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Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions
Get PDFThe objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback.
These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects.
In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications:
• At test bench
• In small-markets like large off-road engines
The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor.
In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket.
From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications.
Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines
A take on complexity: bio-molecules and human metabolism interaction modelling for health and nutrition with machine learning
Get PDFThe advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a
complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of
omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns.
The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure
Efficacy and safety of immunotherapy added to standard-of-care therapy for newly diagnosed Multiple Myeloma patients eligible to high-dose chemotherapy
Get PDFLo scenario terapeutico del Mieloma Multiplo (MM) si è ampiamente evoluto nelle ultime decadi con l’introduzione di un numero sempre maggiore di combinazioni di nuovi farmaci molto efficaci. In tal contesto, spicca Daratumumab (dara), grazie ai suoi dati di efficacia e di sicurezza dimostrati sia nel setting del paziente ricaduto/refrattario che di nuova diagnosi. Lo scopo del presente studio è quello di aggiungere dati circa la combinazione di dara con la terapia standard nel contesto di un programma trapiantologico per pazienti di nuova diagnosi candidabili alla chemioterapia ad alte dosi, con un particolare focus sull’impatto dell’anticorpo monoclonale sulla raccolta delle cellule staminali (PBSC). Sono stati analizzati 41 pazienti trattati presso il nostro centro nell’ambito di due studi clinici (EMN17 e EMN18). Con un follow-up mediano pari a 19 mesi, dara aggiunto alla terapia standard ha dimostrato un’ottima efficacia, in termini di risposte profonde e sopravvivenza libera da malattia, ed un buon profilo di sicurezza, senza tossicità aggiuntive o inaspettate. Inoltre, nello studio registrativo CASSIOPEIA dara non ha avuto un impatto negativo sulla raccolta delle PBSC; infatti, nei pazienti sottoposti a dara il numero il numero mediano di PBSC raccolte è risultato inferiore e questi hanno necessitato più frequentemente di Plerixafor, senza, tuttavia, modifiche nell’iter trapiantologico rispetto al gruppo di controllo. Analogamente, nella nostra analisi i pazienti del gruppo dara hanno utilizzato maggiormente Plerixafor ed è emerso come questi possano beneficiare da un dosaggio maggiore di Ciclofosfamide mobilizzante (3 g/mq rispetto 2 g/mq). Durante lo svolgimento del presente progetto dara è stato approvato in pratica clinica prima in Europa (2020) e poi in Italia (2021). Il presente studio ha confermato come dara aggiunto ad un regime di induzione Bortezomib-based rappresenti un nuovo standard of care per i pazienti con MM di nuova diagnosi eleggibili alla chemioterapia ad alte dosi.The therapeutic scenario of Multiple Myeloma (MM) patients has dramatically evolved in the last decades, due to the increasing availability of novel drug-based combinations. Particularly, Daratumumab (dara) showed great results in terms of efficacy and safety, that led to its approval in clinical practice. The purpose of this study is to add data about dara in combination with the standard of care (SOC) for newly diagnosed MM patients eligible to high-dose chemotherapy, with a particular focus on its impact on the collection of stem cells. We retrospectively analyzed 41 patients treated at our center into two clinical trials (EMN17 and EMN18). With a median follow-up of 19 months, the addition of dara to the SOC confirmed a clinical benefit in terms of deep responses (≥VGPR) and progression free survival (PFS), without additional or unexpected toxicities. Moreover, in the literature dara does not seem to have an impact on the collection of stem cells. Specifically, in the CASSIOPEIA pivotal trial, the median number of collected stem cells was lower for patients who were treated with dara than those in the control group, with a greater need to use Plerixafor. Despite this, no differences in terms of successful transplantation emerged between the two groups. Similarly, in our analysis, patients who were treated with dara required more frequently the use of Plerixafor and they could have a benefit in terms of number of collected stem cells from a higher dosage of mobilizing chemotherapy (2 vs 3 grams per square meter). During the development of this project, dara has been approved in clinical practice in Europe (2020) and, very recently, in Italy (2021). The present study confirmed that dara added to bortezomib-base induction regimens represents a new SOC for newly diagnosed MM patients eligible to high-dose chemotherapy
Physiological and biochemical adaptation to salinity in wild halophytes suitable for Mediterranean agriculture
Get PDFDue to the accelerating processes of soil salinization and shortage of fresh water, the practice of saline agriculture is gaining momentum in many areas of the world.
