Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Stability, viscous dissipation and local thermal non-equilibrium in fluid saturated porous media

In this thesis, the field of study related to the stability analysis of fluid saturated porous media is investigated. In particular the contribution of the viscous heating to the onset of convective instability in the flow through ducts is analysed. In order to evaluate the contribution of the viscous dissipation, different geometries, different models describing the balance equations and different boundary conditions are used. Moreover, the local thermal non-equilibrium model is used to study the evolution of the temperature differences between the fluid and the solid matrix in a thermal boundary layer problem. On studying the onset of instability, different techniques for eigenvalue problems has been used. Analytical solutions, asymptotic analyses and numerical solutions by means of original and commercial codes are carried out.

Numerical simulations of magma chamber dynamics at Campi Flegrei, and associated seismicity, deformation and gravity changes

Understanding the complex relationships between quantities measured by volcanic monitoring network and shallow magma processes is a crucial headway for the comprehension of volcanic processes and a more realistic evaluation of the associated hazard. This question is very relevant at Campi Flegrei, a volcanic quiescent caldera immediately north-west of Napoli (Italy). The system activity shows a high fumarole release and periodic ground slow movement (bradyseism) with high seismicity. This activity, with the high people density and the presence of military and industrial buildings, makes Campi Flegrei one of the areas with higher volcanic hazard in the world. In such a context my thesis has been focused on magma dynamics due to the refilling of shallow magma chambers, and on the geophysical signals detectable by seismic, deformative and gravimetric monitoring networks that are associated with this phenomenologies. Indeed, the refilling of magma chambers is a process frequently occurring just before a volcanic eruption; therefore, the faculty of identifying this dynamics by means of recorded signal analysis is important to evaluate the short term volcanic hazard. The space-time evolution of dynamics due to injection of new magma in the magma chamber has been studied performing numerical simulations with, and implementing additional features in, the code GALES (Longo et al., 2006), recently developed and still on the upgrade at the Istituto Nazionale di Geofisica e Vulcanologia in Pisa (Italy). GALES is a finite element code based on a physico-mathematical two dimensional, transient model able to treat fluids as multiphase homogeneous mixtures, compressible to incompressible. The fundamental equations of mass, momentum and energy balance are discretised both in time and space using the Galerkin Least-Squares and discontinuity-capturing stabilisation technique. The physical properties of the mixture are computed as a function of local conditions of magma composition, pressure and temperature.The model features enable to study a broad range of phenomenologies characterizing pre and sin-eruptive magma dynamics in a wide domain from the volcanic crater to deep magma feeding zones. The study of displacement field associated with the simulated fluid dynamics has been carried out with a numerical code developed by the Geophysical group at the University College Dublin (O’Brien and Bean, 2004b), with whom we started a very profitable collaboration. In this code, the seismic wave propagation in heterogeneous media with free surface (e.g. the Earth’s surface) is simulated using a discrete elastic lattice where particle interactions are controlled by the Hooke’s law. This method allows to consider medium heterogeneities and complex topography. The initial and boundary conditions for the simulations have been defined within a coordinate project (INGV-DPC 2004-06 V3_2 “Research on active volcanoes, precursors, scenarios, hazard and risk - Campi Flegrei”), to which this thesis contributes, and many researchers experienced on Campi Flegrei in volcanological, seismic, petrological, geochemical fields, etc. collaborate. Numerical simulations of magma and rock dynamis have been coupled as described in the thesis. The first part of the thesis consists of a parametric study aimed at understanding the eect of the presence in magma of carbon dioxide in magma in the convection dynamics. Indeed, the presence of this volatile was relevant in many Campi Flegrei eruptions, including some eruptions commonly considered as reference for a future activity of this volcano. A set of simulations considering an elliptical magma chamber, compositionally uniform, refilled from below by a magma with volatile content equal or dierent from that of the resident magma has been performed. To do this, a multicomponent non-ideal magma saturation model (Papale et al., 2006) that considers the simultaneous presence of CO2 and H2O, has been implemented in GALES. Results show that the presence of CO2 in the incoming magma increases its buoyancy force promoting convection ad mixing. The simulated dynamics produce pressure transients with frequency and amplitude in the sensitivity range of modern geophysical monitoring networks such as the one installed at Campi Flegrei . In the second part, simulations more related with the Campi Flegrei volcanic system have been performed. The simulated system has been defined on the basis of conditions consistent with the bulk of knowledge of Campi Flegrei and in particular of the Agnano-Monte Spina eruption (4100 B.P.), commonly considered as reference for a future high intensity eruption in this area. The magmatic system has been modelled as a long dyke refilling a small shallow magma chamber; magmas with trachytic and phonolitic composition and variable volatile content of H2O and CO2 have been considered. The simulations have been carried out changing the condition of magma injection, the system configuration (magma chamber geometry, dyke size) and the resident and refilling magma composition and volatile content, in order to study the influence of these factors on the simulated dynamics. Simulation results allow to follow each step of the gas-rich magma ascent in the denser magma, highlighting the details of magma convection and mixing. In particular, the presence of more CO2 in the deep magma results in more ecient and faster dynamics. Through this simulations the variation of the gravimetric field has been determined. Afterward, the space-time distribution of stress resulting from numerical simulations have been used as boundary conditions for the simulations of the displacement field imposed by the magmatic dynamics on rocks. The properties of the simulated domain (rock density, P and S wave velocities) have been based on data from literature on active and passive tomographic experiments, obtained through a collaboration with A. Zollo at the Dept. of Physics of the Federici II Univeristy in Napoli. The elasto-dynamics simulations allow to determine the variations of the space-time distribution of deformation and the seismic signal associated with the studied magmatic dynamics. In particular, results show that these dynamics induce deformations similar to those measured at Campi Flegrei and seismic signals with energies concentrated on the typical frequency bands observed in volcanic areas. The present work shows that an approach based on the solution of equations describing the physics of processes within a magmatic fluid and the surrounding rock system is able to recognise and describe the relationships between geophysical signals detectable on the surface and deep magma dynamics. Therefore, the results suggest that the combined study of geophysical data and informations from numerical simulations can allow in a near future a more ecient evaluation of the short term volcanic hazard.

