LectureChat extends the WikiChat conversational AI system by integrating multilingual university lecture transcripts alongside

Wikipedia content. The demo showcases a dual retrieval architecture that combines structured encyclopedic knowledge with academic lecture

material, leveraging multiple segmentation strategies and cross index reconciliation to improve retrieval quality. The system maintains separate

citation spaces for Wikipedia (numeric) and lectures (alphabetic) and preserves temporal provenance for direct video navigation. We present

the overall architecture, interaction flow, implementation details, and a reproducibility plan.

The escalating challenges of the 21st century demand a rethinking of design education, as traditional methods no longer prepare designers to address complexity or contribute to resilient societies. This paper introduces Interwoven Futures, an initiative from a product design department that emphasizes hands-on practice, critical reflection, and multi-stakeholder collaboration. Rather than focusing on linear problem-solving, it equips students to navigate uncertainty and systems-level change. The project has three components: a university-industry collaboration with VAUDE, a curated publication, and a public event. Together, these elements engage with ecological and societal issues while cultivating designers as agents of change who learn to stay with the trouble in real-world contexts. The paper discusses the structure, findings, and implications of Interwoven Futures, positioning it as a case study in adaptive, future- oriented design education that contributes to the evolving discourse on sustainability in design.

Physiological synchrony refers to the temporal alignment of bodily signals, such as heart rate variability, between two or more individuals during social interaction. It reflects implicit, often unconscious processes that arise when people share attention, emotions, or behavioral rhythms in close physical proximity. Because these coordinated physiological patterns are linked to social cohesion, rapport, and effective communication, physiological synchrony provides a valuable window into the quality and dynamics of social interaction. Here, we study physiological synchrony during virtual interaction where interaction partners are not physically co-located but remotely connected via technology. This allows us to capture aspects of social connectedness that are not accessible through self-report or behavior alone, making it a powerful tool for understanding how people engage and collaborate across different media. In our study, triads of participants performed a collective creativity task in one of three conditions: face-to-face (F2F) collaboration, remote collaboration using video conferencing (Video), or remote collaboration using immersive Virtual Reality (VR). To quantify social interaction quality, we measured creative group performance, social presence, and heart rate variability synchrony (HRVS) as a marker of social cohesion. As expected, creative group performance and social presence were highest in the F2F condition and significantly reduced in the VR and Video conditions. However, we observed strong HRV synchrony in the VR and F2F conditions and significantly weaker HRV synchrony in the Video condition. Our study supports the idea that VR (unlike video conferencing) supports physiological synchronization processes important for social interactions. Future studies need to identify the underlying physiological and psychological processes.

In this short experience report, we present our attempt to integrate output from an ongoing research project with a traditional, mostly literature-based, course on media manipulation, bias and fake news, to turn an existing undergraduate course into a more engaging experience for attending students. To this end, we successfully utilized our system BiasScanner for news bias detection and classification (BiasScanner.org).

In this paper, a novel sensing structure to be used for real-time monitoring of soil movements in construction sites is proposed. The structure integrates an array of sensor nodes, to be deployed at different depths according to a tree-shaped structure. Each sensor node measures temperature, Volumetric Water Content (VWC) and soil movement, by exploiting the measurement of pressure variations exerted by a column of water on pressure sensors positioned in the soil. The structure manages the acquisition of data from each sensor node every 30 minutes and transmits it to a remote data management centre using the Long Range Wide Area Network (LoRaWAN) protocol. A prototype of the structure was designed, developed and installed at a test site in Coburg. The results acquired across several months of experimentation demonstrate the accuracy of the measurements as well as the reliability of the overall sensing structure.

Der Grönländer Samuel Kleinschmidt (1814-1886) war Wissenschaftler, Lehrer und Missionar der Herrnhuter Brüdergemeine in Neuherrnhut, das heute zur grönländische Hauptstadt Nuuk gehört. Er hat nicht nur die grönländische Sprache aufgezeichnet und weiterentwickelt, sondern um die Mitte des 19. Jahrhunderts auch Karten von Grönland erstellt, die so detailliert waren, dass sie zu Referenzwerken der europäischen Kartografie wurden. Gefördert durch den dänischen Wissenschaftler und Kolonialverwalter in Grönland Hinrich Rink und unterstützt von vielen weiteren Geografen in ganz Europa, darunter dem einflussreichen Verlag Justus Perthes in Gotha, fuhr Kleinschmidt die Küsten in West- und Südgrönland mit dem Kajak ab, um sie mit einfachsten Geräten zu vermessen und aufzuzeichnen; aus entfernteren Regionen erhielt er genaue Berichte.

