Land subsidence associated with overexploitation of aquifers is a hazard that commonly affects large areas worldwide. The Lorca area, located in southeast Spain, has undergone one of the highest subsidence rates in Europe as a direct consequence of long-term aquifer exploitation. Previous studies carried out on the region assumed that the ground deformation retrieved from satellite radar interferometry corresponds only to vertical displacement. Here we report, for the first time, the two- and three-dimensional displacement field over the study area using synthetic aperture radar (SAR) data from Sentinel-1A images and Global Navigation Satellite System (GNSS) observations. By modeling this displacement, we provide new insights on the spatial and temporal evolution of the subsidence processes and on the main governing mechanisms. Additionally, we also demonstrate the importance of knowing both the vertical and horizontal components of the displacement to properly characterize similar hazards. Based on these results, we propose some general guidelines for the sustainable management and monitoring of land subsidence related to anthropogenic activities.

From its introduction in the last decade, affine arithmetic (AA) has shown beneficial properties to speed up the time of computation procedures in a wide variety of areas. In the determination of the optimum set of finite word-lengths of the digital signal processing systems, the use of AA has been recently suggested by several authors, but the existing procedures provide pessimistic results. The aim is to present a novel approach to compute the round-off noise (RON) using AA which is both faster and more accurate than the existing techniques and to justify that this type of computation is restricted to linear time-invariant systems. By a novel definition of AA-based models, this is the first methodology that performs interval-based computation of the RON. The provided comparative results show that the proposed technique is faster than the existing numerical ones with an observed speed-up ranging from 1.6 to 20.48, and that the application of discrete noise models leads to results up to five times more accurate than the traditional estimations.

Atherosclerosis plays a key role in cardiovascular disease in patients with rheumatoid arthritis (RA). Although therapy with TNF-alpha antagonists has resulted in dramatic improvement in the prognosis of RA, its effects on circulatory lipids are unclear. We conducted a systematic review of the literature to summarize the available evidence on lipid profile modification in patients with RA treated with TNF-alpha antagonists, with extensive searches in PubMed, the Cochrane Collaboration database (Central), and SCOPUS. Twenty-four observational studies met the inclusion criteria; 12 included only patients with RA treated with infliximab and three, patients with RA treated with adalimumab. The other nine included a mix of patients with various rheumatic diseases, or receiving one of several TNF-alpha antagonists. Eleven studies found a statistically significant increase in total cholesterol (TC) and high-density lipoprotein (HDL); six of 20 found significant increases in triglycerides (TG). Four of 13 studies found a statistical increase in low-density lipoprotein. No major changes were observed for ApoB/ApoA1 ratios. A small trend to increased TC was observed in patients receiving TNF-alpha antagonists, mostly due to an increase in HDL. There was a small trend to increased TG, and no changes in ApoB/ApoA1 ratio. The clinical impact of these findings is unclear, and further studies are needed to clarify the role of these lipid changes on cardiovascular morbidity in RA.

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A fast and accurate quantization noise estimator aiming at fixed-point implementations of Digital Signal Processing (DSP) algorithms is presented. The estimator enables significant reduction in the computation time required to perform complex wordlength optimizations. The proposed estimator is based on the use of Affine Arithmetic (AA) and it is presented in two versions: (i) a general version suitable for differentiable nonlinear algorithms, and Linear Time-Invariant (LTI) algorithms with and without feedbacks; and (ii) an LTI optimized version. The process relies on the parameterization of the statistical properties of the noise at the output of fixed-point algorithms. Once the output noise is parameterized (i.e., related to the fixed-point formats of the algorithm signals), a fast estimation can be applied throughout the word-length optimization process using as a precision metric the Signal-to-Quantization Noise Ratio (SQNR). The estimator is tested using different LTI filters and transforms, as well as a subset of non-linear operations, such as vector operations, adaptive filters, and a channel equalizer. Fixed-point optimization times are boosted by three orders of magnitude while keeping the average estimation error down to 4%.

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Specifications of data computations may not necessar-

* Autor a quien debe ser dirigida la correspondencia.Recibido Dic. 9, 2014; Aceptado Ene. 20, 2015; Versión final recibida Mar. 9, 2015 Resumen El objetivo del estudio es analizar el proceso de autorregulación del aprendizaje en entornos personales de aprendizaje. El análisis se enfoca en acciones realizadas y logros obtenidos por los estudiantes durante las fases de actuación y de reflexión de este proceso. Se aplicó un cuestionario, tipo escala Likert, a una muestra aleatoria por conglomerados del grado en Educación Primaria de la Universidad de Granada en España. Sobre los datos se realizan análisis descriptivos e inferenciales, también pruebas no paramétricas de correlaciones y de varianzas. Los resultados muestran que las herramientas digitales y los profesores son elementos importantes en el proceso de autorregulación del aprendizaje. En general, la población es exitosa en ambas fases de este proceso, también hay subgrupos de estudiantes que sobresalen por sus logros. Se concluye que el uso adecuado de las herramientas digitales del entorno personal de aprendizaje favorece la autorregulación del aprendizaje en ambas fases. Palabras clave: autorregulación del aprendizaje, entornos personales de aprendizaje, herramientas digitales Self-regulated Learning in Personal Learning Environments on the Grade of Elementary Education, University of Granada, Spain AbstractThe objective of the study is to analyze the process of self-regulation of the learning in personal learning environments. The analysis focuses on actions taken and achievements made of students during the phases of action and self-reflection of this process. A Likert scale type questionnaire was applied to a random cluster sample from the degree in Elementary Education of the University of Granada in Spain. The study performed descriptive and inferential analysis of the data, non-parametric tests of correlations and variances. The results show that digital tools and the teachers are important elements in the process of selfregulated learning. In general, the population is successful in both phases of this process. There are also subgroups of students who stand out for their achievements. It is concluded that proper use of digital tools of personal learning environment favors the self-regulation of the learning process in both phases.