Attivita' fisica adattata nella riabilitazione post-ictus: Risultati al follow-up di 12 mesi

L’ictus è un importante problema di salute pubblica, è causa di morte e disabilità nella popolazione anziana. La necessità di strategie di prevenzione secondaria e terziaria per migliorare il funzionamento post-ictus e prevenire o ritardare altre condizioni disabilitanti, ha portato l’Italia a sviluppare un intervento di Attività Fisica Adattata (AFA) per l’ictus, che permettesse di migliorare gli esiti della riabilitazione. Obiettivo dello studio è di valutare se l’AFA unita all’Educazione Terapeutica (ET), rispetto al trattamento riabilitativo standard, migliora il funzionamento e la qualità di vita in pazienti con ictus. Studio clinico non randomizzato, in cui sono stati valutati 229 pazienti in riabilitazione post-ictus, 126 nel gruppo sperimentale (AFA+ET) e 103 nel gruppo di controllo. I pazienti sono stati valutati al baseline, a 4 e a 12 mesi di follow-up. Le misure di esito sono il cambiamento a 4 mesi di follow-up (che corrisponde a 2 mesi post-intervento nel gruppo sperimentale) di: distanza percorsa, Berg Balance Scale, Short Physical Performance Battery, e Motricity Index. Le variabili misurate a 4 e a 12 mesi di follow-up sono: Barthel Index, Geriatric Depression Scale, SF-12 e Caregiver Strain Index. La distanza percorsa, la performance fisica, l’equilibrio e il punteggio della componente fisica della qualità di vita sono migliorate a 4 mesi nel gruppo AFA+ET e rimasti stabili nel gruppo di controllo. A 12 mesi di follow-up, il gruppo AFA+ET ottiene un cambiamento maggiore, rispetto al gruppo di controllo, nell’abilità di svolgimento delle attività giornaliere e nella qualità di vita. Infine il gruppo AFA+ET riporta, nell’ultimo anno, un minor numero di fratture e minor ricorso a visite riabilitative rispetto al gruppo di controllo. I risultati confermano che l’AFA+ET è efficace nel migliorare le condizioni cliniche di pazienti con ictus e che gli effetti, soprattutto sulla riabilitazione fisica, sono mantenuti anche a lungo termine.

Physical and mineralogical changes of Hungarian monumental stones exposed to different conditions: stone-testing in-situ and under laboratory conditions

The Székesfehérvár Ruin Garden is a unique assemblage of monuments belonging to the cultural heritage of Hungary due to its important role in the Middle Ages as the coronation and burial church of the Kings of the Hungarian Christian Kingdom. It has been nominated for “National Monument” and as a consequence, its protection in the present and future is required. Moreover, it was reconstructed and expanded several times throughout Hungarian history. By a quick overview of the current state of the monument, the presence of several lithotypes can be found among the remained building and decorative stones. Therefore, the research related to the materials is crucial not only for the conservation of that specific monument but also for other historic structures in Central Europe. The current research is divided in three main parts: i) description of lithologies and their provenance, ii) physical properties testing of historic material and iii) durability tests of analogous stones obtained from active quarries. The survey of the National Monument of Székesfehérvár, focuses on the historical importance and the architecture of the monument, the different construction periods, the identification of the different building stones and their distribution in the remaining parts of the monument and it also included provenance analyses. The second one was the in situ and laboratory testing of physical properties of historic material. As a final phase samples were taken from local quarries with similar physical and mineralogical characteristics to the ones used in the monument. The three studied lithologies are: fine oolitic limestone, a coarse oolitic limestone and a red compact limestone. These stones were used for rock mechanical and durability tests under laboratory conditions. The following techniques were used: a) in-situ: Schmidt Hammer Values, moisture content measurements, DRMS, mapping (construction ages, lithotypes, weathering forms) b) laboratory: petrographic analysis, XRD, determination of real density by means of helium pycnometer and bulk density by means of mercury pycnometer, pore size distribution by mercury intrusion porosimetry and by nitrogen adsorption, water absorption, determination of open porosity, DRMS, frost resistance, ultrasonic pulse velocity test, uniaxial compressive strength test and dynamic modulus of elasticity. The results show that initial uniaxial compressive strength is not necessarily a clear indicator of the stone durability. Bedding and other lithological heterogeneities can influence the strength and durability of individual specimens. In addition, long-term behaviour is influenced by exposure conditions, fabric and, especially, the pore size distribution of each sample. Therefore, a statistic evaluation of the results is highly recommended and they should be evaluated in combination with other investigations on internal structure and micro-scale heterogeneities of the material, such as petrographic observation, ultrasound pulse velocity and porosimetry. Laboratory tests used to estimate the durability of natural stone may give a good guidance to its short-term performance but they should not be taken as an ultimate indication of the long-term behaviour of the stone. The interdisciplinary study of the results confirms that stones in the monument show deterioration in terms of mineralogy, fabric and physical properties in comparison with quarried stones. Moreover stone-testing proves compatibility between quarried and historical stones. Good correlation is observed between the non-destructive-techniques and laboratory tests results which allow us to minimize sampling and assessing the condition of the materials. Concluding, this research can contribute to the diagnostic knowledge for further studies that are needed in order to evaluate the effect of recent and future protective measures.