Während die Inuit sich nicht mit Karten, sondern mit Hilfe von Reiseberichten, Überlieferungen und Landschaftsmarkierungen orientierten, ließ Kleinschmidt seine Karten nach europäischer Tradition drucken und vervielfältigen. Sie waren so zuverlässig, dass sie im entlegenen und vereisten Grönland eine Küstenlandschaft erkennen ließen, wie sie sonst nur von mediterranen Portolankarten bekannt war. So trugen die Karten schon vor hundertfünfzig Jahren dazu bei, dass sich aus der Fokussierung auf das „ewige Eis“ des Nordpols allmählich eine arktische Meereskartografie entwickelte. Kleinschmidts politische und wissenschaftliche Leistungen sind vielfach beschrieben worden. Seine Karten wurden jedoch nur en passant beachtet. Der Vortrag wird ihre kartografische Bedeutung erläutern und sie in den Zusammenhang zur Kultur der Inuit, zur europäischen Kartografie und der voranschreitenden Erforschung der Arktis stellen.

Aims: This study introduces and evaluates a virtual reality (VR) prototype designed for the Loving-Kindness Meditation (LKM) to support
mental health rehabilitation and relaxation in clinical contexts. The aims include the co-creation of a VR-based mindfulness experience with
clinical experts and the evaluation of its usability, user experience, and short-term effects on relaxation, affect, and self-compassion.

Methods: Following a design thinking and co-creation approach, the VR-based LKM experience was developed iteratively with input from
clinicians and computer scientists. The final prototype was implemented for the Meta Quest 3 and included five immersive scenes
representing phases of the LKM and transition scenes guided by a professionally narrated audio track. Eleven participants (M = 36.5 years,
SD = 14.6) experienced the 12-minute session. Pre- and post-session measures included relaxation, positive and negative affect schedule,
and self-compassion, complemented in the end by the Igroup Presence Questionnaire, usability measures and a semi-structured qualitative
interview.

Results: Participants reported significant decreases in negative affect (t(10) = -2.512, p = .0307, d = -1.037) and stress (t(10) = -3.318, p = .007,
d = -1.328), as well as increases in relaxation (t(10) = 5.487, p < .0001, d = 2.471) and self-compassion (t(10) = 2.231, p = .0497, d = 0.283).
Usability was rated as excellent (M = 92.5), and presence as good (M = 4.0, SD = 0.43). Qualitative feedback described the experience as
calming, aesthetically pleasing, and easy to engage with, highlighting the falling leaves and pulsating orb as effective design elements.

Conclusion: The co-designed VR-LKM prototype was perceived as highly usable and beneficial for inducing relaxation and self-compassion,
suggesting its potential as a supportive tool for clinical mindfulness interventions. The results indicate that immersive VR can effectively
facilitate engagement and emotional regulation, providing a foundation for future clinical trials and broader implementation in therapeutic
and wellness settings.

In der Coburger Landesbibliothek (Kt 478) befindet sich einer der ältesten seriell hergestellten Reliefgloben aus der Produktion des Berliner Globenherstellers Karl Wilhelm Kummer. Er stammt aus der Zeit um 1820/22. Wir werden Gelegenheit haben, diesen besonderen Globus im Original zu betrachten.

Blinden- und Reliefgloben haben keine glatte, sondern eine erhabene Oberfläche, durch die sie Gebirge und Täler besonders betonen und ertastbar machen. Sie vermitteln ein plastisches Bild der Geografie und wurden ursprünglich für Blindenschulen entwickelt.

Die Auseinandersetzung mit dem Globus führt zu grundsätzlichen Fragen über die Verwendung, die Techniken und Konventionen von Modellen unseres Planeten. Im Zeitalter der Globalisierung ist die Frage nicht unwesentlich, worum es sich bei dem "Globalen" eigentlich handelt und welche unterschiedlichen Wahrnehmungs-weisen darauf möglich sind.

We investigated the adaptation and performance of Masked Autoencoders (MAEs) with Vision Transformer (ViT) architectures for self-supervised representation learning on one-dimensional (1D) ultrasound signals. Although MAEs have demonstrated significant success in computer vision and other domains, their use for 1D signal analysis, especially for raw ultrasound data, remains largely unexplored. Ultrasound signals are vital in industrial applications such as nondestructive testing (NDT) and structural health monitoring (SHM), where labeled data are often scarce and signal processing is highly task-specific. We propose an approach that leverages MAE to pre-train on unlabeled synthetic ultrasound signals, enabling the model to learn robust representations that enhance performance in downstream tasks, such as time-of-flight (ToF) classification. This study systematically investigated the impact of model size, patch size, and masking ratio on pre-training efficiency and downstream accuracy. Our results show that pre-trained models significantly outperform models trained from scratch and strong convolutional neural network (CNN) baselines optimized for the downstream task. Additionally, pre-training on synthetic data demonstrates superior transferability to real-world measured signals compared with training solely on limited real datasets. This study underscores the potential of MAEs for advancing ultrasound signal analysis through scalable, self-supervised learning.