TY - INPR A1 - Vogel, Sven K. A1 - Wölfer, Christian A1 - Ramirez-Diaz, Diego A. A1 - Flassig, Robert J. A1 - Sundmacher, Kai A1 - Schwille, Petra T1 - Symmetry breaking and emergence of directional flows in minimal actomyosin cortices KW - bottom-up synthetic biology KW - motor proteins KW - pattern formation KW - self-organization Y1 - 2020 UR - https://www.preprints.org/manuscript/202004.0008/v1 U6 - https://doi.org/10.20944/preprints202004.0008.v1 ER - TY - INPR A1 - Tuset-Peiro, Pere A1 - Pilgermann, Michael A1 - Pegueroles, Josep A1 - Vilajosana, Xavier T1 - Assessing Cybersecurity of Internet-Facing Medical IT Systems in Germany & Spain Using OSINT Tools N2 - This paper investigates cybersecurity threats in medical IT (Information Technology) systems exposed to the Internet. To that end, we develop a methodology and build a data processing pipeline that allows to gather data from different OSINT (Open Source Intelligence) sources, and processes it to obtain relevant cybersecurity metrics. To validate its operation and usefulness, we apply it to two countries, Germany and Spain, allowing to study the main threats that affect medical IT systems in these countries. Our initial findings reveal that 20% of German hosts and 15% of Spanish hosts tagged as medical devices have at least one CVE (Common Vulnerabilities and Exposures) with a CVSS (Common Vulnerability Scoring System) graded as critical (i.e., value 8 or greater). Moreover, we found that 74% of CVEs found in German hosts are dated from earlier than 2020, whereas for Spanish hosts the percentage is 60%. This indicates that medical IT systems exposed to the Internet are seldom updated, which further increases their exposure to cyberthreats. Based on these initial findings, we finish the paper providing some insights on how to improve cybersecurity of these systems. Y1 - 2025 U6 - https://doi.org/10.20944/preprints202503.1340.v1 SP - 190 EP - 197 ER - TY - INPR A1 - Pepe, Alberto A1 - Lasenby, Joan A1 - Buchholz, Sven T1 - STAResNet: A Network in Spacetime Algebra to solve Maxwell's PDEs T2 - arXiv N2 - We introduce STAResNet, a ResNet architecture in Spacetime Algebra (STA) to solve Maxwell's partial differential equations (PDEs). Recently, networks in Geometric Algebra (GA) have been demonstrated to be an asset for truly geometric machine learning. In [1], GA networks have been employed for the first time to solve partial differential equations (PDEs), demonstrating an increased accuracy over real-valued networks. In this work we solve Maxwell's PDEs both in GA and STA employing the same ResNet architecture and dataset, to discuss the impact that the choice of the right algebra has on the accuracy of GA networks. Our study on STAResNet shows how the correct geometric embedding in Clifford Networks gives a mean square error (MSE), between ground truth and estimated fields, up to 2.6 times lower than than obtained with a standard Clifford ResNet with 6 times fewer trainable parameters. STAREsNet demonstrates consistently lower MSE and higher correlation regardless of scenario. The scenarios tested are: sampling period of the dataset; presence of obstacles with either seen or unseen configurations; the number of channels in the ResNet architecture; the number of rollout steps; whether the field is in 2D or 3D space. This demonstrates how choosing the right algebra in Clifford networks is a crucial factor for more compact, accurate, descriptive and better generalising pipelines. Y1 - 2024 UR - https://arxiv.org/pdf/2408.13619 SP - 1 EP - 17 PB - arXiv ER - TY - INPR A1 - Nitze, André T1 - Future-proofing Education: A Prototype for Simulating Oral Examinations Using Large Language Models N2 - This study explores the impact of Large Language Models (LLMs) in higher education, focusing on an automated oral examination simulation using a prototype. The design considerations of the prototype are described, and the system is evaluated with a select group of educators and students. Technical and pedagogical observations are discussed. The prototype proved to be effective in simulating oral exams, providing personalized feedback, and streamlining educators' workloads. The promising results of the prototype show the potential for LLMs in democratizing education, inclusion of diverse student populations, and improvement of teaching quality and efficiency. Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2401.06160 SP - 1 EP - 6 PB - arXiv ER - TY - INPR A1 - Markgraf, Klaus A1 - Müller, Katja A1 - Henkel, Clara A1 - Flassig, Robert A1 - Janke, Christian A1 - Flassig, Peter T1 - Application of Explainable Artificial Intelligence (XAI) in Combination with Bootstrap to Improve Processes in Model-Based Aero-Engine Development N2 - In aerospace engineering, data-driven surrogate models are increasingly employed to mitigate the computational and temporal costs of simulations, numerical analyses, and experiments. Two major challenges accompany this trend. First, the training of surrogate models often requires a sufficient amount of data, the determination of which is inherently difficult. Second, these models often exhibit high complexity, limiting both the traceability of their outputs and the extraction of useful insights. Explainable Artificial Intelligence (XAI) methods have therefore emerged as promising tools to enhance the interpretability, explainability, and transparency of such models. In this work, a combination of the established Shapley Additive Explanations (SHAP) approach with a bootstrap-based method is investigated. The proposed framework provides insights into the contribution of individual features and enables an assessment of data sufficiency with respect to surrogate model performance. Building upon these findings, the Bootstrap-Informed Feature Importance (BIFI) method is proposed. BIFI offers a model-agnostic, robust identification of relevant features.The method is analyzed in the context of Design of Experiments (DOE) processes used for surrogate model construction. Evaluation on four synthetic datasets of increasing complexity, as well as a dataset from aero-engine development, demonstrates that BIFI-based DOEs can improve surrogate model quality measured in terms of R and MSE by up to 90%. Consequently, the proposed method enables more efficient utilization of simulations, computations, and experiments while reducing the required number of samples. Y1 - 2026 U6 - https://doi.org/10.21203/rs.3.rs-8590595/v1 SP - 1 EP - 23 ER - TY - INPR A1 - Frosch, Katharina T1 - Open Design of HRM Instruments: new perspectives on people management in SMEs N2 - When it comes to human resource management (HRM), small and medium-sized enterprises (SMEs) primarily rely on informal approaches. Thereby, HR practitioners often listen to their guts feeling instead of using more systematic HR practices that are, as research evidence shows, more effective for attracting, motivating and retaining talented staff. This paper elaborates on the question how SMEs may profit from the design and implementation of evidence-based, systematic HRM instruments. The analysis focuses on the antecedents of the so called science-practitioner gap in HRM and why it is even more pronounced in SMEs as compared to larger companies. As a conclusion, we find that SMEs need to design HRM instruments that are systematic and evidence-based in their approach, but can be used by HR practitioners on an intuitive basis without ex ante training or cumbersome formal procedures. However, designing HRM instruments based on a so-called "walk-up-and-use" approach means beating new paths. Given the scarce resources for people management in SMEs, such innovative HRM instruments cannot be developed by a single SME alone. Therefore, the paradigm of open cooperation as it has been successfully applied in open source software (OSS) development is evaluated , in particular whether it can be transferred on the design of HRM instruments that take into account the specific needs of SMEs. First of all, we conceptualize a general framework how HR practitioners from SMEs and HR experts from business and academia can jointly develop Open HRM instruments. Then we discuss the social side of Open HRM, in particular why someone should contribute to Open HRM without receiving immediate profits, how to ensure the quality of openly developed HRM instruments and other gov-ernance issues. As a conclusion, we find that-despite a number of technical and social challenges that have to be overcome-Open HRM has a great potential in order to open up evidence-based HRM for SMEs. Y1 - 2019 SP - 1 EP - 35 ER -