However, there are some concerns that using saline water for irrigation may be non-environmentally sustainable, with potential to cause irreversible soil degradation. In addition, there is a lack of information on the morphological, physiological, and biochemical changes that can occur in plants when irrigated with saline water.
In light of the above, the major aim of this work was to investigate the effects of a range of water salinity levels and irrigation regimes on the performances of salt tolerant species promising as future crop plants for saline agriculture. The following objectives were addressed:
To determine the effects of different water regimes (leaching irrigation vs. no leaching irrigation) with water at increasing salinity concentrations on the growth, ion accumulation and water relations of Sorghum bicolor plants grown under saline soil conditions.
To describe the germination response of Salicornia europaea seeds across a wide range of water salinity levels through six reliable indices for screening salinity tolerance at the seed germination stage.
To explore the different physiological responses of six wild halophytes commonly found in the Mediterranean area (Artemisia absinthium, Artemisia vulgaris, Atriplex halimus, Chenopodium album, Salsola komarovii, and Sanguisorba minor), and rank their tolerance after exposure to growing levels of water salinity.
To identify the main adaptation mechanisms that distinguish C3 from C4 halophytes when exposed to increasing salinity in the growth media, through a comparative study between the C3 species Atriplex hortensis and the C4 species Atriplex halimus.
To identify the main adaptation mechanisms that distinguish annual from perennial halophytes when exposed to severe conditions of salinity and drought, through a comparative analysis between two annual Salicornia spp. and the perennial Sarcocornia fruticosa
Design, development and guidance of the Airborne’s quadrotor
Get PDFThe main goal of the Airborne project is to develop, at technology readiness level 8 (TRL8), a few selected robotic aerial technologies for quick localization of victims by avalanches by equipping drones with two forefront sensors used in SAR operations in case of avalanches, namely the ARVA and RECCO. This thesis focuses on the design, development, and guidance of the TRL8 quadrotor developed during the project. We present and describe the design method that allowed us to obtain an EMI shielded UAV capable of integrating both RECCO and ARVA sensors. Besides, is presented the avionics and power train design and building procedure in order to obtain a modular UAV frame that can be easily carried by rescuers and achieves all the performance benchmarks of the project. Additionally, in addition to the onboard algorithms, a multivariate regressive convolutional neural network whose goal is the localization of the ARVA signal is presented. On guidance, the automatic flight procedure is described, and the onboard waypoint generator algorithm is presented. The goal of this algorithm is the generation and execution of an automatic grid pattern without the need to know the map in advance and without the support of a control ground station (CGS). Moreover, we present an iterative trajectory planner that does not need pre-knowledge of the map and uses Bézier curves to address optimal, dynamically feasible, safe, and re-plannable trajectories. The goal is to develop a method that allows local and fast replannings in case of an obstacle pop up or if some waypoints change. This makes the novel planner suitable to be applied in SAR operations. The introduction of the final version of the quadrotor is supported by internal flight tests and field tests performed in real operative scenarios by the Club Alpino Italiano (CAI)
Perceiving the 3d world from single images
Get PDFDepth represents a crucial piece of information in many practical applications, such as obstacle avoidance and environment mapping. This information can be provided either by active sensors, such as LiDARs, or by passive devices like cameras. A popular passive device is the binocular rig, which allows triangulating the depth of the scene through two synchronized and aligned cameras. However, many devices that are already available in several infrastructures are monocular passive sensors, such as most of the surveillance cameras. The intrinsic ambiguity of the problem makes monocular depth estimation a challenging task. Nevertheless, the recent progress of deep learning strategies is paving the way towards a new class of algorithms able to handle this complexity.
