Structural Optimization of Meta-Reinforcement Learning-based Finite-Control-Set Direct Torque Control of Permanent Magnet Synchronous Motors - Jakobeit, Darius; Peña López, Mario; Schenke, Maximilian; Haucke-Korber, Barnabas; Wallscheid, Oliver (2025 IEEE International Electric Machines & Drives Conference (IEMDC))

Reinforcement Learning-based Direct Torque Control of Externally Excited Synchronous Motors: a Proof of Concept - Haucke-Korber, Barnabas; Aung, Nyi Nyi; Schenke, Maximilian; Peña López, Mario; Jakobeit, Darius; Wallscheid, Oliver (2025 IEEE International Electric Machines & Drives Conference (IEMDC))

Reinforcement Learning Control of Three-Level Converter Permanent Magnet Synchronous Machine Drives - Peña López, Mario; Schenke, Maximilian; Jakobeit, Darius; Haucke-Korber, Barnabas; Wallscheid, Oliver (2025 IEEE International Electric Machines & Drives Conference (IEMDC))

Linear dimension of group actions - Devillers, Alice; Giudici, Michael; Hawtin, Daniel R.; Klawuhn, Lukas-André Dominik; Morgan, Luke
Two fundamental ways to represent a group are as permutations and as matrices. In this paper, we study linear representations of groups that intertwine with a permutation representation. Recently, D'Alconzo and Di Scala investigated how small the matrices in such a linear representation can be. The minimal dimension of such a representation is the linear dimension of the group action and this has applications in cryptography and cryptosystems. We develop the idea of linear dimension from an algebraic point of view by using the theory of permutation modules. We give structural results about representations of minimal dimension and investigate the implications of faithfulness, transitivity and primitivity on the linear dimension. Furthermore, we compute the linear dimension of several classes of finite primitive permutation groups. We also study wreath products, allowing us to determine the linear dimension of imprimitive group actions. Finally, we give the linear dimension of almost simple finite $2$-transitive groups, some of which may be used for further applications in cryptography. Our results also open up many new questions about linear representations of group actions.

Protest gegen Kommerzialisierung im Fußball: Theoretische Überlegungen zu Entstehung, Strukturen und Nutzen - Riedl, Lars; Meier, Heiko (FuG – Zeitschrift für Fußball und Gesellschaft)
Ausgangspunkt des Beitrags sind die wiederkehrenden Zuschauerproteste gegen die Kommerzialisierung des Fußballs und die Frage nach einer Erklärung für deren Entstehung. Gezeigt wird, dass Zuschauerproteste bereits umfassend beforscht sind, bislang allerdings keine theoretische Einordung zu ihrer Entwicklung vorgelegt wurde. Entsprechend liegt das Ziel des Beitrags darin, unter Rückgriff auf systemtheoretische Überlegungen, insbesondere auch zur Funktion des Publikums für den Fußball, und typologische Unterscheidungen, angereichert durch kulturanthropologische Betrachtungen, theoretische Erklärungen für die Ursprünge und Bedeutung von Zuschauerprotesten zu liefern. Im Anschluss hieran wird betrachtet, wie sich Zuschauerproteste in theoretische Konzepte zu Protestbewegungen einordnen lassen, um abschließend deren Nutzen für die Fußballclubs und -verbände zu bestimmen.

In Situ Investigation of the Frictional Behaviour in Friction-Spinning - Wiens, Eugen; Hijazi, Dina; Jüttner, Maik; Homberg, Werner; Kensy, Mark Dennis; Tillmann, Wolfgang (Journal of Manufacturing and Materials Processing)
Friction-spinning is an incremental thermomechanical forming process that has huge potential due to its simple yet effective mechanism of utilising friction between a rotating workpiece and a forming tool to increase the workpiece’s temperature, which reduces the required forces and increases formability during the forming process. Despite the simplicity of the process’s setup, the thermomechanical loads and high relative velocities involved, especially in the contact zone, make the application of classical methods for characterising friction inaccurate. It is therefore essential to find a way to describe the frictional behaviour under real process conditions to be able to gain a holistic understanding of the process and the effect of the adjustable parameters on the outcome, especially the temperature. To achieve this goal, an experimental setup that considers the actual process boundary conditions in forming tubes made of EN AW-6060 was used to measure in situ normal and frictional forces, in addition to process temperatures, under varying rotational speed and feed rate values.

