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Data-driven approaches for enhanced on-board fault diagnosis and emission monitoring to support Euro 7 standard implementation
Get PDFThe European Commission has introduced the Euro 7 standard to reduce pollutant emissions in the transport sector. This regulation emphasizes the role of On-Board Monitoring (OBM) in ensuring low emissions throughout a vehicle’s lifespan, considering system aging and potential faults. The research presented in this dissertation explores data-driven methods for detecting emission-related engine faults, supporting On-Board Diagnostics (OBD), and enabling real-time emission monitoring under various operating conditions, key challenges posed by Euro 7 OBM requirements.
To achieve this, common emission-related engine faults were simulated using a validated 0-D model of a Diesel Plug-in Hybrid Electric Vehicle (PHEV). The study assessed their impact on NOx emissions and identified useful on-board signals for OBM-oriented models. Various classifiers were evaluated based on accuracy, training time, and prediction speed, with Tree, Ensemble, and Neural Networks emerging as the best-performing ones. These models were further optimized using Bayesian techniques to enhance classification accuracy.
The same methodology was applied to develop OBM-oriented regression models for NOx emission estimation. Using the same dataset, regression models were trained to correct the reference ECU model when non-nominal conditions are considered. These models leverage on-board signals to refine NOx predictions in presence of engine faults, significantly reducing estimation errors. Tests across different driving cycles and fault conditions confirmed high accuracy, good interpolation, and robust generalization. Neural Networks outperformed other models, offering the best balance between accuracy, generalization, and complexity.
For real-world application, the models were deployed on a Raspberry Pi and tested in a Hardware-in-the-Loop (HiL) environment, demonstrating feasibility for low-cost on-board integration via CAN-bus communication. Further validation was conducted using real test bench data, confirming the models' effectiveness and potential to help manufacturers comply with Euro 7 regulations.
This research was conducted at the Green Mobility Research Lab, a collaboration between the University of Bologna and FEV Italia s.r.l
Innovative 2D materials for reducing friction in tribological systems: ab initio simulations coupled with experiments
Get PDFTribology, the science of friction, wear, and lubrication, plays a crucial role in improving energy efficiency across industrial and everyday applications. Controlling friction can lead to significant energy savings, as friction and wear contribute to nearly 20% of global energy consumption. Advances in tribology, particularly through innovative materials, offer substantial economic and environmental benefits, making it essential for technological progress and sustainability. Lubrication technologies rely on both liquid and solid lubricants. While liquid lubricants, such as synthetic oils, form protective films to reduce friction, they may fail under extreme conditions like high temperatures or vacuum. In such cases, solid lubricants, including graphite, diamond-like carbon (DLC), and transition metal dichalcogenides (TMDs) like MoS2 and WSe2, provide a more effective solution. These layered materials facilitate low-shear interlayer sliding, making them ideal for aerospace and precision engineering. Emerging 2D materials, such as MXenes and Transition Metal Carbo-Chalcogenides (TMCCs), combine mechanical strength with self-lubrication, representing a promising frontier in tribology. Computational simulations, particularly quantum mechanical approaches, play a pivotal role in understanding tribological phenomena at the atomic level. These methods allow for the study of interlayer sliding, adhesion, oxidation, and tribochemical reactions, guiding the design of new lubricant materials while reducing experimental costs.
