OPUS documents https://opus4.kobv.de/opus4-oth-regensburg/index/index/ Mon, 17 Aug 2026 10:17:16 +0200 Mon, 17 Aug 2026 10:17:16 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10123 The following topics are dealt with: radar imaging; iterative methods; electromagnetic fields; radar detection; learning (artificial intelligence); electromagnetic interference; transfer functions; image resolution; synthetic aperture radar; ferrites. Matthias G. Ehrnsperger; H. L. Hoese; U. Siart; T. F. Eibert conferenceobject https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10123 Mon, 17 Aug 2026 10:17:16 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10208 The strategic adoption of Artificial Intelligence (AI) is a critical determinant of competitive advantage, yet organizations face high failure rates. This paper aims to identify and categorize the Critical Success Factors (CSFs) that influence successful AI adoption by synthesizing academic and practitioner knowledge from a top-management perspective. We conducted a multivocal literature review of 57 academic and 20 practitioner sources, screened per PRISMA. From vote-count synthesis we identified 16 CSFs grouped via the Technology-Organization-Environment (TOE) framework, with organizational factors dominating such as leadership support, AI literacy, and cultural readiness. Practitioner evidence corroborates most academic CSFs and adds implementation-centric aspects (e.g., AI scalability, use-case–value alignment, partnerships). Implications for top management/Chief Information Officers include prioritizing data governance, change capability, and portfolio-level value realization. From a theoretical perspective, the paper supports continued relevance of the TOE framework for AI while highlighting the amplified importance of its organizational dimension. Leonhard Bürkner; Markus Westner conferenceobject https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10208 Mon, 17 Aug 2026 10:02:05 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10205 Aims  Systematic visualization of anatomical landmarks is critical to prevent "blind spots" during esophagogastroduodenoscopy (EGD), which are a primary cause of missed upper gastrointestinal cancers. Standardized documentation serves as a secondary but essential tool for quality assurance. We aimed to develop a deep learning approach for the automated classification of 28 anatomical categories, including a 22-segment mapping of the stomach based on the Japanese Systemic Stomach Screening (SSS) protocol. The primary goal was to provide a technical foundation for real-time monitoring of mucosal coverage to ensure examination completeness. Primary outcomes were macro F1-score and overall accuracy for this 28-class classification task. Methods  We used a multi-center dataset of 9.012 endoscopic images from 1.553 patients, merging the public GastroHUN database (5.202 images; 385 patients) [1] and an internal dataset (3.810 images; 1.168 patients) from a European tertiary referral centre (Augsburg, Germany). All images were obtained during routine EGD using Olympus endoscopes and anonymized prior to analysis. Each image was labelled at image level into one of 28 anatomical classes: oropharynx, esophagus, esophagogastric junction, duodenal bulb, second part of the duodenum, papilla and 22 gastric segments based on the SSS classification using a consensus-based multi-annotator process (n=4). A trained and supervised specialist annotated additional data from Augsburg. To handle this complexity, we employed a Vision Transformer (ViT-L/14) foundation model pre-trained via DINO-v2. Instead of full-parameter fine-tuning, which risks overfitting on medical datasets, we implemented Low-Rank Adaptation (LoRA) [2]. By targeting only the Q- and V-projection layers in the final six transformer blocks, we reduced the trainable parameters to 312.000 (0.36% of the total model). Evaluation was performed using a strict patient-wise 5-fold cross-validation. Results  The model achieved a mean macro F1-score of 0.88±0.01 and an overall accuracy of 0.88±0.01. Beyond robustly identifying major regions like the esophagus and duodenum, the model showed high precision in the more challenging differentiation of fine-grained SSS segments. The use of LoRA enabled stable training and strong generalization across the combined international and local datasets ([Abb. 1]). Conclusions  Integrating transformer-based foundation models with LoRA-based fine-tuning allows for highly accurate UGIT anatomical mapping. An F1-score of 0.88 across 28 classes suggests that this approach is robust enough for automated documentation and real-time quality monitoring. Future work will focus on expanding the multi-center data volume and implementing expert consensus-labeling across