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Robust and Efficient Geometric Methods for Registration, Localization and Mapping
No full textIn the last couple of decades, robotics has developed vertically towards a growing number of fields.
Nowadays, robotics engineering encompasses a wide set of diverse tasks, spanning from the strictly electrical or mechanical ones, to multi-robot fleet coordination, or autonomous and intelligent operations.
The rise among the computer science community of the artificial intelligence techniques has caused this trend to accelerate even further.
This is due to the tendency of applying machine learning techniques to an ever increasing number of fields.
However, even today many industrial and service robotics tasks are solved through model-based approaches.
For this relevant number of use cases, it is important to keep the research going on improving robustness, efficiency and diversity of robotic primitives.
Primitives can be defined as operations that are relevant in a wide number of robotic applications.
A robotic primitive tackled in this dissertation is point cloud registration, which is the estimation of the rigid motion that better aligns different views of the same scene.
Registration has an important role in addressing simultaneous localization and mapping (SLAM), which can be decomposed in subproblems, including alignment of consecutive sensor measurements, loop closure, and place recognition.
Clearly, registration can be seen as one of the cornerstones for performing solid SLAM, as it allows comparison and merging of partially overlapping sensory data into a consistent map, or the assessment of the motion of a mobile robot.
Another important spatial estimation problem is the cross-localization between sensors or robots within a fleet.
It is an instance of pose graph problems involving a network of reference frames constrained by relative measurements.
The specific issues are the density of relative constraints, as well as the emphasis on pose synchronization.
These pose estimation problems are usually defined in the form of an optimization problem on variables, features and transformations described by Lie groups and algebras.
The most common registration methods solve the problem with local search methods relying on an initial guess provided by odometry or coarse-to-fine assessment.
However, more robust evaluation can be guaranteed by global search or, when possible, by globally optimal methods exploiting optimization on Riemannian manifolds in order to certify the behavior of a system.
Robustness is achieved by independence from an initial assessment of the solution, and by certifiable properties such as global optimality.
However, most of the time removing assumptions from a problem can lead to an increased computational complexity of the algorithms that solve it globally.
Because of this, it is paramount to keep an eye on the computational efficiency of these approaches e.g., by simplifying input data eliminating redundancies, or parallelizing as many operations as possible.
This dissertation presents two main contributions related to the geometric approach in the solution of pose estimation problems.
The first main contribution is the proposal of Angular Radon Spectrum (ARS) for point cloud registration.
Angular Radon Spectrum is a descriptor that captures the collinearity (in 2D domain) or the coplanarity (in 3D domain) of a point cloud to a pencil of lines or planes.
The point clouds are represented in the form of Gaussian Mixture Models (GMMs) that effectively model point position uncertainty.
ARS is translation-invariant, and expresses rotation-shifts straightforwardly.
This allows decoupling of rotation and translation estimation.
As such, ARS can be used to perform pairwise rotation estimation through maximization of the correlation function between the two ARS spectra.
There are three original results about ARS presented in this dissertation.
The first one is the algorithm for efficient computation of ARS in planar domain, with general anisotropic Gaussian kernels that compose input GMMs. This algorithm also performs GMM simplification in order to reduce the number of input kernels.
The second outcome is a parallel algorithm for planar ARS computation suitable for GPU-based implementation.
The third specific contribution is the derivation of ARS for 3D point clouds, and the derivation of closed-form series expansion in spherical harmonics.
Full pose registration is achieved through a branch-and-bound translation estimation algorithm.
Experiments show the high accuracy and improved computational speed of the ARS-based rotation estimation, while concisely assessing the potential of ARS in a SLAM scan-based registration and mapping pipeline.
The second main contribution presented is the pose averaging, or cross-localization, of a sensor fleet through a formulation based on the Shape of Motion (SOM) matrix.
The novelty introduced by this approach regards the reformulation of the Riemannian Staircase (RS) algorithm to the specific case needed.
RS is used to exit local minima in which solvers stop with a given dimensionality of the problem, by iteratively increasing the dimension of the cost function members and their associated search space.
Optimization has been performed through Riemannian Geometry and Netwonian solvers.
