Robust Adaptive Control with Applications to Multi-Agent Systems and Mobile Robotics

This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

Dissecting the role of IGF2BP3 in the stress-adaptive response and in intercellular communication in Ewing Sarcoma.

Tumor microenvironment has emerged as key factor influencing tumor progression and metastatization. In this context, small vesicles produced by cancer cells can influence the fate of their surroundings via the horizontal transfer of specific molecular cargos. Ewing Sarcoma, the second most common bone tumor in young patients, presents early metastasis associated to worse prognosis. The RNA binding protein Insulin-like Growth Factor 2 mRNA Binding Protein 3 (IGF2BP3) exerts a pro-oncogenic role associated with metastasis formation and worse prognosis in Ewing Sarcoma. Our aim was to investigate the still unexplored role of IGF2BP3 in the stress-adaptive response to tumor microenvironment and in the interactions between Ewing Sarcoma cells. Hypoxia is a major feature of Ewing Sarcoma microenvironment and we demonstrated that IGF2BP3 can direct the CXCR4-mediated migratory response to CXCL12 in Ewing Sarcoma cells subjected to oxygen deprivation. We also discovered that the interaction between IGF2BP3 and CXCR4 is regulated through CD164 and which colocalize at plasma membrane level, upon CXCL12 exposure. Interestingly, high IGF2BP3 levels in Ewing Sarcoma metastatic lesions positively correlated with the expression of both CD164 and CXCR4, indicating the IGF2BP3/CD164/CXCR4 oncogenic axis as a critical modulator of Ewing Sarcoma metastatic progression. We demonstrated for the first time that IGF2BP3 is loaded into Ewing Sarcoma derived exosomes, accordingly to its cellular levels. We discovered that IGF2BP3+ exosomes carry high levels of IGF2BP3-client mRNAs involved in cellular migration, CD164 and IGF1R, and, by transferring this cargo, sustain the migratory abilities of receiving cells, induce a sharp up-regulation of CD164, CXCR4 and IGF1R and enhance the activation of AKT/mTOR and ERK down-stream signalling pathways. We demostrated that the pro-tumorigenic role of IGF2BP3 is not only exerted at cellular level, but that intercellular communication is crucial in the context of Ewing Sarcoma microenvironment.

Interactions between normative systems and software cognitive agents. A formalization in temporal modal defeasible logic and its implementation

Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

Designing and Programming Organizational Infrastructures for Agents situated in Artifact-based Environments

Actual trends in software development are pushing the need to face a multiplicity of diverse activities and interaction styles characterizing complex and distributed application domains, in such a way that the resulting dynamics exhibits some grade of order, i.e. in terms of evolution of the system and desired equilibrium. Autonomous agents and Multiagent Systems are argued in literature as one of the most immediate approaches for describing such a kind of challenges. Actually, agent research seems to converge towards the definition of renewed abstraction tools aimed at better capturing the new demands of open systems. Besides agents, which are assumed as autonomous entities purposing a series of design objectives, Multiagent Systems account new notions as first-class entities, aimed, above all, at modeling institutional/organizational entities, placed for normative regulation, interaction and teamwork management, as well as environmental entities, placed as resources to further support and regulate agent work. The starting point of this thesis is recognizing that both organizations and environments can be rooted in a unifying perspective. Whereas recent research in agent systems seems to account a set of diverse approaches to specifically face with at least one aspect within the above mentioned, this work aims at proposing a unifying approach where both agents and their organizations can be straightforwardly situated in properly designed working environments. In this line, this work pursues reconciliation of environments with sociality, social interaction with environment based interaction, environmental resources with organizational functionalities with the aim to smoothly integrate the various aspects of complex and situated organizations in a coherent programming approach. Rooted in Agents and Artifacts (A&A) meta-model, which has been recently introduced both in the context of agent oriented software engineering and programming, the thesis promotes the notion of Embodied Organizations, characterized by computational infrastructures attaining a seamless integration between agents, organizations and environmental entities.

