Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (1692) (remove)
Language
- English (1692) (remove)
Document Type
- Article (1359)
- Conference Proceeding (212)
- Book (43)
- Part of a Book (43)
- Doctoral Thesis (18)
- Other (6)
- Patent (4)
- Preprint (3)
- Lecture (2)
- Habilitation (1)
Keywords
- Biosensor (25)
- Finite-Elemente-Methode (12)
- Einspielen <Werkstoff> (10)
- CAD (8)
- civil engineering (8)
- Bauingenieurwesen (7)
- FEM (6)
- Limit analysis (6)
- Shakedown analysis (6)
- shakedown analysis (6)
Cell-based sensors for the detection of gases have long been underrepresented, due to the cellular requirement of being cultured in a liquid environment. In this work we established a cell-based gas biosensor for the detection of toxic substances in air, by adapting a commercial sensor chip (Bionas®), previously used for the measurement of pollutants in liquids. Cells of the respiratory tract (A549, RPMI 2650, V79), which survive at a gas phase in a natural context, are used as biological receptors. The physiological cell parameters acidification, respiration and morphology are continuously monitored in parallel. Ammonia was used as a highly water-soluble model gas to test the feasibility of the sensor system. Infrared measurements confirmed the sufficiency of the medium draining method. This sensor system provides a basis for many sensor applications such as environmental monitoring, building technology and public security.
Using a cell-based gas biosensor for investigation of adverse effects of acetone vapors in vitro
(2013)
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.
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.
Poly(N-isopropylacrylamide) (PNIPAAm) hydrogel films with incorporated graphene oxide (GO) were developed and tested as light-stimulated actuators. GO dispersions were synthesized via Hummers method and characterized toward their optical properties and photothermal energy conversion. The hydrogels were prepared by means of photopolymerization. In addition, the influence of GO within the hydrogel network on the lower critical solution temperature (LCST) was investigated by differential scanning calorimetry (DSC). The optical absorbance and the response to illumination were determined as a function of GO concentration for thin hydrogel films. A proof of principle for the stimulation with light was performed.
Light-stimulated hydrogel actuators with incorporated graphene oxide for microfluidic applications
(2015)
Abstractauthoren Graphene oxide (GO) nanoparticles were incorporated in temperature-sensitive Poly(N-isopropylacrylamide) (PNIPAAm) hydrogels. The nanoparticles increase the light absorption and convert light energy into heat efficiently. Thus, the hydrogels with GO can be stimulated spatially resolved by illumination as it was demonstrated by IR thermography. The temporal progression of the temperature maximum was detected for different concentrations of GO within the polymer network. Furthermore, the compatibility of PNIPAAm hydrogels with GO and cell cultures was investigated. For this purpose, culture medium was incubated with hydrogels containing GO and the viability and morphology of chinese hamster ovary (CHO) cells was examined after several days of culturing in presence of this medium.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.