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The AMDE project (“Applicazioni di Metodi per Diagnostica Elettromagnetica”, in English “Applied Methods for Electromagnetic Evaluation”) is an Italian two-years national granted research project on electromagnetic non-destructive evaluation. This project involves five different research units located in Italy, about twenty researchers and ten among Ph.D. students and post-doc. Here we focus on the contribution of the AMDE project to the reconstruction of 3D volumetric defects in metallic plates as those used in aeronautical and aerospace industry. In particular, in this work we propose an efficient numerical model for evaluating the field due to volumetric anomalies and an inversion method based on the Total Varia

The aim of the paper is to highlight some of the innovative methodologies, techniques and systems for non-destructive electromagnetic testing, which have been developed in the framework of the AMDE project (Applications of Methods of Diagnostics Electromagnetic) partially funded by the Italian Ministry of University and Research. In particular, we will present the feasibility design of a suitable exciting-receiving coils configuration able to detect long defects by means of eddy-currents. To solve the forward eddy-current problem, advanced analysis tools have been developed and validated. In this paper, we will also introduce the approach for numerical simulations in the detection of the surface defects.

In non destructive testing applications, the typical ill conditioning of the underlaying inverse problem, combined with possible poor accuracy in measurements, can lead to quite low reliability estimates for the desired output. While regularization techniques can help to improve the data processing step, a careful optimization of the excitation and measurement systems reveals critical to improve the overall testing process performance. In this paper, the design of testing system will be formulated by introducing suitable “quality” functions and formulation in terms of Multi-Objective Optimization Problem (MOOP). Some test cases are analyzed to demonstrate possible improvements coming from the optimization of the measurements “quality”.

A novel procedure to identify and correct the field inhomogeneities in Nuclear Magnetic Resonance (NMR) devices is proposed. Instead of local field measurements, the procedure makes only use of the information supplied by the standard output (absorption spectrum) of the device to determine the correction field to be supplied to the magnet. The reconstruction of the actual field map starting from the spectrum is carried out by means of a Neural Network (NN) approach. The inputs of NN are, in turn, the moments of the spectrum or a pattern of features extracted by a wavelet pre-processor. The accuracy achieved in correcting the field is acceptable and the computational burden of the operation phases appears to be smaller with respect to other methods. The nature and shape of the wavelets are particularly suitable for treating the asborption spectra signal. The procedure promises to be a possible alternative tool to the frequently needed routine calibrations of the magnetic field in Nuclear Magnetic Resonance devices.

in Electromagnetic Nondestructive Evaluation (II), R. Albanese et al. (Eds.), IOS Press

The aim of fetal monitoring is to identify fetuses at risk of an adverse outcome based on the ability to understand how the fetus reacts to stress before it becomes compromised. Recent works have shown that the ST waveform of the fetal electrocardiogram (fECG) provides continuous information on the capacity of the fetal heart muscle to respond to the stress of labour. The fECG can be ob- tained by a non-invasive technique that consists in collecting elec- trical signals by some sensors on the body of the mother. Unfortu- nately the fetal heartbeat signal yielded by this recording technique is quite weaker than the mother heartbeat signal, also due to the atten- uation during the propagation caused by the tissues; moreover, many other artifacts are superimposed to the two heartbeats. In this paper we propose a method based on wavelet decomposition and indepen- dent component analysis in order to approximate the real shape of the fECG. We also try to evaluate the ST waveform for fetal monitoring.

The synchronization of physiological signals between persons is a well-known proxy of empathy. However, it is also influenced by physiological and environmental factors that should be discriminated to correctly characterize the empathy component. We discuss a framework to compute synchrony and introduce physynch, an open-source package developed to easily replicate its computational procedures. We adopted physynch to study the synchrony of the electrodermal activity in 61 male-female dyads with different types of relationship: strangers (18 dyads), friends (23 dyads) and lovers (20 dyads). The findings confirm previous results on Heart Rate Variability synchrony and suggest that synchrony is influenced by the type of relationship and is stronger in dyads of strangers. physynch is made available for download and use for researchers interested in measuring physiological synchrony. Accepted version

This study investigates the valence of adults’ implicit associations to typical and atypical infant cues, and the consistency of responses across the different stimuli. 48 non-parent adults (25 females, 23 males) were presented three kinds of infant cues, typical cry (TD-cry), atypical cry (ASD-cry) and infant faces, and their implicit associations were measured by means of the Single Category Implicit Association Test (SC-IAT). Results showed that, independently of gender, the implicit associations to typical and atypical infant cries had the same negative valence, whereas infant faces were implicitly associated to the positive dimension. Moreover, data showed that implicit responses to the different infant cues were not associated. These results suggest that more controlled processes influence the perceptions of atypical infant cry, and confirm the need to investigate individual reactions to infant cues by adopting a multilevel approach.

