Diversidad de abejas silvestres en huertas de Madrid, buscando caminos para una transición agroecológica

Farms and its different management practices have substantial effects on biodiversity, with the consequent impact on the supply of certain ecosystem services such us pollination. Wild bees provide pollination services in small scale horticultural farming, which is key element to determine and improve farm production but also to the maintenance of ecosystem´s diversity. In this study we aim to identify which species of wild bees can be found in small horticultural farms in the northern area of Madrid and to analyse how its diversity is influence by agricultural practices and by the elements of the surrounding landscape. In addition, we deepen in the agricultural practices carried out in small scale horticultural production and farmer’s perception about pollination importance. By doing so, we aim to get a perspective of the agroecological transition in Madrid and the management of agroecological practices from farmer´s perspective. To characterize the farms and to obtained information about the agricultural practices we carried out semi-structured interviews. Farmers showed awareness about the importance of pollination and wild bee communities for the development of their crops and other wild plants. Their perception on the effect of agricultural practices on pollinators match with the scientific data, being wild flowers, aromatic plants and the conservation of natural edges the practices that most influences pollinators. Farm management is rather similar within each other since all of them are small horticultural producers located in the same area. In order to quantify the differences within farms, we gave quantitative scores to the agricultural practices measuring impact and time of application. A total of 16 horticultural farms were sample using the pan-trapping method during the flowering period of the horticultural plants to collect wild bees. Surrounding landscape composition was analysing with satellite imagery to identify the different elements present around the farms. In total, 109 wild bee species were identified with individuals from the six bee families present on the Iberian Peninsula. The most predominant genera are Lasioglossum, belonging to the Halictidae family, which are characterized by nesting in soils. The results indicated that the element with most influence on wild bee species richness is sparsely vegetated soil, followed by the presence of forest areas. These areas might correspond to potential areas of nesting sites for wild bees. This thesis aims to contribute to better understanding of the agoecological transition in Madrid and to highlighted the importance of this small scale farming areas to promote biodiversity and landscape diversity

Tan lejos, tan cerca... Actitudes hacia el Estado del Bienestar en Suecia y España

En este artículo se analizan de forma comparada las actitudes hacia el Estado del Bienestar en Suecia y España, distinguiendo entre actitudes hacia la extensión, intensidad, financiación y gestión del mismo. El objetivo de esta comparación es ver hasta qué punto existe relación entre las actitudes hacia el Estado de Bienestar y su nivel de desarrollo; y por tanto, hasta qué punto las actitudes hacia el Estado de Bienestar pueden ser consideradas como una variable explicativa del nivel de desarrollo de los modelos de bienestar.In this paper we analyse comparatively the attitudes towards the Welfare State in Sweden and in Spain. We distinguish between attitudes towards the extension, intensity, financing and private or public management of the WS. The objective is to see wether it exists a relationship between the attitudes towards the WS and the level of development of the WS; and therefore, wether the attitudes towards the WS can be considered a determinant of the level of development of the welfare models

Forecasting high waters at Venice Lagoon using chaotic time series analisys and nonlinear neural netwoks

Time series analysis using nonlinear dynamics systems theory and multilayer neural networks models have been applied to the time sequence of water level data recorded every hour at 'Punta della Salute' from Venice Lagoon during the years 1980-1994. The first method is based on the reconstruction of the state space attractor using time delay embedding vectors and on the characterisation of invariant properties which define its dynamics. The results suggest the existence of a low dimensional chaotic attractor with a Lyapunov dimension, DL, of around 6.6 and a predictability between 8 and 13 hours ahead. Furthermore, once the attractor has been reconstructed it is possible to make predictions by mapping local-neighbourhood to local-neighbourhood in the reconstructed phase space. To compare the prediction results with another nonlinear method, two nonlinear autoregressive models (NAR) based on multilayer feedforward neural networks have been developed. From the study, it can be observed that nonlinear forecasting produces adequate results for the 'normal' dynamic behaviour of the water level of Venice Lagoon, outperforming linear algorithms, however, both methods fail to forecast the 'high water' phenomenon more than 2-3 hours ahead.Publicad

Assessment of downy mildew in grapevine using computer vision and fuzzy logic. Development and validation of a new method

