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Anàlisis geoquímiques i fotos de visu i microscòpia de les mostres que integren la col·lecció de geostandards del Museu de Geologia Valentí Masachs (UPC Manresa). Análisis geoquímicas y fotos de visu y microscopio de las muestras que integran la colección de geostandares del Museo de Geología Valentí Masachs (UPC Manresa). Geochemical analyses and hand and microscopy pictures of the samples belonging to the geostandards collection of the Valenti Masachs Geology Museum (UPC Manresa). Analyses géochimiques et photographies au microscope et visu des échantillons qui forment la collection de geostandards du Musée de Géologie Valentí Masachs (UPC Manresa).

The data refer to an experimental campaign carried out to characterize the forces involved in the failure of the Pont del Petroli (Badalona, Catalonia) due to the storm Gloria happened in the night of the 20 January 2020. The experiments were carried out in the CIEM (Canal d’Investigació i Experimentació Marítima) wave flume in the Laboratory of Maritime Engineering of the UPC (Universitat Politecnica de Catalunya - BarcelonaTech, Barcelona, Catalonia)., Data include measurements of water surface elevation along the wave flume and wave loading (forces + pressures) on elements of the pier. Both raw and post-processed data are provided.

The data base is related to the High Pressure Grinding Rolls (HPGR) modelling. This data was generated in a HPGR manufacturer pilot plant in Freiberg, Germany, and represents the particle size distribution measurement of the feed and the product of the milling reactor, and the calculation of some material features, as the moisture or the density. This data is necessary for the correct modelization of the comminution in a HPGR, and it can be used for different mathematical models., A model for High Pressure Grinding Rolls (HPGR) was developed in this work based on the widely used Population Balance Model (PBM). This approach uses a variety of different functions one of which is the breakage distribution function. The methodology to determine the function parameters is presented and using these values, the model was compared with real processed materials from an HPGR pilot plant, with tungsten ore as the test material. The results of the model parameter determination, and the product of the comminution in the HPGR, showed the dependency of material breakage on the material characteristics, and on the operative and process conditions. The model presented is reasonably robust, showing less error than the 3.0 Root Mean Square Error when compared with a heterogeneous feed particle size distribution material. The operational gap was also studied, and its dependency on the feed particle size, porosity, moisture, and specific pressing force was proven.

Data include the active (kW) and reactive (kvar) power for the pilot area of H2020 RESOLVD project, each item in one column and with a time step of one hour and one year length.

Data include the voltage and current at the transformer terminals, also the measured current losses from applying various switching strategies. This data serves to reproduce Figure 18 and 19 in the paper.

The dataset contains the following files: (1) readme.txt, it is a text file including details about the content of the dataset; (2) Measurement in ARSD_SMS_Data.xls, it is a MS Excel file containing the data used in the analysis of the primary studies, reported in Section 4 of the paper; and, (3) Metrics in ARSD.pdf, it is pdf file containing the complete list of metrics reported in the different primary studies. The metrics are classified into the following categories: QR metrics, QMIs, and QMI metrics. In the MS Excel file, the data is organised in separated sheets: (a) RQ1 - Literature characterisation; (b) RQ2 - QR Metrics, where QR refers to Quality Requirements; (c) RQ3 - QMI, where QMI refers to Quality Management Indicators; (d) RQ3 - Tools, corresponding to the reported tools used to manage QMIs; and, (e) RQ3 - QMI Metrics., This dataset has been used to generate part of the results included in the manuscript: “Quality Measurement in Agile and Rapid Software Development: A Systematic Mapping”, submitted to the Information and Software Technology journal (IST) at the time of publishing this dataset. The paper reports the results of a systematic mapping study surveying the literature related to quality requirements management through metrics in agile and rapid software development processes. The dataset contains the data extracted from the primary studies that was used in the analysis phase of the study and reported in the results section of the paper. The data extracted from the primary studies has been complemented with some data used for specific purposes, e.g. during the analysis phase, we included the list of companies collaborating in the paper analysing the authors’ affiliations to understand the level of implication of companies in the field. Complementing the data analysed, the dataset includes some detailed results that are not included in the body of the paper, i.e., the list of metrics reported in the selected primary studies.

This file includes data on system vertical and lateral stiffness of stainless steel frames under gravity and gravity plus wind load scenarios obtained from the finite element simulations carried out on six stainless steel frames.

Numerical Model for a 19th Century Hydrometric (Case 1: 1000 L/s inlet flow). Aquests datasets són els models numèrics que corresponen als 6 casos de simulacions fetes amb el software de CFD anomenat Flow3D.

Data was generated using the general purpose finite element software ABAQUS and performing advanced nonlinear analyses. The database is comprised of ultimate load factors corresponding to different random samples of six different nominal stainless steel frames under gravity and wind load combinations. The values of the random variable assignments are given for each case. The full details of the finite element model can be found in: Arrayago, I.; Rasmussen, K.J.R.; Zhang, H. System-based reliability analysis of stainless steel frames subjected to wind loads. "Structural Safety", July 2022, vol. 97, art. No. 102211. DOI: https://doi.org/10.1016/j.strusafe.2022.102211

Data associated with the study called "Selectively targeting tumorigenicity in osteosarcoma". Each file corresponds to the raw data of one of the figures of the paper