Machine-Learning-Powered Cyber-Physical Systems

In the last few years, we witnessed the revolution of the Internet of Things (IoT) paradigm and the consequent growth of Cyber-Physical Systems (CPSs). IoT devices, which include a plethora of smart interconnected sensors, actuators, and microcontrollers, have the ability to sense physical phenomena occurring in an environment and provide copious amounts of heterogeneous data about the functioning of a system. As a consequence, the large amounts of generated data represent an opportunity to adopt artificial intelligence and machine learning techniques that can be used to make informed decisions aimed at the optimization of such systems, thus enabling a variety of services and applications across multiple domains. Machine learning processes and analyses such data to generate a feedback, which represents a status the environment is in. A feedback given to the user in order to make an informed decision is called an open-loop feedback. Thus, an open-loop CPS is characterized by the lack of an actuation directed at improving the system itself. A feedback used by the system itself to actuate a change aimed at optimizing the system itself is called a closed-loop feedback. Thus, a closed-loop CPS pairs feedback based on sensing data with an actuation that impacts the system directly. In this dissertation, we propose several applications in the context of CPS. We propose open-loop CPSs designed for the early prediction, diagnosis, and persistency detection of Bovine Respiratory Disease (BRD) in dairy calves, and for gait activity recognition in horses.These works use sensor data, such as pedometers and automated feeders, to perform valuable real-field data collection. Data are then processed by a mix of state-of-the-art approaches as well as novel techniques, before being fed to machine learning algorithms for classification, which informs the user on the status of their animals. Our work further evaluates a variety of trade-offs. In the context of BRD, we adopt optimization techniques to explore the trade-offs of using sensor data as opposed to manual examination performed by domain experts. Similarly, we carry out an extensive analysis on the cost-accuracy trade-offs, which farmers can adopt to make informed decisions on their barn investments. In the context of horse gait recognition we evaluate the benefits of lighter classifications algorithms to improve energy and storage usage, and their impact on classification accuracy. With respect to closed-loop CPS we proposes an incentive-based demand response approach for Heating Ventilation and Air Conditioning (HVAC) designed for peak load reduction in the context of smart grids. Specifically, our approach uses machine learning to process power data from smart thermostats deployed in user homes, along with their personal temperature preferences. Our machine learning models predict power savings due to thermostat changes, which are then plugged into our optimization problem that uses auction theory coupled with behavioral science. This framework selects the set of users who fulfill the power saving requirement, while minimizing financial incentives paid to the users, and, as a consequence, their discomfort. Our work on BRD has been published on IEEE DCOSS 2022 and Frontiers in Animal Science. Our work on gait recognition has been published on IEEE SMARTCOMP 2019 and Elsevier PMC 2020, and our work on energy management and energy prediction has been published on IEEE PerCom 2022 and IEEE SMARTCOMP 2022. Several other works are under submission when this thesis was written, and are included in this document as well

Mechanistic Insight into the Catechol Oxidase Activity by a Biomimetic Dinuclear Copper Complex

The biomimetic catalytic oxidation of 3,5-ditert- butylcatechol by the dicopper(II) complex of the ligand a,a¢-bis{bis[1-(1¢-methyl-2¢-benzimidazolyl) methyl]amino}-m-xylene in the presence of dioxygen has been investigated as a function of temperature and pH in a mixed aqueous/organic solvent. The catalytic cycle occurs in two steps, the first step being faster than the second step. In the first step, one molecule of catechol is oxidized by the dicopper(II) complex, and the copper(II) centers are reduced. From the pH dependence, it is deduced that the active species of the process is the monohydroxo form of the dinuclear complex. In the second step, the second molecule of catechol is oxidized by the dicopper(I)-dioxygen complex formed upon oxygenation of the reduced complex. In both cases, catechol oxidation is an inner-sphere electron transfer process involving binding of the catechol to the active species. The binary catechol-dicopper(II) complex formed in the first step could be characterized at very low temperature (90 C), where substrate oxidation is blocked. On the contrary, the ternary complex of dicopper( I)-O2-catechol relevant to the second step does not accumulate in solution and could not be characterized, even at low temperature. The investigation of the biphasic kinetics of the catalytic reaction over a range of temperatures allowed the thermodynamic (DH and DS) and activation parameters (DH „ and DS „ ) connected with the key steps of the catecholase process to be obtained

