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Income composition can have a significant impact on workers’ well-being, productivity, and career paths. Wages often include a variety of components, such as unconditional bonuses, profit-sharing payments, and incentives based on the individual performance of employees. Each of these may influence employee labour outcomes differently and the worker composition may matter for managers when designing the salary package. Simultaneously, workers’ employment choices and well-being are influenced by income outside the job, such as inheritances and lottery winnings, as well as by external factors like technological change. This dissertation includes five empirical studies that investigate these issues, yielding new insights on the role of monetary gifts, financial incentives, labour market institutions, and technology disruptions in affecting employees’ labour and well-being outcomes.
The role of implicit motives for affective, cognitive and behavioral processes has been a focal part of psychological research for decades. Yet, the majority of research in this field has been concentrated on processes involving implicit motives in adulthood. The systematic investigation of developmental correlates of implicit motives remains largely uncharted. The studies cumulated in this thesis aim to add to the sparse research on implicit motives in childhood and adolescence. Specifically, the development of the implicit power motive in the transition of middle to late childhood as a function of parenting behavior (Chapter 4), the predictive value of the implicit achievement motive for objective swimming performance in children and adolescents (Chapter 5) and the role of motive congruence for successful goal realization in adolescent samples across two cultures (Chapter 6) were investigated. Results of Study 1 (Chapter 4) indicate a negative longitudinal association of authoritarian parenting with the implicit power motive in children that is moderated by children’s perception of psychologically controlling parenting. Study 2 (Chapter 5) extends existing research on the assumed positive association of the implicit achievement motive and sports performance and demonstrates the moderating role of competitive anxiety on this association. Finally, Study 3 (Chapter 6) illustrates a moderating effect of implicit motives on the association of goal commitment and successful goal realization in German and Zambian adolescents, however, this effect was only observed in the domain of power motivation. Findings from all three studies are discussed in the context of the significance of implicit motives for psychological research.
Many developed countries, including Germany, face a steady rise in the share of
individuals obtaining higher education. While rising education itself bears a series
of advantages as extensively studied in previous literature, it is also conceptually
linked to a higher likelihood of working in an occupation that does not match
one’s formal qualifications. Previous studies have predominantly evaluated
how demographic or job‐related aspects correlate with the likelihood of being
educationally ﴾mis﴿matched. However, they have largely ignored institutional
facets of the educational system or industrial organization. Moreover, little is
known about how private wealth affects educational mismatch or whether job
satisfaction is homogenously affected among individuals once such a mismatch
occurs. The five projects collected in this thesis aim to answer these open
questions in the literature for Germany, using data from the Socio‐Economic Panel
and employing different time intervals between 1984 and 2022.
Beginning with the educational system in early childhood, Chapter 2 evaluates
the impact of school‐starting age on the likelihood of over‐ and undereducation.
It exploits the exogenous variation in school‐entry rules across federal states
and years in Germany with regression discontinuity designs. The results report
a negative impact of school‐starting age on the likelihood of undereducation,
but no systematic relationship with overeducation.
Subsequently, Chapter 3 explores the variation in education costs by leveraging
the quasi‐experimental setting induced by the time‐limited introduction of tuition
fees in several German federal states between 2006 and 2014. The increase
in education costs among treated graduates results in a significantly higher
likelihood of overeducation, which endures even several years post‐graduation.
Chapter 4 focuses on the industrial relations system and examines the
correlation between trade union membership and the likelihood and extent of
educational ﴾mis﴿match. The results reveal that trade union members report
significantly less overeducation at both the intensive and extensive margin
and also a higher likelihood of being matched compared to non‐members. Furthermore, the heterogeneity analysis provides evidence that this correlation
is driven by improved bargaining power instead of informational advantages.
Chapter 5 focuses on private wealth as a determinant of educational mismatch
by investigating the impact of a wealth shock through inheritances, lottery
winnings or gifts on the likelihood of over‐ and undereducation. Due to
the diminishing marginal returns of wages with increasing windfall gains the
likelihood of undereducation is expected to decrease, while that of overeducation
is expected to increase. Empirically, these suppositions are supported for
overeducation, as its likelihood increases significantly after the windfall gain.
Further analyses reveal that this effect is driven by individuals switching
occupations while increasing their leisure time, and it materializes only for
medium to large windfall gains.
Contrary to the previous chapters, Chapter 6 focuses on educational mismatch,
more precisely on overeducation, as the independent variable. In particular, it
investigates the correlation between overeducation and job satisfaction. The
results align with the previously established negative correlation for private sector
employees exclusively. In contrast, interaction and subsample analyses reveal a
positive correlation for public sector employees. This link is driven by individuals
with a high degree of altruistic motivation and family orientation.
This dissertation examines how individuals unlock their personal power by investigating individual differences in self-regulation, in particular, how situational conditions interact with the personality dispositions of action versus state orientation. Action-oriented individuals are well able to regulate their affective states and to bridge the intention–behavior gap, showing initiative, implementing demanding intentions, and resisting temptations. State-oriented individuals, by contrast, often struggle to regulate affect and experience difficulties enacting intentions, especially under demanding conditions, tending to hesitate and ruminate. While extensive research has highlighted the advantages of action orientation across various domains such as education and health, this thesis challenges the prevailing one-sided perspective that presents action orientation as inherently superior and frames state orientation negatively. Drawing on Personality Systems Interactions theory, the dissertation adopts a dynamic view that understands these dispositions as context-sensitive rather than fixed. The central assumption is that action and state orientation each require different kinds of situational conditions to fully unlock their potential. Across six empirical studies (overall N = 1,067) using a multimethod approach that combines experimental and survey-based research in diverse populations and contextual settings, this dissertation examines (1) action and state orientation as distinct dispositions, (2) their dynamic interaction with situational factors, and (3) ways to support each in mobilizing personal power. Overall, the findings show that each disposition offers unique advantages - they simply require different situational conditions for their potential to unfold.
Measuring the economic activity of a country requires high-quality data of businesses. In the case of Germany, this is not only required at national level, but also at federal state level and for different economic sectors. Important sources for high-quality business data are the business register and, among others, also 14 business surveys which are conducted by the Federal Statistical Office of Germany. However, the quality requirements of the Federal Statistical Office are in contrast to the interests of the businesses themselves. For them, answering to a survey's questionnaire is an additional cost factor, also known as response burden. A high response burden should be avoided, since it can have a negative impact on the quality of the businesses' responses to the surveys. Therefore, sample coordination can be used as a method to control the distribution of response burden while securing high-quality data.
When applying already existing business survey coordination systems, developed by different statistical institutes, legal and administrative standards of German official statistics have to be taken into account. These standards consider different sampling fractions, rotation fractions, periodicity, and stratification of the aforementioned 14 business surveys. Therefore, the aim of this doctoral thesis is to check the existing business survey coordination systems for their applicability in the context of German official statistics and, if necessary, to modify them accordingly. These modifications include the introduction of individual burden indicators which aim to take the individual perception of response burden into account.
For this purpose, several synthetic data sets have been created to test the application of the modified versions of the different business survey coordination systems through Monte Carlo simulation studies. These data sets include a large panel data set, reflecting the landscape of businesses in Rhineland-Palatinate and three smaller, synthetic data sets. The latter have been created with the help of the R package BuSuCo which has been developed within the scope of this thesis. The above mentioned simulation studies are evaluated based on different measures for estimation quality as well as for the concentration and distribution of response burden.
Bilevel problems are optimization problems for which parts of the variables
are constrained to be an optimal solution to another nested optimization
problem. This structure renders bilevel problems particularly well-suited for
modeling hierarchical decision-making processes. They are widely applicable
in areas such as energy markets, transportation systems, security planning,
and pricing. However, the hierarchical nature of these problems also makes
them inherently challenging to solve, both in theory and in practice.
In this thesis, we study different nonlinear problem settings for the
nested optimization problem. First, we focus on nonlinear but convex bilevel
problems with purely integer variables. We propose a solution algorithm that
uses a branch-and-cut framework with tailored cutting planes. We prove
correctness and finite termination of the method under suitable assumptions
and put it into context of existing literature. Moreover, we provide an
extensive numerical study to showcase the applicability of our method and
we compare it to the state-of-the-art approach for a less general setting on
suitable instances from the literature. Furthermore, we discuss challenges that
arise when we try to generalize our approach to the mixed-integer setting.
Next, we study mixed-integer bilevel problems for which the nested
problem has a nonconvex and quadratic objective function, linear constraints,
and continuous variables. We state and prove a complexity-theoretical hardness result for this
problem class and develop a lower and upper bounding scheme to solve
these problems. We prove correctness and finite termination of the proposed
method under suitable assumptions and test its applicability in a numerical
study.
Finally, we consider bilevel problems with continuous variables, where
the nested problem has a convex-quadratic objective function and linear
constraints. We reformulate them as single-level optimization problems using
necessary and sufficient optimality conditions for the nested problem. Then,
we explore the family of so-called P-split reformulations for this single-level
problem and test their applicability in a preliminary numerical study.
In Vielfalt geeint? Europäische Identitätskonstruktionen im bundesdeutschen Diskurs seit 1990
(2025)
Die Arbeit untersucht den bundesdeutschen Diskurs zur europäischen Integration seit 1990 aus diskurslinguistischer Perspektive und versteht ihn als Aushandlungsraum europäischer Identitätskonstruktionen. Ausgangspunkt ist die Annahme, dass institutionelle Vertiefung und geografische Erweiterung der EU nicht allein als verrechtlichte Integrationsschritte zu begreifen sind, sondern stets auch identitätspolitische Dimensionen tragen. Ziel der Studie ist es, die sprachliche Konstituierung der EU als identitätspolitisches Referenzsystem sichtbar zu machen und damit eine diskurslinguistische Ergänzung zur interdisziplinären Integrationsforschung zu leisten. Auf Grundlage eines diachronen Korpus, das zentrale integrationspolitische Etappen und Krisenphasen umfasst, wird ein Mixed-Methods-Ansatz entwickelt, der korpusgeleitete Verfahren mit der hermeneutischen Annotation diskurslinguistischer Kategorien verbindet. Analysiert werden nicht nur lexikalisch-semantische Repräsentationen Europas, sondern vor allem diskursive Grundfiguren wie Einheit, Vielfalt, Eigenes und Fremdes sowie deren Verbindung zu politischen Sinnzuschreibungen. Die Ergebnisse zeigen, in welchem Maße sich im deutschen Diskurs ein stabiler identitätspolitischer Bezugspunkt zur EU herausgebildet hat, wie sich normative Leitbilder und funktionale Rationalitäten überlagern und wie europäische Integration sprachlich zwischen symbolischer Aufladung und strategischer Instrumentalisierung verhandelt wird.
Extracellular enzymes in microbial communities play a central role in nutrient cycling and the degradation of (pollutant) substances in various natural and anthropogenic systems. Bound in aquatic biofilms, sludge aggregates, or even unbound at their interfaces, they are of great importance for both the environment and human health. In particular, in wastewater treatment plants and inland waters, hydrolytic activities influence the wide-reaching efficiency of nutrient removal and self-purification, thus contributing significantly to overall water quality.
The main goal of this dissertation project was to investigate the factors that influence enzymatic activity and the health of microbial communities in activated sludge and river systems, particularly in relation to anthropogenic influences and natural environmental conditions. The aim was to contribute to a better understanding of the sensitivity of our freshwater ecosystems and to support the long-term preservation of water quality and ecological stability. The development and optimization of appropriate methods, as well as their testing and applicability, were the focal points.