Moderate-to-large deviation asymptotics for real eigenvalues of the elliptic Ginibre matrices - Byun, Sung-Soo; Jalowy, Jonas; Lee, Yong-Woo; Schehr, Grégory (arXiv:2511.09191)
We study the statistics of the number of real eigenvalues in the elliptic deformation of the real Ginibre ensemble. As the matrix dimension grows, the law of large numbers and the central limit theorem for the number of real eigenvalues are well understood, but the probabilities of rare events remain largely unexplored. Large deviation type results have been obtained only in extreme cases, when either a vanishingly small proportion of eigenvalues are real or almost all eigenvalues are real. Here, in both the strong and weak asymmetry regimes, we derive the probabilities of rare events in the moderate-to-large deviation regime, thereby providing a natural connection between the previously known regime of Gaussian fluctuations and the large deviation regime. Our results are new even for the classical real Ginibre ensemble.

Zeros of polynomial powers under the heat flow - Höfert, Antonia; Jalowy, Jonas; Kabluchko, Zakhar (arXiv:2512.17808)
We study the evolution of zeros of high polynomial powers under the heat flow. For any fixed polynomial $P(z)$, we prove that the empirical zero distribution of its heat-evolved $n$-th power converges to a distribution on the complex plane as $n$ tends to infinity. We describe this limit distribution $μ_t$ as a function of the time parameter $t$ of the heat evolution: For small time, zeros start to spread out in approximately semicircular distributions, then intricate curves start to form and merge, until for large time, the zero distribution approaches a widespread semicircle law through the initial center of mass. The Stieltjes transform of the limit distribution $μ_t$ satisfies a self-consistent equation and a Burgers' equation. The present paper deals with general complex-rooted polynomials for which, in contrast to the real-rooted case, no free-probabilistic representation for $μ_t$ is available.

Bildung und Lesesozialisation im Elternhaus - Buhl, Heike M.; Hilkenmeier, Johanna (Handbuch Entwicklungs- und Erziehungspsychologie)

Show, don’t tell - Developing and Validating a Role-Play-Based Simulation (RobS) for the Assessment of Pre-Service EFL Teachers’ Feedback Competence on Writing - Janzen, Thomas
raditional assessment formats in university-based EFL teacher education programs usually focus on cognitive dispositions rather than on the actual performance of pre-service EFL teachers in everyday teaching situations. This assessment gap is addressed in this thesis by developing and validating a role-play-based simulation (RobS) designed for the summative assessment of pre-service EFL teachers' feedback competence on writing. Drawing on theories from multiple disciplines, such as higher education, medical education, teacher education, educational psychology, and EFL-specific didactics, the RobS is developed as a performance-oriented assessment format. In the RobS, pre-service EFL teachers engage in a feedback conversation with trained actors who portray a standardized learner. Following an argument-based approach to validation, the extent to which the RobS can be considered valid is investigated. Data from multiple studies, focusing on aspects such as authenticity, fairness, reliability, and external validity, are presented. The discussion in the validity argument indicates that the RobS can elicit and assess the performative facet of feedback competence on writing with sufficient confidence. This work contributes a novel, empirically supported assessment framework to teacher education research. Moreover, it presents an approach to address the assessment gap, enabling pre-service EFL teachers to show how they provide feedback, rather than just tell their lecturers about it.