Hierarchical Syntactic Models for Human Activity Recognition through Mobility Traces

Recognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known as grammatical inference. We also introduce a measure of similarity that accounts for the intrinsic hierarchical nature of such models, and allows to identify the common traits in the paths induced by different activities at various granularity levels. Our method has been validated on a dataset of real traces representing movements of users in a large metropolitan area. The experimental results show the effectiveness of our similarity measure to correctly identify a set of common coarse-grained activities, as well as their refinement at a finer level of granularity

The metal-nonoate Ni(SalPipNONO) inhibits in vitro tumor growth, invasiveness and angiogenesis

Nitric oxide (NO) exerts conflicting effect on tumor growth and progression, depending on its concentration. We aimed to characterize the anti-cancer activity of a new NO donor, Ni(SalPipNONO) belonging to the class of metal-nonoates, in epithelial derived tumor cells, finally exploring its antiangiogenic properties. Tumor epithelial cells were screened to evaluate the cytotoxic effect of Ni(SalPipNONO), which was able to inhibit cell proliferation in a dose dependent manner, being more effective than the commercial DETA/NO. The human lung carcinoma cells A549 were chosen as model to study the anti-cancer mechanisms exerted by the compound. In these cells, Ni(SalPipNONO) inhibited clonogenicity and cell invasion, while promoting apoptosis. The antitumor activity was partly due to NO-cGMP dependent pathway, contributing to reduced cell number and apoptosis, and partly to the salicylaldehyde moiety and reactive oxygen species (ROS) activated ERK1/2 signaling converging on p53 dependent caspase-3 cleavage. An additional contribution by downstream cycloxygenase-2 (COX-2) derived cyclopentenones may explain the tumor inhibitory activities. As NO has been described to affect tumor angiogenesis, we checked this activity both on tumor and endothelial cell co-cultures and in Matrigel in vivo assay. Our data document that Ni(SalPipNONO) was able to both reduce angiogenic factor expression by tumor cells acting on hypoxia inducible factor-1α (HIF-1 α) level, and endothelial cell functions related to angiogenesis. Collectively, these data confirm the potential use of NO donors and in particular Ni(SalPipNONO) acting through multiple mechanisms, as an agent to be further developed to be used alone or in combination with conventional therapy

Analysis of the Secondary Structure of the Catalytic Domain of Mouse Ras Exchange Factor CDC25Mm

The minimal active domain GEF domain. of the mouse Ras exchange factor CDC25Mm was purified to homogeneity from recombinant Escherichia coli culture. The 256 amino acids polypeptide shows high activity in vitro and forms a stable complex with H-ras p21 in absence of guanine nucleotides. Circular dichroism CD. spectra in the far UV region indicate that this domain is highly structured with a high content of a-helix 42%.. Near UV CD spectra evidenced good signal due to phenylalanine and tyrosine while a poor contribution was elicited by the three tryptophan residues contained in this domain. The tryptophan fluorescence signal was scarcely affected by denaturation of the protein or by formation of the binary complex with H-ras p21, suggesting that the Trp residues, which are well conserved in the GEF domain of several Ras-exchange factors, were exposed to the surface of the protein and they are not most probably directly involved in the interaction with Ras proteins. q1998 Elsevier Science B.

Axial Imidazole Distorsion Effects on the Catalytic and Binding Properties of Chelated Deuterohemin Complexes

The effect of strain in the axial coordination of imidazole to the heme has been studied in the chelate complexes deuterohemin-histidine (DH-His) and deuterohemin-alanylhistidine (DH-AlaHis). Molecular mechanics calculations indicate that three types of distortion of the axial ligand occur in DH-His, due to the relatively short length of the arm carrying the donor group: tilting off-axis, tipping, and inclination of the imidazole plane with respect to the axial Fe-N bond. The effects of tilting (¢ç 10°) and inclination of the imidazole ring (¢ä 17°) are dominant, while tipping is small and is probably of little importance here. By contrast, the axial imidazole coordination is normal in DH-AlaHis and other computed deuterohemin-dipeptide or -tripeptide complexes where histidine is the terminal residue, the only exception being DH-ProHis, where the rigidity of the proline ring reduces the flexibility of the chelating arm. The distortion in the axial iron-imidazole bond in DH-His has profound and negative influence on the binding and catalytic properties of this complex compared to DH-AlaHis. The former complex binds more weakly carbon monoxide, in its reduced form, and imidazole, in its oxidized form, than the latter. The catalytic efficiency in peroxidative oxidations is also reduced in DH-His with respect to DH-AlaHis. The activity of the latter complex is similar to that of microperoxidase-11, the peptide fragment incorporating the heme that results from hydrolytic cleavage of cytochrome