For this purpose, a fluorometric microplate assay was developed and adapted to determine both extracellular enzyme activities (EEAs) in activated sludge samples and in intact biofilms. Its suitability for field studies was subsequently tested. Inhibition and activity of selected hydrolases under different conditions were investigated to better understand the mechanisms and potential environmental risks posed by anthropogenic influences and seasonal fluctuations of hydrochemical and climatic parameters.
The first phase of the doctoral thesis involved studies on the inhibition of alkaline phosphatase in activated sludge by oxyanions. Using the fluorometric microplate assay, the inhibitory effect was sensitively detected over a pH range of 7.0 to 8.5. IC50- and IC20-concentrations were calculated from modeled dose-response functions. It was found that vanadate and tungstate caused strong inhibitory effects, while molybdate moderately inhibited the enzyme. An increasing pH led to a reduction in the inhibitory effect of tungstate and molybdate. The inhibition effects of vanadate were not significantly affected by the pH. In municipal wastewater, the concentrations of such metal ions are usually low, but industrial wastewater may have pollutant loads that can significantly impact the removal of phosphorus-containing compounds, and thus the efficiency of treatment plants.
In the second phase, an attempt was made to further adapt the developed methodology to investigate EEA and kinetics in intact freshwater biofilms. Four different types of bead materials (lava, glass, sintered quartz, and ceramics) fitting into a 96-well microplate were tested as carriers for biofilms on both the laboratory and field scale. The analysis included a total of seven hydrolases as representatives of key nutrient cycles such as phosphorus, carbon, and nitrogen: phosphatases, glucosidases, peptidases (two different types), and sulfatase. Experiments with increasing substrate concentrations led to classical kinetic profiles according to the Michaelis-Menten mechanism. This allowed for the prediction of the biofilm enzymes’ response to different substrate concentrations. Parameters such as Vmax and Km could be derived from the modeled curves.
Ceramic beads are particularly suitable for long-term studies due to their high stability, while sintered quartz beads should be preferred for the use in stagnant media (material loss under turbulent conditions). Lava and glass beads, on the other and, proved suboptimal for uniform biofilm development due to their surface properties. The potential use of this fast and sensitive test for ecotoxicological or even human-toxicological studies was demonstrated by the effects of caffeine on the activity of PDE. The result of this part of the research represents a powerful tool for assessing environmental pollution and monitoring water quality.
The high application potential was clearly highlighted in the final phase of the project. The goal here was to deepen the understanding of interactions between seasonal factors, anthropogenic influences, and biofilm processes in rivers by investigating EEA and biofilm parameters such as biomass and relating them to hydrochemical and climatic factors. Ceramic beads were exposed both upstream and downstream of a wastewater treatment plant discharge and sampled over a period of seven months. EEAs and biomass varied depending on the season and location, with higher microbial activity observed upstream in winter. Winter conditions led to the dilution of most nutrients as well as in an increse of dissolved oxygen. Nutrient concentrations analyzed downstream were significantly higher in the summer. Accumulation of nutrient or pollutants during the summer months cannot be excluded, which may have led to a general reduction in enzyme activities.
Potential causes could be inhibitory effects on the enzymes, or a reduced enzyme activity due to a sufficiently high nutrient supply. In general, the sampling site upstream showed a more pronounced seasonal dynamics, with a significant proportion of the variance in biological parameters (activity and biomass) attributable to seasonal factors. A secondary component, likely reflecting the impact of the treatment plant discharge, explained another portion of the data variance. Regardless of the season, high correlations between biological parameters were observed upstream, while downstream the data were more decorrelated. This could be because the biofilms, under chronic stress, respond less dynamically to seasonal fluctuations.
This dissertation illustrates that in addition to anthropogenic stress factors, seasonal fluctuations of hydrochemical and climatic parameters should also be considered in "stress downstream the pipe" studies. The selected methods are recommended for explaining and considering the data variance, as they highlight the complex interplay between microbial enzymatic activity, environmental factors, and pollutants in the activated sludge of wastewater treatment plants and also in aquatic systems. The novel bead assay could pave the way for the future standardization of effect-oriented studies on intact aquatic biofilms.
Perennial crops eliminate soil disturbance and reduce the amount of synthetic chemicals that are applied to the soil, improving soil biodiversity and food web structure. Additionally, perennial cropping is characterised by all year-round surface coverage which benefits soil biota in terms of habitat and food sources. Perennial intermediate wheatgrass (Thinopyrum intermedium, IWG) was domesticated and commercialised by The Land Institute in Kansas as Kernza® and serves as an example for these nature-based solutions. It develops an extensive root system that has a higher nutrient retention, possibly reducing nutrient runoff. It thereby follows a more resource-conservative strategy with improved belowground-oriented resource allocation in its root system. This may reduce the need for excessive fertiliser as the crop has a higher nitrogen efficiency, among other things.
IWG promoted the earthworm community and its diversity, more specifically, the occurrence of epigeic species (litter inhabitants), since those species benefit from the increased soil coverage and elimination of disturbances in the soil. As IWG creates a dense and extensive root system, as shown by the increased occurrence of root-feeding nematodes, endogeic species (horizontal burrowers) are supported through the provision of a reliable food source. IWG was characterised as a mostly undisturbed system with a highly structured food web through nematode analysis, as expressed through the promotion of structure indicators, for example, that are sensitive to disturbances in the soil and are therefore supported under no-till management. The root microbiome is continuously being shaped by the host as the crop regrows from the roots each vegetation period. This creates a symbiotic relationship and a beneficial feedback loop for the crop. Resultantly, the root-endophytic microbiome under IWG had a higher network complexity, connectivity and stability compared to annual wheat. The regrowth from the roots for IWG requires increased nutrient and energy storage, which was indicated by increased starch values. Correspondingly, the longer residence time of the roots in the soil resulted in higher lignin values. Furthermore, the decomposition pathway was dominated by fungivorous nematodes which may correspond to stimulated nutrient cycling and a heterogeneous resource environment, as seen for low input systems.
Overall, perennial wheat cultivation improved soil biodiversity already after an establishment of 3-6 years. As those benefits were present for all three countries, the varying soil and climate conditions do not seem to interfere with the positive effect of perennial wheat on the soil ecosystem, demonstrating a wide transferability and adaptability of the crop onto other study sites as well. Enhanced complexity and connectivity of the food web in comparison to annual wheat may indicate a resistance against abiotic stress, suggesting IWG cultivation as a viable option for a sustainable and resilient agriculture. The improvement in nutrient cycling and the resource-efficient cultivation strategy for IWG could enable cultivation on marginal land where annual crop cultivation is not possible as the soils are susceptible to erosion and nutrient runoff. This opens up new possibilities for agricultural cultivation on previously unused land, thus contributing to food security in the future.
The application of machine learning and deep learning methods to hydrological modelling has advanced significantly in recent years, offering alternatives to traditional conceptual and physically based approaches. Within the numerous algorithms, long short-term memory (LSTM) networks have proven themselves particularly useful for the task of streamflow modelling. This thesis provides a collection of publications that investigate the capabilities, limitations and interpretability of LSTM for the purpose of streamflow modelling and climate change impact assessment within the lowland Ems catchment in Northwest Germany.
Within a comparative performance evaluation, LSTM and its predecessor, the recurrent neural network, demonstrate superior accuracy compared to the conceptual HBV model across various statistical performance metrics. However, a decline in performance was observed during low-flow conditions in certain sub-catchments. The evaluation of the flow duration curve revealed that the ML models more effectively capture the water balance, while HBV better represents streamflow dynamics.
To enhance the interpretability of LSTM, six explainable artificial intelligence techniques were applied. These methods consistently identified seasonal patterns in the temporal relevance of hydroclimatic input data. In combination with an observed correlation between the internal LSTM states and catchment-scale soil moisture dynamics, the findings suggest that LSTM models are capable of implicitly learning the relevant hydrological processes.
Following, the capabilities of LSTM to model climate change impact scenarios, particularly when they extend beyond historically observed climate conditions, are addressed. An ensemble of climate change projections is provided as hydroclimatic input to evaluate the performance of LSTMs and conceptual models. While all models reveal heterogeneous alterations in streamflow under future climate conditions, significant differences emerge based on the model type. Results provide evidence that LSTMs, in combination with the temperature-based Haude formula for estimating potential evaporation, work inadequately under altered climatic regimes, raising concerns about their applicability in long-term projections. The study also indicates the potential need to incorporate physical constraints into LSTM architectures to ensure model robustness and hydrological plausibility beyond the historical training range.
Collectively, this thesis contributes important insights into the applicability and interpretability of LSTM models in streamflow modelling. Despite the presence of a physically realistic representation of soil moisture dynamics of the Ems catchment, no robust change signals for streamflow under climate change can be derived. Those results underscore the potential of LSTM model approaches for accurate streamflow simulation, however, they require us to always critically question LSTM results, particularly when they are applied outside the training range.
Modellierung von o-PO4- Einträgen in saarländische Oberflächenwasserkörper im Trockenwetterfall
(2025)
Die Verfügbarkeit von ortho-Phosphat (o-PO₄) trägt wesentlich zur Eutrophierung von Fließgewässern bei und gefährdet damit das Erreichen des „guten ökologischen Zustands“ gemäß der EU-Wasserrahmenrichtlinie. Da die kommunalen Kläranlagen zentrale Eintragsquellen darstellen, gewinnt die Reduktion von o-PO₄ an dieser Stelle an Bedeutung. Neben der chemischen Phosphorelimination bietet insbesondere die vierte Reinigungsstufe, primär zur Entfernung von Mikroschadstoffen konzipiert, einen Synergieeffekt mit potenziellen Phosphorentfernungsraten von bis zu 85 %.
Zur Bewertung des Einflusses einer solchen Reinigungsstufe wurde ein Modell für ausgewählte saarländische Oberflächenwasserkörper (OWK) entwickelt, das den Trockenwetterfall als eutrophierungsrelevantes Szenario abbildet. Ein zentraler Bestandteil ist ein neu erarbeiteter Retentionsansatz, der biochemische und physikalische Prozesse wie Adsorption, Sedimentation und biologische Assimilation berücksichtigt. Auf Basis der Differenz zwischen emissionsseitig bilanziertem und gemessenem o-PO₄-Gehalt wurden für jeden OWK Verminderungsraten je Fließmeter abgeleitet und schließlich eine Gleichung zur Abschätzung der Retention in Abhängigkeit der Einzugsgebietsgröße formuliert. Die Validierung zeigt hinreichende Modellgenauigkeit, wenngleich negative Frachtdifferenzen in einigen Gewässern auf zusätzliche, nicht eindeutig quantifizierbare Einträge – etwa aus Landwirtschaft oder Kanalverlusten – hindeuten.
Die Szenarienanalyse belegt, dass eine vierte Reinigungsstufe grundsätzlich zur Reduktion von o-PO₄ an den Messstellen beiträgt. Eine Unterschreitung des geltenden Orientierungswertes wird jedoch nur erreicht, wenn sämtliche Kläranlagen eines OWK nachgerüstet werden – und auch dann nur in einigen Fällen. Damit stellt die vierte Reinigungsstufe allein keine ausreichende Alternative zu den Maßnahmen des 3. Bewirtschaftungsplans des Saarlandes dar, kann jedoch als ergänzende Strategie zur Verringerung der Phosphoreinträge dienen.
Present-day air quality is known through dense monitoring and extensive pollu-
tion control mechanisms. In contrast, knowledge of historical pollution,
particularly before the industrial revolution, is accessible only through occasional
reports of singular local events and through natural archives such as ice or
sediment cores that record global-scale pollution. However, the regular local to
regional pollution that most affects human life is hardly known. Historical
sciences have argued both for and against significant air pollution in and around
historic cities and manufacturing sites. For the Roman era, it has been
hypothesized that air quality played a role in several patterns of action of the period.
