Now showing 1 - 10 of 112
  • Publication
    A concept for a large-scale non-contact strain measurement system using nanostructures
    The monitoring of mechanical strain is essential in developing new materials, designing mechanical components and structural health monitoring. In applications where contactless measurement is required, a novel method is needed to allow for absolute and long-term measurements. We discuss a measuring principle based on diffractive nanostructures featuring these advantages. For the measurement, periodic nanostructures are applied to a component, illuminated with a defined light source and the resulting color impression is monitored. The relationship between the stretched geometry of the nanostructure and diffraction spectra allows to quantify the component’s strain. We present a guide-line for the design of industrial applicable and sensitivity-optimized nanostructures and discuss the advantages in different application scenarios.
  • Publication
    5G in Production - from Use Case to Business Case
    ( 2024-04-26)
    The widespread rollout of 5G in the manufacturing industry depends heavily on its contribution to improving the economic performance of manufacturing companies. The presentation introduces a methodology for calculating the techno-economical potential of 5G use cases. A specific manufacturing use case is presented as a case study, showing the technical and business KPIs and potential economic benefits.
  • Publication
    Technologien und Lösungsansätze für die effiziente Herstellung von Zelltherapeutika für die CAR-Immuntherapie
    Die dynamischen Entwicklungen auf dem Gebiet der zellulären Immuntherapie, insbesondere im Bereich der CAR-T-Zellen, ermöglichen neue Erfolg versprechende Behandlungsoptionen von Krebserkrankungen. Zugleich stellen diese noch jungen Krebstherapien die Medizin vor große Herausforderungen. Wie die Herstellung von zellulären Krebstherapeutika im großen Maßstab zur Versorgung der wachsenden Patientenzahl in der Zukunft gewährleistet werden kann und welche Hürden es dabei zu überwinden gilt, wird im Folgenden adressiert. Erste Optionen zur automatisierten Herstellung von CAR-T-Zellen sind bereits etabliert. Um zukünftig die Behandlung großer Patientengruppen zu gewährleisten, sind neue Herstellungstechnologien wie allogene Zellquellen, digital gesteuerte Prozessstraßen und automatische Qualitätskontrollen erforderlich.
  • Publication
    Young’s Modulus-Independent Determination of Fibre Parameters for Rayleigh-Based Optical Frequency Domain Reflectometry from Cryogenic Temperatures up to 353 K
    ( 2023-05-09)
    Girmen, Caroline
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    Dittmar, Clemens
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    Siedenburg, Thorsten
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    Gastens, Markus
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    Wlochal, Michael
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    Schröder, Kai-Uwe
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    Schael, Stefan
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    The magnetic spectrometer AMS-100, which includes a superconducting coil, is designed to measure cosmic rays and detect cosmic antimatter in space. This extreme environment requires a suitable sensing solution to monitor critical changes in the structure such as the beginning of a quench in the superconducting coil. Rayleigh-scattering-based distributed optical fibre sensors (DOFS) fulfil the high requirements for these extreme conditions but require precise calibration of the temperature and strain coefficients of the optical fibre. Therefore, the fibre-dependent strain and temperature coefficients 𝐾T and 𝐾𝜖 for the temperature range from 77 K to 353 K were investigated in this study. The fibre was integrated into an aluminium tensile test sample with well-calibrated strain gauges to determine the fibre’s 𝐾𝜖 independently of its Young’s modulus. Simulations were used to validate that the strain caused by changes in temperature or mechanical conditions was the same in the optical fibre as in the aluminium test sample. The results indicated a linear temperature dependence of 𝐾𝜖 and a non-linear temperature dependence of 𝐾T. With the parameters presented in this work, it was possible to accurately determine the strain or temperature of an aluminium structure over the entire temperature range from 77 K to 353 K using the DOFS.
  • Publication
    Towards automated CAR-T Cell Manufacturing. Keeping up with Technological Advancement
    ( 2023-05-04) ; ; ;
    Bäckel, Niklas
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    Franz, Paul
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    Hudecek, Michael
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    Rafiq, Qasim
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    Goldrick, Stephen
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    Papantoniou, Ioannis
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    The AIDPATH project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no 101016909. The material presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out.
