KLUEDO Dokumente/documents https://kluedo.ub.rptu.de/index/index/ Thu, 16 Apr 2026 12:33:15 +0200 Thu, 16 Apr 2026 12:33:15 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13045 The next-generation radio access network (NG-RAN) architecture has been standardized by the Third Generation Partnership Project (3GPP) as the radio access network (RAN) architecture for fifth-generation (5G) mobile networks. It consists of a set of next-generation NodeBs (gNBs). Each gNB is composed of a centralized unit (CU), at least one distributed unit (DU), and at least one radio unit (RU). These components of a gNB can be deployed as virtual network functions (VNFs) and/or physical network functions (PNFs). In this thesis, we consider the CU and the DU as VNFs and the RU as a PNF. The CU, DU, and RU can be mapped onto the underlying aggregation data center, edge data center, and cellular network site in the NG-RAN architecture, respectively. The Open Radio Access Network (O-RAN) Alliance has redefined the NG-RAN architecture by establishing open and standard-compliant interfaces. The architecture defined by the O-RAN Alliance, known as the O-RAN architecture, comprises several components that interoperate to create a flexible, cloud-based RAN for 5G and beyond. In addition to the components specified by 3GPP for NG-RAN, the O-RAN Alliance introduces a new component for the management and orchestration of O-RAN elements. This component is referred to as the service management and orchestration (SMO) framework. The SMO framework is responsible for deploying and operating RAN services and coordinating the various O-RAN components. It includes a non-real-time RAN intelligent controller (Non-RT RIC) and can incorporate components from other standards-developing organizations (SDOs). Moreover, the O-RAN architecture features the near-real-time RAN intelligent controller (Near-RT RIC), which performs tasks within a near-real-time time frame. The Near-RT RIC, along with other gNB functions, can be mapped onto the underlying infrastructure. This infrastructure includes open-cloud (O-Cloud) sites, which provide the cloud environment for hosting these functions. The O-Cloud also features a notification interface for receiving relevant events. Overall, the O-RAN architecture aims to enhance flexibility, interoperability, and cloud-native capabilities in the deployment and operation of RAN systems, thereby supporting the evolution of 5G and beyond. The mapping of VNFs onto the underlying physical network infrastructure at the edge of a cellular network is a challenging task due to the joint allocation of virtual compute, storage, and networking resources across nodes and links, the diverse technical requirements of end users, and the need for coordination across multiple host domains. This issue is further complicated by the provisioning of RAN slicing, given the varying characteristics of wireless communication channels. To this end, this thesis addresses the mapping and virtual resource allocation problems of the VNFs of RAN slice subnets onto the underlying intelligent network infrastructure in NG-RAN. In this context, unlike most prior proposals that often fail to meet performance objectives and overlook resource allocation constraints, this thesis introduces and employs automation and intelligent techniques to map VNFs onto their corresponding physical nodes, with the aim of achieving improved efficiency in virtual resource utilization while ensuring the performance of RAN slice subnets in NG-RAN. Adopting a top-down approach, the key contributions of this thesis are as follows: • extend the framework of network slicing, as defined by the Next Generation Mobile Networks (NGMN) Alliance, to the NG-RAN architecture, and provide a critical analysis and overview of the components and functionalities of different types of RAN slices; • integrate the Experiential Network Intelligence (ENI) framework, as proposed by the European Telecommunications Standards Institute (ETSI), into a joint architecture of network functions virtualization--management and orchestration (NFV--MANO), also proposed by ETSI, and the Third Generation Partnership Project network slicing management system (3GPP-NSMS), in order to introduce automation and intelligence into the management and orchestration of different types of RAN slices in NG-RAN; • propose a learning-assisted solution (consisting of three phases: virtual resource automation, virtual resource management, and virtual resource allocation) for mapping the VNFs of a RAN slice subnet onto the underlying intelligent data centers in NG-RAN; • unify the management and orchestration components of 3GPP, ETSI, and the O-RAN Alliance within the SMO framework to enhance the unification and interoperability of various standard-compliant interfaces within the O-RAN architecture; • integrate management data analytics (MDA) into the management systems of 3GPP, ETSI, and the O-RAN Alliance within the SMO framework, with the goal of introducing intelligence and automation into the functionalities of the SMO framework for managing and orchestrating O-RAN components; • explore several deployment scenarios for integrating MDA and automation into the SMO framework, thereby providing network operators with multiple deployment options for enabling intelligence within the SMO framework; • present a comprehensive system model based on which the mapping problem of the CU and DU, internal and external VLs, and the VNFs of a RAN slice subnet onto the underlying infrastructure is mathematically formulated; • discuss various types of machine learning (ML)-assisted algorithms, such as supervised, unsupervised, and reinforcement learning, with a particular focus on the mathematical background and application of reinforcement learning, and select the Q-learning algorithm to solve the VNF mapping problem; • describe the simulation environment (including the simulation setup, network topology, and simulation parameters) considered for simulating the virtual components involved in mapping different types of RAN slices in NG-RAN; • obtain simulation results using the Q-learning algorithm for the mapping of RAN slice subnets, demonstrating significant performance improvements in mapping various types of RAN slice subnets onto the underlying infrastructure under different conditions; • evaluate the performance objectives achieved using the Q-learning algorithm against the service level agreement (SLA); and • provide findings on the global resource allocation required to host a large number of RAN slice subnets in the underlying infrastructure, as well as highlight the advantages of employing Q-learning for VNF mapping compared to other state-of-the-art algorithms. Mohammad Asif Habibi doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13045 Thu, 16 Apr 2026 12:33:15 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13046 Elucidating unknown mixtures is a critical challenge in chemistry and chemical engineering. Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique generally suited for this purpose. However, component-wise elucidation with NMR is tedious for complex mixtures, requires expert knowledge, and often yields ambiguous results. In contrast, identifying and quantifying structural groups in a mixture from NMR spectra is much more straightforward. In prior work, we have introduced ‘NMR fingerprinting’ for the automated elucidation of carbon-, hydrogen-, and oxygen-containing structural groups in unknown mixtures based on standard NMR experiments and a support vector classification (SVC) from machine learning (ML). In the present work, we present a substantially advanced NMR fingerprinting method that employs a deep set model (DSM), addressing major shortcomings of the SVC, and integrates additional information from 2D NMR experiments. The DSM was trained on experimental NMR spectra of pure components from open-source databases, augmented with synthetic spectral data, and comprises invariant and equivariant network structures to ensure predictions independent of the input order of the NMR signals. Tested on experimental pure-component test data, the DSM performs excellently, significantly outperforming our previous approaches. Furthermore, we demonstrate the applicability of the DSM to unknown mixtures by predicting the structural groups from NMR spectra of test mixtures measured using a benchtop NMR spectrometer. The predictions agree very well with the true mixture compositions, highlighting the method's potential for efficient automated mixture analysis and providing a reliable basis for downstream tasks, such as thermodynamic modeling using group-contribution methods. Jens Wagner; Kerstin Münnemann; Thomas Specht; Hans Hasse; Fabian Jirasek article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13046 Wed, 15 Apr 2026 09:48:52 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13049 N-Nitrosamine zählen zu den alkylierenden Agenzien mit genotoxischen, mutagenen und karzinogenen Eigenschaften. Nach Absorption erfolgt die metabolische Aktivierung hauptsächlich in der Leber unter Cytochrom-P450 (CYP450)-Enzym-vermittelter Katalyse. Die Risikobewertung von N-Nitrosaminen in Arzneimitteln erfolgt nach Vorgaben der ICH M7 Guideline, in welcher die Ableitung von substanzspezifischen Aufnahmemengen (AIs) unter Zuhilfenahme bekannter Daten zur Tumorinzidenz gefordert ist (ICH M7, 2023). Dieser Ansatz ist bei Arzneimittelspezifischen Nitrosaminverunreinigungen, bekannt als Nitrosamin Drug Substance-Related Impurities (NDSRIs), für die robuste Kanzerogenitätsdaten strukturnaher Analoga oftmals fehlen, limitiert. Im Fokus dieser Arbeit stand die Etablierung einer in vitro Variante des alkalischen Comet Assays als ergänzende oder alternative Methode zum Ames Test, um die Prädiktivität im Hinblick auf genotoxische Effekte von N-Nitrosaminen zu verbessern. Die Bestimmung der Zytotoxizität und Genotoxizität von zehn strukturell verschiedenen N-Nitrosaminen einschließlich der Ermittlung der metabolischen Kompetenz in PRH war ein wesentlicher Bestandteil dieser Aufgabe. Ferner sollten genotoxische Effekte in genetisch modifizierten HepG2 Zellen sowie in der Wildtyp Zelllinie untersucht werden. Die isolierten PRH verfügten über CYP2E1, CYP3A4, CYP1A2, CYP2D6, CYP2B6 und CYP2C9-Aktivität, wie mittels LC-MS basierter Messung der Stoffwechselverhältnisse mit etablierten CYP Substraten festgestellt wurde. Die beiden NDSRIs N-Nitrosodesloratadin (NND) und N-Nitrosofluoxetin (NFluo) zeigten bereits im µM Bereich zytotoxische Effekte, während N-Nitrosodimethylamin (NDMA), N-Nitrosodiethanolamin (NDELA), N-Methyl-N-Nitroso-iso-propylamin (NMIPA), (S)-N′-Nitrosonornikotin (S-NNN) und N-Methyl-N-Nitroso-tert-butylamin (NMtBu) nicht zytotoxisch waren. N-Nitrosofolsäure (NFA), N-Nitrosomethylanilin (NMA) und N-Nitrosoprolin (NPro) induzierten leichte zytotoxische Effekte in PRH. Für NFluo konnte das stärkste strangbruchinduzierende Potential gemessen werden, gefolgt von NDMA > NMIPA > NDELA, die ebenfalls positiv waren. Die übrigen N-Nitrosamine waren nicht eindeutig strangbruchinduzierend. Der in vitro Comet Assay in PRH resultierte in einer Spezifität von 100 % und in einer Sensitivität von 50 %. Für die NDSRIs N-Nitrosonortryptilin (NNT) und N-Nitrosobetahistin (NBH) war das Ausmaß verursachter DNA-Strangbruchschäden höher als das durch NDMA induzierte. Neben dem Nachweis von O6-Methylguanin- (O6-MeG) und N7-Methylguanin- (N7-MeG) Addukten in mit NDMA behandelten PRH konnte gezeigt werden, dass die hohen Schweifintensitäten nach 2h aufgrund der recht geringen O6-MeG-Adduktlevel vermutlich auf die gebildeten N7-MeG-Addukte und N3-MeA-Addukte zurückzuführen sind. Die Aktivität des Proteins CYP1A2 konnte in HepG2 Zelllinien eindeutig bestätigt werden. CYP2E1 war nur in HepG2-CYP2E1 Zellen nachweisbar. S-NNN war in HepG2 Zellen und in HepG2-CYP1A2 Zellen zytotoxisch, während NDMA und NDELA zu zytotoxischen Effekten in HepG2-CYP2E1 Zellen führten. NDMA, NDELA und S-NNN induzierten mehrheitlich das p53 Proteinlevel in den verwendeten HepG2 Zelllinien. Die CYP2E1 abhängige metabolische Aktivierung von NDMA, NDELA und NMA ließ sich in HepG2-CYP2E1 Zellen demonstrieren. Ferner ließen sich klastogene Effekte von NDMA sowie die Induktion von DNA-cross-links durch NMA in HepG2-CYP2E1 Zellen feststellen. Der alkalische Comet Assay in PRH und in HepG2 Zellen zur Vorhersage des genotoxischen Potentials strukturell verschiedener N- Nitrosamine konnte erfolgreich validiert werden. Christina Felske doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/13049 Wed, 15 Apr 2026 09:17:29 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11761 Die Anfänge der Reformation in Siebenbürgen, einem von den „Kernlanden“ der Reformation (Sachsen, Südwestdeutschland, Schweiz, Niederlande) relativ entferntem Siedlungsgebiet deutsch-/ungarischer Bevölkerung begann sehr früh, waren aber einer starken Gegenreaktion ausgesetzt. Der Band zeichnet die Entwicklung im Licht neuer Quellen nach und arbeitet die Besonderheiten der Siebenbürgischen Reformation heraus. Ulrich Wien book https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11761 Tue, 14 Apr 2026 16:29:10 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11767 The READI Actuaries Science Applied Research Program in Indonesia is looking for potential research related to risk estimation using climate information along with actuarial assumptions and methods. The monthly accumulated precipitation value is one of the climate information recorded by the Meteorology, Climatology, and Geophysical Agency of Indonesia (BMKG in Indonesian language). This weather factor can be used to calculate the financial risks of paddy crops in all provinces of Indonesia. The first stage of this calculation is forecasting the precipitation values in 2016-2017 from the data up to 2015 using Singular Spectrum Analysis (SSA) both Univariate and Multivariate accordingly, considering the three areas of calculations: Province, Region, and Country. The second step is to convert these rainfall values to calculate payouts based on several linear index insurance models, with 6 Million IDR per hectare per planting season as the maximum indemnity. The procedure is based on additional analyses, such as comparisons between areas of calculations, between method combinations of the SSA itself, and between various missing data handling methods, are also included in this research. A simulation study based on different rainfall distributions is also included. The major findings of this research are the better performance of some SSA method combinations and the best linear index insurance model to reproduce the payouts. There are many factors to be considered when discussing good policies and the benefits of such insurance against agricultural risk. Rana Desenaldo doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11767 Thu, 09 Apr 2026 13:11:10 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11758 