all subsets to fürther refine model reliability, alongside developing a real-time visualization tool that provides an intuitive overview of the explored segments. To our knowledge, this is among the first studies to leverage a public endoscopy dataset together with institutional data for upper GI anatomical site classification. P. Löffler; Danilo Weber Nunes; David Rauber; Y. Ignatenko; M. Kaspar; Christoph Palm; Helmut Messmann; David A. Roser conferencepresentation https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10205 Mon, 17 Aug 2026 09:48:37 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10206 Die zuverlässige endoskopische Einschätzung der Infiltrationstiefe bei Neoplasien des Barrett-Ösophagus (BO) ist entscheidend für die Therapieentscheidung zwischen organerhaltender endoskopischer Resektion und chirurgischer Resektion. Ziel dieser Studie ist die Entwicklung eines KIVision- Modells, das endoskopisch kurativ resezierbare Läsionen (LGD; HGD; T1a m1 –T1b sm1, L0, V0 und G1-2; EREAC) von nicht kurativ endoskopisch resezierbaren Läsionen (≥ T1b sm2 und/oder L1, V1, G3; NEREAC) anhand endoskopischer Bildgebung unterscheidet. In einer Pilotstudie mit 116 Patient:innen wurde bei der Unterscheidung von T1a vs. T1b mit 230 Bildern ein F1-Score, eine Sensitivität und Spezifität von 74%, 77% und 64% erreicht. [1] Material und Methodik Es handelt sich um eine ambidirektionale multizentrische Studie mit insgesamt n=578 Patient:innen und n=651 Läsionen im Zeitraum Januar 2014 bis Juni 2025. Eingeschlossen wurden Patient:innen mit gesicherter BO-assoziierter Neoplasie anhand des histologischen Goldstandards durch a) endoskopische Submukosadissektion (ESD) oder b) chirurgische Resektion. Insgesamt wurden 526 Läsionen im Arm EREAC und 125 Läsionen der Gruppe im Arm NEREAC akquiriert. Es werden Bild- und Videodaten aus Olympus und Fuji-Endoskopen verwendet. Aus der Videodokumentation wurden Frames extrahiert und anhand eines vordefinierten Schemas annotiert (u.a. Lasionssichtbarkeit, virtuelle (NBI, TXI) und farbbasierte Chromoendoskopie, Zoommodus). Es erfolgte eine mehrstufige Annotation durch einen medizinischen Doktoranden (J.B.), mit 1:1 Supervision durch einen endoskopisch tätigen Facharzt im Bereich Gastroenterologie (D.R.), sowie durch einen Barrett-Experten (A.E). Aufgrund einer Klassenimbalance zugunsten der EREAC-Gruppe erfolgt zunachst eine Zwischenanalyse aus 185 Patient:innen mit 215 Läsionen mit a 500 Frames. Mittels ConvNeXt Tiny Architektur wurde eine 5-fache Cross-Validierung mit Split auf Patientenebene durchgeführt. Primare Leistungsmetriken sind F1-Score, Sensitivität und Spezifität. Ergebnisse Im aktuellen Test erreichte das KI-Modell für die Klassifikation (EREAC vs. NEREAC) einen mittleren F1-Score von 78.3% (resektabel: 79.8%, nicht 2 resektabel: 76.8%). Die mittlere Sensitivität und Spezifität lag bei je 78.3%. Die klassenspezifische Sensitivität und Spezifität zur Erkennung von NEREAC lag bei 72.0% und 84.6%. Zusammenfassung Ein KI-Assistenzmodell kann die endoskopische Einschatzung der Resektabilität von Barrett-Neoplasien unterstutzen, indem es die Infiltrationstiefe aus endoskopischer Bildgebung pradiziert. Klinisch besonders relevant ist die hohe Spezifität in der Erkennung nicht-resektabler Läsionen. Nächste Schritte sind das weitere Training mit höherer Datenmenge, die adressierte Aufarbeitung der Klassenimbalance, externe Validierung sowie die Echtzeit-Implementation. Jari Bellinghoven; Raphaela Märkl; David Rauber; Alanna Ebigbo; Christoph Palm; Sandra Nagl; Andreas Probst; Helmut Messmann; David Roser conferencepresentation https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10206 Mon, 17 Aug 2026 09:41:20 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10207 This data article describes the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) dataset, a collection of eight complete laparoscopic cholecystectomy videos acquired during routine minimally invasive procedures at three German medical centers. The recordings were captured with different monocular endoscopic camera systems at 25 frames per second and a resolution of 1920 × 1080 pixels, with durations ranging from 28 to 58 minutes. Segments showing regions outside the abdominal cavity were removed for anonymization, and the corresponding cut indices are provided. The dataset offers unified annotations for three interrelated tasks on the same complete surgical sequences: surgical phase recognition, annotated for every frame at 25 fps (485,875 frames), instrument keypoint estimation (19,435 frames), and instrument instance segmentation (19,435 frames), each annotated at one frame per second (every 25th frame). Surgical phases follow the seven-phase Cholec80 scheme, extended by an undefined label for transitional frames. The