Multilevel Domain Decomposition Algorithms for Monolithic Fluid-Structure Interaction Problems with Application to Haemodynamics

Finite element techniques for solving the problem of fluid-structure interaction of an elastic solid material in a laminar incompressible viscous flow are described. The mathematical problem consists of the Navier-Stokes equations in the Arbitrary Lagrangian-Eulerian formulation coupled with a non-linear structure model, considering the problem as one continuum. The coupling between the structure and the fluid is enforced inside a monolithic framework which computes simultaneously for the fluid and the structure unknowns within a unique solver. We used the well-known Crouzeix-Raviart finite element pair for discretization in space and the method of lines for discretization in time. A stability result using the Backward-Euler time-stepping scheme for both fluid and solid part and the finite element method for the space discretization has been proved. The resulting linear system has been solved by multilevel domain decomposition techniques. Our strategy is to solve several local subproblems over subdomain patches using the Schur-complement or GMRES smoother within a multigrid iterative solver. For validation and evaluation of the accuracy of the proposed methodology, we present corresponding results for a set of two FSI benchmark configurations which describe the self-induced elastic deformation of a beam attached to a cylinder in a laminar channel flow, allowing stationary as well as periodically oscillating deformations, and for a benchmark proposed by COMSOL multiphysics where a narrow vertical structure attached to the bottom wall of a channel bends under the force due to both viscous drag and pressure. Then, as an example of fluid-structure interaction in biomedical problems, we considered the academic numerical test which consists in simulating the pressure wave propagation through a straight compliant vessel. All the tests show the applicability and the numerical efficiency of our approach to both two-dimensional and three-dimensional problems.

