Resultados de investigación

If you download all files into a directory on your system and open the .Rmd file in Rstudio, you can knit to execute the code and regenerate all figures from the raw data files (also included), This is a summary of the workflow for carrying out diversity and structure analysis from Lucena-Perez et al. 2023. The starting point are bam files of Lynx pardinus and Lynx lynx data mapped to the Lynx pardinus genome. The following analyses are documented here: Generation of a PCA; Admixture analysis; Genomic diversity analysis, Peer reviewed

Description of individual and population codes used in the different analyses and genomic datasets: Coccinella_p9r05m5_10000.str: Input file used to perform genetic clustering (STRUCTURE) and principal component (PCA) analyses including all genotyped individuals for the taxon Coccinella septempunctata; Andrena_p6r05m5_10000.str: Input file used to perform genetic clustering (STRUCTURE) and principal component (PCA) analyses including all genotyped individuals for the taxon Andrena flavipes; Andrena_p6r05m5_ExcludingSpain_10000.str: Input file used to perform genetic clustering (STRUCTURE) and principal component (PCA) analyses for the taxon Andrena flavipes excluding the populations from Spain; Coccinella_p9r05m5.arp: Input file used to perform ARLEQUIN analyses for the taxon Coccinella septempunctata; Andrena_p6r05m5.arp: Input file used to perform ARLEQUIN analyses for the taxon Andrena flavipes; FASTSIMCOAL2.zip: This ZIP folder contains input files for demographic analyses in FASTSIMCOAL2., SHOWCASing synergies between agriculture, biodiversity and Ecosystem services to help farmers capitalising on native biodiversity, European Commission, Peer reviewed

This is version is the one submitted for publication along Reilly et al. paper., Peer reviewed

Addtion of Maxime_Eeraerts_etal_Vacinnium_corymbosum_USA_2021.ods (2023-05-07), Peer reviewed

Independent files with detailed numeric analysis of precipitation evolution and trends for different countries in the Mediterranean region., Peer reviewed

Ultrasound imaging plays an important role in screening early detection and breast cancer diagnosis. However, speckle noise affects medical ultrasound images and degrades the visual radiologic evaluation, which generally causes several difficulties in identifying the malignant and benignant regions. Denoising is an important step in preprocessing medical images, because it restores the maximum details preserving edges and all information of the images, achieving successful accuracy in anomalies classification. To reduce the speckle noise and retain image features well, we proposed two GANs models to breast ultrasound speckle denoising as preprocessing image, (i) Conditional GAN and (ii) WGAN. The better denoising image quality was measured by peak signal to noise ratio (PSNR) and structural similarity index (SSIM). The experimental analysis clearly shows that the CGAN method achieves better visual image quality in terms of PSNR=38.18 dB and SSIM= 0.96 with respect to WGAN model (PSNR=33.0068 dB and SSIM=0.91) on the small Ultrasound training datasets. Thus, we conclude that GANs can help in denoising ultrasound medical imaging, and as a future work these data can be used as computer system input for image segmentation and classification, reducing the hand-dependence and helping radiologists to improve breast cancer detection., Ministerio de Educación y Formación Profesional PID2019-107790RB-C22 MCIN/AEI/10.13039/501100011033., Peer reviewed