This thesis explores the tribological properties of advanced 2D materials through a combination of simulations and experiments. It investigates (i) the frictional behavior of titanium-based MXenes via density functional theory (DFT), (ii) the synergy between MXene-MoS2 composite coatings, (iii) the in-operando formation of MoSe2 and WSe2 lubricious layers from selenium nanoparticles, and (iv) the promising tribological performance of TMCCs (Nb2S2C and Ta2S2C). These findings contribute to the development of next-generation solid lubricants for demanding applications
Treatment with valacyclovir for prevention of congenital cytomegalovirus infection: a multicenter observational study (MEGAL-ITALI)
Get PDFL’obiettivo di questo studio osservazionale multicentrico (MEGAL-ITALI) è stato valutare l’impatto dell’introduzione del Valaciclovir (VCV) nella pratica clinica per la prevenzione dell’infezione congenita da CMV (cCMV). Gli esiti delle donne trattate con VCV e dei loro feti/neonati sono stati confrontati con quelli di una coorte retrospettiva non trattata, osservata tra il 2010 e il 2020. Sono state incluse le gestanti con diagnosi di infezione primaria da CMV nel periodo periconcezionale o entro la 24a settimana di gestazione. L’obiettivo primario è stato valutare il tasso di trasmissione materno-fetale al momento dell’amniocentesi. Tra gli obiettivi secondari sono stati inclusi le interruzioni della gravidanza, la diagnosi di infezione congenita alla nascita, l'infezione sintomatica alla nascita e un esito composito (interruzione della gravidanza o trasmissione alla nascita). Sono state coinvolte 447 donne in gravidanza provenienti da 10 centri, di cui 205 trattate con Valaciclovir e 242 non trattate. Il trattamento con VCV è stato associato a una significativa riduzione della diagnosi di cCMV al momento dell'amniocentesi (aOR, 0.39; IC al 90%, 0.22-0.68; p = 0.005, riduzione relativa 61%), delle interruzioni di gravidanza (aOR, 0.36; IC al 90%, 0.17-0.75; p = 0.0021, riduzione relativa 64%), e dell'infezione cCMV sintomatica alla nascita (aOR, 0.17; IC al 90%, 0.06-0.49; p = 0.006, riduzione relativa 83%). Il trattamento non ha avuto effetti significativi sul tasso complessivo di diagnosi di cCMV alla nascita (aOR, 0.85; IC al 90%, 0.57-1.26; p = 0.500), sebbene l'outcome composito (interruzione della gravidanza o diagnosi di cCMV alla nascita) è stato più frequente nel gruppo senza VCV (aOR, 0.62; IC al 90%, 0.44-0.88; p=0.024). I nostri dati confermano che il Valaciclovir riduce significativamente la diagnosi di cCMV al momento dell'amniocentesi e dimostrano che il trattamento è associato a una riduzione delle interruzioni di gravidanza e delle infezioni cCMV sintomatiche alla nascita.The objective of this multicenter observational study (MEGAL-ITALI) was to evaluate the effect of the introduction of valacyclovir (VCV) in the clinical practice for the prevention of congenital CMV infection (cCMV). The outcomes of women who received VCV treatment and their fetuses/newborns were compared with those of a retrospective untreated cohort, observed between 2010 and 2020. The inclusion criterion was the diagnosis of CMV primary infection occurring in the periconceptional period or up to the 24th week of gestation. The primary outcome was the transmission by the time of amniocentesis. The secondary outcomes were termination of pregnancy, transmission at birth, symptomatic infection at birth and a composite outcome (termination of pregnancy or transmission at birth).