Support infrastructures for multimedia services with guaranteed continuity and QoS

Advances in wireless networking and content delivery systems are enabling new challenging provisioning scenarios where a growing number of users access multimedia services, e.g., audio/video streaming, while moving among different points of attachment to the Internet, possibly with different connectivity technologies, e.g., Wi-Fi, Bluetooth, and cellular 3G. That calls for novel middlewares capable of dynamically personalizing service provisioning to the characteristics of client environments, in particular to discontinuities in wireless resource availability due to handoffs. This dissertation proposes a novel middleware solution, called MUM, that performs effective and context-aware handoff management to transparently avoid service interruptions during both horizontal and vertical handoffs. To achieve the goal, MUM exploits the full visibility of wireless connections available in client localities and their handoff implementations (handoff awareness), of service quality requirements and handoff-related quality degradations (QoS awareness), and of network topology and resources available in current/future localities (location awareness). The design and implementation of the all main MUM components along with extensive on the field trials of the realized middleware architecture confirmed the validity of the proposed full context-aware handoff management approach. In particular, the reported experimental results demonstrate that MUM can effectively maintain service continuity for a wide range of different multimedia services by exploiting handoff prediction mechanisms, adaptive buffering and pre-fetching techniques, and proactive re-addressing/re-binding.

Morphological and functional study of cerebral aging in rat

Aging is a physiological process characterized by a progressive decline of the “cellular homeostatic reserve”, refereed as the capability to respond suitably to exogenous and endogenous stressful stimuli. Due to their high energetic requests and post-mitotic nature, neurons are peculiarly susceptible to this phenomenon. However, the aged brain maintains a certain level of adaptive capacities and if properly stimulated may warrant a considerable functional recovery. Aim of the present research was to verify the plastic potentialities of the aging brain of rats subjected to two kind of exogenous stimuli: A) the replacement of the standard diet with a ketogenic regimen (the change forces the brain to use ketone bodies (KB) in alternative to glucose to satisfy the energetic needs) and B) a behavioural task able to induce the formation of inhibitory avoidance memory. A) Fifteen male Wistar rats of 19 months of age were divided into three groups (average body weight pair-matched), and fed for 8 weeks with different dietary regimens: i) diet containing 10% medium chain triglycerides (MCT); ii) diet containing 20% MCT; iii) standard commercial chow. Five young (5 months of age) and five old (26-27 months of age) animals fed with the standard diet were used as further controls. The following morphological parameters reflecting synaptic plasticity were evaluated in the stratum moleculare of the hippocampal CA1 region (SM CA1), in the outer molecular layer of the hippocampal dentate gyrus (OML DG), and in the granule cell layer of the cerebellar cortex (GCL-CCx): average area (S), numeric density (Nvs), and surface density (Sv) of synapses, and average volume (V), numeric density (Nvm), and volume density (Vv) of synaptic mitochondria. Moreover, succinic dehydrogenase (SDH) activity was cytochemically determined in Purkinje cells (PC) and V, Nvm, Vv, and cytochemical precipitate area/mitochondrial area (R) of SDH-positive mitochondria were evaluated. In SM CA1, MCT-KDs induced the early appearance of the morphological patterns typical of old animals: higher S and V, and lower Nvs and Nvm. On the contrary, in OML DG, Sv and Vv of MCT-KDs-fed rats were higher (as a result of higher Nvs and Nvm) vs. controls; these modifications are known to improve synaptic function and metabolic supply. The opposite effects of MCT-KDs might reflect the different susceptibility of these brain regions to the aging processes: OML DG is less vulnerable than SM CA1, and the reactivation of ketone bodies uptake and catabolism might occur more efficiently in this region, allowing the exploitation of their peculiar metabolic properties. In GCL-CCx, the results described a new scenario in comparison to that found in the hippocampal formation: 10%MCT-KD induced the early appearance of senescent patterns (decreased Nvs and Nvm; increased V), whereas 20%MCT-KD caused no changes. Since GCL-CCx is more vulnerable to age than DG, and less than CA1, these data further support the hypothesis that MCT-KDs effects in the aging brain critically depend on neuronal vulnerability to age, besides MCT percentage. Regarding PC, it was decided to evaluate only the metabolic effect of the dietetic regimen (20%MCT-KD) characterized by less side effects. KD counteracted age-related decrease in numeric density of SDH-positive mitochondria, and enhanced their energetic efficiency (R was significantly higher in MCT-KD-fed rats vs. all the controls). Since it is well known that Purkinje and dentate gyrus cells are less vulnerable to aging than CA1 neurons, these results corroborate our previous hypothesis. In conclusion, the A) experimental line provides the first evidence that morphological and functional parameters reflecting synaptic plasticity and mitochondrial metabolic competence may be modulated by MCT-KDs in the pre-senescent central nervous system, and that the effects may be heterogeneous in different brain regions. MCT-KDs seem to supply high energy metabolic intermediates and to be beneficial (“anti-aging”) for those neurons that maintain the capability to exploit them. This implies risks but also promising potentialities for the therapeutic use of these diets during aging B) Morphological parameters of synapses and synaptic mitochondria in SM CA1 were investigated in old (26-27 month-old) female Wistar rats following a single trial inhibitory avoidance task. In this memory protocol animals learn to avoid a dark compartment in which they received a mild, inescapable foot-shock. Rats were tested 3 and 6 or 9 hours after the training, divided into good and bad responders according to their performance (retention times above or below 100 s, respectively) and immediately sacrificed. Nvs, S, Sv, Nvm, V, and Vv were evaluated. In the good responder group, the numeric density of synapses and mitochondria was significantly higher and the average mitochondrial volume was significantly smaller 9 hours vs. 6 hours after the training. No significant differences were observed among bad responders. Thus, better performances in passive avoidance memory task are correlated with more efficient plastic remodeling of synaptic contacts and mitochondria in hippocampal CA1. These findings indicate that maintenance of synaptic plastic reactivity during aging is a critical requirement for preserving long-term memory consolidation.

