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This thesis seeks to improve the understanding of evolution and habitat as key factors forming tadpole morphology (i.e. of larvae of the order Anura), uncovers existing gaps in current research and recommends strategies and directions for future research. The present study improves the knowledge about the influences of evolution and habitat on the bauplan of tadpoles in a global scale ensuring maximum standardization and comparability of the data. In relation to the total number of tadpoles assumed to exist, only a small proportion has been described and only a few of them have been identified genetically. The lack of a global standard for their description makes it difficult to compare data. Using the tadpole of a harlequin frog (Atelopus) from Guiana region, it is shown that only an integrative approach with morphological and genetic data can solve taxonomic problems. In the study area of Madagascar, it becomes evident that in this region the common genetic history only has little influence on morphology, in contrast to the aquatic way of life. Tadpoles from flowing waters develop larger eyes, more robust tail muscles and smaller fins to cope better with current conditions and move more efficiently. In an additional study, the examination is extended to an almost global level. To achieve the intended standardization, over 1000 individuals (tadpoles) from 144 species have been examined. It can be shown that the common evolutionary history on a global scale influences morphology as strongly as the habitat. In addition, the influence of specialized nutrition and the climate is investigated.
Expectations play a central role in financial markets, yet investors often disagree about the economy’s future. Such disagreement has long been regarded as a potential driver of asset prices, but it remains uncertain whether it reflects mispricing or a priced source of risk. This study addresses the issue by constructing monthly disagreement indices from Consensus Economics forecasts across 24 OECD markets. Firm-level exposure to economic disagreement is estimated using return regressions. The results reveal pronounced cross-country heterogeneity. In developed markets, particularly the United States, greater exposure to disagreement consistently predicts lower future returns, supporting the mispricing hypothesis. In smaller markets, the evidence is mixed, with some cases indicating positive risk premia and others showing no significant effect. Overall, the findings provide new international evidence that the pricing of forecast disagreement is context-dependent, shaped by market structure and institutional depth.
This thesis examines how Europe sustains its leadership and competitiveness as a global center for foreign direct investment (FDI) and trade between 1991 and 2023. While EU membership historically functioned as the dominant determinant of inward FDI and trade integration, its relative influence has declined as new structural factors, based on trade dynamics and export-platform strategies, have emerged, together with the growing presence of Asian, especially Chinese, investors establishing production hubs in Central and Eastern Europe to serve the wider EU market. Lower trade costs within Europe have reinforced this shift, leading EU investors to focus on vertical FDI, while non-EU investors to adopt export-platform FDI patterns. Chinese investment has moved from infrastructure-focused projects to strategic-sector FDI, highlighting Europe’s exposure to evolving global industrial and geopolitical dynamics.
Chapter 2 examines how traditional determinants of FDI, including EU membership, interact with emerging drivers, such as trade interdependence, export-platform strategies, and Asian influence, to shape investment patterns in Europe. It employs a gravity-based empirical framework augmented with newly developed indicators, comprising the Bilateral Trade Interdependence Index, the Export-Platform Indicator, and Belt and Road Initiative (BRI) participation, together with a functional integration approach, covering over 95% of European countries and their global partners from 2010 to 2023. The findings indicate that trade dependency with non-EU partners grew most rapidly, increasing by 55% between 2011 and 2023. Stronger bilateral trade interdependence is found to significantly predict higher FDI inflows. The BRI analysis and functional classification indicate a shift from infrastructure-focused Chinese investment to strategic sectors, including electric vehicles and semiconductors. Since 2018, export-platform strategies have expanded from Europe’s core economies into Central and Eastern Europe, forming emerging production hubs, and have subsequently moved toward the Western Balkans and Turkey, likely reflecting evolving EU regulations and broader supply-chain realignments.
