Modelling of last hypothesis of climate change impacts on water resources in Sierra de las Cabras aquifer (Southern Spain)

Having models that reflect the reality of a system operation becomes critical to the effec-tive management of water resources in a watershed, especially considering the different scenes of climate change predicted for the Mediterranean regions by the Intergovernmen-tal Panel on Climate Change (IPCC). The fifth Assessment Report of IPCC (AR5) esti-mates an increase in average temperatures and a precipitation decrease between 10 and 20% for Mediterranean region which could generate drought events in the study area. The present research tries to determinate the potential impacts that climate change may have on water resources. The Sacramento model has been used to model the water resources of an inertial aquifer, Sierra de las Cabras. In turn, IPCC forecasts of climate change for the study area (Mediterranean region) have been simulated taking into account the degree as-sessing of affection to the water resources opposite to eventual episodes of drought, and the social and environmental implications that will result have been also determined.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Chaotic gas bubble oscillations in a viscoelastic fluid

Regular and chaotic radial oscillations of an acoustically driven gas bubble in a viscoelastic fluid have been theoretically analyzed. For parameter values usually found in diagnostic ultrasound period-doubling routes to chaos have been identified. Thresholds values of the external pressure amplitude for a first bifurcation in terms of the elasticity and the shear viscosity of the host fluid have also been evaluated. Les oscillations radiales, régulières ou chaotiques, d’une bulle de gaz au sein d’un fluide viscoélastique et soumise à l’action d’un champ acoustique sont analysées théoriquement. Pour des valeurs des paramètres qui sont normalement rencontrées dans le diagnostic médical, des chemins vers le chaos par doublement de la période ont été identifiés. Les valeurs limites pour la première bifurcation en fonction de l’élasticité et de la viscosité du fluide, ont été aussi déterminées

Gevrey expansions of hypergeometric integrals II

We study integral representations of the Gevrey series solutions of irregular hypergeometric systems under certain assumptions. We prove that, for such systems, any Gevrey series solution, along a coordinate hyperplane of its singular support, is the asymptotic expansion of a holomorphic solution given by a carefully chosen integral representation.Comment: 27 pages, 2 figure

Coupled mantle dripping and lateral dragging controlling the lithosphere structure of the NW-Moroccan margin and the Atlas Mountains: A numerical experiment

Recent studies integrating gravity, geoid, surface heat flow, elevation and seismic data indicate a prominent lithospheric mantle thickening beneath the NW-Moroccan margin (LAB >200 km-depth) followed by thinning beneath the Atlas Domain (LAB about 80 km-depth). Such unusual configuration has been explained by the combination of mantle underthrusting due to oblique Africa-Eurasia convergence together with viscous dripping fed by asymmetric lateral mantle dragging, requiring a strong crust-mantle decoupling. In the present work we examine the physical conditions under which the proposed asymmetric mantle drip and drag mechanism can reproduce this lithospheric configuration. We also analyse the influence of varying the kinematic boundary conditions as well as the mantle viscosity and the initial lithosphere geometry. Results indicate that the proposed drip-drag mechanism is dynamically feasible and only requires a lateral variation of the lithospheric strength. The further evolution of the gravitational instability can become either in convective removal of the lithospheric mantle, mantle delamination, or subduction initiation. The model reproduces the main trends of the present-day lithospheric geometry across the NW-Moroccan margin and the Atlas Mountains, the characteristic time of the observed vertical movements, the amplitude and rates of uplift in the Atlas Mountains and offers an explanation to the Miocene to Pliocene volcanism. An abnormal constant tectonic subsidence rate in the margin is predicted. (C) 2013 Elsevier B.V. All rights reserved.Peer ReviewedPostprint (author's final draft

Load-independent characterization of trade-off fronts for operational amplifiers

Abstract—In emerging design methodologies for analog integrated circuits, the use of performance trade-off fronts, also known as Pareto fronts, is a keystone to overcome the limitations of the traditional top-down methodologies. However, most techniques reported so far to generate the front neglect the effect of the surrounding circuitry (such as the output load impedance) on the Pareto-front, thereby making it only valid for the context where the front was generated. This strongly limits its use in hierarchical analog synthesis because of the heavy dependence of key performances on the surrounding circuitry, but, more importantly, because this circuitry remains unknown until the synthesis process. We will address this problem by proposing a new technique to generate the trade-off fronts that is independent of the load that the circuit has to drive. This idea is exploited for a commonly used circuit, the operational amplifier, and experimental results show that this is a promising approach to solve the issue

Spike-based control monitoring and analysis with Address Event Representation

Neuromorphic engineering tries to mimic biological information processing. Address-Event Representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER to the robot control, monitoring and measuring the spike activity inside the robot. The mobile robot is controlled by the AER-Robot tool, and the AER information is sent to a PC using the USBAERmini2 interface.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors

Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.Ministerio de Economía y Competitividad TEC2016-77785-

CCharPPI web server: computational characterization of protein–protein interactions from structure

The atomic structures of protein–protein interactions are central to understanding their role in biological systems, and a wide variety of biophysical functions and potentials have been developed for their characterization and the construction of predictive models. These tools are scattered across a multitude of stand-alone programs, and are often available only as model parameters requiring reimplementation. This acts as a significant barrier to their widespread adoption. CCharPPI integrates many of these tools into a single web server. It calculates up to 108 parameters, including models of electrostatics, desolvation and hydrogen bonding, as well as interface packing and complementarity scores, empirical potentials at various resolutions, docking potentials and composite scoring functions.The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Unions Seventh Framework Programme (FP7/2007- 2013) under REA grant agreement PIEF-GA-2012-327899 and grant BIO2013-48213-R from Spanish Ministry of Economy and Competitiveness.Peer ReviewedPostprint (published version