However, to the author's knowledge, there are no quantitative studies of
Roman emissions. Using the results of modern experimental archaeology, this
study attempts to quantify the emissions from Roman pottery kilns and their
impact on surrounding human settlements. It is shown that although the
pollution did not reach today's limits, it must have approached levels known to cause
adverse health effects. A series of additional test simulations have been
conducted to determine how these first results might be improved in the future.
Spatial microsimulation is an important tool for integrating geographical information into the evaluation of public policies and the analysis of social phenomena in urban regions. These models simulate the behavior and interaction between units of the region, such as individuals, households or firms, under specific conditions that may or not involve projections over time. This requires a representative base data set for their respective units.
In this thesis, we focus on the geo-referencing step of the population in the construction of this data set, where we define the location of the individuals so that the allocation obtained is representative in relation to the population of the region. To do this, we consider the assignment of households to dwellings with specific coordinates by solving a maximum weight matching problem where side constraints are included so that the allocation obtained satisfies statistical structures intrinsic to the considered region.
The model of this problem represents each feasible assignment of household to dwelling as a binary variable, which results in billions of variables for medium-sized municipalities such as the city of Trier, Germany. Therefore, standard solvers for mixed-integer linear optimization are not able to solve it due to their high time and memory consumption. Hence, we develop two approaches capable of producing high-quality allocations using a reasonable amount of computational resources, one based on specific decomposition algorithms, and the other characterized by the application of an approximation algorithm in the framework of Lagrangian relaxation of the side constraints.
We theoretically explore the allocations obtained by both approaches and perform an extensive computational study using synthetic data sets and real-world data sets associated with the city of Trier. The results show that the developed methods are able to obtain near-optimal solutions using significantly less memory and time than the solver Gurobi, which enables them to tackle significantly larger instances, with approximately 100 000 households and dwellings. Furthermore, the allocations obtained for the real-world data sets correspond to a realistic population distribution, which strengthens the practical applicability of our methods.
Dèi e Zangrèi: La lingua ferita, l'identità negata. Gli Elleni di Calabria e i Lombardi di Sicilia
(2025)
Nel libro Dèi e Zangrèi il professor Pasquale Casile scandaglia con mirabile precisione scientifica e in tutta profondità gli abissi della memoria linguistica dei Greci di Calabria. Fornisce risposte valide ai quesiti: Chi sono gli Zangrèi? Sono gli ultimi Dionisiaci della storia e gli eredi diretti delle comunità orfico-pitagoriche della Magna Grecia? E perché vengono così chiamati anche i Catari di Sicilia?
Einige Forschungsergebnisse zeigen, dass emotionale Empfindungen kognitive Bereiche beeinflussen oder mit diesen im Zusammenhang stehen. Aufbauend auf den Ergebnissen wurden zwei Studien konzipiert. In Studie 1 wurde der Zusammenhang zwischen den Valenzen der dispositionalen emotionalen Empfindungen und der globalen Selbstbewertung des Gedächtnisses (Metagedächtnis) bei Lehramtsstudierenden (N = 218) untersucht. Die dispositionalen Empfindungen wurden mittels des deutschen Positive and Negativ Affect Schedule (PANAS) (Krohne, Egloff, Kohlmann & Tausch, 1996) und die globale Selbstbewertung des Gedächtnisses mit dem deutschen Squire Subjective Memory Questionnaire (SSMQ) (Wolf, 2017) erfasst. Angenommen wurde, dass die positive Valenz im Gegensatz zu der negativen Valenz im positiven Zusammenhang mit der höheren Gedächtniseinschätzung stehen. Die Ergebnisse bestätigen die Hypothesen. In Studie 2 wurde die aktuelle Valenz mittels des Open Affective Standardized Image Set (OASIS) (Kurdi, Lozano & Banaji, 2017) induziert, um Veränderungen des Metagedächtnisses und der tatsächlichen Gedächtnisleistung bei Lehramtsstudierenden (N = 44) zu untersuchen. Angenommen wurde, dass die positive Valenz positiv, die negative Valenz negativ und die neutrale Valenz nicht auf das Metagedächtnis und die Gedächtnisleistung wirkt. Weitere Zusammenhänge zwischen dem Metagedächtnis und der Gedächtnisleistung sowie der induzierten Valenz und der Gedächtnisleistung wurden angenommen. Die Messinstrumente aus Studie 1 blieben dieselben. Die Gedächtnisleistung wurde mittels eines sinnarmen Silbentests nach Ebbinghaus (1885) operationalisiert. Die Ergebnisse bestätigen die Hypothesen nicht. Die Emotionsinduktion hatte keinen Erfolg. Die Ergebnisse können damit nicht auf eine veränderte Valenz bezogen werden. Wie in Studie 1 zeigte sich ein Zusammenhang zwischen den dispositionalen Empfindungen und dem Metagedächtnis. Weitere explorative Ergebnisse, vor allem im Bezug auf das Geschlecht, wurden dargestellt. Die Ergebnisse sind bedeutsam für die Professionalisierung von Lehramtsstudierenden.
Three-Point Difference Schemes of High Order of Accuracy for Solving the Sturm-Liouville Problem
(2025)
The dissertation is devoted to the construction and justification of three-point difference schemes of high order of accuracy for solving the Sturm-Liouville problem. A new algorithmic realization of the exact three-point difference scheme on a non-uniform grid has been developed. We show that to compute the coefficients of the exact scheme in an arbitrary grid node, it is necessary to solve two auxiliary Cauchy problems for the system of three linear ordinary differential equations of the first order. The coefficient stability of the exact three-point difference scheme is proved. If the Cauchy problems are solved numerically using any one-step method, we obtain the truncated three-point difference scheme. The accuracy estimate of three-point difference schemes was obtained and the algorithm for finding their solution was developed.
We also developed a new algorithmic realization of the exact three-point difference scheme for the Sturm-Liouville problem with singularities at the ends of the interval. As in the case of the classical Sturm-Liouville problem, to find the coefficients of the exact three-point difference scheme, it is necessary to solve two auxiliary Cauchy problems for each grid node. The coefficient stability of the exact three-point difference scheme is proved. Since the Cauchy problems for the first and last grid nodes are singular, the Taylor series method has been developed to solve them. The accuracy estimate of truncated three-point difference schemes was obtained. To solve the difference scheme, the Newton's iterative method is used.
Numerical experiments are presented which confirm the efficiency of the proposed approach.
Diese Studie untersucht die aktuelle Situation auf dem Wohnungsmarkt und die Wohnungspolitik in Rheinland-Pfalz. Sie zeigt, dass in den Städten hohe Mieten und Immobilienpreise, geringe Wohnflächen und eine starke Mietbelastung insbesondere einkommensschwacher Haushalte dominieren. Etwas anders gelagert stellt sich die Lange in den ländlichen Regionen dar: Zwar spielt Eigentum hier eine größere Rolle und der Wohnungsmarkt ist insgesamt entspannter, jedoch schränkt der kleine Mietwohnungsmarkt die Möglichkeiten für Haushalte mit geringem Einkommen erheblich ein. Zudem breiten sich Preissteigerungen zunehmend aus den Städten in umliegende ländliche Räume aus, insbesondere im Umland von Mainz, entlang des Rheins und im Umfeld von Luxemburg.
Die in Rheinland-Pfalz angewandten wohnungspolitischen Instrumente – von Mietspiegel und Mietpreisbremse bis zur sozialen Wohnraumförderung – haben nur einen dämpfenden Effekt auf die Wohnungsmarktentwicklung, beheben aber nicht die strukturellen Ursachen der Wohnungsfrage. Insbesondere der Rückgriff auf private Investor:innen und zeitlich befristete Sozialbindungen erweisen sich als grundlegende Konstruktionsfehler. Für eine zukunftsfähige soziale Wohnungspolitik müssen Strukturen gefördert werden, die jenseits des Marktmechanismus agieren. Nur so kann eine verlässliche soziale Wohnraumversorgung umgesetzt werden.
Biodiversity is threatened by a wide range of anthropogenic activities. Monitoring offers critical insights into how and why biodiversity is changing, helping to identify effective measures for maintaining biodiversity and its ecosystem services. However, conventional biodiversity monitoring methods are labor-intensive, and standardized long-term monitoring series are scarce. DNA-based approaches like metabarcoding environmental DNA (eDNA) promise rapid, cost-efficient, and highly resolved community data. At the same time, scientists are looking for alternative data sources that can compensate for the lack of long-term monitoring data to study past biodiversity changes. This work explores the potential of the German Environmental Specimen Bank (ESB), a pollution monitoring archive, which appears particularly promising for retrospective biodiversity monitoring. Biota samples from different ecosystems across the country are collected and archived at an exceptional level of standardization. Sampling species act as natural eDNA samplers, accumulating genetic traces from surrounding organisms. The cryogenic storage at the ESB preserves any eDNA in the samples in its original state. In this thesis, Chapter I serves as an introductory chapter, outlining the general chances and challenges of metabarcoding for assessing biodiversity. Chapter II focuses on primer design and testing the utility of ESB sampling species like mussels and macroalgae for characterizing the surrounding community. Both chapters form the basis for Chapters III to V, which report the use of ESB time series to uncover sample-associated communities and the changes they undergo. Chapter III illustrates the value of these time series by revealing the invasion trajectory of an alien barnacle into German coastal waters and linking the process to climate change. Chapter IV forms the core of this thesis by presenting an expanded measurement of biodiversity change in ESB time series across different taxonomic groups and ecosystem types. Here, a gradual compositional change (turnover) is reported from bacterial, fungal, microeukaryotic, and metazoan communities tending to either spatial homogenization or differentiation. Observed trends are tested for significance using a dynamic model of community ecology based on the equilibrium theory of island biogeography. The model reveals significantly accelerated turnover rates across all taxonomic groups and ecosystems investigated, suggesting a common, anthropogenically induced driver of biodiversity change. Since these analyses most likely include DNA derived from dead as well as from living organisms, Chapter V aims to separate both groups by metabarcoding both DNA and less stable ribosomal RNA from mussel samples. Contrary to the hypothesis, RNA is detectable from both living endobionts and dietary taxa. However, it outcompetes DNA in detecting microeukaryotic biodiversity. In summary, this thesis demonstrates the outstanding potential of archived ESB samples for retrospective biodiversity monitoring, a resource that offers many further untapped opportunities for future biodiversity research at multiple scales.
In most textbooks optimal sample allocation is tailored to rather theoretical examples. However, in practice we often face large-scale surveys with conflicting objectives and many restrictions on the quality and cost at population and subpopulation levels. This multiobjectiveness results in a multitude of efficient sample allocations, each giving different weight to a single survey purpose. Additionally, since the input data to the allocation problem often relies on supplementary information derived from estimation, historical data, or expert knowledge, allocations might be inefficient when specified for sampling.
This doctoral thesis presents a framework for optimal allocation to standard sampling schemes that allows for specifying the tradeoff between different objectives and analyzing their sensitivity to other problem components, aiming to support a decision-maker in identifying an at-most preferred sample allocation. It dedicates a full chapter to each of the following core questions: 1) How to efficiently incorporate quality and cost constraints for large-scale surveys, say, for thousands of strata with hundreds of precision and cost constraints? 2) How to handle vector-valued objectives with their components addressing different, possibly conflicting survey purposes? 3) How to consider uncertainty in the input data?
