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Using a previous mechanical characterization of two types of material, several lab-test work have been done. The data shows the particle size distribution of these tests, all the inputs and the model simulation presented in the related paper to this data base. The new mathematical approach use the operative conditions and the feed particle size distribution to obtain a product, which is compared with the lab-test results, An improved approach is presented to model the product particle size distribution resulting from grinding in high-pressure roll crusher with the aim to be used in standard high-pressure grinding rolls (HPGR). This approach uses different breakage distribution function parameter values for a single particle compression condition and a bed compression condition. Two materials were used for the experiments; altered Ta-bearing granite and a calc-silicate tungsten ore. A set of experiments was performed with constant operative conditions, while varying a selected condition to study the influence of the equipment set-up on the model. The material was comminuted using a previously determined specific pressing force, varying the feed particle size, roll speed and the static gap. A fourth group of experiments were performed varying the specific pressing force. Experimental results show the high performance of the comminution in a high-pressure environment. The static gap was the key in order to control the product particle size. A mathematical approach to predict the product particle size distribution is presented and it showed a good fit when compared to experimental data. This is the case when a narrow particle size fraction feed is used, but the fit became remarkably good with a multi-size feed distribution. However, when varying the specific pressing force in the case of the calc-silicate material, the results were not completely accurate. The hypothesis of simultaneous single particle compression and bed compression for different size ranges and with different parameters of the distribution function was probed and reinforced by various simulations that exchanged bed compression parameters over the single particle compression distribution function, and vice versa.

The data have been acquired during the experimental campaign carried out in the Steep Slope Flume at Morphodynamics Laboratory I of the GITS group in BarcelonaTech-Universtitat Politècnica de Catalunya. Data published here comprise the measurements carried out in the laboratory related with velocity profiles in steep channels with low relative submergence. Flume slope ranged between 2-10% and same bed material had been used (a basaltic gravel of 1.45 mm of main diameter) for all the experiments. 30 experiments were carried out with 165 velocity profile measurements.

This dataset has been used to generate part of the results included in the manuscript: "Cooperative Learning for End-to-End Delay Modeling in Multi-Domain Networks", submitted to IEEE Transactions on Network and Service Management (TNSM) at the time of publication of this dataset. The dataset contains synthetic end-to-end (e2e) delay and traffic measurements for multidomain paths established in a network consisting in three domains. Paths traverse either two or three domains. Besides e2e monitoring data, routing information of the paths and the models used to compute the delay introduced for each domain (i.e. intra-domain delay components of total e2e delay) are provided. Traffic and delay data were synthetically generated according to the CURSA-SQ methodology. For further details about it, please refer to the following reports: "The Logistic Queue Model", Tech. Rep. UPC-DAC-RR-GEN-2020-1 (Available online: https://people.ac.upc.edu/lvelasco/docs/research/UPC-DAC-RR-GEN-2020-1.pdf) and "Validation of the CURSA-SQ Methodology", Tech. Rep. UPC-DAC-RR-GEN-2020-2 (Available online: https://people.ac.upc.edu/lvelasco/docs/research/UPC-DAC-RR-GEN-2020-2.pdf)

This file includes data used in the calibration of statistical models for the different random variables affecting stainless steel members. This data was used in the analysis carried out and reported in the publication: Arrayago I., Rasmussen K.J.R., Real E. Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members Journal of Constructional Steel Research 175, 106378, 2020. DOI: https://doi.org/10.1016/j.jcsr.2020.106378 Measured and nominal values are listed for geometry-related data. Measured values are listed for material, imperfection and residual stress data.

The dataset contains four files. File S1 corresponds to cathodoluminescence and BSE images of standard minerals. File S2 contains geochemical data of mineral standards ans samples obtained by SIMS and EPMA. File S3 contains the parameters used to obtain response surface models of IMF in mineral standards. File S4 is a response surface methodology tutorial., Instrumental mass fractionation (IMF) of isotopic SIMS analyses (Cameca 1280HR, CRPG Nancy) was predicted by response surface methodology (RSM) for 18O/16O determinations of plagioclase, K-feldspar and quartz. The three predictive response surface models combined instrumental and compositional inputs. The instrumental parameters were: (i) X and Y position, (ii) LT1DefX and LT1DefY electrostatic deflectors, (iii) chamber pressure and, (iv) primary-ion beam intensity. The compositional inputs included: (i) anorthite content (An%) for the plagioclase model and, (ii) orthoclase (Or%) and barium (BaO%) contents for the K-feldspar model. The three models reached high predictive powers. The coefficients R2 and prediction-R2 were, respectively, 90.47% and 86.74% for plagioclase, 87.56% and 83.17% for K-feldspar and 94.29% and 91.59% for quartz. The results show that RSM can be confidently applied to IMF prediction in stable isotope SIMS analyses by the use of instrumental and compositional variables.

These data are associated to the paper with the same title and are structured according to the figures in the paper. These data correspond to the research results of the WP2 of the European Project 4D-POLYSENSE., The present dataset collects and reports the scientific results corresponding to a scientific study of a commercial and fully flexible versatile bilayer system, composed by a polypropylene (PP) mesh and a covalently bonded poly(N-isopropylacrylamide) (PNIPAAm) hydrogel. In this study the mechanism responsible for cell-adhesion and de-adhesion, when the PNIPAAm-co-MBA monolayer film (adherent on one hand to the PP substrate and anti-adherent on the other hand to cell proliferation) is being employed, has been elucidated. The grafting of the hydrogel was studied and the the graft yield as well as the spectroscopic characterization (FTIR and XPS) of samples treated at different concentration of the crosslinker and different grafting time are ported in the present dataset. The scientific results of cell adhesion and biocompatibility assay are also included, being the in vitro results with fibroblast (COS-1) and epithelial (MCF-7) cells obtained with a mesh modified with a porous iPP-g-PNIPAAm bilayer system, prepared via PNIPAAm grafting for 2 h at the lowest N,NI-methylene bis(acrylamide) (MBA) concentration (1 mM).

Analitical data of several minerals (quartz, K-feldspar, plagioclase, Monazite) of the albitized granites of the Variscan basement in Europe. The samples come from the Catalan Coastal Ranges, the Pyrenees, the Morvan massif and the Sudetes. Most of this data have been used in several papers and in the Cares Fàbrega PhD Thesis.

These data are associated to the paper with the same title and are structured according to the figures in the paper. These data correspond to the research results of the WP1 of the European Project 4D-POLYSENSE., In the scientific publication corresponding to the present dataset, a commercial and fully flexible monofilament polypropylene mesh has been used for the deposition of a thermosensitive hydrogel, generated by graft copolymerization of N-isopropylacrylamide (NIPAAm) and N,NI-methylene bis(acrylamide) (MBA) monomers. The study represents an initial step for the future development of a new generation of surgical meshes, able to interact with the complex three-dimensional structure of biological tissues, as smart materials working as self-evolving motion sensors. The meshes were previously functionalized by O2-plasma method and subsequently grafted with the thermoresponive hydrogel and the data related to micro- and standard spectroscopy techniques empoyed for the characterization, such as Raman spectroscopy, FTIR spectroscopy and XPS, are reported in the present dataset. Additionally, the data of graft yield and thermoresponsive properties of PNIPAAm (VPTT behaviour) are included in the dataset

Datos recopilados en el análisis de la colecciones docentes disponibles en los repositorios institucionales de las universidades españolas.