Performance evaluation of detectors for digital radiography

To date the hospital radiological workflow is completing a transition from analog to digital technology. Since the X-rays digital detection technologies have become mature, hospitals are trading on the natural devices turnover to replace the conventional screen film devices with digital ones. The transition process is complex and involves not just the equipment replacement but also new arrangements for image transmission, display (and reporting) and storage. This work is focused on 2D digital detector’s characterization with a concern to specific clinical application; the systems features linked to the image quality are analyzed to assess the clinical performances, the conversion efficiency, and the minimum dose necessary to get an acceptable image. The first section overviews the digital detector technologies focusing on the recent and promising technological developments. The second section contains a description of the characterization methods considered in this thesis categorized in physical, psychophysical and clinical; theory, models and procedures are described as well. The third section contains a set of characterizations performed on new equipments that appears to be some of the most advanced technologies available to date. The fourth section deals with some procedures and schemes employed for quality assurance programs.

Physical models for numerical simulation of Si-based nanoscale FETs and sensors

To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.

Development and performance assessment of a Plasma Focus electron beam generator for Intra-Operative Radiation Therapy

The Plasma Focus is a device designed to generate a plasma sheet between two coaxial electrodes by means of a high voltage difference. The plasma is then driven to collapse into a “pinch”, where thermonuclear conditions prevail. During the “pinch phase” charged particles are emitted, with two main components: an ion beam peaked forward and an electron beam directed backward. The electron beam emitted backward by Plasma Focus devices is being investigated as a radiation source for medical applications, using it to produce x-rays by interaction with appropriate targets (through bremsstrahlung and characteristic emission). A dedicated Plasma Focus device, named PFMA-3 (Plasma Focus for Medical Applications number 3), has been designed, put in operation and tested by the research groups of the Universities of Bologna and Ferrara. The very high dose rate (several gray per discharge, in less than 1 µs) is a peculiarity of this device that has to be investigated, as it might modify the relative biological effectiveness (RBE). Aim of this Ph.D. project was to investigate the main physical properties of the low-energy x-ray beams produced by a Plasma Focus device and their potential medical applications to IORT treatments. It was necessary to develop the optimal geometrical configuration; to evaluate the x-rays produced and their dose deposited; to estimate the energy electron spectrum produced in the “pinch phase”; to study an optimal target for the conversion of the x-rays; to conduct simulations to study the physics involved; and in order to evaluate the radio-biological features of the beam, cell holders had to be developed for both irradiations and cell growth conditions.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Study of the effect of minor compounds on the oxidative stability and physical properties of bulk oil, oil-in-water emulsion, and food emulsions

Minor components are of particular interest due to their antioxidant and biological properties. Various classes of lipophilic minor components (plant sterols (PS) and α-tocopherol) were selected as they are widely used in the food industry. A Fast GC-MS method for PS analysis in functional dairy products was set up. The analytical performance and significant reduction of the analysis time and consumables, demonstrated that Fast GC-MS could be suitable for the PS analysis in functional dairy products. Due to their chemical structure, PS can undergo oxidation, which could be greatly impacted by matrix nature/composition and thermal treatments. The oxidative stability of PS during microwave heating was evaluated. Two different model systems (PS alone and in combination) were heated up to 30 min at 1000 W. PS degraded faster when they were alone than in presence of TAG. The extent of PS degradation depends on both heating time and the surrounding medium, which can impact the quality and safety of the food product destined to microwave heating/cooking. Many minor lipid components are included in emulsion systems and can affect the rate of lipid oxidation. The oxidative stability of oil-in-water (O/W) emulsions containing PS esters, ω-3 FA and phenolic compounds, were evaluated after a 14-day storage at room temperature. Due to their surface active character, PS could be particularly prone to oxidation when they are incorporated in emulsions, as they are more exposed to water-soluble prooxidants. Finally, some minor lipophilic components may increase oxidative stability of food systems due to their antioxidant activity. á-tocopherol partitioning and antioxidant activity was determined in the presence of excess SDS in stripped soybean O/W emulsions. Results showed that surfactant micelles could play a key role as an antioxidant carrier, by potentially increasing the accessibility of hydrophobic antioxidant to the interface.