The respiratory signal can be accurately evaluated by single-channel electrocardiogram (ECG) processing, as shown in recent literature. Indirect methods to derive the respiratory signal from ECG can benefit from a simultaneous study of both respiratory and cardiac activities. These methods lead to major advantages such as low cost, high efficiency, and continuous noninvasive respiratory monitoring. The aim of this paper is to reconstruct the waveform of the respiratory signal by processing single-channel ECG. To achieve these goals, two techniques of decomposition of the ECG signal into suitable bases of functions are proposed, such as the empirical mode decomposition (EMD) and the wavelet analysis. The results highlight the main differences between them in terms of both theoretical foundations, and performance achieved by applying these algorithms to extract the respiratory waveform shape from single-channel ECG are presented. The results also show that both algorithms are able to reconstruct the respiratory waveform, although the EMD is able to break down the original signal without a preselected basis function, as it is necessary for wavelet decomposition. The EMD outperforms the wavelet approach. Some results on experimental data are presented.

With increased accessibility on Internet, Internet addiction is becoming a serious problem, especially among adolescents. They usually do these activities for entertainment, excitement, challenge seeking, or emotional coping. However, both excessive play of games and frequent use of SNSs may lead to certain negative outcomes. Factors that may influence the tendency for adolescents to become dependent are various. Most existing studies on Internet addiction focus primarily on internal and individual factors that may predispose individuals to problematic Internet use, as personality traits. The main aim of this study was to assessing the risk of Internet addiction in a sample of Italian young adults of High School by looking background factors, attitudes, behavioral habits and personality traits. The results indicate that different dimensions of internet addiction can be predicted by a combination of different users’ characteristics. In particular, Agreeableness-Conscientiousness and Extroversion were inversely related to Internet addiction. The results were discussed in terms of prevention, the identification of specific variables associated with Internet addiction allows for targeting individuals who appear to be at risk for developing Internet addiction.

This contribution applies the social judgment based on warmth and competence in the Italian political context (2008 electoral campaign; N = 625), by integrating insights coming from the literature on the Big Two and on the dual cognition theories. It aims at identifying how the evaluations toward leaders and parties (in terms of assigned warmth and competence, and ingroup/outgroup perception) predict the electoral decision-making. Furthermore, we test the hypothesis that the evaluations of the opposite party (group) and leader (group member) differ. The results are discussed considering the relationship between the Big Two and the following social evaluations and behaviors, in terms of intergroup competition and dual cognitive processes, the peculiar Italian political context and its increasing level of political personalization.

In this study, we investigated how a new food label forms explicit and implicit attitudes toward a product, and through which processes, these attitudes influence consumer behaviours. To this aim, 215 adults (85% female) implicitly and explicitly evaluated labels representing two products: water and chocolate. The labels were presented either in basic form or as having one of four additional symbols representing, respectively, the origin of the product, the respect of the environment, the wellness information, and the shelf life. Results showed that the additional symbolic information creates more of a negative implicit impression but more of a positive explicit attitude toward the products than the basic label does. Moreover, the analysis showed that for the chocolate only were both implicit and explicit reactions critical in driving the approach behaviour toward that food. The theoretical implications of these results are discussed.

Visual Evoked Potentials (VEPs) are referred to electrical potentials due to brief visual stimuli which can be recorded from scalp overlying visual cortex. A way to measure VEPs is through encephalogram (EEG). VEPs are very important because they can quantify functional integrity of the optic pathway. Their study allows to detect abnormalities that affect the visual pathways or visual cortex in the brain, and so methods that permit to identify VEPs components in EEG signals must be defined. However, the background activity measured from EEG hides VEPs components because they have a low voltage. So it is necessary to define a robust method to extract features, which best describe these potentials of interest. In this work Empirical Mode Decomposition (EMD) method is used to separate the EEG components and to detect VEPs. EMD decomposes a signal into components named Intrinsic Mode Functions (IFM). The results, obtained from the study of EEG records of a normal person, suggest that IMFs may be used to determine VEPs in EEG and to obtain important information related to brain activity by a time and frequency analysis of IMF components. It is well comparable with the known Wavelet Transform method, but it is characterized from a greater simplicity of implementation because the basis used in the analysis is generated by the same analyzed signal.

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

The release of petroleum liquids in water, such as marine, riverine, and lacustrine basins, is a matter of concern that shoves authorities and experts to adopt technical approaches for preventing damages, monitoring oil content in water and cleaning up environmental aqueous matrices. In this paper, a dedicated system for oil spill detection is presented. The proposed system consists of an optical fiber sensor and an image processing unit useful to steer and optimize the measurement process. An optical fiber-based antenna sensor is used to detect the oil concentration in water. The sensor consists of two slanted optical probes acting as transmitter and receiver, respectively. Both probes are completely immersed into water being analyzed. The sensing approach is based on the measurement of the light coupling level affected by the reflectivity of the oil layer floating on the water surface. The experimental measurement of different types of oil is performed to assess the sensitivity of the developed system. Special attention is put on the image postelaboration useful to derive the characteristics of the oil distribution on the water surface. In this respect, two different image processing techniques are considered: the first one is based on a suitable energy-minimizing spline fitting procedure subject to external constraint forces, whereas a judicious use of the Hough transform is made in the second one.

