Representation Learning techniques play a crucial role in a wide variety of Deep Learning applications. From Language Generation to Link Prediction on Graphs, learned numerical vector representations often build the foundation for numerous downstream tasks. In Natural Language Processing, word embeddings are contextualized and depend on their current context. This useful property reflects how words can have different meanings based on their neighboring words. In Knowledge Graph Embedding (KGE) approaches, static vector representations are still the dominant approach. While this is sufficient for applications where the underlying Knowledge Graph (KG) mainly stores static information, it becomes a disadvantage when dynamic entity behavior needs to be modelled. To address this issue, KGE approaches would need to model dynamic entities by incorporating situational and sequential context into the vector representations of entities. Analogous to contextualised word embeddings, this would allow entity embeddings to change depending on their history and current situational factors. Therefore, this thesis provides a description of how to transform static KGE approaches to contextualised dynamic approaches and how the specific characteristics of different dynamic scenarios are need to be taken into consideration. As a starting point, we conduct empirical studies that attempt to integrate sequential and situational context into static KG embeddings and investigate the limitations of the different approaches. In a second step, the identified limitations serve as guidance for developing a framework that enables KG embeddings to become truly dynamic, taking into account both the current situation and the past interactions of an entity. The two main contributions in this step are the introduction of the temporally contextualized Knowledge Graph formalism and the corresponding RETRA framework which realizes the contextualisation of entity embeddings. Finally, we demonstrate how situational contextualisation can be realized even in static environments, where all object entities are passive at all times. For this, we introduce a novel task that requires the combination of multiple context modalities and their integration with a KG based view on entity behavior.

This thesis explores local and global normal and Edgeworth approximations for symmetric binomial distributions. Further, it examines the normal approximation of convolution powers of continuous and discrete uniform distributions. We obtain the optimal constant in the local central limit theorem for symmetric binomial distributions and its analogs in higher-order Edgeworth approximation. Further, we offer a novel proof for the known optimal constant in the global central limit theorem for symmetric binomial distributions using Fourier inversion. We also consider the effect of simple continuity correction in the global central limit theorem for symmetric binomial distributions. Here, and in higher-order Edgeworth approximation, we found optimal constants and asymptotically sharp bounds on the approximation error. Furthermore, we prove asymptotically sharp bounds on the error in the local case of a relative normal approximation to symmetric binomial distributions. Additionally, we provide asymptotically sharp bounds on the approximation error in the local central limit theorem for convolution powers of continuous and discrete uniform distributions. Our methods include Fourier inversion formulae, explicit inequalities, and Edgeworth expansions, some of which may be of independent interest.

Mindfulness is a popular technique that helps people to get closer to their self. However, recent findings indicate that mindfulness may not benefit everybody. In the present research, we hypothesized that mindfulness promotes alienation from the self among individuals with low abilities to self-regulate affect (state-oriented individuals) but not among individuals with high abilities to self-regulate affect (action-oriented individuals). In two studies with participants who were mostly naïve to mindfulness practices (70% indicated no experience; N1 = 126, 42 men, 84 women, 0 diverse, aged 17–86 years, Mage = 31.87; N2 = 108, 30 men, 75 women, 3 diverse, aged 17–69 years, Mage = 28.00), we tested a mindfulness group (five-minute mindfulness exercise) against a control group (five-minute text reading). We operationalized alienation as lower consistency in repeated preference judgments and a lower tendency to adopt intrinsic over extrinsic goal recommendations. Results showed that, among state-oriented participants, mindfulness led to significantly lower consistency of preference judgments (Study 1) and lower adoption of intrinsic over extrinsic goals (Study 2) compared to text reading. The alienating effect was absent among action-oriented participants. Thus, mindfulness practice may alienate psychologically vulnerable people from their self and hamper access to preferences and intrinsic goals. We discuss our findings within Personality-Systems-Interactions (PSI) theory.

