KLUEDO Dokumente/documents https://kluedo.ub.rptu.de/index/index/ Wed, 15 Jul 2026 11:54:43 +0200 Wed, 15 Jul 2026 11:54:43 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13338 A Simplified Mechanical Model for Rocking Structures on Compliant Foundations presents a simplified analytical model for predicting the rocking behavior of freestanding structures resting on compliant (flexible) foundations under seismic loading. Unlike the classical Housner model, which assumes a rigid foundation, the proposed model explicitly incorporates soil–structure interaction (SSI) by representing the foundation with equivalent spring–damper elements. The governing equations are derived using Lagrange's equations, allowing the coupled motion of the structure and the deformable foundation to be described efficiently. The model is validated against detailed LS-DYNA finite element simulations and demonstrates good agreement in predicting rocking response while requiring significantly less computational effort. In addition, the authors propose an empirical relationship for estimating the contact stiffness between the foundation and the supporting soil. The simplified model provides an efficient and practical tool for the seismic analysis and preliminary design of rocking structures on compliant foundations. Baojun Yuan; Mirjam Kloos; Hamid Sadegh-Azar article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13338 Wed, 15 Jul 2026 11:54:43 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13334 Pflegeschulen stehen vor vielfältigen Herausforderungen. Neben dem Fachkräftemangel, der Umsetzung der generalistischen Pflegeausbildung und steigenden organisatorischen Anforderungen verändert insbesondere die Digitalisierung die Zusammenarbeit und das Führungshandeln. Gleichzeitig arbeiten Lehrkräfte mit unterschiedlichen beruflichen Erfahrungen, Qualifikationen und Altersgruppen in den Kollegien zusammen. Vor diesem Hintergrund untersucht die vorliegende Arbeit, welche Führungsstrategien Schulleitungen anwenden, um generationenbedingte Herausforderungen im Kontext der Digitalität zu bewältigen. Zur Beantwortung der Forschungsfrage wurde ein qualitatives Forschungsdesign gewählt. Es wurden leitfadengestützte Experteninterviews mit fünf Schulleitungen sowie ergänzend mit vier Lehrkräften geführt. Die Auswertung erfolgte mithilfe der inhaltlich strukturierenden qualitativen Inhaltsanalyse nach Kuckartz und Rädiker. Die Ergebnisse zeigen, dass generationale Unterschiede im Führungsalltag zwar wahrgenommen werden, von den Befragten jedoch nicht als zentrales Problem beschrieben werden. Wesentlich bedeutsamer sind individuelle Persönlichkeiten, berufliche Erfahrungen sowie unterschiedliche Haltungen gegenüber Veränderungen und Digitalisierung. Erfolgreiches Führungshandeln zeichnet sich insbesondere durch transparente Kommunikation, die Einbeziehung der Lehrkräfte in Entscheidungsprozesse, klare Strukturen sowie eine situationsangemessene Verbindung verschiedener Führungsansätze aus. Dabei finden sich sowohl transformationale als auch distributive Elemente, die je nach Situation unterschiedlich eingesetzt werden. Gleichzeitig wird deutlich, dass Digitalisierung weit über den Einsatz digitaler Technologien hinausgeht und Kommunikations-, Kooperations- und Führungsprozesse nachhaltig verändert. Die Ergebnisse verdeutlichen, dass erfolgreiche Führung in Pflegeschulen nicht auf einen einzelnen Führungsstil zurückgeführt werden kann. Vielmehr zeigt sich, dass eine flexible und situationsangemessene Verbindung verschiedener Führungsansätze geeignet ist, den Anforderungen generationenheterogener Kollegien im Kontext der Digitalität zu begegnen. Daraus werden Handlungsempfehlungen für Schulleitungen abgeleitet, die sowohl die organisationale Entwicklung als auch die Zusammenarbeit in heterogenen Kollegien unterstützen. Maja Althoefer masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13334 Wed, 15 Jul 2026 11:32:54 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13330 This article systematically reviews research on public engagement with models of future developments, such as pandemic forecasting or climate change projections. It examines how different actors and stakeholders interpret (often motivated) and communicate (often strategically) scientific uncertainties. So far, lay decision-makers have been studied mostly as receivers. They can handle uncertainty best when expressed in numbers, such as probabilities. In contrast, communicators often fail to provide such information, partly due to misunderstandings about their audience’s needs. The biggest research gaps concern how scientific uncertainty is portrayed by stakeholders in the public sphere, especially on social media. Signe E. Filler; Berend Barkela; Michaela Maier; Stephan Winter; Christian von Sikorski article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13330 Mon, 13 Jul 2026 18:00:38 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13331 Negativity and positivity are crucial in political information, yet research often overlooks positive content consumption. This study examines the degree to which citizens consume positive and negative election-related content and the factors influencing both. Using web-tracking and experience sampling (mobile intensive longitudinal linkage analysis [MILLA]) data from the 2021 German federal election, we find positivity and negativity are equally relevant but vary across channels and methods of data collection. In tracking data, gender and conflict approach predict valence preference, while MILLA data highlight perceived duty, extreme ideology, and conflict approach. Possible interpretations of these systematic differences and their general relevance for