instrument annotations distinguish 19 instrument classes as well as individual instances of the same class, with keypoint annotations comprising two to four class-dependent points labeled with COCO-style visibility states. Segmentation and keypoint labels were created manually using the Computer Vision Annotation Tool (CVAT), whereas phase labels were derived from documented phase-transition timestamps, and all annotations underwent a multi-stage review by a medically trained team. The data are provided in open formats (MP4, CSV, JSON, PNG) together with a frame-extraction script under the CC BY-NC-SA license and are available through controlled access upon request via the Zenodo platform. Because the dataset combines procedural context, instrument pose, and pixel-accurate instance segmentations within full-length recordings from multiple institutions, it can be reused for single-task or multi-task model development, for temporally aware approaches that exploit motion continuity, and for cross-institutional generalization protocols such as leave-one-hospital-out evaluation. The dataset served as the training resource for the PhaKIR Challenge at the Endoscopic Vision (EndoVis) Challenge at MICCAI 2024. Tobias Rückert; Raphaela Maerkl; David Rauber; Leonard Klausmann; Max Gutbrod; Daniel Rueckert; Hubertus Feussner; Dirk Wilhelm; Christoph Palm article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10207 Mon, 17 Aug 2026 09:38:20 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10132 Rainer Schliermann; Oliver Stoll conferenceobject https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10132 Fri, 14 Aug 2026 16:36:40 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10134 Margit Stein; Carl Heese; Hans-Ludwig Schmidt bookpart https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10134 Fri, 14 Aug 2026 16:30:47 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10133 Bernhard Babi´c; Margit Stein; Carl Heese bookpart https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10133 Fri, 14 Aug 2026 16:13:15 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10200 Background Digital therapeutics (DTx) are patient-facing apps designed to support individuals in their daily lives. Therefore, they have the potential to revolutionize healthcare by empowering and engaging patients as active stakeholders in their own care. Despite the increasing adoption of DTx in national healthcare systems, research on their design remains limited. Objective The present research article introduces “DiGATax”, a taxonomy designed to categorize and analyze DTx, including perspectives on content, intervention delivery logic and technology, as well as the patient’s interface, consolidating and expanding upon prior taxonomic work. Methods The taxonomy was created through a multi-method approach, combining a systematic review of existing digital health taxonomies with a qualitative analysis of n = 44 evidence-based, permanently listed applications from the German DiGA directory. Additionally, a taxonomy-based cluster analysis was performed to identify archetypes in the current DTx landscape. Results The proposed taxonomy comprises 19 dimensions and 108 characteristics, enabling a systematic classification and discussion of existing applications. Cluster analysis identified three archetypes: personal goal-centered, gameful designed, and conversational-driven, with the latter dividing into two subtypes. Additional exploratory analyses examined the user interface as a potential factor associated with user acceptance and explored possible links between DTx design, health-related and engagement outcomes. Conclusions By offering new insights into DTx design, this study contributes towards more organized research and reporting, ultimately paving the way for the development of effective solutions. It also marks a further step towards Meta-DTx, which aim to align patient care for multimorbid patients under one umbrella. Egidia Cenko; Thure Georg Weimann; Georgios Raptis article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10200 Fri, 14 Aug 2026 15:52:21 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10203 Shaping the spatial intensity profile of the process laser beam is a promising approach for improving part and surface quality in laser powder bed fusion. However, practical implementation is limited by logistical or economic constraints, since the process beam shape needs to be adapted depending on the material and print process conditions, often involving specialized laser sources or complex optical setups. Here, a single refractive focal beam shaping optic is employed to realize laser beam intensity variations of Gaussian, flat-top (tophat) and annular (ring) beams by controlled defocusing. Additionally, a conduction-mode