Chapter 3 expands the FDI analysis to cover a longer timeframe, from 1991 to 2017, focusing on the period when EU membership exerted a strong influence on FDI in Europe, transforming member countries from primarily cost-attractive destinations into global investment centers. Using an augmented gravity model covering 39 host and origin countries, the analysis finds that EU membership increased FDI inflows by 23%, with investments from core EU members expanding into new EU member states, while FDI from non-EU countries decreased. At the same time, EU membership may also be driven by trade, and EEA participation reflects non-FDI motivations. The chapter also highlights that EU accession strengthens both market-seeking (horizontal) and efficiency-seeking (vertical) FDI motives and applies methods to address negative and zero FDI values issues, ensuring robust estimation. The inclusion of lagged and lead variables shows that the EU integration process is phased over time, affecting FDI inflows with lags of up to 10–15 years after accession.
Chapter 4 expands the range of FDI determinants by deriving trade cost indices as a proxy for connectivity and extending the geographic scope of the analysis. In addition to EU members, the sample includes the Western Balkans, Turkey, and new EU candidates and applicants (Moldova, Ukraine, and Georgia) over the period 2000 to 2020, covering approximately 80% of European FDI flows. Trade costs are calculated for each country in the sample with its trade partners, not only within and between European subregions but also with non-EU partners such as China, and are combined with measures of FDI restrictiveness. The results show that China remains among the EU’s top three trading partners in goods and that trade costs significantly influence FDI inflows in Europe. The analysis also highlights that declining trade costs between European countries have reduced market-seeking (horizontal) FDI, while non-European investors, especially China, increasingly pursue export-platform FDI to serve third-country markets. A sharp reduction in trade costs between the Western Balkans and the EU (-45%) and a smaller decline with China (-35%) illustrates how regional integration reduces the need for local horizontal FDI while reinforcing Europe’s role as a hub for global production.
Chapter 5 shows that despite concerns about increasing outside influence, developed European countries remain the dominant source of FDI in the region. The chapter focuses on China’s role, examining FDI patterns across advanced EU members, new member states, and Western Balkan economies between 2000 and 2019, while distinguishing the effects of EU integration and BRI participation on FDI. Chinese influence has expanded primarily through the Belt and Road Initiative, particularly in accession and neighboring countries. Although BRI participation does not significantly increase FDI on its own, reflecting the dominant part of loan-financed infrastructure rather than private investment, it has strengthened physical and digital connectivity, laying the groundwork for future, longer-term FDI. The analysis also shows that intra-EU trade costs declined significantly after the 2004 and 2007 enlargements, while trade costs between the Western Balkans and China have fallen steadily since the launch of the BRI in 2013. As a result, Chinese influence is more pronounced in new EU member states and Western Balkan economies than in Western Europe. Over time, enhanced connectivity and supply-chain integration may support more diversified FDI inflows.
Towards Seamless Integration: Exploring Cross-Reality for Extending Physical Office Workspaces
(2026)
Immersive systems, like Augmented and Virtual Reality, offer new paradigms fordigital interaction, but confining users to a single reality often presents drawbacksfor complex tasks. Cross-Reality systems, which integrate multiple realities into asingle experience, have significant potential to enhance existing professional workflows by combining the unique strengths of physical and virtual environments. Thisdissertation investigates how Cross-Reality can enhance professional workflows byusing the traditional office as a primary use case, focusing on the central question:How can CR enhance existing workflows in physical settings by extendingthe physical environment with virtual content and environments?To address this, the dissertation presents a body of empirical work structuredaround isolating and investigating one core design challenge for each of the threeprimary types of Cross-Reality systems. The work first addresses transitionalCross-Reality systems, which allow users to switch between different realities, byexamining how to design effective transitions. It demonstrates that in task-drivenscenarios, users prioritize efficient transitions that minimize cognitive disruptionover more elaborate or interactive ones. Next, the dissertation tackles the fundamental problem of unwanted occlusion in Augmented Virtuality, a form of substitutional Cross-Reality systems, which integrate objects from one reality intoanother. It