  • Publication
    Adaptive phase contrast microscopy to compensate for the meniscus effect
    Phase contrast is one of the most important microscopic methods for making visible transparent, unstained cells. Cell cultures are often cultivated in microtiter plates, consisting of several cylindrical wells. The surface tension of the culture medium forms a liquid lens within the well, causing phase contrast conditions to fail in the more curved edge areas, preventing cell observation. Adaptive phase contrast microscopy is a method to strongly increase the observable area by optically compensating for the meniscus effect. The microscope’s condenser annulus is replaced by a transmissive LCD to allow dynamic changes. A deformable, liquid-filled prism is placed in the illumination path. The prism’s surface angle is adaptively inclined to refract transmitted light so that the tangential angle of the liquid lens can be compensated. Besides the observation of the phase contrast image, a beam splitter allows to simultaneously view condenser annulus and phase ring displacement. Algorithms analyze the displacement to dynamically adjust the LCD and prism to guarantee phase contrast conditions. Experiments show a significant increase in observable area, especially for small well sizes. For 96-well-plates, more than twelve times the area can be examined under phase contrast conditions instead of standard phase contrast microscopy.
  • Publication
    LIFTOSCOPE: development of an automated AI-based module for time-effective and contactless analysis and isolation of cells in microtiter plates
    Background: The cultivation, analysis, and isolation of single cells or cell cultures are fundamental to modern biological and medical processes. The novel LIFTOSCOPE technology aims to integrate analysis and isolation into one versatile, fully automated device. Methods: LIFTOSCOPE’s three core technologies are high-speed microscopy for rapid full-surface imaging of cell culture vessels, AI-based semantic segmentation of microscope images for localization and evaluation of cells, and laser-induced forward transfer (LIFT) for contact-free isolation of cells and cell clusters. LIFT transfers cells from a standard microtiter plate (MTP) across an air gap to a receiver plate, from where they can be further cultivated. The LIFT laser is integrated into the optical path of an inverse microscope, allowing to switch quickly between microscopic observation and cell transfer. Results: Tests of the individual process steps prove the feasibility of the concept. A prototype setup shows the compatibility of the microscope stage with the LIFT laser. A specifically designed MTP adapter to hold a receiver plate has been designed and successfully used for material transfers. A suitable AI algorithm has been found for cell selection. Conclusion: LIFTOSCOPE speeds up cell cultivation and analysis with a target process time of 10 minutes, which can be achieved if the cell transfer is sped up using a more efficient path-finding algorithm. Some challenges remain, like finding a suitable cell transfer medium. Significance: The LIFTOSCOPE system can be used to extend existing cell cultivation systems and microscopes for fully automated biotechnological applications.
  • Publication
    Optical coherence tomography and convolutional neural networks can differentiate colorectal liver metastases from liver parenchyma ex vivo
    ( 2023)
    Amygdalos, Iakovos
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    Burkl, Luisa
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    Vargas, David
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    Goßmann, Paul
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    Wolff, Laura I.
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    Druzenko, Mariia
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    Chrysos, Alexandros
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    Jöchle, Katharina
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    Ulmer, Florian
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    Lambertz, Andreas
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    Knüchel-Clarke, Ruth
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    Neumann, Ulf Peter
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    Lang, Sven A.