The techniques presented can be used separately or in combination as a general problem-solving framework for constrained multivariate and multidomain, possibly uncertain, sample allocation. The main problem is formulated in a way that highlights the different components of optimal sample allocation and can be taken as a gateway to develop solution strategies to each of the questions above, while shifting the focus between different problem aspects. The first question is addressed through a conic quadratic reformulation, which can be efficiently solved for large problem instances using interior-point methods. Based on this the second question is tackled using a weighted Chebyshev minimization, which provides insight into the sensitivity of the problem and enables a stepwise procedure for considering nonlinear decision functionals. Lastly, uncertainty in the input data is addressed through regularization, chance constraints and robust problem formulations.
Building on Social Virtual Reality to Support Flexible Collaboration and Enrich Therapy Sessions
(2025)
Social virtual environments allow their users to meet and collaborate in a shared three-dimensional space, even when far apart from each other in the real world. Within these spaces, the appearance and interaction capabilities of both users and environments can be adapted and changed in a myriad of ways. To enable virtual environments to fulfill their potential of supporting a wide variety of collaboration use-cases, both the impacts of basic interaction design decisions and the individual needs of specific usage areas need to be explored further.
This thesis approaches this topic in two ways. First, the basic building blocks of collaboration in social virtual environments are explored by asking the question: "How can social virtual spaces that allow interaction beyond real-world constraints utilize the potential of mutual assistance and shared workflows between multiple users?". Going into further detail for a serious use-case in which direct collaborative interactions and their effect on the included users are especially important, it then explores the potential of collaborative virtual spaces in the therapy domain by asking "How can the potential of social virtual spaces be utilized to support and improve therapy encounters?"
With regards to the first research question, the thesis presents two theoretical frameworks detailing different aspects of supporting smooth and varied collaboration processes. In addition, several user studies on the topic of collaborative virtual interaction are described, focusing on the role that different users can play during shared interaction and the effects that this distribution of roles and responsibilities has on both the performance and experience of the involved user pairs.
The results presented for this first research question show that social virtual spaces have the potential to provide dedicated support for collaborative workflows. To enable users to adapt their working mode individually and as a team, interaction techniques should complement a team's natural interaction and communication. When presenting novel interactions to users, providing them with a way to support each other can ease their adaptation to these interactions. In these cases, the inclusion of all interested collaborators as active participators should be prioritized in order to let all users benefit from being immersed in a virtual environment.
Addressing the combination of social virtual spaces with therapy in relation to the second research question, this thesis presents the result of a series of interviews with practicing physio- and psychotherapists. Motivated by the recorded expert feedback, it also reports on two more detailed explorations of specific areas of interest. The work presented for the second research question demonstrated the promise of using virtual environments in both exercise- and conversation-based therapy practice. Investigating the potential of shared interactions, the exploration of virtual recordings and the adaptation of virtual appearances, the presented work uncovered several topic areas that could be further explored regarding their possible use in the treatment of patients.
Taken together, the six research articles presented in this thesis show both the value of supporting and understanding shared interactions in virtual spaces and their potential place in serious use-cases like the therapy domain. When introducing shared virtual environments to new user groups, the opportunity for mutual support through shared interaction techniques could be a crucial building block towards making virtual spaces both accessible and attractive to a variety of users.
The present dissertation deals with variable stress patterns in English complex adjectives such as celebratory, identifiable or imaginative. This variation is usually described in terms of retaining the stress from the embedded base (idéntify -> idéntifiable) or deviating from the stress of the embedded base (idéntify -> identifíable). While several accounts have explored this variation, none of them have been able to identify a plausible reason for why it occurs. Additionally, the role of individual speaker differences has been disregarded in the discussion. This dissertation therefore explores the empirically observable extent of the variation and investigates possible causes of it with a special focus on individual differences between speakers. It uses data from a complex online experiment that included five different tasks to assess speakers' stress production, perception, morphological processing, vocabulary size and other factors. It furthermore tests the predictions of previous accounts on the large set of authentic utterances from speakers collected using this online experiment. The data show that individual differences in vocabulary size between speakers are a significant predictor of a speaker's tendency to retain the stress of the embedded base.
The new millennium has been characterized by rising digitalization, the proliferation of shadow banking, and significant advancements in machine learning and natural language processing. These trends present both challenges and opportunities, which my dissertation addresses. This cumulative dissertation investigates critical aspects of financial stability, monetary policy, and the transition towards cashless economies through three distinct but interrelated studies.
The first paper examines the risk-taking channel of monetary policy transmission within the euro area, focusing on shadow banks. Through vector autoregressive models, it assesses the impact of conventional and unconventional monetary policy shocks on shadow banks' asset growth and risk asset ratios. The results indicate that lower interest rates lead to a portfolio reallocation towards riskier assets and a general expansion of assets in shadow banks. In the case of conventional monetary policy shocks, both effects last three times as long as in the case of unconventional monetary policy shocks. Country-specific as well as sector-specific estimations confirm these findings. This study bridges gaps in the existing literature, especially in the eurozone, by highlighting the significant role shadow banks play in monetary policy transmission, suggesting implications for financial regulation and stability.
The second paper explores the influence of financial stability considerations on US monetary policy, particularly during the Great Recession. Utilizing natural language processing and machine learning techniques on congressional hearings, this study constructs indicators for financial stability sentiment expressed by the Federal Reserve Chairs. Empirical analysis is conducted using Taylor-rule models, revealing that negative financial stability sentiment is associated with a more accommodative monetary policy stance, even before the Great Recession. This work provides new insights into the integration of financial stability concerns into monetary policy frameworks, demonstrating the need for a balanced approach to economic stability. The article suggests that under a dual mandate, such as that of the Federal Reserve, financial stability can, to some extent, already be factored into monetary policy deliberations.
The third paper sheds new light on ``cash paradox'' by uncovering the factors of the cashless transition that has not been entirely understood so far. Using a comprehensive dataset across 65 countries, the study employs panel data models to explain the paradox (increasing demand for central bank money despite soaring digitalization), especially among technologically advanced countries, e.g., Japan. Empirical evidence suggests that digitalization is not significantly associated with higher reliance on physical cash. It uncovers a unique non-linear relationship between trust and cash usage (``Arch of Trust'') which holds after addressing potential endogeneity issues using 2SLS estimation. Opposed to the widespread misinterpretations of Keynes' (1937) reasons for holding cash, the findings highlight that distrust is the key factor unlocking two distinct puzzles in economics, linking cash hoarding with ``missing'' funds on capital markets and slower shift toward digital payments in low-trust societies. A key insight is the role of trust as a (social) insurance, cushion or safety net, dampening the perception of risk and reducing precautionary and transactionary demand for physical cash, while encouraging a shift towards riskier alternatives. This, in turn, is connected to the third puzzle, the ``paradox of prudence.'' A shift from riskier investments to safer assets, cash, may be prudent at the individual level but risky for the overall economy, a concern for macroprudential policymakers. Additionally, the research highlights the critical role of culture in driving the global movement towards cashless economies. Moreover, cultures that are more self-expression-oriented (which is the main cultural dimension) and culturally closer to Sweden are associated with less cash-intensive economies. These insights are vital for macroprudential regulators as well as for policymakers designing payment systems and CBDC in culturally diverse regions like the Eurozone.
Collectively, these papers contribute to a deeper understanding of monetary policy, financial stability, and the transition from cash-based to (nearly) cashless societies, offering significant theoretical and practical implications for academics, regulators and central bankers.
Biotic communities experienced significant changes in recent decades. Climate change, the overexploitation of natural resources and the immigration of invasive species are major drivers for this change and present unknown challenges for communities worldwide. To assess the impact of these drivers, standardised long-term studies are required, which are currently lacking for many species and ecosystems. Analysing environmental samples and the DNA of associated organisms using metabarcoding and high-throughput sequencing provides a cost-efficient and rapid way to generate the high-resolution biodiversity data which is so direly needed.
In this thesis, I demonstrate the great potential of using samples from the German Environ- mental Specimen Bank (ESB), a long-term monitoring archive that has been collecting and cryogenically storing highly standardised environmental samples since 1985. Modern analytical methods enable retrospective long-term biodiversity monitoring using these samples. In the first chapter, I illustrate metabarcoding as a central method, discussing its strengths and drawbacks, how to avoid them, and new application approaches. This chapter provides the methodological basis for the following studies.
In subsequent chapters, I present time series analyses of communities associated with these environmental samples. While for Chapter two the focus is on terrestrial arthropod communities, in Chapter three aquatic and terrestrial communities across the tree of life are analysed. A null model was developed for this survey for robust conclusions. The studies covered the last three decades and revealed substantial compositional changes across all ecosystems. These changes deviated significantly from the model, indicating that the changes are occurring faster than expected. Moreover, a trend toward homogenization in many terrestrial communities was uncovered. Climate change and the immigration of invasive species in combination with the loss of site-specific species are suspected to be the main drivers for this. In a follow-up study, changes of arthropod communities in German and South Korean terrestrial ecosystems were compared using ESB leaf samples from these two countries. Since both ESBs are harmonised in sample collection and processing, comparative analyses were applicable. This research covered the last decade and revealed substantial declines in species richness in Korea. Abiotic and biotic factors are discussed as potential drivers of these results.
Finally, the possibility of assessing tree health by analysing changes in functional fungal groups using German ESB samples was investigated. The results indicate that increasing infestation of specific functional groups is a proxy for declining tree health, with further analyses planned. In this dissertation, I present the great potential of samples from long-term monitoring archives to conduct retrospective biodiversity trend analyses across the tree of life. As technologies evolve, these samples will help to understand past and predict future ecosystem changes.
The present study investigates the prosody of information-seeking (ISQs) and rhetorical questions (RQs) in Standard Chinese, in polar and wh-questions. Like in other languages, ISQs and RQs in Standard Chinese can have the same surface structure, allowing for a direct prosodic comparison between illocution types (ISQ vs RQ). Since Standard Chinese has lexical tone, the use of f0 as a cue to illocution type may be restricted. We investigate the prosodic differences between ISQs and RQs as well as the interplay of prosodic cues to RQs. In terms of f0, results showed that RQs were lower in f0, with the f0 range on the first word being expanded followed by f0 compression. RQs were further longer in duration and more often realized with non-modal voice quality (glottalized voice) as compared to ISQs. These prosodic cues were largely manipulated in tandem (illocutionary pairs with larger durational differences also showed larger differences in mean f0; voice quality, in turn, seemed to be an additional cue). We suggest three possible explanations (assertive force, focus, speaker attitude) that unite the present findings on RQs in Standard Chinese with the findings on RQs in other, non-tonal languages.
In den letzten Jahren hat die Nutzung von Drohnen deutlich zugenommen. Dies liegt unter anderem an der Leistungssteigerung, der guten Verfügbarkeit und an dem einfachen Einsatz von Drohnen. Damit sind auch Anwendungen in der Forschung möglich geworden, die zuvor unmöglich oder mit hohen Kosten verbunden waren. Als Sensor zur Datenaufzeichnung findet im Bereich der Forschung häufig eine Kamera Verwendung. Zusammen mit einer Drohne können Bereiche einfach und kostengünstig überflogen und dabei erkundet, beobachtet oder überwacht werden. Neben der Kamera als Sensor werden auch häufig Multispektralkameras und Lidar eingesetzt. Dagegen findet Radar im Bereich von kleinen Drohnen kaum Anwendung. Ziel dieser Forschungsarbeit war es zu untersuchen, ob neuste Radartechnik einen Mehrwert in der Fernerkundung mit kleinen Drohnen bieten kann.
