Valutazione della sostenibilità ambientale tramite metodologia LCA di sistemi per lo sfruttamento di fonti alternative di energia e materiali

La dissertazione ha riguardato l’analisi di sostenibilità di un sistema agronomico per la produzione di olio vegetale a fini energetici in terreni resi marginali dall’infestazione di nematodi. Il processo indagato ha previsto il sovescio di una coltura con proprietà biofumiganti (brassicacea) coltivata in precessione alla specie oleosa (soia e tabacco) al fine di contrastare il proliferare dell’infestazione nel terreno. Tale sistema agronomico è stato confrontato attraverso una analisi di ciclo di vita (LCA) ad uno scenario di coltivazione della stessa specie oleosa senza precessione di brassica ma con l’utilizzo di 1-3-dicloropropene come sistema di lotta ai nematodi. Allo scopo di completare l’analisi LCA con una valutazione dell’impatto sull’uso del suolo (Land use Impact) generato dai due scenari a confronto, sono stati costruiti due modelli nel software per il calcolo del Soil Conditioning Index (SCI), un indicatore quali-quantitativo della qualità del terreno definito dal Dipartimento per l’Agricoltura degli Stati Uniti d’America (USDA).

Ottimizzazione di un protocollo di anticoagulazione regionale con citrato in CRRT

Ottimizzazione di un protocollo di anticoagulazione regionale con citrato in CRRT Introduzione: La necessità di un'anticoagulazione continua e l'ipofosforemia in corso di trattamento sono problemi costranti in corso di CRRT. Il nostro studio ha cercato di dimostrare l'efficacia e la sicurezza dell'anticoagulazione regionale con citrato in CVVH basato sull'utilizzo di una soluzione di citrato (18 mmol/L) associata ad una soluzione di reinfusione contenente fosfato, recentemente disponibile in commercio, al fine di ridurre l'ipofosfatemia in corso di CRRT. Metodi: Abbiamo utilizzato il nostro protocollo basato sull'utilizzo di una concentrazione di citrato contenente 18 mmol/l associata ad una soluzione di reinfusione contenente fosfato in un piccolo gruppo di pazienti ricoverati in terapia intensiva post-cardiochirurgica, sottoposti a CRRT per insufficienza renale acuta. Risultati: Il nostro protocollo ha garantito un'adeguata durata del circuito ed un ottimo controllo dell'equilibrio acido-base in ogni paziente. E' stata necessaria solo una minima supplementazione di fosforo in alcuni dei pazienti trattati. Conclusioni: Il nostro protocollo basato sull' utilizzo di una soluzione a concentrazione di citrato maggiore (18 mmol/l), permette un miglior controllo dell'equilibrio acido-base rispetto all'utilizzo della soluzione a più bassa concentrazione di citrato. L'uso di una minore dose di citrato ed il mantenimento di un target maggiore di calcio ionizzato all'interno del circuito sono comunque associati ad un'adeguata durata del circuito. I livelli di fosforemia sono rimasti sostanzialmente stabili nella maggior parte dei pazienti trattati, grazie alla presenza di fosfato nella soluzione utilizzata come reinfusione in post-diluizione.

Towards Centrifugal Compressor Stages Virtual Testing

Flow features inside centrifugal compressor stages are very complicated to simulate with numerical tools due to the highly complex geometry and varying gas conditions all across the machine. For this reason, a big effort is currently being made to increase the fidelity of the numerical models during the design and validation phases. Computational Fluid Dynamics (CFD) plays an increasing role in the assessment of the performance prediction of centrifugal compressor stages. Historically, CFD was considered reliable for performance prediction on a qualitatively level, whereas tests were necessary to predict compressors performance on a quantitatively basis. In fact "standard" CFD with only the flow-path and blades included into the computational domain is known to be weak in capturing efficiency level and operating range accurately due to the under-estimation of losses and the lack of secondary flows modeling. This research project aims to fill the gap in accuracy between "standard" CFD and tests data by including a high fidelity reproduction of the gas domain and the use of advanced numerical models and tools introduced in the author's OEM in-house CFD code. In other words, this thesis describes a methodology by which virtual tests can be conducted on single stages and multistage centrifugal compressors in a similar fashion to a typical rig test that guarantee end users to operate machines with a confidence level not achievable before. Furthermore, the new "high fidelity" approach allowed understanding flow phenomena not fully captured before, increasing aerodynamicists capability and confidence in designing high efficiency and high reliable centrifugal compressor stages.