　

　

　

　

　

This meta-scientific dissertation comprises three research articles that investigated the reproducibility of psychological research. Specifically, they focused on the reproducibility of eye-tracking research on the one hand, and studying preregistration (i.e., the practice of publishing a study protocol before data collection or analysis) as one method to increase reproducibility on the other hand. In Article I, it was demonstrated that eye-tracking data quality is influenced by both the utilized eye-tracker and the specific task it is measuring. That is, distinct strengths and weaknesses were identified in three devices (Tobii Pro X3-120, GP3 HD, EyeLink 1000+) in an extensive test battery. Consequently, both the device and specific task should be considered when designing new studies. Meanwhile, Article II focused on the current perception of preregistration in the psychological research community and future directions for improving this practice. The survey showed that many researchers intended to preregister their research in the future and had overall positive attitudes toward preregistration. However, various obstacles were identified currently hindering preregistration, which should be addressed to increase its adoption. These findings were supplemented by Article III, which took a closer look at one preregistration-specific tool: the PRP-QUANT Template. In a simulation trial and a survey, the template demonstrated high usability and emerged as a valuable resource to support researchers in using preregistration. Future revisions of the template could help to further facilitate this open science practice. In this dissertation, the findings of the three articles are summarized and discussed regarding their implications and potential future steps that could be implemented to improve the reproducibility of psychological research.

Cette contribution pratique présente les principales méthodes d’analyse qui peuvent être utilisées dans diverses matières à l’école, mais qui peuvent aussi favoriser la réflexion sur des conflits personnels qui surviennent au sein de la famille, de la classe ou de la communauté scolaire.

　

This thesis contains four parts that are all connected by their contributions to the Efficient Market Hypothesis and decision-making literature. Chapter two investigates how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020. The results show that lockdown restrictions led to different reactions in a sample of OECD and BRICS countries: there was a general negative effect resulting from the increase in lockdown restrictions, but the study finds strong evidence for underreaction during the lockdown announcement, followed by some overreaction that is corrected subsequently. This under-/overreaction pattern, however, is observed mostly during the first half of our time series, pointing to learning effects. Relaxation of the lockdown restrictions, on the other hand, had a positive effect on markets only during the second half of our sample, while for the first half of the sample, the effect was negative. The third chapter investigates the gender differences in stock selection preferences on the Taiwan Stock Exchange. By utilizing trading data from the Taiwan Stock Exchange over a span of six years, it becomes possible to analyze trading behavior while minimizing the self-selection bias that is typically present in brokerage data. To study gender differences, this study uses firm-level data. The percentage of male traders in a company is the dependent variable, while the company’s industry and fundamental/technical aspects serve as independent variables. The results show that the percentage of women trading a company rises with a company’s age, market capitalization, a company’s systematic risk, and return. Men trade more frequently and show a preference for dividend-paying stocks and for industries with which they are more familiar. The fourth chapter investigated the relationship between regret and malicious and benign envy. The relationship is analyzed in two different studies. In experiment 1, subjects had to fill out psychological scales that measured regret, the two types of envy, core self-evaluation and the big 5 personality traits. In experiment 2, felt regret is measured in a hypothetical scenario, and the subject’s felt regret was regressed on the other variables mentioned above. The two experiments revealed that there is a positive direct relationship between regret and benign envy. The relationship between regret and malicious envy, on the other hand, is mostly an artifact of core self-evaluation and personality influencing both malicious envy and regret. The relationship can be explained by the common action tendency of self-improvement for regret and benign envy. Chapter five discusses the differences in green finance regulation and implementation between the EU and China. China introduced the Green Silk Road, while the EU adopted the Green Deal and started working with its own green taxonomy. The first difference comes from the definition of green finance, particularly with regard to coal-fired power plants. Especially the responsibility of nation-states’ emissions abroad. China is promoting fossil fuel projects abroad through its Belt and Road Initiative, but the EU’s Green Deal does not permit such actions. Furthermore, there are policies in both the EU and China that create contradictory incentives for economic actors. On the one hand, the EU and China are improving the framework conditions for green financing while, on the other hand, still allowing the promotion of conventional fuels. The role of central banks is also different between the EU and China. China’s central bank is actively working towards aligning the financial sector with green finance. A possible new role of the EU central bank or the priority financing of green sectors through political decision-making is still being debated.

　

　

Departing from Roland Barthes’ association of text and textile, and feminist theory on weaving as text production, this article analyzes the textile qualities of Inger Christensen’s “Letter in April” (1979) and Amalie Smith’s “Thread Ripper” (2020). In “Letter in April”, Christensen establishes a connection between writing and spinning or weaving through their shared temporality of varied repetition. In “Thread Ripper” Smith alludes to Christensen and makes of the continuity between text and textile not only the main theme of the book, but also its structuring principle. Through a materialist conception of the text, regarding it as a woven fabric, the article focuses on the textual patterns of the two works (stylistic figures in Christensen, graphic composition in Smith). The connection from Christensen to Smith leads to a further connection to ecocritical conceptions of weaving as no less than a cosmological principle. On a concluding note, the article argues that weaving is not only connecting, but also disconnecting, cutting.

