Data driven characterization of COVID-19

COVID-19 has caused more than 880.000 victims all over the world (September 2020); despite a large effort of the scientific community and of the governments, it is still a great problem, inducing most of the Nations to adopt restriction to mo-bility, social relations and economic activities. Since the beginning of the pandemic, COVID-19 appeared a rather mysterious virus, for which neither a vaccination nor specific medications exist. In this paper, COVID-19 is characterized by using the available data of total number of infected, healed and dead people to identify the contagion, the removed and the death rates. These values depend on various aspects related to the population characteristics, the general health conditions, the social and economical situations, as well as to other features not yet identified by the scientific community. The COVID-19 situation in Italy is herein explored, showing the great heterogeneity of the virus spread in different zones

Evaluation of the effect of different policies in the containment of epidemic spreads for the COVID-19 case

The paper presents a new mathematical model for the SARS-CoV-2 virus propagation, designed to include all the possible actions to prevent the spread and to help in the healing of infected people. After a discussion on the equilibrium and stability properties of the model, the effects of each different control actions on the evolution of the epidemic spread are analysed, through numerical evaluations for a more intuitive and immediate presentation, showing the consequences on the classes of the population

On Local Observer Design for LQR Problems with Tracking

The paper addresses the problem of an observer design for a nonlinear system for which a linear approach is followed for the control synthesis. The linear context driven by the control design allows to focus the observers design in the class of local, i.e. linear, observers. It is shown that when the control contains an external reference, the solution obtained working with the linear approximation to get local solutions produces non consistent results in terms of local regions of convergence for the system and for the observer. The case of a control law which solves a LQR problem with tracking is addressed and two different approaches with respect to the classical one for the observer design are studied. The results are applied to an epidemic spread control to check the differences in the performances for the two different approaches

Classification of ductile cast iron specimens based on image analysis and support vector machine

The ductile irons discovery in 1948 gave a new lease on life to the cast iron family. In fact, these cast irons are characterized both by a high castability and by high toughness values, combining cast irons and steel good properties. The high mechanical properties (especially ductility) are mainly due to the peculiar graphite elements shape: thanks to the addition of some elements like Mg, Ca, Ce, graphite elements shape can be near to spheres (nodules) instead to lamellae as in "normal" grey cast irons. In this work, the problem of classification of ductile cast irons specimens is addressed; first the nodules present in each specimen are identified determining their morphological shapes. These characteristics are suitable used to extract global features of the specimen. Then it is outlined a procedure to train a classifier based of these properties

Dynamical evolution of COVID-19 in Italy with an evaluation of the size of the asymptomatic infective population

The present work deals with an Ordinary Differential Equation (ODE) model specifically designed to describe the COVID-19 evolution in Italy. The model is particularised on the basis of National data about the infection status of the Italian population to obtain numerical solutions that effectively reproduce the real data. Our epidemic model is a classical SEIR model that incorporates two compartments of infected subpopulations, representing diagnosed and undiagnosed individuals respectively, and an additional quarantine compartment. Possible control actions representing social, political, and medical interventions are also included. The numerical results of the proposed model identification by least square fitting are analysed and commented with special emphasis on the estimation of the number of asymptomatic infective individuals. Our fitting results are in good agreement with the epidemiological data. Short and long-term predictions on the evolution of the disease are also given

Age Based Modelling of SARS-CoV-2 Contagion: The Italian case

The paper deals with the modelling of the COVID-19 spread among people with different age. The model introduced is a simplified version of a full age based one where the division into age based groups of the population is performed only for distinguishing the initial contagion step. An identification procedure is performed on the basis of the data acquired for the Italian case showing that the model can describe and explain the actual differences between the different aged individuals with respect to the possibility to acquire the virus

ACTIVE CONTOUR SEGMENTATION FOR THE IDENTIFICATION OF METALLOGRAPHIC AND MORPHOLOGICAL ELEMENTS OF INTEREST IN DUCTILE CAST IRON