communication research are discussed. Michaela Maier; Jürgen Maier; Lea C. Gorski; Felix Schmidt article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13331 Mon, 13 Jul 2026 14:38:36 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13333 Die vorliegende Masterarbeit untersucht das Potenzial des Integrierten Wasserressourcen-Managements (IWRM) als Instrument der Konfliktprävention in der nachhaltigen Entwicklungszusammenarbeit am Beispiel des Nigerflussbeckens. Grundlage der qualitativen Fallstudie bilden theoretische Ansätze des Wasser- und Konfliktmanagements sowie Konzepte der Wassergovernance und grenzüberschreitenden Zusammenarbeit. Darauf aufbauend werden die regionalen Rahmenbedingungen des Nigerflussbeckens, die institutionellen Strukturen sowie ausgewählte Kooperationsprojekte analysiert, um die Potenziale und Grenzen des IWRM für die Konfliktprävention zu untersuchen und Handlungsempfehlungen für die Entwicklungszusammenarbeit abzuleiten. Kathrin Hofer masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13333 Mon, 13 Jul 2026 11:22:31 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9074 Alina Ouissa doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9074 Mon, 13 Jul 2026 09:12:04 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13327 This dissertation examines when and how social media influencers become politically relevant communicators. It distinguishes between influencers who primarily emerge from lifestyle contexts and only sometimes address politics, and those who consistently explain and comment on public affairs. The central argument is that these actors do not become politically consequential in the same way. While some may depend more strongly on relationship-based bonds, others depend more strongly on visible guidance and explanation. To capture these dynamics, the dissertation conceptualizes influencers as communicators who combine personal proximity with functions of orientation and guidance. It also asks a broader normative question: not only whether audiences see influencers as politically relevant, but also whether this relevance is justified in epistemic terms. Across three manuscripts, the dissertation develops a cumulative account of these dynamics. The first shows that political relevance is not evenly distributed, but concentrated especially among politically engaged social media users. The second shows that factual learning depends primarily on the substance of the content, whereas feeling informed is shaped not only by content but also by who delivers it. The third shows that participation-related effects depend more strongly on relational closeness, with parasocial relationships acting as an important moderator. Taken together, the dissertation shows that influencers matter politically in different ways for different audiences and outcomes. Its contribution lies in explaining these differences systematically. That is, by distinguishing influencer types, by outlining that relational closeness and opinion leadership could matter differently across outcomes, and by embedding these findings in a broader framework that considers not just political influence, but also the quality of that influence. Pascal Merz doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13327 Wed, 08 Jul 2026 17:39:54 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13326 Der demografische Wandel, die Deindustrialisierung und ein struktureller wirtschaftlicher Wandel stellen viele (Groß-)Städte in u. a. Europa und Nordamerika vor tiefgreifende Herausforderungen. Schrumpfende Großstädte, die über Jahrzehnte von einzelnen Leitindustrien geprägt waren, kämpfen heute mit Arbeitsplatzverlusten, Leerständen, einem Rückgang der Bevölkerungszahlen und sinkender kommunaler Finanzkraft. Vor diesem Hintergrund rücken Smart-City-Ansätze als mögliche Instrumente der Stadtrevitalisierung zunehmend in den Fokus von Forschung und Praxis. Die vorliegende Arbeit untersucht, inwiefern Smart-City-Ansätze einen Beitrag zur Revitalisierung schrumpfender Städte leisten können und wie sie in bestehende stadtentwicklungspolitische Strukturen integriert werden. Die theoretische Grundlage der Arbeit bildet eine systematische Aufarbeitung der Konzepte von strukturschwächebedingter Stadtschrumpfung, Revitalisierung in der Stadtentwicklung und Smart City. Dabei wird herausgearbeitet, dass Smart Cities nicht ausschließlich technologische Modernisierungsprojekte sind, sondern als ganzheitliche Strategie(n) verstanden werden müssen, die die ökonomischen, sozialen und ökologischen Dimensionen der Stadtentwicklung verbinden. Digitale/smarte Technologienwerden hierbei als Mittel gesehen,umProzesse effizienter, transparenter und partizipativer zu gestalten. Zur empirischen Überprüfung dieser Annahmenwerden zwei Fallbeispiele (Gelsenkirchen (Deutschland) und Cincinnati (USA)) vergleichend untersucht. Beide Städte sind von einer Deindustrialisierung, einem starken Bevölkerungsrückgang und einem wirtschaftsbedingten Strukturwandel betroffen, haben aber unterschiedliche institutionelle und politische Rahmenbedingungen. Mittels qualitativer Methoden, insb. Dokumentenanalysen und leitfadengestützten Expertinnen- und Experteninterviews, werden Strategien und Projekte in den zentralen Handlungsfeldern Smart Living, Smart Economy und Smart Governance analysiert. Die Ergebnisse zeigen, dass Smart-City-Ansätze in schrumpfenden Großstädten v.a. dann Wirkung entfalten, wenn sie an bestehende Revitalisierungsprozesse anschließen und die lokale Bevölkerung aktiv eingebunden wird. In Gelsenkirchen steht dabei v.a. die kommunal getragene Digitalisierung im Mittelpunkt, bspw. in Form von Open-Data-Portalen, Beteiligungsplattformen und intelligenten