Process Mining for Robust Heat Integration through Process- and Product-Centric Energy Demand Modeling - Zapata Gonzalez, David Ricardo; Brennig, Katharina; Benkert, Kay; Schlosser, Florian; Müller, Oliver (ACM SIGEnergy Energy Informatics Review)
Decarbonizing industrial process heat is a crucial step in mitigating climate change. While Process Mining (PM) has gained traction in sustainability research—such as optimizing production scheduling to reduce energy use or accounting for carbon footprints—it has largely overlooked the challenges and opportunities related to thermal energy, accounting for 66% of total energy demand in industrial processes. At the same time, Heat Integration (HI) is an established engineering discipline focused on maximizing the efficiency of thermal energy systems. However, HI traditionally relies on static or incomplete data about energy demands, limiting its effectiveness and accuracy. In this paper, we propose a novel framework that combines PM and HI to enable data-driven, process- and product-centric modeling of industrial energy demands. By integrating event logs and thermal energy data, our approach allows for a fine-grained analysis of heat demand patterns corresponding to specific process activities and product variants. We demonstrate the applicability and advantages of the framework by simulating a pharmaceutical manufacturing process and evaluating energy demands and heat recovery potentials. Our findings show that our PM-enabled HI framework provides more accurate and actionable insights into the temporal and product-specific variation of thermal energy demands. By capturing the causal relationships between process activities, product characteristics, and energy consumption, our approach enables improved analysis, planning, and optimization for heat recovery and process decarbonization. This integration of PM and HI expands the analytical tools for both disciplines and contributes to advancing the sustainable transformation of industrial processes.

Causal Machine Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed Study - Zapata Gonzalez, David Ricardo; Meyer, Marcel; Müller, Oliver (ACM SIGEnergy Energy Informatics Review)
Data centers (DCs) form the backbone of our growing digital economy, but their rising energy demands pose challenges to our environment. At the same time, reusing waste heat from DCs also represents an opportunity, for example, for more sustainable heating of residential buildings. Modeling and optimizing these coupled and dynamic systems of heat generation and reuse is complex. On the one hand, physical simulations can be used to model these systems, but they are time-consuming to develop and run. Machine learning (ML), on the other hand, allows efficient data-driven modeling, but conventional correlation-based approaches struggle with the prediction of interventions and out-of-distribution generalization. Recent advances in causal ML, which combine principles from causal inference with flexible ML methods, are a promising approach for more robust predictions. Due to their focus on modeling interventions and cause-and-effect relationships, it is difficult to evaluate causal ML approaches rigorously. To address this challenge, we built a testbed of a miniature DC with an integrated waste heat network, equipped with sensors and actuators. This testbed allows conducting controlled experiments and automatic collection of realistic data, which can then be used to benchmark conventional and causal ML methods. Our experimental results highlight the strengths and weaknesses of each modeling approach, providing valuable insights on how to appropriately apply different types of machine learning to optimize data center operations and enhance their sustainability.

Causal Machine Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed Study - Gonzalez, David Zapata; Meyer, Marcel; Müller, Oliver (ACM SIGEnergy Energy Informatics Review)
Data centers (DCs) form the backbone of our growing digital economy, but their rising energy demands pose challenges to our environment. At the same time, reusing waste heat from DCs also represents an opportunity, for example, for more sustainable heating of residential buildings. Modeling and optimizing these coupled and dynamic systems of heat generation and reuse is complex. On the one hand, physical simulations can be used to model these systems, but they are time-consuming to develop and run. Machine learning (ML), on the other hand, allows efficient data-driven modeling, but conventional correlation-based approaches struggle with the prediction of interventions and out-of-distribution generalization. Recent advances in causal ML, which combine principles from causal inference with flexible ML methods, are a promising approach for more robust predictions. Due to their focus on modeling interventions and cause-and-effect relationships, it is difficult to evaluate causal ML approaches rigorously. To address this challenge, we built a testbed of a miniature DC with an integrated waste heat network, equipped with sensors and actuators. This testbed allows conducting controlled experiments and automatic collection of realistic data, which can then be used to benchmark conventional and causal ML methods. Our experimental results highlight the strengths and weaknesses of each modeling approach, providing valuable insights on how to appropriately apply different types of machine learning to optimize data center operations and enhance their sustainability.

