Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Employing Distances in Design-based Spatial Estimation

In the last couple of decades we assisted to a reappraisal of spatial design-based techniques. Usually the spatial information regarding the spatial location of the individuals of a population has been used to develop efficient sampling designs. This thesis aims at offering a new technique for both inference on individual values and global population values able to employ the spatial information available before sampling at estimation level by rewriting a deterministic interpolator under a design-based framework. The achieved point estimator of the individual values is treated both in the case of finite spatial populations and continuous spatial domains, while the theory on the estimator of the population global value covers the finite population case only. A fairly broad simulation study compares the results of the point estimator with the simple random sampling without replacement estimator in predictive form and the kriging, which is the benchmark technique for inference on spatial data. The Monte Carlo experiment is carried out on populations generated according to different superpopulation methods in order to manage different aspects of the spatial structure. The simulation outcomes point out that the proposed point estimator has almost the same behaviour as the kriging predictor regardless of the parameters adopted for generating the populations, especially for low sampling fractions. Moreover, the use of the spatial information improves substantially design-based spatial inference on individual values.

Constraint Programming-based Job Dispatching for Modern HPC Applications

A High-Performance Computing job dispatcher is a critical software that assigns the finite computing resources to submitted jobs. This resource assignment over time is known as the on-line job dispatching problem in HPC systems. The fact the problem is on-line means that solutions must be computed in real-time, and their required time cannot exceed some threshold to do not affect the normal system functioning. In addition, a job dispatcher must deal with a lot of uncertainty: submission times, the number of requested resources, and duration of jobs. Heuristic-based techniques have been broadly used in HPC systems, at the cost of achieving (sub-)optimal solutions in a short time. However, the scheduling and resource allocation components are separated, thus generates a decoupled decision that may cause a performance loss. Optimization-based techniques are less used for this problem, although they can significantly improve the performance of HPC systems at the expense of higher computation time. Nowadays, HPC systems are being used for modern applications, such as big data analytics and predictive model building, that employ, in general, many short jobs. However, this information is unknown at dispatching time, and job dispatchers need to process large numbers of them quickly while ensuring high Quality-of-Service (QoS) levels. Constraint Programming (CP) has been shown to be an effective approach to tackle job dispatching problems. However, state-of-the-art CP-based job dispatchers are unable to satisfy the challenges of on-line dispatching, such as generate dispatching decisions in a brief period and integrate current and past information of the housing system. Given the previous reasons, we propose CP-based dispatchers that are more suitable for HPC systems running modern applications, generating on-line dispatching decisions in a proper time and are able to make effective use of job duration predictions to improve QoS levels, especially for workloads dominated by short jobs.

Advanced X-ray techniques for the structural characterisation of Prussian Blue Analogue cathode materials

The thesis is dedicated to the implementation of advanced x-ray-based techniques for the investigation of the battery systems, more predominantly, the cathode materials. The implemented characterisation methods include synchrotron based x-ray absorption spectroscopy, powder x-ray diffraction, 2-dimensional x-ray fluorescence, full field transmission soft x-ray microscopy, and laboratory x-ray photoelectron spectroscopy. The research highlights the different areas of expertise for each described method, in terms of material characterisation, exploring their complementarities and intersections. The results are focused over manganese hexacyanoferrate and partially Ni substituted manganese hexacyanoferrate, through both organic and aqueous battery systems. In aqueous system, the modification of cathode composition has been observed with various techniques, indicating to the processes occurring in bulk, surface, locally or in long-range, including with the speciation by 2-dimensional scanning, and the time-resolution, by the implementation of the operando measurements. In organic media, the inhomogenisation of the cathode material during the aging process was investigated by the development of the special image treatment procedure for the maps, obtained from the transmission soft x-ray microscopy. It worth mentioning, that apart from the combination of the outcomes from the various x-ray measurements, the exploration of the new capabilities was also conducted, namely, probing the oxidation state of the element with the synchrotron-based 2-dimensional x-ray fluorescence technique, which, generally, with conventional set up, is not possible to achieve. The results and methodology from this thesis can, of course, be generalised on the characterisation of the other battery systems, and not only, as the x-ray techniques are one of the most informative and sophisticated methods for advanced structural investigation of the materials.

