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Hydrological and CFD investigations for the flood risk assessment of roads, railways and existing bridges
No full textIncreasingly frequent and intense flood events, combined with the significant industrialization of cities, are placing transportation networks under stress. The loads that roads and railways must withstand are often greater than those originally considered during their design; furthermore, the ageing state of these infrastructures is such that any disturbance, such as a flood, could lead to total or partial traffic interruptions, resulting in socio-economic losses. To support planning and flood risk management, a streamlined methodology is proposed for estimating the risk and potential impacts of inundation on infrastructure. The method assigns a variable risk class (High, Medium, Low, and Null) based on road categories (e.g., highways, main roads, secondary roads, service roads, and others) or railway types (e.g., high-speed or conventional railways), considering both the structural and functional characteristics of the infrastructure (e.g., type of traction, traffic flows) and the magnitude of the expected event. By accounting for the topography of the terrain, the methodology distinguishes between elevated sections (bridges, viaducts) and underground sections (tunnels, underpasses), determining, in addition to the spatial extent of the impacted system and the possible economic damages, the number of flooded railway stations and bridges. During floods, bridges can be partially or completely submerged, having to endure higher hydrodynamic actions that can cause structural collapse. Using Computational Fluid Dynamics (CFD) modelling, the hydrodynamic forces acting on a beam bridge under various hydraulic conditions (under pressure, limited hydraulic clearance) were analysed. The numerical model, calibrated using existing experimental data on forces induced by debris accumulation around piers of different geometries (circular, ogival, semi-circular), and validated with laboratory measurements in the absence of solid material, generated reliable synthetic curves. This practical instrument, transferable to engineers, constitutes a more robust force estimation criterion, targeted at improving the resistance of existing bridges and the design of new ones
Identification of microbiome tailored strategies to improve safety and sustainability of the poultry food system
No full textThis PhD study aimed to identify microbiome tailored strategies to improve safety and sustainability of poultry food system. Three methodological approaches were followed. Initially observational trial was conducted to identify microbiome population that consistently circulating in poultry house with better biosecurity infrastructures. Microbiome biomarkers were characterized by using 16S metagenomic sequencing and analysed with network analysis. Then, systematic literature review was conducted to identify nutritional strategy able to support microbiome markers identified in observational trial. Finally, intervention trial was conducted to test the efficacy of the identified supplement and re-check microbiome dynamics to validate the impact of the intervention on microbiome markers. Link between caeca microbial composition and microbiological safety of the meat was assessed. Observational trial identified Psychrobacter and Ruminiclostridium 9 for their positive actions whereas Bacteroides for negative action. The systematic review identified 91 nutritional interventions that can modulate gut microbiome of broilers and play role in improving performance and control of pathogens. Muramidase was found as the most suitable candidate to support target microbial communities identified in observational trial. Based on observational trial, systematic review, and discussion made with project partners, Muramidase was selected as feed supplement for the intervention trial. Genus level beta diversity showed Muramidase supplementation supported the modulation of caeca microbiome in the interventional trial versus the microbiome composition mapped in the chickens with better biosecurity infrastructures during the observation trial. This shift in the caecal microbiome did not result in better animal performances and blood biomarkers. The study provides insight on the contributions of factors that can possibly affect the microbial dynamics and jeopardize Muramidase supplementation. The findings highlighted the application of shotgun metagenomics sequencing technology for detection of foodborne pathogens. This study strongly encourages future studies on microbiome investigations in different components of broiler food system
Reuse of medical images and segmentation tools to coadiuvate medicalclinical decision
No full textThe widespread use of medical imaging technologies in clinical practice has enabled the creation of large datasets. However, the potential of these data for developing automated decision-support systems remains underutilized due to the lack of capacity to parse and analyze those data. Automated and accurate medical image segmentation is crucial for developing decision-support tools. These segmentations can be valuable for initializing other algorithms, such as simulations, or for quantitative assessments of characteristics across different pathologies. Deep Learning methods require large, annotated datasets, which are not always available in this context. In this work, I have reused existing tools and datasets to enhance or enable the creation of annotated datasets to develop clinical decision-support tools. This work comprises two main tasks: the automated segmentation of the femoral region and the determination of a local reference system to initialize a simulation to estimate femoral fracture risk. A semi-automated tool was developed and validated for the creation of a large segmented