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With two-thirds to three-quarters of all companies, family firms are the most common firm type worldwide and employ around 60 percent of all employees, making them of considerable importance for almost all economies. Despite this high practical relevance, academic research took notice of family firms as intriguing research subjects comparatively late. However, the field of family business research has grown eminently over the past two decades and has established itself as a mature research field with a broad thematic scope. In addition to questions relating to corporate governance, family firm succession and the consideration of entrepreneurial families themselves, researchers mainly focused on the impact of family involvement in firms on their financial performance and firm strategy. This dissertation examines the financial performance and capital structure of family firms in various meta-analytical studies. Meta-analysis is a suitable method for summarizing existing empirical findings of a research field as well as identifying relevant moderators of a relationship of interest.
First, the dissertation examines the question whether family firms show better financial performance than non-family firms. A replication and extension of the study by O’Boyle et al. (2012) based on 1,095 primary studies reveals a slightly better performance of family firms compared to non-family firms. Investigating the moderating impact of methodological choices in primary studies, the results show that outperformance holds mainly for large and publicly listed firms and with regard to accounting-based performance measures. Concerning country culture, family firms show better performance in individualistic countries and countries with a low power distance.
Furthermore, this dissertation investigates the sensitivity of family firm performance with regard to business cycle fluctuations. Family firms show a pro-cyclical performance pattern, i.e. their relative financial performance compared to non-family firms is better in economically good times. This effect is particularly pronounced in Anglo-American countries and emerging markets.
In the next step, a meta-analytic structural equation model (MASEM) is used to examine the market valuation of public family firms. In this model, profitability and firm strategic choices are used as mediators. On the one hand, family firm status itself does not have an impact on firms‘ market value. On the other hand, this study finds a positive indirect effect via higher profitability levels and a negative indirect effect via lower R&D intensity. A split consideration of family ownership and management shows that these two effects are mainly driven by family ownership, while family management results in less diversification and internationalization.
Finally, the dissertation examines the capital structure of public family firms. Univariate meta-analyses indicate on average lower leverage ratios in family firms compared to non-family firms. However, there is significant heterogeneity in mean effect sizes across the 45 countries included in the study. The results of a meta-regression reveal that family firms use leverage strategically to secure their controlling position in the firm. While strong creditor protection leads to lower leverage ratios in family firms, strong shareholder protection has the opposite effect.

Die vorgelegte Dissertation trägt den Titel Regularization Methods for Statistical Modelling in Small Area Estimation. In ihr wird die Verwendung regularisierter Regressionstechniken zur geographisch oder kontextuell hochauflösenden Schätzung aggregatspezifischer Kennzahlen auf Basis kleiner Stichproben studiert. Letzteres wird in der Fachliteratur häufig unter dem Begriff Small Area Estimation betrachtet. Der Kern der Arbeit besteht darin die Effekte von regularisierter Parameterschätzung in Regressionsmodellen, welche gängiger Weise für Small Area Estimation verwendet werden, zu analysieren. Dabei erfolgt die Analyse primär auf theoretischer Ebene, indem die statistischen Eigenschaften dieser Schätzverfahren mathematisch charakterisiert und bewiesen werden. Darüber hinaus werden die Ergebnisse durch numerische Simulationen veranschaulicht, und vor dem Hintergrund empirischer Anwendungen kritisch verortet. Die Dissertation ist in drei Bereiche gegliedert. Jeder Bereich behandelt ein individuelles methodisches Problem im Kontext von Small Area Estimation, welches durch die Verwendung regularisierter Schätzverfahren gelöst werden kann. Im Folgenden wird jedes Problem kurz vorgestellt und im Zuge dessen der Nutzen von Regularisierung erläutert.
Das erste Problem ist Small Area Estimation in der Gegenwart unbeobachteter Messfehler. In Regressionsmodellen werden typischerweise endogene Variablen auf Basis statistisch verwandter exogener Variablen beschrieben. Für eine solche Beschreibung wird ein funktionaler Zusammenhang zwischen den Variablen postuliert, welcher durch ein Set von Modellparametern charakterisiert ist. Dieses Set muss auf Basis von beobachteten Realisationen der jeweiligen Variablen geschätzt werden. Sind die Beobachtungen jedoch durch Messfehler verfälscht, dann liefert der Schätzprozess verzerrte Ergebnisse. Wird anschließend Small Area Estimation betrieben, so sind die geschätzten Kennzahlen nicht verlässlich. In der Fachliteratur existieren hierfür methodische Anpassungen, welche in der Regel aber restriktive Annahmen hinsichtlich der Messfehlerverteilung benötigen. Im Rahmen der Dissertation wird bewiesen, dass Regularisierung in diesem Kontext einer gegen Messfehler robusten Schätzung entspricht - und zwar ungeachtet der Messfehlerverteilung. Diese Äquivalenz wird anschließend verwendet, um robuste Varianten bekannter Small Area Modelle herzuleiten. Für jedes Modell wird ein Algorithmus zur robusten Parameterschätzung konstruiert. Darüber hinaus wird ein neuer Ansatz entwickelt, welcher die Unsicherheit von Small Area Schätzwerten in der Gegenwart unbeobachteter Messfehler quantifiziert. Es wird zusätzlich gezeigt, dass diese Form der robusten Schätzung die wünschenswerte Eigenschaft der statistischen Konsistenz aufweist.
Das zweite Problem ist Small Area Estimation anhand von Datensätzen, welche Hilfsvariablen mit unterschiedlicher Auflösung enthalten. Regressionsmodelle für Small Area Estimation werden normalerweise entweder für personenbezogene Beobachtungen (Unit-Level), oder für aggregatsbezogene Beobachtungen (Area-Level) spezifiziert. Doch vor dem Hintergrund der stetig wachsenden Datenverfügbarkeit gibt es immer häufiger Situationen, in welchen Daten auf beiden Ebenen vorliegen. Dies beinhaltet ein großes Potenzial für Small Area Estimation, da somit neue Multi-Level Modelle mit großem Erklärungsgehalt konstruiert werden können. Allerdings ist die Verbindung der Ebenen aus methodischer Sicht kompliziert. Zentrale Schritte des Inferenzschlusses, wie etwa Variablenselektion und Parameterschätzung, müssen auf beiden Levels gleichzeitig durchgeführt werden. Hierfür existieren in der Fachliteratur kaum allgemein anwendbare Methoden. In der Dissertation wird gezeigt, dass die Verwendung ebenenspezifischer Regularisierungsterme in der Modellierung diese Probleme löst. Es wird ein neuer Algorithmus für stochastischen Gradientenabstieg zur Parameterschätzung entwickelt, welcher die Informationen von allen Ebenen effizient unter adaptiver Regularisierung nutzt. Darüber hinaus werden parametrische Verfahren zur Abschätzung der Unsicherheit für Schätzwerte vorgestellt, welche durch dieses Verfahren erzeugt wurden. Daran anknüpfend wird bewiesen, dass der entwickelte Ansatz bei adäquatem Regularisierungsterm sowohl in der Schätzung als auch in der Variablenselektion konsistent ist.
Das dritte Problem ist Small Area Estimation von Anteilswerten unter starken verteilungsbezogenen Abhängigkeiten innerhalb der Kovariaten. Solche Abhängigkeiten liegen vor, wenn eine exogene Variable durch eine lineare Transformation einer anderen exogenen Variablen darstellbar ist (Multikollinearität). In der Fachliteratur werden hierunter aber auch Situationen verstanden, in welchen mehrere Kovariate stark korreliert sind (Quasi-Multikollinearität). Wird auf einer solchen Datenbasis ein Regressionsmodell spezifiziert, dann können die individuellen Beiträge der exogenen Variablen zur funktionalen Beschreibung der endogenen Variablen nicht identifiziert werden. Die Parameterschätzung ist demnach mit großer Unsicherheit verbunden und resultierende Small Area Schätzwerte sind ungenau. Der Effekt ist besonders stark, wenn die zu modellierende Größe nicht-linear ist, wie etwa ein Anteilswert. Dies rührt daher, dass die zugrundeliegende Likelihood-Funktion nicht mehr geschlossen darstellbar ist und approximiert werden muss. Im Rahmen der Dissertation wird gezeigt, dass die Verwendung einer L2-Regularisierung den Schätzprozess in diesem Kontext signifikant stabilisiert. Am Beispiel von zwei nicht-linearen Small Area Modellen wird ein neuer Algorithmus entwickelt, welche den bereits bekannten Quasi-Likelihood Ansatz (basierend auf der Laplace-Approximation) durch Regularisierung erweitert und verbessert. Zusätzlich werden parametrische Verfahren zur Unsicherheitsmessung für auf diese Weise erhaltene Schätzwerte beschrieben.
Vor dem Hintergrund der theoretischen und numerischen Ergebnisse wird in der Dissertation demonstriert, dass Regularisierungsmethoden eine wertvolle Ergänzung der Fachliteratur für Small Area Estimation darstellen. Die hier entwickelten Verfahren sind robust und vielseitig einsetzbar, was sie zu hilfreichen Werkzeugen der empirischen Datenanalyse macht.

Hypothalamic-pituitary-adrenal (HPA) axis-related genetic variants influence the stress response
(2019)

The physiological stress system includes the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic-adrenal-medullary system (SAM). Parameters representing these systems such as cortisol, blood pressure or heart rate define the physiological reaction in response to a stressor. The main objective of the studies described in this thesis was to understand the role of the HPA-related genetic factors in these two systems. Genetic factors represent one of the components causing individual variations in physiological stress parameters. Five genes involved in the functioning of the HPA axis regarding stress responses are examined in this thesis. They are: corticotropin-releasing hormone (CRH), the glucocorticoid receptor (GR), the mineralocorticoid receptor (MR), the 5-hydroxytryptamine-transporter-linked polymorphic region (5-HTTLPR) in the serotonin transporter (5-HTT) and the brain-derived neurotrophic factor (BDNF) gene. Two hundred thirty-two healthy participants were genotyped. The influence of genetic factors on physiological parameters, such as post-awakening cortisol and blood pressure was assessed, as well as the influence of genetic factors on stress reactivity in response to a socially evaluated cold pressor test (SeCPT). Three studies tested the HPA-related genes each on three different levels. The first study examined the influences of genotypes and haplotypes of these five genes on physiological as well as psychological stress indicators (Chapter 2). The second study examined the effects of GR variants (genotypes and haplotypes) and promoter methylation level on both the SAM system and the HPA axis stress reactivity (Chapter 3). The third study comprised the characterization of CRH promoter haplotypes in an in-vitro study and the association of the CRH promoter with stress indicators in vivo (Chapter 4).

In order to investigate the psychobiological consequences of acute stress under laboratory conditions, a wide range of methods for socially evaluative stress induction have been developed. The present dissertation is concerned with evaluating a virtual reality (VR)-based adaptation of one of the most widely used of those methods, the Trier Social Stress Test (TSST). In the three empirical studies collected in this dissertation, we aimed to examine the efficacy and possible areas of application of the adaptation of this well-established psychosocial stressor in a virtual environment. We found that the TSST-VR reliably incites the activation of the major stress effector systems in the human body, albeit in a slightly less pronounced way than the original paradigm. Moreover, the experience of presence is discussed as one potential factor of influence in the origin of the psychophysiological stress response. Lastly, we present a use scenario for the TSST-VR in which we employed the method to investigate the effects of acute stress on emotion recognition performance. We conclude that, due to its advantages concerning versatility, standardization and economic administration, the paradigm harbors enormous potential not only for psychobiological research, but other applications such as clinical practice as well. Future studies should further explore the underlying effect mechanisms of stress in the virtual realm and the implementation of VR-based paradigms in different fields of application.

Entrepreneurship has become an essential phenomenon all over the world because it is a major driving force behind the economic growth and development of a country. It is widely accepted that entrepreneurship development in a country creates new jobs, pro-motes healthy competition through innovation, and benefits the social well being of individuals and societies. The policymakers in both developed and developing countries focus on entrepreneurship because it helps to alleviate impediments to economic development and social welfare. Therefore, policymakers and academic researchers consider the promotion of entrepreneurship as essential for the economy and research-based support is needed for further development of entrepreneurship activities.
The impact of entrepreneurial activities on economic and social development also varies from country to country. The effect of entrepreneurial activities on economic and social development also varies from country to country because the level of entrepreneur-ship activities also varies from one region to another or one country to another. To under-stand these variations, policymakers have investigated the determinants of entrepreneur-ship at different levels, such as the individual, industry, and country levels. Moreover, entrepreneurship behavior is influenced by various personal and environmental level factors. However, these personal-level factors cannot be separated from the surrounding environment.
The link between religion and entrepreneurship is well established and can be traced back to Weber (1930). Researchers have analyzed the relationship between religion and entrepreneurship from various perspectives, and the research related to religion and entrepreneurship is diversified and scattered across disciplines. This dissertation tries to explain the link between religion and entrepreneurship, specifically Islamic religion and entrepreneurship. Technically this dissertation comprises three parts. The first part of this dissertation consists of two chapters that discuss the definition and theories of entrepreneurship (Chapter 2) and the theoretical relationship between religion and entrepreneur-ship (Chapter 3).
The second part of this dissertation (Chapter 4) provides an overview of the field with a purpose to gain a better understanding of the field’s current state of knowledge to bridge the different views and perspectives. In order to provide an overview of the field, a systematic literature search leading to a descriptive overview of the field based on 270 articles published in 163 journals Subsequently, bibliometric methods are used to identify thematic clusters, the most influential authors and articles, and how they are connected.
The third part of this dissertation (Chapter 5) empirically evaluates the influence of Islamic values and Islamic religious practices on entrepreneurship intentions within the Islamic community. Using the theory of planned behavior as a theoretical lens, we also take into account that the relationship between religion and entrepreneurial intentions can be mediated by individual’s attitude towards entrepreneurship. A self-administrative questionnaire was used to collect the responses from a sample of 1895 Pakistani university students. A structured equation modeling was adopted to perform a nuanced assessment of the relationship between Islamic values and practices and entrepreneurship intentions and to account for mediating effect of attitude towards entrepreneurship.
The research on religion and entrepreneurship has increased sharply during the last years and is scattered across various academic disciplines and fields. The analysis identifies and characterize the most important publications, journals, and authors in the area and map the analyzed religions and regions. The comprehensive overview of previous studies allows us to identify research gaps and derive avenues for future research in a substantiated way. Moreover, this dissertation helps the research scholars to understand the field in its entirety, identify relevant articles, and to uncover parallels and differences across religions and regions. Besides, the study reveals a lack of empirical research related to specific religions and specific regions. Therefore, scholars can take these regions and religions into consideration when conducting empirical research.
Furthermore, the empirical analysis about the influence of Islamic religious values and Islamic religious practices show that Islamic values served as a guiding principle in shaping people’s attitudes towards entrepreneurship in an Islamic community; they had an indirect influence on entrepreneurship intention through attitude. Similarly, the relationship between Islamic religious practices and the entrepreneurship intentions of students was fully mediated by the attitude towards entrepreneurship. Furthermore, this dissertation contributes to prior research on entrepreneurship in Islamic communities by applying a more fine-grained approach to capture the link between religion and entrepreneurship. Moreover, it contributes to the literature on entrepreneurship intentions by showing that the influence of religion on entrepreneurship intentions is mainly due to religious values and practices, which shape the attitude towards entrepreneurship and thereby influence entrepreneurship intentions in religious communities. The entrepreneur-ship research has put a higher emphasis on assessing the influence of a diverse set of con-textual factors. This dissertation introduces Islamic values and Islamic religious practices as critical contextual factors that shape entrepreneurship in countries that are characterized by the Islamic religion.

Why they rebel peacefully: On the violence-reducing effects of a positive attitude towards democracy

Under the impression of Europe’s drift into Nazism and Stalinism in the first half of the 20th century, social psychological research has focused strongly on dangers inherent in people’s attachment to a political system. The dissertation at hand contributes to a more differentiated perspective by examining violence-reducing aspects of political system attachment in four consecutive steps: First, it highlights attachment to a social group as a resource for violence prevention on an intergroup level. The results suggest that group attachment fosters self-control, a well-known protective factor against violence. Second, it demonstrates violence-reducing influences of attachment on a societal level. The findings indicate that attachment to a democracy facilitate peaceful and prevent violent protest tendencies. Third, it introduces the concept of political loyalty, defined as a positive attitude towards democracy, in order to clarify the different approaches of political system attachment. A set of three studies show the reliability and validity of a newly developed political loyalty questionnaire that distinguishes between affective and cognitive aspects. Finally, the dissertation differentiates former findings with regard to protest tendencies using the concept of political loyalty. A set of two experiments show that affective rather than cognitive aspects of political loyalty instigate peaceful protest tendencies and prevent violent ones. Implications of this dissertation for political engagement and peacebuilding as well as avenues for future research are discussed.

This dissertation details how Zeami (ca. 1363 - ca.1443) understood his adoption of the heavenly woman dance within the historical conditions of the Muromachi period. He adopted the dance based on performances by the Ōmi troupe player Inuō in order to expand his own troupe’s repertoire to include a divinely powerful, feminine character. In the first chapter, I show how Zeami, informed by his success as a sexualized child in the service of the political elite (chigo), understood the relationship between performer and audience in gendered terms. In his treatises, he describes how a player must create a complementary relationship between patron and performer (feminine/masculine or yin/yang) that escalates to an ecstasy of successful communication between the two poles, resembling sexual union. Next, I look at how Zeami perceived Inuō’s relationships with patrons, the daimyo Sasaki Dōyo in chapter two and shogun Ashikaga Yoshimitsu in chapter three. Inuō was influenced by Dōyo’s masculine penchant for powerful, awe-inspiring art, but Zeami also recognized that Inuō was able to complement Dōyo’s masculinity with feminine elegance (kakari and yūgen). In his relationship with Yoshimitsu, Inuō used the performance of subversion, both in his public persona and in the aesthetic of his performances, to maintain a rebellious reputation appropriate within the climate of conflict among the martial elite. His play “Aoi no ue” draws on the aristocratic literary tradition of the Genji monogatari, giving Yoshimitsu the role of Prince Genji and confronting him with the consequences of betrayal in the form of a demonic, because jilted, Lady Rokujō. This performance challenged Zeami’s early notion that the extreme masculinity of demons and elegant femininity as exemplified by the aristocracy must be kept separate in character creation. In the fourth chapter, I show how Zeami also combined dominance (masculinity) and submission (femininity) in the corporal capacity of a single player when he adopted the heavenly woman dance. The heavenly woman dance thus complemented not only the masculinity of his male patrons with femininity but also the political power of his patrons with another dominant power, which plays featuring the heavenly woman dance label divine rather than masculine.

