Messa a punto di sistemi per il controllo e la terapia delle malattie virali

A livello globale una delle problematiche più urgenti della sanità pubblica umana e veterinaria è rappresentata dal controllo delle infezioni virali. L’emergenza di nuove malattie, la veloce diffusione di patologie finora confinate ad alcune aree geografiche, lo sviluppo di resistenza dei patogeni alle terapie utilizzate e la mancanza di nuove molecole attive, sono gli aspetti che influiscono più negativamente livello socio-economico in tutto il mondo. Misure per limitare la diffusione delle infezioni virali prevedono strategie per prevenire e controllare le infezioni in soggetti a rischio . Lo scopo di questa tesi è stato quello di indagare il possibile utilizzo di prototipi virali utilizzati come modello di virus umani per valutare l’efficacia di due diversi metodi di controllo delle malattie virali: la rimozione mediante filtrazione di substrati liquidi e gli antivirali di sintesi e di origine naturale. Per quanto riguarda la rimozione di agenti virali da substrati liquidi, questa è considerata come requisito essenziale per garantire la sicurezza microbiologica non solo di acqua ad uso alimentare , ma anche dei prodotti utilizzati a scopo farmaceutico e medico. Le Autorità competenti quali WHO ed EMEA hanno redatto delle linee guida molto restrittive su qualità e sicurezza microbiologica dei prodotti biologici per garantire la rimozione di agenti virali che possono essere trasmessi con prodotti utilizzati a scopo terapeutico. Nell'industria biomedicale e farmaceutica c'è l'esigenza di una tecnologia che permetta la rimozione dei virus velocemente, in grande quantità, a costi contenuti, senza alterare le caratteristiche del prodotto finale . La collaborazione con l’azienda GVS (Zola Predosa, Italia) ha avuto come obiettivo lo studio di una tecnologia di filtrazione che permette la rimozione dei virus tramite membrane innovative e/o tessuti-non-tessuti funzionalizzati che sfruttano l’attrazione elettrostatica per ritenere ed asportare i virus contenuti in matrici liquide. Anche gli antivirali possono essere considerati validi mezzi per il controllo delle malattie infettive degli animali e nell’uomo quando la vaccinazione non è realizzabile come ad esempio in caso di scoppio improvviso di un focolaio o di un attacco bioterroristico. La scoperta degli antivirali è relativamente recente ed il loro utilizzo è attualmente limitato alla patologia umana, ma è in costante aumento l’interesse per questo gruppo di farmaci. Negli ultimi decenni si è evidenziata una crescente necessità di mettere a punto farmaci ad azione antivirale in grado di curare malattie ad alta letalità con elevato impatto socio-economico, per le quali non esiste ancora un’efficace profilassi vaccinale. Un interesse sempre maggiore viene rivolto agli animali e alle loro patologie spontanee, come modello di studio di analoghe malattie dell’uomo. L’utilizzo di farmaci ad azione antivirale in medicina veterinaria potrebbe contribuire a ridurre l’impatto economico delle malattie limitando, nel contempo, la disseminazione dei patogeni nell’ambiente e, di conseguenza, il rischio sanitario per altri animali e per l’uomo in caso di zoonosi. Le piante sono sempre state utilizzate dall’industria farmaceutica per l’isolamento dei composti attivi e circa il 40% dei farmaci moderni contengono principi d’origine naturale. Alla luce delle recenti emergenze sanitarie, i fitofarmaci sono stati considerati come una valida per migliorare la salute degli animali e la qualità dei prodotti da essi derivati. L’obiettivo del nostro studio è stato indagare l’attività antivirale in vitro di estratti naturali e di molecole di sintesi nei confronti di virus a RNA usando come prototipo il Canine Distemper Virus, modello di studio per virus a RNA a polarità negativa, filogeneticamente correlato al virus del morbillo umano. La scelta di questo virus è dipesa dal fatto che rispetto ai virus a DNA e ai retrovirus attualmente l’offerta di farmaci capaci di contrastare le infezioni da virus a RNA è molto limitata e legata a molecole datate con alti livelli di tossicità. Tra le infezioni emergenti causate da virus a RNA sono sicuramente da menzionare quelle provocate da arbovirus. Le encefaliti virali da arbovirus rappresentano una emergenza a livello globale ed attualmente non esiste una terapia specifica. Una delle molecole più promettenti in vitro per la terapia delle infezioni da arbovirus è la ribavirina (RBV) che, con il suo meccanismo d’azione pleiotropico, si presta ad essere ulteriormente studiata in vivo per la sua attività antivirale nei confronti delle infezioni da arbovirus. Uno dei fattori limitanti l’utilizzo in vivo di questa molecola è l’incapacità della molecola di oltrepassare la barriera emato-encefalica. Nel nostro studio abbiamo messo a punto una formulazione per la somministrazione endonasale di RBV e ne abbiamo indagato la diffusione dalla cavità nasale all’encefalo attraverso l’identificazione e quantificazione della molecola antivirale nei diversi comparti cerebrali . Infine è stato condotto un esperimento in vivo per valutare l’efficacia di un composto a base di semi di Neem, di cui sono già note le proprietà antimicrobiche, nei confronti dell’infezione da orf virus, una zoonosi a diffusione mondiale, che ha un elevato impatto economico in aree ad alta densità ovi-caprina e può provocare lesioni invalidanti anche nell’uomo.

Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

La diagnostica sonica nell'arboricoltura ornamentale

Il tomografo sonico è uno strumento di recente applicazione nell’analisi morfo-sintomatica delle alberature. Si tratta di uno strumento che sfrutta la propagazione delle onde sonore nel legno per determinarne la densità e le possibili alterazioni interne. Oltre all’applicazione su larga scala in un parco di Imola, per effettuare una valutazione approfondita di tutti gli esemplari, lo strumento è stato applicato per scopi diversi. In prima analisi è stato utilizzato per valutare stadi precoci di alterazione e l’evoluzione delle patologie interne nel tempo. Successivamente si voleva identificare il percorso di sostanze liquide iniettate con mezzi endoterapici nel tronco, attraverso l’applicazione di tomografia sonica sopra e sotto il punto di iniezione. In ultima analisi è stato effettuato un confronto tra tomografia sonica e risonanza magnetica nucleare per identificare patologie invisibili ai normali strumenti utilizzati nell’analisi della stabilità delle piante.

General effective medium model for the complex permittivity extraction with an open-ended coaxial probe in presence of a multilayer material under test

The work presented in this thesis is focused on the open-ended coaxial-probe frequency-domain reflectometry technique for complex permittivity measurement at microwave frequencies of dispersive dielectric multilayer materials. An effective dielectric model is introduced and validated to extend the applicability of this technique to multilayer materials in on-line system context. In addition, the thesis presents: 1) a numerical study regarding the imperfectness of the contact at the probe-material interface, 2) a review of the available models and techniques, 3) a new classification of the extraction schemes with guidelines on how they can be used to improve the overall performance of the probe according to the problem requirements.

Content extraction: Identifying the main content in HTML documents

Except the article forming the main content most HTML documents on the WWW contain additional contents such as navigation menus, design elements or commercial banners. In the context of several applications it is necessary to draw the distinction between main and additional content automatically. Content extraction and template detection are the two approaches to solve this task. This thesis gives an extensive overview of existing algorithms from both areas. It contributes an objective way to measure and evaluate the performance of content extraction algorithms under different aspects. These evaluation measures allow to draw the first objective comparison of existing extraction solutions. The newly introduced content code blurring algorithm overcomes several drawbacks of previous approaches and proves to be the best content extraction algorithm at the moment. An analysis of methods to cluster web documents according to their underlying templates is the third major contribution of this thesis. In combination with a localised crawling process this clustering analysis can be used to automatically create sets of training documents for template detection algorithms. As the whole process can be automated it allows to perform template detection on a single document, thereby combining the advantages of single and multi document algorithms.

Valorization of pomaces from the mechanical extraction of virgin olive oils in dairy animal feeding

This research work is aimed at the valorization of two types of pomace deriving from the extra virgin olive oil mechanical extraction process, such as olive pomace and a new by-product named “paté”, in the livestock sector as important sources of antioxidants and unsaturated fatty acids. In the first research the suitability of dried stoned olive pomace as a dietary supplement for dairy buffaloes was evaluated. The effectiveness of this utilization in modifying fatty acid composition and improving the oxidative stability of buffalo milk and mozzarella cheese have been proven by means of the analysis of qualitative and quantitative parameters. In the second research the use of paté as a new by-product in dietary feed supplementation for dairy ewes, already fed with a source of unsaturated fatty acids such as extruded linseed, was studied in order to assess the effect of this combination on the dairy products obtained. The characterization of paté as a new by-product was also carried out, studying the optimal conditions of its stabilization and preservation at the same time. The main results, common to both researches, have been the detection and the characterization of hydrophilic phenols in the milk. The analytical detection of hydroxytyrosol and tyrosol in the ewes’ milk fed with the paté and hydroxytyrosol in buffalo fed with pomace showed for the first time the presence in the milk of hydroxytyrosol, which is one of the most important bioactive compounds of the oil industry products; the transfer of these antioxidants and the proven improvement of the quality of milk fat could positively interact in the prevention of some human cardiovascular diseases and some tumours, increasing in this manner the quality of dairy products, also improving their shelf-life. These results also provide important information on the bioavailability of these phenolic compounds.

Knowledge Patterns for the Web: extraction, tranformation and reuse

This thesis aims at investigating methods and software architectures for discovering what are the typical and frequently occurring structures used for organizing knowledge in the Web. We identify these structures as Knowledge Patterns (KPs). KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Then we present K~ore, a software architecture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.

Secondary Microseisms Characterization and Green’s Function Extraction at the Larderello-Travale Geothermal Field (Italy)

Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.