A total of 447 pregnant women from 10 centers were included, 205 women treated with valacyclovir and 242 women not treated with valacyclovir. Valacyclovir treatment was significantly associated with a reduction of the diagnosis of congenital CMV infection by the time of amniocentesis (aOR, 0.39; 90% CI, 0.22-0.68; p = 0.005, relative reduction of 61%), termination of pregnancy (aOR, 0.36; 90% CI, 0.17-0.75; p = 0.0021, relative reduction of 64%), symptomatic cCMV infection at birth (aOR, 0.17; 90% CI, 0.06-0.49; p = 0.006, relative reduction of 83%). The treatment had no significant effect on the rate of diagnosis of cCMV infection at birth (aOR, 0.85; 90% CI, 0.57-1.26; p = 0.500), but the composite outcome (termination of pregnancy or diagnosis of cCMV infection at birth) occurred more frequently in the no-VCV group (aOR, 0.62; 90% CI, 0.44-0.88; p = 0.024). Our data confirm that valacyclovir significantly reduces the rate of cCMV diagnosis at the time of amniocentesis. Furthermore, the treatment is associated with a reduction of termination of pregnancy and symptomatic cCMV infection at birth
Tracing star cluster formation and evolution with stellar kinematics
Get PDFIt is well established that star clusters are valuable probes in Astronomy across a wide range of disciplines from cosmology to stellar evolution. Indeed, star clusters are efficient tracers of intense star formation episodes across cosmic time and rich cradles of stellar-mass black holes (BHs), which are prime sources of gravitational waves. However, fundamental questions about the possible unifying principles governing their formation are yet unanswered. In addition, whether clusters form through the monolithic collapse of the gas cloud or the hierarchical merger of clumps is still an intense matter of debate. Despite tremendous observational and theoretical efforts, our understanding of star cluster formation and the actual role of the different underlying physical processes is still in its infancy. This thesis explores this long-standing problem with a multi-faceted approach, largely based on the dynamical study of very young clusters and associations in nearby star-forming regions and old massive clusters in the Galactic halo. Local star clusters represent the ideal laboratory for constraining the physical mechanisms at the basis of cluster formation as they can be resolved into individual stars, and thus they can be studied with a level of detail that cannot be achieved for distant systems. To this aim, this thesis uses a multi-diagnostic and multi-instrument approach, which is largely based on Gaia, Hubble Space Telescope (HST), and properly selected spectroscopic surveys (such as observations from the Multi Unit Spectroscopic Explorer, MUSE).
We also used tailored N-body and Monte Carlo simulations to interpret the observed stellar cluster properties and to constrain the initial physical conditions for cluster formation and evolution. The analysis focused on two main aspects: i) the study of the early phases of cluster assembly and survival and ii) the long-term evolution of star clusters and the role of massive compact objects, such as BHs
Design of high-performance electronic power converters based on GaN-on-Si semiconductors devices
Get PDFIn recent times, automotive world has been witnessing a paradigm change: hybrid, plug-in hybrid and battery electric vehicles (HEVs, PHEVs, BEVs) are progressively replacing the internal combustion engine vehicles (ICEVs) in circulation. A strong motivation derives from the carbon dioxide (CO2) emission performance standards that have been set by several legislative institutions aiming to tackle climate change challenges, as in the case of Regulation EU 2019/631 of the European Parliament. In this context, power electronics is assuming a pivotal role in automotive industry. In fact, an increase of just few percentage points in terms of efficiency or power density can make a huge difference for the driving range, since they have a direct influence on size, weight, charging time and cost of the EV major components (batteries, electric motors, and power electronic converters). Considering also the concerns related to the low profit margins, the development of top-performing and cost-effective power converters (AC/DC, DC/DC, DC/AC) is of crucial importance for automotive players. In the last decades, the Wide Band Gap (WBG) technology, based on Gallium Nitride and Silicon Carbide semiconductors, has had a disruptive impact on power electronics, paving the way for a new generation of power components, targeting not only the automotive market but also other applications such as home appliances, mobile charges, datacenters, railways, robotics and industrial motor drives. The objective of this thesis is to explain the design approach that has been followed to pursue the development of a top notch GaN-based Bi-directional OBC (On-Board Charger) prototype for automotive application, also emphasizing the challenges posed by the adoption of such technology. The final product, after being fully tested and certified, will enter mass production exhibiting state-of-the-art performance
Mastering power control in HPC CPUs: a journey through modeling, algorithms, and hardware insights
