Resultados de investigación

The Kinect Evaluation in Orchard conditions (KEvOr) dataset is comprised of a set of RGB-D captures carried out with the Microsoft Kinect v2 to evaluate the performance of this sensor at different lighting conditions in agricultural orchards and from different distances to the measured target. Three Microsoft Kinect v2 sensors (K2S1, K2S2 and K2S3) were used to scan Fuji apple trees along the afternoon and evening, from the higher sun illuminance (55000 lux) until achieving dark conditions (0.1 lux), obtaining a total of 252 captures: 28 lighting conditions * 3 sensors * 3 repetitions. The data provided for each capture is: the acquired point cloud, illuminance level at the center of the measured scene, and wind speed. The sensors where placed as follows: K2S1: Oriented to the north, measuring the row of trees side under direct sunlight. This sensor was placed at 2.5 m from the measured target. K2S2: Oriented to the north, measuring the row of trees side under direct sunlight. This sensor was placed at 1.5 m from the measured target. K2S3 Oriented to the south, measuring the row of trees side under indirect sunlight. This sensor was placed at 2.5 m from the measured target. The dataset also includes two additional registered captures measuring the same scene from 1.5 m and from 2.5 m., Dades primàries associades a un article publicat a la revista Sensors disponible a l'adreça https://doi.org/10.3390/s20247072

Measurements of the Root Mean Square of Successive Differences (RMSSD) of 10 volunteers before and during the COVID-19 pandemic., Dades primàries associades a un article pendent d'avaluació., This work was supported by the Institut de Desenvolupament Social i Territorial (INDEST) – Universitat de Lleida and the Spanish National Plan – European Union RTI2018-094142-B-C21.

(International) research collaboration (IRC) is considered one of the most important aspects of academic careers and, although it is often linked to co-authorship, investigations of academic perceptions and practices are rare. Reflections on factors affecting IRC, as well as effective technology for use in IRC are also now particularly vital, due to the outbreak of COVID-19. The aim of this three-round Delphi study, conducted prior to the pandemic, was to explore why and how academics conduct IRC in the field of Education. The results indicate that the benefits of IRC are more relevant than the barriers, and that networking with and learning from others are two of the most important reasons for conducting IRC. Four stages of IRC were identified, alongside a range of influencing factors, which could inform future project management training. Suggestions for institutional IRC policy are provided, as well as considerations for early career researchers., Dades primàries associades a un article publicat a la revista Journal of New Approaches in Educational Research disponible a l'adreça https://doi.org/10.7821/naer.2021.7.614

This document contains the data from the questionnaires carried out with families. This study aimed to explore the emotional competences and cognitive emotion regulation strategies of northern spanish parents and to observe relationships with respect to levels of parental stress and life satisfaction.Results showed positive relationships between some of the adaptative cognitive emotion regulation strategies and emotional competences, and negative relationships for non-adaptative one's. A mediating effect of parental stress was found for emotion awareness, catastrophizing and self-blame on life satisfaction of parents., Dades primàries associades a un article pendent d'avaluació: Priego-Ojeda, Maria., Ros-Morente, Agnes., Filella-Guiu, Gemma., Perez-Escoda, Nuria. (2022).Competences for Emotion Regulation: The Mediating Role of Parental stress on Life Satisfaction. Journal of Children and Family Studies. (Submitted to review)

The file contains the genotypic data of the 138 pigs used for GWAS for intramuscular fat content and fatty acids that passed data quality control criteria, with genotypes coded as 0 (homozygous), 1 (heterozygous), and 2 (opposite homozygous)., Dades primàries associades a un article publicat a la revista Plos One disponible a l'adreça https://doi.org/10.1371/journal.pone.0152496

Mesures del camp de velocitat del vent (3 components), temperatura sònica i de l'aire a alta freqüència (8-10 Hz) separades per fitxers en base temporal cada 30 min., Dades primàries associades a un article publicat a la revista Water Resources Research disponible a l'adreça https://doi.org/10.1029/2018WR022808

