@inproceedings{BeckerBragard2024,
  author    = {Becker, Tim and Bragard, Michael},
  title     = {Low-Voltage DC Training Lab for Electric Drives - Optimizing the Balancing Act Between High Student Throughput and Individual Learning Speed},
  series = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  booktitle = {2024 IEEE Global Engineering Education Conference (EDUCON)},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2165-9559},
  doi       = {10.1109/EDUCON60312.2024.10578902},
  pages     = {8 Seiten},
  year      = {2024},
  abstract  = {After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.},
  language  = {en}
}
@article{Golland2024,
  author    = {Golland, Alexander},
  title     = {Datenschutz beim Einsatz k{\"u}nstlicher Intelligenz im Unternehmen},
  series = {NWB},
  journal   = {NWB},
  number    = {6},
  publisher = {NWB},
  address   = {Herne},
  issn      = {0028-3460},
  pages     = {425 -- 432},
  year      = {2024},
  abstract  = {Seit Ende 2022 pr{\"a}gt das Schlagwort „K{\"u}nstliche Intelligenz" (KI) nicht nur den rechtswissenschaftlichen Diskurs. Die allgemeine Verf{\"u}gbarkeit von generativen KI-Modellen, allen voran die großen Sprachmodelle (Large Language Models, kurz: LLM) wie ChatGPT von OpenAI oder Bing AI von Microsoft, erfreuen sich gr{\"o}ßter Beliebtheit: LLM sind in der Lage, auf Grundlage statistischer Methoden - eine entsprechende Schnittstelle (Interface) vorausgesetzt - auch technisch wenig versierten Nutzern verst{\"a}ndliche Antworten auf ihre Fragen zu liefern. Dabei werden nicht nur umfassend Nutzerdaten verarbeitet, sondern auch auf weitere personenbezogene Daten zugegriffen sowie neue Daten erzeugt. Der Beitrag geht der Frage nach, welche spezifischen datenschutzrechtlichen Herausforderungen sich f{\"u}r Unternehmen beim Einsatz solcher LLM stellen.},
  language  = {de}
}
@article{EngelmannSimsekShalabyetal.2024,
  author    = {Engelmann, Ulrich M. and Simsek, Beril and Shalaby, Ahmed and Krause, Hans-Joachim},
  title     = {Key contributors to signal generation in frequency mixing magnetic detection (FMMD): an in silico study},
  series = {Sensors},
  volume    = {24},
  journal   = {Sensors},
  number    = {6},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s24061945},
  pages     = {Artikel 1945},
  year      = {2024},
  abstract  = {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 N{\´e}el-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.},
  language  = {en}
}
@article{OehlenschlaegerVolkmarStiefelmaieretal.2024,
  author    = {Oehlenschl{\"a}ger, Katharina and Volkmar, Marianne and Stiefelmaier, Judith and Langsdorf, Alexander and Holtmann, Dirk and Tippk{\"o}tter, Nils and Ulber, Roland},
  title     = {New insights into the influence of pre-culture on robust solvent production of C. acetobutylicum},
  series = {Applied Microbiology and Biotechnology},
  volume    = {108},
  journal   = {Applied Microbiology and Biotechnology},
  publisher = {Springer},
  address   = {Berlin, Heidelberg},
  issn      = {1432-0614},
  doi       = {10.1007/s00253-023-12981-8},
  pages     = {10 Seiten},
  year      = {2024},
  abstract  = {Clostridia are known for their solvent production, especially the production of butanol. Concerning the projected depletion of fossil fuels, this is of great interest. The cultivation of clostridia is known to be challenging, and it is difficult to achieve reproducible results and robust processes. However, existing publications usually concentrate on the cultivation conditions of the main culture. In this paper, the influence of cryo-conservation and pre-culture on growth and solvent production in the resulting main cultivation are examined. A protocol was developed that leads to reproducible cultivations of Clostridium acetobutylicum. Detailed investigation of the cell conservation in cryo-cultures ensured reliable cell growth in the pre-culture. Moreover, a reason for the acid crash in the main culture was found, based on the cultivation conditions of the pre-culture. The critical parameter to avoid the acid crash and accomplish the shift to the solventogenesis of clostridia is the metabolic phase in which the cells of the pre-culture were at the time of inoculation of the main culture; this depends on the cultivation time of the pre-culture. Using cells from the exponential growth phase to inoculate the main culture leads to an acid crash. To achieve the solventogenic phase with butanol production, the inoculum should consist of older cells which are in the stationary growth phase. Considering these parameters, which affect the entire cultivation process, reproducible results and reliable solvent production are ensured.},
  language  = {en}
}
@techreport{HoffmannUllrich2024,
  type      = {Working Paper},
  author    = {Hoffmann, Sarah and Ullrich, Anna Valentine},
  title     = {30 Minuten FDM f{\"u}r HAW. Ein Informationsformat f{\"u}r Forschende an HAW in NRW},
  doi       = {10.5281/zenodo.12569282},
  pages     = {1 Seite},
  year      = {2024},
  abstract  = {Wie kann man das Thema Forschungsdatenmanagement (FDM) konkret und anwendbar f{\"u}r Forschende gestalten, die bisher noch wenig Kontakt damit hatten? Auf diese Frage gibt das Konzept „30 Minuten FDM f{\"u}r HAW. Ein Informationsformat f{\"u}r Forschende an HAW in NRW" eine Antwort. Es entstand als Projektarbeit im Zertifikatskurs Forschungsdatenmanagement 2023/24},
  language  = {de}
}
@techreport{BirmansSchickTamborninoetal.2024,
  type      = {Working Paper},
  author    = {Birmans, Katrin and Schick, Elena and Tambornino, Philipp and Ullrich, Anna Valentine},
  title     = {Ingenieurwissenschaften im Fokus: Zug{\"a}nge zu einem effektiven Forschungsdatenmanagement an HAW},
  doi       = {10.5281/zenodo.12545429},
  pages     = {49 Seiten},
  year      = {2024},
  abstract  = {Im Rahmen der Love Data Week vom 12. bis 16.02.2024 haben die BMBF-Projekte FDM2_TH_Koeln der TH K{\"o}ln (FK 16FDFH105) und Persist@HAW der FH Aachen (FK 16FDFH129) am 15.02.2024 gemeinsam eine Online-Veranstaltung mit dem Titel „Ingenieurwissenschaften im Fokus: Zug{\"a}nge zu einem effektiven Forschungsdatenmanagement an HAW" angeboten. Diese richtete sich an Forschende aus den Ingenieurwissenschaften, die einen ersten Zugang zum Thema Forschungsdatenmanagement (FDM) suchen und erfahren m{\"o}chten, welche speziellen Angebote f{\"u}r die Daten aus den Ingenieurwissenschaften existieren. In der Veranstaltung wurden wesentliche Aspekte des Forschungsdatenmanagements entlang des Datenlebenszyklus beleuchtet. Ziel war es, den Teilnehmenden praxisnahe Einblicke und Hilfestellungen zu einem effektiven Umgang mit Forschungsdaten an Hochschulen f{\"u}r Angewandte Wissenschaften (HAW) zu bieten. Durch Beispiele und konkrete Empfehlungen wurde das Thema zug{\"a}nglich gemacht.},
  language  = {de}
}