Infrastruktursystemen. Damit soll u.a. das Verwaltungshandeln modernisiert und die Bürgerinnen und Bürger stärker in Planungsprozesse einbezogen werden. In Cincinnati hingegen basieren die Smart-City-Ansätze stärker auf einer Public-Private-Partnership-Logik, die durch universitäre Kooperationen, privatwirtschaftliche Innovationsnetzwerke und zivilgesellschaftliche Initiativen geprägt ist. Hier fungieren digitale Instrumente als Katalysator für wirtschaftliche Diversifizierung und soziale Innovation. Die vergleichende Analyse macht deutlich, dass Smart-City-Ansätze das Potenzial besitzen, Schrumpfungsprozesse in neue (Stadt-)Entwicklungsdynamiken zu überführen. Entscheidend hierfür ist jedoch, dass technologische Innovationen nicht isoliert, sondern in Verbindung mit Governance-, Beteiligungs- und Lernprozessen umgesetzt werden. Wo Smart-City-Maßnahmen als Teil einer übergeordneten Revitalisierungsstrategie verstanden werden, können sie zur Stärkung der urbanen Resilienz, zur Verbesserung der Lebensqualität und zur Förderung von Bürgerpartizipation, sprich zur Revitalisierung strukturschwacher und schrumpfender Städte, beitragen. Abschließend lässt sich festhalten, dass Smart-City-Konzepte allein keine umfassende Antwort auf den strukturellen Wandel bieten (können), aber durchaus neue Wege für eine nachhaltige, lernendeundkooperative Stadtentwicklung eröffnen. Ihre Wirksamkeit hängt dabeiwesentlich von der institutionellen Einbettung, intersektoralen Kooperationen und der Fähigkeit der Städte ab, digitale Innovationen mit sozialer Verantwortung zu verbinden. Die Arbeit leistet damit einen Beitrag zur Debatte um die Zukunft schrumpfender Städte und zeigt, wie Smart-City-Ansätze als Teil integrierter Revitalisierungsstrategien genutzt werden (können). Jakob Schackmar doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13326 Mon, 06 Jul 2026 09:27:51 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13282 Pesticides are widely used in modern agriculture and have been linked to insect decline and biodiversity loss. They enter freshwater systems via various pathways, such as spray drift and surface runoff. Small streams are a widely distributed type of freshwater ecosystem, which are typically characterized by an adjacent riparian zone that is subject to frequent flooding. As part of this aquatic-terrestrial transition zone, riparian zones are considered biodiversity hotspots. Yet, the possibility of flood mediated pesticide transfer into these ecosystems remains largely unexplored, particularly with respect to varying flooding regimes and the potential for trophic propagation within riparian food webs. Furthermore, climate change is projected to increase the frequency and intensity of flooding events, potentially amplifying the flood-mediated pesticide transfer. This thesis investigated the flood-mediated pesticide transfer at three experimental scales. Organic pesticides were analysed by high-performance liquid chromatography tandem to triple quadrupole mass spectrometry. In a mesocosm experiment, the detection of six pesticides in previously unflooded soil following repeated flooding events demonstrated the occurrence of the flood-mediated pesticide transfer. Further, pesticide concentrations in riparian soils increased both with repeated flooding and longer flooding durations. A field study, conducted in small to medium sized streams, confirmed the occurrence of the flood-mediated pesticide transfer into riparian soils, with subsequent uptake and accumulation of flood-borne pesticides observed in riparian plants. Finally, a climate chamber experiment investigated the uptake of 31 pesticides from floodwaters into the root-zone soil of stinging nettle (Urtica dioica) and their subsequent accumulation in stinging nettles and aphids. Across all studies, riparian soils acted as sinks for flood-borne pesticides, with accumulation increasing with both flooding frequency and duration. Riparian plants bioaccumulated these pesticides and transferred them further into higher trophic levels. In aphids feeding on contaminated stinging nettles approximately half the pesticides present in floodwater were detected, with evidence of biomagnification for selected compounds. These findings demonstrate that pesticides can infiltrate the riparian food web via flooding. With climate change projected to intensify flooding events, especially in small streams, this exposure pathway may become increasingly relevant. Moreover, the flood-mediated pesticide transfer described in this thesis is only one of many exposure pathways that reach riparian zones, with potential consequences to the riparian food-web and functionality of the riparian ecosystem. Franziska Anna Fiolka doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13282 Thu, 02 Jul 2026 16:26:01 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13283 The BLM helicase is a critical genome maintenance protein in v olv ed in div erse cellular processes including DNA replication, repair, transcription, and chromosome segregation. During mitosis, it cooperates with the PICH helicase and topoisomerases to resolve ultrafine DNA bridges (UFBs)—nonchromatinized DNA str uct ures that link sister chromatids—through a mechanism that is not yet fully understood. Here, we tagged endogenous BLM and PICH with fluorescent proteins and BLM with an auxin-inducible degron to generate a cell model system that enables temporal tracking of UFB dynamics in the presence or absence of BLM. Time-resolved lattice light sheet microscopy established the dynamic localization patterns of BLM and PICH throughout the cell cy cle. While BLM cy cles betw een PML bodies and DNA repair foci in interphase, these str uct ures disappear at the mitotic