Resultados de investigación

Samples were obtained during the Schmidt Ocean Institute cruise "Exploring Fronts With Multiple Robots" to the Pacific Ocean in 2018 (https://schmidtocean.org/cruise/exploring_fronts_with_multiple_aerial-surface-underwater-vehicles/). This expedition target the Subtropical Front, located approximately 1,000 nautical miles off the coast of Southern California. A SEABIRD SBE 9 PLUS CTD profiler with sensors for water temperature, salinity, oxygen, fluorescence and turbidity was used during this expedition. CTD profiles were taken within water depths between 300 m and 500 m. In total, 126 CTD casts at different stations were run. The achieved data have been converted using the software SBE Data Processing. Water samples for microplankton analysis were also collected in some of the CTD stations using a multi water sampler (rosette) from the research vessel "Falkor" and concentrated on board in a 0.2 um Sterivex filter. Results from 18S and 16S amplicon sequencing are public available in ENA-EMBL archive with the project accession number PRJEB32783.

The dataset is composed of the RSSI fingerprinting calibration of two malls employing four different smartphones with the random walking survey method. Moreover, the dataset includes validation routes performed with ten smartphones from various brands and labeled with the code of the shops where they were registered. For evaluation purposes, together with the samples, information related to the shopping center like the Euclidean distance between shops is provided. The files are described as follows: -'building.csv’: two rows with the id of mall 1 and mall 2. -‘floor.csv’: there is a row for each of the floors of the two malls. Three floors for mall 1 and two floors for mall 2 -‘zones.csv’: for each zone is indicated the id of the mall and the id floor. There are 69 zones from mall 1 and 124 for mall 2 -‘training.csv’: in this file are registered the ids and the description of the five different calibrations performed (one per smartphone) in each of the malls. -‘training_sample.csv’: each row of the file has the RSSI in dBm recorded during the off-line calibration phase together with the timestamp, channel, and MAC of the AP. -‘route.csv’: the id’s and the description of each of the validation routes are recorded in this file. -‘route_sample.csv’: with a similar structure than the training_sample.csv, the RSSI, timestamp, channel, and MAC acquired during the validation routes are stored in this file. -‘euclidea_distance.csv”: to evaluate the error of the different algorithms, this file recorded the euclidean distance from the center of a shop to each other in meters.

This upload contains data for the article "RF Coil Design for Accurate Parallel Imaging on 13C MRSI using 23Na Sensitivity Profiles" published in Magnetic Resonance in Medicine, https://doi.org/10.1002/mrm.29259. Data are organized with respect to the figures in the article. To read and process the GE MR raw files (p-files) GE software tools are required including Matlab software from the GE MNS Research Pack. For the human data, the raw data are provided in mat-files without header information. All data were processed in Matlab to produce the results presented in the article. Please do not hesitate to reach out, if you are interested in any data processing methods or details, we will be happy to share relevant source code.

Description: Column 1: Longitude (°) Column 2: Latitude (°) Column 3: Crustal thickness, Tc (km) Column 4: Effective elastic thickness, Te (km) Column 5: Te error (km) Column 6: Surface heat flow, Fs (mW/m²) Column 7: Surface heat flow, 1-σ uncertainty (mW/m²) Column 8: Temperature at the base of the crust, Tcb (K) If you use the crustal thickness model in your work, please cite: Jiménez-Díaz, A., Ruiz, J., Kirby, J.F., Romeo, I., Tejero, R., Capote, R., 2015. Lithospheric structure of Venus from gravity and topography. Icarus 260, 215–231. https://doi.org/10.1016/j.icarus.2015.07.020 If you use the effective elastic thickness model in your work, please cite: Jiménez-Díaz, A., Ruiz, J., Kirby, J.F., Romeo, I., Tejero, R., Capote, R., 2015. Lithospheric structure of Venus from gravity and topography. Icarus 260, 215–231. https://doi.org/10.1016/j.icarus.2015.07.020 Ruiz, J., Jiménez-Díaz, A., Egea-González, I., Romeo, I., Kirby, J.F., Audet, P., 2024. Heat loss and internal dynamics of Venus from global surface heat flow estimates. arXiv:2401.06558. https://doi.org/10.48550/arXiv.2401.06558

Data set associated with the published article entitled: Mineralogy, Geochemistry and Environmental Hazards of Different Types of Mining Waste from a Former Mediterranean Metal Mining Area

Earthworm community metrics data collected during the years 2019 and 2020 from organically and conventionally managed wheat fields (188 fields in total) in nine pedo-climatic zones of Europe, together with associated site information on climate, soil properties and agricultural management of the fields.

This dataset includes the data obtained during the installation of a camera system and development of a LSPIV methodology to determine the velocities of runoff generated in the BLOCK rainfall simulator located at the Universidade da Coruña. The dataset consists of raw and processed images and surface velocity maps obtained during the assessment of the full process. This data will help to improve and assess imaging techniques in urban environments with the presence of realistic rain, and test new preprocessing and postprocessing methods to optimize the different processes. This dataset is a result from the Joint Research Activity 3 (WP8, Improving Resilience and Sustainability in Urban Drainage solutions), Task 8.1.1. (Development of Scalable Hydrodynamic Performance Protocols.) within Co-UDlabs project, funded under the European Union s Horizon 2020 research and innovation programme under grant agreement No 101008626.