@article{JanusAchtsnichtDrinicetal.2023,
  author    = {Janus, Kevin Alexander and Achtsnicht, Stefan and Drinic, Aleksander and Kopp, Alexander and Keusgen, Michael and Sch{\"o}ning, Michael Josef},
  title     = {Transient magnesium-based thin-film temperature sensor on a flexible, bioabsorbable substrate for future medical applications},
  series = {Applied Research},
  journal   = {Applied Research},
  number    = {Accepted manuscript},
  publisher = {Wiley-VCH},
  issn      = {2702-4288 (Print)},
  doi       = {10.1002/appl.202300102},
  pages     = {22 Seiten},
  year      = {2023},
  abstract  = {In this work, the bioabsorbable materials, namely fibroin, polylactide acid (PLA), magnesium and magnesium oxide are investigated for their application as transient, resistive temperature detectors (RTD). For this purpose, a thin-film magnesium-based meander-like electrode is deposited onto a flexible, bioabsorbable substrate (fibroin or PLA) and encapsulated (passivated) by additional magnesium oxide layers on top and below the magnesium-based electrode. The morphology of different layered RTDs is analyzed by scanning electron microscopy. The sensor performance and lifetime of the RTD is characterized both under ambient atmospheric conditions between 30°C and 43°C, and wet tissue-like conditions with a constant temperature regime of 37°C. The latter triggers the degradation process of the magnesium-based layers. The 3-layers RTDs on a PLA substrate could achieve a lifetime of 8.5 h. These sensors also show the best sensor performance under ambient atmospheric conditions with a mean sensitivity of 0.48 Ω/°C ± 0.01 Ω/°C.},
  language  = {en}
}
@article{KarschuckSchmidtAchtsnichtetal.2023,
  author    = {Karschuck, Tobias and Schmidt, Stefan and Achtsnicht, Stefan and Poghossian, Arshak and Wagner, Patrick and Sch{\"o}ning, Michael Josef},
  title     = {Multiplexing system for automated characterization of a capacitive field-effect sensor array},
  series = {Physica Status Solidi A},
  volume    = {220},
  journal   = {Physica Status Solidi A},
  number    = {22},
  publisher = {Wiley-VCH},
  address   = {Weinheim},
  issn      = {1862-6300 (Print)},
  doi       = {10.1002/pssa.202300265},
  pages     = {7 Seiten},
  year      = {2023},
  abstract  = {In comparison to single-analyte devices, multiplexed systems for a multianalyte detection offer a reduced assay time and sample volume, low cost, and high throughput. Herein, a multiplexing platform for an automated quasi-simultaneous characterization of multiple (up to 16) capacitive field-effect sensors by the capacitive-voltage (C-V) and the constant-capacitance (ConCap) mode is presented. The sensors are mounted in a newly designed multicell arrangement with one common reference electrode and are electrically connected to the impedance analyzer via the base station. A Python script for the automated characterization of the sensors executes the user-defined measurement protocol. The developed multiplexing system is tested for pH measurements and the label-free detection of ligand-stabilized, charged gold nanoparticles.},
  language  = {en}
}
@article{BornheimGriegerBlanecketal.2024,
  author    = {Bornheim, Tobias and Grieger, Niklas and Blaneck, Patrick Gustav and Bialonski, Stephan},
  title     = {Speaker Attribution in German Parliamentary Debates with QLoRA-adapted Large Language Models},
  series = {Journal for language technology and computational linguistics : JLCL},
  volume    = {37},
  journal   = {Journal for language technology and computational linguistics : JLCL},
  number    = {1},
  publisher = {Gesellschaft f{\"u}r Sprachtechnologie und Computerlinguistik},
  address   = {Regensburg},
  issn      = {2190-6858},
  doi       = {10.21248/jlcl.37.2024.244},
  pages     = {13 Seiten},
  year      = {2024},
  abstract  = {The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.},
  language  = {en}
}