entry, and BLM then re-associates with chromatin during anaphase to UFBs as well as to CENP-B- positive mitotic foci. Acute BLM depletion during mitosis increased the fraction of unresolved UFBs, micronuclei containing acentric fragments, binucleation, and resulted in subtle genomic abnormalities detected by single-cell whole genome sequencing. These findings highlight a mitosis- specific role for BLM in UFB resolution and underscore its function in preserving genomic stability. Tamara Eleanore Hamann; Angela Wieland; Farbod Mohensi; Kruno Vukušić; Andrea Tirincsi; Rene Wardenaar; Marialucrezia Losito; Iris Harmsen; Ipek Ilgin Gönenc; Bernd Wollnik; Floris Foijer; Iva M. Tolić; Zuzana Storchová; Markus Räschle article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13283 Thu, 02 Jul 2026 13:17:35 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13268 Recent progress in generative artificial intelligence, particularly in large language models (LLMs), has enabled significant advances in natural language processing across many application areas. In expert-oriented systems, however, these models continue to exhibit critical limitations, including hallucinated content, factual inaccuracies, and reduced robustness when applied to specialized or technical domains. Retrieval-Augmented Generation (RAG) has emerged as a promising approach to mitigate these issues by explicitly grounding model outputs in external knowledge sources. This thesis examines the design and empirical evaluation of a modular RAG pipeline intended for expert applications such as technical documentation assistance and process automation. The work specifically investigates whether combining multiple retrieval modalities ranging from dense vector-based retrieval to graph-based symbolic reasoning can improve the factual grounding, relevance, and explainability of generated responses. Particular attention is paid to how different retrieval strategies affect downstream generation quality in real-world technical settings. The architecture integrates interchangeable retrieval components, context augmentation strategies, and transformer-based language models, enabling systematic comparison across multiple retrieval configurations. An iterative design and evaluation methodology is adopted, encompassing architectural analysis, implementation of retrieval and generation modules, and performance assessment on domain-specific datasets. Evaluation is conducted using automated metrics, with a focus on faithfulness and contextual relevance as measured by the RAGAS framework. The results provide practical insights into when and how retrieval augmentation improves expert-oriented text generation. In particular, the findings highlight the importance of retrieval quality, effective filtering, and modular system design for building reliable, transparent, and deployable RAG-based AI expert systems. Irfhanna Ameer Bahadur Ibrahim Kalifullah masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13268 Fri, 26 Jun 2026 11:45:46 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13267 This cumulative dissertation is composed of five individual research papers that focus on request acceptance and scheduling decisions in different operations research environments. Fundamentally, this work studies the Capacitated Profitable Tour Problem (CPTP), a routing optimization problem in which a subset of requests is selected to maximize total profit while respecting vehicle capacity constraints and visiting their associated locations. In this background, coordinated scheduling of accepted requests can induce nonlinear cost effects, as routing costs generally do not scale proportionally with the distances between locations. On the one hand, the CPTP is studied in dynamic and stochastic sequential decision-making environments, where decisions are made over time under uncertainty. On the other hand, static and deterministic variants of the CPTP are considered to provide insights into optimal policies and ex-post solutions derived under full information. Furthermore, different subtour elimination constraints are analyzed for their computational efficiency in solving the CPTP. Regarding problem extensions, the impact of allowing split deliveries and incomplete services in the CPTP is investigated in detail. In addition to studying the CPTP, this dissertation introduces the dynamic and stochastic multidimensional knapsack problem with a generalized upper bound, in which item classes arrive sequentially under uncertainty, and at most one item from each arriving class may be accepted to schedule resource consumption. Methodologically, this dissertation develops Markov decision process formulations and mixed-integer linear programming formulations for various request acceptance and scheduling problems. Based on these formulations, optimal, approximate, and heuristic policies are derived to solve the corresponding problems. Building on recent advances in machine learning, extensive computational experiments on well-established benchmark datasets demonstrate the strong potential of reinforcement learning and value function approximation methods for dynamic and stochastic decision-making in request acceptance and scheduling environments. In addition to advancing the academic literature through the development of new models, solution methods, applications, and results, this dissertation makes a practical contribution by releasing open-source software implementations of model formulations and proposed solution methods. Marvin Caspar doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13267 Fri, 26 Jun 2026 08:07:59 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13264 In this thesis, we study the problem of