The Costs of Drought: the Exceptional 2007-2008 Case of Barcelona

35 p.

Respuesta a la sequía de Pinus radiata D. Don y su implicación en los procesos de tolerancia

160 p. (Bibliogr. 141-160)

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Impacts of Climate Change on European Critical Infrastructures: The Case of the Power Sector

23 p.

Identifying social determinants of urban low carbon transitions: the case of energy transition in Bilbao, Basque Country

33 p.

Early response to nanoparticles in the Arabidopsis transcriptome compromises plant defence and root-hair development through salicylic acid signalling

Background: The impact of nano-scaled materials on photosynthetic organisms needs to be evaluated. Plants represent the largest interface between the environment and biosphere, so understanding how nanoparticles affect them is especially relevant for environmental assessments. Nanotoxicology studies in plants allude to quantum size effects and other properties specific of the nano-stage to explain increased toxicity respect to bulk compounds. However, gene expression profiles after exposure to nanoparticles and other sources of environmental stress have not been compared and the impact on plant defence has not been analysed. Results: Arabidopsis plants were exposed to TiO2-nanoparticles, Ag-nanoparticles, and multi-walled carbon nanotubes as well as different sources of biotic (microbial pathogens) or abiotic (saline, drought, or wounding) stresses. Changes in gene expression profiles and plant phenotypic responses were evaluated. Transcriptome analysis shows similarity of expression patterns for all plants exposed to nanoparticles and a low impact on gene expression compared to other stress inducers. Nanoparticle exposure repressed transcriptional responses to microbial pathogens, resulting in increased bacterial colonization during an experimental infection. Inhibition of root hair development and transcriptional patterns characteristic of phosphate starvation response were also observed. The exogenous addition of salicylic acid prevented some nano-specific transcriptional and phenotypic effects, including the reduction in root hair formation and the colonization of distal leaves by bacteria. Conclusions: This study integrates the effect of nanoparticles on gene expression with plant responses to major sources of environmental stress and paves the way to remediate the impact of these potentially damaging compounds through hormonal priming.