Research Data Repository of Saxon Universities
OPARA is the Open Access Repository and Archive for Research Data of Saxon Universities.
Researchers of Saxon Universities can either publish their research data on OPARA, or archive it here to comply with requirements of funding acencies and good scientic practice, without public access.
You can find the documentation of this service at the ZIH Data Compendium websites. If you need suppourt using OPARA please contact the Servicedesk of TU Dresden.
Please note: The OPARA service was recently upgraded to a new technical platform (this site). Previously stored data will not be available here immediately. It can be found at the still active old version of OPARA. These stock data will be migrated in near future and then the old version of OPARA will finally be shut down. Existing DOIs for data publications remain valid.
Communities in OPARA
Select a community to browse its collections.
Recent Submissions
SPP 2419: 3D printing of alumina components via Fused Granulate Fabrication technology and solvent-free debinding of highly filled feedstocks comprising (LD)-polyethylene and cellulose
(Technische Universität Bergakademie Freiberg, 2026-03-30) Brachhold, Nora; Heuer, Claudia; Bock-Seefeld, Benjamin; Kaiser, Patricia; Weigelt, Christian; Malczyk, Piotr; Trimis, Dimosthenis; Aneziris, Christos G.
This study focuses on the development of components in gyroid structure based on alumina as integral part of the novel burner designed for the non-premixed combustion of ammonia. During application, the component has to withstand repeated thermal shocks of approx. 600 K or more. Due to the high geometric complexity of the gyroid structure and the need for lightweight design with both macroporous regions and microporous features only the
3D printing was suitable as manufacturing technology; in the present work Fused Granulate Fabrication was used. The manufacturing routine for the employed granules with special regard to the binder system is developed. A customized thermal debinding regime without wick or solvent debinding is presented. Challenges such as the formation of bubbles and the swelling of the samples during thermal debinding were met by adjusting the
printing parameters to create porosity and cavities between the deposited strands during 3D printing. Sintered bars fabricated using optimized printing parameters had a shrinkage of 13 %, an open porosity of 41 % and a flexural strength of 50 MPa, respectively. These values are sufficient for the application of the components in the novel burners. As last part of this work sheet-gyroid structures were prepared using a 1.0 mm and 0.4 mm nozzles. These structures successfully survived 5 thermal shock cycles, each involving heating to 1100 ◦C followed by air quenching, which is an excellent result in terms of thermal shock performance.
ResNet to the ResCue: An automated approach for the detection of measurable residual disease in patients with acute myeloid leukemia.
(Technische Universität Dresden, 2026-03-18) Thielecke, Lars; Roehnert, Maximilian-Alexander
This repository provides a minimal, end‑to‑end example pipeline demonstrating how a trained ResNet‑34 model can recognize MRD‑associated patterns in UMAP embeddings derived from flow‑cytometry data of AML patients. ResNet‑based classifiers are widely used for image‑recognition tasks , making them well‑suited for distinguishing subtle MRD‑related patterns in UMAP‑transformed cytometry data.
The pipeline consists of a small collection of Python and R scripts organized as a lightweight workflow, following the standard idea of pipelines as sequences of data‑processing and prediction steps .
Included in the repository are:
- a single example patient dataset (raw data, pre‑processed data, and generated image)
- an R script for preprocessing the raw flow‑cytometry data
- a Python script that converts the tabular preprocessed data into 2D images
- the representative UMAP embedding needed for generating standardized 2D representations of patient-specific data
- a Python script that loads the ResNet‑34 architecture (including the custom classifier head), initializes the trained weights , and runs the prediction procedure to distinguish MRD‑positive from MRD‑negative image patterns
This example is intentionally minimal: it is not a production‑ready pipeline but an educational demonstration of how the core steps—data preparation, image generation, and model prediction—link together in a transparent, reproducible workflow.
