Hessisches Ministerium für Wissenschaft und Kunst
00zd5gr55 
5054833-5 Research Data
Research Data Legume-colonizing aphids as potential PNYDV-vectors: Reproduction and infestation dynamics in two different field bean varieties [Dataset](Universität Kassel) Berawe, Ahmed; Ziebell, Heiko; Seeger, Judith Nora; Saucke, HelmutThis data and corresponding manuscript partly demonstrates why the ‘GL Sunrise’ faba bean variety has exhibiting lower viral symptoms in the field despite lacking resistance to Pea necrotic yellow dwarf virus (PNYDV). The apparent field resistance to PNYDV in the faba bean cultivar ‘GL Sunrise’ is due to effects on aphid vectors that transmit the virus between plants. This research shows aphid reproduction on the ‘GL Sunrise’ variety was lower compared to the ‘Fuego’ variety. This work also shows the importance of conducting lab experiments to complement field work with relevant field-derived aphid strains. This research provides valuable insights into PNYDV occurrence in the field and informs the development of resistant varieties. This work also shows that varietal testing should include assays to test a range of aphid behaviours as well as growth and reproduction when evaluating new varieties.Research Data Performance of Thermo-Mechanically Processed AA7075 Alloy at Elevated Temperatures—From Microstructure to Mechanical PropertiesSajjadifar, Seyedvahid; Scharif, Emad; Steinhoff, Kurt; Niendorf, Thomas; Weidig, UrsulaResearch Data Mechanical Properties of Ultra-High Performance Concrete (UHPC)(Universität Kassel) Rezazadeh, Farzad; Dürrbaum, Axel; Abrishambaf, Amin; Zimmermann, Gregor; Kroll, AndreasUltra-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.