A neural network model is proposed to treat inverse problems in electromagnetics, which includes wavelet functions to improve local approximation capabilities. This processor couples the advantages of an interpretation of the problem based on "features" to the accuracy derived from using wavelets where local corrections are needed. The combined model allows one to cope with singularities of the mapping and to slightly modify the mapping in real time. The detection and characterization of a circular defect in a conducting plate by using eddy current testing is shown to take advantage from the proposed approach in a test case, when unforeseen disturbances are present.

The optimal design of a set of actual shimming coils for NMR magnets is addressed. The problem is firstly described in the framework of electromagnetic inverse problems and then regularized on the basis of feasibility considerations, in the limit of negligible cross sections. The effects of finite cross section are then introduced, and an assessment of the results is done. Finally, by employing a genetic, global optimisation technique, a broad range search in the parameters space is performed, leading to solutions not foreseen by the studies based on the thin coil assumption.

Subterranean waters are often polluted by industrial and anthropic effluents that are drained in subsoil. To prevent and control pollution, legislations of different developed countries require an online monitoring measurement, especially for detecting organic solvents (chlorinated and unchlorinated ones). Online measurements include both real-time and no real-time measurements. In general, it is difficult to implement real-time measurements in stricto sensu for online acquisitions on aqueous effluents since they need to be processed by a modeling. This research presents an experimental measurement system based on infrared (IR) spectroscopy for aqueous effluents containing hydrocarbons and capable of displaying excellent values of pollutant concentrations even in instable conditions; the system is able to detect pollutants either in laminar or turbulent flow. The results show the possibility of avoiding the use of “Pitot tube” that is employed to create a stagnation point in order to convert kinetic energy into potential one. This conversion allows the transformation of a turbulent flow in a laminar flow making easy measurement of pollutants included in an aqueous effluent. Obviously, “Pitot tube” is also used for other fluid effluents. The obtained results have been compared with those produced by means of sophisticated IR instrumentation for laboratory applications.

An eddy currents testing system for the identification of a single crack may be puzzled in the presence of multiple defects. In this paper we propose a hybrid neuro-fuzzy scheme to deal with the possible presence of two neighboring cracks. The procedure consists of a fuzzy pre-processor which recognizes the number of cracks in the region of interest, i.e. classifies the data into different classes associated with the number of defects. The second part of the procedure is based on an array of classical back-propagation neural networks, each of them specialized for data inversion in each class.

A linear model for feedback control of the plasma position and shape in the International Thermonuclear Experimental Reactor (ITER) is discussed. A model of the poloidal field (PF) system and of the disturbances is first derived. The main task of the control system is to avoid any contact of the hot plasma with the wall during the long duration of the burn phase. For this purpose, the control variables are specified as six gaps between the plasma separatrix and the first wall, including divertor channels. The structure model includes PF coils, vacuum vessel, first wall, backplate, and divertor fins, and it refers to the TAC-4 outline design ITER geometry. A multivariable controller is designed using the optimal linear quadratic approach. The simulation of the closed-loop system shows how the plasma shape is recovered: Step gap variations of 15 cm and poloidal beta drops of 0.2 are considered as disturbances. The performance parameters are voltages and currents in the PF coils and gap recovery time; voltage saturation of the actuators is also taken into account.

The application of a rotating field like that of induction machines is proposed for the eddy current testing of conducting cylindrical structures. This method allows for fast tracking of the position and geometrical parameters of cracks. In order to improve the capability to discriminate the depth of buried cracks, a suitable range of frequencies is considered. The measurement data are processed with a hybrid neuro-fuzzy system. Two artificial neural networks are used, one is specialized for surface cracks and the other one for buried cracks. The fuzzy system is used to perform the switching strategy between the two networks.

We present here some original methodologies for the solution of the direct and the inverse problems in Eddy Current Testing (ECT), developed or improved in the framework of the MADEND (Methods and Applications of Non-destructive Electromagnetic Diagnostic) research project partially funded by the Italian Research Ministry. Of the direct methods, the CARIDDI integral formulation has been tailored specifically for ECT problems, and an original discrete geometric approach of magneto-quasistatics has been developed. In order to validate and compare these formulations, a number of experimental benchmarks have been defined and set up with either inner or outer defects. Methods and techniques for the solution of ill-conditioned inverse problems have also been developed, such as a new non-iterative inversion method for electrical resistance tomography, the transformation from a hyperbolic problem into a parabolic problem and innovative approaches to conductivity distribution identification. In addition, an estimation of the reliability of the ECT results has been performed and, to reduce the Probability of False Indication of the reconstruction, a new stochastic approach has been developed.