Microbiologically induced calcium carbonate precipitation (MICP) is an emerging technology with applications in geotechnical engineering and construction. This dissertation investigates the ureolytic MICP process, focusing on optimizing its efficiency and applicability for biocementation of granular materials such as sand. The study systematically examines key influencing factors, biomass concentration, temperature, the composition of the cementation solution and particle size distribution. Experiments were conducted using the ureolytic bacterium Sporosarcina pasteurii to induce calcium carbonate precipitation under controlled conditions. The research explores the kinetics of ureolysis and its impact on the efficiency of calcium carbonate precipitation. A particular focus is placed on the influence of sand particle size on the mechanical properties and pore structure of MICP-treated sand. Variations in particle size affect the distribution and bonding of calcium carbonate, impacting overall compressive strength and durability. Following this, the study employs response surface methodology (RSM) to optimize compressive strength by systematically varying and analyzing multiple parameters to enhance biocementation outcomes. Despite the advantages of MICP as a sustainable alternative to conventional cement-based materials, challenges remain. The production of ammonium as a by-product and the energy-intensive synthesis of urea present environmental concerns that require further optimization. This work contributes to a deeper understanding of MICP and provides a framework for improving its efficiency and scalability in construction and soil stabilization applications. The findings highlight the potential of MICP to enhance the durability of built environments while identifying key areas for future research in microbial mineralization processes. Niklas Erdmann doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11758 Tue, 07 Apr 2026 06:35:12 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11756 Urban water management faces growing pressure from population growth, pollution, and climate variability, demanding innovative strategies to ensure long-term sustainability. This study applies the Life Cycle Sustainability Assessment (LCSA) across four case studies in Brazil and Germany, evaluating integrated systems that combine constructed wetlands for greywater treatment with rainwater harvesting for non-potable use. The scenarios include a single-family household, a high-rise residential building, a rural residence, and worker housing. A multi-criteria analysis was conducted to derive consolidated sustainability indicators, and sensitivity analysis explored the influence of dimension weighting. Results showed that water reuse scenarios consistently outperformed conventional counterparts across environmental, economic, and social dimensions. Life Cycle Assessment (LCA) revealed notable reductions in global warming potential, terrestrial acidification, and eutrophication. Life Cycle Costing (LCC) confirmed financial feasibility when externalities were considered, especially in large-scale systems. Social Life Cycle Assessment (S-LCA) highlighted the perceived benefits in terms of health, safety, and sustainability engagement. Integrated water reuse systems achieved overall sustainability scores up to 4.8 times higher than their baseline equivalents. These findings underscore the effectiveness of decentralized water reuse as a complementary and robust alternative to conventional supply and treatment models, supporting climate resilience and sustainable development goals. Hugo de Simone Souza; Carlo Morandi; Heidrun Steinmetz; Paula Paulo; Marc Boncz article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11756 Thu, 02 Apr 2026 12:12:12 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11747 Amtliche Bekanntmachung der RPTU Nr.3/31..03.2026 periodicalpart https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11747 Wed, 01 Apr 2026 10:15:58 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11751 Die Arbeit untersucht den Zusammenhang zwischen Organisationsentwicklung und Theater und widmet sich der Frage, ob Methoden aus der Theaterpädagogik und dem Schauspieltraining einen Mehrwert beim Einsatz im Rahmen der Organisationsentwicklung bieten können. Hierzu wird untersucht, welche Bezüge sich zwischen den der Organisationsentwicklung zugrundeliegenden Theorien, wie etwa der Systemtheorie, und relevanten Diskursen der Theaterwissenschaft herstellen lassen. Auf dieser Basis wird argumentiert, dass sich aufgrund diverser theoretischer Bezüge ein Mehrwert nachwweisen lässt. Dabei wird die These aufgestellt, dass Methoden, welche die Mitarbeitenden selbst zu aktiven Schauspielenden machen, den größten Erfolg in der Organisationsentwicklung versprechen. Am Beispiel von ausgewählten Augusto Boals wird schließlich der Einsatz in der Praxis der Teamentwicklung diskutiert. Leonie Pohlmann masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11751 Tue, 31 Mar 2026 12:55:11 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11749 Facility location planning problems are a well-studied topic in optimization - and for good reason. Their applications appear in lots of different areas of real life. In this thesis, we study location problems in the context of parametric networks, where the parameter is introduced on the weights of the edges. Furthermore, interdiction location problems are analyzed, that include an opposing force - the interdictor - with the goal to destroy the existing network by removing edges of the network to make the situation as unfavorable as possible for the locator. In the first part of the work, we investigate location problems in the context of parametric optimization. Here, we assume that the edge weights in the considered networks are linearly dependent on a parameter lambda. Parametric optimization has been studied in relation to many other classical optimization problems; however, so far, there have been no results on location problems in networks with parametric edge weights. For this purpose, we analyze the classical 1-median and 1-center problems on general graphs and also on trees. In doing so, we examine the complexity of both the solution itself and the objective function value as a function of the parameter. We emphasize that the complexity of the optimal value function can be super-polynomial on directed general graphs for both median and center problems, which motivates the development of approximation schemes for these cases. In fact, approximation methods that rely on an existing approximation scheme are introduced for both location problems on directed and undirected general graphs. The developed method is based on the fact that both median and center problems can be divided into subproblems, that get approximated individually before combining the gained information into an overall approximate solution without losing the initial approximation guarantee. Furthermore, exact algorithms are given for the two considered parametric location problems on both directed and undirected trees. These algorithms exploit the properties of trees - precisely the uniqueness of the shortest paths in said structures. In the second part of the thesis, we introduce the p-median interdiction problem on trees. The goal of the interdictor is to remove edges of the underlying network to deteriorate the initial situation of the locator