optimizing data processing in database systems using learned models. As data volumes increase and datasets become structurally complex, classical database components struggle to exploit underlying data distributions, resulting in suboptimal performance and excessive memory usage due to their rigid designs. Advances in machine learning offer an opportunity to rethink the database operations as predictive tasks that capture complex correlations and provide compact representations. However, integrating them into database systems poses significant challenges, including reasoning over complex data, controlling model size and inference, and generating representative training and evaluation workloads. To address the challenges, we first introduce a memory-efficient learned index for metric data that supports point, range, and nearest-neighbor queries. The index projects points into a learned one-dimensional ordering using distance-based transformations. For high-dimensional categorical inputs where learned models struggle to remain compact, we propose a compressed learned Bloom filter. By partitioning attributes based on value distributions, the compression reduces embedding size and memory usage while preserving accuracy and provides a foundation for compressing other approaches proposed in this thesis. We further propose supervised and unsupervised estimators for cardinality estimation in knowledge graphs to handle complex subgraph patterns and their correlations, enabling accurate predictions with low memory overhead. For collections of variable-size sets, we design permutation-invariant models that support indexing, membership, and cardinality estimation by combining compression with the hybrid integration of learned and classical components. Finally, to address the scarcity of representative training workloads, we explore generative models for automated workload synthesis and compensate for their limitations in producing selectivity-constrained queries. These models produce diverse, semantically meaningful query workloads, reducing bias and mitigating cold-start issues. Angjela Davitkova Gjurovska doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13264 Fri, 26 Jun 2026 07:58:56 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13263 In this work, \(^{183}\text{W}\), \(^{195}\text{Pt}\), \(^{199}\text{Hg}\) and \(^{207}\text{Pb}\) NMR chemical shifts of small test molecules were calculated using relativistic four- and two-component quantum chemical methods. At first, basis set convergence studies were carried out. For this, Dyall's all-electron Gaussian-type basis set dyall.aexz (x = 2, 3, 4) with relativistically optimised exponents was successively augmented in the series dyall.ae2z \(\rightarrow\) dyall.ae3z \(\rightarrow\) mixed \(\rightarrow\) dyall.ae4z. The mixed basis employs dyall.ae4z for the heavy metal atom whose NMR chemical shift is to be calculated and dyall.ae3z for all other atoms. It could be shown that NMR shielding constants and chemical shifts exhibit a different basis set convergence behaviour: For NMR shielding constants, basis set convergence occurs with the mixed basis set. Contrary to this, for NMR chemical shifts, converged values are already obtained by applying dyall.ae3z because the changes in NMR shielding constants when going from dyall.ae3z to the mixed basis are nearly constant and hence, they almost completely cancel each other upon calculation of the NMR chemical shift. Next, the influence of the XC functionals SVWN5 (LDA), BP86, PBE, KT3 (GGAs), B3LYP, PBE0 and PBE38 (hybrids) on the NMR chemical shift was investigated. It could be demonstrated that in the series LDA \(\rightarrow\) GGA \(\rightarrow\) hybrid, the calculated NMR chemical shifts become more positive (low-field shift) while at the same time, the agreement with experimental values gets significantly improved. Furthermore, a low-field shift can also be observed with increasing amount of HF exchange in the XC functional. Moreover, the latter one is a more dominant factor than the specific choice of an XC functional. Finally, the hybrid PBE38 is the most reliable XC functional for an accurate prediction of \(^{183}\text{W}\), \(^{195}\text{Pt}\), \(^{199}\text{Hg}\) and \(^{207}\text{Pb}\) NMR chemical shifts. Apart from this, the specific choice of a magnetic balance condition (UKB versus RMB) in a fully relativistic four-component theory has virtually no effect on the computed NMR chemical shift. Likewise, it hardly makes a difference whether the SNSO or the mSNSO correction is used in an X2C method. Additionally, it could be revealed that the X2C-mSNSO approach represents a reasonable approximation to the fully relativistic four-component Dirac-Coulomb-Hamiltonian. In this work, an investigation of solvent effects is restricted to the mercury test molecules. It turns out that COSMO solvation effects on the \(^{199}\text{Hg}\) NMR chemical shift are rather small while COSMO geometrical effects drop out to be even less. To minimise the deviations of the calculated \(^{199}\text{Hg}\) NMR chemical shifts from experiment, it is important to take the solvent explicitly into account. A combined treatment of explicit and implicit solvation effects (COSMO-NMR computations on solute-solvent complexes) further improves the experimental agreement of calculated results. For the mercury molecules studied in this work, the best agreement of computed \(^{199}\text{Hg}\) NMR chemical shifts with experiment is achieved by performing COSMO-NMR calculations on DFT-D3/B3LYP optimised solute-solvent complexes with three solvent molecules at the DFT/PBE38 level of theory employing the relativistic exact two-component X2C-mSNSO approach together with the basis set