Project: Integrated Assessment of Atlantic Marine Ecosystems in Space and Time (iAtlantic)., Dendrophyllia_Bycatch * Latitude: 43.398822 * Longitude: -8.700804 * Date/Time: 2019-09-11T00:00:00 * Elevation: -150.0 m * Location: Atlantic Ocean * Method/Device: Accidental bycatch sampling., El dataset se puede consultar y descargar en el siguiente enlace https://doi.org/10.1594/PANGAEA.963072, A 9-month aquarium experiment with the cold-water Dendrophyllia cornigera was conducted to investigate the single and combined effects of warming, acidification and deoxygenation on its ecophysiological response. The experiment took place at the Aquarium finisterrae (A Coruña, Spain) between 2022-05-06 and 2023-02-24. Treatment values for each parameter (current in situ vs. climate change) were: 12 °C and 15 °C (temperature); ~7.99 and 7.69 (pH); ~8.63 mg/L and 6.45 mg/L (dissolved oxygen concentration). A total of eight treatments (with 3 replicates each, 5 L aquaria) were set up. Concentrations of dissolved nitrates, nitrite, silicate and phosphate were analysed from each experimental aquaria after one, six and nine months. Inorganic nutrient concentrations in seawater were determined using a SFA (Segmented Flow Autoanalyzer) (Aminot & Kérouel, 2007) with a SEAL Analytical QuAAtro analyzer using established colorimetric methods (Hydes et al. 2010 & Becker et al. 2020). RMNs (Reference Material for nutrients in seawater) with different concentration ranges were used for quality control and accuracy of our analysis. Low nutrient seawater (surface seawater filtered and aged) is also used to control low nutrient concentrations., Horizon 2020 (H2020), grant/award no. 818123: Integrated Assessment of Atlantic Marine Ecosystems in Space and Time, Peer reviewed

Linear infrastructure represent a barrier to movement for many species, reducing the connectivity of the landscapes in which they reside. Of all linear infrastructure, roads and fences are two of the most ubiquitous, and are understood to reduce landscape connectivity for wildlife. However, what is often neglected consideration is a holistic approach of modelling the effects of multiple types of linear infrastructure simultaneously. Few studies have examined this, typically assessing the impacts of a singular kind of infrastructure on landscape connectivity. Therefore, the aim of this study is to address the relative importance of considering multiple kinds of linear infrastructure in landscape connectivity modelling. We utilised presence data of red deer Cervus elaphus and wild boar Sus scrofa in Doñana Biosphere Reserve (Spain) to generate a sequential approach of scenarios of landscape connectivity; firstly only with environmental variables, secondly with roads as the sole infrastructure, thirdly with the addition of fences, and finally with the further addition of fences and wildlife road-crossing structures. We found that the connectivity of the landscape was greatly affected by the addition of fences and wildlife road-crossing structures in both species, with fences in particular causing considerable alterations to estimated movement pathways. Our finding impresses a need to consider multiple different types of linear infrastructure when modelling landscape connectivity to enable a more realistic view of wildlife movement and inform mitigation and conservation measures more accurately., HORIZON EUROPE European Innovation Council : 101060429, European Union’s Horizon Europe Research and Innovation Programme; Government of the United Kingdom , Turing Scheme; Fundação para a Ciência e Tecnologia : 2022.01773.CEECIND, CEECIND; European Commission : LIFEWATCH-2019-09-CSIC-13; European Commission : POPE2014-2020; Ministry of Economy, Industry and Competitiveness : RYC2021-033192-I, Ramón y Cajal Program; Ministerio de Ciencia e Innovación : IJC2019-039662-I, Juan de la Cierva Incorporación Program, Peer reviewed

Genome assembly and gene prediction of Rhizopus stolonifer BLUCD01 version 1., Peer reviewed

Quality controlled temperature data at daily resolution at CTS, HRR, HYS, NVC, RSI and SGV and the most relevant codes for data processing used in: García-Pereira, F., González-Rouco, J. F., Schmid, T., Melo-Aguilar, C, Vegas-Cañas, C., Steinert, N. J., Roldán-Gómez, P. J., Cuesta-Valero, F. J., García-García, A., Beltrami, H., and de Vrese, H.: "Thermodynamic and hydrological drivers of the subsurface thermal regime in Central Spain". Earth Surf. Dynam., submitted, 2023., All data can be also freely obtained for research from the original data sources, GuMNet (https://www.ucm.es/gumnet/) and AEMET (https://www.aemet.es/en/datos_abiertos). Further details of the code are available upon request to the corresponding author (Félix García-Pereira, felgar03@ucm.es)., Peer reviewed