Oblique ionograms automatic scaling and eikonal based ray tracing

A method for automatic scaling of oblique ionograms has been introduced. This method also provides a rejection procedure for ionograms that are considered to lack sufficient information, depicting a very good success rate. Observing the Kp index of each autoscaled ionogram, can be noticed that the behavior of the autoscaling program does not depend on geomagnetic conditions. The comparison between the values of the MUF provided by the presented software and those obtained by an experienced operator indicate that the procedure developed for detecting the nose of oblique ionogram traces is sufficiently efficient and becomes much more efficient as the quality of the ionograms improves. These results demonstrate the program allows the real-time evaluation of MUF values associated with a particular radio link through an oblique radio sounding. The automatic recognition of a part of the trace allows determine for certain frequencies, the time taken by the radio wave to travel the path between the transmitter and receiver. The reconstruction of the ionogram traces, suggests the possibility of estimating the electron density between the transmitter and the receiver, from an oblique ionogram. The showed results have been obtained with a ray-tracing procedure based on the integration of the eikonal equation and using an analytical ionospheric model with free parameters. This indicates the possibility of applying an adaptive model and a ray-tracing algorithm to estimate the electron density in the ionosphere between the transmitter and the receiver An additional study has been conducted on a high quality ionospheric soundings data set and another algorithm has been designed for the conversion of an oblique ionogram into a vertical one, using Martyn's theorem. This allows a further analysis of oblique soundings, throw the use of the INGV Autoscala program for the automatic scaling of vertical ionograms.

