Publikationen

2024

• Auswirkungen der Energiekrise auf Margining-Verpflichtungen

  Lorenz, B., Perlwitz, H., & Heinen, A. (2024). Auswirkungen der Energiekrise auf Margining-Verpflichtungen. ew — Magazin für die Energiewirtschaft, (51).

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  • 2024
  • Journal Article
  • • Benedikt Lorenz
    • Holger Perlwitz
    • Andreas Heinen

• Green hydrogen production with offshore wind at Colombian Caribbean Sea: Analysis for Atlántico Department s coast

  Bermejo, E., Berrío, J., Llain, J., Rincón, A., Schlipf, D., & Zambrano, H. (2024). Green hydrogen production with offshore wind at Colombian Caribbean Sea: Analysis for Atlántico Department s coast. http://doi.org/10.5281/zenodo.10912206

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    • Schlipf, David

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  • 2024
  • Miscellaneous
  • • Edwin Bermejo
    • Julián Berrío
    • Jose Llain
    • Andrés. Rincón
    • David Schlipf
    • Habib Zambrano

• Influence of Compressive Stresses on Core Losses and Magnetization Demand of Electrical Steel Sheets and Press Fitted Stator Cores

  Regnet, M., Pérez, A. V., Dietz, A., Loehlein, B., & Reinlein, M. (2024). Influence of Compressive Stresses on Core Losses and Magnetization Demand of Electrical Steel Sheets and Press Fitted Stator Cores. In 14th International Electric Drives Production Conference (EDPC).

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  • 2024
  • Conference Paper
  • • Martin Regnet
    • Alejandro Pérez
    • Armin Dietz
    • Bernd Loehlein
    • Michael Reinlein

• Breast cancer survival prediction using an automated mitosis detection pipeline

  Stathonikos, N., Aubreville, M., de Vries, S., Wilm, F., Bertram, C. A., Veta, M., & van Diest, P. J. (2024). Breast cancer survival prediction using an automated mitosis detection pipeline. The Journal of Pathology: Clinical Research, 10, e70008. http://doi.org/https://doi.org/10.1002/2056-4538.70008

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  Abstract Mitotic count (MC) is the most common measure to assess tumor proliferation in breast cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter- and intraobserver variation and reproducibility challenges that may hamper its clinical utility. In past studies, artificial intelligence (AI)-supported MC has been shown to correlate well with traditional MC on glass slides. Considering the potential of AI to improve reproducibility of MC between pathologists, we undertook the next validation step by evaluating the prognostic value of a fully automatic method to detect and count mitoses on whole slide images using a deep learning model. The model was developed in the context of the Mitosis Domain Generalization Challenge 2021 (MIDOG21) grand challenge and was expanded by a novel automatic area selector method to find the optimal mitotic hotspot and calculate the MC per 2 mm2. We employed this method on a breast cancer cohort with long-term follow-up from the University Medical Centre Utrecht (N = 912) and compared predictive values for overall survival of AI-based MC and light-microscopic MC, previously assessed during routine diagnostics. The MIDOG21 model was prognostically comparable to the original MC from the pathology report in uni- and multivariate survival analysis. In conclusion, a fully automated MC AI algorithm was validated in a large cohort of breast cancer with regard to retained prognostic value compared with traditional light-microscopic MC.

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    • Aubreville, Marc

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

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    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Nikolas Stathonikos
    • Marc Aubreville
    • Sjoerd de Vries
    • Frauke Wilm
    • Christof Bertram
    • Mitko Veta
    • Paul van Diest
  • • artificial intelligence
    • machine learning
    • histopathology
    • prognosis
    • mitosis
    • outcome
    • deep learning

• The risk trilemma of how to hedge gas-fired power plants in times of war

  Schneider, C., Römmich, M., & Heinen, A. (2024). The risk trilemma of how to hedge gas-fired power plants in times of war. In S. Behringer (Hrsg.), Konferenzband CARF Luzern 2024: Controlling. Accounting. Risiko. Finanzen (S. 199–212). Rotkreuz: Verlag IFZ — Hochschule Luzern.

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  • 2024
  • Conference Paper
  • • Cedric Schneider
    • Michael Römmich
    • Andreas Heinen
    • Stefan Behringer

• TorqTwin—An open-source reference multibody modeling framework for wind turbine structural dynamics

  Guo, F., Gao, Z., & Schlipf, D. (2024). TorqTwin—An open-source reference multibody modeling framework for wind turbine structural dynamics. Renewable Energy, 235, 121268. http://doi.org/10.1016/j.renene.2024.121268

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    • Schlipf, David

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  • 2024
  • Journal Article
  • • Feng Guo
    • Zhen Gao
    • David Schlipf

• Hochtemperaturwärmepumpen in der Nah- und Fernwärmeversorgung — Technologieperspektive für den kurz- und mittelfristigen Einsatz in multivalenten Systemen

  Freißmann, J., Fritz, M., & Tuschy, I. (2024). Hochtemperaturwärmepumpen in der Nah- und Fernwärmeversorgung — Technologieperspektive für den kurz- und mittelfristigen Einsatz in multivalenten Systemen. http://doi.org/10.5281/zenodo.13311533