dyall.ae3z. Finally, this work shall serve as basis for further investigations: It is crucial to extend relativistic NMR calculations to larger sets of test molecules but also to other heavy metal atom nuclei than \(^{183}\text{W}\), \(^{195}\text{Pt}\), \(^{199}\text{Hg}\) or \(^{207}\text{Pb}\) to gain more experience in the prediction of heavy metal atom NMR chemical shifts! Marcel Lechner doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13263 Fri, 26 Jun 2026 07:50:10 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13213 Die vorliegende Masterarbeit untersucht das bislang wissenschaftlich nicht systematisch ausgearbeitete Phänomen des „Migrationskitsches“ als ästhetische Praxis innerhalb der deutschen Einwanderungsgesellschaft. Ausgehend von der Frage, inwiefern Migrationskitsch Machtstrukturen und gesellschaftliche Ungleichheiten sichtbar macht und zugleich stabilisiert, wird der Begriff theoretisch fundiert und begrifflich präzisiert. Die Untersuchung basiert auf einer hermeneutisch-analytischen Literaturarbeit und verbindet Ansätze aus der Kitsch- und Ästhetikforschung mit migrations-, macht- und differenztheoretischen Perspektiven. Unter Rückgriff auf unter anderem Adorno, Bourdieu, Rancière, Foroutan und Bartels wird gezeigt, dass migrationsbezogene Darstellungen häufig komplexe soziale Realitäten affektiv verdichten, moralisch aufladen und in vereinfachte Narrative überführen. Diese können sowohl innerhalb migrantischer Communities identitätsstiftende und erinnerungskulturelle Funktionen erfüllen als auch in der Mehrheitsgesellschaft zur Stabilisierung von Differenzordnungen und Deutungshoheiten beitragen. Migrationskitsch wird dabei als analytischer Begriff verstanden, der weder mit rassistischen noch mit populären Darstellungsformen gleichzusetzen ist, sondern die Verschränkung von Ästhetik, Wahrnehmung und Macht sichtbar macht. Abschließend diskutiert die Arbeit die Potenziale inklusiver ästhetischer Bildung für die kritische Reflexion gesellschaftlicher Bewertungsordnungen und eröffnet Perspektiven für weitere Forschung. Carolin Denter masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13213 Thu, 25 Jun 2026 11:28:09 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13255 On the one hand, this work introduces concepts facilitating a more expressive and efficient system timing analysis. On the other hand, it introduces schemes for ensuring that the system stays within its operational bounds, such as execution time envelopes under resource contention and does so in the presence of power and thermal restrictions. Kai Lampka habilitation https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13255 Wed, 24 Jun 2026 12:03:20 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13259 In this dissertation, we study the challenges of performing end-to-end timing analysis in safety-critical real-time systems with multi-rate cause-effect chains and multi-core architecture. The main contribution of this dissertation consists of proposing methods to verify and improve the end-to-end latencies of safety-critical real-time applications with tasks applying the Logical Execution Time (LET) communication paradigm. Evaluations using automotive benchmarks and synthetic task sets show the benefits of our methods under different end-to-end latency metrics such as reaction time and data age. Luiz Gonzaga Nunes Maia Neto doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13259 Wed, 24 Jun 2026 11:09:26 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13256 Organizational routines are central to understanding how work is accomplished and transformed in contemporary organizations. This cumulative dissertation, situated in the field of organization theory and grounded in routine dynamics research, explores how agility unfolds through the enactment of routines. Across four dissertation papers, it advances a processual understanding of how organizational phenomena evolve through the enactment of agile routines. The first paper conceptualizes agility as an emergent property of repeated routine performance. Drawing on routine dynamics, it theorizes how frequency and variation in agile routines generate adaptability over time, showing that becoming agile is a process rather than a state. The second paper extends this perspective to the educational context. Based on qualitative case data from agile learning routines, it identifies mechanisms of expansion and contraction that shape learning paths, demonstrating how agility in education is enacted through those recursive dynamics. The third paper connects routine dynamics with Strategyas-Practice research. It theorizes how mundane routines acquire strategic significance through “strategic connection work” – revealing strategizing as a distributed and emergent process. The fourth paper introduces the notion of truce dynamics to explain how tensions are articulated, contested, and absorbed within the everyday organizing of an agile team, and how truces are negotiated in a spiral process. Taken together, this dissertation contributes to organizational theory in four ways: (1) by further explaining agility through a routine dynamics lens; (2) by advancing a strong process ontology in organization studies that captures how stability and change co-emerge in situated action; (3) by connecting routines performances across enactments, and (4) by linking microlevel routine performances to macro-level organizational outcomes to show how local, situated actions collectively produce organizational phenomena. Kathrin Lemm doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13256 Tue, 23 Jun 2026 11:11:00 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13229 Designing magnetic sensor