Introduction to the study of the trust

Grado en Derech

A hybrid intelligent system for the analysis of atmospheric pollution: a case study in two European regions

The combined application of several soft-computing and statistical techniques is proposed for the characterization of atmospheric conditions in two European regions: Madrid (Spain) and Prague (Czech Republic). The resulting Hybrid Artificial Intelligence System (HAIS) combines projection models for dimensionality reduction and clustering, combining neural and fuzzy paradigms, in a decision support tool. In present article, this proposed HAIS is applied to analyse the air quality in these two geographical regions and get a better understanding of its circumstances and evolution. To do so, real-life data from six data-acquisition stations are analysed. The main pollutants recorded at these stations between 2007 and 2014, their geographical locations and seasonal changes are all studied, in a research that shows how such factors determine variations in air-borne pollutants. Furthermore, neural projections of the clustering results from data on atmospheric pollution are studied

Self-Organizing Maps to Validate Anti-Pollution Policies

This study presents the application of self-organizing maps to air-quality data in order to analyze episodes of high pollution in Madrid (Spain’s capital city). The goal of this work is to explore the dataset and then compare several scenarios with similar atmospheric conditions (periods of high Nitrogen dioxide concentration): some of them when no actions were taken and some when traffic restrictions were imposed. The levels of main pollutants, recorded at these stations for eleven days at four different times from 2015 to 2018, are analyzed in order to determine the effectiveness of the anti-pollution measures. The visualization of trajectories on the self-organizing map let us clearly see the evolution of pollution levels and consequently evaluate the effectiveness of the taken measures, after and during the protocol activation time

La clase Pino-Juniperetea en la provincia de León

Se ha realizado un estudio fitosociológico tanto de los sabinares montanos, como de los enebrales rastreros subalpinos y oromediterraneos, en la provincia de León, describiéndose cuatro nuevas subasociaciones: Juniperetum sabino-thuriferae quercetosum fagineae, Genisto sanabrensis-Juniperetum nanae echinospartetosum iberici y vaccinietosum uliginosi y Vaccinio myrtilli-Juniperetum nanae jasionetosum brevisepalae.In this paper a phytosociological study about montanous savin forets and, subalpine and oromediterranean creeping juniper shrubs in Leon province (NW Spain) is made.Four new subassociations are described: Juniperetum sahino-thunferae quercetosum fagineae, Gen isto sanabrensis-Juniperetum nanae echinospartetosum iberici and vaccinietosum uliginosi and Vaccinio myrtilli-Juniperetum nanae jasionetosumbrevisepalae

On the specificity of avian blood parasites: Revealing specific and generalist relationships between haemosporidians and biting midges

The study of host-parasite relationships involving vector-borne parasites requires understanding interactions between parasites and vectors. The capacity of haemosporidians to infect insects has clear evolutionary consequences for the transmission of diseases. Here, we investigated (i) the associations between blood parasites, biting midges and birds and (ii) the potential specificity between biting midge and haemosporidian haplotypes. A total of 629 parous biting midges Culicoides and 224 wild birds (belonging to seven species) from a locality of central Spain were individually examined for the presence of Haemoproteus and Plasmodium parasites by sequencing a fragment of cytochrome B. Biting midges were identified morphologically and characterized on the basis of a fragment of the cytochrome c oxidase (COI) gene. Overall, 12 Haemoproteus and three Plasmodium haplotypes were isolated and sequenced. Among them, 10 haplotypes were exclusively isolated from biting midges, three haplotypes only from birds and two haplotypes from both biting midges and birds. Biting midge haplotypes showed both specific and generalist relationships with Haemoproteus haplotypes but only generalist relationships with Plasmodium haplotypes. Several C. festivipennis and C. kibunesis haplotypes established significant coevolutionary links with Haemoproteus haplotypes. These results shed light on the specificity of interactions between vectors and blood parasites. © 2011 Blackwell Publishing Ltd.Peer Reviewe

Humidity forecasting in a potato plantation using time-series neural models

It is widely acknowledged that, under the frame of sustainable farming, using the minimum water resources is a relevant requirement. In order to do that, precision irrigation aims at identifying the irrigation needs of plantations and irrigate accordingly. Artificial intelligence is a promising solution in this field as intelligent models are able to learn the soil moisture dynamics in the soil-plant-atmosphere system and then generating appropriate irrigation scheduling. This is a complex task as the phenology of plants and its water demand vary with soil properties and weather conditions. The present research contributes to this challenging task by proposing the application of neural networks in order to learn the time-series evolution of irrigation needs associated to a potato plantation. Several of such models are thoroughly compared, together with different interpolation methods, in order to find the best combination for accurately forecasting water needs. In order to predict the soil water content in a potato field crop, in which soil humidity probes were installed at 15, 30, and 45 cm depth during the whole cycle of a potato crop. This innovative study and its promising results provide with significant contributions to address the problem of predicting and managing groundwater for agricultural use in a sustainable way.Lab-Ferrer (METER Group) and the UBUCOMP research group at the University of Burgos