Concepts and methods for efficient decentralized learning in federated settings

Deep Neural Networks (DNNs) have revolutionized a wide range of applications beyond traditional machine learning and artificial intelligence fields, e.g., computer vision, healthcare, natural language processing and others. At the same time, edge devices have become central in our society, generating an unprecedented amount of data which could be used to train data-hungry models such as DNNs. However, the potentially sensitive or confidential nature of gathered data poses privacy concerns when storing and processing them in centralized locations. To this purpose, decentralized learning decouples model training from the need of directly accessing raw data, by alternating on-device training and periodic communications. The ability of distilling knowledge from decentralized data, however, comes at the cost of facing more challenging learning settings, such as coping with heterogeneous hardware and network connectivity, statistical diversity of data, and ensuring verifiable privacy guarantees. This Thesis proposes an extensive overview of decentralized learning literature, including a novel taxonomy and a detailed description of the most relevant system-level contributions in the related literature for privacy, communication efficiency, data and system heterogeneity, and poisoning defense. Next, this Thesis presents the design of an original solution to tackle communication efficiency and system heterogeneity, and empirically evaluates it on federated settings. For communication efficiency, an original method, specifically designed for Convolutional Neural Networks, is also described and evaluated against the state-of-the-art. Furthermore, this Thesis provides an in-depth review of recently proposed methods to tackle the performance degradation introduced by data heterogeneity, followed by empirical evaluations on challenging data distributions, highlighting strengths and possible weaknesses of the considered solutions. Finally, this Thesis presents a novel perspective on the usage of Knowledge Distillation as a mean for optimizing decentralized learning systems in settings characterized by data heterogeneity or system heterogeneity. Our vision on relevant future research directions close the manuscript.

Governing algorithms in the big data era for balancing new digital rights - designing GDPR compliant and trustworthy XAI systems

This thesis investigates the legal, ethical, technical, and psychological issues of general data processing and artificial intelligence practices and the explainability of AI systems. It consists of two main parts. In the initial section, we provide a comprehensive overview of the big data processing ecosystem and the main challenges we face today. We then evaluate the GDPR’s data privacy framework in the European Union. The Trustworthy AI Framework proposed by the EU’s High-Level Expert Group on AI (AI HLEG) is examined in detail. The ethical principles for the foundation and realization of Trustworthy AI are analyzed along with the assessment list prepared by the AI HLEG. Then, we list the main big data challenges the European researchers and institutions identified and provide a literature review on the technical and organizational measures to address these challenges. A quantitative analysis is conducted on the identified big data challenges and the measures to address them, which leads to practical recommendations for better data processing and AI practices in the EU. In the subsequent part, we concentrate on the explainability of AI systems. We clarify the terminology and list the goals aimed at the explainability of AI systems. We identify the reasons for the explainability-accuracy trade-off and how we can address it. We conduct a comparative cognitive analysis between human reasoning and machine-generated explanations with the aim of understanding how explainable AI can contribute to human reasoning. We then focus on the technical and legal responses to remedy the explainability problem. In this part, GDPR’s right to explanation framework and safeguards are analyzed in-depth with their contribution to the realization of Trustworthy AI. Then, we analyze the explanation techniques applicable at different stages of machine learning and propose several recommendations in chronological order to develop GDPR-compliant and Trustworthy XAI systems.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

Aspetti innovativi per la valutazione e la misura della porosità nei materiali dell'edilizia antica e moderna. La geometria frattale della porosità

