Resultados de investigación

This dataset contains the experimental data that supports the paper: Guillén-Ludeña, S., Lopez, D., Mignot, E., & Riviere, N. (2019). Flow Resistance for a Varying Density of Obstacles on Smooth and Rough Beds. Journal of Hydraulic Engineering, 146(2), 04019059.

Data set associated with the published article entitled: In vitro lead tolerance and accumulation in three Chrysanthemum cultivars for phytoremediation purposes with ornamental plants.

We present a novel, low-cost telerehabilitation system dedicated for bimanual training. The system captures the user’s movements with a Microsoft Kinect sensor and an inertial measurement unit (IMU). Herein, we deposit data we collected on a single, healthy subject who interacted with our system as described in our manuscript.

This dataset corresponds to yield, price and fuel consumption from organic rainfed almond orchards in SE Spain under different diversification and tillage practices. The objective is to carry out an integrated environmental (focused on the CO2 emissions) and economic assessment of farm operations under different diversification and tillage practices through a cradle-to-farm gate life cycle assessment (LCA) based on these data. These data correspond to the open-access article "Carbon emissions and economic assessment of farm operations under different tillage practices in organic rainfed almond orchards under semiarid Mediterranean conditions" published in Scientia Horticulturae. (https://doi.org/10.1016/j.scienta.2019.108978), funded by the European Commission Horizon 2020 project Diverfarming [grant agreement 728003].

This data set contains information from a choice experiment survey developed to value the socio-economic benefits of intercropping practices in Mediterranean agroecosystems. These data correspond to the open-access article "Valuing diversification benefits through intercropping in Mediterranean agroecosystems: A choice experiment approach" published in Ecological Economics. (https://doi.org/10.1016/j.ecolecon.2020.106593), funded by he European Commission Horizon 2020 project Diverfarming [grant agreement 728003].

The study of soft matter films under mechanical confinement was originally made possible by the emergence of the Surface Force Apparatus and the Atomic Force Microscope. These techniques provide accurate interaction forces at different separations. However, they do not provide structural information. Going beyond measurements of forces and measuring near-surface structures has been a challenge for a number of decades. In this regard, Neutron Reflectometry (NR) offers unparalleled possibilities for extracting structural information of mechanically confined thin films. Recently, a team partly formed by the applicants developed a sample environment for NR studies of mechanically confined thin soft films that has been a breakthrough in confined soft matter investigations. However, there is significant room for improvement. Specifically, the possibility to study shear-induced structural rearrangements would be of great value in lubrication science along with a number of other fields. We have addressed this challenge and designed a new NR confinement cell allowing shearing of two opposing surfaces. Here, we apply for beam time to test the first prototype of this novel sample environment.

Data on C:N:P of lab-cultured marine dinoflagellates were identified by searching in the ISI Web of Science using keywords such as elemental composition, elemental stoichiometry, elemental ratios, C:N, C:P or C:N combined with the word dinoflagellate. These studies and suitable studies cited within these sources were evaluated for data collection. Experimental conditions were recorded along with the elemental composition data including culturing methods, the media used, culture temperature and salinity. Cell volume and growth rate data were collected when available. Species were then assigned the following traits: 1. thecate or athecate; 2. non-toxic or the potential to produce C-rich or N-rich toxins; and 3. small, medium or large cell volume.

This dataset is related to the protocol developed by the authors on the evaluation of the effects of cold atmospheric plasma and plasma-treated liquids in cancer cell cultures. More specifically, the data correspond to the anticipated results presented in the paper submitted to Nature Protocols, The present dataset corresponds to the anticipated results that can be obtained following the protocol described in the article. In particular, dataset corresponding to Figure 8 presents the absorbance values from the WST-1 cytotoxicity assay as a function of the well size where the experiment is performed. Data from Figure 9b show absorbance values from the WST-1 cytotoxicity assay as a function of the treatment time. Data from figure 9c-e show the absorbance or fluorescence values obtained in the experiments to quantify RONS, together with the values from the calibration curves. Data fromfigure 10 a provide the list and values of mRNA fold induction of the genes analyzed, and data from figure 10c show the pixel intensity obtained for the phospho-kinase antibody array., 1

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., 1

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., 1