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    • Freißmann, Jonas
    • Fritz, Malte
    • Tuschy, Ilja

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  • 2024
  • Report
  • • Jonas Freißmann
    • Malte Fritz
    • Ilja Tuschy

• Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis

  Ganz, J., Marzahl, C., Ammeling, J., Rosbach, E., Richter, B., Puget, C., … Aubreville, M. (2024). Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis. Scientific Reports, 14, 26273. http://doi.org/10.1038/s41598-024-77244-6

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  Abstract The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation. Furthermore, label noise introduced during the annotation process may impede the algorithms’ performance. Unlike H&E, where identification of MFs is based mainly on morphological features, the mitosis-specific antibody phospho-histone H3 (PHH3) specifically highlights MFs. Counting MFs on slides stained against PHH3 leads to higher agreement among raters and has therefore recently been used as a ground truth for the annotation of MFs in H&E. However, as PHH3 facilitates the recognition of cells indistinguishable from H&E staining alone, the use of this ground truth could potentially introduce an interpretation shift and even label noise into the H&E-related dataset, impacting model performance. This study analyzes the impact of PHH3-assisted MF annotation on inter-rater reliability and object level agreement through an extensive multi-rater experiment. Subsequently, MF detectors, including a novel dual-stain detector, were evaluated on the resulting datasets to investigate the influence of PHH3-assisted labeling on the models’ performance. We found that the annotators’ object-level agreement significantly increased when using PHH3-assisted labeling (F1: 0.53 to 0.74). However, this enhancement in label consistency did not translate to improved performance for H&E-based detectors, neither during the training phase nor the evaluation phase. Conversely, the dual-stain detector was able to benefit from the higher consistency. This reveals an information mismatch between the H&E and PHH3-stained images as the cause of this effect, which renders PHH3-assisted annotations not well-aligned for use with H&E-based detectors. Based on our findings, we propose an improved PHH3-assisted labeling procedure.

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    • Aubreville, Marc

  • Forschungsprojekt

    • (mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research
    • CIVU – Center for Interaction, Visualization and Usability

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    • Informatik und Gestaltung

  • Forschungsfeld

    • Human-Computer-Interaction
    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Jonathan Ganz
    • Christian Marzahl
    • Jonas Ammeling
    • Emely Rosbach
    • Barbara Richter
    • Chloé Puget
    • Daniela Denk
    • Elena Demeter
    • Flaviu Tăbăran
    • Gabriel Wasinger
    • Karoline Lipnik
    • Marco Tecilla
    • Matthew Valentine
    • Michael Dark
    • Niklas Abele
    • Pompei Bolfa
    • Ramona Erber
    • Robert Klopfleisch
    • Sophie Merz
    • Taryn Donovan
    • Samir Jabari
    • Christof Bertram
    • Katharina Breininger
    • Marc Aubreville

• Influence of flexibility options on the German transmission grid — A sector-coupled mid-term scenario

  Büttner, C., Esterl, K., Cußmann, I., Realpe, C. A. E., Amme, J., & Nadal, A. (2024). Influence of flexibility options on the German transmission grid — A sector-coupled mid-term scenario. Renewable and Sustainable Energy Transition, 5, 100082. http://doi.org/https://doi.org/10.1016/j.rset.2024.100082

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  Germany must decarbonise all energy sectors to meet international and national climate goals. This task necessitates linking the electricity with the gas, heat and mobility sectors. On the one hand, sector coupling increases the demand for electrical energy and changes well-known demand patterns requiring updates to the grid infrastructure. On the other hand, the newly coupled sectors offer flexibility options to support the grid infrastructure and reduce expansion needs. This study employs a highly detailed model of the German transmission grid to analyse the impact of sector coupling comprising additional electricity demands and flexibility options on grid and storage expansion needs in the year 2035. The results demonstrate that utilising flexibility options can reduce system costs and lower CO2 emissions. The research adheres to open source and open data principles, with all data and tools being publicly accessible.

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  • Forschungsprojekt

    • eGon

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  • 2024
  • Journal Article
  • • Clara Büttner
    • Katharina Esterl
    • Ilka Cußmann
    • Carlos Realpe
    • Jonathan Amme
    • Amélia Nadal
  • • Energy system modelling
    • Sector coupling
    • Flexibility options
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• Green Hydrogen for the Energy Transition in Germany - Potentials, Limits, and Priorities

  Doucet, F., Blohm, M., von Düsterlho, D. J.-E., & Bannert, J. (2024). Green Hydrogen for the Energy Transition in Germany - Potentials, Limits, and Priorities. In 20th International Conference on the European Energy Market (EEM). http://doi.org/https://doi.org/10.1109/EEM60825.2024.10609015

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    • Blohm, Marina

  • Forschungsprojekt

    • NRL Norddeutsches Reallabor

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2024
  • Conference Paper
  • • Felix Doucet
    • Marina Blohm
    • Prof. Dr. von Düsterlho
    • Jonas Bannert