introduces and evaluates technical strategies to ensure physical toolsremain accessible within virtual spaces, revealing a critical trade-off between theefficacy of these solutions and user experience factors like cybersickness. Finally,the research explores multi-user Cross-Reality systems that enable collaborationbetween multiple users who may be experiencing different degrees of virtualitysimultaneously, and the complexities of enabling collaboration across multiplestages, underscoring the unique challenges of supporting shared awareness andmanaging asymmetric roles.These findings are grounded by a detailed analysis of the underlying hardware, which highlights how technical and perceptual issues inherent to VideoSee-Through and Optical See-Through Head-Mounted Displays directly impactthe feasibility and design of Cross-Reality systems. The overarching contributionof this dissertation is to provide a set of empirically-grounded design principlesfor applying Cross-Reality in productivity-focused environments. By shifting thedesign focus from entertainment to pragmatic qualities, this work offers valuableinsights into creating Cross-Reality systems that genuinely enhance workflows, prioritizing efficiency, usability, and seamless interaction while navigating technical
This thesis presents four contributions in the domains of schema/ontology alignment and query processing. First, we present a novel alignment approach, denoted as FiLiPo (Finding Linkage Points), to align the schema of RDF knowledge bases with the response schema of RESTful Web APIs. FiLiPo only requires knowledge about a knowledge base (e.g., class names) but no prior knowledge about the
Web APIs’ data structure. It uses fifteen different string similarity metrics to find an alignment between the schema of a knowledge base and that of aWeb API.
Next, a benchmark system named ETARA (Evaluation Toolkit for API and RDF Alignment) is introduced that was created with the goal to simulate RESTful Web APIs and is able to cover all important characteristics of Web APIs, i.e., latency, timeouts, rate limits and, furthermore, provides configurable response structures (e.g., JSON or XML). Additionally, it was designed to support researchers during
the development of alignment systems.
Afterward, the alignments determined by FiLiPo are used to create a hybrid and federated query processor named TunA (Tunable Query Optimizer forWeb APIs and User Preferences), which allows SPARQL queries combining knowledge bases and RESTful Web APIs and is tunable towards user preferences, i.e., coverage, reliability and execution time. The primary goal of TunA is to return a query result that satisfies the user’s preferences in terms of data quality, even when using unreliable data sources by performing a majority vote over multiple sources.
Lastly, we present a federated query processor, denoted as ORAQL (Overlap and Reliability Aware Query Processing Layer), which uses overlap information to reduce the number of selected sources that are available in a federation. The goal is to reduce redundant data and, hence, improve the query execution speed. Therefore, ORAQL uses a profile feature that provides information about the overlap between all data sources of a federation. Furthermore, we extend the quality estimation of TunA to cover Triple Pattern Fragment interfaces to ensure a user-provided reliability goal.
This thesis serves as proof of concept for the tensile strength simulation-based nonwoven material design. Objective is the adjustment of the parameters of an underlying production process with regard to a desired tensile strength behavior (optimization). As an example, we focus on the nonwoven airlay production and consider a thermobonding procedure for the consolidation of the nonwoven fabrics.
To be able to map production parameters to the associated tensile strength behavior, we present a model-simulation framework composed of a model for the nonwoven fiber structure generation and a model for the nonwovens’ mechanical behavior under vertical load. The model for the fiber structure generation replicates the stochastic fiber lay-down of the airlay production and results in a random three-dimensional fiber web. This web is consolidated using a virtual bonding procedure that mimics the thermobonding of the nonwoven material. The topology of the resulting adhered fiber structure can be described by a graph, which serves as basis for the subsequent tensile strength simulation. The model used for this purpose describes the mechanical behavior of the material at fiber network level. Therefore, the considered fiber structure sample is interpreted as truss and the fiber connections are equipped with a nonlinear material law, which allows to describe the elastic phase of the nonwovens’ tensile strength behavior. The existence and uniqueness of a solution to the model as well as its numerical treatment are discussed. Moreover, we present data reduction strategies that enable more efficient simulations by removing fiber structure parts that do not contribute to the tensile strength behavior.