Data of three real networks are presented. The objective is to assess the cost reduction achieved when rotation scheduling is applied instead of on-demand scheduling. Demand discharges were calculated using Clement's first formula. For a more complete analysis, the design flow (Qd) was also calculated. The design flow is the flow used to size the network's pipes. As the Clement flow is obtained from a statistical formula, which is based on certain initial hypotheses, it needs to be revised in order to check that the final value obtained is consistent with the different scenarios that could be found within a given network. In the cases of homogeneous plots, the flow within a given section must be a multiple of the assigned discharge (d = 21.43 l/s) because there can only be a whole number of open hydrants (not a fraction). It would not be realistic to give an intermediate flow that is not a multiple of the discharge. The criterion applied to calculate the design flow was that it should be the multiple of the discharge immediately above the Clement flow. In this way, we always consider real flows that are greater than the Clement flows. Discharges under rotation scheduling were calculated assuming that plots within a rotation shared the discharge, so they will never be irrigating at the same time., Dades primàries associades a un article pendent d'avaluació.

The Fuji-SfM dataset includes: (1) a set of 288 colour images and the corresponding annotations (apples segmentation masks) for training instance segmentation neural networks such as Mask-RCNN; (2) a set of 582 images defining a motion sequence of the scene which was used to generate the 3D model of 11 Fuji apple trees containing 1455 apples by using SfM; (3) the 3D point cloud of the scanned scene with the corresponding apple positions ground truth in global coordinates. This data allows the development, training, and test of fruit detection algorithms either based on RGB images, on coloured point clouds or on the combination of both types of data., Dades primàries associades a un article publicat a la revista Computers and Electronics in Agriculture disponible a l'adreça https://doi.org/10.1016/j.compag.2019.105165 i a la revista Data in Brief disponible a l'adreça https://doi.org/10.1016/j.dib.2020.105591

The LFuji-air dataset contains LiDAR based point clouds of 11 Fuji apples trees and the corresponding apples location ground truth. A mobile terrestrial laser scanner (MTLS) comprised of a LiDAR sensor and a real-time kinematics global navigation satellite system was used to acquire the data. The MTLS was mounted on an air-assisted sprayer used to generate different air flow conditions. A total of 8 scans per tree were performed, including scans from different LiDAR sensor positions (multi-view approach) and under different air flow conditions. These variability of the scanning conditions allows to use the LFuji-air dataset not only for training and testing new fruit detection algorithms, but also to study the usefullness of the multi-view approach and the application of forced air flow to reduce the number of fruit oclusions., Dades primàries associades a un article publicat a la revista Computers and Electronics in Agriculture disponible a l'adreça https://doi.org/10.1016/j.compag.2019.105121 i a la revista Data in Brief disponible a l'adreça https://doi.org/10.1016/j.dib.2020.105248, This work was partly funded by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Economy and Competitiveness (project AGL2013-48297-C2-2-R) and the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). The Spanish Ministry of Education is thanked for Mr. J. Gené’s pre-doctoral fellowships (FPU15/03355). The work of Jordi Llorens was supported by the Spanish Ministry of Economy, Industry and Competitiveness through a postdoctoral position named Juan de la Cierva Incorporación (JDCI-2016-29464_N18003). We would also like to thank CONICYT FONDECYT 1171431 and CONICYT FB0008.

The KFuji RGB-DS dataset is composed by 967 multi-modal images of Fuji apples on trees captured using Microsoft Kinect v2 (Microsoft, Redmond, WA, USA). Each image contains information from 3 different modalities: color (RGB), depth (D) and range corrected IR intensity (S). Ground truth fruit locations were manually annotated, labeling a total of 12,839 apples in all the dataset., Dades primàries associades a un article publicat a la revista Computers and Electronics in Agriculture disponible a l'adreça https://doi.org/10.1016/j.compag.2019.05.016 i a la revista Data in Brief disponible a l'adreça https://doi.org/10.1016/j.dib.2019.104289, This work was partly funded by the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya, the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (ERDF) under Grants 2017 SGR 646, AGL2013-48297-C2-2-R and MALEGRA, TEC2016-75976-R. The Spanish Ministry of Education is thanked for Mr. J. Gené's pre-doctoral fellowships (FPU15/03355). We would also like to thank Nufri and Vicens Maquinaria Agrícola S.A. for their support during data acquisition.