Luminescent Systems for Genomics and Proteomics

The present PhD project was focused on the development of new tools and methods for luminescence-based techniques. In particular, the ultimate goal was to present substantial improvements to the currently available technologies for both research and diagnostic in the fields of biology, proteomics and genomics. Different aspects and problems were investigated, requiring different strategies and approaches. The whole work was thus divided into separate chapters, each based on the study of one specific aspect of luminescence: Chemiluminescence, Fluorescence and Electrochemiluminescence. CHAPTER 1, Chemiluminescence The work on luminol-enhancer solution lead to a new luminol solution formulation with 1 order of magnitude lower detection limit for HRP. This technology was patented with Cyanagen brand and is now sold worldwide for Western Blot and ELISA applications. CHAPTER 2, Fluorescescence The work on dyed-doped silica nanoparticles is marking a new milestone in the development of nanotechnologies for biological applications. While the project is still in progress, preliminary studies on model structures are leading to very promising results. The improved brightness of these nano-sized objects, their simple synthesis and handling, their low toxicity will soon turn them, we strongly believe, into a new generation of fluorescent labels for many applications. CHAPTER 3, Electrochemiluminescence The work on electrochemiluminescence produced interesting results that can potentially turn into great improvements from an analytical point of view. Ru(bpy)3 derivatives were employed both for on-chip microarray (Chapter 3.1) and for microscopic imaging applications (Chapter 3.2). The development of these new techniques is still under investigation, but the obtained results confirm the possibility to achieve the final goal. Furthermore the development of new ECL-active species (Chapter 3.3, 3.4, 3.5) and their use in these applications can significantly improve overall performances, thus helping to spread ECL as powerful analytical tool for routinary techniques. To conclude, the results obtained are of strong value to largely increase the sensitivity of luminescence techniques, thus fulfilling the expectation we had at the beginning of this research work.

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Terapie sistemiche dell'epatocarcinoma (HCC): dalla preclinica alla clinica

Introduzione Attualmente i principali punti critici del trattamento dell’HCC avanzato sono: 1) la mancanza di predittori di risposta alla terapia con sorafenib, 2) lo sviluppo resistenze al sorafenib, 3) la mancanza di terapie di seconda linea codificate. Scopo della tesi 1) ricerca di predittori clinico-laboratoristici di risposta al sorafenib in pazienti ambulatoriali con HCC; 2) valutazione dell’impatto della sospensione temporanea-definitiva del sorafenib in un modello murino di HCC mediante tecniche ecografiche; 3) valutazione dell’efficacia della capecitabina metronomica come seconda linea dell’HCC non responsivo a sorafenib. Risultati Studio-1: 94 pazienti con HCC trattato con sorafenib: a presenza di metastasi e PVT-neoplastica non sembra inficiare l’efficacia del sorafenib. AFP basale <19 ng/ml è risultata predittrice di maggiore sopravvivenza, mentre lo sviluppo di nausea di una peggiore sopravvivenza. Studio -2: 14 topi con xenografts di HCC: gruppo-1 trattato con placebo, gruppo-2 trattato con sorafenib con interruzione temporanea del farmaco e gruppo-3 trattato con sorafenib con sospensione definitiva del sorafenib. La CEUS targettata per il VEGFR2 ha mostrato al giorno 13 valori maggiori di dTE nel gruppo-3 confermato da un aumento del VEGFR2 al Western-Blot. I tumori del gruppo-2 dopo 2 giorni di ritrattamento, hanno mostrato un aumento dell’elasticità tissutale all’elastonografia. Studio-3:19 pazienti trattati con capecitabina metronomica dopo sorafenib. Il TTP è stato di 5 mesi (95% CI 0-10), la PFS di 3,6 mesi (95% CI 2,8-4,3) ed la OS di 6,3 mesi (95% CI 4-8,6). Conclusioni Lo sviluppo di nausea ed astenia ed AFP basale >19, sono risultati predittivi di una minore risposta al sorafenib. La sospensione temporanea del sorafenib in un modello murino di HCC non impedisce il ripristino della risposta tumorale, mentre una interruzione definitiva tende a stimolare un “effetto rebound” dell’angiogenesi. La capecitabina metronomica dopo sorafenib ha mostrato una discreta attività anti-neoplastica ed una sicurezza accettabile.