Theoretical and empirical research assumes a negative development of student achievement motivation over the course of their school careers (i.e., mean-level declines of achievement motivation). However, the exact magnitude of this motivational change remains elusive and it is unclear whether different motivational constructs show similar developmental trends. Furthermore, it is unknown whether motivational declines are related to a particular school stage (i.e., elementary, middle, or high school) or the school transition, and which additional changes are associated with motivational decreases (e.g., changes in student achievement). Finally, previous research has remained inconsistent regarding the question whether ability grouping of students helps prevent motivational declines or results in additional motivational “costs” for students.
This dissertation presents three articles that were designed to address these research questions. In Article 1, a meta-analysis based on 107 independent longitudinal studies investigated student mean-level changes in self-esteem, academic self-concept, academic self-efficacy, intrinsic motivation, and achievement goals from first to 13th grade. Article 2 comprised two longitudinal studies with German adolescents (Study: n = 745 students assessed in four waves in grades 5-7; Study 2: n = 1420 students assessed in four waves in grades 5-8). Both longitudinal studies investigated the separate and the joint development of achievement goals, interest, and achievement in math. In Article 3, a longitudinal study (n = 296 high-ability students assessed in four waves in grades 5-7) investigated the effects of full-time ability grouping on student development of academic self-concept and achievement in math.
The meta-analysis revealed significant decreases in math and language academic self-concept, intrinsic motivation, and mastery and performance-approach goals, whereas no significant changes in self-esteem, general academic self-concept, academic self-efficacy, and performance-avoidance goals were found. Interestingly, motivational declines were not related to school stage or school transition. In Article 2, decreases in interest and mastery, performance-approach, and performance-avoidance goals were indicated by both longitudinal studies. Development of mastery and performance-approach goals was positively related or unrelated to development in interest and achievement, whereas development of performance-avoidance goals was negatively related or unrelated to development of interest and achievement. Finally, the longitudinal study in Article 3 revealed no significant change in student academic self-concept in math over time. Ability grouping showed no positive or negative effects on student academic self-concept. However, high-ability students that were grouped together demonstrated greater gains in their achievement than high-ability students in regular classes.

This dissertation investigates corporate acquisition decisions that represent important corporate development activities for family and non-family firms. The main research objective of this dissertation is to generate insights into the subjective decision-making behavior of corporate decision-makers from family and non-family firms and their weighting of M&A decision-criteria during the early pre-acquisition target screening and selection process. The main methodology chosen for the investigation of M&A decision-making preferences and the weighting of M&A decision criteria is a choice-based conjoint analysis. The overall sample of this dissertation consists of 304 decision-makers from 264 private and public family and non-family firms from mainly Germany and the DACH-region. In the first empirical part of the dissertation, the relative importance of strategic, organizational and financial M&A decision-criteria for corporate acquirers in acquisition target screening is investigated. In addition, the author uses a cluster analysis to explore whether distinct decision-making patterns exist in acquisition target screening. In the second empirical part, the dissertation explores whether there are differences in investment preferences in acquisition target screening between family and non-family firms and within the group of family firms. With regards to the heterogeneity of family firms, the dissertation generated insights into how family-firm specific characteristics like family management, the generational stage of the firm and non-economic goals such as transgenerational control intention influences the weighting of different M&A decision criteria in acquisition target screening. The dissertation contributes to strategic management research, in specific to M&A literature, and to family business research. The results of this dissertation generate insights into the weighting of M&A decision-making criteria and facilitate a better understanding of corporate M&A decisions in family and non-family firms. The findings show that decision-making preferences (hence the weighting of M&A decision criteria) are influenced by characteristics of the individual decision-maker, the firm and the environment in which the firm operates.

In the modeling context, non-linearities and uncertainty go hand in hand. In fact, the utility function's curvature determines the degree of risk-aversion. This concept is exploited in the first article of this thesis, which incorporates uncertainty into a small-scale DSGE model. More specifically, this is done by a second-order approximation, while carrying out the derivation in great detail and carefully discussing the more formal aspects. Moreover, the consequences of this method are discussed when calibrating the equilibrium condition. The second article of the thesis considers the essential model part of the first paper and focuses on the (forward-looking) data needed to meet the model's requirements. A large number of uncertainty measures are utilized to explain a possible approximation bias. The last article keeps to the same topic but uses statistical distributions instead of actual data. In addition, theoretical (model) and calibrated (data) parameters are used to produce more general statements. In this way, several relationships are revealed with regard to a biased interpretation of this class of models. In this dissertation, the respective approaches are explained in full detail and also how they build on each other.
In summary, the question remains whether the exact interpretation of model equations should play a role in macroeconomics. If we answer this positively, this work shows to what extent the practical use can lead to biased results.

Internet interventions have gained popularity and the idea is to use them to increase the availability of psychological treatment. Research suggests that internet interventions are effective for a number of psychological disorders with effect sizes comparable to those found in face-to-face treatment. However, when provided as an add-on to treatment as usual, internet interventions do not seem to provide additional benefit. Furthermore, adherence and dropout rates vary greatly between studies, limiting the generalizability of the findings. This underlines the need to further investigate differences between internet interventions, participating patients, and their usage of interventions. A stronger focus on the processes of change seems necessary to better understand the varying findings regarding outcome, adherence and dropout in internet interventions. Thus, the aim of this dissertation was to investigate change processes in internet interventions and the factors that impact treatment response. This could help to identify important variables that should be considered in research on internet interventions as well as in clinical settings that make use of internet interventions.
Study I (Chapter 5) investigated early change patterns in participants of an internet intervention targeting depression. Data from 409 participants were analyzed using Growth Mixture Modeling. Specifically a piecewise model was applied to model change from screening to registration (pretreatment) and early change (registration to week four of treatment). Three early change patterns were identified; two were characterized by improvement and one by deterioration. The patterns were predictive of treatment outcome. The results therefore indicated that early change should be closely monitored in internet interventions, as early change may be an important indicator of treatment outcome.
Study II (Chapter 6) picked up on the idea of analyzing change patterns in internet interventions and extended it by using the Muthen-Roy model to identify change-dropout patterns. A sligthly bigger sample of the dataset from Study I was analyzed (N = 483). Four change-dropout patterns emerged; high risk of dropout was associated with rapid improvement and deterioration. These findings indicate that clinicians should consider how dropout may depend on patient characteristics as well as symptom change, as dropout is associated with both deterioration and a good enough dosage of treatment.
Study III (Chapter 7) compared adherence and outcome in different participant groups and investigated the impact of adherence to treatment components on treatment outcome in an internet intervention targeting anxiety symptoms. 50 outpatient participants waiting for face- to-face treatment and 37 self-referred participants were compared regarding adherence to treatment components and outcome. In addition, outpatient participants were compared to a matched sample of outpatients, who had no access to the internet intervention during the waiting period. Adherence to treatment components was investigated as a predictor of treatment outcome. Results suggested that especially adherence may vary depending on participant group. Also using specific measures of adherence such as adherence to treatment components may be crucial to detect change mechanisms in internet interventions. Fostering adherence to treatment components in participants may increase the effectiveness of internet interventions.
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.

Global food security poses large challenges to a fast changing human society and has been a key topic for scientists, agriculturist, and policy makers in the 21st century. The United Nation predicts a total world population of 9.15 billion in 2050 and defines the provision of food security as the second major point in the UN Sustainable Development Goals. As the capacities of both, land and water resources, are finite and locally heavily overused, reducing agriculture’s environmental impact while meeting an increasing demand for food of a constantly growing population is one of the greatest challenges of our century. Therefore, a multifaceted solution is required, including approaches using geospatial data to optimize agricultural food production.
The availability of precise and up-to-date information on vegetation parameters is mandatory to fulfill the requirements of agricultural applications. Direct field measurements of such vegetation parameters are expensive and time-consuming. On the contrary, remote sensing offers a variety of techniques for a cost-effective and non-destructive retrieval of vegetation parameters. Although not widely used, hyperspectral thermal infrared (TIR) remote sensing has demonstrated being a valuable addition to existing remote sensing techniques for the retrieval of vegetation parameters.
This thesis examined the potential of TIR imaging spectroscopy as an important contribution to the growing need of food security. The main scientific question dealt with the extraction of vegetation parameters from imaging TIR spectroscopy. To this end, two studies impressively demonstrated the ability of extracting vegetation related parameters from leaf emissivity spectra: (i) the discrimination of eight plant species based on their emissivity spectra and (ii) the detection of drought stress in potato plants using temperature measures and emissivity spectra.
The datasets used in these studies were collected using the Telops Hyper-Cam LW, a novel imaging spectrometer. Since this FTIR spectrometer presents some particularities, special attention was paid on the development of dedicated experimental data acquisition setups and on data processing chains. The latter include data preprocessing and the development of algorithms for extracting precise surface temperatures, reproducible emissivity spectra and, in the end, vegetation parameters.
The spectrometer’s versatility allows the collection of airborne imaging spectroscopy datasets. Since the general availability of airborne TIR spectrometers is limited, the preprocessing and
data extraction methods are underexplored compared to reflective remote sensing. This counts especially for atmospheric correction (AC) and temperature and emissivity separation (TES) algorithms. Therefore, we implemented a powerful simulation environment for the development of preprocessing algorithms for airborne hyperspectral TIR image data. This simulation tool is designed in a modular way and includes the image data acquisition and processing chain from surface temperature and emissivity to the final at-sensor radiance data. It includes a series of available algorithms for TES, AC as well as combined AC and TES approaches. Using this simulator, one of the most promising algorithms for the preprocessing of airborne TIR data – ARTEMISS – was significantly optimized. The retrieval error of the atmospheric water vapor during the atmospheric characterization was reduced. As a result, this improvement in atmospheric characterization accuracy enhanced the subsequent retrieval of surface temperatures and surface emissivities intensely.
Although, the potential of hyperspectral TIR applications in ecology, agriculture, and biodiversity has been impressively demonstrated, a serious contribution to a global provision of food security requires the retrieval of vegetation related parameters with global coverage, high spatial resolution and at high revisit frequencies.
Emerging from the findings in this thesis, the spectral configuration of a spaceborne TIR spectrometer concept was developed. The sensors spectral configuration aims at the retrieval of precise land surface temperatures and land surface emissivity spectra. Complemented with additional characteristics, i.e. short revisit times and a high spatial resolution, this sensor potentially allows the retrieval of valuable vegetation parameters needed for agricultural optimizations. The technical feasibility of such a sensor concept underlines the potential contribution to the multifaceted solution required for achieving the challenging goal of guaranteeing global food security in a world of increasing population.
In conclusion, thermal remote sensing and more precisely hyperspectral thermal remote sensing has been presented as a valuable technique for a variety of applications contributing to the final goal of a global food security.

This dissertation deals with consistent estimates in household surveys. Household surveys are often drawn via cluster sampling, with households sampled at the first stage and persons selected at the second stage. The collected data provide information for estimation at both the person and the household level. However, consistent estimates are desirable in the sense that the estimated household-level totals should coincide with the estimated totals obtained at the person-level. Current practice in statistical offices is to use integrated weighting. In this approach consistent estimates are guaranteed by equal weights for all persons within a household and the household itself. However, due to the forced equality of weights, the individual patterns of persons are lost and the heterogeneity within households is not taken into account. In order to avoid the negative consequences of integrated weighting, we propose alternative weighting methods in the first part of this dissertation that ensure both consistent estimates and individual person weights within a household. The underlying idea is to limit the consistency conditions to variables that emerge in both the personal and household data sets. These common variables are included in the person- and household-level estimator as additional auxiliary variables. This achieves consistency more directly and only for the relevant variables, rather than indirectly by forcing equal weights on all persons within a household. Further decisive advantages of the proposed alternative weighting methods are that original individual rather than the constructed aggregated auxiliaries are utilized and that the variable selection process is more flexible because different auxiliary variables can be incorporated in the person-level estimator than in the household-level estimator.
In the second part of this dissertation, the variances of a person-level GREG estimator and an integrated estimator are compared in order to quantify the effects of the consistency requirements in the integrated weighting approach. One of the challenges is that the estimators to be compared are of different dimensions. The proposed solution is to decompose the variance of the integrated estimator into the variance of a reduced GREG estimator, whose underlying model is of the same dimensions as the person-level GREG estimator, and add a constructed term that captures the effects disregarded by the reduced model. Subsequently, further fields of application for the derived decomposition are proposed such as the variable selection process in the field of econometrics or survey statistics.

Competitive analysis is a well known method for analyzing online algorithms.
Two online optimization problems, the scheduling problems and the list accessing problems, are considered in the thesis of Yida Zhu in the respect of this method.
For both problems, several existing online and offline algorithms are studied. Their performances are compared with the performances of corresponding offline optimal algorithms.
In particular, the list accessing algorithm BIT is carefully reviewed.
The classical proof of its worst case performance get simplified by adapting the knowledge about the optimal offline algorithm.
With regard to average case analysis, a new closed formula is developed to determine the performance of BIT on specific class of instances.
All algorithm considered in this thesis are also implemented in Julia.
Their empirical performances are studied and compared with each other directly.

This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.

This thesis discusses revue as a significantly inter-cultural genre in the history of global theatre. During the ‘modernisation’ period in Europe, America and Japan, most major urban cities experienced a boom in revue venues and performances. Few studies about revue have yet been done in theatre studies or in urban cultural studies. My thesis will attempt to reevaluate and redefine revue as a highly intercultural theatre genre by using the concept of liminality. In other words, the aim is to examine revue as a genre built on ‘modern composition of betweenness’, bridging seemingly opposing elements, such as the foreign and the domestic, the classic and the innovative, the traditional and the modern, the professional and the amateur, high and low culture, and the feminine and the masculine. The goal is to regard revue as a liminal genre constructed amidst the negotiations between these binaries, existing in a state of constant flux.
The purpose of this approach is to capture revue as a transitory phenomena in five dimensions: conceptual, spatial, temporal, categorical and physical. Over the course of six chapters, this
inter-disciplinary discussion will reveal the reasons why and the ways by which revue came to establish its prominent position in the Japanese theatre industry. The whole structure is also an attempt to provide plausible ways to apply sociological considerations to theatre studies.

Nonlocal operators are used in a wide variety of models and applications due to many natural phenomena being driven by nonlocal dynamics. Nonlocal operators are integral operators allowing for interactions between two distinct points in space. The nonlocal models investigated in this thesis involve kernels that are assumed to have a finite range of nonlocal interactions. Kernels of this type are used in nonlocal elasticity and convection-diffusion models as well as finance and image analysis. Also within the mathematical theory they arouse great interest, as they are asymptotically related to fractional and classical differential equations.
The results in this thesis can be grouped according to the following three aspects: modeling and analysis, discretization and optimization.
Mathematical models demonstrate their true usefulness when put into numerical practice. For computational purposes, it is important that the support of the kernel is clearly determined. Therefore nonlocal interactions are typically assumed to occur within an Euclidean ball of finite radius. In this thesis we consider more general interaction sets including norm induced balls as special cases and extend established results about well-posedness and asymptotic limits.
The discretization of integral equations is a challenging endeavor. Especially kernels which are truncated by Euclidean balls require carefully designed quadrature rules for the implementation of efficient finite element codes. In this thesis we investigate the computational benefits of polyhedral interaction sets as well as geometrically approximated interaction sets. In addition to that we outline the computational advantages of sufficiently structured problem settings.
Shape optimization methods have been proven useful for identifying interfaces in models governed by partial differential equations. Here we consider a class of shape optimization problems constrained by nonlocal equations which involve interface-dependent kernels. We derive the shape derivative associated to the nonlocal system model and solve the problem by established numerical techniques.

In this thesis, we aim to study the sampling allocation problem of survey statistics under uncertainty. We know that the stratum specific variances are generally not known precisely and we have no information about the distribution of uncertainty. The cost of interviewing each person in a stratum is also a highly uncertain parameter as sometimes people are unavailable for the interview. We propose robust allocations to deal with the uncertainty in both stratum specific variances and costs. However, in real life situations, we can face such cases when only one of the variances or costs is uncertain. So we propose three different robust formulations representing these different cases. To the best of our knowledge robust allocation in the sampling allocation problem has not been considered so far in any research.
The first robust formulation for linear problems was proposed by Soyster (1973). Bertsimas and Sim (2004) proposed a less conservative robust formulation for linear problems. We study these formulations and extend them for the nonlinear sampling allocation problem. It is very unlikely to happen that all of the stratum specific variances and costs are uncertain. So the robust formulations are in such a way that we can select how many strata are uncertain which we refer to as the level of uncertainty. We prove that an upper bound on the probability of violation of the nonlinear constraints can be calculated before solving the robust optimization problem. We consider various kinds of datasets and compute robust allocations. We perform multiple experiments to check the quality of the robust allocations and compare them with the existing allocation techniques.

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.

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.

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.

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.

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.

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.

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 location 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. In 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. Moreover, 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. This 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. On 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. In 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. To 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. As 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. Numerical 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. Aims 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. Materials 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. Conclusion: 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).

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.

