets. Considering more than two sets yields the so called cyclic projections approach. Here some known facts for subspaces and convex sets will be shown. Moreover, we will see a new convergence result on cyclic projections among a sequence of manifolds in Section 5.4.rnrnIn the context of cp-factorizations, a local convergence result for the introduced algorithm will be given. This result is based on the known convergence for alternating projections between semialgebraic sets.rnrnTo obtain cp-facrorizations with this first method, it is necessary to solve a second order cone problem in every projection step, which is very costly. Therefore, in Section 6.2, we will see an additional heuristic extension, which improves the numerical performance of the algorithm. Extensive numerical tests in Chapter 7 will show that the factorization method is very fast in most instances. In addition, we will see how to derive a certificate for the matrix to be an element of the interior of the completely positive cone.rnrnAs a further application, this method can be extended to find a symmetric nonnegative matrix factorization, where we consider an additional low-rank constraint. Here again, the method to derive factorizations for completely positive matrices can be used, albeit with some further adjustments, introduced in Section 8.1. Moreover, we will see that even for the general case of deriving a nonnegative matrix factorization for a given rectangular matrix A, the key aspects of the completely positive factorization approach can be used. To this end, it becomes necessary to extend the idea of finding a completely positive factorization such that it can be used for rectangular matrices. This yields an applicable algorithm for nonnegative matrix factorization in Section 8.2.rnNumerical results for this approach will suggest that the presented algorithms and techniques to obtain completely positive matrix factorizations can be extended to general nonnegative factorization problems.

We will consider discrete dynamical systems (X,T) which consist of a state space X and a linear operator T acting on X. Given a state x in X at time zero, its state at time n is determined by the n-th iteration T^n(x). We are interested in the long-term behaviour of this system, that means we want to know how the sequence (T^n (x))_(n in N) behaves for increasing n and x in X. In the first chapter, we will sum up the relevant definitions and results of linear dynamics. In particular, in topological dynamics the notions of hypercyclic, frequently hypercyclic and mixing operators will be presented. In the setting of measurable dynamics, the most important definitions will be those of weakly and strongly mixing operators. If U is an open set in the (extended) complex plane containing 0, we can define the Taylor shift operator on the space H(U) of functions f holomorphic in U as Tf(z) = (f(z)- f(0))/z if z is not equal to 0 and otherwise Tf(0) = f'(0). In the second chapter, we will start examining the Taylor shift on H(U) endowed with the topology of locally uniform convergence. Depending on the choice of U, we will study whether or not the Taylor shift is weakly or strongly mixing in the Gaussian sense. Next, we will consider Banach spaces of functions holomorphic on the unit disc D. The first section of this chapter will sum up the basic properties of Bergman and Hardy spaces in order to analyse the dynamical behaviour of the Taylor shift on these Banach spaces in the next part. In the third section, we study the space of Cauchy transforms of complex Borel measures on the unit circle first endowed with the quotient norm of the total variation and then with a weak-* topology. While the Taylor shift is not even hypercyclic in the first case, we show that it is mixing for the latter case. In Chapter 4, we will first introduce Bergman spaces A^p(U) for general open sets and provide approximation results which will be needed in the next chapter where we examine the Taylor shift on these spaces on its dynamical properties. In particular, for 1<=p<2 we will find sufficient conditions for the Taylor shift to be weakly mixing or strongly mixing in the Gaussian sense. For p>=2, we consider specific Cauchy transforms in order to determine open sets U such that the Taylor shift is mixing on A^p(U). In both sections, we will illustrate the results with appropriate examples. Finally, we apply our results to universal Taylor series. The results of Chapter 5 about the Taylor shift allow us to consider the behaviour of the partial sums of the Taylor expansion of functions in general Bergman spaces outside its disc of convergence.