This work addresses many relevant topics related to the monocular depth estimation problem. It presents networks capable of predicting accurate depth values even on embedded devices and without the need of expensive ground-truth labels at training time. Moreover, it introduces strategies to estimate the uncertainty of these models, and it shows that monocular networks can easily generate training labels for different tasks at scale. Finally, it evaluates off-the-shelf monocular depth predictors for the relevant use case of social distance monitoring, and shows how this technology allows to overcome already existing strategies limitations
Neuroprotective role of nutraceutical and phytochemical components
Get PDFNeurodegenerative diseases (NDs) are characterized by a multifactorial etiology, in which oxidative stress and inflammation are the main causative factors. For this reason, increasing attention is being paid to the characterization and the identification of nutraceuticals and phytochemicals with intrinsic pleiotropic activity. Moreover, in a Circular Economy perspective, these natural compounds can be obtained also from renewable resources derived from the food industry by-products and can be used for both preventive and therapeutic purposes.
The aim of this PhD program was to identify nutraceuticals and phytochemicals, both as extracts and pure compounds, and obtained from both plant and renewable sources, which due to their antioxidant and anti-inflammatory properties, were able to counteract cellular and molecular alterations that characterize NDs. Their neuroprotective potential has been evaluated in an in vitro model of neuroinflammation (the LPS-activated BV-2 microglial cell line), and/or in an in vitro model of neuronal oxidative stress (the neuron-like SH-SY5Y cell line differentiated with retinoic acid and exposed to H2O2).
Four different projects, although deeply linked by the aforementioned common goal, have been discussed in this thesis:
1_ Impact of phenolic profile of different cherry cultivars on the potential neuroprotective effect in SH-SY5Y cells.
2_Anti-inflammatory activities of Spilanthol-rich essential oil from Acmella oleracea (L.).
3_Study of the anti-inflammatory activity of novel tacrine derivatives with lipids extracted from cashew nutshell liquid.
4_Coffee Silverskin (CSS) and Spent Coffee Grounds (SCG): coffee industry by-products as a promising source of neuroprotective agents.
In general, it is, therefore, possible to conclude that the natural compounds studied in this thesis have been proven, due to their antioxidant and/or anti-inflammatory properties, to be valid preventive and therapeutic strategies for the treatment of NDs, to improve the life quality of these patients and of the general population by preventing and combating the onset of these deleterious diseases
Study of Bone Biomineralization in 2D and 3D Cultures of a Human Osteosarcoma Cell Line As Osteoblast-like Model
Get PDFThis 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
Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens
Get PDFAir pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years.
Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities.
This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements
Subsidence history, thermal maturity, and structural inversion of the Greater Caucasus-Kura-Adjara-Trialeti basin system of central-eastern Georgia
Get PDFThis study aims at defining the tectonic evolution of a portion of the Caucasian region, in Georgia, which experienced a complex pattern of deformation events throughout Mesozoic and Cenozoic times. An integrated approach was applied to unravel the thermo-tectonic history of three inverted sedimentary basins from burial to exhumation. Additionally, this dissertation provides examples of structural inversion of sedimentary basins in response to far-field transmission of compressional stresses away from collision zones, contributing to elucidate the dynamics of stress partitioning during continental collisions.
The Adjara-Trialeti fold-and-thrust belt in south-western Georgia results from the structural inversion of a Middle Eocene continental back-arc rift basin opened as a consequence of the Northern Neotethys slab rollback. This study quantitatively defines the subsidence and exhumation history of the Adjara-Trialeti basin, constraining its Middle Miocene inception of structural inversion.
The western Kura Basin is a flexural foreland basin trapped between the Lesser Caucasus to the south and the Greater Caucasus to the north. This study constrains successive and competing episodes of flexural subsidence during Oligocene-Miocene times, followed by partial inversion through thick- and thin-skinned tectonics in response to continued convergence between the adjacent, oppositely verging orogenic belts.
The Greater Caucasus results from the structural inversion of a Jurassic continental back-arc basin, but the timing of its growth is still debated. An across-strike transect in its southern central domain was studied, indicating that this sector of the Greater Caucasus experienced two phases of structural inversion during Late Cretaceous-Paleocene and Late Miocene times. Overall, the dataset presented in this dissertation points to a complex and episodic history of incremental deformation, characterised by successive phases of extensional and compressional tectonics which developed in response to sequential terrane accretion at the southwestern margin of Eurasia since Late Cretaceous times, eventually determining the current configuration of the Arabia-Eurasia collision zone