Hierfür wurden moderne Radarsensoren aus dem Automobilbereich ausgewählt. Als Drohnen wurden sowohl Quadrocopter als auch eine Starrflügler-Drohne eingesetzt. Für die Analyse, Berechnung und Auswertung der Daten wurde MATLAB verwendet. Der erste Ansatz beruhte auf einer Starrflügler-Drohne, die sich durch ihren freien Zugriff auf die Steuerung auszeichnet. Dadurch können auch spezielle Anforderungen an die Flugregelung berücksichtigt werden. Allerdings können mit einer Starrflügler-Drohne keine langsamen oder sogar statische Luftaufnahmen erstellt werden, um Erfahrung mit den Radardaten zu erlangen. Aus diesem Grund wurde anschließend ein Radar-Messsystem entworfen, das unabhängig von der Drohne eingesetzt werden kann. Zusammen mit einem Quadrocopter konnten so statische Radarmessungen durchgeführt werden, um die Verwendbarkeit der Radardaten in der Fernerkundung zu bestätigen. Das Messsystem konnte so aber nur für 2-dimensionale Anwendungen eingesetzt werden. In der weiteren Forschungsarbeit wurde untersucht, ob es möglich ist, mit einem Radarsensor der nur in 2-dimensionen misst eine 3-dimensionale Aufzeichnungen zu erstellen. Als Versuchsobjekt wurde eine Hütte gewählt, die Anhand der Radardaten dargestellt werden sollte. Dafür wurde ein Prozess zur Datenverarbeitung mit elf Schritten entworfen, womit die Hütte auf 0,6 Meter genau rekonstruiert werden konnte. Im letzten Teil der Forschungsarbeit wurde untersucht, ob sich die Genauigkeit des Messsystems erhöhen lässt, um noch mehr Anwendungsfälle bedienen zu können. Dafür wurde ein neuer Radarsensor eingesetzt, der eine höhere Genauigkeit besitzt. Die Forschungsarbeit konzentrierte sich darauf, die Abhängigkeit der Radardaten zum ungenauen Lagesensor aufzulösen. Dabei wurde die Fluglage über die Radardaten selbst berechnet, womit die Fluglage genauer bestimmt werden kann als allein über den Lagesensor. Erst damit kann die höhere Genauigkeit des neuen Radarsensors auch tatsächlich ausgenutzt werden.
Mit den Ergebnissen der Forschungsarbeit sowie den vorgestellten Radarsensoren, stehen der Fernerkundung mit kleinen Drohnen, neben den klassischen Sensoren, zukünftig auch Radarsensoren zur Verfügung. Mit dem Messsystem und den Erkenntnissen aus der Forschungsarbeit werden bereits erste spezifische Anwendungen in Forschungsprojekten untersucht. Darüber hinaus konnten auch Anwendungsfälle außerhalb der Fernerkundung identifiziert werden. Die Weiterentwicklung im Bereich des autonomen Fahrens wird für Leistungssteigerungen bei Radarsensoren sorgen. Damit stehen auch der Fernerkundung zukünftig noch bessere Radarsensoren zur Verfügung.
Entrepreneurship is recognized as an important discipline to achieve sustainable development and to address sustainability goals without losing sight of economic aspects. However, entrepreneurship rates are rather low in many industrialized countries with high income levels. Research clearly shows that there is a gap in the entrepreneurial process between intentions and subsequent actions. This means that not everyone with entrepreneurial ambitions also follows through and implements actions. This gap also exists for aspects of sustainability. As a result, there is a need to better understand the traditional and sustainability-focused entrepreneurial process in order to increase corresponding actions. This dissertation offers such a comprehensive perspective and sheds light on individual and contextual predictors for traditional and sustainability-focused behavior of entrepreneurs and self-employed across four studies.
The first three studies focus on individual predictors. By providing a systematic literature review with 107 articles, Chapter 2 highlights the ambivalent role of religion for the entrepreneurial process. Relying on the theory of planned behavior (TPB) as theoretical basis, religion can have positive effects on entrepreneurial attitudes and behavioral control, but also negative consequences for other aspects of behavioral control and subjective norms due to religious restrictions.
The quantitative empirical study in Chapter 3 similarly relies on the TPB and sheds light on individual perceptual factors influencing the sustainability-related intention-action gap in entrepreneurship. Using data from the 2021 Global Entrepreneurship Monitor (GEM) Adult Population Survey (APS) including 22,008 early-stage entrepreneurs from 44 countries worldwide, the results support our theoretical reasoning that sustainability-focused intentions are positively related to social entrepreneurial actions. In addition, it is demonstrated that positive perceptual moderators such as self-efficacy and knowing other entrepreneurs as role models strengthen this relationship while a negative perception such as fear of failure restricts social actions in early-stage entrepreneurship.
The next quantitative empirical study in Chapter 4 examines the behavioral consequences of well-being at a sample of 6,955 German self-employed during COVID-19. This chapter builds on two complementary behavioral perspectives to predict how reductions in financial and non-financial well-being relate to investments in venture development. In this regard, reductions in financial well-being are positively related to time investments, supporting the performance feedback perspective in terms of higher search efforts under negative performance. In contrast, reductions in non-financial well-being are negatively related to time and monetary investments, yielding support for the broadening-and-build perspective indicating that negative psychological experiences narrow the thought-action repertoire and hinder resource deployment. The insights across these first three studies about individual predictors indicate that many different, subjective beliefs, perceptions and emotional states can influence the entrepreneurial process making entrepreneurship and self-employment highly individualized disciplines.
The last quantitative empirical study provides an explorative view on a large number of contextual predictors for social and ecological considerations in entrepreneurial actions. Combining GEM data from 2021 on country level with further information from the World Bank and the OECD, a machine learning approach is employed on a sample of 84 countries worldwide. The results suggest that governmental and regulatory as well as cultural factors are relevant to predict social and ecological considerations. Moreover, market-related aspects are shown to be relevant predictors, especially socio-economic factors for social considerations and economic factors for ecological considerations. Overall, the four studies in this dissertation highlight the complexity of the entrepreneurial process being determined by many different individual and contextual factors. Due to the multitude of potential predictors, this dissertation can only give an initial overview of a selection of factors with many more aspects and interdependencies still to be examined by future research.
Within this thesis the hedging behaviour of airlines from 2005 to 2019 is analysed by using an unbalanced panel dataset consisting of a total of 78 airlines from 39 countries. The focus of the analysis is on financial and operational hedging as well as the influence of both on CO2 emissions and the development of emitted CO2 emissions. For the analysis Probit models with random effects and OLS models with fixed effects were used.
The results regarding the relationship between leverage and financial hedging indicate a negative relationship between everage and financial fuel hedging and a non-linear convex relationship for highly leveraged airlines, which is contrary to the theory of financial distress.
In addition, the study provides evidence that airlines using other types of derivatives, such as interest rate derivatives, engage in more fuel hedging.
In terms of operational hedging, the analysis suggests that operating a diversified fleet is a complement to, rather than a substitute for, financial hedging. With regard to alliance membership, the results do not show that alliance membership is a substitute for financial hedging, as members of alliances are more likely to engage in hedging transactions and to a greater extent.
The analysis shows that the relative CO2 emissions fall in the period under review, but this does not apply to the absolute amount. No general statement can be made about the influence of financial and operational hedging on CO2 emissions, as the results are mixed.
Zirkularität und zirkulare Geschäftsmodelle in der Holzindustrie: eine empirische Untersuchung
(2025)
Der ökologische Zustand der Erde befindet sich infolge von Umweltverschmutzung, Abfallaufkommen und CO₂-bedingtem Klimawandel in einem kritischen Zustand. Mit rund 40 % trägt der Bau- und Gebäudesektor erheblich zu den globalen Treibhausgasemissionen bei. Holz gilt als klimafreundliche Alternative zu Beton und Stahl, bedarf jedoch ebenfalls einer nachhaltigen Nutzung. Die Kreislaufwirtschaft bietet mit der Wiederverwendung ein zukunftsweisendes Konzept: So sind etwa 45% des beim Rückbau von Gebäuden anfallenden Holzes potenziell als Rohstoff nutzbar. Dadurch werden alternative Rohstoffquellen erschlossen und das Abfallaufkommen reduziert.
Trotz dieses Potenzials liegt der Zirkularitätsgrad der Weltwirtschaft derzeit nur bei 7,2 %. Vor diesem Hintergrund untersucht die Dissertation, welche Wettbewerbsstrategien und welche organisationalen Fähigkeiten die Entwicklung zirkulärer Geschäftsmodelle fördern. Der Fokus liegt auf der Holzindustrie der DACH-Region, die historisch durch forstwirtschaftliche Nachhaltigkeit geprägt ist, jedoch bislang überwiegend linearen Strukturen folgt.
Die Arbeit kombiniert theoretische Fundierung, eine vierjährige Literaturrecherche, Experteninterviews sowie im Zentrum eine quantitative Unternehmensbefragung (n = 200). Daraus wurde eine aktivitätsorientierte Skala zur Bewertung der Zirkularität eines Geschäftsmodells entwickelt. Analysiert wurden drei Perspektiven: Fähigkeiten, Strategien und Stakeholder.
Im Kontext der Fähigkeitsperspektive wurde ermittelt, dass die dynamischen Fähigkeiten positive Implikationen auf die Umsetzung von Zirkularität haben. Im Forschungsfeld der Strategieperspektive wurde deutlich, dass die Innovationsführerschaft positive Effekte auf die Umsetzung der Kreislaufwirtschaft besitzt. Zudem weisen sowohl die Innovationsführerschaft als auch die Qualitätsführerschaft einen positiven indirekten Effekt über die dynamischen Fähigkeiten auf die Entwicklung zirkulärer Geschäftsmodelle auf. Im Rahmen der Stakeholderperspektive wurde eruiert, dass der Stakeholder-Druck im Zusammenwirken mit einem grünen Unternehmensimage eine Katalysator-Wirkung besitzt. Der Einfluss der Interessengruppen führt dazu, dass die Unternehmen ein grünes Image in eine substanzielle Umsetzungsphase überführen. Darüber hinaus wurde ersichtlich, dass der Stakeholder-Druck als zentraler Veränderungsfaktor wirkt. Während die direkten Auswirkungen der dynamischen Fähigkeiten durch den Druck zurückgehen, nehmen die indirekten Effekte auf die Erreichung von Zirkularität zu. Abschließend werden Handlungsempfehlungen für Unternehmen sowie wissenschaftliche Implikationen und zukünftige Forschungsmöglichkeiten abgeleitet.
When natural phenomena and data-based relations are driven by dynamics which are not purely local, they cannot be described satisfactorily by partial differential equations. As a consequence, mathematical models governed by nonlocal operators are of interest. This thesis is concerned with nonlocal operators of the form
$\mathcal{L}u(x) = PV \int_{\mathbb{R}^d} (u(x)-u(y)) K(x,dy), x \in \mathbb{R}^d$,
which are determined through a family of Borel measures $K=(K(x, \cdot))_{x \in \mathbb{R}^d}$ on $\mathbb{R}^d$ and which act on the vector space of Borel measurable functions $u: \mathbb{R}^d \rightarrow \mathbb{R}$. For a large class of families $K$, namely those where $K$ is a symmetric transition kernel satisfying a specific non-degeneracy condition, a variational theory for nonlocal equations of the type $\mathcal{L}u=f$ is established which builds upon gadgets from both measure theory and classical analysis. While measure theory is used to provide a nonlocal integration by parts formula that allows to set up a reasonable variational formulation of the above equation in dependency of the particular boundary condition (Dirichlet, Robin, Neumann) considered, Hilbert space theory and fixed-point approaches are utilized to develop sufficient conditions for the existence of variational solutions. This theory is then applied to two specific realizations of $\mathcal{L}$ of interest before a weak maximum principle is established which is finally used to study overlapping domain decomposition methods for the nonlocal and homogeneous Dirichlet problem.