Given a compact set K in R^d, the theory of extension operators examines the question, under which conditions on K, the linear and continuous restriction operators r_n:E^n(R^d)→E^n(K),f↦(∂^α f|_K)_{|α|≤n}, n in N_0 and r:E(R^d)→E(K),f↦(∂^α f|_K)_{α in N_0^d}, have a linear and continuous right inverse. This inverse is called extension operator and this problem is known as Whitney's extension problem, named after Hassler Whitney. In this context, E^n(K) respectively E(K) denote spaces of Whitney jets of order n respectively of infinite order. With E^n(R^d) and E(R^d), we denote the spaces of n-times respectively infinitely often continuously partially differentiable functions on R^d. Whitney already solved the question for finite order completely. He showed that it is always possible to construct a linear and continuous right inverse E_n for r_n. This work is concerned with the question of how the existence of a linear and continuous right inverse of r, fulfilling certain continuity estimates, can be characterized by properties of K. On E(K), we introduce a full real scale of generalized Whitney seminorms (|·|_{s,K})_{s≥0}, where |·|_{s,K} coincides with the classical Whitney seminorms for s in N_0. We equip also E(R^d) with a family (|·|_{s,L})_{s≥0} of those seminorms, where L shall be a a compact set with K in L-°. This family of seminorms on E(R^d) suffices to characterize the continuity properties of an extension operator E, since we can without loss of generality assume that E(E(K)) in D^s(L).
In Chapter 2, we introduce basic concepts and summarize the classical results of Whitney and Stein.
In Chapter 3, we modify the classical construction of Whitney's operators E_n and show that |E_n(·)|_{s,L}≤C|·|_{s,K} for s in[n,n+1).
In Chapter 4, we generalize a result of Frerick, Jordá and Wengenroth and show that LMI(1) for K implies the existence of an extension operator E without loss of derivatives, i.e. we have it fulfils |E(·)|_{s,L}≤C|·|_{s,K} for all s≥0. We show that a large class of self similar sets, which includes the Cantor set and the Sierpinski triangle, admits an extensions operator without loss of derivatives.
In Chapter 5 we generalize a result of Frerick, Jordá and Wengenroth and show that WLMI(r) for r≥1 implies the existence of a tame linear extension operator E having a homogeneous loss of derivatives, such that |E(·)|_{s,L}≤C|·|_{(r+ε)s,K} for all s≥0 and all ε>0.
In the last chapter we characterize the existence of an extension operator having an arbitrary loss of derivatives by the existence of measures on K.

Industrial companies mainly aim for increasing their profit. That is why they intend to reduce production costs without sacrificing the quality. Furthermore, in the context of the 2020 energy targets, energy efficiency plays a crucial role. Mathematical modeling, simulation and optimization tools can contribute to the achievement of these industrial and environmental goals. For the process of white wine fermentation, there exists a huge potential for saving energy. In this thesis mathematical modeling, simulation and optimization tools are customized to the needs of this biochemical process and applied to it. Two different models are derived that represent the process as it can be observed in real experiments. One model takes the growth, division and death behavior of the single yeast cell into account. This is modeled by a partial integro-differential equation and additional multiple ordinary integro-differential equations showing the development of the other substrates involved. The other model, described by ordinary differential equations, represents the growth and death behavior of the yeast concentration and development of the other substrates involved. The more detailed model is investigated analytically and numerically. Thereby existence and uniqueness of solutions are studied and the process is simulated. These investigations initiate a discussion regarding the value of the additional benefit of this model compared to the simpler one. For optimization, the process is described by the less detailed model. The process is identified by a parameter and state estimation problem. The energy and quality targets are formulated in the objective function of an optimal control or model predictive control problem controlling the fermentation temperature. This means that cooling during the process of wine fermentation is controlled. Parameter and state estimation with nonlinear economic model predictive control is applied in two experiments. For the first experiment, the optimization problems are solved by multiple shooting with a backward differentiation formula method for the discretization of the problem and a sequential quadratic programming method with a line search strategy and a Broyden-Fletcher-Goldfarb-Shanno update for the solution of the constrained nonlinear optimization problems. Different rounding strategies are applied to the resulting post-fermentation control profile. Furthermore, a quality assurance test is performed. The outcomes of this experiment are remarkable energy savings and tasty wine. For the next experiment, some modifications are made, and the optimization problems are solved by using direct transcription via orthogonal collocation on finite elements for the discretization and an interior-point filter line-search method for the solution of the constrained nonlinear optimization problems. The second experiment verifies the results of the first experiment. This means that by the use of this novel control strategy energy conservation is ensured and production costs are reduced. From now on tasty white wine can be produced at a lower price and with a clearer conscience at the same time.

