DaKS - University of Kassel's research data repository

DaKS is the institutional repository of the University of Kassel for research data. It offers structured storage of research data alongside with descriptive metadata, long-term archiving for at least 10 years and – if requested – the publication of the dataset with a DOI.

DaKS is managed by the university library and the IT Service Centre of the University of Kassel. It is hosted at Philipps-Universität Marburg. We are happy to advise you via daks@uni-kassel.de.

Recent Submissions

Brownian motion of DNA-functionalized magnetic nanoparticles as a function of DNA length for conformation analysis beyond the optical resolution limit
(Universität Kassel) Janzen, Christian; Ehresmann, Arno; Hütten, Andreas
Brownian motion provides access to hydrodynamic properties of nanoscale objects independent of their optical resolvability. Here, we present a diffusion-based approach to infer effective particle size distributions of DNA-functionalized magnetic nanoparticles (MNPs), consisting of a magnetic core and a polystyrene shell, in a regime where direct geometric sizing is limited by optical diffraction. Using multi-particle tracking microscopy, we analyze the Brownian dynamics of MNPs grafted with double-stranded DNA (dsDNA) of varying contour length under low-salt conditions. A physically motivated model is introduced that relates dsDNA contour length to an effective hydrodynamic diameter via an attenuated corona description. The measured diffusion coefficient distributions exhibit a systematic and monotonic dependence on dsDNA length in quantitative agreement with the model. While the tracked objects are predominantly dsDNA-mediated agglomerates rather than isolated nanoparticles, clustering does not obscure the length-dependent signal. Instead, the dsDNA corona determines the hydrodynamic scaling, whereas agglomeration mainly introduces an offset and distribution broadening. These results demonstrate that Brownian dynamics enables robust readout of biomolecular length scales even far below the optical resolution limit. The distribution-based approach is inherently tolerant to polydispersity and aggregation, making diffusion-based tracking a simple and promising strategy for future biotechnological and biomedical assays.
Digitale Zwillinge in Produktion und Logistik – Modellfabriken und Reifegradmodelle
(Universität Kassel) Gliem, Deike; Wenzel, Sigrid
Die Dokumentation umfasst zum einen eine systematische Literaturrecherche zur Identifikation bestehender Modellfabriken für Digitale Zwillinge. Insgesamt werden 17 Modellfabriken herangezogen, um eine Handlungsempfehlung zur Anschaffung einer Modellfabrik für Digitale Zwillinge in Produktion und Logistik am Fachgebiet pfp der Universität Kassel auszusprechen. Die Ergebnisse entstanden in Zusammenarbeit mit Luca Rehs (Rehs, Luca-Joshua: Konzeptionierung einer Modellfabrik zur Untersuchung Digitaler Logistikzwillinge. Bachelorarbeit, Universität Kassel, Studiengang Maschinenbau, 05/2024 (Prof. Wenzel / Gliem, FB 15, Universität Kassel)). Die Dokumentation umfasst zum anderen eine weitere systematische Literaturrecherche zur Identifikation bestehender Reifegradmodelle für Digitale Zwillinge. Insgesamt werden 31 Modelle herangezogen, um ein eigenes Reifegradmodell für Digitale Zwillinge in Produktion und Logistik abzuleiten. Das entwickelte Modell ist speziell auf die Anforderungen und Rahmenbedingungen von kleinen und mittleren Unternehmen (KMU) zugeschnitten. Die Struktur des Reifegradmodells wird vollständig beschrieben und umfasst vier Dimensionen mit jeweils vier Indikatoren, anhand derer die Reife eines Digitalen Zwillings bewertet werden kann. Zusätzlich wird die praktische Anwendung des Modells anhand von drei Use Cases demonstriert, die mögliche Einsatzszenarien in industriellen Umgebungen abbilden.Der Titel der Publikation wurde am 20.02.2026 geändert. Vorheriger Titel: Modellfabrik und Reifegradmodell für Digitale Zwillinge in Produktion und Logistik
Kartierungsergebnisse der krautigen Vegetation der Park-/Grünanlagen der Stadt Freiburg i. Br. [Daten]
(Universität Kassel, 2025) Barthelmes, Beatrice