in order to worsen their objective function value. In this part, we first show that the p-median interdiction problem on trees is NP-complete by a reduction from the knapsack problem with bounded profit ratio of 2. Furthermore, we present algorithms for solving the problem on paths with unit and arbitrary lengths. Finally, an exact algorithm is presented for trees with unit edge weights and a single interdiction. Let e be the edge that is incident to the leaf that is nearest to the median location of the initial tree. We prove that removing this edge is the optimal interdiction strategy. Lena Leiß doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11749 Tue, 31 Mar 2026 08:02:58 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9711 Die Masterarbeit untersucht, wie Führungskräfte selbstorganisierte Teams auf Distanz wirksam unterstützen können und welche Rahmenbedingungen und Methoden hierfür förderlich sind. ​ Im Mittelpunkt steht ein systemtheoretisch fundiertes Führungsverständnis im Kontext von New Work und VUCA, das Führung primär als Gestaltung von Strukturen, Prozessen und Kommunikationsmustern begreift, um Selbstorganisation, Autonomie, Vertrauen und Selbstführung in virtuellen bzw. hybriden Teams zu ermöglichen. Auf Basis eines theoriebasierten Vorgehens werden ein praxisorientierter, ein radikal selbstführungsorientierter und ein forschungsbasierter Ansatz (u.a. Seeger, Laloux, Blessin & Wick) vergleichend analysiert, um daraus praxisnahe Empfehlungen für Führungshandeln auf Distanz abzuleiten und zugleich die Grenzen kausaler Zuschreibungen von Führungserfolg in komplexen, selbstorganisierten Systemen zu reflektieren. Ute Erdenberger masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9711 Mon, 30 Mar 2026 06:43:53 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11746 Automated reasoning about complex data structures is fundamental to reliable software verification. Strings, in particular, present a unique challenge in Satisfiability Modulo Theories (SMT) due to the intricate interaction between algebraic structure and arithmetic constraints on length, as well as rich regular-language properties arising from real- world regular-expression libraries. These interactions underpin many verification tasks, including symbolic execution, safety checking of string-heavy code, and analysis of parameterised systems, but often push existing SMT-based approaches to their limits. This thesis addresses these challenges from a computational perspective, fundamentally organised around the idea of constraint propagation through string functions and regular languages. The first part introduces a proof system for Regular Constraint Propagation (RCP) and identifies a large decidable class of string constraints, the orderable fragment, for which RCP is complete. This fragment strictly subsumes several major known decidable classes, including the chain-free and straight-line fragments. We also prove a limitation theorem: even when augmented with Nielsen-style transformations and the Cut rule, RCP cannot refute all unsatisfiable constraints over word equations and regular languages. Building on these foundations, the thesis presents OSTRICH2, a modular string solver that integrates RCP with equational splitting, algebraic-datatype reasoning, cost- enriched solving, and preprocessing. OSTRICH2 provides native support for SMT-LIB Unicode strings, ECMAScript-style regular expressions, and string-to-string transductions. A detailed system description is presented, and experiments show that this portfolio architecture is competitive, particularly on unsatisfiable SMT-LIB instances. We then demonstrate how modern string solvers enable new forms of verification. We introduce HornStr, the first CHC-based solver over the SMT-LIB string theory, which encodes Regular Model Checking (RMC) as constrained Horn clauses. HornStr synthesizes inductive invariants using automata learning techniques combined with string solvers. This yields effective verification for a range of parameterised systems and produces the incremental benchmark suite for the QF S division in the SMT-LIB standard. Two complementary contributions broaden the scope of the work. We investigate sequences over infinite alphabets, establishing the first systematic decidability and com- plexity results for combining concatenation with expressive constraints like Parametric Automata (PA) and parametric transducers. Additionally, we conduct a study in al- gorithmic learning of monadic decomposition, which yields a polynomial-time algorithm for learning finite unions of integer hypercubes. This result provides a geometric technique for analysing complex Presburger length constraints, which enables their translation into the monadic fragment and thus makes them suitable for established string solver techniques. Oliver Markgraf doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11746 Mon, 30 Mar 2026 06:32:04 +0200 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/8601 Freshwater crayfish are an ancient group of decapod crustaceans. They are keystone species of freshwater habitats acting as ecosystem engineers, trophic regulators and biodiversity indicators. At the beginning of the 20th century, a collapse of native Europe freshwater crayfish populations occurred due to the introduction of the invasive oomycete pathogen, Aphanomyces astaci Schikora (1906), causative agent of the crayfish plague disease. Later, numerous introductions of invasive freshwater crayfish species, which are latently infected with their respective Ap. astaci strains, facilitated pathogen host-jumps and accelerated the decline of European freshwater crayfish stocks. However, latent infections have also been observed in European freshwater crayfish populations. In this context, my thesis focuses on elucidating the molecular mechanisms that underly the freshwater crayfish immune response to the pathogen Ap. astaci. I analyse both the susceptible and resistant host´s gene expression patterns to elucidate molecular pathways involved in the host immune response towards Ap. astaci challenge. This led me to the discovery of novel immune response factors involved in the response towards Ap. astaci, such as antimicrobial peptides (AMPs), pattern recognition receptors (PRRs), and transcription factors. My quest to elucidate the dynamics of this host-pathogen interaction has revealed that the disease progression is correlated to the pathogen progression, which occurs in multiple stages. Moreover, I identified and characterised novel transcription factors, namely CCAAT-enhancer-binding protein (C/EBP) and Krüppel homologue 1 (Kr-h1) as candidate genes in the innate immunity. Ultimately, my research highlights the complexity of the freshwater crayfish immunity, displaying how different coevolutionary mechanisms shape our understanding of this host-pathogen interaction. These results can facilitate the innovative genomic approaches in crayfish plague disease management and conservation. Ljudevit Luka Boštjančić doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/8601 Fri, 27 Mar 2026 13:15:39 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11744 Addressing the persistent heterogeneity in psychopathology, treatment outcomes, and the science–practice gap requires a systematic approach to personalizing psychotherapy. Case conceptualization seeks to understand a patient’s unique psychopathology by generating and continuously updating hypotheses