At any given moment, our senses are assaulted with a flood of information from the environment around us. We need to pick our way through all this information in order to be able to effectively respond to that what is relevant to us. In most cases we are usually able to select information relevant to our intentions from what is not relevant. However, what happens to the information that is not relevant to us? Is this irrelevant information completely ignored so that it does not affect our actions? The literature suggests that even though we mayrnignore an irrelevant stimulus, it may still interfere with our actions. One of the ways in which irrelevant stimuli can affect actions is by retrieving a response with which it was associated. An irrelevant stimulus that is presented in close temporal contiguity with a relevant stimulus can be associated with the response made to the relevant stimulus " an observation termed distractor-response binding (Rothermund, Wentura, & De Houwer, 2005). The studies presented in this work take a closer look at such distractor-response bindings, and therncircumstances in which they occur. Specifically, the study reported in chapter 6 examined whether only an exact repetition of the distractor can retrieve the response with which it was associated, or whether even similar distractors may cause retrieval. The results suggested that even repeating a similar distractor caused retrieval, albeit less than an exact repetition. In chapter 7, the existence of bindings between a distractor and a response were tested beyond arnperceptual level, to see whether they exist at an (abstract) conceptual level. Similar to perceptual repetition, distractor-based retrieval of the response was observed for the repetition of concepts. The study reported in chapter 8 of this work examined the influence of attention on the feature-response binding of irrelevant features. The results pointed towards a stronger binding effects when attention was directed towards the irrelevant feature compared to whenrnit was not. The study in chapter 9 presented here looked at the processes underlying distractor-based retrieval and distractor inhibition. The data suggest that motor processes underlie distractor-based retrieval and cognitive process underlie distractor inhibition. Finally, the findings of all four studies are also discussed in the context of learning.

Water-deficit stress, usually shortened to water- or drought stress, is one of the most critical abiotic stressors limiting plant growth, crop yield and quality concerning food production. Today, agriculture consumes about 80-90% of the global freshwater used by humans and about two thirds are used for crop irrigation. An increasing world population and a predicted rise of 1.0-2.5-°C in the annual mean global temperature as a result of climate change will further increase the demand of water in agriculture. Therefore, one of the most challenging tasks of our generation is to reduce the amount water used per unit yield to satisfy the second UN Sustainable Development Goal and to ensure global food security. Precision agriculture offers new farming methods with the goal to improve the efficiency of crop production by a sustainable use of resources. Plant responses to water stress are complex and co-occur with other environmental stresses under natural conditions. In general, water stress causes plant physiological and biochemical changes that depend on the severity and the duration of the actual plant water deficit. Stomatal closure is one of the first responses to plant water stress causing a decrease in plant transpiration and thus an increase in plant temperature. Prolonged or severe water stress leads to irreversible damage to the photosynthetic machinery and is associated with decreasing chlorophyll content and leaf structural changes (e.g., leaf rolling). Since a crop can already be irreversibly damaged by only mild water deficit, a pre-visual detection of water stress symptoms is essential to avoid yield loss. Remote sensing offers a non-destructive and spatio-temporal method for measuring numerous physiological, biochemical and structural crop characteristics at different scales and thus is one of the key technologies used in precision agriculture. With respect to the detection of plant responses to water stress, the current state-of-the-art hyperspectral remote sensing imaging techniques are based on measurements of thermal infrared emission (TIR; 8-14 -µm), visible, near- and shortwave infrared reflectance (VNIR/SWIR; 0.4-2.5 -µm), and sun-induced fluorescence (SIF; 0.69 and 0.76 -µm). It is, however, still unclear how sensitive these techniques are with respect to water stress detection. Therefore, the overall aim of this dissertation was to provide a comparative assessment of remotely sensed measures from the TIR, SIF, and VNIR/SWIR domains for their ability to detect plant responses to water stress at ground- and airborne level. The main findings of this thesis are: (i) temperature-based indices (e.g., CWSI) were most sensitive for the detection of plant water stress in comparison to reflectance-based VNIR/SWIR indices (e.g., PRI) and SIF at both, ground- and airborne level, (ii) for the first time, spectral emissivity as measured by the new hyperspectral TIR instrument could be used to detect plant water stress at ground level. Based on these findings it can be stated that hyperspectral TIR remote sensing offers great potential for the detection of plant responses to water stress at ground- and airborne level based on both TIR key variables, surface temperature and spectral emissivity. However, the large-scale application of water stress detection based on hyperspectral TIR measures in precision agriculture will be challenged by several problems: (i) missing thresholds of temperature-based indices (e.g., CWSI) for the application in irrigation scheduling, (ii) lack of current TIR satellite missions with suitable spectral and spatial resolution, (iii) lack of appropriate data processing schemes (including atmosphere correction and temperature emissivity separation) for hyperspectral TIR remote sensing at airborne- and satellite level.

Educational researchers have intensively investigated students" academic self-concept (ASC) and self-efficacy (SE). Both constructs are part of the competence-related self-perceptions of students and are considered to support students" academic success and their career development in a positive manner (e.g., Abele-Brehm & Stief, 2004; Richardson, Abraham, & Bond, 2012; Schneider & Preckel, 2017). However, there is a lack of basic research on ASC and SE in higher education in general, and in undergraduate psychology courses in particular. Therefore, according to the within-network and between-network approaches of construct validation (Byrne, 1984), the present dissertation comprises three empirical studies examining the structure (research question 1), measurement (research question 2), correlates (research question 3), and differentiation (research question 4) of ASC and SE in a total sample of N = 1243 psychology students. Concerning research question 1, results of confirmatory factor analysis (CFAs) implied that students" ASC and SE are domain-specific in the sense of multidimensionality, but they are also hierarchically structured, with a general factor at the apex according to the nested Marsh/Shavelson model (NMS model, Brunner et al., 2010). Additionally, psychology students" SE to master specific psychological tasks in different areas of psychological application could be described by a 2-dimensional model with six factors according to the Multitrait-Multimethod (MTMM)-approach (Campbell & Fiske, 1959). With regard to research question 2, results revealed that the internal structure of ASC and SE could be validly assessed. However, the assessment of psychology students" SE should follow a task-specific measurement strategy. Results of research question 3 further showed that both constructs of psychology students" competence-related self-perceptions were positively correlated to achievement in undergraduate psychology courses if predictor (ASC, SE) corresponded to measurement specificity of the criterion (achievement). Overall, ASC provided substantially stronger relations to achievement compared to SE. Moreover, there was evidence for negative paths (contrast effects) from achievement in one psychological domain on ASC of another psychological domain as postulated by the internal/external frame of reference (I/E) model (Marsh, 1986). Finally, building on research questions 1 to 3 (structure, measurement, and correlates of ASC and SE), psychology students" ASC and SE were be differentiated on an empirical level (research question 4). Implications for future research practices are discussed. Furthermore, practical implications for enhancing ASC and SE in higher education are proposed to support academic achievement and the career development of psychology students.

Digital libraries have become a central aspect of our live. They provide us with an immediate access to an amount of data which has been unthinkable in the past. Support of computers and the ability to aggregate data from different libraries enables small projects to maintain large digital collections on various topics. A central aspect of digital libraries is the metadata -- the information that describes the objects in the collection. Metadata are digital and can be processed and studied automatically. In recent years, several studies considered different aspects of metadata. Many studies focus on finding defects in the data. Specifically, locating errors related to the handling of personal names has drawn attention. In most cases the studies concentrate on the most recent metadata of a collection. For example, they look for errors in the collection at day X. This is a reasonable approach for many applications. However, to answer questions such as when the errors were added to the collection we need to consider the history of the metadata itself. In this work, we study how the history of metadata can be used to improve the understanding of a digital library. To this goal, we consider how digital libraries handle and store their metadata. Based in this information we develop a taxonomy to describe available historical data which means data on how the metadata records changed over time. We develop a system that identifies changes to metadata over time and groups them in semantically related blocks. We found that historical meta data is often unavailable. However, we were able to apply our system on a set of large real-world collections. A central part of this work is the identification and analysis of changes to metadata which corrected a defect in the collection. These corrections are the accumulated effort to ensure data quality of a digital library. In this work, we present a system that automatically extracts corrections of defects from the set of all modifications. We present test collections containing more than 100,000 test cases which we created by extracting defects and their corrections from DBLP. This collections can be used to evaluate automatic approaches for error detection. Furthermore, we use these collections to study properties of defects. We will concentrate on defects related to the person name problem. We show that many defects occur in situations where very little context information is available. This has major implications for automatic defect detection. We also show that properties of defects depend on the digital library in which they occur. We also discuss briefly how corrected defects can be used to detect hidden or future defects. Besides the study of defects, we show that historical metadata can be used to study the development of a digital library over time. In this work, we present different studies as example how historical metadata can be used. At first we describe the development of the DBLP collection over a period of 15 years. Specifically, we study how the coverage of different computer science sub fields changed over time. We show that DBLP evolved from a specialized project to a collection that encompasses most parts of computer science. In another study we analyze the impact of user emails to defect corrections in DBLP. We show that these emails trigger a significant amount of error corrections. Based on these data we can draw conclusions on why users report a defective entry in DBLP.

The search for relevant determinants of knowledge acquisition has a long tradition in educational research, with systematic analyses having started over a century ago. To date, a variety of relevant environmental and learner-related characteristics have been identified, providing a wide body of empirical evidence. However, there are still some gaps in the literature, which are highlighted in the current dissertation. The dissertation includes two meta-analyses summarizing the evidence on the effectiveness of electrical brain stimulation and the effects of prior knowledge on later learning outcomes and one empirical study employing latent profile transition analysis to investigate the changes in conceptual knowledge over time. The results from the three studies demonstrate how learning outcomes can be advanced by input from the environment and that they are highly related to the students" level of prior knowledge. It is concluded that the effects of environmental and learner-related variables impact both the biological and cognitive processes underlying knowledge acquisition. Based on the findings from the three studies, methodological and practical implications are provided, followed by an outline of four recommendations for future research on knowledge acquisition.

This thesis is divided into three main parts: The description of the calibration problem, the numerical solution of this problem and the connection to optimal stochastic control problems. Fitting model prices to given market prices leads to an abstract least squares formulation as calibration problem. The corresponding option price can be computed by solving a stochastic differential equation via the Monte-Carlo method which seems to be preferred by most practitioners. Due to the fact that the Monte-Carlo method is expensive in terms of computational effort and requires memory, more sophisticated stochastic predictor-corrector schemes are established in this thesis. The numerical advantage of these predictor-corrector schemes ispresented and discussed. The adjoint method is applied to the calibration. The theoretical advantage of the adjoint method is discussed in detail. It is shown that the computational effort of gradient calculation via the adjoint method is independent of the number of calibration parameters. Numerical results confirm the theoretical results and summarize the computational advantage of the adjoint method. Furthermore, provides the connection to optimal stochastic control problems is proven in this thesis.

Surveys are commonly tailored to produce estimates of aggregate statistics with a desired level of precision. This may lead to very small sample sizes for subpopulations of interest, defined geographically or by content, which are not incorporated into the survey design. We refer to subpopulations where the sample size is too small to provide direct estimates with adequate precision as small areas or small domains. Despite the small sample sizes, reliable small area estimates are needed for economic and political decision making. Hence, model-based estimation techniques are used which increase the effective sample size by borrowing strength from other areas to provide accurate information for small areas. The paragraph above introduced small area estimation as a field of survey statistics where two conflicting philosophies of statistical inference meet: the design-based and the model-based approach. While the first approach is well suited for the precise estimation of aggregate statistics, the latter approach furnishes reliable small area estimates. In most applications, estimates for both large and small domains based on the same sample are needed. This poses a challenge to the survey planner, as the sampling design has to reflect different and potentially conflicting requirements simultaneously. In order to enable efficient design-based estimates for large domains, the sampling design should incorporate information related to the variables of interest. This may be achieved using stratification or sampling with unequal probabilities. Many model-based small area techniques require an ignorable sampling design such that after conditioning on the covariates the variable of interest does not contain further information about the sample membership. If this condition is not fulfilled, biased model-based estimates may result, as the model which holds for the sample is different from the one valid for the population. Hence, an optimisation of the sampling design without investigating the implications for model-based approaches will not be sufficient. Analogously, disregarding the design altogether and focussing only on the model is prone to failure as well. Instead, a profound knowledge of the interplay between the sample design and statistical modelling is a prerequisite for implementing an effective small area estimation strategy. In this work, we concentrate on two approaches to address this conflict. Our first approach takes the sampling design as given and can be used after the sample has been collected. It amounts to incorporate the survey design into the small area model to avoid biases stemming from informative sampling. Thus, once a model is validated for the sample, we know that it holds for the population as well. We derive such a procedure under a lognormal mixed model, which is a popular choice when the support of the dependent variable is limited to positive values. Besides, we propose a three pillar strategy to select the additional variable accounting for the design, based on a graphical examination of the relationship, a comparison of the predictive accuracy of the choices and a check regarding the normality assumptions.rnrnOur second approach to deal with the conflict is based on the notion that the design should allow applying a wide variety of analyses using the sample data. Thus, if the use of model-based estimation strategies can be anticipated before the sample is drawn, this should be reflected in the design. The same applies for the estimation of national statistics using design-based approaches. Therefore, we propose to construct the design such that the sampling mechanism is non-informative but allows for precise design-based estimates at an aggregate level.

In this thesis, we present a new approach for estimating the effects of wind turbines for a local bat population. We build an individual based model (IBM) which simulates the movement behaviour of every single bat of the population with its own preferences, foraging behaviour and other species characteristics. This behaviour is normalized by a Monte-Carlo simulation which gives us the average behaviour of the population. The result is an occurrence map of the considered habitat which tells us how often the bat and therefore the considered bat population frequent every region of this habitat. Hence, it is possible to estimate the crossing rate of the position of an existing or potential wind turbine. We compare this individual based approach with a partial differential equation based method. This second approach produces a lower computational effort but, unfortunately, we lose information about the movement trajectories at the same time. Additionally, the PDE based model only gives us a density profile. Hence, we lose the information how often each bat crosses special points in the habitat in one night. In a next step we predict the average number of fatalities for each wind turbine in the habitat, depending on the type of the wind turbine and the behaviour of the considered bat species. This gives us the extra mortality caused by the wind turbines for the local population. This value is used for a population model and finally we can calculate whether the population still grows or if there already is a decline in population size which leads to the extinction of the population. Using the combination of all these models, we are able to evaluate the conflict of wind turbines and bats and to predict the result of this conflict. Furthermore, it is possible to find better positions for wind turbines such that the local bat population has a better chance to survive. Since bats tend to move in swarm formations under certain circumstances, we introduce swarm simulation using partial integro-differential equations. Thereby, we have a closer look at existence and uniqueness properties of solutions.

Interaction between the Hypothalamic-Pituitary-Adrenal Axis and the Circadian Clock System in Humans
(2017)

Rotation of the Earth creates day and night cycles of 24 h. The endogenous circadian clocks sense these light/dark rhythms and the master pacemaker situated in the suprachiasmatic nucleus of the hypothalamus entrains the physical activities according to this information. The circadian machinery is built from the transcriptional/translational feedback loops generating the oscillations in all nucleated cells of the body. In addition, unexpected environmental changes, called stressors, also challenge living systems. A response to these stimuli is provided immediately via the autonomic-nervous system and slowly via the hypothalamus"pituitary"adrenal (HPA) axis. When the HPA axis is activated, circulating glucocorticoids are elevated and regulate organ activities in order to maintain survival of the organism. Both the clock and the stress systems are essential for continuity and interact with each other to keep internal homeostasis. The physiological interactions between the HPA axis and the circadian clock system are mainly addressed in animal studies, which focus on the effects of stress and circadian disturbances on cardiovascular, psychiatric and metabolic disorders. Although these studies give opportunity to test in whole body, apply unwelcome techniques, control and manipulate the parameters at the high level, generalization of the results to humans is still a debate. On the other hand, studies established with cell lines cannot really reflect the conditions occurring in a living organism. Thus, human studies are absolutely necessary to investigate mechanisms involved in stress and circadian responses. The studies presented in this thesis were intended to determine the effects of cortisol as an end-product of the HPA axis on PERIOD (PER1, PER2 and PER3) transcripts as circadian clock genes in healthy humans. The expression levels of PERIOD genes were measured under baseline conditions and after stress in whole blood. The results demonstrated here have given better understanding of transcriptional programming regulated by pulsatile cortisol at standard conditions and short-term effects of cortisol increase on circadian clocks after acute stress. These findings also draw attention to inter-individual variations in stress response as well as non-circadian functions of PERIOD genes in the periphery, which need to be examined in details in the future.

Automata theory is the study of abstract machines. It is a theory in theoretical computer science and discrete mathematics (a subject of study in mathematics and computer science). The word automata (the plural of automaton) comes from a Greek word which means "self-acting". Automata theory is closely related to formal language theory [99, 101]. The theory of formal languages constitutes the backbone of the field of science now generally known as theoretical computer science. This thesis aims to introduce a few types of automata and studies then class of languages recognized by them. Chapter 1 is the road map with introduction and preliminaries. In Chapter 2 we consider few formal languages associated to graphs that has Eulerian trails. We place few languages in the Chomsky hierarchy that has some other properties together with the Eulerian property. In Chapter 3 we consider jumping finite automata, i. e., finite automata in which input head after reading and consuming a symbol, can jump to an arbitrary position of the remaining input. We characterize the class of languages described by jumping finite automata in terms of special shuffle expressions and survey other equivalent notions from the existing literature. We could also characterize some super classes of this language class. In Chapter 4 we introduce boustrophedon finite automata, i. e., finite automata working on rectangular shaped arrays (i. e., pictures) in a boustrophedon mode and we also introduce returning finite automata that reads the input, line after line, does not alters the direction like boustrophedon finite automata i. e., reads always from left to right, line after line. We provide close relationships with the well-established class of regular matrix (array) languages. We sketch possible applications to character recognition and kolam patterns. Chapter 5 deals with general boustrophedon finite automata, general returning finite automata that read with different scanning strategies. We show that all 32 different variants only describe two different classes of array languages. We also introduce Mealy machines working on pictures and show how these can be used in a modular design of picture processing devices. In Chapter 6 we compare three different types of regular grammars of array languages introduced in the literature, regular matrix grammars, (regular : regular) array grammars, isometric regular array grammars, and variants thereof, focusing on hierarchical questions. We also refine the presentation of (regular : regular) array grammars in order to clarify the interrelations. In Chapter 7 we provide further directions of research with respect to the study that we have done in each of the chapters.