Small and medium-sized enterprises (SMEs) and mid-sized companies are vital contributors to the global economy, driving employment growth, fostering innovation, and enhancing international competiveness. However, in the aftermath of the Great Financial Crisis (GFC) and the collapse of the large finance company CIT Group, which provided 60% loans to US middle-market firms, banks reduced their lending activities. Thus, it became challenging for firms to obtain long-term loans. The financing gap has increased further due to high interest rates, the COVID-19 pandemic, the unstable situation in the real estate market as well as higher costs due to the adoption of digital infrastructure and sustainability goals. Therefore, the search for alternative financing solutions outside bank lending and public markets became unavoidable for SMEs and mid-sized companies. Private debt funds entered the market, and, since the GFC, they have played a crucial role in offering alternative financing for firms globally. Private debt fund managers raise capital commitments through closed-end funds (like private equity) and make senior loans (like banks) directly to, mostly, middlemarket firms. The private debt market has experienced rapid growth in recent decades. The private debt funds assets under management (AuM) increased by 380% from 2008 to 2022, reaching $1.5 trillion AuM in 2022 . The high growth of private debt shows great interest from investors in this alternative asset class and lucrative investment opportunities.
Despite its substantial and growing size, the private debt market is relatively understudied. This dissertation introduces private debt as an important alternative financing source, provides an overview of private debt strategies, seniority, and structure, discusses the legal considerations concerning private debt, and briefly compares the two most mature private debt markets: Europe and the U.S. Moreover, it assesses the size of the European private debt market and compares its development in different European regions. Furthermore, it examines in detail the business model of private debt funds based on a survey of 191 European and U.S. private debt managers with private debt assets under management of over $390 billion. Finally, it delves deeper into the relationship between private debt and private equity funds and their role in buyouts.
To sum up, this dissertation provides a basis and inspiration for future research to expand upon and dive deeper into the world of private debt funds, their business model, and their impact on portfolio companies and the economy as a whole.
Immer wieder tauchen Fragen nach dem Stüve-Diagramm und seiner Benutzung auf. Es gibt zwar neben der Vorlesung “Einführung in die Meteorologie” auch erklärende Darstellungen in den empfohlenen Lehrbüchern und im Internet. Diese scheinen aber offenbar nicht zufriedenstellend zu sein. Deshalb habe ich nachfolgend versucht, die Antworten auf die häufigsten Fragen in Form einer Anleitung zusammen zu fassen. Ich danke em. Prof. Dr. Alfred Helbig, der im Rahmen seiner früheren Tätigkeit im operationellen Dienst umfangreiche praktische Erfahrung mit Radiosonden-Aufstiegen erworben hat, sowie Dr. Micha Gryschka (Institut für Meteorologie und Klimatologie, Leibniz Universität Hannover) für die hilfreichen Kommentare zum Manuskript.
Knapp 90 Jahre nach Erscheinen des Buchs von Paul Graindor zu den „Bustes et Statues-Portraits d'Egypte Romaine“ widmet sich mit der vorliegenden Dissertation erstmals wieder eine monographische Studie der marmornen Bildnisplastik der römischen Provinz Aegyptus von ihrer Gründung im Jahr 30 v. Chr. bis zum Ende des 3. Jhs. n. Chr. Basierend auf einer umfassenden Zusammenstellung bekannter, aber auch bislang unpublizierter Portraits sowie einer Neudokumentation zahlreicher Objekte gelingt erstmalig eine belastbare chronologische und typologische Auswertung dieser Bildnisse. Zwar bilden dabei die Darstellungen aus weißem Marmor die zentrale und auch quantitativ bei weitem größte Materialgruppe, doch es finden auch Bildnisse aus anderen Werkstoffen wie Bronze, Kalkstein, Gips oder Alabaster Berücksichtigung. Da die Provinz aufgrund geringer eigener Marmorvorkommen fast ausschließlich auf Importe angewiesen war, sind die Marmorbildnisse ein exzellentes Forschungsobjekt, um nicht nur den Handel von Marmor nach Ägypten und seine Distribution und Weiterverarbeitung in der Provinz zu untersuchen, sondern auch damit verbundene handwerkliche Besonderheiten, wie die häufig zu beobachtenden Ergänzungen mit Stuck- oder Steinelementen. Darüber hinaus werden auch Überlegungen zur Semantik des Materials sowie der Herkunft und dem Selbstverständnis der dargestellten Personen angestellt.
Mit Fokus auf historischen Liedern aus Deutschland, Frankreich, England, Irland, den USA, Österreich, den Niederlanden, Slowenien, Polen, Italien, Neuseeland und der Schweiz zeichnet dieses Buch ein breites und lebendiges Panorama der Frühen Neuzeit.
Die Sammlung spannt den Bogen von klassischen Lerninhalten bis hin zu aktuellen Forschungsperspektiven: Reformation, Amerikanische und Französische Revolution, Höfische Kultur, Kriminalität, Seefahrt, militärische und diplomatische Konflikte sind ebenso Thema wie die Geschlechterordnung, globale Migration oder historische Identitäts- und Fremdheitsvorstellungen. Eine systematische Verschlagwortung erleichtert den Zugriff und erlaubt vielfältige Kombinationen für die akademische und schulische Lehre.
Jedes der 101 Lieder wird mit Informationen zum historischen Kontext, zur Überlieferung und zu online verfügbaren Vertonungen präsentiert. Hinzu kommen Aufgabenstellungen und Anregungen für die Diskussion im Kurs oder Seminar. Auch das lange und mitunter ambivalente Nachleben neuzeitlicher Lieder im 19. und 20. Jahrhundert wird beleuchtet.
Darüber hinaus bietet der Band methodische Hinweise und Anregungen zur eigenständigen Recherche und Analyse historischer Lieder, beispielsweise in Seminar- und Abschlussarbeiten.
Die Abteilung Kunstschutz der deutschen Wehrmacht im besetzten Griechenland (1941-1944) bestand aus wehrpflichtigen deutschen Archäologen. Sie waren zunächst Stipendiaten oder Mitarbeiter des Archäologischen Instituts des Deutschen Reiches (AIDR) unter den Bedingungen des Nationalsozialismus, bevor sie im Zweiten Weltkrieg in der Uniform der Wehrmacht zurückkehrten. Ihre Biografien im Kontext der Abteilung Athen, deren Direktor Georg Karo bis 1936 war, sowie der Zentrale der Instituts, unter dem von 1932 bis 1936 amtierenden Präsidenten Theodor Wiegand, sind ein Untersuchungsgegenstand. Die außenpolitische Legitimation des NS-Regimes durch die Olympischen Spiele und der wichtigste wissenschaftspolitische Erfolg des Institutes, die Wiederaufnahme der Olympiagrabung, die Wiegand und Karo seit 1933 anstrebten und durch ihre politischen Netzwerke 1936 erreichten, werden in der Dissertation in ihrer wechselseitigen Bedingtheit aufgezeigt. Diese Anpassungsleistungen an das NS-Regime prägten den eigenen archäologischen Nachwuchs aber auch die griechische Gesellschaft.
Schutzmaßnahmen waren nur ein kleiner Tätigkeitsbereich der Kunstschützer aber ein wichtiger Teil der Wehrmachtspropaganda. Der Institutspräsident Martin Schede (1937 bis 1945) forderte Mitarbeitern vor allem für zwei AIDR-Projekte an: die Erstellung von Flugbildern von möglichst ganz Griechenland und Ausgrabungen auf Kreta. Bereits diese Zwischenergebnisse berechtigen zu dem Titel „Kunstschutz als Alibi“.
Die Dissertation versucht, die Frage zu beantworten, warum der archäologische Kunstschutz nicht mehr als ein Alibi sein konnte. Dies geschieht vor allem unter Berücksichtigung der politischen aber auch der militärischen Traditionslinien deutscher Archäologie in Griechenland und Deutschland.
Case-Based Reasoning (CBR) is a symbolic Artificial Intelligence (AI) approach that has been successfully applied across various domains, including medical diagnosis, product configuration, and customer support, to solve problems based on experiential knowledge and analogy. A key aspect of CBR is its problem-solving procedure, where new solutions are created by referencing similar experiences, which makes CBR explainable and effective even with small amounts of data. However, one of the most significant challenges in CBR lies in defining and computing meaningful similarities between new and past problems, which heavily relies on domain-specific knowledge. This knowledge, typically only available through human experts, must be manually acquired, leading to what is commonly known as the knowledge-acquisition bottleneck.
One way to mitigate the knowledge-acquisition bottleneck is through a hybrid approach that combines the symbolic reasoning strengths of CBR with the learning capabilities of Deep Learning (DL), a sub-symbolic AI method. DL, which utilizes deep neural networks, has gained immense popularity due to its ability to automatically learn from raw data to solve complex AI problems such as object detection, question answering, and machine translation. While DL minimizes manual knowledge acquisition by automatically training models from data, it comes with its own limitations, such as requiring large datasets, and being difficult to explain, often functioning as a "black box". By bringing together the symbolic nature of CBR and the data-driven learning abilities of DL, a neuro-symbolic, hybrid AI approach can potentially overcome the limitations of both methods, resulting in systems that are both explainable and capable of learning from data.
The focus of this thesis is on integrating DL into the core task of similarity assessment within CBR, specifically in the domain of process management. Processes are fundamental to numerous industries and sectors, with process management techniques, particularly Business Process Management (BPM), being widely applied to optimize organizational workflows. Process-Oriented Case-Based Reasoning (POCBR) extends traditional CBR to handle procedural data, enabling applications such as adaptive manufacturing, where past processes are analyzed to find alternative solutions when problems arise. However, applying CBR to process management introduces additional complexity, as procedural cases are typically represented as semantically annotated graphs, increasing the knowledge-acquisition effort for both case modeling and similarity assessment.
The key contributions of this thesis are as follows: It presents a method for preparing procedural cases, represented as semantic graphs, to be used as input for neural networks. Handling such complex, structured data represents a significant challenge, particularly given the scarcity of available process data in most organizations. To overcome the issue of data scarcity, the thesis proposes data augmentation techniques to artificially expand the process datasets, enabling more effective training of DL models. Moreover, it explores several deep learning architectures and training setups for learning similarity measures between procedural cases in POCBR applications. This includes the use of experience-based Hyperparameter Optimization (HPO) methods to fine-tune the deep learning models.
Additionally, the thesis addresses the computational challenges posed by graph-based similarity assessments in CBR. The traditional method of determining similarity through subgraph isomorphism checks, which compare nodes and edges across graphs, is computationally expensive. To alleviate this issue, the hybrid approach seeks to use DL models to approximate these similarity calculations more efficiently, thus reducing the computational complexity involved in graph matching.
The experimental evaluations of the corresponding contributions provide consistent results that indicate the benefits of using DL-based similarity measures and case retrieval methods in POCBR applications. The comparison with existing methods, e.g., based on subgraph isomorphism, shows several advantages but also some disadvantages of the compared methods. In summary, the methods and contributions outlined in this work enable more efficient and robust applications of hybrid CBR and DL in process management applications.