Wave driven devices for the oxygenation of bottom layers

This thesis discusses the design of a system to use wave energy to pump oxygen-rich surface water towards the bottom of the sea. A simple device, called OXYFLUX, is proposed in a scale model and tested in a wave flume in order to validate its supposed theoretical functioning. Once its effectiveness has been demonstrated, a overset mesh, CFD model has been developed and validated by means of the physical model results. Both numerical and physical results show how wave height affects the behavior of the device. Wave heights lower than about 0.5 m overtop the floater and fall into it. As the wave height increases, phase shift between water surface and vertical displacement of the device also increases its influence on the functioning mechanism. In these situations, with wave heights between 0.5 and 0.9 m, the downward flux is due to the higher head established in the water column inside the device respect to the outside wave field. Furthermore, as the wave height grows over 0.9 m, water flux inverts the direction thanks to depression caused by the wave crest pass over the floater. In this situation the wave crest goes over the float but does not go into it and it draws water from the bottom to the surface through the device pipe. By virtue of these results a new shape of the floater has been designed and tested in CFD model. Such new geometry is based on the already known Lazzari’s profile and it aims to grab as much water as possible from the wave crest during the emergence of the floater from the wave field. Results coming from the new device are compared with the first ones in order to identify differences between the two shapes and their possible areas of application.

Basi molecolari ed implicazioni fisio-patologiche dell'alterata glicosilazione di IgG nell'invecchiamento

Introduzione: Le catene N-linked associate al principale sito di N-glicosilazione (Asn297) delle IgG sono di tipo bi-antennario e presentano una grande microeterogeneità in quanto una o entrambe le antenne possono terminare con uno o due residui di acido sialico, galattosio o N-acetilglucosammina ed essere core-fucosilate. Nell’invecchiamento e in malattie infiammatorie aumenta la percentuale di glicani associati alle catene pesanti delle IgG privi del galattosio terminale (IgG-G0). La glicosilazione enzimatica delle proteine è classicamente un processo intracellulare, sebbene recenti studi abbiano messo in evidenza la possibilità di una glicosilazione ecto-cellulare in quanto le piastrine sono ottimi donatori di nucleotidi-zuccheri. Scopo: Misurare le attività delle glicosiltrasferasi ST6Gal1 e B4GalT plasmatiche (potenzialmente responsabili della glicosilazione di proteine plasmatiche) in soggetti di entrambi i sessi e di età compresa tra 5 e 105 anni e correlarle con lo stato di glicosilazione di IgG circolanti (analizzato mediante lectin-blot) e il GlycoAge test, un noto marcatore di invecchiamento, espresso come il logaritmo del rapporto tra gli N-glicani agalattosilati e di-galattosilati associati a glicoproteine plasmatiche. Risultati e conclusioni: I dati ottenuti indicano che: 1) l’attività B4GalT si propone come nuovo marcatore di invecchiamento perché aumenta linearmente con l’età; 2) la ST6Gal1 è maggiormente espressa solo nei bambini e negli over 80; 3) le attività delle due glicosilatransferasi non risultano correlate in modo significativo né tra loro né con il GlycoAge test, indicando che questi tre marcatori siano espressioni di diversi quadri fisio-patologici legati all’invecchiamento; 4) con l’età si ha una predominanza di glicoforme di IgG pro-infiammatorie, ovvero prive dell’acido sialico, del galattosio terminali e del core fucose; 5) l’attività della ST6Gal1 e B4GalT risultano in controtendenza con il grado di sialilazione e galattosilazione delle IgG, indicando quindi che la loro glicosilazione non avviene a livello extracellulare.

Geomorphological and statistical analysis on Ravenna dune fields changes, based on Terrestrial Laser Technology

Coastal sand dunes represent a richness first of all in terms of defense from the sea storms waves and the saltwater ingression; moreover these morphological elements constitute an unique ecosystem of transition between the sea and the land environment. The research about dune system is a strong part of the coastal sciences, since the last century. Nowadays this branch have assumed even more importance for two reasons: on one side the born of brand new technologies, especially related to the Remote Sensing, have increased the researcher possibilities; on the other side the intense urbanization of these days have strongly limited the dune possibilities of development and fragmented what was remaining from the last century. This is particularly true in the Ravenna area, where the industrialization united to the touristic economy and an intense subsidence, have left only few dune ridges residual still active. In this work three different foredune ridges, along the Ravenna coast, have been studied with Laser Scanner technology. This research didn’t limit to analyze volume or spatial difference, but try also to find new ways and new features to monitor this environment. Moreover the author planned a series of test to validate data from Terrestrial Laser Scanner (TLS), with the additional aim of finalize a methodology to test 3D survey accuracy. Data acquired by TLS were then applied on one hand to test some brand new applications, such as Digital Shore Line Analysis System (DSAS) and Computational Fluid Dynamics (CFD), to prove their efficacy in this field; on the other hand the author used TLS data to find any correlation with meteorological indexes (Forcing Factors), linked to sea and wind (Fryberger's method) applying statistical tools, such as the Principal Component Analysis (PCA).