Fostering positive and realistic self-concepts of individuals is a major goal in education worldwide (Trautwein & Möller, 2016). Individuals spend most of their childhood and adolescence in school. Thus, schools are important contexts for individuals to develop positive self-perceptions such as self-concepts. In order to enhance positive self-concepts in educational settings and in general, it is indispensable to have a comprehensive knowledge about the development and structure of self-concepts and their determinants. To date, extensive empirical and theoretical work on antecedents and change processes of self-concept has been conducted. However, several research gaps still exist, and several of these are the focus of the present dissertation. Specifically, these research gaps encompass (a) the development of multiple self-concepts from multiple perspectives regarding stability and change, (b) the direction of longitudinal interplay between self-concept facets over the entire time period from childhood to late adolescence, and (c) the evidence that a recently developed structural model of academic self-concept (nested Marsh/Shavelson model [Brunner et al., 2010]) fits the data in elementary school students, (d) the investigation of structural changes in academic self-concept profile formation within this model, (e) the investigation of dimensional comparison processes as determinants of academic self-concept profile formation in elementary school students within the internal/external frame of reference model (I/E model; Marsh, 1986), (f) the test of moderating variables for dimensional comparison processes in elementary school, (g) the test of the key assumptions of the I/E model that effects of dimensional comparisons depend to a large degree on the existence of achievement differences between subjects, and (h) the generalizability of the findings regarding the I/E model over different statistical analytic methods. Thus, the aim of the present dissertation is to contribute to close these gaps with three studies. Thereby, data from German students enrolled in elementary school to secondary school education were gathered in three projects comprising the developmental time span from childhood to adolescence (ages 6 to 20). Three vital self-concept areas in childhood and adolescence were in-vestigated: general self-concept (i.e., self-esteem), academic self-concepts (general, math, reading, writing, native language), and social self-concepts (of acceptance and assertion). In all studies, data were analyzed within a latent variable framework. Findings are discussed with respect to the research aims of acquiring more comprehensive knowledge on the structure and development of significant self-concept in childhood and adolescence and their determinants. In addition, theoretical and practical implications derived from the findings of the present studies are outlined. Strengths and limitations of the present dissertation are discussed. Finally, an outlook for future research on self-concepts is given.

Background and rationale: Changing working conditions demand adaptation, resulting in higher stress levels in employees. In consequence, decreased productivity, increasing rates of sick leave, and cases of early retirement result in higher direct, indirect, and intangible costs.rnAims of the Research Project: The aim of the study was to test the usefulness of a novel translational diagnostic tool, Neuropattern, for early detection, prevention, and personalized treatment of stress-related disorders. The trial was designed as a pilot study with a wait list control group.rnMaterials and Methods: In this study, 70 employees of the Forestry Department Rhineland-Palatinate, Germany, were enrolled. Subjects were block-randomized according to the functional group of their career field, and either underwent Neuropattern diagnostics immediately, or after a waiting period of three months. After the diagnostic assessment, their physicians received the Neuropattern Medical Report, including the diagnostic results and treatment recommendations. Participants were informed by the Neuropattern Patient Report, and were eligible to an individualized Neuropattern Online Counseling account. Results: The application of Neuropattern diagnostics significantly improved mental health and health-related behavior, reduced perceived stress, emotional exhaustion, overcommitment and possibly, presenteeism. Additionally, Neuropattern sensitively detected functional changes in stress physiology at an early stage, thus allowing timely personalized interventions to prevent and treat stress pathology.rnConclusion: The present study encouraged the application of Neuropattern diagnostics to early intervention in non-clinical populations. However, further research is required to determine the best operating conditions.