modules is a complex process often relying on simulation to avoid costly and time-consuming prototypes. However, existing simulation tools are typically generic, leading to key limitations: magnetic field data cannot be exported for detailed analysis, interfaces are overloaded with unnecessary features while lacking essential ones, and resource demands are unnecessarily high. To address these drawbacks, we have developed a dedicated software solution at RPTU University Kaiserslautern-Landau that combines functionality, intuitiveness, computational efficiency, and openness. Users can define geometric and material properties through an intuitive interface, with all process data, including sensor signals and magnetic field distributions, available for in-depth analysis. The modular architecture enables easy integration of custom sensors, streamlining the development of new magnetic sensor designs. The software is open-source, written in Python, freely available on GitHub, and can be extended without restrictions. Tim Becker; Claudia Glenske; Lukas Rauber; Jörg Seewig article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13229 Fri, 19 Jun 2026 12:22:21 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13216 Amtliche Bekanntmachung der RPTU Nr.6/18.06.2026 periodicalpart https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13216 Thu, 18 Jun 2026 08:37:30 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13211 Floating-point numbers often represent real numbers in computer systems. They are applicable in many domains, including embedded systems, machine learning, and scientific computing. Despite their widespread use, they pose some difficulties. Floating-point numbers and operations typically suffer from roundoff errors, making computations over floating-points inaccurate with respect to a real-valued specification. Moreover, the IEEE 754 floating-point standard, a fundamental element in formalizing floating-point arithmetic for today’s computers, presents additional challenges due to special values and resulting unintuitive behaviors. This thesis has three main contributions that address existing gaps in automated reasoning about floating-point arithmetic, making it easier for developers and researchers to understand, verify, and trust the floating-point computations in their programs. First, we introduce the first floating-point support in a deductive verifier for the Java programming language. Our support in the KeY verifier automatically handles floating-point arithmetic and transcendental functions. We achieve this with a combination of delegation to external SMT solvers on one hand, and rule-based reasoning within KeY on the other, exploiting the complementary strengths of both approaches. As a result, this approach can prove functional floating-point properties for realistic programs. Second, inspired by KeY’s treatment of method calls and the need for a scalable roundoff error analysis, we present the first modular optimization-based roundoff error analysis for non-recursive procedural floating-point programs. Our key idea is to achieve modularity while maintaining reasonable accuracy by automatically computing procedure summaries that are a function of the input parameters. Technically, we extend an existing optimization-based roundoff error analysis and show how to effectively use first-order Taylor approximations to compute precise procedure summaries, and how to integrate those to obtain end-to-end roundoff error bounds. Third, our experience using SMT solvers to discharge KeY’s floating-point verification conditions revealed unexpected performance behavior, motivating a systematic study of floating-point reasoning in SMT solvers. We propose a metamorphic testing approach that uses semantics-preserving rewrite rules, focusing on floating-point special values, to uncover unexpected performance behavior in SMT solvers’ handling of floating-point formulas, such as an increase in solving time when the SMT queries are simplified. Using real-world test inputs, our approach can identify such performance bugs for every SMT solver tested. Rosa Abbasi doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13211 Tue, 16 Jun 2026 12:04:50 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13189 Modern society increasingly depends on visual inspection systems that must operate reliably in high-stakes environments where mistakes have serious consequences. This dissertation addresses challenges in applied computer vision: developing automated systems that match or exceed human visual judgment while providing the interpretability, efficiency, and robustness required for real-world deployment across vastly different scales and domains. Two critical areas are investigated where rapid, accurate visual assessment can mean the difference between safety and catastrophe. In manufacturing, the failure of protective thin-film coatings can lead to catastrophic equipment breakdown, yet current quality control relies on subjective human interpretation that creates bottlenecks and inconsistent standards. In humanitarian disaster response, building damage assessment is dangerous and time-consuming, creating critical delays when rapid resource allocation can save lives. These disparate problems share fundamental challenges that have resisted automation: limited annotated training data, the need for interpretable results experts can trust, and operation under resource constraints. Existing models often fail outside controlled conditions, particularly in developing regions where Western-trained models do not generalize to local materials and architectural styles. The dissertation demonstrates that problems orders of magnitude apart in spatial