Development of a microgrid with renewable energy sources and electrochemical storage system integration

Beside the traditional paradigm of "centralized" power generation, a new concept of "distributed" generation is emerging, in which the same user becomes pro-sumer. During this transition, the Energy Storage Systems (ESS) can provide multiple services and features, which are necessary for a higher quality of the electrical system and for the optimization of non-programmable Renewable Energy Source (RES) power plants. A ESS prototype was designed, developed and integrated into a renewable energy production system in order to create a smart microgrid and consequently manage in an efficient and intelligent way the energy flow as a function of the power demand. The produced energy can be introduced into the grid, supplied to the load directly or stored in batteries. The microgrid is composed by a 7 kW wind turbine (WT) and a 17 kW photovoltaic (PV) plant are part of. The load is given by electrical utilities of a cheese factory. The ESS is composed by the following two subsystems, a Battery Energy Storage System (BESS) and a Power Control System (PCS). With the aim of sizing the ESS, a Remote Grid Analyzer (RGA) was designed, realized and connected to the wind turbine, photovoltaic plant and the switchboard. Afterwards, different electrochemical storage technologies were studied, and taking into account the load requirements present in the cheese factory, the most suitable solution was identified in the high temperatures salt Na-NiCl2 battery technology. The data acquisition from all electrical utilities provided a detailed load analysis, indicating the optimal storage size equal to a 30 kW battery system. Moreover a container was designed and realized to locate the BESS and PCS, meeting all the requirements and safety conditions. Furthermore, a smart control system was implemented in order to handle the different applications of the ESS, such as peak shaving or load levelling.

Synthesis of constrained peptidomimetics for therapeutic, diagnostic and theranostic applications

This thesis work deals, principally, with the development of different chemical protocols ranging from environmental sustainability peptide synthesis to asymmetric synthesis of modified tryptophans to a series of straightforward procedures for constraining peptide backbones without the need for a pre-formed scaffold. Much efforts have been dedicated to the structural analysis in a biomimetic environment, fundamental for predicting the in vivo conformation of compounds, as well as for giving a rationale to the experimentally determined bioactivity. The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, titration experiments, molecular dynamics, etc.), FT-IR and ECD spectroscopy. As a practical application, 3D rigid scaffolds have been employed for the synthesis of biological active compounds based on peptidomimetic and retro-mimetic structures. These mimics have been investigated for their potential as antiflammatory agents and actually the results obtained are very promising. Moreover, the synthesis of Amo ring permitted the development of an alternative high effective synthetic pathway for obtaining Linezolid antibiotic. The final section is, instead, dedicated to the construction of a new biosensor based on zeolite L SAMs functionalized with the integrin ligand c[RGDfK], that has showed high efficiency for the selective detection of tumor cells. Such kind of sensor could, in fact, enable the convenient, non-invasive detection and diagnosis of cancer in early stages, from a few drops of a patient's blood or other biological fluids. In conclusion, the researches described herein demonstrate that the peptidomimetic approach to 3D definite structures, allows unambiguous investigation of the structure-activity relationships, giving an access to a wide range bioactive compounds of pharmaceutical interest to use not only as potential drugs but also for diagnostic and theranostic applications.

NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System.

Wheat proteins evolution and environmental triggers of Wheat-related diseases

Cereals, and in particular wheat, have always been recognized as a fundamental food worldwide. In particular, the success of wheat is linked with unique properties of the gluten protein fraction used in bread making process to obtain products that are widely used in traditional and modern diets. The rapid increase in the world population let to a parallel increases in food production, particularly of wheat. Increasing yield potential and selection of cultivars much more resistant to plant disease and to environmental factors could have negatively affected the quality of the grain. Moreover, the “green revolution” was characterized by a widespread use of agricultural chemicals and by industrialization of food production that led to a huge rise in the consumption of refined products. Modern baking practices have shortened bread leavening, increased the use of chemical/yeast leavening agents and there is well-documented scientific evidence of the negative effects of ultra-processed food in human healthy. All this changes profoundly modified the human diet and, as a result, may have affected Gluten-related disease (GRDs) that has arisen in the whole word populations. Gluten-related diseases (GRDs) are multifactorial pathologies in which environmental factors and genetic background contribute to a low-grade chronic inflammation of the gastrointestinal tract. Here, I investigated the potential pro-inflammatory effect of different wheat varieties and whether bread making processing are involved in the onset or worsening of gut inflammation. In vitro, ex vivo and in vivo studies conducted throughout my Phd period have shown a pro-inflammatory effect of wheat especially marked in modern varieties and a higher inflammatory response linked to the use of common raising agent as Saccharomyces Cerevisiae and to the addiction of chemical bakery improver substances.