„Zeit für Gender“ – Podcasts aus der Fachcommunity 2 - Eremin, Oxana; Richter, Susanne; Letzner, Celina (blog interdisziplinäre geschlechterforschung)

Targeting visual-sensory and cognitive impairments following lateral ankle sprains: a practical framework for functional assessment across the return-to-sport continuum—Part 1. Sensory reweighting and cognitive impairments: what are we really talking about and why clinicians should consider central alterations in return to sport criteria - Picot, Brice; Maricot, Alexandre; Fourchet, François; Gokeler, Alli; Tassignon, Bruno; Lopes, Ronny; Hardy, Alexandre (Frontiers in Sports and Active Living)
Lateral ankle sprain (LAS) is the most common traumatic injury, with a high recurrence rate and chronic ankle instability (CAI) developing in ∼40% of cases. LAS leads to patho-mechanical, sensory-perceptual and motor-behavioral deficits. Poor management of the return-to-sport (RTS) is now considered a major cause of re-injury and development of CAI, particularly due to the lack of validated tests and the failure of existing ones to account for those central deficits. The first part of this topic aimed to clarify concepts of cognitive constructs and sensory reweighting and their association with CAI. We also aimed to identify objective RTS criteria and discuss their limits regarding their ability to encompass central impairments. Motor-cognitive deficits have been identified using computerized cognitive tasks and dual-task paradigms. More specifically, deficits in visual memory, processing speed or inhibitory control and attentional resource allocation have demonstrated reduced performance in CAI populations. In addition, altered sensory reweighting process towards visual input has also been observed. While objective criteria are crucial to prevent re-injury, current evaluations remain largely subjective and central impairments are unaccounted for in conventional RTS testing. The Ankle-GO TM score was recently developed to guide clinicians in decision making process. To date, it is the first validated score that could help to identify patients who will RTS at the same level, those at risk of recurrence and those who are more likely to become copers. Unfortunately, it does not target cognitive or sensory reweighting alterations, that are both relevant in sport to manage gameplay demands.

Secure Distributed State Management for Stateful Signatures with a Practical and Universally Composable Protocol - Blömer, Johannes; Bröcher, Henrik; Krummel, Volker; Porzenheim, Laurens Alexander
Stateful signatures like the NIST standardized signature schemes LMS and XMSS provide an efficient and mature realization of post-quantum secure signature schemes. They are recommended for long-term use cases like e.g. firmware signing. However, stateful signature schemes require to properly manage a so-called state. In stateful signature schemes like LMS and XMSS, signing keys consist of a set of keys of a one-time signature scheme and it has to be guaranteed that each one-time key is used only once. This is done by updating a state in each signature computation, basically recording which one-time keys have already been used. While this is straightforward in centralized systems, in distributed systems like secure enclaves consisting of e.g. multiple hardware security modules (HSMs) with limited communication keeping a distributed state that at any point in time is consistent among all parties involved presents a challenge. This challenge is not addressed by the current standardization processes. In this paper we present a security model for the distributed key management of post-quantum secure stateful signatures like XMSS and LMS. We also present a simple, efficient, and easy to implement protocol proven secure in this security model, i.e. the protocol guarantees at any point in time a consistent state among the parties in a distributed system, like a distributed security enclave. The security model is defined in the universal composabilty (UC) framework by Ran Canetti by providing an ideal functionality for the distributed key management for stateful signatures. Hence our protocol remains secure even if arbitrarily composed with other instances of the same or other protocols, a necessity for the security of distributed key management protocols. Our main application are security enclaves consisting of HSMs, but the model and the protocol can easily be adapted to other scenarios of distributed key management of stateful signature schemes.
Keywords: distributed state; hash-based signature; stateful hash-based signature; universal composability; secure enclave