There is a wide range of methodologies for policy evaluation and socio-economic impact assessment. A fundamental distinction can be made between micro and macro approaches. In contrast to micro models, which focus on the micro-unit, macro models are used to analyze aggregate variables. The ability of microsimulation models to capture interactions occurring at the micro-level makes them particularly suitable for modeling complex real-world phenomena. The inclusion of a behavioral component into microsimulation models provides a framework for assessing the behavioral effects of policy changes.
The labor market is a primary area of interest for both economists and policy makers. The projection of labor-related variables is particularly important for assessing economic and social development needs, as it provides insight into the potential trajectory of these variables and can be used to design effective policy responses. As a result, the analysis of labor market behavior is a primary area of application for behavioral microsimulation models. Behavioral microsimulation models allow for the study of second-round effects, including changes in hours worked and participation rates resulting from policy reforms. It is important to note, however, that most microsimulation models do not consider the demand side of the labor market.
The combination of micro and macro models offers a possible solution as it constitutes a promising way to integrate the strengths of both models. Of particular relevance is the combination of microsimulation models with general equilibrium models, especially computable general equilibrium (CGE) models. CGE models are classified as structural macroeconomic models, which are defined by their basis in economic theory. Another important category of macroeconomic models are time series models. This thesis examines the potential for linking micro and macro models. The different types of microsimulation models are presented, with special emphasis on discrete-time dynamic microsimulation models. The concept of behavioral microsimulation is introduced to demonstrate the integration of a behavioral element into microsimulation models. For this reason, the concept of utility is introduced and the random utility approach is described in detail. In addition, a brief overview of macro models is given with a focus on general equilibrium models and time series models. Various approaches for linking micro and macro models, which can either be categorized as sequential approaches or integrated approaches, are presented. Furthermore, the concept of link variables is introduced, which play a central role in combining both models. The focus is on the most complex sequential approach, i.e., the bi-directional linking of behavioral microsimulation models with general equilibrium macro models.
The goal of this work is to compare operators that are defined on probably varying Hilbert spaces. Distance concepts for operators as well as convergence concepts for such operators are explained and examined. For distance concepts we present three main notions. All have in common that they use space-linking operators that connect the spaces. At first, we look at unitary maps and compare the unitary orbits of the operators. Then, we consider isometric embeddings, which is based on a concept of Joachim Weidmann. Then we look at contractions but with more norm equations in comparison. The latter idea is based on a concept of Olaf Post called quasi-unitary equivalence. Our main result is that the unitary and isometric distances are equal provided the operators are both self-adjoint and have 0 in their essential spectra. In the third chapter, we focus specifically on the investigation of these distance terms for compact operators or operators in p-Schatten classes. In this case, the interpretation of the spectra as null sequences allows further distance investigation. Chapter four deals mainly with convergence terms of operators on varying Hilbert spaces. The analyses in this work deal exclusively with concepts of norm resolvent convergence. The main conclusion of the chapter is that the generalisation for norm resolvent convergence of Joachim Weidmann and the generalisation of Olaf Post, called quasi-unitary equivalence, are equivalent to each other. In addition, we specify error bounds and deal with the convergence speed of both concepts. Two important implications of these convergence notions are that the approximation is spectrally exact, i.e., the spectra converge suitably, and that the convergence is transferred to the functional calculus of the bounded functions vanishing at infinity.
Der Arbeits- und Fachkräftemangel ist ein breit diskutiertes Thema in Deutschland. Auch im Landkreis Bernkas-tel-Wittlich hat diese Herausforderung in den letzten Jahren zunehmend an Bedeutung gewonnen. Ziel dieses Forschungsberichtes ist es deshalb erstens einen Überblick über die Arbeits- und Fachkräftesituation im Land-kreis zu bieten. Aufbauend auf diese Forschungsergebnisse werden zweitens Handlungsfelder benannt, die ei-nen Rahmen zur Stärkung des Landkreises als produktiven Wirtschaftsstandort und attraktiven Arbeitsort geben sollen.
In this dissertation, I analyze how large players in financial markets exert influence on smaller players and how this affects the decisions of the large ones. I focus on how the large players process information in an uncertain environment, form expectations and communicate these to smaller players through their actions. I examine these relationships empirically in the foreign exchange market and in the context of a game-theoretic model of an investment project.
In Chapter 2, I investigate the relationship between the foreign exchange trading activity of large US-based market participants and the volatility of the nominal spot exchange rate. Using a novel dataset, I utilize the weekly growth rate of aggregate foreign currency positions of major market participants to proxy trading activity in the foreign exchange market. By estimating the heterogeneous autoregressive model of realized volatility (HAR-RV), I find evidence of a positive relationship between trading activity and volatility, which is mainly driven by unexpected changes in trading activity and is asymmetric for some of the currencies considered. My results contribute to the understanding of the drivers of exchange rate volatility and the role of large players in the flow of information in financial markets.
In Chapters 3 and 4, I consider a sequential global game of an investment project to examine how a large creditor influences the decisions of small creditors with her lending decision. I pay particular attention to the timing of the large player’s decision, i.e. whether she makes her decision to roll over a credit before or after the small players. I show that she faces a trade-off between signaling to and learning from small creditors. By being a focal point for coordination, her actions have a substantial impact on the probability of coordination failure and the failure of the investment project. I investigate the sensitivity of the equilibrium by comparing settings with perfect and imperfect learning. The results highlight the importance of signaling and provide a new perspective on the idea of catalytic finance and the influence of a lender-of-last-resort in self-fulfilling debt crises.
The cumulative and bidirectional groundwater-surface water (GW-SW) interaction along a stream is defined as hydrological turnover (HT) influencing solute transport and source water composition. However, HT proves to be highly variable, producing spatial exchange patterns influenced by local groundwater, geology, and topography. Hence, identifying factors controlling HT poses a challenge. We studied spatiotemporal HT variability at two reaches of a third order tributary of the river Mosel, Germany. Additionally, we sampled for silica concentrations in the stream and in the near-stream groundwater. Thus, creating snapshots of the boundary layer between ground- and surface water where HT occurs, driven by mixing processes in the hyporheic zone. We utilize an enhanced hydrograph separation method, unveiling reach differences in storage drainage based on aquifer dimension and connectivity. The data shows a site-specific negative correlation of HT with discharge, while hydraulic gradients correlate with HT only at the reach with faster catchment drainage behavior. Examining silica concentrations between stream and wells shows that silica variation increases significantly with the decrease of HT under low flow conditions at the slower draining reach. At the fast draining reach this relationship is seasonal. In Summary, our results show that stream discharge shapes the influence of HT on solute transport. Yet, reach drainage behavior shapes seasonal states of groundwater storages and can be an additional control of HT. Hence, concentration change of pollutants could be masked by HT. Thus, our findings contribute to the understanding of HT variability along streams and its ability of influencing physico-chemical stream water composition.
Introduction: Apart from a few studies with limited sample sizes, we have little data on attitudes toward lesbian and gay (LG) people in Greece. Methods: This study examines this topic in 949 heterosexual Greek participants. Based on previous research in cultural contexts other than Greece, we hypothesized that four demographics (gender, age, education, area of residence) and religious and political orientation predict a substantial amount of variance in homophobia (i.e., anti-LG attitudes). Results: We verified all observed variables except area of residence as significant predictors. Regarding the “intergroup contact hypothesis,” we distinguished the direct effects of the predictor variables from indirect effects mediated by contact with lesbians and gay men. All variables except area of residence showed a direct effect and, except for education, also an indirect effect on homophobia. The strongest effects were found for religious and political orientation, followed by gender. Highly religious, right-wing oriented, and male participants reported the highest levels of homophobia, partially mediated by their low level of contact with LG people. Discussion/Conclusion: The results confirm and further explain the detrimental role the Greek Orthodox Church, right-wing political parties, and traditional gender roles play in the acceptance of sexual minorities.
Background: Large language models (LLMs) are increasingly used in mental health, showing promise in assessing disorders. However, concerns exist regarding their accuracy, reliability, and fairness. Societal biases and underrepresentation of certain populations may impact LLMs. Because LLMs are already used for clinical practice, including decision support, it is important to investigate potential biases to ensure a responsible use of LLMs. Anorexia nervosa (AN) and bulimia nervosa (BN) show a lifetime prevalence of 1%-2%, affecting more women than men. Among men, homosexual men face a higher risk of eating disorders (EDs) than heterosexual men. However, men are underrepresented in ED research, and studies on gender, sexual orientation, and their impact on AN and BN prevalence, symptoms, and treatment outcomes remain limited.
Objectives: We aimed to estimate the presence and size of bias related to gender and sexual orientation produced by a common LLM as well as a smaller LLM specifically trained for mental health analyses, exemplified in the context of ED symptomatology and health-related quality of life (HRQoL) of patients with AN or BN.
Methods: We extracted 30 case vignettes (22 AN and 8 BN) from scientific papers. We adapted each vignette to create 4 versions, describing a female versus male patient living with their female versus male partner (2 × 2 design), yielding 120 vignettes. We then fed each vignette into ChatGPT-4 and to “MentaLLaMA” based on the Large Language Model Meta AI (LLaMA) architecture thrice with the instruction to evaluate them by providing responses to 2 psychometric instruments, the RAND-36 questionnaire assessing HRQoL and the eating disorder examination questionnaire. With the resulting LLM-generated scores, we calculated multilevel models with a random intercept for gender and sexual orientation (accounting for within-vignette variance), nested in vignettes (accounting for between-vignette variance).
Results: In ChatGPT-4, the multilevel model with 360 observations indicated a significant association with gender for the RAND-36 mental composite summary (conditional means: 12.8 for male and 15.1 for female cases; 95% CI of the effect –6.15 to -0.35; P=.04) but neither with sexual orientation (P=.71) nor with an interaction effect (P=.37). We found no indications for main effects of gender (conditional means: 5.65 for male and 5.61 for female cases; 95% CI –0.10 to 0.14; P=.88), sexual orientation (conditional means: 5.63 for heterosexual and 5.62 for homosexual cases; 95% CI –0.14 to 0.09; P=.67), or for an interaction effect (P=.61, 95% CI –0.11 to 0.19) for the eating disorder examination questionnaire overall score (conditional means 5.59-5.65 95% CIs 5.45 to 5.7). MentaLLaMA did not yield reliable results.
Conclusions: LLM-generated mental HRQoL estimates for AN and BN case vignettes may be biased by gender, with male cases scoring lower despite no real-world evidence supporting this pattern. This highlights the risk of bias in generative artificial intelligence in the field of mental health. Understanding and mitigating biases related to gender and other factors, such as ethnicity, and socioeconomic status are crucial for responsible use in diagnostics and treatment recommendations.
Background: Suicide represents a critical public health concern, and machine learning (ML) models offer the potential for identifying at-risk individuals. Recent studies using benchmark datasets and real-world social media data have demonstrated the capability of pretrained large language models in predicting suicidal ideation and behaviors (SIB) in speech and text.
Objective: This study aimed to (1) develop and implement ML methods for predicting SIBs in a real-world crisis helpline dataset, using transformer-based pretrained models as a foundation; (2) evaluate, cross-validate, and benchmark the model against traditional text classification approaches; and (3) train an explainable model to highlight relevant risk-associated features.
Methods: We analyzed chat protocols from adolescents and young adults (aged 14-25 years) seeking assistance from a German crisis helpline. An ML model was developed using a transformer-based language model architecture with pretrained weights and long short-term memory layers. The model predicted suicidal ideation (SI) and advanced suicidal engagement (ASE), as indicated by composite Columbia-Suicide Severity Rating Scale scores. We compared model performance against a classical word-vector-based ML model. We subsequently computed discrimination, calibration, clinical utility, and explainability information using a Shapley Additive Explanations value-based post hoc estimation model.
