Motion control and real-time systems: an approach to trajectory rebuilding in non-deterministic networks

Motion control is a sub-field of automation, in which the position and/or velocity of machines are controlled using some type of device. In motion control the position, velocity, force, pressure, etc., profiles are designed in such a way that the different mechanical parts work as an harmonious whole in which a perfect synchronization must be achieved. The real-time exchange of information in the distributed system that is nowadays an industrial plant plays an important role in order to achieve always better performance, better effectiveness and better safety. The network for connecting field devices such as sensors, actuators, field controllers such as PLCs, regulators, drive controller etc., and man-machine interfaces is commonly called fieldbus. Since the motion transmission is now task of the communication system, and not more of kinematic chains as in the past, the communication protocol must assure that the desired profiles, and their properties, are correctly transmitted to the axes then reproduced or else the synchronization among the different parts is lost with all the resulting consequences. In this thesis, the problem of trajectory reconstruction in the case of an event-triggered communication system is faced. The most important feature that a real-time communication system must have is the preservation of the following temporal and spatial properties: absolute temporal consistency, relative temporal consistency, spatial consistency. Starting from the basic system composed by one master and one slave and passing through systems made up by many slaves and one master or many masters and one slave, the problems in the profile reconstruction and temporal properties preservation, and subsequently the synchronization of different profiles in network adopting an event-triggered communication system, have been shown. These networks are characterized by the fact that a common knowledge of the global time is not available. Therefore they are non-deterministic networks. Each topology is analyzed and the proposed solution based on phase-locked loops adopted for the basic master-slave case has been improved to face with the other configurations.

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Advances in methods to detect, isolate and quantify foodborne pathogens

Foodborne diseases impact human health and economies worldwide in terms of health care and productivity loss. Prevention is necessary and methods to detect, isolate and quantify foodborne pathogens play a fundamental role, changing continuously to face microorganisms and food production evolution. Official methods are mainly based on microorganisms growth in different media and their isolation on selective agars followed by confirmation of presumptive colonies through biochemical and serological test. A complete identification requires form 7 to 10 days. Over the last decades, new molecular techniques based on antibodies and nucleic acids allow a more accurate typing and a faster detection and quantification. The present thesis aims to apply molecular techniques to improve official methods performances regarding two pathogens: Shiga-like Toxin-producing Escherichia coli (STEC) and Listeria monocytogenes. In 2011, a new strain of STEC belonging to the serogroup O104 provoked a large outbreak. Therefore, the development of a method to detect and isolate STEC O104 is demanded. The first objective of this work is the detection, isolation and identification of STEC O104 in sprouts artificially contaminated. Multiplex PCR assays and antibodies anti-O104 incorporated in reagents for immunomagnetic separation and latex agglutination were employed. Contamination levels of less than 1 CFU/g were detected. Multiplex PCR assays permitted a rapid screening of enriched food samples and identification of isolated colonies. Immunomagnetic separation and latex agglutination allowed a high sensitivity and rapid identification of O104 antigen, respectively. The development of a rapid method to detect and quantify Listeria monocytogenes, a high-risk pathogen, is the second objective. Detection of 1 CFU/ml and quantification of 10–1,000 CFU/ml in raw milk were achieved by a sample pretreatment step and quantitative PCR in about 3h. L. monocytogenes growth in raw milk was also evaluated.

Development of new chemical entities to target neuroinflammatory pathways.