about predisposing, precipitating, and maintaining factors. This study introduces a new data-driven method to formalize this process with personalized network estimation, combining prior elicitation and Bayesian inference. It is the first to test its clinical usefulness with 12 patients, primarily treated for depression, and their therapists (preregistered and can be found as the additional online materials: https://osf.io/38qdx). Patients employed the Perceived Causal Networks method to create personalized “prior networks,” mapping how they perceived their symptoms to interact. Bayesian inference was used to update these prior networks using longitudinal data collected subsequently 6 times daily over 15 days (N = 935), resulting in personalized “posterior networks.” Both Perceived Causal Networks and longitudinal assessments were evaluated as feasible and acceptable. Face validity was scored highest for the posterior networks. Patients emphasized the personal relevance of these networks, while therapists noted their value in guiding the therapeutic process. However, prior, posterior, and data networks showed significant dissimilarities. These differences may stem from patients’ limited insight into symptom interactions, insufficient power in the longitudinal data, or variations in self-perception. Despite some inconsistencies, the study shows potential for combining two methods to create personalized models of psychopathology, highlighting the need for future research to refine this formalization process into a more rigorous theoretical-empirical cycle to test these models. Saskia Scholten; Lars Klintwall; Julia Anna Glombiewski; Julian Burger article https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11744 Thu, 26 Mar 2026 18:20:14 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11745 Die fortschreitende Digitalisierung nimmt in nahezu allen Wirtschaftssektoren, einschließlich des Bauhandwerks, eine zunehmend bedeutende Stellung ein. Im Jahr 2017 integrierten nur etwa 45 Prozent der Handwerksbetriebe digitale Technologien in ihre Arbeitsabläufe; 2022 stieg der Anteil auf 75 Prozent an. Die Entwicklung zwischen den Jahren 2017 bis 2022 zeigt zwar kontinuierliche Fortschritte, legt jedoch auch die bestehenden Herausforderungen und den erheblichen Nachholbedarf vieler kleiner und mittlerer Unternehmen (KMU) offen, die sich der digitalen Transformation stellen müssen. Die Bundesregierung hat sich das Ziel gesetzt, die Digitalisierung in der Bauwirtschaft bis zum Jahr 2030 umfassend zu fördern, dennoch fühlen sich zahlreiche Handwerksbetriebe von diesem Transformationsprozess überfordert. Ergänzend dazu ergeben sich Schwierigkeiten wie unzureichende Infrastruktur, mangelnde Schulungsangebote sowie Engpässe bei Fachkräften, die den Übergang in die digitale Zukunft zusätzlich erschweren. Aus diesem Grund gewinnt die digitale Kompetenzbildung von Auszubildenden im Bauhandwerk zunehmend an Relevanz. An der Rheinland-Pfälzischen Technischen Universität (RPTU) Kaiserslautern-Landau engagiert sich das Forschungsteam unter der Leitung von Universitätsprofessor Dr.-Ing. Karsten Körkemeyer im Fachbereich Bauingenieurwesen, Fachbereich Baubetrieb und Bauwirtschaft, seit mehreren Jahren intensiv mit der Thematik der Digitalisierung in der Bauwirtschaft. Zu den bereits erfolgreich abgeschlossenen Projekten zählen unter anderem InfraBau4.0 , Digital Construction Management (DiCoMa) sowie umfassende Studien zum Stand der Digitalisierung der Baubranche . Des Weiteren wurde eine Einführungsstrategie für Building Information Modeling (BIM) im Landesbetrieb Liegenschafts- und Baubetreuung Rheinland-Pfalz entwickelt. Aktuell befindet sich das Forschungsteam in der zweiten Phase des Projekts Offene Digitalisierungsallianz Pfalz II (ODPfalz-II) , in dem es im Rahmen des Innovationsbereich (IB) Arbeit das Arbeitspaket fünf (A5) übernimmt, der sich zwischen 2023 und 2027 mit der Integration digitaler Lehrinhalte in die berufliche Ausbildung im Bauhandwerk befasst. Die Forschungsarbeit bietet eine bedeutende Möglichkeit, das weitreichende Spektrum der Digitalisierung innerhalb der Wertschöpfungskette der Bauwirtschaft zu erweitern und zu vertiefen. Im Besonderen fokussiert sich das aktuelle Forschungsvorhaben auf die Implementierung neuer Lehrmethoden und die Entwicklung von Kompetenzen im Umgang mit digitalen Technologien. Ziel ist es, die Digitalisierung im Bauhandwerk proaktiv zu fördern und weiter voranzutreiben. Vorangegangene Forschungsergebnisse verdeutlichen die Notwendigkeit, digitale Kompetenzen bereits während der Ausbildung zu vermitteln, um die zukünftigen Fachkräfte adäquat auf die Anforderungen einer zunehmend digitalisierten Arbeitswelt vorzubereiten und somit einen entscheidenden Beitrag zur nachhaltigen Entwicklung der Baubranche zu leisten. Im Rahmen der vorliegenden Arbeit wird ein Teilbereich des Innovationsbereichs (IB) Arbeit, Arbeitspaket fünf (A5), vertieft analysiert und bearbeitet. Das Ziel bestand darin, den aktuellen Zustand und die Bedarfe der Bauwirtschaft in der Pfalz mittels einer Onlineumfrage und Experteninterviews mit Handwerksbetrieben zu erheben. Aufbauend auf diesen Erkenntnissen wurden diejenigen tatsächlich erforderlichen digitalen Kompetenzen für Auszubildende identifiziert, die in der Praxis auch benötigt werden. Die Ergebnisse der Onlineumfrage verdeutlichen die vielfältigen Herausforderungen, die mit der Digitalisierung einhergehen. Sie weisen darauf hin, dass bereits in der Berufsausbildung von jungen Handwerkerinnen und Handwerkern gezielt in digitale Kompetenzen investiert werden muss. Diese frühzeitige Förderung kann die Digitalisierung der Handwerksbetriebe beschleunigen und dem drohenden Fachkräftemangel entgegenwirken. Basierend auf den Erkenntnissen der empirischen Erhebungen widmet sich die Arbeit im Gestaltungsteil der Entwicklung eines vierstufigen digitalen Modells zu Kompetenzbildung für Auszubildende im Bauhandwerk. Das Modell umfasst dabei grundlegende digitale Fähigkeiten sowie berufsspezifische Anforderungen. Die Evaluation des digitalen Kompetenzmodells erfolgt im Rahmen von vier Workshops. Die teilnehmenden Auszubildenden des Gewerkes Zimmerer wurden mithilfe einer quantitativen Onlinebefragung gebeten, nach Abschluss des Workshops das entwickelte Kompetenzmodell zu bewerten. Die Ergebnisse zeigen, dass Auszubildende über unterschiedliche Erfahrungen mit digitalen Technologien im Arbeitsalltag verfügen, eine umfassende Information und Schulung über digitale Themen jedoch begrüßen. Dies unterstreicht den Bedarf, digitale Technologien und Inhalte in den Berufsschulunterricht zu integrieren und die Auszubildenden frühzeitig zu fördern Jennifer Aha doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11745 Thu, 26 Mar 2026 09:50:44 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11741 Der vorliegende Methoden-Reader bietet eine praxisnahe Sammlung von Lehr-Lern-Methoden, die speziell darauf abzielen, den Transfer von Wissen und Kompetenzen in der Hochschullehre zu fördern. Im Mittelpunkt stehen Formate, die Lernprozesse aktivieren, Inhalte vertiefen und die Anwendung des Gelernten in unterschiedlichen Kontexten unterstützen. Die Methoden sind vielseitig einsetzbar – in Vorlesungen, Seminaren oder Workshops – und eignen sich besonders für eine Lehrpraxis, die Studierende zur aktiven Auseinandersetzung mit Inhalten anregen möchte. Die Bandbreite reicht von diskussionsorientierten und kollaborativen Formaten bis hin zu