A relevant part of the work regards the search of an exit direction leading to a point with cost lower than the one where the optimization stopped at the previous staircase step, based on searching a negative eigenvalue of the Riemannian Hessian of the cost function, after increasing the dimensionality of the problem
From the genesis to the application: design of cocrystals based on natural ingredients and monitoring of their synthesis and activation
No full textThe aim of this thesis is the stabilization of natural EOs through cocrystallization with designed coformers. The coformers were synthesized in order to show photo-responsive properties and well interact with the selected EOs. The release of the resulting cocrystals was evaluated upon UV radiation and dark conditions. As a second purpose, the mechanism of two mechanochemical cocrystallizations was investigated with different techniques. Both the reactions involved thymol (EO) as coformer and showed the presence of low melting eutectic compositions that act as liquid intermediates. The nature of low eutectic composition was further explored using the Pair Distribution Function (PDF ) analysis. Finally, a systematic study on binary mixture systems was proposed in order to estimate ab initio the thermodynamical requirements to obtain low melting eutectic systems
Controllo attivo di zone sonore personali mediante elaborazione digitale del segnale
No full textThe advancement of audio technology in a world characterized by increasing connectivity and constant background noise has led to the development of personal sound zone systems. These systems are designed to provide tailored audio experiences to individual users in shared spaces. By utilizing several loudspeakers, personal sound zone systems can deliver distinct audio signals to various zones without the need for headphones, improving listener comfort and privacy, and reducing noise pollution. Personal sound zone systems find applications in various scenarios, including in-vehicle audio, public and home entertainment, and communication. They have the potential to offer benefits, such as individualized sound zones for passengers during car or public vehicle journeys, separate audio areas for multiple individuals at home and public spaces, and enhanced audio quality for phone calls, video conferencing, and online meetings. However, designing and implementing personal sound zone systems presents several challenges, including achieving high acoustic contrast among zones, minimizing signal distortion and interference, optimizing array configurations, and adapting to changing user preferences. To control the sound field in personal sound zone systems, advanced digital signal processing techniques are required. These techniques have applications in immersive audio experiences, virtual and augmented reality, gaming, noise cancellation, and personal sound zone generation. This thesis deals with various aspects of a personal sound zone systems with application in the automotive scenario. Related to the capabilities of personal sound zone systems to control the soundfield in a particularly reverberant scenario, such as the cabin of a vehicle, this research introduces four methods for processing the measured impulse responses, reducing late reflections to enhanceacoustic contrats, robustness, and sound quality. Various methods have been proposed for sound field control, such as pressure matching and acoustic contrast control techniques. For a part of this work, the personal sound zone method is adopted, however, also the performance of the acoustic contrast control method in terms of sound quality in a real-world system is investigated. Moreover, two techniques derived from the pressure matching method are proposed to improve the acoustic contrast, reproduction error and robustness in the considered scenario. With the purpose of achieving a high fidelity of the reproduced audio, an acoustic pressure with flat spectrum and constant group delay is considered as target in most of the literature related to pressure matching. However, this may not be the optimal target in order to improve acoustic contrast maintaining high fidelity reproduction. For this reason, the first proposed technique involves the optimization of the target phase for pressure matching with the aim of acoustic contrast maximization. One of the disadvantages of the original formulation of pressure matching is that the performance is not robust against errors in the measurement positions with respect to the realistic positions of the listeners. With the purpose of solving this weakness, a statistical pressure matching algorithm is developed. This technique allows to improve the reproduction fidelity and acoustic contrast by using several measurements to average out the effect of the errors. A significant aspect of personal sound zone systems involves designing filters to control the audio signals at the inputs of the loudspeakers based on the acoustic responses and assessing the resulting performance. Early evaluations were often performed under ideal conditions, thus, overestimating the system achievable performance in realistic conditions. To address these limitations, a stochastic model is proposed to generate mismatched frequency response for realistic performance prediction. This model considers complex coefficients in the frequency domain and perturbs the acoustic responses in the performance evaluation step
Robust inference of phenotypic traits from low-coverage ancient genomes
No full textLa fenotipizzazione forense del DNA (FDP) consente di prevedere determinati tratti fenotipici di un individuo, quali l’aspetto fisico, l’ascendenza biogeografica e l’età, a partire da minime quantità di DNA provenienti da campioni biologici. Tale tecnica risulta particolarmente utile nell’identificazione di autori sconosciuti di reati, nei casi in cui la profilazione forense standard non fornisca informazioni sufficienti a causa della mancanza di sospetti noti o profili presenti in database nazionali di DNA.