New concepts on porosity appraisal in ancient and modern construction materials. The role of Fractal Geometry on porosity characterization and transport phenomena. This work studied the potential of Fractal Geometry to the characterization of porous materials. Besides the descriptive aspects of the pore size distribution, the fractal dimensions have led to the development of rational relations for the prediction of permeability coefficients to fluid and heat transfer. The research considered natural materials used in historical buildings (rock and earth) as well as currently employed materials as hydraulic cement and technologically advanced materials such as silicon carbide or YSZ ceramics. The experimental results of porosity derived from the techniques of mercury intrusion and from the image analysis. Data elaboration was carried out according to established procedures of Fractal Geometry. It was found that certain classes of materials are clearly fractal and respond to simple patterns such as Sierpinski and Menger models. In several cases, however, the fractal character is not recognised because the microstructure of the material is based on different phases at different dimensional scales, and in consequence the “fractal dimensions” calculated from porosimetric data do not come within the standard range (less than 3). Using different type and numbers of fractal units is possible, however, to obtain “virtual” microstructures that have the fraction of voids and pore size distribution equivalent with the experimental ones for almost any material. Thus it was possible to take the expressions for the permeability and the thermal conduction which does not require empirical “constants”, these expressions have also provided values that are generally in agreement with the experimental available data. More problematic has been the fractal discussion of the geometry of the rupture of the material subjected to mechanical stress both external and internal applied. The results achieved on these issues are qualitative and prone to future studies. Keywords: Materials, Microstructure, Porosity, Fractal Geometry, Permeability, Thermal conduction, Mechanical strength.

Meccanismi di formazione dei tubi di lava

Two analytical models are proposed to describe two different mechanisms of lava tubes formation. A first model is introduced to describe the development of a solid crust in the central region of the channel, and the formation of a tube when crust widens until it reaches the leve\'es. The Newtonian assumption is considered and the steady state Navier- Stokes equation in a rectangular conduit is solved. A constant heat flux density assigned at the upper flow surface resumes the combined effects of two thermal processes: radiation and convection into the atmosphere. Advective terms are also included, by the introduction of velocity into the expression of temperature. Velocity is calculated as an average value over the channel width, so that lateral variations of temperature are neglected. As long as the upper flow surface cools, a solid layer develops, described as a plastic body, having a resistance to shear deformation. If the applied shear stress exceeds this resistance, crust breaks, otherwise, solid fragments present at the flow surface can weld together forming a continuous roof, as it happens in the sidewall flow regions. Variations of channel width, ground slope and effusion rate are analyzed, as parameters that strongly affect the shear stress values. Crust growing is favored when the channel widens, and tube formation is possible when the ground slope or the effusion rate reduce. A comparison of results is successfully made with data obtained from the analysis of pictures of actual flows. The second model describes the formation of a stable, well defined crust along both channel sides, their growing towards the center and their welding to form the tube roof. The fluid motion is described as in the model above. Thermal budget takes into account conduction into the atmosphere, and advection is included considering the velocity depending both on depth and channel width. The solidified crust has a non uniform thickness along the channel width. Stresses acting on the crust are calculated using the equations of the elastic thin plate, pinned at its ends. The model allows to calculate the distance where crust thickness is able to resist the drag of the underlying fluid and to sustain its weight by itself, and the level of the fluid can lower below the tube roof. Viscosity and thermal conductivity have been experimentally investigated through the use of a rotational viscosimeter. Analyzing samples coming from Mount Etna (2002) the following results have been obtained: the fluid is Newtonian and the thermal conductivity is constant in a range of temperature above the liquidus. For lower temperature, the fluid becomes non homogeneous, and the used experimental techniques are not able to detect any properties, because measurements are not reproducible.

Letteratura postmoderna e comunicazione pubblicitaria, problemi teorici e analisi testuali