The first part of this thesis offers a theoretical foundation for the analysis of Tolkien- texts. Each of the three fields of interest, nostalgia, utopia, and the pastoral tradition, are introduced in separate chapters. Special attention is given to the interrelations of the three fields. Their history, meaning, and functions are shortly elaborated and definitions applicable to their occurrences in fantasy texts are reached. In doing so, new categories and terms are proposed that enable a detailed analysis of the nostalgic, pastoral, and utopian properties of Tolkien- works. As nostalgia and utopia are important ingredients of pastoral writing, they are each introduced first and are finally related to a definition of the pastoral. The main part of this thesis applies the definitions and insights reached in the theoretical chapters to Tolkien- The Lord of the Rings and The Hobbit. This part is divided into three main sections. Again, the order of the chapters follows the line of argumentation. The first section contains the analysis of pastoral depictions in the two texts. Given the separation of the pastoral into different categories, which were outlined in the theoretical part, the chapters examine bucolic and georgic pastoral creatures and landscapes before turning to non-pastoral depictions, which are sub-divided into the antipastoral and the unpastoral. A separate chapter looks at the bucolic and georgic pastoral- positions and functions in the primary texts. This analysis is followed by a chapter on men- special position in Tolkien- mythology, as their depiction reveals their potential to be both pastoral and antipastoral. The second section of the analytical part is concerned with the role of nostalgia within pastoral culture. The focus is laid on the meaning and function of the different kinds of nostalgia, which were defined in the theoretical part, detectable in bucolic and georgic pastoral cultures. Finally, the analysis turns to the utopian potential of Tolkien- mythology. Again, the focus lies on the pastoral and non-pastoral creatures. Their utopian and dystopian visions are presented and contrasted. This way, different kinds of utopian vision are detected and set in relation to the overall dystopian fate of Tolkien- fictional universe. Drawing on the results of this thesis and on Terry Gifford- ecocritical work, the final chapter argues that Tolkien- texts can be defined as modern pastorals. The connection between Tolkien- work and pastoral literature made explicit in the analysis is thus cemented in generic terms. The conclusion presents a summary of the central findings of this thesis and introduces questions for further study.

A phenomenon of recent decades is that digital marketplaces on the Internet are establishing themselves for a wide variety of products and services. Recently, it has become possible for private individuals to invest in young and innovative companies (so-called "start-ups"). Via Internet portals, potential investors can examine various start-ups and then directly invest in their chosen start-up. In return, investors receive a share in the firm- profit, while companies can use the raised capital to finance their projects. This new way of financing is called "Equity Crowdfunding" (ECF) or "Crowdinvesting". The aim of this dissertation is to provide empirical findings about the characteristics of ECF. In particular, the question of whether ECF is able to overcome geographic barriers, the interdependence of ECF and capital structure, and the risk of failure for funded start-ups and their chances of receiving follow-up funding by venture capitalists or business angels will be analyzed. The results of the first part of this dissertation show that investors in ECF prefer local companies. In particular, investors who invest larger amounts have a stronger tendency to invest in local start-ups. The second part of the dissertation provides first indications of the interdependencies between capital structure and ECF. The analysis makes clear that the capital structure is not a determinant for undertaking an ECF campaign. The third part of the dissertation analyzes the success of companies financed by ECF in a country comparison. The results show that after a successful ECF campaign German companies have a higher chance of receiving follow-up funding by venture capitalists compared to British companies. The probability of survival, however, is slightly lower for German companies. The results provide relevant implications for theory and practice. The existing literature in the area of entrepreneurial finance will be extended by insights into investor behavior, additions to the capital structure theory and a country comparison in ECF. In addition, implications are provided for various actors in practice.

Entrepreneurship is a process of discovering and exploiting opportunities, during which two crucial milestones emerge: in the very beginning when entrepreneurs start their businesses, and in the end when they determine the future of the business. This dissertation examines the establishment and exit of newly created as well as of acquired firms, in particular the behavior and performance of entrepreneurs at these two important stages of entrepreneurship. The first part of the dissertation investigates the impact of characteristics at the individual and at the firm level on an entrepreneur- selection of entry modes across new venture start-up and business takeover. The second part of the dissertation compares firm performance across different entrepreneurship entry modes and then examines management succession issues that family firm owners have to confront. This study has four main findings. First, previous work experience in small firms, same sector experience, and management experience affect an entrepreneur- choice of entry modes. Second, the choice of entry mode for hybrid entrepreneurs is associated with their characteristics, such as occupational experience, level of education, and gender, as well as with the characteristics of their firms, such as location. Third, business takeovers survive longer than new venture start-ups, and both entry modes have different survival determinants. Fourth, the family firm- decision of recruiting a family or a nonfamily manager is not only determined by a manager- abilities, but also by the relationship between the firm- economic and non-economic goals and the measurability of these goals. The findings of this study extend our knowledge on entrepreneurship entry modes by showing that new venture start-ups and business takeovers are two distinct entrepreneurship entry modes in terms of their founders" profiles, their survival rates and survival determinants. Moreover, this study contributes to the literature on top management hiring in family firms: it establishes family firm- non-economic goals as another factor that impacts the family firm- hiring decision between a family and a nonfamily manager.

Why do some people become entrepreneurs while others stay in paid employment? Searching for a distinctive set of entrepreneurial skills that matches the profile of the entrepreneurial task, Lazear introduced a theoretical model featuring skill variety for entrepreneurs. He argues that because entrepreneurs perform many different tasks, they should be multi-skilled in various areas. First, this dissertation provides the reader with an overview of previous relevant research results on skill variety with regard to entrepreneurship. The majority of the studies discussed focus on the effects of skill variety. Most studies come to the conclusion that skill variety mainly affects the decision to become self-employed. Skill variety also favors entrepreneurial intentions. Less clear are the results with regard to the influence of skill variety on the entrepreneurial success. Measured on the basis of income and survival of the company, a negative or U-shaped correlation is shown. Within the empirical part of this dissertation three research goals are tackled. First, this dissertation investigates whether a variety of early interests and activities in adolescence predicts subsequent variety in skills and knowledge. Second, the determinants of skill variety and variety of early interests and activities are investigated. Third, skill variety is tested as a mediator of the gender gap in entrepreneurial intentions. This dissertation employs structural equation modeling (SEM) using longitudinal data collected over ten years from Finnish secondary school students aged 16 to 26. As indicator for skill variety the number of functional areas in which the participant had prior educational or work experience is used. The results of the study suggest that a variety of early interests and activities lead to skill variety, which in turn leads to entrepreneurial intentions. Furthermore, the study shows that an early variety is predicted by openness and an entrepreneurial personality profile. Skill variety is also encouraged by an entrepreneurial personality profile. From a gender perspective, there is indeed a gap in entrepreneurial intentions. While a positive correlation has been found between the early variety of subjects and being female, there are negative correlations between the other two variables, education and work related Skill variety, and being female. The negative effect of work-related skill variety is the strongest. The results of this dissertation are relevant for research, politics, educational institutions and special entrepreneurship education programs. The results are also important for self-employed parents that plan the succession of the family business. Educational programs promoting entrepreneurship can be optimized on the basis of the results of this dissertation by making the transmission of a variety of skills a central goal. A focus on teenagers could also increase the success as well as a preselection based on the personality profile of the participants. Regarding the gender gap, state policies should aim to provide women with more incentives to acquire skill variety. For this purpose, education programs can be tailored specifically to women and self-employment can be presented as an attractive alternative to dependent employment.

This study aims to estimate the cotton yield at the field and regional level via the APSIM/OZCOT crop model, using an optimization-based recalibration approach based on the state variable of the cotton canopy - the leaf area index (LAI), derived from atmospherically corrected Landsat-8 OLI remote sensing images in 2014. First, a local sensitivity and global analysis approach was employed to test the sensitivity of cultivar, soil and agronomic parameters to the dynamics of the LAI. After sensitivity analyses, a series of sensitive parameters were obtained. Then, the APSIM/OZCOT crop model was calibrated by observations over a two-year span (2006-2007) at the Aksu station, combined with these sensitive cultivar parameters and the current understanding of cotton cultivar parameters. Third, the relationship between the observed in-situ LAI and synchronous perpendicular vegetation indices derived from six Landsat-8 OLI images covering the entire growth stage was modelled to generate LAI maps in time and space. Finally, the Particle Swarm Optimization (PSO) and general-purpose optimization approach (based on Nelder-Mead algorithm) were used to recalibrate four sensitive agronomic parameters (row spacing, sowing density per row, irrigation amount and total fertilization) according to the minimization of the root-mean-square deviation (RMSE) between the simulated LAI from the APSIM/OZCOT model and retrieved LAI from Landsat-8 OLI remote sensing images. After the recalibration, the best simulated results compared with observed cotton yield were obtained. The results showed that: (1) FRUDD, FLAI and DDISQ were the major cultivar parameters suitable for calibrating the cotton cultivar. (2) After the calibration, the simulated LAI performed well with an RMSE and mean absolute error (MAE) of 0.45 and 0.33, respectively, in 2006 and 0.46 and 0.41, respectively, in 2007. The coefficient of determination between the observed and simulated LAI was 0.83 and 0.97, respectively, in 2006 and 2007. The Pearson- correlation coefficient was 0.913 and 0.988 in 2006 and 2007, respectively, with a significant positive correlation between the simulated and observed LAI. The difference between the observed and simulated yield was 776.72 kg/ha and 259.98 kg/ha in 2006 and 2007, respectively. (3) Cotton cultivation in 2014 was obtained using three Landsat-8 OLI images - DOY136 (May), DOY 168 (June) and DOY 200 (July) - based on the phenological differences in cotton and other vegetation types. (4) The yield estimation after the assimilation closely approximated the field-observed values, and the coefficient of determination was as high as 0.82, after recalibration of the APSIM/OZCOT model for ten cotton fields. The difference between the observed and assimilated yields for the ten fields ranged from 18.2 to 939.7 kg/ha. The RMSE and MAE between the assimilated and observed yield was 417.5 and 303.1 kg/ha, respectively. These findings provide scientific evidence for the feasibility of coupled remote sensing and APSIM/OZCOT model at the field level. (5) Upscaling from field level to regional level, the assimilation algorithm and scheme are both especially important. Although the PSO method is very efficient, the computational efficiency is also the shortcoming of the assimilation strategy on a regional scale. Comparisons between the PSO and general-purpose optimization method (based on the Nelder-Mead algorithm) were implemented from the RSME, LAI curve and computational time. The general-purpose optimization method (based on the Nelder-Mead algorithm) was used for the regional assimilation between remote sensing and the APSIM/OZCOT model. Meanwhile, the basic unit for regional assimilation was also determined as cotton field rather than pixel. Moreover, the crop growth simulation was also divided into two phases (vegetative growth and reproductive growth) for regional assimilation. (6) The regional assimilation at the vegetative growth stage between the remote sensing derived and APSIM/OZCOT model-simulated LAI was implemented by adjusting two parameters: row spacing and sowing density per row. The results showed that the sowing density of cotton was higher in the southern part than in the northern part of the study area. The spatial pattern of cotton density was also consistent with the reclamation from 2001 to 2013. Cotton fields after early reclamation were mainly located in the southern part while the recent reclamation was located in the northern part. Poor soil quality, lack of irrigation facilities and woodland belts of cotton fields in the northern part caused the low density of cotton. Regarding the row spacing, the northern part was larger than the southern part due to the variation of two agronomic modes from military and private companies. (7) The irrigation and fertilization amount were both used as key parameters to be adjusted for regional assimilation during the reproductive growth period. The result showed that the irrigation per time ranged from 58.14 to 89.99 mm in the study area. The spatial distribution of the irrigation amount is higher in the northern part while lower in southern study area. The application of urea fertilization ranged from 500.35 to 1598.59 kg/ha in the study area. The spatial distribution of fertilization was lower in the northern part and higher in the southern part. More fertilization applied in the southern study area aims to increase the boll weight and number for pursuing higher yields of cotton. The frequency of the RSME during the second assimilation was mainly located in the range of 0.4-0.6 m2/m2. The estimated cotton yield ranged from 1489 to 8895 kg/ha. The spatial distribution of the estimated yield is also higher in the southern part than the northern study area.

Numerous RCTs demonstrate that cognitive behavioral therapy (CBT) for depression is effective. However, these findings are not necessarily representative of CBT under routine care conditions. Routine care studies are not usually subjected to comparable standardizations, e.g. often therapists may not follow treatment manuals and patients are less homogeneous with regard to their diagnoses and sociodemographic variables. Results on the transferability of findings from clinical trials to routine care are sparse and point in different directions. As RCT samples are selective due to a stringent application of inclusion/exclusion criteria, comparisons between routine care and clinical trials must be based on a consistent analytic strategy. The present work demonstrates the merits of propensity score matching (PSM), which offers solutions to reduce bias by balancing two samples based on a range of pretreatment differences. The objective of this dissertation is the investigation of the transferability of findings from RCTs to routine care settings.

Flexibility and spatial mobility of labour are central characteristics of modern societies which contribute not only to higher overall economic growth but also to a reduction of interregional employment disparities. For these reasons, there is the political will in many countries to expand labour market areas, resulting especially in an overall increase in commuting. The picture of the various, unintended long-term consequences of commuting on individuals is, however, relatively unclear. Therefore, in recent years, the journey to work has gained high attention especially in the study of health and well-being. Empirical analyses based on longitudinal as well as European data on how commuting may affect health and well-being are nevertheless rare. The principle aim of this thesis is, thus, to address this question with regard to Germany using data from the Socio-Economic Panel. Chapter 2 empirically investigates the causal impact of commuting on absence from work due to sickness-related reasons. Whereas an exogenous change in commuting distance does not affect the number of absence days of those individuals who commute short distances to work, it increases the number of absence days of those employees who commute middle (25 " 49 kilometres) or long distances (50 kilometres and more). Moreover, our results highlight that commuting may deteriorate an individual- health. However, this effect is not sufficient to explain the observed impact of commuting on absence from work. Chapter 3 explores the relationship between commuting distance and height-adjusted weight and sheds some light on the mechanisms through which commuting might affect individual body weight. We find no evidence that commuting leads to excess weight. Compensating health behaviour of commuters, especially healthy dietary habits, could explain the non-relationship of commuting and height-adjusted weight. In Chapter 4, a multivariate probit approach is used to estimate recursive systems of equations for commuting and health-related behaviours. Controlling for potential endogeneity of commuting, the results show that long distance commutes significantly decrease the propensity to engage in health-related activities. Furthermore, unobservable individual heterogeneity can influence both the decision to commute and healthy lifestyle choices. Chapter 5 investigates the relationship between commuting and several cognitive and affective components of subjective well-being. The results suggest that commuting is related to lower levels of satisfaction with family life and leisure time which can largely be ascribed to changes in daily time use patterns, influenced by the work commute.

In recent decades, the Arctic has been undergoing a wide range of fast environmental changes. The sea ice covering the Arctic Ocean not only reacts rapidly to these changes, but also influences and alters the physical properties of the atmospheric boundary layer and the underlying ocean on various scales. In that regard, polynyas, i.e. regions of open water and thin ice within thernclosed pack ice, play a key role as being regions of enhanced atmosphere-ice-ocean interactions and extensive new ice formation during winter. A precise long-term monitoring and increased efforts to employ long-term and high-resolution satellite data is therefore of high interest for the polar scientific community. The retrieval of thin-ice thickness (TIT) fields from thermal infrared satellite data and atmospheric reanalysis, utilizing a one-dimensional energy balance model, allows for the estimation of the heat loss to the atmosphere and hence, ice-production rates. However, an extended application of this approach is inherently connected with severe challenges that originate predominantly from the disturbing influence of clouds and necessary simplifications in the model set-up, which all need to be carefully considered and compensated for. The presented thesis addresses these challenges and demonstrates the applicability of thermal infrared TIT distributions for a long-term polynya monitoring, as well as an accurate estimation of ice production in Arctic polynyas at a relatively high spatial resolution. Being written in a cumulative style, the thesis is subdivided into three parts that show the consequent evolution and improvement of the TIT retrieval, based on two regional studies (Storfjorden and North Water (NOW) polynya) and a final large-scale, pan-Arctic study. The first study on the Storfjorden polynya, situated in the Svalbard archipelago, represents the first long-term investigation on spatial and temporal polynya characteristics that is solely based on daily TIT fields derived from MODIS thermal infrared satellite data and ECMWF ERA-Interim atmospheric reanalysis data. Typical quantities such as polynya area (POLA), the TIT distribution, frequencies of polynya events as well as the total ice production are derived and compared to previous remote sensing and modeling studies. The study includes a first basic approach that aims for a compensation of cloud-induced gaps in daily TIT composites. This coverage-correction (CC) is a mathematically simple upscaling procedure that depends solely on the daily percentage of available MODIS coverage and yields daily POLA with an error-margin of 5 to 6 %. The NOW polynya in northern Baffin Bay is the main focus region of the second study, which follows two main goals. First, a new statistics-based cloud interpolation scheme (Spatial Feature Reconstruction - SFR) as well as additional cloud-screening procedures are successfully adapted and implemented in the TIT retrieval for usage in Arctic polynya regions. For a 13-yr period, results on polynya characteristics are compared to the CC approach. Furthermore, an investigation on highly variable ice-bridge dynamics in Nares Strait is presented. Second, an analysis of decadal changes of the NOW polynya is carried out, as the additional use of a suite of passive microwave sensors leads to an extended record of 37 consecutive winter seasons, thereby enabling detailed inter-sensor comparisons. In the final study, the SFR-interpolated daily TIT composites are used to infer spatial and temporal characteristics of 17 circumpolar polynya regions in the Arctic for 2002/2003 to 2014/2015. All polynya regions combined cover an average thin-ice area of 226.6 -± 36.1 x 10-³ km-² during winter (November to March) and yield an average total wintertime accumulated ice production of about 1811 -± 293 km-³. Regional differences in derived ice production trends are noticeable. The Laptev Sea on the Siberian shelf is presented as a focus region, as frequently appearing polynyas along the fast-ice edge promote high rates of new ice production. New affirming results on a distinct relation to sea-ice area export rates and hence, the Transpolar Drift, are shown. This new high-resolution pan-Arctic data set can be further utilized and build upon in a variety of atmospheric and oceanographic applications, while still offering room for further improvements such as incorporating high-resolution atmospheric data sets and an optimized lead-detection.