scale—micrometer-level surface defects to meter-scale building damage can be addressed through similar methodological approaches. For industrial applicationsfully automated quality control systems eliminate human subjectivity while providing more detailed and consistent assessment, transforming quality assurance into an integrated component of smart manufacturing compatible with Industry 4.0. For disaster response, rapid assessment using drone imagery can be deployed immediately after disasters, even where infrastructure is limited, providing standardized damage classifications that enable efficient resource allocation and faster relief coordination for Sub-Saharan African architecture that existing models cannot handle. Beyond validating a practical approach, the research yields insights into building robust computer-vision systems for high-stakes applications. Key findings demonstrate that unified approaches emphasizing feature interpretability, architectural efficiency, and systematic handling of class imbalance can bridge the gap between laboratory prototypes and production-ready systems. Damjan Hatić doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13189 Tue, 16 Jun 2026 11:48:07 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13212 Nuclear magnetic resonance (NMR) spectroscopy is a versatile analytical technique that enables noninvasive, quantitative measurements of chemical processes and transport phenomena without calibration. In chemical engineering, three practical barriers have so far restricted its wider use: prohibitively long measurement times, insufficient sensitivity of low-gyromagnetic-ratio nuclei such as 13C NMR, and the difficulty of performing quantitative analysis under continuous-flow. This dissertation addresses all three barriers by combining targeted applications and methodological developments, with a particular focus on paramagnetic relaxation enhancement (PRE) as a strategy for improving sensitivity and accelerating measurements. The first part investigates the chemical reactivity of hydrogen sulfide (H2S) in aqueous amine solutions relevant to industrial sour~gas treatment. Quantitative 1H and 13C NMR spectroscopy demonstrate that H2S leads to protonation of the amines without forming additional reaction products. These results provide experimental validation for assumptions commonly used in thermodynamic models for the design and simulation of sour gas reactive absorption processes. The second part addresses the determination of self-diffusion coefficients of synthetic fuels by pulsed-field-gradient (PFG) NMR spectroscopy over a broad temperature range. The resulting dataset serves as valuable input for the development of an entropy-scaling approach, thereby enhancing predictive capabilities for mass transport properties. The third part focuses on overcoming limitations of benchtop NMR spectroscopy under continuous-flow conditions. Although compact instruments are attractive for process monitoring, the low sensitivity of 13C nuclei and insufficient polarization build-up restrict their applicability at high flow rates for quantitative analysis. Introducing PRE via a synthesized immobilized PRE agent, enables quantitative 13C NMR measurements of mixtures at high flow rates by significantly reducing the spin-lattice relaxation time T1. Finally, a novel concept for accelerating NMR experiments is introduced. By spatially decoupling PRE from the detection region and shuttling the sample during the inter-scan delay, rapid polarization buildup is achieved under stagnant measurement conditions. This strategy reduces 13C NMR measurement times by one order of magnitude while maintaining spectral quality and quantitative accuracy. Together, these contributions advance NMR spectroscopy as a practical tool for chemical engineering, enabling faster measurements, more reliable quantitative analysis, and improved experimental data for the modeling and monitoring of industrial processes. Sarah Mross doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13212 Tue, 16 Jun 2026 11:34:12 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13196 Subject teaching and learning are hardly possible without language competence; teachers are therefore required to conceptualize subject lessons in a language-aware manner. Many universities in Germany respond by offering additional modules or integrating language support into subject didactics—often without accompanying empirical research. This study examines pre-service teachers’ understanding of Linguistically Sensitive Subject Teaching and academic language, as well as factors influencing this understanding in the context of university teach¬ing, including both learning and individual beliefs. Different conceptual knowledge bases lead to diverging under¬standings of these concepts among pre-service teachers. Zuzana Münch-Manková; Juliane Müller de Acevedo contributiontoperiodical https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13196 Mon, 15 Jun 2026 13:32:45 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13205 Schon das frühe Vorlesen mit dem kleinen Kind gilt zahlreichen Studien zufolge als „ideale Sprachlernsituation“ (Snow & Ninio 1986; Ulich 2003; Becker 2019) zugleich als eine der ersten ‚Literacy‘-Erfahrungen. Dieser Beitrag konzentriert sich auf gemeinsame Rezeptionssituationen von Mutter und Kind zum (gereimten) Bilderbuchklassiker „Das kleine Blau und das kleine Gelb“ von Lionni (1959/1962). Leitfrage dabei ist, auf welche Weise kontinuierliches vorschulisches Vorlesen sprachlichliterale und imaginative Fähigkeiten fördern kann. Petra Wieler contributiontoperiodical https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13205 Mon, 15 Jun 2026 13:16:41 +0200