Premise: In the literary works of our anthropological and cultural imagination, the various languages and the different discursive practices are not necessarily quoted, expressly alluded to or declared through clear expressive mechanisms; instead, they rather constitute a substratum, a background, now consolidated, which with irony and intertextuality shines through the thematic and formal elements of each text. The various contaminations, hybridizations and promptings that we find in the expressive forms, the rhetorical procedures and the linguistic and thematic choices of post-modern literary texts are shaped as fluid and familiar categories. Exchanges and passages are no longer only allowed but also inevitable; the post-modern imagination is made up of an agglomeration of discourses that are no longer really separable, built up from texts that blend and quote one another, composing, each with its own specificities, the great family of the cultural products of our social scenario. A literary work, therefore, is not only a whole phenomenon, delimited hic et nunc by a beginning and an ending, but is a fragment of that complex, dense and boundless network that is given by the continual interrelations between human forms of communication and symbolization. The research hypothesis: A vision is delineated of comparative literature as a discipline attentive to the social contexts in which texts take shape and move and to the media-type consistency that literary phenomena inevitably take on. Hence literature is seen as an open systematicity that chooses to be contaminated by other languages and other discursive practices of an imagination that is more than ever polymorphic and irregular. Inside this interpretative framework the aim is to focus the analysis on the relationship that postmodern literature establishes with advertising discourse. On one side post-modern literature is inserted in the world of communication, loudly asserting the blending and reciprocal contamination of literary modes with media ones, absorbing their languages and signification practices, translating them now into thematic nuclei, motifs and sub-motifs and now into formal expedients and new narrative choices; on the other side advertising is chosen as a signification practice of the media universe, which since the 1960s has actively contributed to shaping the dynamics of our socio-cultural scenarios, in terms which are just as important as those of other discursive practices. Advertising has always been a form of communication and symbolization that draws on the collective imagination – myths, actors and values – turning them into specific narrative programs for its own texts. Hence the aim is to interpret and analyze this relationship both from a strictly thematic perspective – and therefore trying to understand what literature speaks about when it speaks about advertising, and seeking advertising quotations in post-modern fiction – and from a formal perspective, with a search for parallels and discordances between the rhetorical procedures, the languages and the verifiable stylistic choices in the texts of the two different signification practices. The analysis method chosen, for the purpose of constructive multiplication of the perspectives, aims to approach the analytical processes of semiotics, applying, when possible, the instruments of the latter, in order to highlight the thematic and formal relationships between literature and advertising. The corpus: The corpus of the literary texts is made up of various novels and, although attention is focused on the post-modern period, there will also be ineludible quotations from essential authors that with their works prompted various reflections: H. De Balzac, Zola, Fitzgerald, Joyce, Calvino, etc… However, the analysis focuses the corpus on three authors: Don DeLillo, Martin Amis and Aldo Nove, and in particular the followings novels: “Americana” (1971) and “Underworld” (1999) by Don DeLillo, “Money” (1984) by Martin Amis and “Woobinda and other stories without a happy ending” (1996) and “Superwoobinda” (1998) by Aldo Nove. The corpus selection is restricted to these novels for two fundamental reasons: 1. assuming parameters of spatio-temporal evaluation, the texts are representative of different socio-cultural contexts and collective imaginations (from the masterly glimpses of American life by DeLillo, to the examples of contemporary Italian life by Nove, down to the English imagination of Amis) and of different historical moments (the 1970s of DeLillo’s Americana, the 1980s of Amis, down to the 1990s of Nove, decades often used as criteria of division of postmodernism into phases); 2. adopting a perspective of strictly thematic analysis, as mentioned in the research hypothesis, the variations and the constants in the novels (thematic nuclei, topoi, images and narrative developments) frequently speak of advertising and inside the narrative plot they affirm various expressions and realizations of it: value ones, thematic ones, textual ones, urban ones, etc… In these novels the themes and the processes of signification of advertising discourse pervade time, space and the relationships that the narrator character builds around him. We are looking at “particle-characters” whose endless facets attest the influence and contamination of advertising in a large part of the narrative developments of the plot: on everyday life, on the processes of acquisition and encoding of the reality, on ideological and cultural baggage, on the relationships and interchanges with the other characters, etc… Often the characters are victims of the implacable consequentiality of the advertising mechanism, since the latter gets the upper hand over the usual processes of communication, which are overwhelmed by it, wittingly or unwittingly (for example: disturbing openings in which the protagonist kills his or her parents on the basis of a spot, former advertisers that live life codifying it through the commercial mechanisms of products, sons and daughters of advertisers that as children instead of playing outside for whole nights saw tapes of spots.) Hence the analysis arises from the text and aims to show how much the developments and the narrative plots of the novels encode, elaborate and recount the myths, the values and the narrative programs of advertising discourse, transforming them into novel components in their own right. And also starting from the text a socio-cultural reference context is delineated, a collective imagination that is different, now geographically, now historically, and from comparison between them the aim is to deduce the constants, the similarities and the variations in the relationship between literature and advertising.