Uno strumento di fenotipizzazione forense già sviluppato e validato è il sistema HIrisPlex-S, progettato per la previsione simultanea del colore degli occhi, dei capelli e della pelle. Basato sull'analisi di 41 polimorfismi genetici associati alla pigmentazione, questo sistema permette di stimare le probabilità individuali per tre categorie di colore degli occhi, quattro di colore dei capelli e cinque di colore della pelle, utilizzando esclusivamente i dati genotipici.
Questo strumento, originariamente sviluppato per supportare indagini criminali specifiche, è stato ampiamente utilizzato negli ultimi anni anche per prevedere il fenotipo di resti scheletrici umani antichi.
Fino ad oggi, la predizione fenotipica basata su dati antichi, degradati e a bassa copertura, è stata effettuata assumendo la conoscenza dello stato allelico e genotipico dei campioni nelle 41 posizioni di interesse. Tuttavia, è noto che la chiamata diretta delle varianti genotipiche da tali dati presenta numerose sfide, a causa della frammentazione del materiale genetico, del rischio di contaminazione e della degradazione. Quest'ultima provoca, nel tempo, la rottura del DNA in frammenti molto piccoli, rendendo difficile l'ottenimento di sequenze complete e accurate. Ciò comporta una bassa profondità di sequenziamento, che influisce drasticamente sulla capacità di identificare in modo affidabile i genotipi, contribuendo così ad errori nell’inferenza fenotipica.
Nella prima parte di questo lavoro di tesi è stata valutata la robustezza del sistema HIrisPlex-S nella procedura inferenziale fenotipica applicata a dati antichi e a bassa copertura, testandolo a diversi livelli di copertura. È stato determinato il livello di copertura necessario per garantire un'inferenza robusta e valutato quando applicare il protocollo classico di HIrisPlex-S e quando invece ricorrere a metodi alternativi che considerino l'incertezza nella chiamata genotipica. La valutazione è stata con-dotta analizzando i risultati delle predizioni fenotipiche per il colore degli occhi, dei capelli e della pelle, ottenuti tramite tre modelli di predizione: 1) il protocollo standard di HIrisPlex-S, basato sulla chiamata diretta delle varianti; 2) un modello specificamente sviluppato in questo lavoro, che integra il sistema classico con le genotype likelihoods, per considerare l’incertezza associata ai dati a bassa copertura nella chiamata dei genotipi; 3) l’imputazione, utilizzata per gestire i dati potenzialmente mancanti in genomi a bassa copertura.
A tale scopo, sono stati analizzati tre campioni presenti in letteratura ad alta copertura: uno prove-niente dalla Siberia del Paleolitico, uno dalla Svezia del Mesolitico e uno dalla Germania dell’Età del Bronzo. Utilizzando una procedura di abbassamento artificiale della copertura, sono state effettuate previsioni fenotipiche sui colori degli occhi, dei capelli e della pelle, testando i tre diversi modelli di predizione. I risultati delle previsioni fenotipiche per ciascun approccio e livello di copertura sono stati confrontati con il "fenotipo reale", inferito dal genoma originale ad alta copertura. È stato quindi valutato quante volte ciascun metodo, a ogni livello di copertura, ha prodotto previsioni corrette, al fine di determinare i limiti e l'approccio più idoneo per la predizione fenotipica da dati antichi, riducendo al minimo gli errori nelle stime.
Le conclusioni di questa prima parte indicano che, indipendentemente dal periodo storico del campione analizzato, è consigliabile applicare il protocollo standard di HIrisPlex-S se si raggiungono livelli minimi di copertura di almeno 8x su ciascuna delle 41 posizioni di interesse. Per coperture inferiori a 8x, si raccomanda invece l'uso del metodo ideato e testato in questo studio, che utilizza le genotype likelihoods per la stima dei genotipi.
