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Paleoproteomics and osteoarchaeology: sex and species determination from fragmentary bone remains
Get PDFLa buona riuscita delle analisi archeozoologiche e antropologiche è molto condizionata dallo stato di conservazione in cui si trova il reperto da analizzare. Soprattutto nei siti paleolitici, l’alto tasso di frammentazione dei resti può ostacolare l’ottenimento delle informazioni, compromettendo la comprensione del contesto preso in esame. Il presente studio ha avuto come scopo quello di sperimentare e proporre un protocollo metodologico che supportasse l’approccio morfologico tradizionale combinandolo con quello proteomico. Diverse sono le problematiche affrontate: la penuria di informazioni tassonomiche ricavabili da contesti paleolitici con ossa particolarmente frammentate, l’impossibilità di ottenere dati sulla stima del sesso in individui non adulti e la limitata attendibilità nell’ottenimento della determinazione del sesso negli individui privi dei distretti scheletrici sessualmente dimorfici. Nel primo caso, lo studio morfologico di resti provenienti da contesti di transizione tra Paleolitico medio e superiore è stato combinato alla ZooMS (Zooarchaeology by mass spectrometry) una tecnica di peptide mass fingerprinting che permette di identificare la specie di un frammento osseo tramite l’analisi della proteina più abbondante all’interno delle ossa, il collagene I. L’analisi dell’amelogenina, una proteina contenuta all’interno dello smalto dentale, è stata proposta come metodo alternativo per la stima del sesso, applicata a diversi casi studio per avvalorare la sua affidabilità. Il metodo qui proposto ha permesso di rendere informativi dei frammenti ossei e dentari indeterminati che normalmente non avrebbero contribuito, se non marginalmente, alle analisi archeozoologiche e antropologiche.The success of the archaeozoological and anthropological analyses is conditioned by the state of conservation of the samples. Especially in the paleolithic sites, the high rate of fragmentation of the remains can hinder the obtaining of the information, compromising the understanding of the context. The purpose of this study was to experiment and propose a methodological protocol that supported the traditional morphological approach combining it with the proteomic one. Several problems were addressed: the shortage of taxonomic information from paleolithic contexts with particularly fragmented bones, the impossibility of obtaining data on the estimation of sex in non adult individuals and the limited reliability in obtaining the determination of sex in individuals without sexually dimorphic skeletal districts. In the first case, the morphological study of rests coming from contexts of transition between middle and upper Paleolithic has been combined to the ZooMS (Zooarchaeology by mass Spectrometry) a peptide mass fingerprinting technique that allows the identification of the species of a bone fragment through the analysis of the most abundant protein within bones, collagen I. The analysis of amelogenin, a protein contained within the dental enamel, has been proposed as an alternative method for estimating sex, applied to several case studies to substantiate its reliability. The method proposed here has made it possible to obtain information from indeterminate bone and dental fragments that would not normally have contributed, if not marginally, to archaeozoological and anthropological analyses
Innovative strategies for the mitigation of acrylamide content in different food products
Get PDFAcrylamide (AA) is an undesirable food toxic compound, classified as 'probably carcinogenic to humans' by the International Agency for Research on Cancer due to its toxic effects, including neurotoxicity, genotoxicity, carcinogenicity and reproductive toxicity. AA is mainly formed during the heat treatment of foods (> 120 °C) by the Maillard reaction, an essential reaction that also allows the desired levels of shelf-life and sensory properties of various food products to be achieved. Over the years, authorities and regulations have become more restrictive regarding the maximum levels of AA permitted in foods and beverages. The latest Commission Regulation (EU) 2017/2158 contains reference levels and measures to reduce AA in several food groups that contribute to the highest dietary intake, making necessary the study of promising AA mitigation strategies.
The aim of this PhD research project was to identify, characterise and optimise some AA mitigation strategies in the most at-risk widely consumed foods such as potato, coffee and bakery products. Some AA control strategies were selected and investigated for each food category, also considering the main quality characteristics of the final products.