Ductile cast irons are characterized by a wide range of mechanical properties that depend on graphite elements morphology and microstructure properties. Both chemical composition and manufacturing conditions control matrix microstructure, and ferritic, pearlitic, ferritic-pearlitic, martensitic, bainitic, austenitic and austempered ductile irons can be obtained. Considering crack propagation resistance of ductile cast irons, their peculiar behaviour is due to the graphite elements shape, that is approximately spheroidal. Due to their morphology, graphite elements can act as crack arresters: as a consequence ductile cast irons are characterized by high ductility and toughness values and can be used for loading conditions that could be considered as critical for other cast irons types (e.g. fatigue loading conditions). Up to some years ago, microstructure analysis was mainly performed by means of semi-quantitative procedures applied to metallographically prepared specimens, with the characteristics evaluation that was mainly based on the operator expertise. Only recently there has been an increasing interest in numerical procedures of image analysis for quantitative evaluation of materials. In this work the problem of the estimation of the morphological parameters of elements such as graphite nodules, domains of chemical etching and metallic matrix has been taken up by a variational approach of image segmentation by active contours. Considering ductile irons, images obtained by means of a light optical microscope (LOM) on metallographically prepared specimens show both graphite elements (spheroids, nodules, lamaellas etc.) and microstructure elements (ferrite grains, pearlite lamaellas, etc.) and some artefacts due the preparing procedure that should be distinguished by more interesting elements. An automatic identification procedure is here proposed to distinguish the nodules from the metallic matrix and to evaluate the nodules shape parameters of interest and the composition of the metallic matrix (ferrite/pearlite volume fraction)

ACTIVE CONTOUR SEGMENTATION FOR THE IDENTIFICATION OF METALLOGRAPHIC AND MORPHOLOGICAL ELEMENTS OF INTEREST IN DUCTILE CAST IRON

Ductile cast irons are characterized by a wide range of mechanical properties that depend on graphite elements morphology and microstructure properties. Both chemical composition and manufacturing conditions control matrix microstructure, and ferritic, pearlitic, ferritic-pearlitic, martensitic, bainitic, austenitic and austempered ductile irons can be obtained. Considering crack propagation resistance of ductile cast irons, their peculiar behaviour is due to the graphite elements shape, that is approximately spheroidal. Due to their morphology, graphite elements can act as crack arresters: as a consequence ductile cast irons are characterized by high ductility and toughness values and can be used for loading conditions that could be considered as critical for other cast irons types (e.g. fatigue loading conditions). Up to some years ago, microstructure analysis was mainly performed by means of semi-quantitative procedures applied to metallographically prepared specimens, with the characteristics evaluation that was mainly based on the operator expertise. Only recently there has been an increasing interest in numerical procedures of image analysis for quantitative evaluation of materials. In this work the problem of the estimation of the morphological parameters of elements such as graphite nodules, domains of chemical etching and metallic matrix has been taken up by a variational approach of image segmentation by active contours. Considering ductile irons, images obtained by means of a light optical microscope (LOM) on metallographically prepared specimens show both graphite elements (spheroids, nodules, lamaellas etc.) and microstructure elements (ferrite grains, pearlite lamaellas, etc.) and some artefacts due the preparing procedure that should be distinguished by more interesting elements. An automatic identification procedure is here proposed to distinguish the nodules from the metallic matrix and to evaluate the nodules shape parameters of interest and the composition of the metallic matrix (ferrite/pearlite volume fraction)

Enhanced composite plate impact damage detection and characterisation using X-Ray refraction and scattering contrast combined with ultrasonic imaging

Ultrasonic imaging and radiography are widely used in the aerospace industry for non-destructive evaluation of damage in fibre-reinforced composites. Novel phase-based X-ray imaging methods use phase effects occurring in inhomogeneous specimens to extract additional information and achieve improved contrast. Edge Illumination employs a coded aperture system to extract refraction and scattering driven signals in addition to conventional absorption. Comparison with ultrasonic immersion C-scan imaging and with a commercial X-ray CT system for impact damage analysis in a small cross-ply carbon fibre-reinforced plate sample was performed to evaluate the potential of this new technique. The retrieved refraction and scattering signals provide complementary information, revealing previously unavailable insight on the damage extent and scale, not observed in the conventional X-ray absorption and ultrasonic imaging, allowing improved damage characterisation