La seconda parte di questo progetto di tesi ha previsto l'applicazione del protocollo a un dataset di 348 individui eurasiatici, che spaziano dal Paleolitico superiore all'Età del Ferro, con l'obiettivo di osservare la variazione del colore degli occhi, dei capelli e della pelle negli ultimi 45.000 anni. La fotografia che emerge rivela un'evoluzione complessa di questi tratti: sebbene i fenotipi scuri siano stati predominanti per gran parte del periodo esaminato, i fenotipi chiari sono comparsi a partire dal Mesolitico, nelle regioni che richiedevano un adattamento ambientale alle alte latitudini. In seguito, tali fenotipi chiari si sono diffusi ulteriormente nei periodi successivi grazie a una complessa interazione tra adattamento ambientale ed eventi demografici.Forensic DNA phenotyping (FDP) enables the prediction of specific phenotypic traits of an individual, such as physical appearance, biogeographical ancestry, and age, from minimal amounts of DNA obtained from biological samples. FDP is particularly useful in identifying unknown perpetrators of crimes, especially when standard forensic profiling does not provide sufficient information due to the absence of known suspects or profiles in national DNA databases.
A validated forensic phenotyping tool is the HIrisPlex-S system, designed for the simultaneous prediction of eye, hair, and skin colour. Based on the analysis of 41 genetic polymorphisms associated with pigmentation, this system allows for the estimation of individual probabilities for three categories of eye colour, four categories of hair colour, and five categories of skin colour, using exclusively genotypic data.
Originally developed to support specific criminal investigations, this tool has also been extensively used in recent years to predict the phenotype of ancient human skeletal remains.
To date, phenotypic prediction based on ancient, degraded, and low-coverage data has been carried out by assuming knowledge of the allelic and genotypic states of the samples at the 41 loci of interest. However, it is well known that directly calling genotypic variants from such data presents numerous challenges due to genetic material fragmentation, contamination risks, and degradation. Over time, degradation causes the DNA to break into very small fragments, making it difficult to obtain complete and accurate sequences. This results in low sequencing depth, which drastically affects the ability to reliably identify genotypes, thereby contributing to errors in phenotypic inference.
In the first part of this thesis, the robustness of the HIrisPlex-S system in phenotypic inference applied to ancient and low-coverage data was evaluated by testing it at various coverage levels. The required coverage level for ensuring robust inference was determined, and guidelines were established for when to apply the standard HIrisPlex-S protocol versus when to use alternative methods that account for uncertainty in genotypic calls. The evaluation was conducted by analysing the results of phenotypic predictions for eye, hair, and skin colour obtained through three prediction models: 1) the standard HIrisPlex-S protocol, based on direct variant calling; 2) a model specifically developed in this work, which integrates the classic system with genotype likelihoods to account for
Robust inference of phenotypic traits from low-coverage ancient genomes
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the uncertainty associated with low-coverage data in genotype calling; 3) imputation, used to handle potentially missing data in low-coverage genomes.
To this scope, three available high-coverage samples were analysed: one from Palaeolithic Siberia, one from Mesolithic Sweden, and one from Bronze Age Germany. Using a downsampling procedure, phenotypic predictions for eye, hair, and skin colour were made by applying the three different prediction models. The results of phenotypic predictions for each approach and coverage level were compared with the "true phenotype" inferred from the original high-coverage genome. Subsequently, the frequency of correct predictions by each method at each coverage level was evaluated to determine the limits and the most suitable approach for phenotypic prediction from ancient data, thereby minimizing errors in the estimations.
The conclusions of this first part indicate that, regardless of the historical period of the analysed sample, it is advisable to apply the standard HIrisPlex-S protocol if minimum coverage levels of at least 8x at each of the 41 loci of interest are achieved. For coverages below 8x, the method developed and tested in this study, which uses genotype likelihoods for genotype estimation, is recommended instead.
The second part of this thesis project involved applying the protocol to a dataset of 348 Eurasian individuals ranging from the Upper Palaeolithic to the Iron Age, with the goal of examining the variation in eye, hair, and skin colour over the past 45,000 years. The resulting picture reveals a complex evolution of these traits: while dark phenotypes predominated for much of the studied period, light phenotypes began to appear from the Mesolithic onward in regions requiring environmental adaptation to high latitudes. Subsequently, these light phenotypes further spread in later periods due to a complex interaction between environmental adaptation and demographic events
Unraveling the role of topology in complex long range systems and deep neural networks
No full textQuesta ricerca approfondisce due ambiti principali: le proprietà critiche dei sistemi a lungo raggio e i meccanismi di apprendimento delle caratteristiche nelle reti neurali profonde.