dataset, used to test both the automated segmentation algorithm and the automated reference system identification. The automated segmentation tool combines existing deep learning models with graph-cut techniques, while the automated reference system consists of unsupervised techniques that don't require shape priors. The second task focused on the rapid segmentation of white matter hyperintensities in FLAIR MRI sequences of patients with Myotonic Dys-trophy Type 1 or Sickle Cell Disease. Here, a tool initially developed for multiple sclerosis was adapted to the new tasks. This tool, in conjunction with neuroradiologist expertise, was successfully used to create gold-standard segmented datasets and then adapted for the two target conditions. In summary, using existing tools for large-scale data annotation and integrating machine learning models, the research demonstrates more efficient segmentation workflows, paving the way for further advances in automated diagnostics
Injective treatment of knee OA with bone marrow aspirate concentrate: Randomized Clinical Trial comparing combined intra-articular and sub-chondral injection vs intra-articular injection alone
No full textObiettivo: L’infiltrazione intra-articolare di concentrato autologo di midollo osseo (BMAC) si è dimostrata promettente per il trattamento della osteoartrite (OA) di ginocchio. L’azione combinata a livello intra-articolare e sub-condrale potrebbe portare ad un maggiore beneficio clinico. L’obiettivo di questa tesi è valutare mediante un RCT i risultati clinici e radiologici dell’infiltrazione combinata di BMAC rispetto alla sola infiltrazione intra-articolare per il trattamento della OA di ginocchio. Metodi: Sono stati inclusi 86 pazienti con OA mediale (Kellgren-Lawrence 2-3) randomizzati in due gruppi: Gruppo Combinato, gruppo trattamento, in cui 43 pazienti sono stati sottoposti a infiltrazione intra-articolare di BMAC associata ad un’infiltrazione subcondrale del compartimento mediale del ginocchio; Gruppo Intra-articolare, gruppo controllo, in cui 43 pazienti sono stati sottoposti alla sola infiltrazione intra-articolare. Il prelievo di BMAC è stato effettuato dalla cresta iliaca omolaterale e una parte di esso è stata analizzata in laboratorio per caratterizzazione. I pazienti sono stati valutati a i follow-up di 2, 6 e 12 mesi con score clinici (WOMAC, IKDC soggettivo e oggettivo, Tegner, EQ-VAS ed EQ-5D) ed esami radiologici (TC e RM). Risultati: In entrambi i gruppi è stato riportato un miglioramento significativo in tutti gli score a partire dai 2 mesi di follow-up. Non sono state dimostrate differenze significative nei miglioramenti degli scores tra Gruppo Combinato e Gruppo Intra-articolare ai vari follow-up. Non sono state documentate differenze in termini di score di RM e TC tra i gruppi. Due pazienti hanno riferito eventi avversi. Due pazienti, uno per gruppo, sono stati considerati fallimenti, e hanno richiesto un nuovo trattamento infiltrativo/chirurgico. Conclusione: Benché entrambi i gruppi di studio abbiano presentato miglioramenti significativi a tutti i follow-up, i risultati di questo RCT dimostrano come l’aggiunta di infiltrazioni subcondrali di BMAC non migliorino il beneficio clinico apportato dalle singole infiltrazioni intra-articolari per il trattamento dell’OA di ginocchio.Objective: The use of autologous bone marrow aspirate concentrate (BMAC) as intra-articular injections has proven to be a promising approach to treat knee osteoarthritis (OA). There is evidence suggesting that the combined action at the intra-articular and subchondral levels could lead to greater clinical benefit compared to intra-articular infiltration alone. The objective of this thesis is to evaluate through a RCT the clinical and radiological result of combined injection of BMAC compared to intra-articular injection alone to treat knee OA. Methods: 86 patients with medial OA (Kellgren-Lawrence 2-3) were included and randomized into two groups: Combined Group, the treatment group, in which 43 patients underwent intra-articular injection of BMAC associated with a subchondral injection of the medial compartment of the knee; Intra-articular Group, the control group, in which 43 patients underwent intra-articular injection alone. BMAC was collected from the ipsilateral iliac crest and a portion of it was analyzed in the laboratory for characterization. Patients were evaluated at 2, 6 and 12 months follow-up with clinical scores (WOMAC, subjective and objective IKDC, Tegner, EQ-VAS and EQ-5D scores) and imaging (dual energy CT and MRI). Results: Significant improvement was reported in all scores starting from the 2-month follow-up in both groups. No significant differences were demonstrated in the score improvements between the two groups at the various follow-ups. No differences were documented in terms of MRI and CT scores between the two groups. Two patients reported adverse events, considered unrelated to the treatments under study. Two patients, one for each group, were considered failures, and required a new injective/surgical treatment. Conclusion: Although both groups showed significant improvements at all follow-ups, the results of this RCT demonstrate that the addition of subchondral BMAC injections does not improve the clinical benefit provided by single intra-articular injections for the treatment of knee OA
Advancing hyperspectral imaging for cultural heritage: new acquisition systems and multivariate image analysis
No full textCultural heritage serves as a bridge between historical eras and the present, providing invaluable insights into the evolution of human civilisation and artistic expression. However, the complexity and diversity of materials, coupled with their irreversible degradation over time, constantly challenge scientific research to characterize materials used in cultural heritage, addressing conservation and restoration issues.
