Finite element modeling of ground deformation and gravity field at Mt. Etna

An elastic 3-D axi-symmetric model based on Finite Element Method (FEM) is proposed to compute ground deformation and gravity changes caused by overpressure sources in volcanic areas. The numerical computations are focused on the modeling of a complex description of Mt Etna in order to evaluate the effect of topography, medium heterogeneities and source geometries. Both ground deformation and gravity changes are investigated by solving a coupled numerical problem considering a simplified ground surface profile and a multi-layered crustal structure inferred from seismic tomography. The role of the source geometry is also explored taking into account spherical and ellipsoidal volumetric sources. The comparison between numerical results and those predicted by analytical solutions disclosed significant discrepancies. These differences constrain the applicability of simple spherical source and homogeneous half-space hypotheses, which are usually implicitly assumed when analytical solutions are applied

An Improved Solver for the M/EEG Forward Problem

Noninvasive investigation of the brain activity via electroencephalography (EEG) and magnetoencephalography (MEG) involves a typical inverse problem whose solution process requires an accurate and fast forward solver. We propose the Method of Fundamental Solutions (MFS) as a truly meshfree alternative to the Boundary Element Method (BEM) for solving the M/EEG forward problem. The solution of the forward problem is obtained, via the Method of Particular Solutions (MPS), by numerically solving a set of coupled boundary value problems for the 3D Laplace equation. Numerical accuracy and computational load are investigated for spherical geometries and comparisons with a state-of-the-art BEM solver shows that the proposed method is competitive

IL METODO DELLE SOLUZIONI FONDAMENTALI PER LA SOLUZIONE DEL PROBLEMA DIRETTO M/EEG

The research already started on the mesh-free solution of the M / EEG direct problem has led to the development of a solver based on the method of fundamental solutions (MFS, method of fundamental solutions) able to manage the physical-geometric complexity of realistic models of the head more efficiently than traditional

Integrated inversion of ground deformation and magnetic data at Etna volcano using a genetic algorithm technique

Geodetic and magnetic investigations have been playing an increasingly important role in studies on Mt. Etna eruptive processes. During ascent, magma interacts with surrounding rocks and fluids, and inevitably crustal deformation and disturbances in the local magnetic field are produced. These effects are generally interpreted separately from each other and consistency of interpretations obtained from different methods is qualitatively checked only a posteriori. In order to make the estimation of source parameters more robust we propose an integrated inversion from deformation and magnetic data that leads to the best possible understanding of the underlying geophysical process. The inversion problem was formulated following a global optimization approach based on the use of genetic algorithms. The proposed modeling inversion technique was applied on field data sets recorded during the onset of the 2002-2003 Etna flank eruption. The deformation pattern and the magnetic anomalies were consistent with a piezomagnetic effect caused by a dyke intrusion propagating along the NE direction

STIMA DEL POTENZIALE ELETTRICO IN tDCS CON APPROCCIO MESHLESS INNOVATIVO

Transcranial DC stimulation (transcranial Direct Current Stimulation, tDCS) is a non-invasive technique aimed at modifying neuronal activity for the purpose therapeutic and / or for the improvement of mental performance. A continuous current of entity modest (below the threshold of perception) is injected into the brain via electrodes placed on the scalp surface to produce changes in long-term cortical activity. Despite the increasing use of this and other similar techniques, and the relevant ones applications - for example in the field of neuropsychological rehabilitation - their impact on neuronal activity is not yet fully known, mainly due to the difficulty of predict the spatial distribution of the current within the brain, and to determine the optimal position and size of the electrodes

The HOTSAT volcano monitoring system based on combined use of SEVIRI and MODIS multispectral data

Spaceborne remote sensing of high-temperature volcanic features offers an excellent opportunity to monitor the onset and development of new eruptive activity. To provide a basis for real-time response during eruptive events, we designed and developed the volcano monitoring system that we call HOTSAT. This multiplatform system can elaborate both Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, and it is here applied to the monitoring of the Etna volcano. The main advantage of this approach is that the different features of both of these sensors can be used. It can be refreshed every 15 min due to the high frequency of the SEVIRI acquisition, and it can detect smaller and/or less intense thermal anomalies through the MODIS data. The system consists of data preprocessing, detection of volcano hotspots, and radiative power estimation. To locate thermal anomalies, a new contextual algorithm is introduced that takes advantage of both the spectral and spatial comparison methods. The derivation of the radiative power is carried out at all ‘hot’ pixels using the middle infrared radiance technique. The whole processing chain was tested during the 2008 Etna eruption. The results show the robustness of the system after it detected the lava fountain that occurred on May 10 through the SEVIRI data, and the very beginning of the eruption on May 13 through the MODIS data analysis

ADVANCED BIO-ELECTROMAGNETIC NUMERICAL MODELLING AND ICT FOR HUMAN BRAIN RESEARCH

Functional imaging is used in the research area neurological, neurophysiology and cognitive psychology, for the diagnosis of diseases metabolic and for the detection of thin / squamous lesions (eg Alzheimer's disease) and for the development of neural interfaces (brain-computer interfaces - BCI)

Inverse modeling in geophysical applications

The interpretation of the potential ¯eld data is an useful tool that allows for both investigating the subsurface structures and providing a quantitative evalu- ation of the geophysical process preceding and accompanying period of volcanic unrest. Potential ¯eld inversion problem are required to combine forward mod- els with appropriate optimization algorithms and automatically ¯nd the best set of parameters that well matches the available observations. Indeed, investi- gations on the mathematical equations to be inverted, have revealed that these models are ill-posed and highly non-linear. Numerical methods for modeling potential ¯eld observations are proposed and applied on real dataset