Early life adversity (ELA) is associated with a higher risk for diseases in adulthood. Changes in the immune system have been proposed to underlie this association. Although higher levels of inflammation and immunosenescence have been reported, data on cell-specific immune effects are largely absent. In addition, stress systems and health behaviors are altered in ELA, which may contribute to the generation of the "ELA immune phenotype". In this thesis, we have investigated the ELA immune phenotype on a cellular level and whether this is an indirect consequence of changes in behavior or stress reactivity. To address these questions the EpiPath cohort was established, consisting of 115 young adults with or without ELA. ELA participants had experienced separation from their parents in early childhood and were subsequently adopted, which is a standard model for ELA, whereas control participants grew up with their biological parents. At a first visit, blood samples were taken for analysis of epigenetic markers and immune parameters. A selection of the cohort underwent a standardized laboratory stress test (SLST). Endocrine, immune, and cardiovascular parameters were assessed at several time points before and after stress. At a second visit, participants underwent structural clinical interviews and filled out psychological questionnaires. We observed a higher number of activated T cells in ELA, measured by HLA-DR and CD25 expression. Neither cortisol levels nor health-risk behaviors explained the observed group differences. Besides a trend towards higher numbers of CCR4+CXCR3-CCR6+ CD4 T cells in ELA, relative numbers of immune cell subsets in circulation were similar between groups. No difference was observed in telomere length or in methylation levels of age-related CpGs in whole blood. However, we found a higher expression of senescence markers (CD57) on T cells in ELA. In addition, these cells had an increased cytolytic potential. A mediation analysis demonstrated that cytomegalovirus infection " an important driving force of immunosenescence " largely accounted for elevated CD57 expression. The psychological investigations revealed that after adoption, family conditions appeared to have been similar to the controls. However, PhD thesis MMC Elwenspoek 18 ELA participants scored higher on a depression index, chronic stress, and lower on self-esteem. Psychological, endocrine, and cardiovascular parameters significantly responded to the SLST, but were largely similar between the two groups. Only in a smaller subset of groups matched for gender, BMI, and age, the cortisol response seemed to be blunted in ELA participants. Although we found small differences in the methylation level of the GR promoter, GR sensitivity and mRNA expression levels GR as well as expression of the GR target genes FKBP5 and GILZ were similar between groups. Taken together, our data suggest an elevated state of immune activation in ELA, in which particularly T cells are affected. Furthermore, we found higher levels of T cells immunosenescence in ELA. Our data suggest that ELA may increase the risk of cytomegalovirus infection in early childhood, thereby mediating the effect of ELA on T cell specific immunosenescence. Importantly, we found no evidence of HPA dysregulation in participants exposed to ELA in the EpiPath cohort. Thus, the observed immune phenotype does not seem to be secondary to alterations in the stress system or health-risk behaviors, but rather a primary effect of early life programming on immune cells. Longitudinal studies will be necessary to further dissect cause from effect in the development of the ELA immune phenotype.

This thesis is focused on improving the knowledge on a group of threatened species, the European cave salamanders (genus Hydromantes). There are three main sections gathering studies dealing with different topics: Ecology (first part), Life traits (second part) and Monitoring methodologies (third part). First part starts with the study of the response of Hydromantes to the variation of climatic conditions, analysing 15 different localities throughout a full year (CHAPTER I; published in PEERJ in August 2015). After that, the focus moves on identify which is the operative temperature that these salamander experience, including how their body respond to variation of environmental temperature. This study was conducted using one of the most advanced tool, an infrared thermocamera, which gave the opportunity to perform detailed observation on salamanders body (CHAPTER II; published in JOURNAL OF THERMAL BIOLOGY in June 2016). In the next chapter we use the previous results to analyse the ecological niche of all eight Hydromantes species. The study mostly underlines the mismatch between macro- and microscale analysis of ecological niche, showing a weak conservatism of ecological niches within the evolution of species (CHAPTER III; unpublished manuscript). We then focus only on hybrids, which occur within the natural distribution of mainland species. Here, we analyse if the ecological niche of hybrids shows divergences from those of parental species, thus evaluating the power of hybrids adaptation (CHAPTER IV; unpublished manuscript). Considering that hybrids may represent a potential threat for parental species (in terms of genetic erosion and competition), we produced the first ecological study on an allochthonous mixed population of Hydromantes, analysing population structure, ecological requirements and diet. The interest on this particular population mostly comes by the fact that its members are coming from all three mainland Hydromantes species, and thus it may represent a potential source of new hybrids (CHAPTER V; accepted in AMPHIBIA-REPTILIA in October 2017). The focus than moves on how bioclimatic parameters affect species within their distributional range. Using as model species the microendemic H. flavus, we analyse the relationship between environmental suitability and local abundance of the species, also focusing on all intermediate dynamics which provide useful information on spatial variation of individual fitness (CHAPTER VI; submitted to SCIENTIFIC REPORTS in November 2017). The first part ends with an analysis of the interaction between Hydromantes and Batracobdella algira leeches, the only known ectoparasite for European cave salamanders. Considering that the effect of leeches on their hosts is potentially detrimental, we investigated if these ectoparasites may represent a further threat for Hydromantes (CHAPTER VII; submitted to INTERNATIONAL JOURNAL FOR PARASITOLOGY: PARASITES AND WILDLIFE in November 2017). The second part is related to the reproduction of Hydromantes. In the first study we perform analyses on the breeding behaviour of several females belonging to a single population, identifying differences and similarities occurring in cohorting females (CHAPTER VIII; published in NORTH-WESTERN JOURNAL OF ZOOLOGY in December 2015). In the second study we gather information from all Hydromantes species, analysing size and development of breeding females, and identifying a relationship between breeding time and climatic conditions (CHAPTER IX; submitted to SALAMANDRA in June 2017). In the last part of this thesis, we analyse two potential methods for monitoring Hydromantes populations. In the first study we evaluate the efficiency of the marking method involving Alpha tags (CHAPTER X; published in SALAMANDRA in October 2017). In the second study we focus on evaluating N-mixtures models as a methodology for estimating abundance in wild populations (CHAPTER XI; submitted to BIODIVERSITY & CONSERVATION in October 2017).