This dissertation explores advancements in hyperspectral imaging (HSI) systems and chemometric data processing methods for analysing cultural heritage materials non-invasively. The research investigates and enhances the application on several HSI systems:
1.The IRIS system by XGLab: enables the co-registered acquisition of XRF (0-48 keV), VNIR (380–1100 nm) and SWIR (1100–2500 nm) reflectance spectroscopy, and excels in the in-depth analysis of multi-layered paintings.
2.A custom-made ER-FT-IR mapping system: combines a portable FT-IR spectrometer (5500-650 cm-1) with a high-precision motorised stage to explore the capabilities of macro-reflectance mapping in the NIR-MIR region for the investigation of multi-layered paintings.
3.A steady-state HSI system integrates reflectance (400-1000nm) and fluorescence (540-1000nm) imaging for analysis of dyed wool samples, focusing on dye identification and degradation detection.
Given the massive and complex data generated by the HSI, parallel research is being conducted into chemometrics based multivariate image analysis. Several explorations have been carried out, adapted to different data generated by different systems, including data fusion, PCA, wavelet denoising, clustering methods, and MCR-ALS for efficient data reduction, information extraction, interpretation, and visualisation. These techniques are adept at analysing complex painting compositions, stratigraphic information, and recognise the degradation patterns and stages of dye degradation in wool samples.
Overall, this dissertation aims to deepen the understanding of the sophisticated relationship between hyperspectral imaging techniques and data processing explorations, stressing their essential role in the advanced analysis of cultural heritage materials
Development of MS-based analytical approaches for targeted/untargeted analysis of metabolites and bioactive compounds applied to different scientific fields
No full textThis PhD thesis explores the power of analytical methodologies, particularly GC-MS and LC-MS/MS, in understanding biological systems. The initial chapter lays the groundwork by establishing core concepts in analytical chemistry and metabolomics. It emphasizes the crucial role of mass spectrometry in deciphering the complexities of biological systems. A significant focus of the thesis is the development and validation of targeted analytical methods. Chapter 3 details the creation of an LC-MS/MS method designed to quantify bile and oxo-bile acids in fecal samples. Subsequent chapters showcase the application of these methods in various contexts. Chapter 4 demonstrates the use of the bile acid method in a study of dogs suffering from chronic inflammatory enteropathy. By applying this method, researchers aimed to identify potential biomarkers indicative of the pathological state. Chapter 5 presents the development and validation of an LC-MS/MS method for quantifying pollutants in mussels, a common food source. This section explores the challenges of creating a multiresidue method and introduces a novel sample treatment approach. The validated method was then applied in environmental research to assess pollutant accumulation in mussels, providing valuable insights into environmental safety. Chapter 6 highlights the application of GC-MS in a biomedical context. It details the use of this technique to quantify SCFA in a mouse model of Fabry disease exemplifying the potential of GC-MS for disease research and biomarker identification. Chapter 7 emphasizes the crucial role of targeted and untargeted metabolomics in clinical research. It details a comprehensive analysis to identify and quantify biomarkers related to the severity of COVID-19. Overall, this thesis emphasizes the power of targeted and untargeted metabolomics in unveiling the intricate workings of biological systems. The developed and validated analytical methods pave the way for further research in disease diagnosis, environmental monitoring, and food safety
Parallel computing architectures and techniques for heterogeneous acceleration of AI algorithms
No full textThe field of computer architecture is currently marked by a dual pursuit of high performance and efficiency on the one hand and the demand for general, standardized, and reusable solutions on the other.
The rapid growth of artificial intelligence (AI) workloads has significantly influenced computer architecture design from edge to high-performance computing since AI acceleration has become paramount.
This thesis addresses the complex and diverse challenges of accelerating AI workloads, highlighting the crucial factors of performance, area, power constraints, and communication bottlenecks. Various strategies and techniques are proposed to navigate this intricate landscape, acknowledging the need for efficient solutions that cater to a wide range of applications. The proposed strategies and techniques open avenues for further research and the development of the next generation of computer architectures
Photocatalytic production of chemicals from biomass
No full textFurfural (FF) has recently been considered to be one of the most appealing model molecules among the biomass feedstock. One of the most promising upgrading methods for FF is heterogeneous photocatalysis.