The comprehensive results obtained during the three years of research activity have allowed a deeper knowledge of the traditional and innovative AA mitigation strategies, which can be extremely useful for both the food industry and international authorities. The most promising strategies studied in terms of reduction of AA while maintaining the main quality characteristics of the examined foods were: the application of pulsed electric fields and yeast immersion as pre-treatments of chips for frying; the selection of high roasting degrees for coffee products; the selection of static baking conditions for biscuits; the optimisation of alternative biscuit’ formulations by both the use of chickpea legume flour and of flour from bean with intact cotyledon cell walls
Essays on Information Economics
Get PDFThis thesis consists of three essays on information economics. I explore how information is strategically communicated or designed by senders who aim to influence the decisions of a receiver. In the first chapter, I study a cheap talk game between two imperfectly informed experts and a decision maker. The experts receive noisy signals about the state and sequentially communicate the relevant information to the decision maker. I refine the self-serving belief system under uncertainty and Ι characterise the most informative equilibrium that might arise in such environments.In the second chapter, I consider the case where a decision maker seeks advice from a biased expert who cares also about establishing a reputation of being competent. The expert has the incentives to misreport her information but she faces a trade-off between the gain from misrepresentation and the potential reputation loss. I show that the equilibrium is fully-revealing if the expert is not too biased and not too highly reputable. If there is competition between two experts the information transmission is always improved. However, in cases where the experts are more than two the result is ambiguous, and it depends on the players’ prior belief over states.In the last chapter, I consider a model of strategic communication where a privately and imperfectly informed sender can persuade a receiver. The sender may receive favorable or unfavorable private information about her preferred state. I describe two ways that are adopted in real life situations and theoretically improve equilibrium informativeness given sender's private information. First, a policy that suggests symmetry constraints to the experiments' choice. Second, an approval strategy characterised by a low precision threshold where the receiver will accept the sender with a positive probability and a higher one where the sender will be accepted with certainty
Science of retracted science: a citation analysis of the arts and humanities domain
Get PDFIn the scholarly publishing domain, a retraction is raised when a specific publication is considered erroneous by the venue in which it appeared after it was published. The aim of this work is uncovering new insights and learn new important information to help us understand the retraction phenomenon in the arts and humanities domain. Our investigation is based on a methodology defined using quantitative and qualitative measures derived from previous studies in the transdisciplinary research field of “science of science” (SciSci). The designed methodology takes into account a general case of retraction and applies a citation analysis based on five phases. Citations to retracted publications (before and after their retraction) are gathered and characterized with a set of attributes, including general metadata and information extracted from citing entities’ full text. The annotated characteristics are further considered for a statistical and a textual analysis (i.e., a topic modeling analysis). The contribution of this thesis is grounded by addressing the following research questions: (RQ1) How did scholarly research cite retracted humanities publications before and after their retraction? (RQ2) Did all the humanities areas behave similarly concerning the retraction phenomenon? (RQ3) What are the main differences and similarities in the retraction dynamics between the humanities domain and the STEM disciplines? RQ1 and RQ2 are addressed by tuning and applying the methodology on the analysis of the retracted publications in the humanities domain. RQ3 is addressed on two levels, i.e., considering and comparing: (L1) the outcomes of the past studies on the retraction in STEM, and (L2) the results obtained from an analysis of a retraction case in STEM using the defined methodology
Interrogation of human monoclonal antibodies induced by 4C-MenB to identify protective antigens contained in the OMV component
Get PDFNeisseria meningitidis is a gram negative human obligated pathogen, mostly found as a commensal in the oropharyngeal mucosa of healthy individuals. It can invade this epithelium determining rare but devastating and fast progressing outcomes, such as meningococcal meningitidis and septicemia, leading to death (about 135000 per year worldwide).
Conjugated vaccines for serogroups A, C, W135, X and Y were developed, while for N. meningitidis serogroup B (MenB) the vaccines were based on Outern Membrane Vesicles (OMV). One of them is the 4C-MenB (Bexsero).
The antigens included in this vaccine’s formulation are, in addition to the OMV from New Zeland epidemic strain 98/254, three recombinant proteins: NadA, NHBA and fHbp. While the role of these recombinant components was deeply characterized, the vesicular contribution in 4C-MenB elicited protection is mediated mainly by porin A and other unidentified antigens.
