BUSCADOR RECOLECTA

Project developed by Giovanni Federico (Università di Pisa) and Antonio Tena Junguito (Universidad Carlos III de Madrid). This data base outlines changes in world trade from 1800 to 2016. Dataset: Egypt

Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Bolivia

Ha ido alternando a lo largo de los años el número de cada tipo de ganado, y también el uso (p. ej. las caballerías antes se usaban para trabajo, ahora para paseos). Denominaciones para animales, según sexo y edad., Ao longo dos anos, o número de cada tipo de gado tem alternado, assim como o uso (por exemplo, a cavalaria costumava ser usada para o trabalho, agora para caminhadas). Denominações para animais, de acordo com o sexo e a idade., Over the years, the number of each type of livestock has alternated, and so has the use (e.g. cavalry used to be used for work, now for walks). Denominations for animals, according to sex and age.

Entrevista a informante 1 en Laranjeiras. ¿Como era la vida en la infancia? Malas vías de comunicación y medios de transporte precarios. Juegos infantiles., Como era a vida na infância? Maus canais de comunicação e meios precários de transporte. Jogos Infantis., What was life like in childhood? Bad communication ways and precarious means of transport. Childish games.

En 2019 se realizó el estudio"Medición del Acceso Abierto en las universidades españolas y el CSIC (2014-2018)"con el objetivo de analizar el seguimiento del Acceso Abierto en las instituciones REBIUN, en cumplimiento de la acción "1. Hacer un diagnóstico de la situación del acceso abierto en España y un seguimiento constante de su evolución de forma que la información de que se disponga esté siempre actualizada" del documento"Compromisos de las universidades ante la Open Science"elaborado por el Grupo CRUE sobre Open Science y aprobado por la Asamblea General de la CRUE el 19 de febrero de 2019.
En 2021 se ha procedido a la medición del Acceso Abierto del período 2016-2020 y a realizar la comparativa con el estudio realizado en 2019.

Juegos infantiles. Travesuras. La escuela. Discoteca. Fiestas. Bebían vino en la “boiga” de los padres. Rutina habitual de los jóvenes., Jogos de crianças. Travessuras. A escola. Discoteca. Festas. Bebiam vinho na boiga dos pais. Rotina habitual dos jovens., Children's games. Mischief. The school. Disco. Parties. They drank wine in the parents' "boiga". Usual routine of the young people.

This dataset contains the MATHEMATICA code used to implement the linear stability analysis developed in Anil Kumar et al.

Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Austria-Hungary

Machine learning (ML) algorithms offer quick and accurate predictions of material properties at a low computational cost. In this project, the mechanical properties of multiscale poly(3-hydroxybutyrate) (P3HB)-based nanocomposites reinforced with different concentrations of multiwalled carbon nanotubes (MWCNTs), WS2 nanosheets and sepiolite (SEP) nanoclay have been predicted. The nanocomposites were prepared via solution casting. SEM images revealed that the three nanofillers were homogenously and randomly dispersed into the matrix. A synergistic reinforcement effect was attained, resulting in an unprecedented stiffness improvement of 132% upon addition of 1:2:2 wt% SEP:MWCNTs:WS2. Conversely, the increments in strength were only moderates (up to 13.4%). A beneficial effect in the matrix ductility was also found due to the presence of both nanofillers. Four ML approaches, Recurrent Neural Network (RNN), RNN with Levenberg's algorithm (RNN-LV), decision tree (DT) and Random Forest (RF), were applied. The correlation coefficient (R2), mean absolute error (MAE) and mean square error (MSE) were used as statistical indicators to compare their performance. The developed models represent a powerful tool for the optimization of the mechanical properties in multiscale hybrid polymer nanocomposites, saving time and resources in the experimental characterization process.

Project developed by Christopher Absell (University Gothenburg and Instituto Figuerola) Giovanni Federico (New York University Dubai) and Antonio Tena Junguito (Universidad Carlos III de Madrid and Instituto Figuerola). Dataset: Thailand