To this end, the following thesis work is divided into three parts:
The first part of the work is focused on the hydrogenation of FF to produce FA over pure TiO2 prepared from the microemulsion method with different calcination temperatures. The hydrogenation ability of these catalysts has been verified and compared. It has been found that the TiO2 with a calcination temperature of 400 °C had the best hydrogenation performance with a > 90% yield of FA. The outperformance of 400-TiO2-m_A is related to its suitable crystallinity, specific surface area and particle size. Furthermore, a hydrogen transfer reaction pathway has been proposed based on the analysis of both liquid and gas-phase products.
The second part of the work is focused to the acetalization of FF to produce furaldehyde diethyl acetal (FDA) on various Pd/g-C3N4. The results have indicated that the Pd/g-C3N4 prepared with photo-deposition (PD) with a real loading of 2.8% possesses the best acetalization ability (yield of FDA up to 80%). This has been attributed to the presence of suitable amount of Pd-H and Pd2+.
The third part of the work is in its initial stage and inspired by the conclusion from the second part. In this chapter, the hydrogenation of FF to generate FA was conducted over various Au loaded TiO2. The results suggest that the 1.5 wt.% Au/TiO2 prepared with PD with a particle size of 13 nm obtained the best hydrogenation ability (yield of FA up to 80%), this was attributed to the presence of suitable amount of AuOx
Computer simulations of polymeric functional materials
No full textMolecular Dynamics (MD) is a widely used methodology for investigating the dynamic behavior of soft matter at a level of detail that is hardly accessible by experiments. Fundamentals of MD simulations start by covering Newton's equations, the basis of classical mechanics, and then continue to Force-Field (FF) methods for modeling potential energy surfaces.
MD simulations are commonly carried out at the all-atom level: thanks to tremendous advances in computer techniques and algorithms, millisecond-scale simulations are now feasible for smaller systems and proteins. Yet, since this span may not be enough to cover the time scale of biological events, many research efforts have been devoted to reducing, or in other words, coarse-graining, the atomistic representation in order to extend the time and length scale of simulations.
In this thesis, both the all-atom and coarse-grain methodologies were exploited to investigate two polymeric systems. After introducing the theoretical background of the simulation technique (Chapter 1), Chapter 2 illustrates the application of all-atom MD simulations to the determination of the elastic properties of two well-known semiconducting polymers, i.e. PBTTT and IDTBT, in their amorphous and crystalline phases. The prediction of mechanical properties, namely the Young moduli and the Poisson's ratios, was fulfilled by the calculation of the stiffness tensor using linear elasticity equations.
The last part of the thesis (Chapter 3) reports the study of the self-assembly in solution of the oligomeric sequence GCCG, by performing MD simulations using the coarse-grained oxDNA model. The focus was set on the deduction of the mechanism employed for the self-assembly process and on the verification of a liquid crystalline (LC) ordering that this sequence is predicted to show. We empowered our computational findings with the good agreement that was found with experimental results
Modeling and optimization of leakage current in polypropylene dc-link capacitors
No full textThin polypropylene film is having a strategic role at present because it is the dielectric of choice for high-energy density and high-power density dc-link capacitors. The fast evolution of green energy applications is demanding for higher energy and power density, with expected operating temperature and electric field up to 115°C and above 250V/µm respectively, at which the insulation resistance becomes a key performance factor. Studies on thin film polypropylene are rare in literature and the characterization of ultra-thin films poses several technical challenges. In this work, the use of relatively large capacitance wound film capacitors allowed to improve the sensitivity of conductivity measurements, and to perform multiple breakdown analyses.
Two different commercial polypropylene films were tested. Films and capacitors were submitted to processes aimed at reducing the leakage current at high temperatures and high electric fields. The selected treatments made possible to improve the high temperature performance, with significant reduction of leakage current.
One relevant observation highlighted in this work regards the constant decay of current during dc polarization experiments, combined with the absence of a steady state condition, as reported by few other authors before. The explanation of such observation required the formulation of a novel mechanism, deviating from a pure conductivity model. A theoretical model based on charge injection and electric field distortion was developed to explain the experimental leakage current results, with focus on the decay of leakage current with time. Numerical simulation was implemented and used to validate the model and qualitatively simulate experimental results. According to the proposed model, leakage current includes a dissipative contribute from conduction through the material and a reversible contribute due to injection of charge with formation of space charge and distortion of the internal electric field