thermal model using measured beam profiles and temperature-dependent properties is implemented. The model correlates well with published single-track melt pool dimensions for Gaussian and ring beams and predicts lack-of-fusion defects. The observations indicate that tophat and shallow ring beam profiles lead to a smaller spread of part density values in SS 316L across low to moderate energy densities, compared to other beam profiles explored in the study. Topographical characterization of the top surfaces indicates that tophat beams exhibit superior surface quality (lower roughness). Frederik Maiwald; Thejaswi U. Tumkur; Felix Weiß; Manyalibo J. Matthews; Stefan Hierl; Michael Schmidt article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10203 Fri, 14 Aug 2026 10:53:35 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10199 AI-generated text is produced at scale across diverse domains and heterogeneous generators, making robustness to distribution shift a central requirement for reliable detection. We train transformer-based detectors on HC3-Plus and adopt a deployment-realistic fixed-threshold protocol: a single decision threshold is calibrated on held-out validation data and kept fixed across all downstream test distributions. This protocol reveals that near-ceiling in-domain performance (up to 99.5% balanced accuracy) degrades significantly under cross-dataset and generator shift, exposing strong complementary failure modes across backbones (human-preserving vs. AI-aggressive). Feature augmentation that fuses handcrafted linguistic signals with transformer representations via a learnable attention module substantially improves transfer: while BERT and RoBERTa show complementary weaknesses, our best configuration, DeBERTa-v3-base + FeatAttn, yields the most balanced and robust profile, reaching 85.9% balanced accuracy on the multi-domain, multi-generator M4 benchmark (81.3% human recall, 90.5% AI recall). Multi-seed experiments (5 seeds) confirm high stability with a macro-average of 83.15 ± 1.04% on M4, and under the exact same fixed-threshold protocol our model outperforms strong zero-shot baselines (Fast-DetectGPT, RADAR, Log-Rank) by up to +7.22 points. Category-level ablations further show that readability and vocabulary features contribute most to robustness under shift. Overall, these results demonstrate that feature augmentation and a modern DeBERTa backbone significantly outperform earlier BERT/RoBERTa models, while the fixed-threshold protocol, combined with generator-aware error profiling and explicit feature analysis, provides a more realistic and informative assessment of practical detector robustness. Mohamed Mady; Johannes Reschke; Björn W. Schuller preprint https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10199 Wed, 12 Aug 2026 10:02:04 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10198 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. Thomas Neidhart; Jürgen Quarg-Vonscheidt; Ulrich Trunk article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10198 Fri, 07 Aug 2026 08:05:21 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10058 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 Valerius Abb; Artur Samp; Jens Fürst; Jörg Franke; Martin Kammler preprint https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10058 Mon, 03 Aug 2026 15:05:17 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10059 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. Andreas Hartmannsgruber doctoralthesis https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10059 Mon, 03 Aug 2026 14:44:34 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10197 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. Oliver Engling; Felix Schwägerl; Thomas Buchmann conferenceobject https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10197 Mon, 03 Aug 2026 14:24:05 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10066 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. Raphael Gebhart; Luis Weber; Franciscus L. J. van der Linden conferenceobject https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10066 Wed, 29 Jul 2026 14:03:34 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10067 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. Xie Wang; Leonardo Castañeda-Losada; Hemlata Agarwala; Yan Xie; Jonas Honacker; Theresa Wenig; Stacy Reginald Iggan; Veronika Lederer; Michelle Judaeva; Steffen Roth; Michael Richter; Inês A. Cardoso Pereira; Rita R. Manuel; Dawit T. Filmon; Benjamin Fluhrer; Geet Mehta; David González-Pérez; Miguel Alcalde; Alaa Alsheikh Oughli; Tobias Vöpel; Steffen Hardt; Nicolas Plumeré preprint https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10067 Wed, 29 Jul 2026 13:58:53 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10196 Markus Seibt