Cognitive and behavioural assessment of parkinsonian syndromes at onset: a longitudinal study

Background: cognitive impairment is one of the non motor features widely descripted in parkinsonian syndrome, it has been related to the motor characteristics of the parkinsonian syndrome, associated with neuropsychiatric dysfunction and the characteristic sleep and autonomic features. It has been shown to be highly prevalent at all disease stages and to contribute significantly to disability. Objectives: aim of this study is to evaluate longitudinally the cognitive and behavioral characteristics of patients with a parkinsonian syndrome at onset; to describe the cognitive and behavioral characteristics of each parkinsonian syndrome; to define in PD patients at onset the presence of MCI or Parkinson disease dementia; to correlate the cognitive and behavioral characteristics with the features of the parkinsonian syndrome and with the associated sleep and autonomic features. Results: we recruited 55 patients, 22 did not present cognitive impairment both at T0 and at T1. 18 patients presented a progression of cognitive impairment. Progressive cognitively impaired patients were older and presented the worst motor phenotype. Progression of cognitive impairment was not associated to sleep and autonomic features. Conclusion: the evaluation of cognitive impairment could not be useful as a predictor of a correct diagnosis but each non motor domain will help to clarify and characterize the motor syndrome. The diagnosis of parkinsonian disorders lies in building a clinical profile in conjunction with other clinical characteristics such as mode of presentation, disease progression, response to medications, sleep and autonomic features.

Functional relationship of colorectal cancer-associated glycans with malignant phenotype and transcriptome changes

Glycosyltransferases ST6GAL1 and B4GALNT2 (and their cognate antigens Sia6LacNAc and Sda, respectively) are associated with colorectal cancer (CRC) but it is not fully clear their biological and clinical significance. We explored the clinical relevance of both glycosyltransferases by interrogating The Cancer Genome Atlas (TCGA) database while the phenotypic/transcriptomic effects of ST6GAL1/B4GALNT2 overexpression were studied in genetically modified CRC cell lines. Transcriptomic data from CRC patients in TCGA database suggested a moderate impact of ST6GAL1 on CRC progression, although it was not possible to define a clear role for this glycosyltransferase. Transcriptomic analysis of ST6GAL1-transduced cell lines revealed a much deeper effect of ST6GAL1 on gene expression in SW948 than in SW48. The overexpression of ST6GAL1 induced opposite effects on soft agar growth and wound healing in both cell lines. These results indicate that the impact of a cancer-associated glycosyltransferase change on phenotype/transcriptome can be extremely variable, depending on the molecular context of the tumor cell. On the contrary, transcriptomic analysis of B4GALNT2-modified cell lines together with TCGA database survey demonstrated a strong impact of B4GALNT2 on the transcriptional activity of CRC cells, in particular its association with a better prognosis. We suggest an anti-tumoral role of B4GALNT2 in CRC. We also investigated the glycan changes related to ST6GAL1/B4GALNT2 expression in a small cohort of tissues/plasma as well as the N-glycomic profile of CRC, normal and polyp tissues. We found an increase of ST6GAL1 activity in CRC and inflammatory bowel disease plasma samples comparing with plasma from healthy donors. A different Sda protein carrier pattern was observed between healthy donors and CRC plasma samples. β-arrestin 1 is a possible candidate as Sda carrier protein in plasma samples although future validation studies are needed. The alterations found in the N-glycan pattern highlight the importance of N-glycome as a molecular signature in cancer.