    Purpose: Optical coherence tomography (OCT) is an imaging technology based on low-coherence interferometry, which provides non-invasive, high-resolution cross-sectional images of biological tissues. A potential clinical application is the intraoperative examination of resection margins, as a real-time adjunct to histological examination. In this ex vivo study, we investigated the ability of OCT to differentiate colorectal liver metastases (CRLM) from healthy liver parenchyma, when combined with convolutional neural networks (CNN). Methods: Between June and August 2020, consecutive adult patients undergoing elective liver resections for CRLM were included in this study. Fresh resection specimens were scanned ex vivo, before fixation in formalin, using a table-top OCT device at 1310 nm wavelength. Scanned areas were marked and histologically examined. A pre-trained CNN (Xception) was used to match OCT scans to their corresponding histological diagnoses. To validate the results, a stratified k-fold cross-validation (CV) was carried out. Results: A total of 26 scans (containing approx. 26,500 images in total) were obtained from 15 patients. Of these, 13 were of normal liver parenchyma and 13 of CRLM. The CNN distinguished CRLM from healthy liver parenchyma with an F1-score of 0.93 (0.03), and a sensitivity and specificity of 0.94 (0.04) and 0.93 (0.04), respectively. Conclusion: Optical coherence tomography combined with CNN can distinguish between healthy liver and CRLM with great accuracy ex vivo. Further studies are needed to improve upon these results and develop in vivo diagnostic technologies, such as intraoperative scanning of resection margins.
  • Publication
    Empirical study on 5G NR Adjacent Channel Coexistence
    ( 2023)
    Caro, Jordi Biosca
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    Ansari, Junaid
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    Sayyed, Ahmed Raza
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    Bruin, Peter de
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    Sachs, Joachim
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    5G New Radio (NR) non-public network deployments for industrial and enterprise applications are becoming highly popular in locally licensed and/or operator spectrum. The interference from coexisting networks on adjacent channels (in same or adjacent spectrum bands) could potentially deteriorate the performance characteristics in certain deployment scenarios. Appropriate interference mitigation is thus required to achieve the desired performance levels. In this paper, we present our detailed empirical results on the performance impact of coexisting 5G NR networks operating on adjacent channels. Our experimental study conducted on an industrial shopfloor reports the impact on the downlink and uplink latency and throughput when using the same and different Time Division Duplexing patterns for coexisting networks. Our empirical evaluation includes realistic user equipment deployment locations and traffic load conditions. We also present our results on different mitigation techniques to counter the adjacent channel interference effects.
  • Publication
    Optical coherence tomography combined with convolutional neural networks can differentiate between intrahepatic cholangiocarcinoma and liver parenchyma ex vivo
    ( 2023)
    Wolff, Laura I.
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    Goßmann, Paul
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    Druzenko, Mariia
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    Chrysos, Alexandros
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    Jöchle, Katharina
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    Truhn, Daniel
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    Kather, Jakob Nikolas
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    Lambertz, Andreas
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    Gaisa, Nadine Therese
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    Jonigk, Danny David
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    Ulmer, Florian T.
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    Neumann, Ulf Peter
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    Lang, Sven Arke
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    Amygdalos, Iakovos
    Purpose: Surgical resection with complete tumor excision (R0) provides the best chance of long-term survival for patients with intrahepatic cholangiocarcinoma (iCCA). A non-invasive imaging technology, which could provide quick intraoperative assessment of resection margins, as an adjunct to histological examination, is optical coherence tomography (OCT). In this study, we investigated the ability of OCT combined with convolutional neural networks (CNN), to differentiate iCCA from normal liver parenchyma ex vivo. Methods: Consecutive adult patients undergoing elective liver resections for iCCA between June 2020 and April 2021 (n = 11) were included in this study. Areas of interest from resection specimens were scanned ex vivo, before formalin fixation, using a table-top OCT device at 1310 nm wavelength. Scanned areas were marked and histologically examined, providing a diagnosis for each scan. An Xception CNN was trained, validated, and tested in matching OCT scans to their corresponding histological diagnoses, through a 5 × 5 stratified cross-validation process. Results: Twenty-four three-dimensional scans (corresponding to approx. 85,603 individual) from ten patients were included in the analysis. In 5 × 5 cross-validation, the model achieved a mean F1-score, sensitivity, and specificity of 0.94, 0.94, and 0.93, respectively. Conclusion: Optical coherence tomography combined with CNN can differentiate iCCA from liver parenchyma ex vivo. Further studies are necessary to expand on these results and lead to innovative in vivo OCT applications, such as intraoperative or endoscopic scanning.