There are large health, societal, and economic costs associated with attrition from psychological services. The recently emerged, innovative statistical tool of complex network analysis was used in the present proof-of-concept study to improve the prediction of attrition. Fifty-eight patients undergoing psychological treatment for mood or anxiety disorders were assessed using Ecological Momentary Assessments four times a day for two weeks before treatment (3,248 measurements). Multilevel vector autoregressive models were employed to compute dynamic symptom networks. Intake variables and network parameters (centrality measures) were used as predictors for dropout using machine-learning algorithms. Networks for patients differed significantly between completers and dropouts. Among intake variables, initial impairment and sex predicted dropout explaining 6% of the variance. The network analysis identified four additional predictors: Expected force of being excited, outstrength of experiencing social support, betweenness of feeling nervous, and instrength of being active. The final model with the two intake and four network variables explained 32% of variance in dropout and identified 47 out of 58 patients correctly. The findings indicate that patients" dynamic network structures may improve the prediction of dropout. When implemented in routine care, such prediction models could identify patients at risk for attrition and inform personalized treatment recommendations.

The availability of data on the feeding habits of species of conservation value may be of great importance to develop analyses for both scientific and management purposes. Stomach flushing is a harmless technique that allowed us to collect extensive data on the feeding habits of six Hydromantes species. Here, we present two datasets originating from a three-year study performed in multiple seasons (spring and autumn) on 19 different populations of cave salamanders. The first dataset contains data of the stomach content of 1,250 salamanders, where 6,010 items were recognized; the second one reports the size of the intact prey items found in the stomachs. These datasets integrate considerably data already available on the diet of the European plethodontid salamanders, being also of potential use for large scale meta-analyses on amphibian diet.

Leeches can parasitize many vertebrate taxa. In amphibians, leech parasitism often has potential detrimental effects including population decline. Most of studies on the host-parasite interactions involving leeches and amphibians focus on freshwater environments, while they are very scarce for terrestrial amphibians. In this work, we studied the relationship between the leech Batracobdella algira and the European terrestrial salamanders of the genus Hydromantes, identifying environmental features related to the presence of the leeches and their possible effects on the hosts. We performed observation throughout Sardinia (Italy), covering the distribution area of all Hydromantes species endemic to this island. From September 2015 to May 2017, we conducted >150 surveys in 26 underground environments, collecting data on 2629 salamanders and 131 leeches. Water hardness was the only environmental feature correlated with the presence of B. algira, linking this leech to active karstic systems. Leeches were more frequently parasitizing salamanders with large body size. Body Condition Index was not significantly different between parasitized and non-parasitized salamanders. Our study shows the importance of abiotic environmental features for host-parasite interactions, and poses new questions on complex interspecific interactions between this ectoparasite and amphibians.

