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Combination tones (CTs) generated by the inner ear have been widely investigated in the past, starting from the famous Tartini's “third tone.” Instead, much less attention has been dedicated to the CTs generated by musical instruments. In this paper, the CTs generated by a set of violins of different quality and age have been investigated when playing a selected set of dyads. CTs were found in all of the violins, and the strongest of them occurred at a frequency below the lower note of the dyad. Its amplitude was strongly dependent on violin and dyad played and was greatest in two old Italian violins and decreased down to a minimum in a factory-made violin. All of these findings are well explained by the boosting action of A0, the main air resonance of the violin that correlates well with the strongest CT. A listening test, performed using selected dyads and violins, showed that the differences between dyads with and without CTs were correctly recognized by a group of professional and amateur musicians, suggesting a possible musical significance of the main CT. The results investigating the possible source of violin nonlinearity are also described.

In the context of climate change, the correct management of groundwater, which is strategic for meeting water needs, becomes essential. Groundwater modeling is particularly crucial for the sustainable and efficient management of groundwater. This manuscript provides different types of modeling according to data availability and features of three porous aquifer systems in Italy (Empoli, Magra, and Brenta systems). The models calibrated on robust time series enabled the performing of forecast simulations capable of representing the quantitative and qualitative response to expected climate regimes. For the Empoli aquifer, the process-based models highlighted the system’s ability to mitigate the effects of dry climate conditions thanks to its storage capability. The data-driven models concerning the Brenta foothill aquifer pointed out the high sensitivity of the system to climate extremes, thus suggesting the need for specific water management actions. The integrated data-driven/process-based approach developed for the Magra Valley aquifer remarked that the water quantity and quality effects are tied to certain boundary conditions over dry climate periods. This work shows that, for groundwater modeling, the choice of the suitable approach is mandatory, and it mainly depends on the specific aquifer features that result in different ways to be sensitive to climate. This manuscript also provides a novel outcome involving the integrated approach wherein it is a very efficient tool for forecasting modeling when boundary conditions, which significantly affect the behavior of such systems, are subjected to evolve under expected climate scenarios.

This paper focuses on power-flow equations solutions, based on the Newton-Raphson method. Two major contributions are offered. First, the definition of novel solution variants, resorting to Wirtinger calculus, is attempted. The obtained developments, although original in their formulation, led to already known variants. Despite the impaired originality of the obtained solution, there are significant lessons learned from such an effort. The second major contribution consists of a deep comparison analysis of existing solution strategies, based on complex and real variables, and the Wirtinger based ones, all properly reformulated to allow direct comparison with each other. The goal is to investigate strengths and weaknesses of the addressed techniques in terms of computational effort and convergence rate, which are the most relevant aspects to consider while choosing the approach to employ to solve power-flow equations for a specific power system under study.

The Adriatic region is highly vulnerable to the adverse impacts of climate change. Although attention has been paid to understand the climate change impact and risks over the last decades, the Adriatic community still faces a lack of a common risk assessment. For this reason, ASTERIS project has been financed at the Call for proposal 2017 Priority Axis Safety and resilience of Interregional V Italy-Croatia 2014-2020 Program. To this overall objective, the project will provide two main outputs: i) a map of vulnerability to coastal salinization at the macro-regional scale (Adriatic) based on future scenarios for sea-level rise and the hydrological cycle and ii) best practice and guidelines for the management of vulnerable sites defined though the analysis of representative case studies in Italy and Croatia. Within these general purposes, hydrogeological and geochemical surveys in two specific shallow aquifer systems that develop in the coastal areas of Fano and Ravenna (central-eastern Italy), were carried out. Several periodical campaigns, aimed at measuring water level and physical-chemical parameters by vertical logs in wells or piezometers, were also conducted. Additionally, ground and surface water samples were also collected for chemical and isotopic analyses to define the compositional features and the main geochemical processes affecting the two shallow aquifers. Preliminary investigations suggested that the Ravenna shallow aquifer is already strongly spoiled by a significant seawater intrusion (up to 80 %), whereas at Fano the presence of the saline wedge can be regarded as negligible. This indicates that the aquifer system of Fano can be considered as a good proxy for evaluating and simulating potential processes of saline-fresh water interactions by either the increasing demand of water exploitation and sea level rise due to anthropogenic pressure and climate change, respectively. In order to simulate possible future ingressions of seawater in the aquifer system of Fano, groundwater flow and transport models are currently in progress. These models will be implemented and calibrated according to the hydrogeological and geochemical data collected within the framework of the ASTERIS project. The expected modelled scenarios, obtained through predictive simulations, are of pivotal importance for assessing the possible groundwater response to climate change and for a correct management and protection of water resources, which can be exported to other aquifers system along the Adriatic Sea.