Numerical assessment of the water injection application to GDI engines

A possible future scenario for the water injection (WI) application has been explored as an advanced strategy for modern GDI engines. The aim is to verify whether the PWI (Port Water Injection) and DWI (Direct Water Injection) architectures can replace current fuel enrichment strategies to limit turbine inlet temperatures (TiT) and knock engine attitude. In this way, it might be possible to extend the stoichiometric mixture condition over the entire engine map, meeting possible future restrictions in the use of AES (Auxiliary Emission Strategies) and future emission limitations. The research was first addressed through a comprehensive assessment of the state-of-the-art of the technology and the main effects of the chemical-physical water properties. Then, detailed chemical kinetics simulations were performed in order to compute the effects of WI on combustion development and auto-ignition. The latter represents an important methodology step for accurate numerical combustion simulations. The water injection was then analysed in detail for a PWI system, through an experimental campaign for macroscopic and microscopic injector characterization inside a test chamber. The collected data were used to perform a numerical validation of the spray models, obtaining an excellent matching in terms of particle size and droplet velocity distributions. Finally, a wide range of three-dimensional CFD simulations of a virtual high-bmep engine were realized and compared, exploring also different engine designs and water/fuel injection strategies under non-reacting and reacting flow conditions. According to the latter, it was found that thanks to the introduction of water, for both PWI and DWI systems, it could be possible to obtain an increase of the target performance and an optimization of the bsfc (Break Specific Fuel Consumption), lowering the engine knock risk at the same time, while the TiT target has been achieved hardly only for one DWI configuration.

Development of a patient-specific model for stroke risk assessment in atrial fibrillation patients

Atrial fibrillation is associated with a five-fold increase in the risk of cerebrovascular events,being responsible of 15-18% of all strokes.The morphological and functional remodelling of the left atrium caused by atrial fibrillation favours blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that stroke risk stratification could be improved by using haemodynamic information on the left atrium (LA) and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid-dynamics (CFD) model of the left atrium which could clarify the haemodynamic implications of atrial fibrillation on a patient specific basis. The developed CFD model was first applied to better understand the role of LAA in stroke risk. Infact, the interplay of the LAA geometric parameters such as LAA length, tortuosity, surface area and volume with the fluid-dynamics parameters and the effects of the LAA closure have not been investigated. Results demonstrated the capabilities of the CFD model to reproduce the real physiological behaviour of the blood flow dynamics inside the LA and the LAA. Finally, we determined that the fluid-dynamics parameters enhanced in this research project could be used as new quantitative indexes to describe the different types of AF and open new scenarios for the patient-specific stroke risk stratification.

Impact of Glycosyltransferases on the Phenotype, Signaling and Transcriptome of Colorectal Cancer Cell Lines. Focus on the role of glycosyltransferases B4GALNT2 and FUT6 and their cognate Sda and sLex antigens

In colorectal cancer (CRC), two carbohydrate structures are modulated: the Sda antigen, synthesized by B4GALNT2, and sLex antigen, mainly synthesized by FUT6. sLex antigen is often overexpressed and associated with worse prognosis; B4GALNT2/Sda antigen are dramatically downregulated but their role in tumor progression and development is not fully clear. TCGA interrogation revealed a dramatic down-regulation of B4GALNT2 mRNA in CRC, compared with normal samples. Patients with higher B4GALNT2 mRNA in CRC samples displayed longer survival. Yet, methylation and miRNA expression play a relevant role in B4GALNT2 downregulation in CRC. To clarify the mechanisms linking the B4GALNT2/Sda expression level to CRC phenotype, three different CRC cell lines were modified to express B4GALNT2: LS174T cell line, in which the constitutively expressed sLex antigen was partially replaced by Sda; SW480/SW620 pair, both lacking Sda and sLex antigens. In LS174T cells, the expression of B4GALNT2 reduced the ability to grow in poor adherence conditions and the expression of ALDH, a stemness marker. In SW620 cells, B4GALNT2 expression impacted on the main aspects of malignancy. In SW480 cells the expression of B4GALNT2 left unchanged the proliferation rate and the wound healing ability. To clarify the impact of sLex on CRC phenotype, the SW480/SW620 pair were permanently transfected to express FUT6 cDNA. In both cell lines, overexpression of FUT6/sLex boosted the clonogenic ability in standard growth conditions. Conversely, the growth in soft agar and the capacity to close a wound were enhanced only in SW620 cells. Transcriptome analysis of CRC cell lines transfected either with B4GALNT2 or FUT6 showed a relevant impact of both enzymes on gene expression modulation. Overall, current data may help to personalize therapies for CRC patients according to the B4GALNT2 levels and support a causal effect of this glycosyltransferase on reducing malignancy independently of sLex inhibition.