Development and Detailed Characterization of Innovative, High-Performance Membrane Materials for CO2 Capture Processes

The scope of this dissertation is to study the transport phenomena of small molecules in polymers and membranes for gas separation applications, with particular attention to energy efficiency and environmental sustainability. This work seeks to contribute to the development of new competitive selective materials through the characterization of novel organic polymers such as CANALs and ROMPs, as well as through the combination of selective materials obtaining mixed matrix membranes (MMMs), to make membrane technologies competitive with the traditional ones. Kinetic and thermodynamic aspects of the transport properties were investigated in ideal and non-ideal scenarios, such as mixed-gas experiments. The information we gathered contributed to the development of the fundamental understanding related to phenomenon like CO2-induced plasticization and physical aging. Among the most significant results, ZIF-8/PPO MMMs provided materials whose permeability and selectivity were higher than those of the pure materials for He/CO2 separation. The CANALs featured norbornyl benzocyclobutene backbone and thereby introduced a third typology of ladder polymers in the gas separation field, expanding the structural diversity of microporous materials. CANALs have a completely hydrocarbon-based and non-polar rigid backbone, which makes them an ideal model system to investigate structure-property correlations. ROMPs were synthesized by means of the ring opening metathesis living polymerization, which allowed the formation of bottlebrush polymers. CF3-ROMP reveled to be ultrapermeable to CO2, with unprecedented plasticization resistance properties. Mixed-gas experiments in glassy polymer showed that solubility-selectivity controls the separation efficiency of materials in multicomponent conditions. Finally, it was determined that plasticization pressure in not an intrinsic property of a material and does not represent a state of the system, but rather comes from the contribution of solubility coefficient and diffusivity coefficient in the framework of the solution-diffusion model.

Applicazioni tecnologiche e nuovi metodi di valutazione della performance negli sport acquatici

Nello sport di alto livello l’uso della tecnologia ha raggiunto un ruolo di notevole importanza per l’analisi e la valutazione della prestazione. Negli ultimi anni sono emerse nuove tecnologie e sono migliorate quelle pre-esistenti (i.e. accelerometri, giroscopi e software per l’analisi video) in termini di campionamento, acquisizione dati, dimensione dei sensori che ha permesso la loro “indossabilità” e l’inserimento degli stessi all’interno degli attrezzi sportivi. La tecnologia è sempre stata al servizio degli atleti come strumento di supporto per raggiungere l’apice dei risultati sportivi. Per questo motivo la valutazione funzionale dell’atleta associata all’uso di tecnologie si pone lo scopo di valutare i miglioramenti degli atleti misurando la condizione fisica e/o la competenza tecnica di una determinata disciplina sportiva. L’obiettivo di questa tesi è studiare l’utilizzo delle applicazioni tecnologiche e individuare nuovi metodi di valutazione della performance in alcuni sport acquatici. La prima parte (capitoli 1-5), si concentra sulla tecnologia prototipale chiamata E-kayak e le varie applicazioni nel kayak di velocità. In questi lavori è stata verificata l’attendibilità dei dati forniti dal sistema E-kayak con i sistemi presenti in letteratura. Inoltre, sono stati indagati nuovi parametri utili a comprendere il modello di prestazione del paddler. La seconda parte (capitolo 6), si riferisce all’analisi cinematica della spinta verticale del pallanuotista, attraverso l’utilizzo della video analisi 2D, per l’individuazione delle relazioni Forza-velocità e Potenza-velocità direttamente in acqua. Questo studio pilota, potrà fornire indicazioni utili al monitoraggio e condizionamento di forza e potenza da svolgere direttamente in acqua. Infine la terza parte (capitoli 7-8), si focalizza sull’individuazione della sequenza di Fibonacci (sequenza divina) nel nuoto a stile libero e a farfalla. I risultati di questi studi suggeriscono che il ritmo di nuotata tenuto durante le medie/lunghe distanze gioca un ruolo chiave. Inoltre, il livello di autosomiglianza (self-similarity) aumenta con la tecnica del nuoto.