Earth observation (EO) is a prerequisite for sustainable land use management, and the open-data Landsat mission is at the forefront of this development. However, increasing data volumes have led to a "digital-divide", and consequently, it is key to develop methods that account for the most data-intensive processing steps, then used for the generation and provision of analysis-ready, standardized, higher-level (Level 2 and Level 3) baseline products for enhanced uptake in environmental monitoring systems. Accordingly, the overarching research task of this dissertation was to develop such a framework with a special emphasis on the yet under-researched drylands of Southern Africa. A fully automatic and memory-resident radiometric preprocessing streamline (Level 2) was implemented. The method was applied to the complete Angolan, Zambian, Zimbabwean, Botswanan, and Namibian Landsat record, amounting 58,731 images with a total data volume of nearly 15 TB. Cloud/shadow detection capabilities were improved for drylands. An integrated correction of atmospheric, topographic and bidirectional effects was implemented, based on radiative theory with corrections for multiple scatterings, and adjacency effects, as well as including a multilayered toolset for estimating aerosol optical depth over persistent dark targets or by falling back on a spatio-temporal climatology. Topographic and bidirectional effects were reduced with a semi-empirical C-correction and a global set of correction parameters, respectively. Gridding and reprojection were already included to facilitate easy and efficient further processing. The selection of phenologically similar observations is a key monitoring requirement for multi-temporal analyses, and hence, the generation of Level 3 products that realize phenological normalization on the pixel-level was pursued. As a prerequisite, coarse resolution Land Surface Phenology (LSP) was derived in a first step, then spatially refined by fusing it with a small number of Level 2 images. For this purpose, a novel data fusion technique was developed, wherein a focal filter based approach employs multi-scale and source prediction proxies. Phenologically normalized composites (Level 3) were generated by coupling the target day (i.e. the main compositing criterion) to the input LSP. The approach was demonstrated by generating peak, end and minimum of season composites, and by comparing these with static composites (fixed target day). It was shown that the phenological normalization accounts for terrain- and land cover class-induced LSP differences, and the use of Level 2 inputs enables a wide range of monitoring options, among them the detection of within state processes like forest degradation. In summary, the developed preprocessing framework is capable of generating several analysis-ready baseline EO satellite products. These datasets can be used for regional case studies, but may also be directly integrated into more operational monitoring systems " e.g. in support of the Reducing Emissions from Deforestation and Forest Degradation (REDD) incentive. In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Trier University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.

Monetary Policy During Times of Crisis - Frictions and Non-Linearities in the Transmission Mechanism
(2017)

For a long time it was believed that monetary policy would be able to maintain price stability and foster economic growth during all phases of the business cycle. The era of the Great Moderation, often also called the Volcker-Greenspan period, beginning in the mid 1980s was characterized by a decline in volatility of output growth and inflation among the industrialized countries. The term itself is first used by Stock and Watson (2003). Economist have long studied what triggered the decline in volatility and pointed out several main factors. An important research strand points out structural changes in the economy, such as a decline of volatility in the goods producing sector through better inventory controls and developments in the financial sector and government spending (McConnell2000, Blanchard2001, Stock2003, Kim2004, Davis2008). While many believed that monetary policy was only 'lucky' in terms of their reaction towards inflation and exogenous shocks (Stock2003, Primiceri2005, Sims2006, Gambetti2008), others reveal a more complex picture of the story. Rule based monetary policy (Taylor1993) that incorporates inflation targeting (Svensson1999) has been identified as a major source of inflation stabilization by increasing transparency (Clarida2000, Davis2008, Benati2009, Coibion2011). Apart from that, the mechanics of monetary policy transmission have changed. Giannone et al. (2008) compare the pre-Great Moderation era with the Great Modertation and find that the economies reaction towards monetary shocks has decreased. This finding is supported by Boivin et al. (2011). Similar to this, Herrera and Pesavento (2009) show that monetary policy during the Volcker-Greenspan period was very effective in dampening the effects of exogenous oil price shocks on the economy, while this cannot be found for the period thereafter. Yet, the subprime crisis unexpectedly hit worldwide economies and ended the era of Great Moderation. Financial deregulation and innovation has given banks opportunities for excessive risk taking, weakened financial stability (Crotty2009, Calomiris2009) and led to the build-up of credit-driven asset price bubbles (SchularickTaylor2012). The Federal Reserve (FED), that was thought to be the omnipotent conductor of price stability and economic growth during the Great Moderation, failed at preventing a harsh crisis. Even more, it did intensify the bubble with low interest rates following the Dotcom crisis of the early 2000s and misjudged the impact of its interventions (Taylor2009, Obstfeld2009). New results give a more detailed explanation on the question of latitude for monetary policy raised by Bernanke and suggest the existence of non-linearities in the transmission of monetary policy. Weise (1999), Garcia and Schaller (2002), Lo and Piger (2005), Mishkin (2009), Neuenkirch (2013) and Jannsen et al. (2015) find that monetary policy is more potent during times of financial distress and recessions. Its effectiveness during 'normal times' is much weaker or even insignificant. This prompts the question if these non-linearities limit central banks ability to lean against bubbles and financial imbalances (White2009, Walsh2009, Boivin2010, Mishkin2011).

This dissertation looked at both design-based and model-based estimation for rare and clustered populations using the idea of the ACS design. The ACS design (Thompson, 2012, p. 319) starts with an initial sample that is selected by a probability sampling method. If any of the selected units meets a pre-specified condition, its neighboring units are added to the sample and observed. If any of the added units meets the pre-specified condition, its neighboring units are further added to the sample and observed. The procedure continues until there are no more units that meet the pre-specified condition. In this dissertation, the pre-specified condition is the detection of at least one animal in a selected unit. In the design-based estimation, three estimators were proposed under three specific design setting. The first design was stratified strip ACS design that is suitable for aerial or ship surveys. This was a case study in estimating population totals of African elephants. In this case, units/quadrant were observed only once during an aerial survey. The Des Raj estimator (Raj, 1956) was modified to obtain an unbiased estimate of the population total. The design was evaluated using simulated data with different levels of rarity and clusteredness. The design was also evaluated on real data of African elephants that was obtained from an aerial census conducted in parts of Kenya and Tanzania in October (dry season) 2013. In this study, the order in which the samples were observed was maintained. Re-ordering the samples by making use of the Murthy's estimator (Murthy, 1957) can produce more efficient estimates. Hence a possible extension of this study. The computation cost resulting from the n! permutations in the Murthy's estimator however, needs to be put into consideration. The second setting was when there exists an auxiliary variable that is negatively correlated with the study variable. The Murthy's estimator (Murthy, 1964) was modified. Situations when the modified estimator is preferable was given both in theory and simulations using simulated and two real data sets. The study variable for the real data sets was the distribution and counts of oryx and wildbeest. This was obtained from an aerial census that was conducted in parts of Kenya and Tanzania in October (dry season) 2013. Temperature was the auxiliary variable for two study variables. Temperature data was obtained from R package raster. The modified estimator provided more efficient estimates with lower bias compared to the original Murthy's estimator (Murthy, 1964). The modified estimator was also more efficient compared to the modified HH and the modified HT estimators of (Thompson, 2012, p. 319). In this study, one auxiliary variable is considered. A fruitful area for future research would be to incorporate multi-auxiliary information at the estimation phase of an ACS design. This could, in principle, be done by using for instance a multivariate extension of the product estimator (Singh, 1967) or by using the generalized regression estimator (Särndal et al., 1992). The third case under design-based estimation, studied the conjoint use of the stopping rule (Gattone and Di Battista, 2011) and the use of the without replacement of clusters (Dryver and Thompson, 2007). Each of these two methods was proposed to reduce the sampling cost though the use of the stopping rule results in biased estimates. Despite this bias, the new estimator resulted in higher efficiency gain in comparison to the without replacement of cluster design. It was also more efficient compared to the stratified design which is known to reduce final sample size when networks are truncated at stratum boundaries. The above evaluation was based on simulated and real data. The real data was the distribution and counts of hartebeest, elephants and oryx obtained in the same census as above. The bias attributed by the stopping rule has not been evaluated analytically. This may not be direct since the truncated network formed depends on the initial unit sampled (Gattone et al., 2016a). This and the order of the bias however, deserves further investigation as it may help in understanding the effect of the increase in the initial sample size together with the population characteristics on the efficiency of the proposed estimator. Chapter four modeled data that was obtained using the stratified strip ACS (as described in sub-section (3.1)). This was an extension of the model of Rapley and Welsh (2008) by modeling data that was obtained from a different design, the introduction of an auxiliary variable and the use of the without replacement of clusters mechanism. Ideally, model-based estimation does not depend on the design or rather how the sample was obtained. This is however, not the case if the design is informative; such as the ACS design. In this case, the procedure that was used to obtain the sample was incorporated in the model. Both model-based and design-based simulations were conducted using artificial and real data. The study and the auxiliary variable for the real data was the distribution and counts of elephants collected during an aerial census in parts of Kenya and Tanzania in October (dry season) and April (wet season) 2013 respectively. Areas of possible future research include predicting the population total of African elephants in all parks in Kenya. This can be achieved in an economical and reliable way by using the theory of SAE. Chapter five compared the different proposed strategies using the elephant data. Again the study variable was the elephant data from October (dry season) 2013 and the auxiliary variable was the elephant data from April (wet season) 2013. The results show that the choice of particular strategy to use depends on the characteristic of the population under study and the level and the direction of the correlation between the study and the auxiliary variable (if present). One general area of the ACS design that is still behind, is the implementation of the design in the field especially on animal populations. This is partly attributed by the challenges associated with the field implementation, some of which were discussed in section 2.3. Green et al. (2010) however, provides new insights in undertaking the ACS design during an aerial survey such as how the aircraft should turn while surveying neighboring units. A key point throughout the dissertation is the reduction of cost during a survey which can be seen by the reduction in the number of units in the final sample (through the use of stopping rule, use of stratification and truncating networks at stratum boundaries) and ensuring that units are observed only once (by using the without replacement of cluster sampling technique). The cost of surveying an edge unit(s) is assumed to be low in which case the efficiency of the ACS design relative to the non-adaptive design is achieved (Thompson and Collins, 2002). This is however not the case in aerial surveys as the aircraft flies at constant speed and height (Norton-Griffiths, 1978). Hence the cost of surveying an edge unit is the same as the cost of surveying a unit that meets the condition of interest. The without replacement of cluster technique plays a greater role of reducing the cost of sampling in such surveys. Other key points that motivated the sections in the dissertation include gains in efficiency (in all sections) and practicability of the designs in the specific setting. Even though the dissertation focused on animal populations, the methods can as well be implemented in any population that is rare and clustered such as in the study of forestry, plants, pollution, minerals and so on.

The development of our society contributed to increased occurrence of emerging substances (pesticides, pharmaceuticals, personal care products, etc.) in wastewater. Because of their potential hazard on ecosystems and humans, Wastewater Treatment Plants (WWTPs) need to adapt to better remove these compounds. Technology or policy development should however comply with sustainable development, e.g. based on Life Cycle Assessment (LCA) metrics. Nevertheless, the reliability or consistency of LCA results can sometimes be debatable. The main objective of this work was to explore how LCA can better support the implementation of innovative wastewater treatment options, in particular including removal benefits. The method was applied to support solutions for pharmaceuticals elimination from wastewater, regarding: (i) UV technology design, (ii) choice of advanced technology and (iii) centralized or decentralized treatment policy. The assessment approach followed by previous authors based on net impacts calculation seemed very promising to consider both environmental effects induced by treatment plant operation and environmental benefits obtained from pollutants removal. It was therefore applied to compare UV configuration types. LCA outcomes were consistent with degradation kinetics analysis. For the comparison of advanced technologies and policy scenarios, the common practice (net impacts based on EDIP method) was compared to other assessments, to better consider elimination benefits. First, USEtox consensus was applied for the avoided (eco)toxicity impacts, in combination with the recent method ReCiPe for generated impacts. Then, an eco-efficiency indicator (EFI) was developed to weigh the treatment efforts (generated impacts based on EDIP and ReCiPe methods) by the average removal efficiency (overcoming (eco)toxicity uncertainty issues). In total, the four types of comparative assessment showed the same trends: (i) ozonation and activated carbon perform better than UV irradiation, and (ii) no clear advantage distinguished between policy scenarios. It cannot be however concluded that advanced treatment of pharmaceuticals is not necessary because other criteria should be considered (risk assessment, bacterial resistance, etc.) and large uncertainties were embedded in calculations. Indeed, a significant part of this work was dedicated to the discussion of uncertainty and limitations of the LCA outcomes. At the inventory level, it was difficult to model technology operation at development stage. For impact assessment, the newly developed characterization factors for pharmaceuticals (eco)toxicity showed large uncertainties, mainly due to the lack of data and quality for toxicity tests. The use of information made available under REACH framework to develop CFs for detergent ingredients tried to cope with this issue but the benefits were limited due to the mismatch of information between REACH and USEtox method. The highlighted uncertainties were treated with sensitivity analyses to understand their effects on LCA results. This research work finally presents perspectives on the use of transparently generated data (technology inventory and (eco)toxicity factors) and further development of EFI indicator. Also, an accent is made on increasing the reliability of LCA outcomes, in particular through the implementation of advanced techniques for uncertainty management. To conclude, innovative technology/product development (e.g. based on circular economy approach) needs the involvement of all types of actors and the support from sustainability metrics.

Educational assessment tends to rely on more or less standardized tests, teacher judgments, and observations. Although teachers spend approximately half of their professional conduct in assessment-related activities, most of them enter their professional life unprepared, as classroom assessment is often not part of their educational training. Since teacher judgments matter for the educational development of students, the judgments should be up to a high standard. The present dissertation comprises three studies focusing on accuracy of teacher judgments (Study 1), consequences of (mis-)judgment regarding teacher nomination for gifted programming (Study 2) and teacher recommendations for secondary school tracks (Study 3), and individual student characteristics that impact and potentially bias teacher judgment (Studies 1 through 3). All studies were designed to contribute to a further understanding of classroom assessment skills of teachers. Overall, the results implied that, teacher judgment of cognitive ability was an important constant for teacher nominations and recommendations but lacked accuracy. Furthermore, teacher judgments of various traits and school achievement were substantially related to social background variables, especially the parents" educational background. However, multivariate analysis showed social background variables to impact nomination and recommendation only marginally if at all. All results indicated differentiated but potentially biased teacher judgments to impact their far-reaching referral decisions directly, while the influence of social background on the referral decisions itself seems mediated. Implications regarding further research practices and educational assessment strategies are discussed. The implications on the needs of teachers to be educated on judgment and educational assessment are of particular interest and importance.

The main achievement of this thesis is an analysis of the accuracy of computations with Loader's algorithm for the binomial density. This analysis in later progress of work could be used for a theorem about the numerical accuracy of algorithms that compute rectangle probabilities for scan statistics of a multinomially distributed random variable. An example that shall illustrate the practical use of probabilities for scan statistics is the following, which arises in epidemiology: Let n patients arrive at a clinic in d = 365 days, each of the patients with probability 1/d at each of these d days and all patients independently from each other. The knowledge of the probability, that there exist 3 adjacent days, in which together more than k patients arrive, helps deciding, after observing data, if there is a cluster which we would not suspect to have occurred randomly but for which we suspect there must be a reason. Formally, this epidemiological example can be described by a multinomial model. As multinomially distributed random variables are examples of Markov increments, which is a fact already used implicitly by Corrado (2011) to compute the distribution function of the multinomial maximum, we can use a generalized version of Corrado's Algorithm to compute the probability described in our example. To compute its result, the algorithm for rectangle probabilities for Markov increments always uses transition probabilities of the corresponding Markov Chain. In the multinomial case, the transition probabilities of the corresponding Markov Chain are binomial probabilities. Therefore, we start an analysis of accuracy of Loader's algorithm for the binomial density, which for example the statistical software R uses. With the help of accuracy bounds for the binomial density we would be able to derive accuracy bounds for the computation of rectangle probabilities for scan statistics of multinomially distributed random variables. To figure out how sharp derived accuracy bounds are, in examples these can be compared to rigorous upper bounds and rigorous lower bounds which we obtain by interval-arithmetical computations.

Phase-amplitude cross-frequency coupling is a mechanism thought to facilitate communication between neuronal ensembles. The mechanism could underlie the implementation of complex cognitive processes, like executive functions, in the brain. This thesis contributes to answering the question, whether phase-amplitude cross-frequency coupling - assessed via electroencephalography (EEG) - is a mechanism by which executive functioning is implemented in the brain and whether an assumed performance effect of stress on executive functioning is reflected in phase-amplitude coupling strength. A huge body of studies shows that stress can influence executive functioning, in essence having detrimental effects. In two independent studies, each being comprised of two core executive function tasks (flexibility and behavioural inhibition as well as cognitive inhibition and working memory), beta-gamma phase-amplitude coupling was robustly detected in the left and right prefrontal hemispheres. No systematic pattern of coupling strength modulation by either task demands or acute stress was detected. Beta-gamma coupling might also be present in more basic attention processes. This is the first investigation of the relationship between stress, executive functions and phase-amplitude coupling. Therefore, many aspects have not been explored yet. For example, studying phase precision instead of coupling strength as an indicator for phase-amplitude coupling modulations. Furthermore, data was analysed in source space (independent component analysis); comparability to sensor space has still to be determined. These as well as other aspects should be investigated, due to the promising finding of very robust and strong beta-gamma coupling for all executive functions. Additionally, this thesis tested the performance of two widely used phase-amplitude coupling measures (mean vector length and modulation index). Both measures are specific and sensitive to coupling strength and coupling width. The simulation study also drew attention to several confounding factors, which influence phase-amplitude coupling measures (e. g. data length, multimodality).