Dry tropical forests are facing massive conversion and degradation processes and they are the most endangered forest type worldwide. One of the largest dry forest types are Miombo forests that stretch across the Southern African subcontinent and the proportionally largest part of this type can be found in Angola. The study site of this thesis is located in south-central Angola. The country still suffers from the consequences of the 27 years of civil war (1975 " 2002) that provides a unique socio-economic setting. The natural characteristics are a representative cross section which proved ideal to study underlying drivers as well as current and retrospective land use change dynamics. The major land change dynamic of the study area is the conversion of Miombo forests to cultivation areas as well as modification of forest areas, i.e. degradation, due to the extraction of natural resources. With future predictions of population growth, climate change and large scale investments, land pressure is expected to further increase. To fully understand the impacts of these dynamics, both, conversion and modification of forest areas were assessed. By using the conceptual framework of ecosystem services, the predominant trade-off between food and timber in the study area was analyzed, including retrospective dynamics and impacts. This approach accounts for products that contribute directly or indirectly to human well-being. For this purpose, data from the Landsat archive since 1989 until 2013 was applied in different study area adapted approaches. The objectives of these approaches were (I) to detect underlying drivers and their temporal and spatial extent of impact, (II) to describe modification and conversion processes that reach from times of armed conflicts over the ceasefire and the post-war period and (III) to provide an assessment of drivers and impacts in a comparative setting. It could be shown that major underlying drivers for the conversion processes are resettlement dynamics as well as the location and quality of streets and settlements. Furthermore, forests that are selectively used for resource extraction have a higher chance of being converted to a field. Drivers of forest degradation are on one hand also strongly connected to settlement and infrastructural structures. But also to a large extent to fire dynamics that occur mostly in more remote and presumably undisturbed forest areas. The loss of woody biomass as well as its slow recovery after the abandonment of fields could be quantified and stands in large contrast to the amount of potentially cultivated food that is necessarily needed. The results of the thesis support the fundamental understanding of drivers and impacts in the study area and can thus contribute to a sustainable resource management.

This thesis considers the general task of computing a partition of a set of given objects such that each set of the partition has a cardinality of at least a fixed number k. Among such kinds of partitions, which we call k-clusters, the objective is to find the k-cluster which minimises a certain cost derived from a given pairwise difference between objects which end up the same set. As a first step, this thesis introduces a general problem, denoted by (||.||,f)-k-cluster, which models the task to find a k-cluster of minimum cost given by an objective function computed with respect to specific choices for the cost functions f and ||.||. In particular this thesis considers three different choices for f and also three different choices for ||.|| which results in a total of nine different variants of the general problem. Especially with the idea to use the concept of parameterised approximation, we first investigate the role of the lower bound on the cluster cardinalities and find that k is not a suitable parameter, due to remaining NP-hardness even for the restriction to the constant 3. The reductions presented to show this hardness yield the even stronger result which states that polynomial time approximations with some constant performance ratio for any of the nine variants of (||.||,f)-k-cluster require a restriction to instances for which the pairwise distance on the objects satisfies the triangle inequality. For this restriction to what we informally refer to as metric instances, constant-factor approximation algorithms for eight of the nine variants of (||.||,f)-k-cluster are presented. While two of these algorithms yield the provably best approximation ratio (assuming P!=NP), others can only guarantee a performance which depends on the lower bound k. With the positive effect of the triangle inequality and applications to facility location in mind, we discuss the further restriction to the setting where the given objects are points in the Euclidean metric space. Considering the effect of computational hardness caused by high dimensionality of the input for other related problems (curse of dimensionality) we check if this is also the source of intractability for (||.||,f)-k-cluster. Remaining NP-hardness for restriction to small constant dimensionality however disproves this theory. We then use parameterisation to develop approximation algorithms for (||.||,f)-k-cluster without restriction to metric instances. In particular, we discuss structural parameters which reflect how much the given input differs from a metric. This idea results in parameterised approximation algorithms with parameters such as the number of conflicts (our name for pairs of objects for which the triangle inequality is violated) or the number of conflict vertices (objects involved in a conflict). The performance ratios of these parameterised approximations are in most cases identical to those of the approximations for metric instances. This shows that for most variants of (||.||,f)-k-cluster efficient and reasonable solutions are also possible for non-metric instances.