Downy mildew is a major disease of grapevine. Conventional methods for assessing crop diseases are time-consuming and require trained personnel. This work aimed to develop and validate a new method to automatically estimate the severity of downy mildew in grapevine leaves using fuzzy logic and computer vision techniques. Leaf discs of two grapevine varieties were inoculated with Plasmopara viticola and subsequently, RGB images were acquired under indoor conditions. Computer vision techniques were applied for leaf disc location in Petri dishes, image pre-processing and segmentation of pre-processed disc images to separate the pixels representing downy mildew sporulation from the rest of the leaf. Fuzzy logic was applied to improve the segmentation of disc images, rating pixels with a degree of infection according to the intensity of sporulation. To validate the new method, the downy mildew severity was visually evaluated by eleven experts and averaged score was used as the reference value. A coefficient of determination (R2) of 0.87 and a root mean squared error (RMSE) of 7.61 % was observed between the downy mildew severity obtained by the new method and the visual assessment values. Classification of the severity of the infection into three levels was also attempted, achieving an accuracy of 86 % and an F1 score of 0.78. These results indicate that computer vision and fuzzy logic can be used to automatically estimate the severity of downy mildew in grapevine leaves. A new method has been developed and validated to assess the severity of downy mildew in grapevine. The new method can be adapted to assess the severity of other diseases and crops in agriculture.European Commission 828940Spanish Government PID2020-119478GB-I00Universidad de La Rioja 1150/2020 Gobierno de La Rioj

Artificial Intelligence and Novel Sensing Technologies for Assessing Downy Mildew in Grapevine

Plant diseases and pests cause a large loss of world agricultural production. Downy mildew is a major disease in grapevine. Conventional techniques for plant diseases evaluations are time-consuming and require expert personnel. This work investigates novel sensing technologies and artificial intelligence applications for assessing downy mildew in grapevine under laboratory conditions. In our methodology, machine vision is applied to assess downy mildew sporulation, while hyperspectral imaging is used to explore its potential capability towards early detection of this disease. Image analysis applied to RGB leaf disc images is used to estimate downy mildew (Plamopara viticola) severity in grapevine (Vitis vinifera L. cv Tempranillo). A determination coefficient (R2) of 0.76 ** and a root mean square error (RMSE) of 20.53% are observed in the correlation between downy mildew severity by computer vision and expert’s visual assessment. Furthermore, an accuracy of 81% is achieved to detect downy mildew early using hyperspectral images. These results indicate that non-invasive sensing technologies and computer vision can be applied for assessing and quantify sporulation of downy mildew in grapevine leaves. The severity of this key disease is evaluated in grapevine under laboratory conditions. In conclusion, computer vision, hyperspectral imaging and machine learning could be applied for important disease detection in grapevine.Project NoPest (Novel Pesticides for a Sustainable Agriculture

Hominización desde una óptica de género:visibilización de la mujer en la evolución de la especie humana. Una propuesta didáctica para las materias de ciencias

En este trabajo se presenta una propuesta para trabajar la perspectiva de género en los contenidos de varias materias de ciencias en Educación Secundaria. La experiencia, que se ha realizado en dos centros educativos, busca potenciar el espíritu crítico a través del análisis de los procesos de construcción del conocimiento científico y los sesgos quese arrastran en él. También se analiza el papel de la ciencia en la fundamentación de creencias en la sociedad. Para ello, se valoran hipótesis que ya no prevalecen en el mundo científico actual, pero que se mantienen sólidas en la cosmovisión de nuestra sociedad. En concreto se utiliza la perspectiva de género en el tema de la hominización para ver cómo la ciencia es influenciada por los juicios de valor de la sociedad y cómo, a su vez, esta retroalimenta esos juicios de valo

Studying the capacity of cellular encoding to generate feedforward neural network topologies

Proceeding of: IEEE International Joint Conference on Neural Networks, IJCNN 2004, Budapest, 25-29 July 2004Many methods to codify artificial neural networks have been developed to avoid the disadvantages of direct encoding schema, improving the search into the solution's space. A method to analyse how the search space is covered and how are the movements along search process applying genetic operators is needed in order to evaluate the different encoding strategies for multilayer perceptrons (MLP). In this paper, the generative capacity, this is how the search space is covered for a indirect scheme based on cellular systems, is studied. The capacity of the methods to cover the search space (topologies of MLP space) is compared with the direct encoding scheme.Publicad

Generative capacities of cellular automata codification for evolution of NN codification

Proceeding of: International Conference on Artificial Neural Networks. ICANN 2002, Madrid, Spain, August 28-30, 2002Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary computation has been used as a search technique to find appropriate NN architectures. Direct and indirect encoding methods are used to codify the net architecture into the chromosome. A reformulation of an indirect encoding method, based on two bi-dimensional cellular automata, and its generative capacity are presented.Publicad