Besides well-known positive aspects of conservation tillage combined with mulching, a drawback may be the survival of phytopathogenic fungi like Fusarium species on plant residues. This may endanger the health of the following crop by increasing the infection risk for specific plant diseases. In infected plant organs, these pathogens are able to produce mycotoxins like deoxynivalenol (DON). Mycotoxins like DON persist during storage, are heat resistant and of major concern for human and animal health after consumption of contaminated food and feed, respectively. Among fungivorous soil organisms, there are representatives of the soil fauna which are obviously antagonistic to a Fusarium infection and the contamination with mycotoxins. Earthworms (Lumbricus terrestris), collembolans (Folsomia candida) and nematodes (Aphelenchoides saprophilus) provide a wide range of ecosystem services including the stimulation of decomposition processes which may result in the regulation of plant pathogens and the degradation of environmental contaminants. Several investigations under laboratory conditions and in the field were conducted to test the following hypotheses: (1) Fusarium-infected and DON-contaminated wheat straw provides a more attractive food substrate than non-infected control straw (2) the introduced soil fauna reduce the biomass of F. culmorum and the content of DON in infected wheat straw under laboratory and field conditions (3) the species interaction of the introduced soil fauna enhances the degradation of Fusarium biomass and DON concentration in wheat straw; (4) the degradation efficiency of soil fauna is affected by soil texture. The results of the present thesis pointed out that the degradation performance of the introduced soil fauna must be considered as an important contribution to the biological control of plant diseases and environmental pollutants. As in particular L. terrestris revealed to be the driver of the degradation process, earthworms contribute to a sustainable control of fungal pathogens like Fusarium and its mycotoxins in wheat straw, thus reducing the risk of plant diseases and environmental pollution as ecosystem services.

Shape optimization is of interest in many fields of application. In particular, shape optimization problems arise frequently in technological processes which are modelled by partial differential equations (PDEs). In a lot of practical circumstances, the shape under investigation is parametrized by a finite number of parameters, which, on the one hand, allows the application of standard optimization approaches, but, on the other hand, unnecessarily limits the space of reachable shapes. Shape calculus presents a way to circumvent this dilemma. However, so far shape optimization based on shape calculus is mainly performed using gradient descent methods. One reason for this is the lack of symmetry of second order shape derivatives or shape Hessians. A major difference between shape optimization and the standard PDE constrained optimization framework is the lack of a linear space structure on shape spaces. If one cannot use a linear space structure, then the next best structure is a Riemannian manifold structure, in which one works with Riemannian shape Hessians. They possess the often sought property of symmetry, characterize well-posedness of optimization problems and define sufficient optimality conditions. In general, shape Hessians are used to accelerate gradient-based shape optimization methods. This thesis deals with shape optimization problems constrained by PDEs and embeds these problems in the framework of optimization on Riemannian manifolds to provide efficient techniques for PDE constrained shape optimization problems on shape spaces. A Lagrange-Newton and a quasi-Newton technique in shape spaces for PDE constrained shape optimization problems are formulated. These techniques are based on the Hadamard-form of shape derivatives, i.e., on the form of integrals over the surface of the shape under investigation. It is often a very tedious, not to say painful, process to derive such surface expressions. Along the way, volume formulations in the form of integrals over the entire domain appear as an intermediate step. This thesis couples volume integral formulations of shape derivatives with optimization strategies on shape spaces in order to establish efficient shape algorithms reducing analytical effort and programming work. In this context, a novel shape space is proposed.

Exposure to fine and ultra-fine environmental particles is still a problem of concern in many industrialized parts of the world and the intensified use of nanotechnology may further increase exposure to small particles. Since many years air pollution is recognized as a critical problem in western countries, which led to rigorous regulation of air quality and the introduction of strict guidelines. However, the upper thresholds for particulates in ambient air recommended by the world health organization are often exceeded several times in newly industrialized countries. Such high levels of air pollution have the potential to induce adverse effects on human health. The response triggered by air pollutants is not limited to local effects of the respiratory system but is often systemic, resulting in endothelial dysfunction or atherosclerotic malady. The link between air pollution and cardiovascular disease is now accepted by the scientific community but the underlying mechanisms responsible for the pro-atherogenic potential still need to be unraveled in detail. Based on the results from in- vivo and in vitro studies the production of reactive oxygen species due to exposure to particles is the most important mechanism to explain the observed adverse effects. However, the doses that were applied in many in vivo and in vitro studies are far beyond the range of what humans are exposed to and there is the need for more realistic exposure studies. Complex in vitro coculture systems may be valuable tools to study particle-induced processes and to extrapolate effects of particles on the lung. One of the objectives of this PhD thesis was the establishment and further improvement of a complex coculture system initially described by Alfaro-Moreno et al. [1]. The system is composed of an alveolar type-II cell line (A549), differentiated macrophage-like cells (THP-1), mast cells (HMC-1) and endothelial cells (EA.hy 926), seeded in a 3D-orientation on a microporous membrane to mimic the cell response of the alveolar surface in vitro in conjunction with native aerosol exposure (VitrocellTM chamber). The tetraculture system was carefully characterized to ensure its performance and repeatability of results. The spatial distribution of the cells in the tetraculture was analyzed by confocal laser scanning microscopy (CLSM), showing a confluent layer of endothelial and epithelial cells on both sides of the Transwellâ„¢. Macrophage-like cells and mast cells can be found on top of the epithelial cells. The latter cells formed colonies under submerged conditions, which disappeared at the air-liquid-interface (ALI). The VitrocellTM aerosol exposure system was not significantly influencing the viability. Using this system, cells were exposed to an aerosol of 50 nm SiO2-Rhodamine nanoparticles (NPs) in PBS. The distribution of the NPs in the tetraculture after exposure was evaluated by CLSM. Fluorescence from internalized particles was detected in CD11b-positive THP-1 cells only. Furthermore, all cell lines were found to be able to respond to xenobiotic model compounds, such as benzo[a]pyrene (B[a]P) or 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) with the upregulation of CYP1 mRNA. With this tetraculture system the response of the endothelial part of the alveolar barrier was studied in- vitro in a still realistic exposure scenario representing the conditions for a polluted situation without direct exposure of endothelial cells. After exposure to diesel exhaust particulate matter (DEPM) the expression of different anti-oxidant target genes and inflammatory genes such as NAD(P)H dehydrogenase quinone 1 (NQO1), superoxide dismutase 1 (SOD1) and heme oxygenase 1 (HMOX1), as well as the nuclear translocation nuclear factor erythroid-derived 2 (Nrf2) was evaluated. In addition, the potential of DEPM to induce the upregulation of CYP1A1 mRNA in the endothelium was analyzed. DEPM exposure led not to an upregulation of the anti-oxidant or inflammatory target genes, but to clear nuclear translocation of Nrf2. The endothelial cells responded to the DEPM treatment also with the upregulation of CYP1A1 mRNA and nuclear translocation of the aryl hydrocarbon receptor (AhR). Overall, DEPM triggered a response in the endothelial cells after indirect exposure of the tetraculture system to low doses of DEPM, underlining the sensitivity of ALI exposure systems. The use of the tetraculture together with the native aerosol exposure equipment may finally lead to a more realistic judgment regarding the hazard of new compounds and/or new nano-scaled materials in the future. For the first time, it was possible to study the response of the endothelial cells of the alveolar barrier in vitro in a realistic exposure scenario avoiding direct exposure of endothelial cells to high amounts of particulates.

The present work considers the normal approximation of the binomial distribution and yields estimations of the supremum distance of the distribution functions of the binomial- and the corresponding standardized normal distribution. The type of the estimations correspond to the classical Berry-Esseen theorem, in the special case that all random variables are identically Bernoulli distributed. In this case we state the optimal constant for the Berry-Esseen theorem. In the proof of these estimations several inequalities regarding the density as well as the distribution function of the binomial distribution are presented. Furthermore in the estimations mentioned above the distribution function is replaced by the probability of arbitrary, not only unlimited intervals and in this new situation we also present an upper bound.

The equity premium (Mehra and Prescott, 1985) is still a puzzle in the sense that there are still no convincing explanations for the size of the equity premium. In this dissertation, we study this long-standing puzzle and several possible behavioral explanations. First, we apply the IRR methodology proposed by Fama and French (1999) to achieve large firm level data on the equity premia for N = 28,256 companies in 54 countries around the world. Second, by using preferences data from the INTRA study (Rieger et. al., 2014), we could test the relevant risk factors together with time cognition to explain the equity premium. We document the failure of the Myopic Loss Aversion hypothesis by Benartzi and Thaler (1995) but provides rigorous empirical evidence to support the behavioral theory of ambiguity aversion to account for the equity premium. The observations shed some light on the new approach of integrating risk and ambiguity (together with time preferences) into a more general model of uncertainty, in which both risk premium and ambiguity premium play roles in asset pricing models.

Cognitive performance is contingent upon multiple factors. Beyond the impact of en-vironmental circumstances, the bodily state may hinder or promote cognitive processing. Af-ferent transmission from the viscera, for instance, is crucial not only for the genesis of affect and emotion, but further exerts significant influences on memory and attention. In particular, afferent cardiovascular feedback from baroreceptors demonstrated subcortical and cortical inhibition. Consequences for human cognition and behavior are the impairment of simple perception and sensorimotor functioning. Four studies are presented that investigate the mod-ulatory impact of baro-afferent feedback on selective attention. The first study demonstrates that the modulation of sensory processing by baroreceptor activity applies to the processing of complex stimulus configurations. By the use of a visual masking task in which a target had to be selected against a visual mask, perceptual interference was reduced when target and mask were presented during the ventricular systole compared to the diastole. In study two, selection efficiency was systematically manipulated in a visual selection task in which a target letter was flanked by distracting stimuli. By comparing participants" performance under homogene-ous and heterogeneous stimulus conditions, selection efficiency was assessed as a function of the cardiac cycle phase in which the targets and distractors were presented. The susceptibility of selection performance to the stimulus condition at hand was less pronounced during the ventricular systole compared to the diastole. Study one and two therefore indicate that inter-ference from irrelevant sensory input, resulting from temporally overlapping processing traces or from the simultaneous presentation of distractor stimuli, is reduced during phases of in-creased baro-afferent feedback. Study three experimentally manipulated baroreceptor activity by systematically varying the participant- body position while a sequential distractor priming task was completed. In this study, negative priming and distractor-response binding effects were obtained as indices of controlled and automatic distractor processing, respectively. It was found that only controlled distractor processing was affected by tonic increases in baro-receptor activity. In line with study one and two these results indicate that controlled selection processes are more efficient during enhanced baro-afferent feedback, observable in dimin-ished aftereffects of controlled distractor processing. Due to previous findings that indicated baro-afferent transmission to affect central, rather than response-related processing stages, study four measured lateralized-readiness potentials (LRPs) and reaction times (RTs), while participants, again, had to selectively respond to target stimuli that were surrounded by dis-tractors. The impact of distractor inhibition on stimulus-related, but not on response-related LRPs suggests that in a sequential distractor priming task, the sensory representations of dis-tractors, rather than motor responses are targeted by inhibition. Together with the results from studies one through three and the finding of baroreceptor-mediated behavioral inhibition tar-geting central processing stages, study four corroborates the presumption of baro-afferent signal transmission to modulate controlled processes involved in selective attention. In sum, the work presented shows that visual selective attention benefits from in-creased baro-afferent feedback as its effects are not confined to simple perception, but may facilitate the active suppression of neural activity related to sensory input from distractors. Hence, due to noise reduction, baroreceptor-mediated inhibition may promote effective selec-tion in vision.

The efficacy and effectiveness of psychotherapeutic interventions have been proven time and again. We therefore know that, in general, evidence-based treatments work for the average patient. However, it has also repeatedly been shown that some patients do not profit from or even deteriorate during treatment. Patient-focused psychotherapy research takes these differences between patients into account by focusing on the individual patient. The aim of this research approach is to analyze individual treatment courses in order to evaluate when and under which circumstances a generally effective treatment works for an individual patient. The goal is to identify evidence based clinical decision rules for the adaptation of treatment to prevent treatment failure. Patient-focused research has illustrated how different intake indicators and early change patterns predict the individual course of treatment, but they leave a lot of variance unexplained. The thesis at hand analyzed whether Ecological Momentary Assessment (EMA) strategies could be integrated into patient-focused psychotherapy research in order to improve treatment response prediction models. EMA is an electronically supported diary approach, in which multiple real-time assessments are conducted in participants" everyday lives. We applied EMA over a two-week period before treatment onset in a mixed sample of patients seeking outpatient treatment. The four daily measurements in the patients" everyday environment focused on assessing momentary affect and levels of rumination, perceived self-efficacy, social support and positive or negative life events since the previous assessment. The aim of this thesis project was threefold: First, to test the feasibility of EMA in a routine care outpatient setting. Second, to analyze the interrelation of different psychological processes within patients" everyday lives. Third and last, to test whether individual indicators of psychological processes during everyday life, which were assessed before treatment onset, could be used to improve prediction models of early treatment response. Results from Study I indicate good feasibility of EMA application during the waiting period for outpatient treatment. High average compliance rates over the entire assessment period and low average burdens perceived by the patients support good applicability. Technical challenges and the results of in-depth missing analyses are reported to guide future EMA applications in outpatient settings. Results from Study II shed further light on the rumination-affect link. We replicated results from earlier studies, which identified a negative association between state rumination and affect on a within-person level and additionally showed a) that this finding holds for the majority but not every individual in a diverse patient sample with mixed Axis-I disorders, b) that rumination is linked to negative but also to positive affect and c) that dispositional rumination significantly affects the state rumination-affect association. The results provide exploratory evidence that rumination might be considered a transdiagnostic mechanism of psychological functioning and well-being. Results from Study III finally suggest that the integration of indicators derived from EMA applications before treatment onset can improve prediction models of early treatment response. Positive-negative affect ratios as well as fluctuations in negative affect measured during patients" daily lives allow the prediction of early treatment response. Our results indicate that the combination of commonly applied intake predictors and EMA indicators of individual patients" daily experiences can improve treatment response predictions models. We therefore conclude that EMA can successfully be integrated into patient-focused research approaches in routine care settings to ameliorate or optimize individual care.

Matching problems with additional resource constraints are generalizations of the classical matching problem. The focus of this work is on matching problems with two types of additional resource constraints: The couple constrained matching problem and the level constrained matching problem. The first one is a matching problem which has imposed a set of additional equality constraints. Each constraint demands that for a given pair of edges either both edges are in the matching or none of them is in the matching. The second one is a matching problem which has imposed a single equality constraint. This constraint demands that an exact number of edges in the matching are so-called on-level edges. In a bipartite graph with fixed indices of the nodes, these are the edges with end-nodes that have the same index. As a central result concerning the couple constrained matching problem we prove that this problem is NP-hard, even on bipartite cycle graphs. Concerning the complexity of the level constrained perfect matching problem we show that it is polynomially equivalent to three other combinatorial optimization problems from the literature. For different combinations of fixed and variable parameters of one of these problems, the restricted perfect matching problem, we investigate their effect on the complexity of the problem. Further, the complexity of the assignment problem with an additional equality constraint is investigated. In a central part of this work we bring couple constraints into connection with a level constraint. We introduce the couple and level constrained matching problem with on-level couples, which is a matching problem with a special case of couple constraints together with a level constraint imposed on it. We prove that the decision version of this problem is NP-complete. This shows that the level constraint can be sufficient for making a polynomially solvable problem NP-hard when being imposed on that problem. This work also deals with the polyhedral structure of resource constrained matching problems. For the polytope corresponding to the relaxation of the level constrained perfect matching problem we develop a characterization of its non-integral vertices. We prove that for any given non-integral vertex of the polytope a corresponding inequality which separates this vertex from the convex hull of integral points can be found in polynomial time. Regarding the calculation of solutions of resource constrained matching problems, two new algorithms are presented. We develop a polynomial approximation algorithm for the level constrained matching problem on level graphs, which returns solutions whose size is at most one less than the size of an optimal solution. We then describe the Objective Branching Algorithm, a new algorithm for exactly solving the perfect matching problem with an additional equality constraint. The algorithm makes use of the fact that the weighted perfect matching problem without an additional side constraint is polynomially solvable. In the Appendix, experimental results of an implementation of the Objective Branching Algorithm are listed.

Globalization and the emergence of global value chains have not only changed the way we live, but also the way economists study international economics. These changes are visible in various areas and dimension. This dissertation deals " mostly empirically " with some of these issues related to global value chains. It starts by critically examining the political economy forces determining the occurrence and the extent of trade liberalization conditions in World Bank lending agreements. The focal point is whether these are affected by the World Bank- most influential member countries. Afterwards, the thesis moves on to describe trade of the European Union member countries at each stage of the value chain. The description is based on a new classification of goods into parts, components and final products as well as a newly developed measure describing the average level of development of a countries trading partners. This descriptive exercise is followed by critically examining discrepancies between gross trade and trade in value added with respect to comparative advantage. A gravity model is employed to contrast results when studying the institutional determinants of comparative advantage. Finally, the thesis deals with determinants of regional location choices for foreign direct investment. The analysis is based on a theoretical new economic geography model and employs a newly developed index that accounts for the presence of potentially all suppliers and buyers at all stages of the value chain.

Floods are hydrological extremes that have enormous environmental, social and economic consequences.The objective of this thesis was a contribution to the implementation of a processing chain that integrates remote sensing information into hydraulic models. Specifically, the aim was to improve water elevation and discharge simulations by assimilating microwave remote sensing-derived flood information into hydraulic models. The first component of the proposed processing chain is represented by a fully automated flood mapping algorithm that enables the automated, objective, and reliable flood extent extraction from Synthetic Aperture Radar images, providing accurate results in both rural and urban regions. The method operates with minimum data requirements and is efficient in terms of computational time. The map obtained with the developed algorithm is still subject to uncertainties, both introduced by the flood mapping algorithm and inherent in the image itself. In this work, particular attention was given to image uncertainty deriving from speckle. By bootstrapping the original satellite image pixels, several synthetic images were generated and provided as input to the developed flood mapping algorithm. From the analysis performed on the mapping products, speckle uncertainty can be considered as a negligible component of the total uncertainty. In the final step of the proposed processing chain real event water elevations, obtained from satellite observations, were assimilated in a hydraulic model with an adapted version of the Particle Filter, modified to work with non-Gaussian distribution of observations. To deal with model structure error and possibly biased observations, a global and a local weight variant of the Particle Filter were tested. The variant to be preferred depends on the level of confidence that is attributed to the observations or to the model. This study also highlighted the complementarity of remote sensing derived and in-situ data sets. An accurate binary flood map represents an invaluable product for different end users. However, deriving from this binary map additional hydraulic information, such as water elevations, is a way of enhancing the value of the product itself. The derived data can be assimilated into hydraulic models that will fill the gaps where, for technical reasons, Earth Observation data cannot provide information, also enabling a more accurate and reliable prediction of flooded areas.