Get PDFHigh-Performance Computing (HPC) has rapidly evolved to meet the increasing computational demands of data-intensive fields such as climate modeling, artificial intelligence, and physics research. This growth is driven by the demand for massive computational power that spans various demographics, including researchers, industry professionals, and governments, reaching end-users with the rise of Large Language Models (LLMs). Emerging trends in HPC, including many-core and heterogeneous architectures, present significant complexity, especially as they adopt advanced chiplet-based designs with specialized accelerators. These innovations introduce challenges that necessitate sophisticated control strategies to manage power and thermal dynamics effectively. The open-source RISC-V ISA has spurred the entry of new players into this market segment. However, despite advances in hardware design, there remains a noticeable gap in research concerning on-chip power and thermal control strategies. Existing efforts have largely focused on high-level, software-based control mechanisms at the operating system or application level, leaving low-level control methods underexplored. This thesis addresses this gap by developing and evaluating advanced low-level control algorithms for power and thermal management in HPC environments. It introduces a comprehensive modeling framework that captures essential system dynamics and highlights the unique challenges of low-level control, such as leakage power management, actuator non-idealities, and coupling constraints. The proposed control strategies, including fuzzy-inspired and Model Predictive Control (MPC) approaches, are validated using a Hardware-in-the-Loop (HIL) testing platform to demonstrate their effectiveness in real-time scenarios. Results indicate that these advanced controllers significantly enhance thermal regulation, minimize performance degradation, and achieve superior energy efficiency. The thesis concludes by outlining future research directions, such as integrating machine learning for predictive control and exploring distributed control frameworks to further optimize HPC system performance
Metabolic dysfunction-associated steatotic liver disease:non-invasive assessment of disease progression
Get PDFThis doctoral thesis, undertaken as part of a joint PhD program between the University of Medicine and Pharmacy "Iuliu Hațieganu," Cluj-Napoca, Romania, and Alma Mater Studiorum University of Bologna, Italy, focuses on metabolic dysfunction-associated steatotic liver disease (MASLD). With its increasing prevalence and potential progression to advanced fibrosis, cirrhosis, and hepatocellular carcinoma, the research explores non-invasive diagnostic techniques and therapeutic strategies aimed at improving disease management and patient outcomes. The study I validated vibration-controlled transient elastography (VCTE)-based scores—Agile 3+, Agile 4, and FAST—in Caucasian MASLD patients for the first time. Agile 3+ and Agile 4 demonstrated excellent diagnostic accuracy in identifying advanced fibrosis and cirrhosis, while the FAST score showed moderate performance in detecting fibrotic metabolic dysfunction-associated steatohepatitis (MASH). Within Study II, a multilevel random effects model meta-analysis established standardized cut-off values for two-dimensional shear wave elastography (2D-SWE) in staging liver fibrosis, supporting its broader clinical use. Study III examined the role of non-selective beta-blockers (NSBB) in preventing the first decompensation event in patients with compensated cirrhosis and clinically significant portal hypertension (CSPH). NSBB significantly reduced the risk of first decompensation, even in patients with small varices and porto-systemic shunts. Notably, type 2 diabetes mellitus (T2DM) emerged as an independent predictor of decompensation, regardless of liver disease etiology. These findings contribute to the refinement of non-invasive fibrosis assessment in MASLD and highlight the therapeutic value of NSBB in cirrhosis management. By improving diagnostic precision and identifying key risk factors for disease progression, this research offers valuable insights for optimizing MASLD patient care and prognosis
Uncovering genetic determinants of disease resistance in durum wheat against causative agents of Yellow Rust and Septoria Tritici Blotch and, environmental adaptation of Zymoseptoria tritici: insights from multi-environment GWAS and pathogen thermal adaptation
Get PDFThis thesis investigates the genetic basis of disease resistance and environmental adaptation in durum wheat and Zymoseptoria tritici, aiming to support sustainable crop management. Chapter 1 explores genetic resistance to Yellow rust (Puccinia striiformis f. sp. tritici) in a panel of 1324 Triticum turgidum landraces from the Mediterranean (Italy, Turkey, Tunisia, Lebanon). Genome-Wide Association Studies (GWAS) using four models (MLM, MLMM, FarmCPU, BLINK) identified 11 significant QTLs on chromosomes 1B, 2A, 2B, 5B, 7A, and 7B. Haplotype analysis revealed allelic diversity, origins, and phenotypic effects, improving knowledge of resistant variants. Subpopulation-specific GWAS further dissected rare alleles and QTL origins. Chapter 2 examines genetic resistance to Septoria tritici blotch (Zymoseptoria tritici) in