spielerischen oder digitalen Elementen. Ziel dieses Readers ist es, Dozierenden unkomplizierte Anregungen zur Gestaltung transferförderlicher Lehrsituationen an die Hand zu geben und damit Impulse für eine wirksame und transferförderliche Hochschullehre zu setzen. Lilli-Marie Scheller; Luisa Hartnack; Alisha Koch; Pia Schäfer; Susanne Wißhak other https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11741 Tue, 24 Mar 2026 12:29:09 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11743 The rise of artificial intelligence (AI) as a general solution in image processing problems, such as segmentation and detection tasks, has sparked growing interest in generating synthetic image data. A significant factor is that real data is often not available in sufficient quantity or quality for the thorough development, evaluation, and analysis of solutions. The reasons for this are diverse: image acquisition can be costly, labeling may require unfeasible and error-prone manual annotation, or the data may have low variability that does not allow for generalization. With the increase in computational power over the last few decades, synthetic data has become an essential component in the development of solutions as it addresses the shortcomings of real data. Furthermore, it provides almost unlimited diversity, is easily acquired, and comes with perfect annotation. This thesis consists of three parts that highlight the significance of synthetic data in developing, validating, and analyzing methods and results in image processing. In the first part, we present a convex optimization method for removing stripe artifacts. These elongated and parallel corruptions appear frequently with various imaging techniques including light-sheet fluorescence microscopy (LSFM), focused ion beam scanning electron microscopy (FIB-SEM), and remote sensing. Our approach offers intuitive parametrization and is highly flexible to different scenarios of image structures and stripes. We demonstrate the effectiveness and advantages of our approach over existing solutions by comparing them across real images from LSFM, FIB-SEM, and remote sensing through visual inspection. Based on synthetic LSFM data obtained by simulating physical light propagation we enrich our analysis by comparing the processed images to ground truth data and quantitatively confirming the performance observed on real data. In the second part, we discuss the assessment of quality for results in binary image segmentation tasks by comparing a large variety of established traditional metrics and distance-based approaches. This includes a distance-based metric that we propose, which captures the spatial distribution of errors while offering desirable properties such as normalization and interpretability. Using predominantly synthetic data and some real segmentation results, we perform a thorough analysis of the segmentation metrics across diverse conditions. This demonstrates the robustness and effectiveness of our metric in distinguishing errors near the surface from those farther away across different structural contexts. We illustrate its inclusion to real-world segmentation tasks by extending a previous study on segmenting cracks in CT images. In the third part, we conduct a systematic study of morphologically diverse geometric structures with the goal to characterize the morphology of 3D spatial structures in terms of their anisotropy, scale and angularity based on the measurement of common morphological features. Geometries are entirely generated using stochastic models whose parameters intuitively translate to the studied concepts and yield morphologically diverse structures. Using classical machine learning approaches for dimensionality reduction our study finds a series of measures for anisotropy, scale and angularity based on linear combination of the morphological features that distinguish between synthetic structures accordingly. We exemplify and discuss their use on real data for modeling of general spatial structures. Niklas Rottmayer doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11743 Mon, 23 Mar 2026 12:35:12 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11742 Die Masterarbeit beleuchtet den konkreten betrieblichen Handlungsbedarf, der sich aus der KI-Verordnung für Anbieter und Betreiber von KI-Systemen ergibt. Zunächst wird dargestellt, unter welchen Voraussetzungen Unternehmen in den Anwendungsbereich der Verordnung fallen und damit von ihren Regelungen erfasst sind. Anschließend folgt eine Klassifizierung der KI-Systeme in unterschiedliche Risikoklassen, die maßgeblich für die jeweiligen Pflichten sind, ergänzt durch Praxisbeispiele zur Verdeutlichung, welcher Kategorie die in Unternehmen eingesetzten KI-Systeme unterliegen. Nach der insofern dargestellten Illustration der allgemeinen Handlungsnotwendigkeiten wird der weitergehende universelle Handlungsbedarf analysiert, der für alle von den Regelungen der Verordnung betroffenen Unternehmen relevant ist und sich in Mapping und die Sicherstellung von KI-Compliance, die unternehmensweite Vermittlung und Aufrechterhaltung von KI-Kompetenz sowie die Einführung organisatorischer Strukturmaßnahmen aufgliedert. Danach wird der risikospezifische Handlungsbedarf anhand von selektierten, wesentlichen Pflichten verschiedener Risikokategorien erörtert und praktische Umsetzungsmöglichkeiten aufgezeigt – mit einem Fokus auf dem für Hochrisiko-KI-Systeme eine zentrale Rolle einnehmenden Risikomanagementsystem (Art. 9 KI-VO) und der für KI-Systeme mit begrenztem Risiko bestehenden Deepfake-Kennzeichnungspflicht (Art. 50 Abs. 4 UAbs. 1 KI-VO). Die Ausarbeitung schließt mit einer resümierenden Darstellung der Ergebnisse und praktischen Handlungsempfehlungen, die Unternehmen eine Orientierung für den rechtskonformen und verantwortungsvollen Einsatz von KI-Systemen im Einklang mit den regulatorischen Vorgaben der KI-VO bieten. Luke Niklas Schmidt masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11742 Mon, 23 Mar 2026 06:17:21 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11737 Die Arbeit untersucht die Möglichkeit einer gezielten Einsetzbarkeit von Metaphern im systemischen Coaching im Hinblick auf die mögliche Unterstützung im Rahmen von individuellen Veränderungsprozessen. Die kognitive als auch emotionale Wirkung von Metaphern im Coachingprozess wird analysiert. Es erfolgt eine theoretische Fundierung des Metaphernbegriffs unter Einbezug verschiedener disziplinärer Ansätze sowie die Untersuchung der Wirkmechanismen von Metaphern in Bezug auf Kognition, Emotion, körperliche Prozesse und Verhalten. Der menschliche Veränderungsprozess wird in Beziehung zur Metaphernarbeit gesetzt sowie die Berücksichtigung des Einflusses von Glaubenssätzen, Werten und Emotionen. Das systemische Coaching wird von anderen Beratungsansätzen abgegrenzt und die Eignung von Metaphern innerhalb des systemischen Ansatz diskutiert mit Schwerpunkt auf Perspektivwechsel und Anschlussfähigkeit. Es wird der Frage nachgegangen, inwieweit Metaphern im systemischen Coaching als wirksames Instrument im individuellen Veränderungsprozess betrachtet werden können und die Nutzung klient:inseitiger und coach:inseitiger Nutzung untersucht. Auf dieser Grundlage wird ein Modell zur systematischen Integration von Metaphern entwickelt. Daniela Kunkel masterthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/11737 Thu, 19 Mar 2026 11:08:39 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9736 Linear