Der vorliegende Beitrag greift die öffentliche Diskussion um den rechtspolitischen Umgang mit Hass, Hetze und Antisemitismus auf, die insbesondere nach dem Terroranschlag der Hamas am 07.10.2023 an Intensität und Dringlichkeit zugenommen hat. Dabei beleuchtet er einerseits das Straf- und Zivilrecht, legt andererseits einen besonderen Fokus auf öffentlich-rechtliche Konstellationen. Auf jedem dieser Gebiete werden Schwächen und Potenziale des Rechts und der Rechtsprechung aufgezeigt, zugleich aber auch die Grenzen staatlicher Gewalt verdeutlicht. Denn letztlich handelt es sich um ein gesellschaftliches Problem, dem – trotz aller Notwendigkeit staatlichen Handelns – in erster Linie durch Information, und erst in zweiter Linie durch das Recht begegnet werden muss.

　

In machine learning, classification is the task of predicting a label for each point within a data set. When the class of each point in the labeled subset is already known, this information is used to recognize patterns and make predictions about the points in the remainder of the set, referred to as the unlabeled set. This scenario falls in the field of supervised learning. However, the number of labeled points can be restricted, because, e.g., it is expensive to obtain this information. Besides, this subset may be biased, such as in the case of self-selection in a survey. Consequently, the classification performance for unlabeled points may be limited. To improve the reliability of the results, semi-supervised learning tackles the setting of labeled and unlabeled data. Moreover, in many cases, additional information about the size of each class can be available from undisclosed sources. This cumulative thesis presents different studies to combine this external cardinality constraint information within three important algorithms for binary classification in the supervised context: support vector machines (SVM), classification trees, and random forests. From a mathematical point of view, we focus on mixed-integer programming (MIP) models for semi-supervised approaches that consider a cardinality constraint for each class for each algorithm. Furthermore, since the proposed MIP models are computationally challenging, we also present techniques that simplify the process of solving these problems. In the SVM setting, we introduce a re-clustering method and further computational techniques to reduce the computational cost. In the context of classification trees, we provide correct values for certain bounds that play a crucial role for the solver performance. For the random forest model, we develop preprocessing techniques and an intuitive branching rule to reduce the solution time. For all three methods, our numerical results show that our approaches have better statistical performances for biased samples than the standard approach.

　

Visualizing brain simulation data is in many aspects a challenging task. For one, data used in brain simulations and the resulting datasets is heterogeneous and insight is derived by relating all different kinds of it. Second, the analysis process is rapidly changing while creating hypotheses about the results. Third, the scale of data entities in these heterogeneous datasets is manifold, reaching from single neurons to brain areas interconnecting millions. Fourth, the heterogeneous data consists of a variety of modalities, e.g.: from time series data to connectivity data, from single parameters to a set of parameters spanning parameter spaces with multiple possible and biological meaningful solutions; from geometrical data to hierarchies and textual descriptions, all on mostly different scales. Fifth, visualizing includes finding suitable representations and providing real-time interaction while supporting varying analysis workflows. To this end, this thesis presents a scalable and flexible software architecture for visualizing, integrating and interacting with brain simulations data. The scalability and flexibility is achieved by interconnected services forming in a series of Coordinated Multiple View (CMV) systems. Multiple use cases are presented, introducing views leveraging this architecture, extending its ecosystem and resulting in a Problem Solving Environment (PSE) from which custom-tailored CMV systems can be build. The construction of such CMV system is assisted by semantic reasoning hence the term semantic-aware CMVs.

In order to shed light on the important function Inger Christensen had for the German poetry scene in the 1990s and 2000s, the article examines texts by Thomas Kling and Oswald Egger. The central argument is that both Kling and Egger drew on Christensen’s sophisticated nature-philosophical inspired poetics in “det”/“das” to break away from an experimental poetry that is primarily interested in questions of language and media theory. Both seem to be particularly fascinated by Christensen’s attempt to think of the relationship between language and the world in terms of a chiastic entanglement, which shows clear traces of Maurice Merleau-Ponty’s phenomenology of perception. But despite this similarity, they react very differently to the poetological considerations of the Danish poet. Both do not adopt Christensen’s reflections uncritically but attempt to utilize them for their own aesthetic purposes.

