Resultados de investigación

Data on seedling emergence and first-year growth of oaks seeded at 45 sites in 16 European countries., Methods are described in the associated paper., This research was funded by grants TED2021-130976B-I00, funded by MICIU/AEI/10.13039/501100011033 and by the European Union Next GenerationEU/PRTR; RESISTRES (C-EXP267-UGR23) from University of Granada/ Junta de Andalucía/ FEDER; and SMART-OAK, funded by the European Union through FORWARDS (Horizon Europe Project No. 101084481) grants to third parties managed by European Forest Institute. The participant network stemmed primarily from the PEN-CAFoRR COST Action (European Cooperation in Science and Technology). The work at each field site was funded by variable sources granted to co-authors. ABL acknowledges mobility grant Salvador de Madariaga (PRX23/00558) and from the Alexander von Humboldt Foundation while writing this manuscript. Funding statements and acknowledgements from the field sites are provided in Appendix S2 of the paper., The file contains the data on seedling emergence and growth from the publication. For the data on soil characteristics, acorn batch quality, remotely-sensed weather, and species-level SLA, see data availability statement in the paper.

This paper is part of the R+D+I “Knowledge Generation” financed by MICIU/AEI /10.13039/501100011033/ and by FEDER, UE., MICIU/AEI /10.13039/501100011033/, FEDER, UE

Dataset with quality and quantity labour indicators and the number of refugees in host Middle Eastern countries (Egypt, Iran, Lebanon, Jordan and Turkiye) from 1991 to 2021. Data are collected from World Bank Open data and the statistics on working poverty by ILOSTAT. It includes: Refugee ratio (as a percentage of the total population of each country); Official development assistance. Quantitative labour market indicators: unemployment rate, labour force, number of own-account workers. Qualitative labour market indicators: distribution of employment by income level in developing countries.

Este archivo incluye una base de datos con los tweets publicados sobre balcones durante el confinamiento domiciliario de 2020, el código utilizado para la extracción de tweets y generación de la base de datos, y el código utilizado para el análisis mediante técnicas de procesamiento natural del lenguaje. Es parte de los resultados del artículo: Mesa-Pedrazas, Á., Nogueras-Zondag, R., & Duque-Calvache, R. (2023). The new town square: Twitter discourses about balconies during the 2020 lockdown in Spain. Cities, 143, 104595. [https://doi.org/10.1016/j.cities.2023.104595], Estos resultados son parte del proyecto Multi-methodological Approach to Residential Behaviour and Everyday Life, MARBEL (PID2020-119569GA-I00). Financiado por el Ministerio de Ciencia e Innovación, Gobierno de España.

Base de datos de la Encuesta de Empleo del Tiempo 2010 y de la Encuesta de Estructura Salarial, En formato Stata. Database of Time Use Survey 2010 (TUS_2010) and Wages Survey (WS_2018). Stata format.

Corresponding author: Dr. Sergio Cantero Chinchilla. sergio.canterochinchilla@bristol.ac.uk // scanteroch@gmail.com Involved institutions: University of Nottingham (UK), University of the Basque Country (ES), Technological Institute of Aragón (ES), University of Granada (ES)., Ultrasonic guided-wave test data taken from a fatigue test experiment over a notched aluminium plate. Data summary.- Ultrasonic guided-wave test data: Frequency of excitation: 300 kHz (radial mode of vibration) Shape: sinusoid of 4 cycles Amplitude: 45 Vpp Sampling frequency: 60 kHz Fatigue test data.- Load type: Tension-Tension (using Instron 8850 servo-hydraulic fatigue testing machine) Minimum load: 1kN Maximum load: 10kN Frequency: 6Hz Number of cycles: 100 000 Specimen information.- Aluminum plate Alloy: QQA250/5 ‘O’ 2024 Dimensions: 245mm x 500mm x 1mm Central notch length: 22.5mm (centered with respect to the test sample centerline and machined using a laser cutting procedure) Further description.- The fatigue test has been performed using a middle tension [M(T)] specimen with a centered crack and loaded in tension using a positive loading ratio. A fatigue pre-cracking procedure was applied to develop a fresh and straight crack front to mitigate the effect of the machined started notch. The detection and monitoring of the crack onset and growth was carried out using two phased-arrays of six piezoelectric wafer active sensors (PWAS), one set as transmitter, the other as receiver. Piezoelectric ceramic disc transducers of 7mm diameter and 0.5mm thickness have been used in this fatigue test. They PWAS were placed symmetrically with regards to the sample centerline and bonded to the aluminum surface using a 3M Scotch-Weld DP490 epoxy adhesive (TradeMarks). File naming convention: “P_AL_S01_BF6.mat” or “P_AL_S01_BF6_XXX.mat” with XXX=1000, 2000, 3000, 100 000; P stands for Plate; AL stands for Aluminum; S01 stands for specimen 01; BF6 stands for Beamforming using 6 transducers; XXX are the number of cycles at which the fatigue test stopped and the ultrasonic guided-wave tests were performed (every 1000 fatigue cycle). Note 1: The file “P_AL_S01_BF6.mat” contains the data with the structure in pristine state. Note 2: The files “P_AL_S01_BF6_XXX.mat” contains the data after XXX fatigue cycles. Further details about the internal data structure of the MAT-files included within the Readme file within the dataset.

Metabolic reprogramming of cancer cells represents an orchestrated network of evolving molecular and functional adaptations during oncogenic progression. In particular, how metabolic reprogramming is orchestrated in breast cancer and its decisive role in the oncogenic process and tumor evolving adaptations are well consolidated at the molecular level. Nevertheless, potential correlations between functional metabolic features and breast cancer clinical classification still represent issues that have not been fully studied to date. Accordingly, we aimed to investigate whether breast cancer cell models representative of each clinical subtype might display different metabolic phenotypes that correlate with current clinical classifications. In the present work, functional metabolic profiling was performed for breast cancer cell models representative of each clinical subtype based on the combination of enzyme inhibitors for key metabolic pathways, and isotope-labeled tracing dynamic analysis. The results indicated the main metabolic phenotypes, so-called ‘metabophenotypes’, in terms of their dependency on glycolytic metabolism or their reliance on mitochondrial oxidative metabolism. The results showed that breast cancer cell subtypes display different metabophenotypes. Importantly, these metabophenotypes are clearly correlated with the current clinical classifications., Funding: This research, including APC charges, was funded by the Spanish Agencia Estatal de Investigación (Ministry of Science and Innovation) and the European Regional Development Fund [grant numbers CTQ2014-56370-R and CTQ2017-85658-R]; the Fundación Ramón Areces; and the initiative Solidaridad Entre Montañas.