parametric optimization has been used for decades to combine multiple objective functions into a single problem. The solution to this problem is a set of optimal solutions, containing a solution that is optimal for each parameter. Multi-objective optimization is commonly used when multiple objectives are optimized simultaneously, and these objectives are often conflicting. Because these objective functions are conflicting, there is usually no unique optimal solution. Instead, the goal is to find all nondominated images that represent the trade-offs among the objectives. The weighted sum scalarization method is a well-known approach for finding nondominated images by transforming a multi-objective optimization problem into a single-objective optimization problem. In this thesis, we consider linear parametric programming problems with multiple objective functions depending linearly on some parameters. Both parametric (single-objective) linear programming and (non-parametric) multi-objective linear programming are well-researched topics. However, literature on the combination of both, parametric linear programming with multiple objectives, is scarce. This research gap encourages our work in this field. More precisely, we examine linear parametric programs with multiple objective functions that depend linearly on some parameters. We investigate various cases of parametric biobjective linear programs and multi-parametric biobjective linear programs. We establish a connection of these problems to non-parametric multi-objective problems. Using the so-called weight set decomposition, we are able to explain the behavior of parametric biobjective linear programs when the parameter value is variated. We prove that there is a one-to-one correspondence between the solution of some parametric biobjective programs and the solution of the corresponding multi-objective linear program using the weighted sum scalarization. We provide structural insights to the solution of parametric biobjective linear programs with respect to extreme weights of the weight set of the multi-objective linear program and develop solution strategies for the parametric program. Similarly, we extend our analysis to biparametric biobjective linear programs and a generalization of our findings to parametric multi-objective linear programs. We characterize the structure of the parameter set of both single and biparametric problems using the weight set of the multi-objective linear programs. Finally, we develop algorithms to solve parametric biobjective linear programs based on the weight-set decomposition. Kezang Yuden doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9736 Thu, 19 Mar 2026 10:20:14 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9731 This dissertation investigates the developmental trajectory of abstract and lexically dependent syntactic representations in monolingually and bilingually raised children. To examine the nature of these representations, the dissertation employs the structural priming paradigm—the tendency to reproduce previously encountered syntactic structures independent of specific lexical items (Bock, 1986). Structural priming provides a powerful methodological tool for investigating how syntactic knowledge develops and how structural representations are shaped by linguistic experience. The empirical focus of the dissertation is the dative alternation in German, which contrasts double-object constructions (e.g., Dora sent Boots the rabbit) with prepositional-object constructions (e.g., Dora sent the rabbit to Boots). Importantly, the prepositional-object construction is strongly dispreferred in German and rarely occurs in the linguistic input to young children. Evidence for this distribution is established through a corpus analysis of child-directed speech from the CHILDES database as well as an acceptability judgment and elicited production study with adult speakers. Building on these findings, Chapter 5 presents two structural priming experiments examining the production of the German dative alternation in monolingual and bilingual children across three age groups (3–4 years, 5–6 years, and 7–8 years) as well as in adults. The results reveal robust immediate and cumulative structural priming effects across all age groups. However, these effects are strongest in the youngest children and gradually decrease with age. This pattern suggests that syntactic representations in younger children are less stable than in adults and therefore more susceptible to adaptation both immediately and over time, potentially due to stronger surprisal when encountering less expected structures. In contrast, lexical boost effects were absent in the youngest group but emerged gradually with increasing age. This developmental pattern may reflect limitations in younger children’s working-memory capacity, which may constrain their ability to temporarily maintain lexical information that could strengthen priming effects. Alternatively, it may reflect still-developing links between verbs and their associated argument structures in the mental lexicon, which may become more firmly established with increasing age. Taken together, the findings support the Implicit Learning Account of structural priming, according to which syntactic representations are continuously updated through exposure to structural input via prediction-error mechanisms. The results suggest that structural learning mechanisms are particularly active early in development, whereas lexically dependent priming effects emerge only later as children’s cognitive and linguistic systems mature. More broadly, the dissertation contributes to our understanding of how syntactic representations develop in both monolingual and bilingual acquisition and how structural frequency and lexical information interact in shaping children’s syntactic choices. Alina Kholodova doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9731 Tue, 17 Mar 2026 13:47:20 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9728 Christopher Allison doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9728 Tue, 17 Mar 2026 10:41:38 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9726 Computer-generated images, videos, and visual effects are indispensable resources for digital content creation that enable artists to create engaging visual stories. However, creating compelling stories often requires photorealistic 3D models that are designed by skilled digital artists. Novel View Synthesis (NVS) has emerged as a cheaper means to achieve photorealism. NVS uses a collection of photographs to render a scene from novel camera poses without relying on expensive models of geometry, materials, or light. This thesis introduces a number of view synthesis approaches with varying levels of input complexity, ranging from multi-view stereo and sparse multi-view spherical images to 2D semantic maps and simple textual descriptions. The proposed methods improve the state-of-the-art in terms of accuracy, efficiency, and usability. In the multi-view stereo input setting, the proposed FastNVS method significantly outperforms existing techniques in terms of speed and accuracy. FastNVS achieves this by decomposing the NVS problem into two structured prediction tasks, namely, proxy geometry estimation and texture inpainting. In the more challenging setting of spherical input images, prior work relies on the Multisphere Images (MSI) scene representation. MSI-based methods achieve fast