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Zeitweise fließfähige selbstverdichtende Verfüllbaustoffe (ZFSV) bestehen aus Bodenmaterial, Bindemitteln (z. B. Zement), Wasser und Zusatzstoffen, z. B. Bentonit. Sie zeichnen sich durch Fließfähigkeit im frischen Zustand und Verfestigung nach dem Einbau aus, ohne mechanische Verdichtung zu benötigen. ZFSV sind Boden-Bindemittelgemische wie Bodenbehandlungen mit Bindemitteln, Baugrundverbesserungen im Nassmischverfahren, Betone und Mörtel, weshalb die Einordnung und Abgrenzung der Materialeigenschaften vorgenommen werden. Die Beschreibung des erhärteten Materials erfolgt mit Methoden der Bodenmechanik. Besondere Beachtung erfordern die rheologischen Eigenschaften im fließfähigen Zustand und die zeitabhängigen Veränderungen der Materialeigenschaften. ZFSV werden mit unterschiedlichen Rezepturen im Rohr- und Leitungsbau sowie für die Bettung von Fernwärme- und Stromleitungen und als Baugrundverbesserung für Flächengründungen und Stützbauwerke eingesetzt.
Metal–Organic Frameworks (MOFs) have emerged as promising materials for optical sensing due to their refractive index response to guest molecule uptake within their porous structure. However, in situ characterization of MOF refractive indices, particularly directly on sensor substrates, remains a significant challenge. Here, we present a novel method to quantify the refractive index of MOF thin films grown on multimode optical fibers via far-field intensity patterns (FFPs), demonstrated using ZIF-8. Refractive indices were determined under vacuum, nitrogen, and methane atmospheres by evaluating the radii of the corresponding FFPs, establishing a direct quantitative relationship between refractive index and transmitted light power. The method was validated using aqueous sodium metatungstate (SMT) solutions of known refractive index applied to a cladding-stripped reference fiber. ZIF-8 thin films grown directly on exposed multimode fiber cores enable transmission-based gas sensing. Gas adsorption in the ZIF-8 pores increases the film’s refractive index, leading to decoupling of high-order guided modes, hence reducing light transmission. Transmitted intensity was measured under vacuum, nitrogen, and methane (1 bar) to assess sensitivity and selectivity. Scanning electron microscopy (SEM) revealed a continuous ZIF-8 thin film with distinct crystallites on the fiber surface and a defect-free reference core after mechanical stripping
Autonomous Driving (AD) has advanced significantly in recent years, yet widespread deployment remains limited. One of the most enduring challenges in Autonomous Vehicle (AV) development is planning a safe, comfortable, and efficient motion in complex, real-world environments. This thesis addresses motion planning across three distinct domains: urban shuttles, passenger vehicles, and truck-trailer systems. It contributes practical insights and novel approaches toward scalable autonomous mobility. The first part of this work presents an integrated motion planning framework for the Continental Urban Mobility Experience (CUbE) driverless shuttle. Extensive real-world testing over several years highlights the system’s robustness and underscores the importance of long-term validation in urban settings. Key innovations include a multi-layered planning stack and a data-driven motion forecasting approach that enhances interaction with human traffic participants. The second part investigates the behavior of human drivers in understructured traffic environments. Those are areas that fall between well-defined road systems and fully unstructured spaces. A novel analysis framework is introduced for mining patterns from naturalistic trajectory datasets, enabling AVs to better blend into human traffic and navigate ambiguous scenarios with improved predictability and safety. The final part of the thesis explores Deep Reinforcement Learning (DRL) for planning and controlling complex truck-trailer maneuvers. A DRL-based approach is developed and evaluated in simulated environments, demonstrating the method’s potential to handle the nonlinear dynamics of articulated vehicles. These contributions advance the field of motion planning by combining theoretical insights, system-level integration, and empirical evaluation. They offer pathways for improving AV behavior across diverse platforms and use cases, ultimately supporting the broader adoption of AD technologies.
Model-Driven Software Engineering has long excelled at generating code from static structural models, yet the specification and generation of dynamic behavioral models remains a persistent challenge. Meanwhile, Large Language Models (LLMs) offer flexible, natural-language based code generation but suffer from non-determinism and hallucinations. This paper presents a semi-formal approach that bridges these two paradigms for behavioral modeling via UML state machines. We contribute a textual modeling language that captures the essential elements of UML state diagrams-states, transitions, events, guards, and entry/exit actions-alongside a deterministic code generator that transforms state machine models into Java code following the Gang of Four State design pattern. The language supports two complementary action annotation styles: direct code fragments for concise, self-contained actions, and natural language descriptions for semantically richer behavior to be completed by an LLM weaver . LLM involvement is deliberately scoped to small, well-constrained action bodies, reducing token consumption and non-determinism compared to fully LLM-based approaches. Validated through the Gumball Machine case study, correctness is confirmed by automated tests covering state and transition coverage criteria, and repeating the LLM weaving step produced consistent results across all runs. Compared to both classical UML tooling and fully LLM-based generation, the approach offers stronger determinism, better traceability, lower cognitive modeling effort, and reduced computational cost, while retaining the flexibility to express complex action behavior in natural language where formal specification would be unnecessarily burdensome.