Dynamic Spallation Energy Dissipation: Evaluation Methods for Split Hopkinson Bar Tests _ Dataset.rar
(Technische Universität Dresden, 2026-03-11) Davoudkhani, Milad; Maca, Petr; Krcmarova, Nela; Beckmann, Birgit; Maas, Hans-Gerd
This dataset comprises the data of the study on Dynamic Spallation Energy Dissipation: Evaluation Methods for Split Hopkinson Bar Tests. In this study, we employ a single high-speed
camera setup with photogrammetric methods. The approach is based on enhanced inverse spatial resection principles for 3D tracking from single camera image sequence data and on
Structure-from-Motion techniques for 3D shape reconstruction of multiple fragments produced in split Hopkinson bar impact experiments. These fragment shape and motion data
allow to estimate the energy of each fragment, providing a key component in the analysis of energy dissipation.
Research Data - Determination of total hemispherical emissivity utilizing an in-situ calibrated, coupled experimental-simulative electron beam calorimetric approach
(Technische Universität Bergakademie Freiberg, 2026-03-10) Kerber, Konrad
The accurate determination of the total hemispherical emission coefficient (THEC) of materials is essential for modeling radiative
heat transfer in high-temperature vacuum environments. This study presents a rapid steady-state calorimetric method to determine
the THEC using a vacuum electron beam (EB) facility. A graphite-coated Inconel 718 foil with a thickness comparable to the
electron penetration depth was used as the emission target, allowing temperature equalization within seconds. Surface temperatures
were recorded via a calibrated two-colour thermal imaging system. An in-situ calibration was conducted, using the melting point
of pure copper as a fixed reference. Numerical simulations were employed to validate both the emissivity determination and the
temperature calibration methodology. EB heating efficiency was determined at 150 keV in a combined experimental-simulative
approach using Monte Carlo simulations and backscattered electron intensity capture. Temperature calibration showed high reproducibility
with a median absolute deviation of +- 0.4% and a half range of +- 1.1% at 1085 °C, and was shown to be transferable to
other materials. EB heating efficiency slightly decreased from 0.832 +- 0.003 at room temperature to 0.825 +- 0.002 between 800 °C
to 1140 °C. THEC values between 0.88 and 0.92 with a maximum half range of +-0.06 were obtained in the range of 840 °C to
1110 °C for graphite-coated Inconel 718 with a median roughness of Ra = 1.2 µm. Reflected radiation from the emission target
and thermal losses from conduction and sublimation were assessed and found negligible. Results were consistent with literature,
particularly under high surface roughness or pre-oxidized conditions.
Test data for ICPR 2026 - RARE-Vision Competition
(Technische Universität Dresden, 2026-03-09) Le Floch, Maxime
The RARE-VISION test dataset consists of three previously unseen capsule endoscopy examinations acquired with the Navicam system at the University Hospital Carl Gustav Carus, Technical University of Dresden. The dataset is strictly separated from the development data, and ground-truth annotations are withheld for final evaluation.
Each case is provided as a complete chronological video sequence at a resolution of 480 × 480 pixels, preserving the original temporal order without trimming or manual segmentation. The three videos contain:
44,878 frames
53,220 frames
62,927 frames
The data reflect real-world clinical variability and the natural class imbalance of capsule endoscopy, where rare pathological findings occur sparsely within long sequences of normal mucosa.
Annotations are defined as temporal events (start frame, end frame, label) corresponding to the 17 competition target classes. The label set includes anatomical regions and pathological findings only; no anatomical landmarks are annotated.
The dataset is designed to evaluate robust rare-event detection, temporal consistency, and fully automatic inference on long sequential video streams.
The videos are provided exclusively for scientific research within the scope of the ICPR 2026 RARE-VISION competition and must not be used for any commercial purposes. For detailed terms of use, please refer to the official competition report and documentation.
This study was approved by the Ethics Committee of the University Hospital Carl Gustav Carus at the Technical University of Dresden on December 16, 2022 (Ethics ID: BO-EK-534122022), confirming adherence to the ethical principles of the Declaration of Helsinki. Due to the retrospective anonymization of the data and their collection during clinically indicated routine interventions, explicit consent was not required. This is additionally supported by the Ethics Committee’s approval, a consultation with the data privacy officer, and local law. Section 34, Paragraph 1 of the Saxon Hospital Act (SächsKHG) explicitly allows the collection and analysis of this type of data.