Contributions to the performance analysis of continuum parallel robots

Continuum parallel robots (CPRs) are manipulators employing multiple flexible beams arranged in parallel and connected to a rigid end-effector. CPRs promise higher payload and accuracy than serial CRs while keeping great flexibility. As the risk of injury during accidental contacts between a human and a CPR should be reduced, CPRs may be used in large-scale collaborative tasks or assisted robotic surgery. There exist various CPR designs, but the prototype conception is rarely based on performance considerations, and the CPRs realization in mainly based on intuitions or rigid-link parallel manipulators architectures. This thesis focuses on the performance analysis of CPRs, and the tools needed for such evaluation, such as workspace computation algorithms. In particular, workspace computation strategies for CPRs are essential for the performance assessment, since the CPRs workspace may be used as a performance index or it can serve for optimal-design tools. Two new workspace computation algorithms are proposed in this manuscript, the former focusing on the workspace volume computation and the certification of its numerical results, while the latter aims at computing the workspace boundary only. Due to the elastic nature of CPRs, a key performance indicator for these robots is the stability of their equilibrium configurations. This thesis proposes the experimental validation of the equilibrium stability assessment on a real prototype, demonstrating limitations of some commonly used assumptions. Additionally, a performance index measuring the distance to instability is originally proposed in this manuscript. Differently from the majority of the existing approaches, the clear advantage of the proposed index is a sound physical meaning; accordingly, the index can be used for a more straightforward performance quantification, and to derive robot specifications.

Novel methods of state estimation and parameter identification for high-performance motorcycles

This research activity aims at providing a reliable estimation of particular state variables or parameters concerning the dynamics and performance optimization of a MotoGP-class motorcycle, integrating the classical model-based approach with new methodologies involving artificial intelligence. The first topic of the research focuses on the estimation of the thermal behavior of the MotoGP carbon braking system. Numerical tools are developed to assess the instantaneous surface temperature distribution in the motorcycle's front brake discs. Within this application other important brake parameters are identified using Kalman filters, such as the disc convection coefficient and the power distribution in the disc-pads contact region. Subsequently, a physical model of the brake is built to estimate the instantaneous braking torque. However, the results obtained with this approach are highly limited by the knowledge of the friction coefficient (μ) between the disc rotor and the pads. Since the value of μ is a highly nonlinear function of many variables (namely temperature, pressure and angular velocity of the disc), an analytical model for the friction coefficient estimation appears impractical to establish. To overcome this challenge, an innovative hybrid solution is implemented, combining the benefit of artificial intelligence (AI) with classical model-based approach. Indeed, the disc temperature estimated through the thermal model previously implemented is processed by a machine learning algorithm that outputs the actual value of the friction coefficient thus improving the braking torque computation performed by the physical model of the brake. Finally, the last topic of this research activity regards the development of an AI algorithm to estimate the current sideslip angle of the motorcycle's front tire. While a single-track motorcycle kinematic model and IMU accelerometer signals theoretically enable sideslip calculation, the presence of accelerometer noise leads to a significant drift over time. To address this issue, a long short-term memory (LSTM) network is implemented.

Directly training spiking neural networks for cyber-physical systems: from supervised to reinforcement learning

Spiking Neural Networks (SNNs) are bio-inspired Artificial Neural Networks (ANNs) utilizing discrete spiking signals, akin to neuron communication in the brain, making them ideal for real-time and energy-efficient Cyber-Physical Systems (CPSs). This thesis explores their potential in Structural Health Monitoring (SHM), leveraging low-cost MEMS accelerometers for early damage detection in motorway bridges. The study focuses on Long Short-Term SNNs (LSNNs), although their complex learning processes pose challenges. Comparing LSNNs with other ANN models and training algorithms for SHM, findings indicate LSNNs' effectiveness in damage identification, comparable to ANNs trained using traditional methods. Additionally, an optimized embedded LSNN implementation demonstrates a 54% reduction in execution time, but with longer pre-processing due to spike-based encoding. Furthermore, SNNs are applied in UAV obstacle avoidance, trained directly using a Reinforcement Learning (RL) algorithm with event-based input from a Dynamic Vision Sensor (DVS). Performance evaluation against Convolutional Neural Networks (CNNs) highlights SNNs' superior energy efficiency, showing a 6x decrease in energy consumption. The study also investigates embedded SNN implementations' latency and throughput in real-world deployments, emphasizing their potential for energy-efficient monitoring systems. This research contributes to advancing SHM and UAV obstacle avoidance through SNNs' efficient information processing and decision-making capabilities within CPS domains.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.