Evaluation of alpha-synuclein RT-QuIC for an early and differential diagnosis of Lewy body disease

Synucleinopathies are a group of neurodegenerative diseases characterized by tissue deposition of insoluble aggregates of the protein α-synuclein. Currently, the clinical diagnosis of these diseases, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), is very challenging, especially at an early disease stage, due to the heterogeneous and often non-specific clinical manifestations. Therefore, identifying specific biomarkers to aid the diagnosis and improve the clinical management of patients with these disorders represents a primary goal in the field. Pursuing this aim, we applied the α-Syn Real-Time Quaking-Induced Conversion (RT-QuIC), an ultrasensitive technique able to detect minute amounts of amyloidogenic proteins, to a large cohort of 953 CSF samples from clinically well-characterized (“clinical” group), or neuropathologically verified (“NP” group) patients with parkinsonism or dementia. Of significance, we also studied patients with prodromal synucleinopathies (“prodromal” group), such as pure autonomic failure (PAF) (n = 28), isolated REM sleep behavior disorder (iRBD) (n = 18), and mild cognitive impairment due to probable Lewy body (LB) disease (MCI-LB) (n = 81). Our findings show that α-syn RT-QuIC can accurately detect α-Syn seeding activity across the whole spectrum of LB-related disorders (LBD), exhibiting a mean sensitivity of 95.2% in the “clinical” and “NP” group, while ranging between 89.3% (PAF) and 100% (RBD) in the “prodromal group”. Moreover, we observed 95.1% sensitivity and 96.6% specificity in the distinction between MCI-LB patients and cognitively unimpaired controls, demonstrating the solid diagnostic potential of α-Syn RT-QuIC in the early phase of the disease. Finally, 13.3% of MCI-AD patients also had a positive test, suggesting an underlying LB co-pathology. This work demonstrated that α-Syn RT-QuIC is an efficient assay for accurate and early diagnosis of LBD, which should be implemented for clinical management and recruitment for clinical trials in memory clinics.

Development of numerical methodologies to predict the liquid fuel sprays - wall interaction to optimize the mixing process of direct injection spark ignition engines

Nowadays the development of new Internal Combustion Engines is mainly driven by the need to reduce tailpipe emissions of pollutants, Green-House Gases and avoid the fossil fuels wasting. The design of dimension and shape of the combustion chamber together with the implementation of different injection strategies e.g., injection timing, spray targeting, higher injection pressure, play a key role in the accomplishment of the aforementioned targets. As far as the match between the fuel injection and evaporation and the combustion chamber shape is concerned, the assessment of the interaction between the liquid fuel spray and the engine walls in gasoline direct injection engines is crucial. The use of numerical simulations is an acknowledged technique to support the study of new technological solutions such as the design of new gasoline blends and of tailored injection strategies to pursue the target mixture formation. The current simulation framework lacks a well-defined best practice for the liquid fuel spray interaction simulation, which is a complex multi-physics problem. This thesis deals with the development of robust methodologies to approach the numerical simulation of the liquid fuel spray interaction with walls and lubricants. The accomplishment of this task was divided into three tasks: i) setup and validation of spray-wall impingement three-dimensional CFD spray simulations; ii) development of a one-dimensional model describing the liquid fuel – lubricant oil interaction; iii) development of a machine learning based algorithm aimed to define which mixture of known pure components mimics the physical behaviour of the real gasoline for the simulation of the liquid fuel spray interaction.

Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

Development and characterization of deep learning techniques for neuroimaging data

Deep learning methods are extremely promising machine learning tools to analyze neuroimaging data. However, their potential use in clinical settings is limited because of the existing challenges of applying these methods to neuroimaging data. In this study, first a data leakage type caused by slice-level data split that is introduced during training and validation of a 2D CNN is surveyed and a quantitative assessment of the model’s performance overestimation is presented. Second, an interpretable, leakage-fee deep learning software written in a python language with a wide range of options has been developed to conduct both classification and regression analysis. The software was applied to the study of mild cognitive impairment (MCI) in patients with small vessel disease (SVD) using multi-parametric MRI data where the cognitive performance of 58 patients measured by five neuropsychological tests is predicted using a multi-input CNN model taking brain image and demographic data. Each of the cognitive test scores was predicted using different MRI-derived features. As MCI due to SVD has been hypothesized to be the effect of white matter damage, DTI-derived features MD and FA produced the best prediction outcome of the TMT-A score which is consistent with the existing literature. In a second study, an interpretable deep learning system aimed at 1) classifying Alzheimer disease and healthy subjects 2) examining the neural correlates of the disease that causes a cognitive decline in AD patients using CNN visualization tools and 3) highlighting the potential of interpretability techniques to capture a biased deep learning model is developed. Structural magnetic resonance imaging (MRI) data of 200 subjects was used by the proposed CNN model which was trained using a transfer learning-based approach producing a balanced accuracy of 71.6%. Brain regions in the frontal and parietal lobe showing the cerebral cortex atrophy were highlighted by the visualization tools.