Traditionally, critical infrastructures demand for high dependability, being the services they provide essential to human beings and the society at large. However, more recent attention to cautious usage of energy resources is changing this vision and calls for solutions accounting for appropriate multi-requirements combinations when developing a critical infrastructure. In such a context, analysis supports able to assist the designer in envisioning a satisfactory trade-off among the multi-requirements for the system at hand are highly helpful. In this paper, the focus is on the railway sector and the contribution is a stochastic model-based analysis framework to quantitatively assess trade-offs between dependability indicators and electrical energy consumption incurred by the rail switch heating system.Moving from a preliminary study that concentrated on energy consumption only, the analysis framework has been extended to become a solid support to devise appropriate tuning of the heating policy that guarantees satisfactory trade-offs between dependability and energy consumption. An evaluation campaign in a variety of climate scenarios demonstrates the feasibility and utility of the developed framework.

In this study, geochemical data processing and statistical/geostatistical techniques were coupled to achieve Water Framework Directive goals, collecting useful information from a complex database. Considering the Greater Turin metropolitan area, located in North-Western Italy, chemical data of 135 wells sampled and collected from 2000 to 2018 by the Environmental Protection Agency of Piedmont were analyzed. Both the processes that determine the groundwater chemical composition and the origin and evolution of groundwater were decoded and understood. The presence of two different components in the foothill aquifer system investigated was found. A bicarbonate alkaline earthy type component, linked with different degrees to phenomena of water-rock interaction, and a chlorinated type component related to nitrates, whose effects related to human activities can be recognized. This last component was mapped by using geostatistical techniques to define the most critical zones of the study area. Time series analysis on chlorides and nitrates displayed the presence of statistically significant increasing trends in some areas of the Turin plain. This study shows that the combining of geochemical approach, geostatistical techniques, and time series analysis can be used as reliable tools to understand geochemical processes acting on the system, to identify temporal and spatial hydrochemical variability, as well as to forecast water quality evolution. In this perspective, the multi-disciplinary approach developed in this study represents a reliable methodology for extracting useful information from a complex database and achieving the Water Framework Directive goals.

Railways monitoring and control are currently performed by different heterogeneous vertical systems working in isolation without or with limited cooperation among them. Such configuration, widely adopted in practical deployments today, is in contrast with the integrated vision of systems that are at the foundation of the smart-city concept. In order to overcome the current fractured ecosystem that monitors and controls railways functionalities, the adoption of a novel integrated approach is mandatory to create an all-in-one railway system. To this aim, new IoT-based communication technologies, like wireless or Power Line Communication technologies, are considered the main enablers to integrate in a very rapid and easy manner existing vertical systems. In this work, we analyse the architecture of future railways systems based on a mix of wireless and Power Line Communication technologies. In our analysis, we aim at studying possible failure management strategies on rail-road switches to improve the level of reliability, crucial requirement for systems that demand maximum resiliency as they manage a critical function of the infrastructure. In particular, we propose a set of solutions aimed at detecting and handling network and sensor failures to ensure continuity in the execution of the basic control functions. The proposed approach is evaluated by means of simulations and demonstrated to be effective in ensuring a good level of performance even when failures occur.

FeedForward Deep Neural Networks (DNNs) robustness is a relevant property to study, since it allows to establish whether the classification performed by DNNs is vulnerable to small perturbations in the provided input, and several verification approaches have been developed to assess such robustness degree. Recently, an approach has been introduced to evaluate forward robustness, based on symbolic computations and designed for the ReLU activation function. In this paper, a generalization of such a symbolic approach for the widely adopted LeakyReLU activation function is developed. A preliminary numerical campaign, briefly discussed in the paper, shows interesting results.

Awareness and efforts to moderate energy consumption, desirable from both economical and environmental perspectives, are nowadays increasingly pursued. However, when critical sectors are addressed, energy saving should be cautiously tackled, so to not impair stringent dependability properties such contexts typically require. This is the case of the railway transportation system, which is the critical infrastructure this paper focuses on. For this system category, the attitude has been typically to neglect efficient usage of energy sources, motivated by avoiding to put dependability in danger. The new directives, both at national and international level, are going to change this way of thinking. Our study intends to be a useful support to careful energy consumption. In particular, a refined stochastic modeling framework is offered, tailored to the railroad switch heating system, through which analyses can be performed to understand the sophisticated dynamics between the system (both the cyber and physical components) and the surrounding weather conditions.

