Nuevas aportaciones al conocimiento de los Alysiinae españoles (Hymenoptera: Braconidae)

Se citen 21 espècies d'Alysiinae de les províncies de València, Terol i Conca, una de les quals és nova per a la fauna espanyola.Twenty one species of Alysiinae in the Spanish provinces of Valencia, Teruel and Cuenca are appointed, one of them being new for the Spanish fauna.Se citan 21 especies de Alysiinae de las provincias de Valencia, Teruel y Cuenca, una de las cuales es nueva para la fauna española

On the trade-off between feature extraction and fine tuning in transfer learning

Transfer learning is the default solution when using deep learning in image-related tasks, like image classification. When a model has been trained in a large and varied enough dataset, it allows to reuse the visual features that it has learnt for tasks that may have limited training data or environments with limited computational resources. In this work we perform an experimental study on feature extraction and fine-tuning, the two most common transfer learning approaches for image classification. We evaluate the trade-offs of performing a hyperparameter search and the subsequent task with both approaches, in relation to performance, environmental footprint, computational and human involved resources. This work shows the cases in which feature extraction or fine tuning are preferable and proposes a series of recommendations of use for transfer learning, with respect to the aforementioned metrics

Economic considerations play only a limited role in explaining support for Catalonian independence, but could be crucial in deciding the final outcome

The Scottish independence referendum saw economic considerations prove decisive, with the Yes campaign never fully convincing the electorate that voting for independence would bring with it greater prosperity. In Catalonia, a similar debate is under way, but this time economic considerations are set to play a smaller role – though they could yet be decisive in deciding whether independence eventually happens, according to Jordi Muñoz and Raül Tormos

Democracy and its advocates must adapt to the Covid-19 pandemic

The COVID-19 pandemic has put much of American life on hold, and efforts to ensure the robustness of US democracy have not been exempt. Fernando Tormos-Aponte and Michael Latner write that, to ensure November’s general election is as free and fair as possible, electoral democracy advocates must now find new ways of exerting policy influence online and to open up virtual spaces to constituents and advocacy groups. Read this article in Spanish/Lee este [...

Una aproximacion al panorama de las publicaciones periódicas literarias mexIcanas (1950-1995)

Sin resume

OBIA for combining LiDAR and multispectral data to characterize forested areas and land cover in a tropical region

International audiencePrioritizing and designing forest restoration strategies requires an adequate survey to inform on the status (degraded or not) of forest types and the human disturbances over a territory. Very High Spatial Resolution (VHSR) remotely sensed data offers valuable information for performing such survey. We present in this study an OBIA methodology for mapping forest types at risk and land cover in a tropical context (Mayotte Island) combining LiDAR data (1 m pixel), VHSR multispectral images (Spot 5 XS 10 m pixel and orthophotos 0.5 m pixel) and ancillary data (existing thematic information). A Digital Canopy Model (DCM) was derived from LiDAR data and additional information was built from the DCM in order to better take into account the horizontal variability of canopy height: max and high Pass filters (3m x 3m kernel size) and Haralick variance texture image (51m x 51m kernel size). OBIA emerges as a suitable framework for exploiting multisource information during segmentation as well as during the classification process. A precise map (84% total accuracy) was obtained informing on (i) surfaces of forest types (defined according to their structure, i.e. canopy height of forest patches for specific type); (ii) degradation (identified in the heterogeneity of canopy height and presence of eroded areas) and (iii) human disturbances. Improvements can be made when discriminating forest types according to their composition (deciduous, evergreen or mixed), in particular by exploiting a more radiometrically homogenous VHSR multispectral image