In the first part of this work we generalize a method of building optimal confidence bounds provided in Buehler (1957) by specializing an exhaustive class of confidence regions inspired by Sterne (1954). The resulting confidence regions, also called Buehlerizations, are valid in general models and depend on a designated statistic'' that can be chosen according to some desired monotonicity behaviour of the confidence region. For a fixed designated statistic, the thus obtained family of confidence regions indexed by their confidence level is nested. Buehlerizations have furthermore the optimality property of being the smallest (w.r.t. set inclusion) confidence regions that are increasing in their designated statistic. The theory is eventually applied to normal, binomial, and exponential samples. The second part deals with the statistical comparison of pairs of diagnostic tests and establishes relations 1. between the sets of lower confidence bounds, 2. between the sets of pairs of comparable lower confidence bounds, and 3. between the sets of admissible lower confidence bounds in various models for diverse parameters of interest.

In recent years, the study of dynamical systems has developed into a central research area in mathematics. Actually, in combination with keywords such as "chaos" or "butterfly effect", parts of this theory have been incorporated in other scientific fields, e.g. in physics, biology, meteorology and economics. In general, a discrete dynamical system is given by a set X and a self-map f of X. The set X can be interpreted as the state space of the system and the function f describes the temporal development of the system. If the system is in state x âˆˆ X at time zero, its state at time n âˆˆ N is denoted by f^n(x), where f^n stands for the n-th iterate of the map f. Typically, one is interested in the long-time behaviour of the dynamical system, i.e. in the behaviour of the sequence (f^n(x)) for an arbitrary initial state x âˆˆ X as the time n increases. On the one hand, it is possible that there exist certain states x âˆˆ X such that the system behaves stably, which means that f^n(x) approaches a state of equilibrium for nâ†’âˆž. On the other hand, it might be the case that the system runs unstably for some initial states x âˆˆ X so that the sequence (f^n(x)) somehow shows chaotic behaviour. In case of a non-linear entire function f, the complex plane always decomposes into two disjoint parts, the Fatou set F_f of f and the Julia set J_f of f. These two sets are defined in such a way that the sequence of iterates (f^n) behaves quite "wildly" or "chaotically" on J_f whereas, on the other hand, the behaviour of (f^n) on F_f is rather "nice" and well-understood. However, this nice behaviour of the iterates on the Fatou set can "change dramatically" if we compose the iterates from the left with just one other suitable holomorphic function, i.e. if we consider sequences of the form (gâˆ˜f^n) on D, where D is an open subset of F_f with f(D)âŠ‚ D and g is holomorphic on D. The general aim of this work is to study the long-time behaviour of such modified sequences. In particular, we will prove the existence of holomorphic functions g on D having the property that the behaviour of the sequence of compositions (gâˆ˜f^n) on the set D becomes quite similarly chaotic as the behaviour of the sequence (f^n) on the Julia set of f. With this approach, we immerse ourselves into the theory of universal families and hypercyclic operators, which itself has developed into an own branch of research. In general, for topological spaces X, Y and a family {T_i: i âˆˆ I} of continuous functions T_i:Xâ†’Y, an element x âˆˆ X is called universal for the family {T_i: i âˆˆ I} if the set {T_i(x): i âˆˆ I} is dense in Y. In case that X is a topological vector space and T is a continuous linear operator on X, a vector x âˆˆ X is called hypercyclic for T if it is universal for the family {T^n: n âˆˆ N}. Thus, roughly speaking, universality and hypercyclicity can be described via the following two aspects: There exists a single object which allows us, via simple analytical operations, to approximate every element of a whole class of objects. In the above situation, i.e. for a non-linear entire function f and an open subset D of F_f with f(D)âŠ‚ D, we endow the space H(D) of holomorphic functions on D with the topology of locally uniform convergence and we consider the map C_f:H(D)â†’H(D), C_f(g):=gâˆ˜f|_D, which is called the composition operator with symbol f. The transform C_f is a continuous linear operator on the Fréchet space H(D). In order to show that the above-mentioned "nice" behaviour of the sequence of iterates (f^n) on the set D âŠ‚ F_f can "change dramatically" if we compose the iterates from the left with another suitable holomorphic function, our aim consists in finding functions g âˆˆ H(D) which are hypercyclic for C_f. Indeed, for each hypercyclic function g for C_f, the set of compositions {gâˆ˜f^n|_D: n âˆˆ N} is dense in H(D) so that the sequence of compositions (gâˆ˜f^n|_D) is kind of "maximally divergent" " meaning that each function in H(D) can be approximated locally uniformly on D via subsequences of (gâˆ˜f^n|_D). This kind of behaviour stands in sharp contrast to the fact that the sequence of iterates (f^n) itself converges, behaves like a rotation or shows some "wandering behaviour" on each component of F_f. To put it in a nutshell, this work combines the theory of non-linear complex dynamics in the complex plane with the theory of dynamics of continuous linear operators on spaces of holomorphic functions. As far as the author knows, this approach has not been investigated before.

Evapotranspiration (ET) is one of the most important variables in hydrological studies. In the ET process, energy exchange and water transfer are involved. ET consists of transpiration and evaporation. The amount of plants transpiration dominates in ET. Especially in the forest regions, the ratio of transpiration to ET is in general 80-90 %. Meteorological variables, vegetation properties, precipitation and soil moisture are critical influence factors for ET generation. The study area is located in the forest area of Nahe catchment (Rhineland-Palatinate, Germany). The Nahe catchment is highly wooded. About 54.6 % of this area is covered by forest, with deciduous forest and coniferous forest are two primary types. A hydrological model, WaSiM-ETH, was employed for a long-term simulation from 1971-2003 in the Nahe catchment. In WaSiM-ETH, the potential evapotranspiration (ETP) was firstly calculated by the Penman-Monteith equation, and subsequently reduced according to the soil water content to obtain the actual evapotranspiration (ETA). The Penman-Monteith equation has been widely used and recommended for ETP estimation. The difficulties in applying this equation are the high demand of ground-measured meteorological data and the determination of surface resistance. A method combined remote sensing images with ground-measured meteorological data was also used to retrieve the ETA. This method is based on the surface properties such as surface albedo, fractional vegetation cover (FVC) and land surface temperature (LST) to obtain the latent heat flux (LE, corresponding to ETA) through the surface energy balance equation. LST is a critical variable for surface energy components estimation. It was retrieved from the TM/ETM+ thermal infrared (TIR) band. Due to the high-quality and cloudy-free requirements for TM/ETM+ data selection as well as the overlapping cycle of TM/ETM+ sensor is 16 days, images on only five dates are available during 1971-2003 (model ran) " May 15, 2000, July 05, 2001, July 19, August 04 and September 21 in 2003. It is found that the climate conditions of 2000, 2001 and 2003 are wet, medium wet and dry, respectively. Therefore, the remote sensing-retrieved observations are noncontinuous in a limited number over time but contain multiple climate conditions. Aerodynamic resistance and surface resistance are two most important parameters in the Penman-Monteith equation. However, for forest area, the aerodynamic resistance is calculated by a function of wind speed in the model. Since transpiration and evaporation are separately calculated by the Penman-Monteith equation in the model, the surface resistance was divided into canopy surface resistance rsc and soil surface resistance rse. rsc is related to the plants transpiration and rse is related to the bare soil evaporation. The interception evaporation was not taken into account due to its negligible contribution to ET rate under a dry-canopy (no rainfall) condition. Based on the remote sensing-retrieved observations, rsc and rse were calibrated in the WaSiM-ETH model for both forest types: for deciduous forest, rsc = 150 smâˆ’1, rse = 250 smâˆ’1; for coniferous forest, rsc = 300 smâˆ’1, rse = 650 smâˆ’1. We also carried out sensitivity analysis on rsc and rse. The appropriate value ranges of rsc and rse were determined as (annual maximum): for deciduous forest, [100,225] smâˆ’1 for rsc and [50,450] smâˆ’1 for rse; for coniferous forest, [225,375] smâˆ’1 for rsc and [350,1200] smâˆ’1 for rse. Due to the features of the observations that are in a limited number but contain multiple climate conditions, the statistical indices for model performance evaluation are required to be sensitive to extreme values. In this study, boxplots were found to well exhibit the model performance at both spatial and temporal scale. Nush-Sutcliffe efficiency (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), mean bias error (MBE), mean variance of error distribution (S2d), index of agreement (d), root mean square error (RMSE) were found as appropriate statistical indices to provide additional evaluation information to the boxplots. The model performance can be judged as satisfactory if NSE > 0.5, RSR â‰¤ 0.7, PBIAS < -±12, MBE < -±0.45, S2d < 1.11, d > 0.79, RMSE < 0.97. rsc played a more important role than rse in ETP and ETA estimation by the Penman-Monteith equation, which is attributed to the fact that transpiration dominates in ET. The ETP estimation was found the most correlated to the relative humidity (RH), followed by air temperature (T), relative sunshine duration (SSD) and wind speed (WS). Under wet or medium wet climate conditions, ETA estimation was found the most correlated to T, followed by RH, SSD and WS. Under a water-stress condition, there were very small correlations between ETA and each meteorological variable.

The last decades of stress research have yielded substantial advancements highlighting the importance of the phenomenon for basic psychological functions as well as physical health and well-being. Progress in stress research heavily relies on the availability of suitable and well validated laboratory stressors. Appropriate laboratory stressors need to be able to reliably provoke a response in the relevant parameters and be applicable in different research settings or experimental designs. This thesis focuses on the Cold Pressor Test (CPT) as a stress induction technique. Three published experiments are presented that show how the advantages of the CPT can be used to test stress effects on memory processes and how some of its disadvantages can be met by a simple modification that retains its feasibility and validity. The first experiment applies the CPT in a substantial sample to investigate the consolidation effects of post-learning sympathetic arousal. Stressed participants with high increases in heart rate during the CPT showed enhanced memory performance one day after learning compared to both the warm water control group and low heart rate responders. This finding suggests that beta-adrenergic activation elicited shortly after learning enhances memory consolidation and that the CPT induced heart rate response is a predictor for this effect. Moreover, the CPT proved to be an appropriate stressor to test hypothesis about endogenous adrenergic effects on memory processes. The second experiment addresses known practical limitations of the standard dominant hand CPT protocol. A bilateral feet CPT modification is presented, the elicited neuroendocrine stress response assessed and validated against the standard CPT in a within-subjects design. The bilateral feet CPT elicited a substantial neuroendocrine stress response. Moreover, with the exception of blood pressure responses, all stress parameters were enhanced compared to the standard CPT. This shows that the bilateral feet CPT is a valid alternative to the standard CPT. The third experiment further validates the bilateral feet CPT and its corresponding control procedure by employing it in a typical application scenario. Specifically, the bilateral feet CPT was used to modulate retrieval of event files in a distractor-response binding paradigm that required lateralized bimanual responses. Again, the bilateral feet CPT induced significant increases in heart rate, blood pressure and cortisol, no such increases could be observed in the warm water control condition. Moreover, stressed participants showed diminished retrieval compared to controls. These results provide further evidence for the feasibility and validity of the bilateral feet CPT and its warm water control procedure. Together the experiments presented here highlight the usefulness of the CPT as a tool in psychophysiological stress research. It is especially well suited to test hypothesis concerning stress effects on memory processes and its applicability can be further increased by the bilateral feet modification.

Climate change and habitat fragmentation modify the natural habitat of many wetland biota and lead to new compositions of biodiversity in these ecosystems. While the direct effects of climate are often well known, indirect effects due to biotic interactions remain poorly understood. The water meadow grasshopper, Chorthippus montanus, is a univoltine habitat specialist, which is adapted to permanently moist habitats. Land use change and drainage led to highly fragmented populations of this generally flightless species. In large parts of the Palaearctic Ch. montanus occurs sympatrically with its widespread congener, the meadow grasshopper Chorthippus parallelus. Due to their close relationship and their similar songs, hybridization is likely to occur in syntopic populations. Such a species pair of a habitat specialist and a habitat generalist represents an ideal model system to examine the role of ongoing climate change and an accumulation of extreme climatic events on the life history strategies, population dynamics and inter-specific interactions. In Chapter I a laboratory experiment was conducted to identify the impact of environmental factors on intra-specific life-history traits of Ch. montanus. Like other Orthoptera species, Ch. montanus follows a converse temperature size rule. In line with the dimorphic niche hypothesis, which states that sexual size dimorphism evolved in response to the different sexual reproductive roles, both sexes showed different responses to increasing density at lower temperatures. Males attained smaller body sizes at high densities, whereas females had a prolonged development time. This is the first evidence for a sex-specific phenotypic plasticity in Ch. montanus. Females benefit from the prolonged development as their reproductive success depends on the size and number of egg clutches they may produce. By contrast, the reproductive success of males depends on the chance to fertilize virgin females, which increases with faster development. This may become a disadvantage for Ch. montanus as an intraspecific phenology shift may increase hybridization risk with the sibling species. Despite the widespread assumption that hybridization between two sympatric species is rare due to complete reproductive barriers, the genetic analyses of 16 populations (Chapter II) provided evidence for wide prevalence of hybridization between both species in the wild. As no complete admixture was found in the examined population, it is assumed that hybridization only occurs in ecotones between wetlands and drier parts. Reproductive barriers (habitat isolation, behavior, phenology) seem to prevent the genetic swamping of Ch. montanus populations. Although a behavioral experiment showed that mate choice presents an important reproductive barrier between both species, the experiment also revealed that reproductive barriers could be altered by environmental change (e.g. increasing heterospecific frequency). Chapter III analyzes the impact of extreme climatic events on population dynamics and interspecific hybridization. A mark-recapture analysis combined with weather records over five years provides evidence that the embryonic development in Ch. montanus is vulnerable to extreme climatic events. Strong population declines in Ch. montanus lead to a disequilibrium between Ch. montanus and Ch. parallelus populations and increases the risk of hybridization. The highest hybridization risk was found in the first weeks of a season, when both species had an overlapping phenology. Furthermore, hybrids were generally localized at the edge of the Ch. montanus distribution with higher heterospecific encounter probabilities. The hybridization rate reached up to 19.6%. The genetic analyses in Chapter II and III show that hybridization differentially affects specialists and generalists. While generalists may benefit from hybridization by an increasing genetic diversity, such a positive correlation was not found for Ch. montanus. The results underline the importance of reproductive barriers for the co-existence of these sympatric species. However, climate change and other anthropogenic disturbances alter reproductive barriers and promote hybridization, which may threaten small populations by genetic displacement. As anthropogenic hybridization is recognized as a major threat to biodiversity, it should be considered in environmental law and policy. In Chapter IV the role of hybrids and hybridization in three levels of law and the historical backgrounds of hybrids becoming a part of legal instruments is analyzed. Due to legal uncertainties and the complexity of this topic a legal assessment of hybrids is challenging and argues for species-specific approaches. Nonetheless, existing legal norms provide a suitable basis, but need to be specified. Finally, this chapter discusses different opportunities for the management of hybrids and hybridization in a conservation perspective and their necessity.

Service innovation has increasingly gained acknowledgement to contribute to economic growth and well-being. Despite this increased relevance in practice, service innovation is a developing research field. To advance literature on service innovation, this work analyzes with a qualitative study how firms manage service innovation activities in their organization differently. In addition, it evaluates the influence of top management commitment and corporate service innovativeness on service innovation capabilities of a firm and their implications for firm-level performance by conducting a quantitative study. Accordingly, the main overall research questions of this dissertation are: 1.) How and why do firms manage service innovation activities in their organization differently? 2.) What influence do top management commitment and corporate service innovativeness have on service innovation capabilities of a firm and what are the implications for firm-level performance? To respond to the first research question the way firms manage service innovation activities in their organization is investigated and by whom and how service innovations are developed. Moreover, it is examined why firms implement their service innovation activities differently. To achieve this a qualitative empirical study is conducted which included 22 semi-structured interviews with 15 firms in the sectors of construction, financial services, IT services, and logistics. Addressing the second research question, the aim is to improve the understanding about factors that enhance firm-level performance through service innovations. Deploying a dynamic capabilities perspective, a quantitative study is performed which underlines the importance of service innovation capabilities. More specifically, a theoretical framework is developed that proposes a positive relationship of top management commitment and corporate service innovativeness with service innovation capabilities and a positive relationship between service innovation capabilities and the firm-level performance indicators market performance, competitive advantage, and efficiency. A survey with double respondents from 87 companies from the sectors construction, financial services, IT services, and logistics was conducted to test the proposed theoretical framework by applying partial least squares structural equation modeling (PLS-SEM).

Part-time entrepreneurship has become increasingly popular and is a rather new field of research. Two important research topics are addressed in this dissertation: (a) the impact of culture on part-time and full-time entrepreneurship and (b) the motivational aspects of the transition from part-time to full-time entrepreneurship. Specifically, this dissertation advances prior research by highlighting the direct and indirect differential impact of macro-level societal culture on part-time and full-time entrepreneurship. Gender egalitarianism, uncertainty avoidance and future orientation have a significantly stronger impact on full-time than on part-time entrepreneurship. Furthermore the moderating impact of societal culture on micro-level relationships for both forms of entrepreneurship is explored. The age-old and well-established relationship between education and entrepreneurial activity is moderated by different forms of collectivism for part-time and full-time entrepreneurship. Regarding the motivation of part-time entrepreneurs to transition to full-time entrepreneurship, the entrepreneurial motives of self-realization and independence are significantly positively associated with the transition, whereas the entrepreneurial motives of income supplementation and recognition are significantly negatively associated with the transition. This dissertation advances academic research by indicating conceptual differences between part-time and full-time entrepreneurship in a multi country setting and by showing that both forms of entrepreneurship are impacted through different cultural mechanisms. Based on the findings, policy makers can identify the direct and indirect impact of societal culture on part-time and full-time entrepreneurship. As a result, policy makers can better target support and transition programs to foster entrepreneurial activity.