Many studies in neuropsychology have highlighted that expert musicians, who started learning music in childhood, present structural differences in their brains with respect to non-musicians. This indicates that early music learning affects the development of the brain. Also, musicians' neuronal activity is different depending on the played instrument and on the expertise. This difference can be analysed by processing electroencephalographic (EEG) signals through Artificial Intelligence models. This paper explores the feasibility to build an automatic model that distinguishes violinists from pianists based only on their brain signals. To this aim, EEG signals of violinists and pianists are recorded while they play classical music pieces and an Artificial Neural Network is trained through a cloud computing platform to build a binary classifier of segments of these signals. Our model has the best classification performance on 20 seconds EEG segments, but this performance depends on the involved musicians' expertise. Also, the brain signals of a cellist are demonstrated to be more similar to violinists' signals than to pianists' signals. In summary, this paper demonstrates that distinctive information is present in the two types of musicians' brain signals, and that this information can be detected even by an automatic model working with a basic EEG equipment.

Many foothill zones in Italy contain aquifer systems of strategic interest for water supplying, especially for drinking purposes (Doveri et al., 2016). The hydrogeological features in these environments generally promote the infiltration of both local rainfall and seepage from stream water originating in mountain catchments. On the other hand, because of their linkage with mountain areas, these systems are characterized by significant sensitivity towards the meteo-climatic variations and changes. To cope with climate change, a high level of knowledge of this type of aquifer should be reached in order to address the water management issues. This work focus on the aquifer system extending in the foothill plain located in the Piedmont region (NW Italy), between the Western Alps and the Torino Hill (Piana et al., 2017). Taking into account previous studies (De Luca et al., 2014 and references therein) and datasets from monitoring activities institutionally performed by the Environmental Protection Agency of Piedmont Region (ARPA Piemonte), the study examined the geological, hydrogeological and hydraulic-hydrodynamic features of the aquifer, as well as the chemistry of groundwater. This comprehensive approach steered the definition of the aquifer system conceptual model as well as the evolution of groundwater quantity and the chemical quality of groundwater. The statistical analysis performed on datasets highlighted some trends over the lasts two decades, both for groundwater quantity and quality. In particular, a significant sensitivity to meteo-climate conditions was pointed out by high confidence trends of piezometric level decrease occurred over both the periods 2004-2008 and 2010-2017, because of the respective rainfall decrease patterns. The rainy year 2009, which interposed itself between the two relatively dry periods, promoted sharp increases in terms of piezometric levels and concentrations of some chemical compounds in groundwater, thus pointing out as the hydrologic extremes can lead to the accumulation of nutrients and salinity in the unsaturated zone of the aquifer and their successive concentrate release in groundwater.

Möbius is well known as a modeling and evaluation environment for performance and dependability indicators. One of Möbius' key features is the modular and compositional approach to model definition and analysis. In particular, the modeler can define submodels using several formalisms and compose them to form the overall model of the system under analysis. The current algorithm for model composition in Möbius revealed performance issues when large systems are considered (such as in the modeling of realistic segments of energy or transportation infrastructures), due to the chosen data flow scheme. In this paper, a new algorithm for the same composition mechanism is proposed to improve efficiency. A case study is also developed to demonstrate the performance enhancements.