Nello studio dei sistemi a lungo raggio, abbiamo esaminato il modello di Ising ferromagnetico in una e due dimensioni, caratterizzato da interazioni della forma . Utilizzando una nuova dinamica locale su una rete di Lévy dinamica (DLL), siamo stati in grado di riprodurre gli esponenti critici statici coerenti con la letteratura consolidata. Questo approccio localizzato offre una metodologia versatile per esplorare le proprietà dinamiche di vari modelli a lungo raggio. In particolare, la nostra analisi del tempo di rilassamento alla temperatura critica ha rivelato sfumature nella relazione tra l'esponente dinamico e il parametro di decadimento , suggerendo una possibile disparità tra le proprietà critiche dinamiche e di equilibrio. Inoltre, grazie alla versatilità della nostra strategia (DLL), siamo stati in grado di condurre lavori preliminari nello studio delle proprietà critiche del modello Long Range .
Passando alle reti neurali profonde, abbiamo esplorato le disparità nell'apprendimento delle caratteristiche tra le reti completamente connesse (FCN) e le architetture convoluzionali (CNNs). Studi empirici su reti completamente connesse nel regime di larghezza infinita hanno rivelato un plateau nel miglioramento delle prestazioni, attribuito alla natura statica del loro kernel durante l'addestramento. Questo suggerisce che qualsiasi apprendimento intrinseco delle caratteristiche in tali strutture FCN ha un impatto limitato sulla generalizzazione. Al contrario, le architetture convoluzionali (CNNs), in particolare nell'impostazione a larghezza finita, hanno mostrato prestazioni superiori. Il nostro quadro teorico per le reti a singolo strato nascosto chiarisce questa disparità. Mentre le prestazioni di una FCN a larghezza infinita possono essere replicate dalla sua controparte a larghezza finita usando specifici priori gaussiani, le CNNs con un singolo strato nascosto convoluzionale subiscono un diverso processo di rinormalizzazione del kernel. A differenza degli aggiustamenti globali osservati nelle reti FC, le CNNs sperimentano una rinormalizzazione localizzata, consentendo la selezione adattiva dei componenti dipendenti dai dati per le previsioni. Questa distinzione enfatizza l'elevata capacità di apprendimento delle caratteristiche presente nelle CNNs sovraparametrizzate, che non si osserva in architetture FC equivalenti.
Collettivamente, questi studi gettano luce sulla profonda influenza della topologia in sistemi diversi, che vanno dal comportamento dei modelli fisici a lungo raggio ai complessi processi di estrazione delle caratteristiche nelle architetture neurali.This research delves into two primary domains: the intricate critical properties of long-range systems and the feature learning mechanisms in deep neural networks.
In the study of long-range systems, we examined the ferromagnetic Ising model in both one and two dimensions, characterized by interactions of the form . Utilizing a novel local dynamics on a dynamical Lévy lattice (DLL), we were able to reproduce the static critical exponents consistent with established literature, based on the interaction parameter . This localized approach offers a versatile methodology to probe the dynamical properties of various long-range models. Notably, our analysis of the relaxation time at the critical temperature revealed nuances in the relationship between the dynamical exponent and the decay parameter , suggesting a potential disparity between dynamical and equilibrium critical properties. Moreover, due to the versatility of our strategy (DLL), we were able to conduct preliminary work in the study of the critical properties of the Long Range model.
Turning to deep neural networks, we explored the disparities in feature learning between fully-connected networks (FCN) and convolutional architectures (CNNs). Empirical studies on fully-connected networks in the infinite-width regime revealed a plateau in performance enhancement, attributed to the static nature of their kernel during training. This suggests that any inherent feature learning in such FCN structures has limited impact on generalization. Conversely, convolutional architectures (CNNs), particularly in the finite-width setting, have shown superior performance. Our theoretical framework for single hidden layer networks elucidates this disparity. While an infinite-width FCN's performance can be replicated by its finite-width counterpart using specific Gaussian priors, CNNs with a single convolutional hidden layer undergo a different kernel renormalization process. Unlike the global adjustments seen in FC networks, CNNs experience a localized renormalization, enabling adaptive selection of data-dependent components for predictions. This distinction emphasizes the advanced feature learning potential present in overparametrized shallow CNNs, which is not observed in equivalent FC architectures.