This study examines the relationship between media content, its production, and its reception in Japanese popular culture with the example of the so-called yuri ("lily") genre that centers on representations of intimate relationships between female characters. Based on contemporary genre theory, which posits that genres are not inherent properties of texts, the central question of this study is how the yuri genre is discursively produced in Japan. To examine this question, the study takes a variety of sources into consideration: Firstly, it discusses ten exemplary texts from the 1910s to 2010s that in the Japanese discourse on the yuri genre are deemed the milestone texts of the yuri genre's historical development (Hana monogatari, Otome no minato, Secret Love, Shiroi heya no futari, BishÅjo senshi Sailor Moon, Maria-sama ga miteru, ShÅjo Sect, Aoi hana, Yuru yuri, and Yuri danshi). Secondly, interviews with ten editors working for Japanese manga magazines shed light on their assessment of the yuri genre. Finally, the results of an online survey among Japanese fans of the yuri genre, which returned 1,352 completed questionnaires, question hitherto assumptions about the fans and their reasons for liking the yuri genre. The central argument of this study is that the yuri genre is for the most part constructed not through assignments on part of the genre's producers but through interpretations on part of the genre's fans. The intimacy portrayed in the texts ranges from "friendship" to "love," and often the ideas of "innocence" and "beauty" are emphasized. Nevertheless, the formation of the yuri genre occurs outside the bounds of the texts, most importantly in fan works, i.e. derivative texts created by fans. The actual content of the originals merely serves as a starting point for these interpretations. Located at the intersection of Japanese studies, cultural studies, media studies, and sociology, this study contributes to our understanding of contemporary Japanese popular culture by showing the mutual dependencies between media content, production, and reception. It provides a deeper look at these processes through first-hand accounts of both producers and fans of the yuri genre.

Death is perceived as a severe threat to the self. Although it is certain that everyone has to die, people usually don't think about the finiteness of their life. Everything reminding of death is ignored, rationalized and death-related thoughts and fears are pushed out of mind (TMT; Pyszczynski et al., 1999). However, people differ in their ability to regulate negative affect and to access their self-system (Kuhl, 2001). As death is assumed to arouse existential fears, the ability to regulate such fears is particularly important, higher self-access could be relevant in defending central personal values. This thesis aimed at showing existential fears under mortality salience and effects of self-regulation of affect under mortality salience. In two studies (Chapter 2) implicit negative affect under mortality salience was demonstrated. An additional study (Chapter 3) shows the effects of self-regulation on implicit negative affect, whereas four studies in Chapter 4 displayed differences in self-access under mortality salience depending on people- ability of self-regulating negative affect.

Financing of Small and Medium-Sized Enterprises in Europe - Financing Patterns and 'Crowdfunding'
(2015)

Small and medium-sized enterprises (SMEs) play a vital role for the innovativeness, economic growth and competitiveness of Europe. One of the most pressing problems of SMEs is access to finance to ensure their survival and growth. This dissertation uses both quantitative and qualitative exploratory research methods and increases with its holistic approach the transparency in SME financing. The results of a cluster analysis including 12,726 SMEs in 28 European countries reveal that SME financing in Europe is not homogenous but that different financing patterns exist which differ according to the number of financing instruments used and the combinations thereof. Furthermore, the SME financing types can be profiled according to their firm-, product-, industry- and country-specific characteristics. The results of this analysis provide some support for prior findings that smaller, younger and innovative SMEs suffer from a financing gap which cannot be closed with traditional financing instruments. One alternative to close this financing gap is crowdfunding. Even though crowdfunding has shown tremendous growth rates over the past few years, little is known about the determinants of this financing alternative. This dissertation systematically analyses the existing scientific literature on crowdfunding as an alternative in SME financing and reveals existing research gaps. Afterwards, the focus is on the role of investor communication as a way to reduce information asymmetries of the crowd in equity-based crowdfunding. The results of 24 interviews with market participants in equity-based crowdfunding reveal that crowd investors seem to replace personal contacts with alternative ways of communicating, which can be characterized as pseudo-personal (i.e., by using presentation videos, social media and investor relations channels). In addition, it was found that third party endorsements (e.g., other crowd investors, professional investors, customers and platforms) reduce the information asymmetries of crowd investors and hence, increase the likelihood of their investment.

In politics and economics, and thus in the official statistics, the precise estimation of indicators for small regions or parts of populations, the so-called Small Areas or domains, is discussed intensively. The design-based estimation methods currently used are mainly based on asymptotic properties and are thus reliable for large sample sizes. With small sample sizes, however, this design based considerations often do not apply, which is why special model-based estimation methods have been developed for this case - the Small Area methods. While these may be biased, they often have a smaller mean squared error (MSE) as the unbiased design based estimators. In this work both classic design-based estimation methods and model-based estimation methods are presented and compared. The focus lies on the suitability of the various methods for their use in official statistics. First theory and algorithms suitable for the required statistical models are presented, which are the basis for the subsequent model-based estimators. Sampling designs are then presented apt for Small Area applications. Based on these fundamentals, both design-based estimators and as well model-based estimation methods are developed. Particular consideration is given in this case to the area-level empirical best predictor for binomial variables. Numerical and Monte Carlo estimation methods are proposed and compared for this analytically unsolvable estimator. Furthermore, MSE estimation methods are proposed and compared. A very popular and flexible resampling method that is widely used in the field of Small Area Statistics, is the parametric bootstrap. One major drawback of this method is its high computational intensity. To mitigate this disadvantage, a variance reduction method for parametric bootstrap is proposed. On the basis of theoretical considerations the enormous potential of this proposal is proved. A Monte Carlo simulation study shows the immense variance reduction that can be achieved with this method in realistic scenarios. This can be up to 90%. This actually enables the use of parametric bootstrap in applications in official statistics. Finally, the presented estimation methods in a large Monte Carlo simulation study in a specific application for the Swiss structural survey are examined. Here problems are discussed, which are of high relevance for official statistics. These are in particular: (a) How small can the areas be without leading to inappropriate or to high precision estimates? (b) Are the accuracy specifications for the Small Area estimators reliable enough to use it for publication? (c) Do very small areas infer in the modeling of the variables of interest? Could they cause thus a deterioration of the estimates of larger and therefore more important areas? (d) How can covariates, which are in different levels of aggregation be used in an appropriate way to improve the estimates. The data basis is the Swiss census of 2001. The main results are that in the author- view, the use of small area estimators for the production of estimates for areas with very small sample sizes is advisable in spite of the modeling effort. The MSE estimates provide a useful measure of precision, but do not reach in all Small Areas the level of reliability of the variance estimates for design-based estimators.

The Role of Dopamine and Acetylcholine as Modulators of Selective Attention and Response Speed
(2015)

The principles of top-down and bottom-up processing are essential to cognitive psychology. At their broadest, most general definition, they denote that processing can be driven either by the salience of the stimulus input or by individual goals and strategies. Selective top-down attention, specifically, consists in the deliberate prioritizing of stimuli that are deemed goal-relevant, while selective bottom-up attention relies on the automatic allocation of attention to salient stimuli (Connor, Egeth, & Yantis, 2004; Schneider, Schote, Meyer, & Frings, 2014). Variations within neurotransmitter systems can modulate cognitive performance in a domain-specific fashion (Greenwood, Fossella, & Parasuraman, 2005). Noudoost and Moore (2011a) proposed that the influence of the dopaminergic neurotransmitter system on selective top-down attention might be greater than the influence of this system on selective bottom-up attention; likewise, they assumed that the cholinergic neurotransmitter system might be more important for selective bottom-up than top-down attention. To test this hypothesis, naturally occurring variations within the two neurotransmitter systems were assessed. Five polymorphisms were selected; two of the dopaminergic system (the COMT Val158Met polymorphism and the DAT1 polymorphism) and three of the cholinergic system (the CHRNA4 rs1044396 polymorphism, the CHRNA5 rs3841324 polymorphism, and the CHRNA5 rs16969968 polymorphism). It was tested whether these polymorphisms modulated the performance in tasks of selective top-down attention (a Stroop task and a Negative priming task) and in a task of selective bottom-up attention (a Posner-Cuing task). Indeed, the dopaminergic polymorphisms influenced selective top-down attention, but exerted no effects on bottom-up attention. This aligned with the hypothesis proposed by Noudoost and Moore (2011a). In contrast, the cholinergic polymorphisms were not found to modulate selective bottom-up attention. The three cholinergic polymorphisms, however, affected the general response speed in the Stroop task, Negative priming task, and Posner-Cuing task (irrespective of attentional processing). In sum, the findings of this study provide strong indications that the dopaminergic system modulates selective top-down attention, while the cholinergic system is highly relevant for the general speed of information processing.

The distractor-response binding effect (Frings & Rothermund, 2011; Frings, Rothermund, & Wentura, 2007; Rothermund, Wentura, & De Houwer, 2005) is based on the idea that irrelevant information will be integrated with the response to the relevant stimuli in an episodic memory trace. The immediate re-encounter of any aspect of this saved episode " be it relevant or irrelevant " can lead to retrieval of the whole episode. As a consequence, the previously executed and now retrieved response may influencing the response to the current relevant stimulus. That is, the current response may either be facilitated or be impaired by the retrieved response, depending on whether it is compatible or incompatible to the currently demanded response. Previous research on this kind of episodic retrieval focused on the influence on action control. I examined if distractor response binding also plays a role in decision making in addition to action control. To this end I adapted the distractor-to-distractor priming paradigm (Frings et al., 2007) and conducted nine experiments in which participants had to decide as fast as possible which disease a fictional patient suffered from. To infer the correct diagnosis, two cues were presented; one did not give any hint for a disease (the irrelevant cue), whereas the other did (the relevant cue). Experiments 1a to 1c showed that the distractor-response binding effect is present in deterministic decision situations. Further, experiments 2a and 2b indicate that distractor-response binding also influences decisions under uncertainty. Finally, experiments 3a to 3d were conducted to test some constraints and underlying mechanisms of the distractor-response binding effect in decision making under uncertainty. In sum, these nine experiments provide strong evidence that distractor-response binding influences decision making.

Stress related disorders increase continuously. It is not yet clear if stress also promotes breast cancer. This dissertation provides an analyses of the current state of research and focuses on the significance of pre-/postnatal stress factors and chronic stress. The derived hypotheses are empirically examined on breast cancer patients. The clinical study investigates the links between those factors and prognosis and outcome.

This thesis deals with economic aspects of employees' sickness. In addition to the classical case of sickness absence, in which an employee is completely unable to work and hence stays at home, there is the case of sickness presenteeism, in which the employee comes to work despite being sick. Accordingly, the thesis at hand covers research on both sickness states, absence and presenteeism. The first section covers sickness absence and labour market institutions. Chapter 2 presents theoretical and empirical evidence that differences in the social norm against benefit fraud, so-called benefit morale, can explain cross country diversity in the generosity of statutory sick pay entitlements between developed countries. In our political economy model, a stricter benefit morale reduces the absence rate, with counteracting effects on the politically set sick pay replacement rate. On the one hand, less absence caused by a stricter norm, makes the tax-financed insurance cheaper, leading to the usual demand side effect and hence to more generous sick pay entitlements. On the other hand, being less likely to be absent due to a stricter norm, the voters prefer a smaller fee over more insurance. We document both effects in a sample of 31 developed countries, capturing the years from 1981 to 2010. In Chapter 3 we investigate the relationship between the existence of works councils and illness-related absence and its consequences for plants. Using individual data from the German Socio-Economic Panel (SOEP), we find that the existence of a works council is positively correlated with the incidence and the annual duration of absence. Additionally, linked employer-employee data (LIAB) suggests that employers are more likely to expect personnel problems due to absence in plants with a works council. In western Germany, we find significant effects using a difference-in-differences approach, which can be causally interpreted. The second part of this thesis covers two studies on sickness presenteeism. In Chapter 4, we empirically investigate the determinants of the annual duration of sickness presenteeism using the European Working Conditions Survey (EWCS). Work autonomy, workload and tenure are positively related to the number of sickness presenteeism days, while a good working environment comes with less presenteeism. In Chapter 5 we theoretically and empirically analyze sickness absence and presenteeism behaviour with a focus on their interdependence. Specifically, we ask whether work-related factors lead to a substitutive, a complementary or no relationship between sickness absence and presenteeism. In other words, we want to know whether changes in absence and presenteeism behaviour incurred by work-related characteristics point in opposite directions (substitutive), the same direction (complementary), or whether they only affect either one of the two sickness states (no relationship). Our theoretical model shows that the relationship between sickness absence and presenteeism with regard to work-related characteristics is not necessarily of a substitutive nature. Instead, a complementary or no relationship can emerge as well. Turning to the empirical investigation, we find that only one out of 16 work-related factors, namely the supervisor status, leads to a substitutive relationship between absence and presenteeism. Few of the other determinants are complements, while the large majority is either related to sickness absence or presenteeism.

Chapter 2: Using data from the German Socio-Economic Panel, this study examines the relation-ship between immigrant residential segregation and immigrants" satisfaction with the neighbor-hood. The estimates show that immigrants living in segregated areas are less satisfied with the neighborhood. This is consistent with the hypothesis that housing discrimination rather than self-selection plays an important role in immigrant residential segregation. Our result holds true even when controlling for other influences such as household income and quality of the dwelling. It also holds true in fixed effects estimates that account for unobserved time-invariant influences. Chapter 3: Using survey data from the German Socio-Economic Panel, this study shows that immigrants living in segregated residential areas are more likely to report discrimination because of their ethnic background. This applies to both segregated areas where most neighbors are immigrants from the same country of origin as the surveyed person and segregated areas where most neighbors are immigrants from other countries of origin. The results suggest that housing discrimination rather than self-selection plays an important role in immigrant residential segregation. Chapter 4: Using data from the German Socio-Economic Panel (SOEP) and administrative data from 1996 to 2009, I investigate the question whether or not right-wing extremism of German residents is affected by the ethnic concentration of foreigners living in the same residential area. My results show a positive but insignificant relationship between ethnic concentration at the county level and the probability of extreme right-wing voting behavior for West Germany. However, due to potential endogeneity issues, I additionally instrument the share of foreigners in a county with the share of foreigners in each federal state (following an approach of Dustmann/Preston 2001). I find evidence for the interethnic contact theory, predicting a negative relationship between foreign-ers" share and right-wing voting. Moreover, I analyze the moderating role of education and the influence of cultural traits on this relationship. Chapter 5: Using data from the Socio-Economic Panel from 1998 to 2009 and administrative data on regional ethnic diversity, I show that ethnic diversity inhibits significantly people- political interest and participation in political organizations in West Germany. People seem to isolate themselves from political participation if exposed to more ethnic diversity which is particularly relevant with respect to the ongoing integration process of the European Union and the increasing transfer of legislative power from the national to European level. The results are robust if an instrumental variable strategy suggested by Dustmann and Preston (2001) is used to take into account that ethnic diversity measured on a local spatial level could be endogenous due to residential sorting. Interestingly, participation in non-political organizations is positively affected by ethnic diversity if selection bias is corrected for.

The classic Capital Asset Pricing Model and the portfolio theory suggest that investors hold the market portfolio to diversify idiosyncratic risks. The theory predicts that expected return of assets is positive and that reacts linearly on the overall market. However, in reality, we observe that investors often do not have perfectly diversified portfolios. Empirical studies find that new factors influence the deviation from the theoretical optimal investment. In the first part of this work (Chapter 2) we study such an example, namely the influence of maximum daily returns on subsequent returns. Here we follow ideas of Bali et al. (2011). The goal is to find cross-sectional relations between extremely positive returns and expected average returns. We take account a larger number of markets worldwide. Bali et al. (2011) report with respect to the U.S. market a robust negative relation between MAX (the maximum daily return) and the expected return in the subsequent time. We extent substantially their database to a number of other countries, and also take more recent data into account (until end of 2009). From that we conclude that the relation between MAX and expected returns is not consistent in all countries. Moreover, we test the robustness of the results of Bali et al. (2011) in two time-periods using the same data from CRSP. The results show that the effect of extremely positive returns is not stable over time. Indeed we find a negative cross-sectional relation between the extremely positive returns and the average returns for the first half of the time series, however, we do not find significant effects for the second half. The main results of this chapter serve as a basis for an unpublished working paper Yuan and Rieger (2014b). While in Chapter 2 we have studied factors that prevent optimal diversification, we consider in Chapter 3 and 4 situations where the optimal structure of diversification was previously unknown, namely diversification of options (or structured financial products). Financial derivatives are important additional investment form with respect to diversification. Not only common call and put options, but also structured products enable investors to pursue a multitude of investment strategies to improve the risk-return profile. Since derivatives become more and more important, diversification of portfolios with dimension of derivatives is of particularly practical relevance. We investigate the optimal diversification strategies in connection with underlying stocks for classical rational investors with constant relative risk aversion (CRRA). In particular, we apply Monte Carlo method based on the Black-Scholes model and the Heston model for stochastic volatility to model the stock market processes and the pricing of the derivatives. Afterwards, we compare the benchmark portfolio which consists of derivatives on single assets with derivatives on the index of these assets. First we compute the utility improvement of an investment in the risk-free assets and plain-vanilla options for CRRA investors in various scenarios. Furthermore, we extend our analysis to several kinds of structured products, in particular capital protected notes (CPNs), discount certificates (DCs) and bonus certificates (BCs). We find that the decision of an investor between these two diversification strategies leads to remarkable differences. The difference in the utility improvement is influenced by risk-preferences of investors, stock prices and the properties of the derivatives in the portfolio. The results will be presented in Chapter 3 and are the basis for a yet unpublished working paper Yuan and Rieger (2014a). To check furthermore whether underlyings of structured products influence decisions of investors, we discuss explicitly the utility gain of a stock-based product and an index-based product for an investor whose preferences are described by cumulative prospect theory (CPT) (Chapter 4, compare to Yuan (2014)). The goal is that to investigate the dependence of structured products on their underlying where we put emphasis on the difference between index-products and single-stock-products, in particular with respect to loss-aversion and mental accounting. We consider capital protected notes and discount certificates as examples, and model the stock prices and the index of these stocks via Monte Carlo simulations in the Black-Scholes framework. The results point out that market conditions, particularly the expected returns and volatility of the stocks play a crucial role in determining the preferences of investors for stock-based CPNs and index-based CPNs. A median CPT investor prefers the index-based CPNs if the expected return is higher and the volatility is lower, while he prefers the stock-based CPNs in the other situation. We also show that index-based DCs are robustly more attractive as compared to stock-based DCs for CPT investors.