The thermal management-induced drag of conventional ram-air cooling systems for low-temperature fuel-cell propulsion can account for roughly 20% to 25% of total drag in fuel-cell aircraft concepts, while its mass and power impact at the overall aircraft level are far less significant. This drag penalty can severely reduce efficiency, especially when additional parallel power sources for takeoff such as gas turbine engines are undesirable. To address this, we propose augmenting low- and medium-temperature fuel-cell cooling with an auxiliary water-evaporation system. This mechanism is used only when needed, primarily during takeoff in hot ambient conditions, while the ram-air system can be downsized to meet cruise requirements. Water evaporation can achieve coefficients of performance of 50 to 100, while reducing the required mass flow by two orders of magnitude. It provides a heat-rejection energy density of approximately 670 Wh/kg, far exceeding that of state-of-the-art high-power-density batteries. Furthermore, the resulting vapor can be vented overboard, and the system is expected to outperform batteries in reliability, durability, and environmental impact. The paper introduces several architectures for integrating water-evaporation cooling into aircraft systems and discusses their respective advantages, limitations, and implications for overall aircraft performance. Initial results indicate that enabling evaporative cooling can significantly reduce the required ram-air channel size and drag, offering a promising pathway to more efficient fuel-cell-powered aircraft. In the EU project TheMa4HERA, aircraft-level design trades and scaled experimental validation for aviation applications of water evaporation are planned in 2026.
Transferable Enzyme-Polymer Stickers for Modular Assembly of Single and Multi-analyte Biosensors
(2026)
Electrochemical biosensors have achieved widespread commercial success due to their high selectivity, ease of use, and low cost. However, the fabrication of many such systems, especially when targeting multianalyte sensing, is often constrained by the preparation of the sensing 5 film, which typically relies on drop-casting polymer–enzyme solutions followed by drying to form the active layer. Depending on the 6 enzyme-polymer formulation, this step can be difficult to integrate into large-scale, roll-to-roll production processes and lacks flexibility for constructing multianalyte sensors. Here, we introduce a new assembly strategy in which sensing films composed of redox-active polymers and enzymes are pre-fabricated as sensor stickers that can be transferred in a single step either onto individual electrodes to generate single-analyte sensors or combined on electrode arrays for multianalyte sensing. We demonstrate the sensor sticker conc ept using four oxidoreductases as biorecognition elements targeting four analytes: hydrogen, formate, nitrate, and NADPH. Accurate sensing was achieved both on conventional glassy carbon electrodes and on custom-designed microelectrode arrays modified with the sensor stickers. The resulting sensors displayed high selectivity with minimal cross-interference, even in complex mixtures containing all four analytes. This modular approach to assembling multianalyte sensors on microarrays is broadly applicable to other analytes and holds strong promise for flexible, customizable, and scalable fabrication of multianalyte biosensors.
Dieses Lehrbuch vermittelt Studierenden der Sozial- und Gesundheitswissenschaften fundierte ethische Kompetenzen für ihre spätere Berufspraxis in den vielfältigen Handlungsfeldern. Der Autor macht deutlich, dass Soziale Arbeit und Gesundheitsberufe im Kern ethische Professionen sind und der Weg zur Profession nur über eine Berufsethik führt. Anhand konkreter Fallbeispiele und Dilemmata aus dem Berufsalltag (Angewandte Ethik) werden zentrale Fragen der Professionsethik praxisnah erörtert. Studierende erhalten zunächst einen Überblick über wichtige philosophische, anthropologische und ethische Ansätze und Prinzipien. Weitere Kapitel widmen sich aktuellen Herausforderungen wie Friedensethik, Klimaprotestaktionen, Künstlicher Intelligenz, Interkulturalität und Interreligiosität, Rollenkonflikten und Ökonomisierung. Mit Hilfe einer vom Autor entwickelten speziellen Diskursmatrix werden die ethischen Dimensionen der Themen aus verschiedenen Perspektiven beleuchtet. Diesen pädagogisch-didaktischen Ansatz hat der Autor auf der Grundlage seiner langjährigen Expertise als Lehrender mit Lernenden an Hochschulen (weiter-)entwickelt. Urteilsfähigkeit und begründete Entscheidungsfindung werden ebenfalls trainiert. Insgesamt vermittelt das Buch die professionsethischen und reflexiven Kompetenzen, die für verantwortliches, wertebasiertes Handeln in Sozialer Arbeit und in Gesundheitsberufen unerlässlich sind. Ein Muss für angehende Profis!
Tonal sounds are often a part of the interior sound in electric vehicles (EV), and their presence can influence the judged sound quality. When generated by the drivetrain, they are especially audible in dynamic driving conditions like acceleration at low speeds. In this study, tonality and unpleasantness was rated in separate experiments for several compositions of tonal components. Synthetic sounds were derived from real EV interior recordings and simulated an acceleration from 250 to 2500 RPM within a duration of 8 seconds. All stimuli contained broadband background noise which increased linearly in sound pressure over time and had a spectral decay of -12 dB/octave. The embedded tonal signatures were either single or multiple orders with different levels of tone-to-noise ratio, either with or without an additional gear order. When present, the additional gear order created either a consonant or dissonant frequency interval with the baseline motor order. The results indicate a main effect of the tone level for the tonality and unpleasantness ratings. Furthermore, the tonality grows with the number of tonal components whereas the unpleasantness seems to be mostly determined by the frequency of the highest tone and the gear ratio only at high tone levels.