book https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10196 Wed, 29 Jul 2026 13:46:53 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10195 Markus Seibt book https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10195 Wed, 29 Jul 2026 13:41:04 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10068 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! Markus Seibt book https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10068 Wed, 29 Jul 2026 13:32:40 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10070 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. conferencesummary https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10070 Wed, 29 Jul 2026 13:10:11 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10071 We present a study to assess the feasibility and implications of replacing internal combustion engine vehicles (ICEVs) with battery-powered electric vehicles (EVs) in a car-sharing fleet. For the analysis, we used operational data from a local car-sharing company, which encompasses various aspects such as trip distance, start and duration, vehicle type, and pickup and return locations. To evaluate the impact of transitioning the entire fleet to EVs, we used EV and charger models to simulate the battery-powered trips and the necessary post-trip recharging. Both could affect the service quality of car-sharing services, as the requested trip distance might not be covered by an electric vehicle due to range or charging time limitations. Specifically, in our simulation-based analysis, we identified chains of consecutive bookings as a critical factor for car-sharing electrification. Furthermore, to assess the potential impact of electrification on the energy grid, we used data about the local grid load and its composition to relate it to the predicted vehicle charging times. This is an extended version of our previous paper, incorporating an additional dataset. Aliyu Tanko Ali; Andreas Schuldei; Martin Sachenbacher; Martin Leucker article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10071 Wed, 29 Jul 2026 12:59:36 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10072 The »Volta-German Shared Colonial Heritage Project« focuses on the archaeology and ›shared heritage‹ of German colonialism in the former Togo/Togoland colony. Following up on initial (field) research in 2022 and 2023, the Ghanaian and German project partners successfully ran an extended field season at Kpando in early 2024. Four lines of investigation were developed. The first involved detailed building archaeological studies of the Palace of the Paramount Chief as well as the so-called Sisters Convent in preparation for rehabilitation planning. The second study expanded research into the urban fabric of Kpando. Historic buildings were described and mapped with the aim of gaining a better understanding of the evolution of the town during the German colonial period. Intercultural building practices were of particular interest. A third line of research supplemented the above studies with investigations of historical sources as well as the documentation of local knowledge of the history of Kpando in the form of personal and family histories. As family histories are manifested in the built fabric of the town, this study adds an important local perspective to our investigations of building cultures during the late 19th and early 20th centuries. The fourth study initiated systematic research on colonial-period soundscapes in the Volta Region and beyond. Numerous church bells were documented, adding a new facet to the study of the ›shared heritage‹ of German colonialism in Africa. Cornelia Kleinitz; Wazi Apoh; Ernest K. Fiador; Christian Hartl-Reiter; Birgit Kleefeld; Dietmar Kurapkat; Jörg Linstädter; Kathrin Loges; Ute Verstegen; Annika Zeitler article https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10072 Wed, 29 Jul 2026 11:46:33 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10185 Florian Spirkl conferencepresentation https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10185 Wed, 29 Jul 2026 10:03:37 +0200 https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10194 Stampflehm stellt eine nachhaltige Alternative zu konventionellen Baustoffen dar. Um die Bemessung und Ansätze zur FE-Modellierung zu verbessern, sind geotechnische Betrachtungen des Baustoffs notwendig. Stampflehm besteht aus natürlich vorkommenden Böden, daher wird sein Verhalten maßgeblich durch bodenmechanische Prozesse beschrieben. Mithilfe von ersten Triaxialversuchen wird das mechanische Verhalten unter unterschiedlichen Spannungszuständen verdeutlicht. Katharina Pfahler; Thomas Neidhart; Charlotte Thiel conferencesummary https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/10194 Wed, 29 Jul 2026 09:38:12 +0200