Impiego di cellule staminali in terapia veterinaria

Over the past few years, in veterinary medicine there has been an increased interest in understanding the biology of mesenchymal stem cells (MSCs). This interest comes from their potential clinical use especially in wound repair, tissue engineering and application in therapeutics fields, including regenerative surgery. MSCs can be isolated directly from bone marrow aspirates, adipose tissue, umbilical cord and various foetal tissues. In this study, mesenchymal stem cells were isolated from equine bone marrow, adipose tissue, cord blood, Wharton’s Jelly and, for the first time, amniotic fluid. All these cell lines underwent in vitro differentiation in chondrocytes, osteocytes and adipocytes. After molecular characterization, cells resulted positive for mesenchymal markers such as CD90, CD105, CD44 and negative for CD45, CD14, CD34 and CD73. Adipose tissue and bone marrow mesenchymal stem cells were successfully applied in the treatment of tendinitis in race horses. Furthermore, for the first time in the horse, skin wounds of septicemic foal, were treated applying amniotic stem cells. Finally, results never reported have been obtained in the present study, isolating mesenchymal stem cells from domestic cat foetal fluid and membranes. All cell lines underwent in vitro differentiation and expressed mesenchymal molecular markers.

Applicazioni cliniche e sperimentali dell’ecografia toracica in pneumologia: la diagnostica precoce delle patologie pleuropolmonari

Lung ultrasound use is increasing in respiratory medicine thanks to its development in the latest years. Actually it allows to study diseases of the chest wall (traumas, infections, neoplasms), diaphragm (paralysis, ipokinesis), pleura (effusions, pneumothorax, thickenings, neoplasms) and lung parenchyma (consolidations, interstitial syndromes, peripheral lesions). One of the most useful application of chest ultrasound is the evaluation of effusions. However, no standardized approach for ultrasound-guided thoracenthesis is available. Our study showed that our usual ultrasonographic landmark (“V-point”) could be a standard site to perform thoracenthesis: in 45 thoracenthesis no pneumothorax occurred, drainage was always successful at first attempt. Values of maximum thickness at V-point and drained fluid volume showed a significative correlation. Proteins concentration of ultrasound patterns of effusions (anechoic, ipoechoic, moving echoic spots, dense moving spots, hyperechoic) were compared to those of the macroscopic features of fluids showing connection between light-yellow fluid and echoic moving spots pattern and between ipoechoic/dense moving spots and cloudy-yellow/serum-haematic fluids. These observations suggest that ultrasound could predict chemical-physical features of effusions. Lung ultrasound provides useful information about many disease of the lung, but actually there is not useful in obstructive bronchial diseases. Analysing diaphragmatic kinetics using M-mode through transhepatic scan we described a similarity between diaphragm excursion during an expiratory forced maneuver and the volume/time curve of spirometry. This allowed us to identify the M-mode Index of Obstruction (MIO), an ultrasound-analogue of FEV1/VC. We observed MIO values of normal subjects (9) and obstructed patients (9) comparing the two groups. FEV1/VC and MIO showed a significant correlation suggesting that MIO may be affected by airways obstruction; MIO values were significatively different between normal and obstructed so that it could identify an obstructive syndrome. The data show that it is possible to suspect the presence of obstructive syndrome of the airways using ultrasonography of the diaphragm.