Neuroinflammatory pathways are main culprits of neurodegenerative diseases' onset and progression, including Alzheimer’s disease (AD). On this basis, several anti-inflammatory drugs were repurposed in clinical trials. However, they have failed, probably because neuroinflammation is a complex network, still not fully understood. From these evidences, this thesis focused on the design and synthesis of new chemical entities as potential neuroinflammatory drugs or chemical probes. Projects 1 and 2 aimed to multi-target-directed ligand (MTDL) development to target neuroinflammation in AD. Polypharmacology by MTDLs is considered one of the most promising strategies to face the multifactorial nature of neurodegenerative diseases. Particularly, Project 1 took inspiration from a cromolyn-ibuprofen drug combination polypharmacological approach, which was recently investigated in AD clinical trials. Based on that, two cromolyn-(S)-ibuprofen codrug series were designed and synthesized. Parent drugs were combined via linking or fusing strategies in 1:2 or 1:1 ratio, by means of hydrolyzable bonds. Project 2 started from a still ongoing AD clinical trial on investigational drug neflamapimod. It is a selective inhibitor of p38α-MAPK, a kinase strictly involved in neuroinflammatory pathways. On the other side, rasagiline, an anti-Parkinson drug, was also repurposed as AD treatment. Indeed, rasagiline’s propargylamine fragment demonstrated to be responsible not only for the MAO-B selective inhibition, but also for the neuroprotective activity. Thus, to synergistically combine these two effects into single-molecules, a small set of neflamapimod-rasagiline hybrids was developed. In the end BMX, a poorly investigated kinase, which seems to be involved in pro-inflammatory mediator production, was explored for the development of new chemical probes. High-quality chemical probes are a powerful tool in target validation and starting points for the development of new drug candidates. Thus, Project 3 focused on the design and synthesis of two series of optimized BMX covalent inhibitors as selective chemical probes.

Abusing data dominance in the digital market. The application of merger control and article 102 TFEU to data-related conducts.

The internet and digital technologies revolutionized the economy. Regulating the digital market has become a priority for the European Union. While promoting innovation and development, EU institutions must assure that the digital market maintains a competitive structure. Among the numerous elements characterizing the digital sector, users’ data are particularly important. Digital services are centered around personal data, the accumulation of which contributed to the centralization of market power in the hands of a few large providers. As a result, data-driven mergers and data-related abuses gained a central role for the purposes of EU antitrust enforcement. In light of these considerations, this work aims at assessing whether EU competition law is well-suited to address data-driven mergers and data-related abuses of dominance. These conducts are of crucial importance to the maintenance of competition in the digital sector, insofar as the accumulation of users’ data constitutes a fundamental competitive advantage. To begin with, part 1 addresses the specific features of the digital market and their impact on the definition of the relevant market and the assessment of dominance by antitrust authorities. Secondly, part 2 analyzes the EU’s case law on data-driven mergers to verify if merger control is well-suited to address these concentrations. Thirdly, part 3 discusses abuses of dominance in the phase of data collection and the legal frameworks applicable to these conducts. Fourthly, part 4 focuses on access to “essential” datasets and the indirect effects of anticompetitive conducts on rivals’ ability to access users’ information. Finally, Part 5 discusses differential pricing practices implemented online and based on personal data. As it will be assessed, the combination of an efficient competition law enforcement and the auspicial adoption of a specific regulation seems to be the best solution to face the challenges raised by “data-related dominance”.

R-loops and G4-structures: from DNA damage to innate immune response gene activation

Non-B DNA structures like R-loops and G-quadruplexes play a pivotal role in several cellular vital processes like DNA transcription regulation. Misregulation of said non-canonical DNA structures can often lead to genome instability, DNA damage, and, eventually, to the activation of an innate immune response. For such reasons they have been studied as adjuvants in anticancer therapies. Here we studied drugs targeting R-loops (Top1 poisons) and G4s (hydrazone derivatives) in order to observe their effects in terms of DNA damage induction and, subsequently, activation of innate immune response. We studied how non-cytotoxic doses of ampthotecin and LMP-776 impact on genome instability, are capable to induce DNA damage and micronuclei, and, eventually lead to an innate immune gene response via the cGAS/STING pathway. G-quadruplexes are another ubiquitous, non-canonical DNA structure, more abundant in telomeric regions, demonstrating a marked relation with the impairment of telomerase and the regulation of DNA replication and transcription. Furthermore, we investigated the properties of new-synthesized molecules belonging to the highly promising class of hydrazone derivatives, in terms of cytotoxicity, ability to stabilize G4-structures, induce DNA damage, and activate interferon-B production. Both Top1 poisons and G4-stabilizers possess several features that can be very useful in clinical applications, in light of their ability to stimulate innate immune response factors and exert a certain cell-killing power, plus they offer a broad and diverse range of treatment options in order to face a variety of patient treatment needs. It is for these very reasons that it is of uttermost importance that further studies are conducted on these compounds, in order to synthesize new and increasingly powerful and flexible ones, with fewer side effects to customize therapies on specific cancers’ and patients’ features.