Physically-based distributed rainfall-runoff models as the standard analysis tools for hydro-logical processes have been used to simulate the water system in detail, which includes spa-tial patterns and temporal dynamics of hydrological variables and processes (Davison et al., 2015; Ek and Holtslag, 2004). In general, catchment models are parameterized with spatial information on soil, vegetation and topography. However, traditional approaches for eval-uation of the hydrological model performance are usually motivated with respect to dis-charge data alone. This may thus cloud model realism and hamper understanding of the catchment behavior. It is necessary to evaluate the model performance with respect to in-ternal hydrological processes within the catchment area as well as other components of wa-ter balance rather than runoff discharge at the catchment outlet only. In particular, a consid-erable amount of dynamics in a catchment occurs in the processes related to interactions of the water, soil and vegetation. Evapotranspiration process, for instance, is one of those key interactive elements, and the parameterization of soil and vegetation in water balance mod-eling strongly influences the simulation of evapotranspiration. Specifically, to parameterize the water flow in unsaturated soil zone, the functional relationships that describe the soil water retention and hydraulic conductivity characteristics are important. To define these functional relationships, Pedo-Transfer Functions (PTFs) are common to use in hydrologi-cal modeling. Opting the appropriate PTFs for the region under investigation is a crucial task in estimating the soil hydraulic parameters, but this choice in a hydrological model is often made arbitrary and without evaluating the spatial and temporal patterns of evapotran-spiration, soil moisture, and distribution and intensity of runoff processes. This may ulti-mately lead to implausible modeling results and possibly to incorrect decisions in regional water management. Therefore, the use of reliable evaluation approaches is continually re-quired to analyze the dynamics of the current interactive hydrological processes and predict the future changes in the water cycle, which eventually contributes to sustainable environ-mental planning and decisions in water management. Remarkable endeavors have been made in development of modelling tools that provide insights into the current and future of hydrological patterns in different scales and their im-pacts on the water resources and climate changes (Doell et al., 2014; Wood et al., 2011). Although, there is a need to consider a proper balance between parameter identifiability and the model's ability to realistically represent the response of the natural system. Neverthe-less, tackling this issue entails investigation of additional information, which usually has to be elaborately assembled, for instance, by mapping the dominant runoff generation pro-cesses in the intended area, or retrieving the spatial patterns of soil moisture and evapotran-spiration by using remote sensing methods, and evaluation at a scale commensurate with hydrological model (Koch et al., 2022; Zink et al., 2018). The present work therefore aims to give insights into the modeling approaches to simulate water balance and to improve the soil and vegetation parameterization scheme in the hydrological model subject to producing more reliable spatial and temporal patterns of evapotranspiration and runoff processes in the catchment. An important contribution to the overall body of work is a book chapter included among publications. The book chapter provides a comprehensive overview of the topic and valua-ble insights into the understanding the water balance and its estimation methods. Moreover, the first paper aimed to evaluate the hydrological model behavior with re-spect to contribution of various sources of information. To do so, a multi-criteria evaluation metric including soft and hard data was used to define constraints on outputs of the 1-D hydrological model WaSiM-ETH. Applying this evaluation metric, we could identify the optimal soil and vegetation parameter sets that resulted in a “behavioral” forest stand water balance model. It was found out that even if simulations of transpiration and soil water con-tent are consistent with measured data, but still the dominant runoff generation processes or total water balance might be wrongly calculated. Therefore, only using an evaluation scheme which looks over different sources of data and embraces an understanding of the local controls of water loss through soil and plant, allowed us to exclude the unrealistic modeling outputs. The results suggested that we may need to question the generally accept-ed soil parameterization procedures that apply default parameter sets. The second paper attempts to tackle the pointed model evaluation hindrance by getting down to the small-scale catchment (in Bavaria). Here, a methodology was introduced to analyze the sensitivity of the catchment water balance model to the choice of the Pedo-Transfer Functions (PTF). By varying the underlying PTFs in a calibrated and validated model, we could determine the resulting effects on the spatial distribution of soil hydraulic properties, total water balance in catchment outlet, and the spatial and temporal variation of the runoff components. Results revealed that the water distribution in the hydrologic system significantly differs amongst various PTFs. Moreover, the simulations of water balance components showed high sensitivity to the spatial distribution of soil hydraulic properties. Therefore, it was suggested that opting the PTFs in hydrological modeling should be care-fully tested by looking over the spatio-temporal distribution of simulated evapotranspira-tion and runoff generation processes, whether they are reasonably represented. To fulfill the previous studies’ suggestions, the third paper then aims to focus on evalu-ating the hydrological model through improving the spatial representation of dominant run-off processes. It was implemented in a mesoscale catchment in southwestern Germany us-ing the hydrological model WaSiM-ETH. Dealing with the issues of inadequate spatial ob-servations for rigorous spatial model evaluation, we made use of a reference soil hydrologic map available for the study area to discern the expected dominant runoff processes across a wide range of hydrological conditions. The model was parameterized by applying 11 PTFs and run by multiple synthetic rainfall events. To compare the simulated spatial patterns to the patterns derived by digital soil map, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability with regard to land use, topography, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions. The three published manuscripts proceeded towards the model evaluation viewpoints that ultimately attain the behavioral model outputs. It was performed through obtaining information about internal hydrological processes that lead to certain model behaviors, and also about the function and sensitivity of some of the soil and vegetation parameters that may primarily influence those internal processes in a catchment. Accordingly, using this understanding on model reactions, and by setting multiple evaluation criteria, it was possi-ble to identify which parameterization could lead to behavioral model realization. This work, in fact, will contribute to solving some of the issues (e.g., spatial variability and modeling methods) identified as the 23 unsolved problems in hydrology in the 21st century (Blöschl et al., 2019). The results obtained in the present work encourage the further inves-tigations toward a comprehensive model calibration procedure considering multiple data sources simultaneously. This will enable developing the new perspectives to the current parameter estimation methods, which in essence, focus on reproducing the plausible dy-namics (spatio-temporal) of the other hydrological processes within the watershed.

