TY - RPRT A1 - Barnat, Miriam A1 - Arntz, Kristian A1 - Bernecker, Andreas A1 - Fissabre, Anke A1 - Franken, Norbert A1 - Goldbach, Daniel A1 - Hüning, Felix A1 - Jörissen, Jörg A1 - Kirsch, Ansgar A1 - Pettrak, Jürgen A1 - Rexforth, Matthias A1 - Josef, Rosenkranz A1 - Terstegge, Andreas T1 - Strategische Gestaltung von Studiengängen für die Zukunft: Ein kollaborativ entwickeltes Self-Assessment BT - Diskussionspapier Nr. 33 T2 - Hochschulforum Digitalisierung - Diskussionspapier N2 - Das Diskussionspapier beschreibt einen Prozess an der FH Aachen zur Entwicklung und Implementierung eines Self-Assessment-Tools für Studiengänge. Dieser Prozess zielte darauf ab, die Relevanz der Themen Digitalisierung, Internationalisierung und Nachhaltigkeit in Studiengängen zu stärken. Durch Workshops und kollaborative Entwicklung mit Studiendekan:innen entstand ein Fragebogen, der zur Reflexion und strategischen Weiterentwicklung der Studiengänge dient. Y1 - 2024 SN - 2365-7081 PB - Stifterverband für die Deutsche Wissenschaft CY - Berlin ER - TY - CHAP A1 - Kahra, Marvin A1 - Breuß, Michael A1 - Kleefeld, Andreas A1 - Welk, Martin ED - Brunetti, Sara ED - Frosini, Andrea ED - Rinaldi, Simone T1 - An Approach to Colour Morphological Supremum Formation Using the LogSumExp Approximation T2 - Discrete Geometry and Mathematical Morphology N2 - Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or infimum with respect to an order over the tonal range in a certain section of the image. The tonal ordering can easily be realised in grey-scale morphology, and some morphological methods have been proposed for colour morphology. However, all of these have certain limitations. In this paper we present a novel approach to colour morphology extending upon previous work in the field based on the Loewner order. We propose to consider an approximation of the supremum by means of a log-sum exponentiation introduced by Maslov. We apply this to the embedding of an RGB image in a field of symmetric 2x2 matrices. In this way we obtain nearly isotropic matrices representing colours and the structural advantage of transitivity. In numerical experiments we highlight some remarkable properties of the proposed approach. Y1 - 2024 SN - 978-3-031-57793-2 U6 - https://doi.org/10.1007/978-3-031-57793-2_25 N1 - Third International Joint Conference, DGMM 2024, Florence, Italy, April 15–18, 2024 SP - 325 EP - 337 PB - Springer CY - Cham ER - TY - JOUR A1 - Engelmann, Ulrich M. A1 - Simsek, Beril A1 - Shalaby, Ahmed A1 - Krause, Hans-Joachim T1 - Key contributors to signal generation in frequency mixing magnetic detection (FMMD): an in silico study JF - Sensors N2 - Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled Néel–Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays. KW - key performance indicators KW - magnetic biosensing KW - coupled Néel–Brownian relaxation dynamics KW - frequency mixing magnetic detection KW - magnetic relaxation KW - micromagnetic simulation KW - magnetic nanoparticles Y1 - 2024 U6 - https://doi.org/10.3390/s24061945 SN - 1424-8220 N1 - This article belongs to the Special Issue "Advances in Magnetic Sensors and Their Applications" VL - 24 IS - 6 PB - MDPI CY - Basel ER - TY - JOUR A1 - Akimbekov, Nuraly S. A1 - Digel, Ilya A1 - Tastambek, Kuanysh T. A1 - Kozhahmetova, Marzhan A1 - Sherelkhan, Dinara K. A1 - Tauanov, Zhandos T1 - Hydrogenotrophic methanogenesis in coal-bearing environments: Methane production, carbon sequestration, and hydrogen availability JF - International Journal of Hydrogen Energy N2 - Methane is a valuable energy source helping to mitigate the growing energy demand worldwide. However, as a potent greenhouse gas, it has also gained additional attention due to its environmental impacts. The biological production of methane is performed primarily hydrogenotrophically from H2 and CO2 by methanogenic archaea. Hydrogenotrophic methanogenesis also represents a great interest with respect to carbon re-cycling and H2 storage. The most significant carbon source, extremely rich in complex organic matter for microbial degradation and biogenic methane production, is coal. Although interest in enhanced microbial coalbed methane production is continuously increasing globally, limited knowledge exists regarding the exact origins of the coalbed methane and the associated microbial communities, including hydrogenotrophic methanogens. Here, we give an overview of hydrogenotrophic methanogens in coal beds and related environments in terms of their energy production mechanisms, unique metabolic pathways, and associated ecological functions. KW - Coal KW - Methanogenesis KW - Methane KW - Hydrogenotrophic methanogens KW - H2 Y1 - 2024 U6 - https://doi.org/10.1016/j.ijhydene.2023.09.223 SN - 1879-3487 (online) SN - 0360-3199 (print) VL - 52 IS - Part D SP - 1264 EP - 1277 PB - Elsevier CY - New York ER -