a panel of 510 durum wheat landraces from the CEREALMED collection, assessed in Cadriano (Bologna) under artificial inoculation. Disease severity was scored at two timepoints to estimate the Area Under the Disease Progression Curve (AUDPC). GWAS identified eight QTLs across the panel and 16 within subpopulations, including novel loci expanding breeding targets for Stb resistance. Chapter 3 investigates genetic determinants of thermal adaptation in Z. tritici using 238 isolates from eight Euro-Mediterranean countries. GWAS linked key genes—heat shock proteins, chaperones, and zinc finger proteins—to optimal growth temperature (Topt), thermal performance breadth (TPB80), and pathogenicity metrics (PLACL, PycLes) assessed via high-throughput phenotyping. These findings highlight essential genetic targets for breeding programs aimed at disease resistance and climate resilience. By enhancing knowledge of host-pathogen interactions and adaptation, this study contributes to sustainable agriculture and supports Green Deal goals to reduce chemical inputs while improving environmental resilience
Development of biosensors for the rapid and low-cost analysis of industrial by-products and wastewater with a circular economy vision
Get PDFBiosensors have emerged as essential tools in addressing critical global challenges, offering real-time, cost-effective, and user-friendly analytical capabilities that contribute to social progress. By integrating biological recognition elements, such as enzymes, proteins, and cells, these devices play an essential role in different fields, from environmental monitoring and food safety to healthcare in detecting specific analytes with high sensitivity and specificity. Thanks to the advances in fabrication techniques, sustainable materials, and portable detection systems have further enhanced their practicality, aligning with global sustainability goals. During my Ph.D. research, I focused the attention on the development of bioluminescent and colorimetric sensing systems integrated with fabrication techniques like wax printing, 3D printing, and CNC milling. These methods facilitated the creation of simple devices capable of detecting pollutants, monitoring toxicological effects, and assessing food freshness with minimal infrastructure. In addition, nanomaterials have been coupled with advanced bioluminescent proteins to significantly enhance the analytical performance of biosensors in terms of sensitivity, specificity, and stability. Portable detection systems like smartphones and cost-effective optical detectors were explored to ensure economical accessibility, suitability, and field applicability. This work focuses on portable and low-cost biosensing devices for bioactivity and toxicity evaluation, emphasizing the importance of sustainability in biosensor design, which contributes to the development of tools that address global needs while minimizing environmental impact. Future work aims to translate these advancements into paper-based multiplexed sensing platforms for the simultaneous detection of multiple analytes. Efforts will also focus on improving the shelf-life of these systems to ensure robustness and applicability in different conditions
Navigating the digital frontier: opportunities and challenges of virtual reality in mental health
Get PDFThis dissertation investigates the potential of virtual reality (VR) to transform mental health care by fostering empathy, promoting well-being, and alleviating psychological distress. It highlights VR’s role as a positive technology, capable of enhancing eudaimonic well-being by fostering purpose, engagement, and personal growth, while complementing its established benefits in reducing negative mental health symptoms. The first study, a systematic review, explores how VR and other digital technologies can enhance empathy among healthcare professionals, a key factor in patient satisfaction and treatment adherence. It demonstrates VR's capacity to immerse clinicians and health workers in patients’ perspectives, promoting empathy and emotional insight. The second study reviews the use of VR interventions to promote positive mental health, finding strong evidence of VR’s efficacy in reducing stress and fostering well-being but identifying gaps in its impact on eudaimonic well-being. Insights from this review informed the development of a VR program evaluated in a pilot study. The third study examines the feasibility and effectiveness of the H.O.M.E._Positivity VR program in reducing psychological distress and enhancing well-being among young adults. The results demonstrate significant improvements in mental health, suggesting that VR can foster positive emotions and psychological resilience. A larger follow-up study is underway to validate these findings. The general discussion synthesizes the findings, addressing theoretical and practical implications, including challenges such as inconsistent definitions of empathy and barriers to VR adoption. Recommendations include advancing VR’s integration into clinical practice, scaling interventions, and conducting more robust research to fully realize its potential in mental health care. This work underscores VR’s transformative role in promoting well-being and shaping the future of mental health interventions