As it becomes evident from the numerical experiments, a single tensile strength simulation for a production-like virtual sample is already computational demanding. Costs accumulate further, since Monte-Carlo simulations are required to account for the randomness in the fiber structure generation. Thus, direct simulations provide an infeasible basis for the nonwoven material design. This motivates the use of a predictive surrogate for optimization. Therefore, we consider regression-based approaches at different levels of information within the simulation framework. It turns out that the coupling of a polynomial model, for the fiber structure feature inference, with a linear one, for the stress-strain curve inference, yields accurate predictions. Once trained, the regression models allow for efficient evaluations and thus represent a suitable surrogate for the nonwoven material design. In this context, we discuss two exemplary problems of interest for the application: First, a tracking-type problem that aims to find the production parameters that result in a desired tensile strength behavior, expressed in terms of stress-strain curves. Second, an in-corridor maximization problem, which aims to identify the production parameters that maximize the probability of ending up in a specified stress-strain corridor.
Price indices play a vital role in economic measurement as they reflect price levels
and measure price fluctuations. Price level measures are used with macroeconomic
indicators to express them in real terms. These measures are also used to index wages,
rents, and pensions. Furthermore, they are used as a reference for monetary policy
conducted by central banks. Therefore, the provision of accurate price indices is one
of the most important goals of National Statistical Institutes (NSIs), and numerous
studies have been devoted to this goal.
This cumulative dissertation also contributes to this goal. It contains four chapters,
each of which represents a separate research. The first two studies are devoted to
the treatment of seasonal products by using different price index methods. The first
research is co-authored with Ken van Loon. The third research is dedicated to finding
the most accurate method to make price predictions for missing products. The fourth
research is focused on the treatment of products by using different price index methods
when products’ quality characteristics are available.
The article discusses “SimStab” [Simulator of Stability], a poetic performance by a young Russian poet, Rostislav Amelin, as an effective hybrid of the innovative poetry, video game, and the cyberpunk genre models. The interaction of these components produces strong, yet not necessarily obvious political over-tones, testing the limits of the audience’s (or readers’, or players’) agency. Like many other cyberpunk texts, “SimStab” explores the conflict between the desire to resist colonization by the pervasive powers dominating contemporary society, and the absolute necessity of willingly colonizing your own body and subjectivity with the products of these powers. Both the poem, game and their shared text embody spaces of utopia reliant on repressed sites of formless abjection, which paradoxically become a source of anarchic freedom. Thus, in “SimStab” the ludic algorithmic with its procedural rhetoric (Ian Bogost) creates spaces of formlessness which repeats the liberatory promise of cyberpunk literature.
The Orbita multimedia and poetry collective, based in Riga, Latvia, has succeeded in making poetry written in Russian an integral part of the Latvian cultural and literary scene, despite the burden borne by Russian language and culture in this society as a result of still unsettled and contested histories of Russian and Soviet imperial domination and cultural imperialism. The article explains this achievement as resulting from the Orbita collective’s practices of “performative translation,” which make translation a highly visible and central element of various forms of artistic activity, including multimedia installations, book publishing, video poetry, public performance, proper, and more. In traditional cultural configurations, translation is thought to transfer the essential features or the spirit of a text from one literary language to another in a manner that makes possible the translation’s readers’ sense of unmediated contact with the original. Such a conception of translation supports the monolingual paradigm – the cultural ideology of separate and distinct national languages – and the political actualities to which it corresponds. Orbita’s practices of performative translation, in contrast, create a multilingual heterotopia in which the actuality of translation as mediation is rendered visible, the boundedness and distinctiveness of national literary languages is undermined, and the social necessity and ubiquity of acts of translation is brought to the fore.