　

Left ventricular assist devices (LVADs) have become a valuable treatment for patients with advanced heart failure. Women appear to be disadvantaged in the usage of LVADs and concerning clinical outcomes such as death and adverse events after LVAD implant. Contrary to typical clinical characteristics (e.g., disease severity), device-related factors such as the intended device strategy, bridge to a heart transplantation or destination therapy, are often not considered in research on gender differences. In addition, the relevance of pre-implant psychosocial risk factors, such as substance abuse and limited social support, for LVAD outcomes is currently unclear. Thus, the aim of this dissertation is to explore the role of pre-implant psychosocial risk factors for gender differences in clinical outcomes, accounting for clinical and device-related risk factors. In the first article, gender differences in pre-implant characteristics of patients registered in The European Registry for Patients with Mechanical Circulatory Support (EUROMACS) were investigated. It was found that women and men differed in multiple pre-implant characteristics depending on device strategy. In the second article, gender differences in major clinical outcomes (i.e., death, heart transplant, device explant due to cardiac recovery, device replacement due to complications) were evaluated for patients in the device strategy destination therapy in the Interagency Registry for Mechanically Assisted Circulation (INTERMACS). Additionally, the association of gender and psychosocial risk factors with the major outcomes were analyzed. Women had similar probabilities to die on LVAD support, and even higher probabilities to experience explant of the device due to cardiac recovery compared with men in the destination therapy subgroup. Pre-implant psychosocial risk factors were not associated with major outcomes. The third article focused on gender differences in 10 adverse events (e.g., device malfunction, bleeding) after LVAD implant in INTERMACS. The association of a psychosocial risk indicator with gender and adverse events after LVAD implantation was evaluated. Women were less likely to have psychosocial risk pre-implant but more likely to experience seven out of 10 adverse events compared with men. Pre-implant psychosocial risk was associated with adverse events, even suggesting a dose response-relationship. These associations appeared to be more pronounced in women. In conclusion, women appear to have similar survival to men when accounting for device strategy. They have higher probabilities of recovery, but higher probabilities of device replacement and adverse events compared with men. Regarding these adverse events, women may be more susceptible to psychosocial risk factors than men. The results of this dissertation illustrate the importance of gender-sensitive research and suggest considering device strategy when studying gender differences in LVAD recipients. Further research is warranted to elucidate the role of specific psychosocial risk factors that lead to higher probabilities of adverse events, to intervene early and improve patient care in both, women and men

Internet-Memes sind ein globales, populäres Medium, oft und zumeist unproblematisiert rezipiert und in ihrer Komik meist nur fragmentarisch, auf bestimmte Aspekte fokussiert analysiert. Die vorliegende Arbeit bemüht sich um eine möglichst umfassende Darstellung der Komik in Memes basierend auf klassischen und modernen Komikkategorien. Auf Grundlage einer umfassend-kritischen Synthese der vorliegenden Fachliteratur und eines präzisen Analysemodells kann so eine begründete Diskussion über memetische Komik, ihre Funktionen und ihre positiven wie problematischen Aspekte geführt werden.