Kartierungsergebnisse der krautigen Vegetation der Park-/Grünanlagen der Stadt Freiburg i. Br. Insgesamt wurden in elf untersuchten Park-/Grünanlagen der Stadt Freiburg i. Br. 127 Aufnahmequadrate für die Vegetationserfassung etabliert. Es wurden extensiv gepflegte (Wiesen und Langgrasflächen) und intensiv gepflegte Bereiche (Rasen) untersucht. Die Kategorien der untersuchten Flächen sind dabei folgende: Wiesen: Bereiche, die in der Regel mit 1-2 Mahdvorgängen im Jahr extensiv gepflegt werden. Das Mahdgut wird abgeräumt. Langgrasflächen: Bereiche, die in der Regel mit 1-2 Mahdvorgängen im Jahr extensiv gepflegt werden. Das Mahdgut verbleibt auf der Fläche. Gebrauchsrasen/Spielrasen: Bereiche, die in regelmäßigen Abständen während der Vegetationsperiode gemulcht werden. Zusätzlich zur Artenvielfalt wurden nach der international verwendeten Aufnahmen-Skala von Braun-Blanquet die Artmächtigkeiten (Menge) und die Mächtigkeiten der blühenden Arten erfasst. Hierbei wurde die ursprüngliche Schätzskala von Braun-Blanquet verwendet. Die Kartierungsjahre waren 2020 und 2021.
Mechanical Properties of Normal Concrete
(Universität Kassel) Rezazadeh, Farzad; Dürrbaum, Axel; Abrishambaf, Amin; Zimmermann, Gregor; Kroll, Andreas
Normal concrete is the most widely used form of concrete, and its mechanical properties can vary due to variations in raw-material quality, dosage errors, and changes in material storage, mixing, and curing conditions, even when a fixed reference mix design is used. This variability constitutes a reproducibility challenge for concrete production under fixed formulations. This dataset examines the effects of variations in raw-material condition and process parameters on the mechanical properties of normal concrete produced from a base mix design targeting a 65 MPa compressive strength. The dataset comprises 32 systematically designed experiments. Compressive strength was measured at 1 day (24 hours), 7 days, and 28 days after mixing. Where available, the reported values represent the average of three specimens per experiment. In addition, five fresh-state properties were measured immediately after each mixing process (temperature, electrical conductivity sensor reading, slump-flow, V-funnel flow time, and air content). All experiments were conducted in the laboratory of G.tecz Engineering GmbH under controlled conditions using the same mixer, mixing tools, and personnel. The dataset provides high-dimensional experimental data with a limited number of observations and is suitable for developing and evaluating regression models in sparse scenarios.
Mechanical Properties of Ultra-High Performance Concrete (UHPC)
(Universität Kassel) Rezazadeh, Farzad; Dürrbaum, Axel; Abrishambaf, Amin; Zimmermann, Gregor; Kroll, Andreas
Ultra-high-performance concrete (UHPC) possesses mechanical characteristics that significantly outperform traditional concrete. However, replicating these properties consistently across different production batches—even when using the same recipe—remains a challenge. This dataset examines how variations in raw materials, environmental conditions, dosage variation, and both mixing and curing practices affect the mechanical properties of UHPC produced from a single reference formulation. Designed according to a three-phase design of experiments methodology, the dataset comprises 150 systematically planned experiments, offering a comprehensive view of the multiple factors influencing UHPC quality. Measurements of compressive and flexural strengths are provided at 24 hours and after 28 days post-mixing. Beside the mechanical properties, the dataset includes five characteristics of the fresh state, measured directly after each mixing process. All experiments are conducted in the laboratory of G.tec Engineering GmbH under controlled conditions, using the same mixer, same mixing tool, and the same team of technicians. The environment is maintained at a constant temperature of 20 °C throughout the experimental process. From each experiment, three specimens are cured under the designed conditions. First, the flexural strength is measured by carefully halving each of the three specimens. Then, the resulting six halves are used to measure the compressive strength. Finally, after a careful analysis of the results from each specimen, the averages for flexural and compressive strengths are reported. The dataset also includes outliers. After analysis by UHPC experts and the data science team, 11 data points (numbered 5, 17, 30, 36, 41, 47, 57, 99, 101, 128, and 148) were identified and removed as outliers to assure data quality. By offering a structured collection of high-dimensional data and a relatively small data size, this dataset is particularly suitable for advanced regression analyses, notably those addressing sparse data scenarios.