Peptidomimetic ligands for tuning integrin-mediated signalling: rational design, synthesis and theranostic applications

Integrins are α/β-heterodimeric transmembrane adhesion receptors that mediate cell-cell and cell-ECM interactions. Integrins are bidirectional signalling receptors that respond to external signals (“outside-in” signalling) and in parallel, transduce internal signals to the matrix (“inside-out” signalling), to regulate vital cellular functions including migration, survival, growth and differentiation. Therefore, dysregulation of these tightly regulated processes often results in uncontrolled integrin activation and abnormal tissue expression that is responsible for many diseases. Because of their important roles in physiological and pathological events, they represent a validated target for therapeutic and diagnostic purposes. The aim of the present Thesis was focused on the development of peptidic ligands for α4β1 and αvβ3 integrin subtypes, involved in inflammatory responses (leukocytes recruitment and extravasation) and cancer progression (angiogenesis, tumor growth, metastasis), respectively. Following the peptidomimetic strategy, we designed and synthesized a small library of linear and cyclic hybrid α/β-peptidomimetics based on the phenylureido-LDV scaffolds for the treatment of chronic inflammatory autoimmune diseases. In order to implement a fast and non-invasive diagnostic method for monitoring the course of the inflammatory processes, a flat glass-surface of dye-loaded Zeolite L-crystal nanoparticles was coated with bioactive α4β1-peptidomimetics to detect specific integrin-expressing cells as biomarkers of inflammatory diseases. Targeted drug delivery has been considered a promising alternative to overcome the pharmacokinetic limitations of conventional anticancer drugs. Thus, a novel Small-Molecule Drug Conjugate was synthesized by connecting the highly cytotoxic Cryptophycin to the tumor-targeting RGDfK-peptide through a protease-cleavable linker. Finally, in view to making the peptide synthesis more sustainable and greener, we developed an alternative method for peptide bonds formation employing solvent-free mechanochemistry and ultra-mild minimal solvent-grinding conditions in common, inexpensive laboratory equipment. To this purpose, standard amino acids, coupling agents and organic-green solvents were used in the presence of nanocrystalline hydroxyapatite as a reusable, bio-compatible inorganic basic catalyst.

Development and optimization of techniques and design parameters for the engineering of atmospheric pressure plasma devices for biomedical applications and plasma medicine

In the last decades, the possibility to generate plasma at atmospheric pressure gave rise to a new emerging field called plasma medicine; it deals with the application of cold atmospheric pressure plasmas (CAPs) or plasma-activated solutions on or in the human body for therapeutic effects. Thanks to a blend of synergic biologically active agents and biocompatible temperatures, different CAP sources were successfully employed in many different biomedical applications such as dentistry, dermatology, wound healing, cancer treatment, blood coagulation, etc.… Despite their effectiveness has been verified in the above-mentioned biomedical applications, over the years, researchers throughout the world described numerous CAP sources which are still laboratory devices not optimized for the specific application. In this perspective, the aim of this dissertation was the development and the optimization of techniques and design parameters for the engineering of CAP sources for different biomedical applications and plasma medicine among which cancer treatment, dentistry and bioaerosol decontamination. In the first section, the discharge electrical parameters, the behavior of the plasma streamers and the liquid and the gas phase chemistry of a multiwire device for the treatment of liquids were performed. Moreover, two different plasma-activated liquids were used for the treatment of Epithelial Ovarian Cancer cells and fibroblasts to assess their selectivity. In the second section, in accordance with the most important standard regulations for medical devices, were reported the realization steps of a Plasma Gun device easy to handle and expected to be mounted on a tabletop device that could be used for dental clinical applications. In the third section, in relation to the current COVID-19 pandemic, were reported the first steps for the design, realization, and optimization of a dielectric barrier discharge source suitable for the treatment of different types of bioaerosol.

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.