Yearly water balance of the Piedmont Alpine zone

Many foothill zones in Italy contain aquifer systems of strategic interest for water supplying, especially for drinking purposes (Doveri et al., 2016). The hydrogeological features in these environments generally promote the infiltration of both local rainfall and stream water originating in mountain catchments. On the other hand, because of their linkage with mountain areas, these systems are characterized by significant sensitivity towards the meteo-climatic variations and changes. Hence, a high level of knowledge of the foothill aquifers should be reached for addressing the water management issues by real technical approaches and management actions. This work focus on the aquifer system extending in the foothill plain located in the Piedmont region (NW Italy), between the Western Alps and the Torino Hill (Piana et al. 2017). This area is of scientific interest, since it represents the hydrogeological "transition zone" between the Western Po Plain and the southern Piedmont Plain aquifer systems (Irace et al., 2010). Furthermore, the interest towards these aquifers is tied to the reliance on their groundwater resource for drinking water supply, which is performed by SMAT (Società Metropolitana Acque Torino). In close cooperation with SMAT, which also co-founded the project, and taking also into account previous studies (De Luca et al., 2014; De Luca and Osella, 2014) and datasets from monitoring activities institutionally performed by the Environmental Protection Agency of Piedmont Region (ARPA Piemonte), the study examined the geological, hydrogeological and hydraulic-hydrodynamic features of the aquifer, as well as the chemistry of groundwater. Furthermore, some preliminary isotopic analyses were performed. The aquifer recharge estimated through a hydrologic balance approach by Brussolo et al. (2018 - in this conference) was also taken into account. This comprehensive approach steered the definition of the aquifer system conceptual model, comprising the kind of rocks hosting groundwater and their hydraulic properties, the arrangement of groundwater flow, the seasonal evolution of groundwater quantity and the chemical quality of groundwater. Furthermore, the statistical analysis performed on datasets from monitoring stations highlighted some trends over decades. The main results can be summarized as follows: - the system consists of a multilayer that has a phreatic aquifer overlying a succession of impermeable and permeable layers, in which groundwater flow generally occurs in confined to semi-confined conditions; -the phreatic aquifer has thicknesses between 30 and 80 m and it is hosted in gravel, sandy gravel and pebbles of fluvial and fluvioglacial origin (Pleistocene-Holocene deposits). The hydraulic conductivity ranges from 5 * 10-4 m/s to 5 * 10-3 m/s; -the confined to semi-confined sub-system mainly develops within the Pliocene continental deposits, which consist of coarse-grained sands and gravels, alternating to peat-rich clayey and silty deposits. The average hydraulic conductivity of this system ranges from 4*10-5 to 4*10-4 m/s; -the aquifer system is fed by infiltration of local rainfall, river seepage and transfers of groundwater that originate in upland zones. The outputs of groundwater is for exploitation by wells and for drainage operated by rivers, in the lower part of the plain. Generally, the groundwater flow of the phreatic aquifer is separated from that of the confined to semi-confined sub-system. Nevertheless, over wide zones the shallow aquifer and the uppermost permeable layers of the deeper system result in continuity (or separated by weak thicknesses of clayey deposits), thus making possible the mixing of groundwater between the two sub-systems. The main groundwater flow paths occur from northwest to southeast and from west to east; -groundwater are mainly of the Ca(Mg)-HCO3 type with a relatively low salinity for both unconfined and confined aquifers. Nevertheless, the phreatic aquifer hosts groundwater with a relatively higher salinity and, in some zones, characterized by increasing of Cl and SO4 contents. Hence, a certain impact from anthropic activities seems to be possible. In this terms the confined to semi-confined sub-system appears effectively more protected, even though the higher salinity and Cl contents observed in a few deeper wells suggest the possibility of connection with the shallower aquifer.

This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models inside the Möbius modeling framework. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, loosely interconnected with each other (as typically encountered in the electrical or transportation sectors). The approach is based on models that define channels shared among replicas, used to exchange the values of each state variable of a replica with the other replicas that need to use them. The goal is to improve the performance of simulation based solvers with respect to the existing state-sharing approach, when employed in the modeling of the addressed class of systems. Simulation results for the time overheads induced by both channel-sharing and state-sharing approaches for different system scenarios are presented and discussed. They confirm the expected gain in efficiency of the proposed channel-sharing approach in the addressed system context.

Diplomazia2 is framed within the program "Science for Diplomacy: Multi-disciplinary Training Program", and it is the result of closer and more mature collaboration between the Directorate General for Cooperation on Development of the Ministry for Foreign Affairs and International Cooperation (MAECI), the Italian Agency for Cooperation on Development (AICS) and the National Research Council (CNR). The implementation of joint projects such as DIPLOMAzia2 highlights the effectiveness of the diplomacy-science partnership as the driving force behind the achievement of relevant goals jointly pursued by the international community.

The groundwater body hosted in the Follonica coastal plain (Grosseto, Italy) is the Italian aquifer system that was chosen for the experimentation of the FREEWAT Platform, a collection of free and open source software tools for water resource management and quantitative and qualitative modeling developed within the EU project Horizon 2020. In consideration of the studies carried out by the Institute of Geosciences and Earth Resources of the Italian National Research Council from 2006 to 2015 for the geological, hydrogeological and geochemical characterization of the 66 regional groundwater bodies (CIS), the Tuscany Region, partner of the project, has entrusted CNR-IGG for the implementation of the numerical model. A conceptual model of the aquifer system was developed by processing and combining all the geological, hydrogeological and geochemical-isotopic data. The supposed hydrostructure was tested and validated through its 3D "solid" construction, defining the geometry and the physical limits of the multi-layered aquifer system and ensuring its coherence and consistency with respect to the other geographical databases. Hydrogeological and geochemical data processing led to identify the aquifer system feeding components, the relationships between surface hydrography and groundwater and the main physical and chemical processes taking place (ion exchange, seawater ingress, etc). On this basis, the development and implementation of the flow model has started, based on the Modflow code. A focus group was organized as part of the project and stakeholders were involved with their active participation to the elaboration of the conceptual model by sharing data and other useful information. This paper describes the methodology used and the results obtained so far.