Collectively, these studies shed light on the profound influence of topology in diverse systems, ranging from the behavior of long-range physical models to the intricate feature extraction processes in neural architectures
Development of analysis techniques for electromagnetic and electrical methods
No full textThe thesis stands as a pivotal contribution in the development of analysis techniques within the realm of Electromagnetic and Electrical methods, specifically delving into geological risks like landslides and levees. The urgency of this research is underscored by recent catastrophic events, including landslides and levee failures during floods, intensified by unforeseen and intense rainfall events that have raised concerns about the impacts of climate change. At its core, the thesis aims to comprehensively address and illuminate various facets of geophysics. Each chapter within the thesis serves a distinct purpose in advancing knowledge in the field. The methodological foundation of this thesis is multi-layered. One crucial facet involves the meticulous calibration of electromagnetic (EMI) data, a process specifically applied to segments of a levee subjected to multiarray EMI surveys. This calibration process is not merely a technical step but a strategic one, as it enables the transposition of the entire survey onto "ERT-like" images. This transposition is integral, enhancing the identification of vulnerabilities in river embankments, a critical aspect for averting potential failures that could have cascading consequences. Another pivotal aspect of the research involves the development of innovative self-potential (SP) survey techniques. This encompasses both conventional (Fixed-Base and Leapfrog) and non-conventional (Sparse Gradient and Full Sparse Gradient) arrays, reflecting a nuanced approach to data acquisition and analysis. Such an approach acknowledges the complexity of geological structures and strives to capture a comprehensive understanding through diverse survey techniques. The research unfolds with noteworthy findings that extend beyond the mere application of methodologies. It becomes evident that the use of new-concept instrumentations like FullWaver serves as a catalyst, facilitating detailed SP surveys with both conventional and unconventional arrays. The breakthrough realization emerges that meaningful SP values can be derived, even in scenarios involving stainless-steel electrodes. This finding is particularly significant, broadening the potential application of SP surveys, including data obtained from electrical resistivity tomography surveys. Moreover, the recoverable SP signal is showcased as not just a data point but a qualitatively useful insight. The exploration of the Amplitude Signal Analytic technique, when applied to the Sparse Gradient array, further enhances the arsenal of tools available for reconnaissance of the source of SP anomalies, marking a significant stride in the interpretative capabilities of SP data. In drawing conclusions, the ramifications of this study extend far beyond the academic realm. The thesis promises real-world impact with practical solutions and insights, addressing vulnerability identification, preventing river embankment failures, which might guide proactive measures against geological hazards
Fare / disfare. L'identità di una capitale europea fuori dall'Europa: Miensk (Minsk)
No full textQual è il rapporto tra l'identità della variegata nazione bielorussa e la rappresentazione della città capitale, dalla scala architettonica a quella urbana, alla luce delle vicende che l'hanno vista più volte soccombere nel corso dei secoli? La presenza di residui architetture pre-sovietiche, moderniste, staliniste, brutaliste, finte antiche, facciataste, post-moderne, decostruttiviste, fino alla ricerca di uno stile identitario lungi dall'essere standardizzato, può indicare - a ritroso - una risposta.What is the relationship between the identity of the variegated Belarusian nation and the representation of the capitai city, from the architectural to the urban scale, in the light of the events that have seen it succumb several times over the centuries? The presence of residuai pre-Soviet, modernist, stalinist, brutalist, faux-ancient, facadeist, post-modem, deconstructivist architectures, up to the search for an identity style far from being standardized, can indicate - backwards - an answer
Reinventing tin packaging: evolution and innovation in packaging for baked goods and confectionery products
No full textQuesta tesi ripercorre l’evoluzione del packaging in latta per i prodotti dolciari, esplorando la sua storia, i processi di lavorazione e lo sviluppo del design. Attraverso l’analisi di casi studio reali, vengono create linee guida per un packaging che unisca tradizione e modernità, integrando soluzioni di smart packaging. La tesi si conclude con la proposta di un packaging innovativo, supportato da nuove strategie promozionali dinamiche e interattive, capaci di rispondere alle sfide contemporanee del mercato e coinvolgere attivamente i consumatoriThis thesis traces the evolution of tin packaging for baked goods and confectionery products, exploring its history, production processes, and design development. Through the analysis of real-world case studies, it establishes guidelines for packaging that blends tradition and modernity, incorporating smart packaging solutions. The thesis concludes with the proposal of an innovative packaging concept, supported by new dynamic and interactive promotional strategies designed to address contemporary market challenges and actively engage consumer