Automotive Radars:towards smarter vehicles

Radars are expected to become the main sensors in various civilian applications, especially for autonomous driving. Their success is mainly due to the availability of low cost integrated devices, equipped with compact antenna arrays, and computationally efficient signal processing techniques. This thesis focuses on the study and the development of different deterministic and learning based techniques for colocated multiple-input multiple-output (MIMO) radars. In particular, after providing an overview on the architecture of these devices, the problem of detecting and estimating multiple targets in stepped frequency continuous wave (SFCW) MIMO radar systems is investigated and different deterministic techniques solving it are illustrated. Moreover, novel solutions, based on an approximate maximum likelihood approach, are developed. The accuracy achieved by all the considered algorithms is assessed on the basis of the raw data acquired from low power wideband radar devices. The results demonstrate that the developed algorithms achieve reasonable accuracies, but at the price of different computational efforts. Another important technical problem investigated in this thesis concerns the exploitation of machine learning and deep learning techniques in the field of colocated MIMO radars. In this thesis, after providing a comprehensive overview of the machine learning and deep learning techniques currently being considered for use in MIMO radar systems, their performance in two different applications is assessed on the basis of synthetically generated and experimental datasets acquired through a commercial frequency modulated continuous wave (FMCW) MIMO radar. Finally, the application of colocated MIMO radars to autonomous driving in smart agriculture is illustrated.

Study of Bone Biomineralization in 2D and 3D Cultures of a Human Osteosarcoma Cell Line As Osteoblast-like Model

This PhD project focuses on the study of the early stages of bone biomineralization in 2D and 3D cultures of osteoblast-like SaOS-2 osteosarcoma cells, exposed to an osteogenic cocktail. The efficacy of osteogenic treatment was assessed on 2D cell cultures after 7 days. A large calcium minerals production, an overexpression of osteogenic markers and of alkaline phosphatase activity occurred in treated samples. TEM microscopy and cryo-XANES micro-spectroscopy were performed for localizing and characterizing Ca-depositions. These techniques revealed a different localization and chemical composition of Ca-minerals over time and after treatment. Nevertheless, the Mito stress test showed in treated samples a significant increase in maximal respiration levels associated to an upregulation of mitochondrial biogenesis indicative of an ongoing differentiation process. The 3D cell cultures were realized using two different hydrogels: a commercial collagen type I and a mixture of agarose and lactose-modified chitosan (CTL). Both biomaterials showed good biocompatibility with SaOS-2 cells. The gene expression analysis of SaOS-2 cells on collagen scaffolds indicated an osteogenic commitment after treatment. and Alizarin red staining highlighted the presence of Ca-spots in the differentiated samples. In addition, the intracellular magnesium quantification, and the X-ray microscopy on mineral depositions, suggested the incorporation of Mg during the early stages of bone formation process., SaOS-2 cells treated with osteogenic cocktail produced Ca mineral deposits also on CTL/agarose scaffolds, as confirmed by alizarin red staining. Further studies are underway to evaluate the differentiation also at the genetic level. Thanks to the combination of conventional laboratory methods and synchrotron-based techniques, it has been demonstrated that SaOS-2 is a suitable model for the study of biomineralization in vitro. These results have contributed to a deeper knowledge of biomineralization process in osteosarcoma cells and could provide new evidences about a therapeutic strategy acting on the reversibility of tumorigenicity by osteogenic induction.

Monitoring of New Psychoactive Substances in the hair of patients with a history of addiction. Evaluation of the public health impact.

Introduction. The term New Psychoactive Substances (NPS) encompasses a broad category of drugs which have become available on the market in recent years and whose illicit use for recreational purposes has recently exploded. The analysis of NPS usually requires mass spectrometry based techniques. The aim of our study was to define the preva-lence of NPS consumption in patients with a history of drug addiction followed by Public Services for Pathological Addictions, with the purpose of highlighting the effective presence of NPS within the area of Bologna and evaluating their association with classical drugs of abuse (DOA). Materials and methods. Sustained by literature, a multi-analyte UHPLC-MS/MS method for the identification of 127 NPS (phenethylamines, arylcyclohexylamines, synthetic opioids, tryptamines, synthetic cannabinoids, synthetic cathinones, designer benzodiazepines) and 15 classic drugs of abuse (DOA) in hair samples was developed and validated according to International Guidelines [112]. Samples pretreatment consisted of washing steps and overnight incubation at 45°C in an acid mixture of methanol and water. After cooling, supernatant were injected into the chromatographic system coupled with a tandem mass spectrometry detector. Results. Successful validation was achieved for almost all of the compounds. The method met all the required technical parameters. LOQ was set from 4 to 80 pg/mg The developed method was applied to 107 cases (85 males and 22 females) of clinical interest. Out of 85 hair samples resulting positive to classical drugs of abuse, NPS were found in twelve (8 male and 4 female). Conclusion. The present methodology represents an easy, low cost, wide-panel method for the de-tection of 127 NPS and 15 DOA in hair samples. Such multi-analyte methods facilitates the study of the prevalence of drugs abused that will enable the competent control authorities to obtain evi-dence-based reports regarding the critical spread of the threat represented by NPS.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).