Influence of Liquid metal embrittlement on load-bearing capacity of resistance spot welds under crash loads: A study based on S-Rail components - Yang, Keke; Biegler, Max; Happe, Linus; Striewe, Marius; Olfert, Viktoria; Hein, David; Rethmeier, Michael; Meschut, Gerson (Materials Research Proceedings)
Abstract. Liquid Metal Embrittlement (LME) cracking is a well-documented issue encountered during resistance spot welding (RSW) of zinc-coated advanced high-strength steels (AHSS) in automotive manufacturing. Given that existing research has predominantly focused on laboratory-scale samples and lacks investigation into the load-bearing capacity of joints under crash conditions, this study aims to fill these gaps by analyzing third-generation zinc-coated AHSS. S-Rail components were produced through stamping to replicate real-world manufacturing conditions and geometries of automotive parts. To account for the disturbances typically encountered in production, samples with LME cracks were intentionally fabricated. Subsequently, a modified three-point bending test, assisted by numerical simulations, was developed to effectively apply loads to the weld spots of the S-Rail components. Results from crash tests demonstrated that observed light crack severity does not significantly compromise the joint's load-bearing capacity or lead to earlier joint failure.

Analysis of fatigue behaviour of self-piercing riveted joints under cyclic loading using laser vibrometry - Olfert, Viktoria; Yang, Keke; Gollnick, Maik; Krause, Jacob; Hein, David; Meschut, Gerson (Materials Research Proceedings)
Abstract. In the field of online condition monitoring, non-destructive testing methods using active acoustic testing [1] emerged as innovative tools. These techniques are particularly effective because damage in joined structures leads to significant changes in their vibrational characteristics. However, the consistent use of online condition monitoring through active acoustic testing combined with complex pattern recognition for early crack detection in joined components has not yet been fully established. This research aims to develop an online crack detection system employing pattern recognition techniques under cyclic loading during fatigue tests, utilizing non-contact active acoustic testing with laser vibrometry. Due to the wide range of materials that can be joined, mechanical joining processes can be used in many different industry branches. Self-pierce riveting (SPR), in particular, is a well-established joining process. Therefore, the investigations for online crack detection initially focus on SPR joints. To achieve this, the fatigue behavior of SPR joints in a lap-shear configuration was characterized. Experimental fatigue testing demonstrated that SPR joint failure occurs either through cracks propagating in the sheet material away from the rivet or in the rivet foot, depending on the material combination. Laser vibrometry has been successfully used as a crack detection system and has proven to be effective in detecting crack initiation in SPR joints. Cracks can be detected without contact regardless of the material combination, the damage location, the size of the damage, or the type of damage. The optimization of the crack detection system involved several key enhancements, including adjusting data acquisition to improve crack detection, incorporating principal component analysis (PCA) to reduce dimensionality, and implementing a classification model based on a global training dataset. An intuitive, problem-specific software demonstrator for analyzing the crack initiation behavior of SPR joints under cyclic loading was developed and iteratively optimized. Future work will focus on the implementation of an autoencoder network to further enhance crack detection capabilities.

Rebellious Witnesses: Why a Reorientation of Patriarchal Scientific and Social Culture is Urgently Needed - Grewe, Felix (Festschrift - Mary Ellen Waithe)

Beyond The Episode: A Case For Serial Literacy in EFL Education - Intveen, Julie; Illigens, Tim (Journal of Media Literacy Education)
Serial storytelling, characterized by its interplay of vertical (episodic) and horizontal (long-form) narrative structures, offers a unique opportunity for media literacy in English as a Foreign Language (EFL) education. This paper argues for the development of a serial literacy framework, a concept that expands traditional film literacy models to accommodate the distinct demands of serialized narratives. By using Inventing Anna (Rhimes, 2022) as a case study, the study explores how serial storytelling fosters engagement with themes of identity construction, ethical ambiguity, and transmedial storytelling. This paper elaborates on serial literacy, considering its implications within foreign language learning contexts. The study highlights how serialized narratives cultivate critical thinking, communicative competence, and media awareness, which renders them a valuable pedagogical tool. By integrating serial literacy into EFL curricula, educators can bridge students’ media consumption habits with analytical engagement and thus foster a generation of critically literate media consumers and producers. This paper elaborates on serial literacy, considering its implications within foreign language learning contexts. The study highlights how serialized narratives cultivate critical thinking, communicative competence, and media awareness, which renders them a valuable pedagogical tool. By integrating serial literacy into EFL curricula, educators can bridge students' media consumption habits with analytical engagement and thus foster a generation of critically literate media consumers and producers.