New tools for authentication and traceability to assure the integrity of pig chain
No full textSeveral voluntary label claims are declared on the label of meat and meat-based products assuring high-quality food with peculiar properties - Raised without antibiotics, No antibiotics ever, Antibiotic-Free - as a consequence of the green transition that meat production systems have undergone. This trend may hide novel threats to the integrity of food systems since new kinds of fraudulent practices may emerge. In this regard, approaching the issue with the classic tools may be not successful in the modern meat market since new assurances may require innovative approaches. The omics sciences represent an emerging field spread on distinct levels - Genomic, Transcriptomic, Proteomic, Metabolomic, and Lipidomic - widely explored in different scientific fields such as food authenticity, and precision medicine. Among the omics hierarchy, the metabolome represents the most sensitive to internal factors like the health status of the organism, and the genetic background and to external factors like environmental inputs, nutrition, and pollutants. All these factors can affect the phenotypic outcome of an organism which can be investigated on metabolite levels through metabolomics. In this Ph.D. thesis, the definition of animal welfare was considered as a starting point to gain a comprehensive overview of the internal and external factors affecting animals’ phenotypic outcomes. Finally, the theoretical framework allowed to set up the experimental framework by employing the untargeted metabolomic approach to compare two different phenotypes of pigs, antibiotic-free and antibiotic-treated, respectively. Therefore, the current Ph.D. thesis was divided into five parts, as follows. In the first chapter, Introduction, a brief contextualization of the case of the antibiotic-free claim as a vulnerable factor for the integrity of the meat chain was outlined considering the scientific and legislative background and the future projections. In the second chapter, Aims of the Ph.D. thesis, both the overall scope of the present thesis and the aim of each study were described. The third chapter is organized into two main sections dealing with the feasibility of metabolomics as a new tool to explore animal welfare and the case of antibiotic-free label claims. In the first section, Metabolomic Insights into Animal Welfare, both the Animal Welfare definition and the application of omics approaches in the field of animal sciences were reviewed. All domains - nutrition (I), environment (II), health (III), behaviour (IV), and mental state (V)- were discussed considering the omics application within each domain. Additionally, the workflow of metabolomics was described to discuss the feasibility of this approach as new a tool for investigating new objects in the field of animal welfare. In the second section, Metabolomic insights into Antibiotic-Free label claims, three case studies exploring both an NMR- and HRMS-based untargeted metabolomics for the comparison between antibiotic-free versus antibiotic-treated pigs were illustrated. In the fourth chapter, Discussion, a general discussion about all the critical aspects was performed to highlight critical points both on experimental and theoretical levels. The fifth chapter, Conclusion, overall conclusion, and outlooks were outlined
Exploring regenerative medicine as an innovative treatment for bacterial infectious diseases: preliminary investigation on the antimicrobial activity of activated platelets supernatant and extracellular vesicles
No full textRegenerative medicine is a relatively new branch of medical scientific research and, as
time passes by, it is gaining more and more attention. Indeed, many studies have already
proved that it can be highly promising in the treatment of inflammatory and immuno mediated diseases. Only recently have scientists begun to explore its potential in the
treatment of infectious diseases, due to the rise of antimicrobial resistance and the urgent
need to find alternatives to traditional antibiotics. The hope is, therefore, to find
regenerative medicine products that could act as alternatives to traditional antibiotics, or
that could at least potentiate them, thus counteracting effectively and safely the
phenomenon of antimicrobial resistance in human and veterinary medicine. The first part
of this thesis will mainly focus on the direct and indirect antimicrobial activity of two
products of regenerative medicine: mesenchymal stromal cells (MSCs), platelet rich
plasma (PRP) and their respective extracellular vesicles (EVs). The second part of this
thesis is, instead, a preliminary in vitro study on the antibacterial properties of bovine
activated-platelets-derived supernatant and isolated extracellular vesicles on some of the
most common mastitis-causing bacteria: Staphylococcus aureus (methicillin-sensible and
methicillin-resistant), Streptococcus agalactiae and Escherichia coli