Synthetic Crysotile Nano-Crystals as a Reference Standard to Investigate Surface-Induce Serum Albumin Structural Modifications

Geoinspired synthetic chrysotile, which represents an ideal asbestos reference standard, has been utilized to investigate homomolecular exchange of bovine serum albumin (BSA), the major plasma protein, between the adsorbed and dissolved state at the interface between asbestos fibers and biological medium. FTIR spectroscopy has been used to quantify BSA structural modifications due to surface adhesion on chrysotile fibers as a function of the surface coating extent. Circular dichroism spectroscopy has been used to investigate the adsorption/desorption equilibrium through analysis of the BSA structural perturbations after protein desorption from chrysotile surface. Data results show clearly that in the solid state BSA modifications are driven by surface interaction with the substrate, following a bimodal adsorption evidenced by two different binding constants. On the other hand, BSA desorbed in solution is able to rearrange, in the lack of substrate, although keeping irreversible modifications with respect to the native species. The lack of regaining its native structure certainly affects albumin interaction with biological environment. The present investigation on the stoichiometric synthetic geoinspired chrysotile nanocrystals is the first approach toward a deeper attempt to use standard synthetic chrysotile reference samples in mimicking the behavior of asbestos fibers and allows to better understand their interaction with a biological environment

Interpenetrated networks from a novel nanometer-sized pseudopeptidic ligand, bridging water, and transition metal ions with CdSO4 topology.

The combination of a new pseudopeptidic ligand, transition metal ions, and bridging water molecules results in the formation of [M(m-TBG)(m-H2O)(H2O)2]?2H2O (M: Cu, Co and H2TBG: terephthaloylbisglycine); both compounds show rare two-fold interpenetrated three-dimensional cds-nets and reversible loss of coordinated and lattice water molecule

Timing analysis of 10-day long BeppoSAX observation of GRS 1915+105 in its ρ class

Published online at http://pos.sissa.it/cgi-bin/reader/conf.cgi?confid=6

Formation of reactive nitrogen species at biologic heme centers: a potential mechanism of nitric oxide-dependent toxicity.

The peroxidase-catalyzed nitration of tyrosine derivatives by nitrite and hydrogen peroxide has been studied in detail using the enzymes lactoperoxidase (LPO) from bovine milk and horseradish peroxidase (HRP). The results indicate the existence of two competing pathways, in which the nitrating species is either nitrogen dioxide or peroxynitrite. The first pathway involves one-electron oxidation of nitrite by the classical peroxidase intermediates compound I and compound II, whereas in the second pathway peroxynitrite is generated by reaction between enzyme-bound nitrite and hydrogen peroxide. The two mechanisms can be simultaneously operative, and their relative importance depends on the reagent concentrations. With HRP the peroxynitrite pathway contributes significantly only at relatively high nitrite concentrations, but for LPO this represents the main pathway even at relatively low (pathophysiological) nitrite concentrations and explains the high efficiency of the enzyme in the nitration. Myoglobin and hemoglobin are also active in the nitration of phenolic compounds, albeit with lower efficiency compared with peroxidases. In the case of myoglobin, endogenous nitration of the protein has been shown to occur in the absence of substrate. The main nitration site is the heme, but a small fraction of nitrated Tyr146 residue has been identified upon proteolytic digestion and high-performance liquid chromatography/mass spectrometry analysis of the peptide fragments. Preliminary investigation of the nitration of tryptophan derivatives by the peroxidase/nitrite/hydrogen peroxide systems shows that a complex pattern of isomeric nitration products is produced, and this pattern varies with nitrite concentration. Comparative experiments using chemical nitrating agents indicate that at low nitrite concentrations, the enzymatic nitration produces a regioisomeric mixture of nitrotryptophanyl derivatives resembling that obtained using nitrogen dioxide, whereas at high nitrite concentrations the product pattern resembles that obtained using peroxynitrite