rendering speed but are limited to modeling low-dimensional color values per-sphere. To alleviate this, we propose a novel scene representation called Soft Occlusion Multisphere Images (SOMSI) that enables modeling high-dimensional appearance features in MSI. This is achieved by assigning appearance features to a few occlusion levels, instead of a large number of MSI spheres. SOMSI produces novel views with significantly higher quality while retaining the fast rendering times of traditional MSI. Furthermore, the usability of view synthesis methods is enhanced by introducing novel techniques that require minimal user input and grant users control over the 3D scene. Additionally, the proposed methods give users great creative freedom by enabling them to create novel 3D scenes for which no input images exist. The first method in this line of research is the GVSNet technique, which allows users to create novel views from a single input 2D semantic sketch. Users can also manipulate the geometry of existing scenes by editing the input semantic map. However, the process of creating and editing a semantic map can easily become a tedious task. In order to further simplify the creative process, a novel approach is proposed that maps input textual scene descriptions into renderable scene representations. The proposed method, Text2MPI, is a diffusion model trained to generate compact Multiplane Images (MPI) representations from text. Text2MPI generates crisp photorealistic novel views that are 3D-consistent and match the input text description. Furthermore, the proposed model harnesses the vast generalization capability of 2D diffusion models by integrating 2D scene priors into its training procedure. Tewodros Amberbir Habtegebrial doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9726 Mon, 16 Mar 2026 12:59:55 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9713 Translation is a ubiquitous, yet enigmatic process central to all cellular life on earth. Despite being a subject of research for many decades, its enormous complexity makes it difficult to study translation. The development of the Ribo-Seq technique, a combination of classical ribosome profiling and next generation sequencing, enabled scientists to get a closer view at translating ribosomes than ever before. This technique allows to investigate the topic with unprecedented detail and to generate deep insights into the mechanics and regulation of translation. In this study, a Ribo-Seq protocol for C. reinhardtii and a Python module for the analysis of Ribo-Seq data was presented. The data generated was analyzed translatome-wide and its quality was assessed regarding sequencing depth, the RPF’s frame preference and their length distribution. The data delivered deep insights into the mixotrophic translatome, clearly demonstrating the dominance of anabolism-related transcripts. Analysis of 5’-P-site offsets shed light on the mechanics of cytosolic translation revealing a clear tri-nucleotide periodicity of cytosolic RPFs. It was shown that ribosome profiles reproducibly reflect the dynamics of translation and can be utilized to refine genomic annotations. The appearance of an RNAi-related ribosome-binding protein (VIG1) among the 150 top-translated transcripts, together with the frequent observation of extreme RPF-coverage within initiation regions indicates that regulation of cytosolic translation in C. reinhardtii may be more complex than previously anticipated. Analysis of chloroplast RPFs indicated that chloroplasts evolved highly specific mechanisms to fine-tune translation and that translational activity in the chloroplast may be regulated on a high level by the titers or ribosomal proteins Rpl20 and PRPL7. An analysis of the translatome of a knock-down mutant of uS11c revealed four transcripts depending on the protein for translation as well as a list of transcripts putatively involved in the formation of palmelloid colonies. Additionally, a seRP approach suggested psaB and ftsH as targets of a transient co-translational interaction of cpSRP54 with the chloroplast ribosome and pointed towards the protein’s involvement in a putative co-translational protein import pathway into the chloroplast. Parts of this study have been published previously in a scientific Journal in the publication “Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas” (Gotsmann et al., 2024). Furthermore, the RPF coverage of genes in the C. reinhardtii genome, version 6.1 was published on the Phytozome platform (Goodstein et al., 2012) to enable the scientific community to compare existing genomic annotations against Ribo-Seq data. Vincent Leon Gotsmann doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9713 Mon, 16 Mar 2026 11:05:22 +0100 https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9716 The automotive sector has seen a surge in demand for increased safety, comfort, and flexibility, driven by the growing popularity of advanced driver assistance systems (ADAS). Detection of other traffic participants in 2D and 3D is essential to avoid accidents and ensure safety. Despite its importance, there has been limited research on reliable pedestrian detection for automotive, particularly when pedestrians are at a distance, e.g., 20-50 meters. This thesis explores different sensor fusion approaches to achieve optimal performance in object detection and human pose estimation, considering the specific strengths and weaknesses of the used sensors. The goal is to determine when and why to use specific fusion methods to achieve reliable perception of the environment, which is critical for ensuring safety and preventing accidents. For monocular 3D detection a 3D decoder and new loss functions are introduced, to achieve state-of-the-art performance and understand the limitations and advantages of RGB-only setups. However, it is limited by the depth ambiguity, where objects at different distances appear similar in the image. Geometric fusion using camera and lidar sensors overcomes this limitation. An approach for long range pedestrian detection (LRPD) focuses on maintaining high performance at long ranges. Showcasing the robustness and versatility of geometric fusion, an approach for human pose estimation using RGB and lidar (HPERL) is developed. A detailed evaluation attributes the gains to depth perception with a significant reduction in center depth error. To address the requirement for complex calibration, a novel calibration-free learned fusion approach is introduced. The approach is able to learn fusion of features, using self-attention. As a result, the approach has strong robustness against random translation and rotation, since it does not depend on the exact sensor alignment like calibration based approaches. Finally, temporal fusion is explored to overcome missing object permanence in current object detectors. The proposed integrated object permanence (IOP) uses predictions of previous frames as priors for the current frame, enabling more reliable detection, even when objects are partially or briefly occluded. Highlighting the importance of sensor fusion in autonomous driving, this work reveals suitability of fusion for various use-cases. Geometric fusion achieves optimal performance, while learned fusion provides calibration-free solutions. Temporal fusion addresses the issue of missing object permanence. David Michael Fürst doctoralthesis https://kluedo.ub.rptu.de/frontdoor/index/index/docId/9716 Mon, 16 Mar 2026 10:16:57 +0100