Results: The dataset comprised 1348 help-seeking encounters (1011 for training and 337 for testing). The transformer-based classifier achieved a macroaveraged area under the curve (AUC) receiver operating characteristic (ROC) of 0.89 (95% CI 0.81-0.91) and an overall accuracy of 0.79 (95% CI 0.73-0.99). This performance surpassed the word-vector-based baseline model (AUC-ROC=0.77, 95% CI 0.64-0.90; accuracy=0.61, 95% CI 0.61-0.80). The transformer model demonstrated excellent prediction for nonsuicidal sessions (AUC-ROC=0.96, 95% CI 0.96-0.99) and good prediction for SI and ASE, with AUC-ROCs of 0.85 (95% CI 0.97-0.86) and 0.87 (95% CI 0.81-0.88), respectively. The Brier Skill Score indicated a 44% improvement in classification performance over the baseline model. The Shapley Additive Explanations model identified language features predictive of SIBs, including self-reference, negation, expressions of low self-esteem, and absolutist language.
Conclusions: Neural networks using large language model–based transfer learning can accurately identify SI and ASE. The post hoc explainer model revealed language features associated with SI and ASE. Such models may potentially support clinical decision-making in suicide prevention services. Future research should explore multimodal input features and temporal aspects of suicide risk.
Background: As digital mental health delivery becomes increasingly prominent, a solid evidence base regarding its efficacy is needed.
Objective: This study aims to synthesize evidence on the comparative efficacy of systemic psychotherapy interventions provided via digital versus face-to-face delivery modalities.
Methods: We followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for searching PubMed, Embase, Cochrane CENTRAL, CINAHL, PsycINFO, and PSYNDEX and conducting a systematic review and meta-analysis. We included randomized controlled trials comparing mental, behavioral, and somatic outcomes of systemic psychotherapy interventions using self- and therapist-guided digital versus face-to-face delivery modalities. The risk of bias was assessed with the revised Cochrane Risk of Bias tool for randomized trials. Where appropriate, we calculated standardized mean differences and risk ratios. We calculated separate mean differences for nonaggregated analysis.
Results: We screened 3633 references and included 12 articles reporting on 4 trials (N=754). Participants were youths with poor diabetic control, traumatic brain injuries, increased risk behavior likelihood, and parents of youths with anorexia nervosa. A total of 56 outcomes were identified. Two trials provided digital intervention delivery via videoconferencing: one via an interactive graphic interface and one via a web-based program. In total, 23% (14/60) of risk of bias judgments were high risk, 42% (25/60) were some concerns, and 35% (21/60) were low risk. Due to heterogeneity in the data, meta-analysis was deemed inappropriate for 96% (54/56) of outcomes, which were interpreted qualitatively instead. Nonaggregated analyses of mean differences and CIs between delivery modalities yielded mixed results, with superiority of the digital delivery modality for 18% (10/56) of outcomes, superiority of the face-to-face delivery modality for 5% (3/56) of outcomes, equivalence between delivery modalities for 2% (1/56) of outcomes, and neither superiority of one modality nor equivalence between modalities for 75% (42/56) of outcomes. Consequently, for most outcome measures, no indication of superiority or equivalence regarding the relative efficacy of either delivery modality can be made at this stage. We further meta-analytically compared digital versus face-to-face delivery modalities for attrition (risk ratio 1.03, 95% CI 0.52-2.03; P=.93) and number of sessions attended (standardized mean difference –0.11; 95% CI –1.13 to –0.91; P=.83), finding no significant differences between modalities, while CIs falling outside the range of the minimal important difference indicate that equivalence cannot be determined at this stage.
Conclusions: Evidence on digital and face-to-face modalities for systemic psychotherapy interventions is largely heterogeneous, limiting conclusions regarding the differential efficacy of digital and face-to-face delivery. Nonaggregated and meta-analytic analyses did not indicate the superiority of either delivery condition. More research is needed to conclude if digital and face-to-face delivery modalities are generally equivalent or if—and in which contexts—one modality is superior to another.
Background: Psychoeducation positively influences the psychological components of chronic low back pain (CLBP) in conventional treatments. The digitalization of health care has led to the discussion of virtual reality (VR) interventions. However, CLBP treatments in VR have some limitations due to full immersion. In comparison, augmented reality (AR) supplements the real world with virtual elements involving one’s own body sensory perception and can combine conventional and VR approaches.
Objective: The aim of this study was to review the state of research on the treatment of CLBP through psychoeducation, including immersive technologies, and to formulate suggestions for psychoeducation in AR for CLBP.
Methods: A scoping review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed in August 2024 by using Livivo ZB MED, PubMed, Web of Science, American Psychological Association PsycINFO (PsycArticle), and PsyArXiv Preprints databases. A qualitative content analysis of the included studies was conducted based on 4 deductively extracted categories.
Results: We included 12 studies published between 2019 and 2024 referring to conventional and VR-based psychoeducation for CLBP treatment, but no study referred to AR. In these studies, educational programs were combined with physiotherapy, encompassing content on pain biology, psychological education, coping strategies, and relaxation techniques. The key outcomes were pain intensity, kinesiophobia, pain catastrophizing, degree of disability, quality of life, well-being, self-efficacy, depression, attrition rate, and user experience. Passive, active, and gamified strategies were used to promote intrinsic motivation from a psychological point of view. Regarding user experience from a software development perspective, user friendliness, operational support, and application challenges were recommended.
In the face of uncontrollable complexity, the concept of a rational design of the organization is being replaced by the notion of an open future that is inherently unpredictable and unplanable. In rapidly changing environments, organizations and leaders are confronted with a constant stream of irritations and unexpected developments, that require ongoing attention. This prompts the question of whether the conceptualization of digital transformation as a paradigm shift also implies the need for new forms of leadership. The article analyzes the discourse on digital leadership and assesses the extent to which this concept relativizes leadership in the context of the evolution of leadership theory, which is characterized by a persistent process of modification and relativization of preceding concepts. Leadership concepts are not only responsive to general needs, but also vary according to specific contexts, such as non-profit leadership or leadership in social welfare organizations and meta-organizations. Results of a discourse analysis, which underscore the significance of adopting a complexity theory perspective on digital leadership, will therefore be contrasted with the initial findings of an empirical study on digitization in such meta-organizations. This allows for a discussion of the general findings on the revitalization of leadership, which will serve as a paradigmatic example of the previously developed context. The article concludes with implications for further theory development with the aim of making a specific contribution to organization-sensitive digitization research. The findings of the empirical study indicate the significance of employing informal structures and a heightened emphasis on subjectivity within meta-organizations, as opposed to the formal structures of organizations. The concept of digital leadership does not signify the obsolescence of traditional leadership; rather, it can be conceptualized as an advanced form of unheroic leadership within the context of external and internal complexity.
Investment theory and related theoretical approaches suggest a dynamic interplay between crystallized intelligence, fluid intelligence, and investment traits like need for cognition. Although cross-sectional studies have found positive correlations between these constructs, longitudinal research testing all of their relations over time is scarce. In our pre-registered longitudinal study, we examined whether initial levels of crystallized intelligence, fluid intelligence, and need for cognition predicted changes in each other. We analyzed data from 341 German students in grades 7–9 who were assessed twice, one year apart. Using multi-process latent change score models, we found that changes in fluid intelligence were positively predicted by prior need for cognition, and changes in need for cognition were positively predicted by prior fluid intelligence. Changes in crystallized intelligence were not significantly predicted by prior Gf, prior NFC, or their interaction, contrary to theoretical assumptions. This pattern of results was largely replicated in a model including all constructs simultaneously. Our findings support the notion that intelligence and investment traits, particularly need for cognition, positively interact during cognitive development, but this interplay was unexpectedly limited to Gf.
Attention in social interactions is directed by social cues such as the face or eye region of an interaction partner. Several factors that influence these attentional biases have been identified in the past. However, most findings are based on paradigms with static stimuli and no interaction potential. Therefore, the current study investigated the influence of one of these factors, namely facial affect in natural social interactions using an evaluated eye-tracking setup. In a sample of 35 female participants, we examined how individuals’ gaze behavior responds to changes in the facial affect of an interaction partner trained in affect modulation.
Our goal was to analyze the effects on attention to facial features and to investigate their temporal dynamics in a natural social interaction. The study results, obtained from both aggregated and dynamic analyses, indicate that facial affect has only subtle influences on gaze behavior during social interactions. In a sample with high measurement precision, these findings highlight the difficulties of capturing the subtleties of social attention in more naturalistic settings. The methodology used in this study serves as a foundation for future research on social attention differences in more ecologically valid scenarios.
Job crafting is the behavior that employees engage in to create personally better fitting work environments, for example, by increasing challenging job demands. To better understand the driving forces behind employees’ engagement in job crafting, we investigated implicit and explicit power motives. While implicit motives tend to operate at the unconscious, explicit motives operate at the unconscious level. We focused on power motives, as power is an agentic motive characterized by the need to influence your environment. Although power is relevant to job crafting in its entirety, in this study, we link it to increasing challenging job demands due to its relevance to job control, which falls under the umbrella of power. Using a cross-sectional design, we collected survey data from a sample of Lebanese nurses (N = 360) working in 18 different hospitals across the country. In both implicit and explicit power motive measures, we focused on integrative power that enable people to stay calm and integrate opposition. The results showed that explicit power predicted job crafting (H1) and that implicit power amplified this effect (H2). Furthermore, job crafting mediated the relationship between congruently high power motives and positive work-related outcomes (H3) that were interrelated (H4). Our findings unravel the driving forces behind one of the most important dimensions of job crafting and extend the benefits of motive congruence to work-related outcomes.
Aims: Fear of physical activity (PA) is discussed as a barrier to regular exercise in patients with heart failure (HF), but HF-specific theoretical concepts are lacking. This study examined associations of fear of PA, heart-focused anxiety and trait anxiety with clinical characteristics and self-reported PA in outpatients with chronic HF. It was also investigated whether personality-related coping styles for dealing with health threats impact fear of PA via symptom perception.
Methods and results: This cross-sectional study enrolled 185 HF outpatients from five hospitals (mean age 62 ± 11 years, mean ejection fraction 36.0 ± 12%, 24% women). Avoidance of PA, sports/exercise participation (yes/no) and the psychological characteristics were assessed by self-reports. Fear of PA was assessed by the Fear of Activity in Situations–Heart Failure (FActS-HF15) questionnaire. In multivariable regression analyses higher NYHA class (b = 0.26, p = 0.036) and a higher number of HF drugs including antidepressants (b = 0.25, p = 0.017) were independently associated with higher fear of PA, but not with heart-focused fear and trait anxiety. Of the three anxiety scores only increased fear of PA was independently associated with more avoidance behavior regarding PA (b = 0.45, SE = 0.06, p < 0.001) and with increased odds of no sports/exercise participation (OR = 1.34, 95% CI 1.03–1.74, p = 0.028). Attention towards cardiac symptoms and symptom distress were positively associated with fear of PA (p < 0.001), which explained higher fear of PA in patients with a vigilant (directing attention towards health threats) coping style (p = 0.004).
Conclusions: Fear of PA assessed by the FActS-HF15 is a specific type of anxiety in patients with HF. Attention towards and being distressed by HF symptoms appear to play a central role in fear of PA, particularly in vigilant patients who are used to direct their attention towards health threats. These findings provide approaches for tailored interventions to reduce fear of PA and to increase PA in patients with HF.