To unravel the relative contribution of these different antigens in eliciting protective antibody responses, we isolated human monoclonal antibodies (mAbs) from single-cell sorted plasmablasts of 3 adult vaccinees peripheral blood. mAbs have been screened for binding to 4C-MenB components by Luminex bead-based assay. OMV-specific mAbs were purified and tested for functionality by serum bactericidal assay (SBA) on 18 different MenB strains and characterized in a protein microarray containing a panel of prioritized meningococcal proteins. The bactericidal mAbs identified to recognize the outer membrane proteins PorA and PorB, stating the importance of PorB in cross-strain protection. In addition, RmpM, BamE, Hyp1065 and ComL were found as immunogenic components of the 4C-MenB vaccine
Integrating Machine Learning Paradigms for Predictive Maintenance in the Fourth Industrial Revolution era
Get PDFIn the last decade, manufacturing companies have been facing two significant challenges. First, digitalization imposes adopting Industry 4.0 technologies and allows creating smart, connected, self-aware, and self-predictive factories. Second, the attention on sustainability imposes to evaluate and reduce the impact of the implemented solutions from economic and social points of view. In manufacturing companies, the maintenance of physical assets assumes a critical role. Increasing the reliability and the availability of production systems leads to the minimization of systems’ downtimes; In addition, the proper system functioning avoids production wastes and potentially catastrophic accidents. Digitalization and new ICT technologies have assumed a relevant role in maintenance strategies. They allow assessing the health condition of machinery at any point in time. Moreover, they allow predicting the future behavior of machinery so that maintenance interventions can be planned, and the useful life of components can be exploited until the time instant before their fault.
This dissertation provides insights on Predictive Maintenance goals and tools in Industry 4.0 and proposes a novel data acquisition, processing, sharing, and storage framework that addresses typical issues machine producers and users encounter. The research elaborates on two research questions that narrow down the potential approaches to data acquisition, processing, and analysis for fault diagnostics in evolving environments. The research activity is developed according to a research framework, where the research questions are addressed by research levers that are explored according to research topics. Each topic requires a specific set of methods and approaches; however, the overarching methodological approach presented in this dissertation includes three fundamental aspects: the maximization of the quality level of input data, the use of Machine Learning methods for data analysis, and the use of case studies deriving from both controlled environments (laboratory) and real-world instances
The Mysteries of Samothrace: Origins of the cult
Get PDFEn el presente trabajo de investigación se aborda la cuestión del origen de los Misterios de Samotracia. Se hace desde una perspectiva novedosa y multidisciplinar; pues, además de las informaciones y opiniones foráneas de los autores de la Antigüedad, se tienen por primera vez en cuenta los testimonios arqueológicos, epigráficos, numismáticos e iconográficos procedentes de la propia isla. Se examinan su territorio (la isla y su entorno, los mitos y leyendas, la toponimia), su culto (las teorías sobre su fundación, el santuario, los dioses) y su historia (desde el Neolítico hasta la Edad del Hierro), para averiguar qué poblaciones habitaron en Samotracia antes de que ésta fuera colonizada por los griegos; con el fin de descubrir la cultura con que éstos habrían tropezado y de la cual habrían heredado su culto. Se llega a la conclusión de que dicha cultura habría sido la tracia; y de que, en origen, en el culto mistérico samotracio habrían sido venerados la “Madre de los Dioses” tracia y Sabacio.Nel presente lavoro di ricerca si affronta la questione dell'origine dei Misteri di Samotracia. Si fa da una prospettiva innovativa e multidisciplinare; poiché, oltre alle informazioni ed alle opinioni esterne degli autori dell'Antichità, per la prima volta si tengono conto delle testimonianze archeologiche, epigrafiche, numismatiche ed iconografiche provenienti dall'isola stessa. Si esaminano il suo territorio (l'isola ed i suoi dintorni, i miti e leggende, la toponimia), il suo culto (le teorie sulla sua fondazione, il santuario, gli dèi) e la sua storia (dal Neolitico all'Età del Ferro), per capire quali popolazioni abitarono Samotracia prima che questa fosse colonizzata dai Greci; al fine di scoprire la cultura in cui essi si sarebbero imbattuti e dalla quale avrebbero ereditato il loro culto. Si arriva alla conclusione che tale cultura sarebbe stata la tracia; e che, in origine, al culto misterico samotracio sarebbero stati venerati la “Madre degli Dèi” tracia e Sabazio.This research work addresses the question of the origins of the Samothracian Mysteries. It is done from a new and multidisciplinary perspective; since, in addition to the foreign information and opinions of the authors of Antiquity, for the first time it takes into account the archaeological, epigraphical, numismatical and iconographical testimonies from the island itself. It examines its territory (the island and its surroundings, the myths and legends, the toponymy), its cult (the theories about its foundation, the sanctuary, the gods) and its history (from the Neolithic to the Iron Age), to find out which populations dwelled on Samothrace before it was colonized by the Greeks; in order to discover the culture they would have encountered and from which they would have inherited their cult. It reaches the conclusion that this culture was the Thracian; and that, originally, at the Samothracian mystery cult were venerated the Thracian “Mother of the Gods” and Sabazius
Advanced voxel-based CAD modelling for FSI simulations for automotive structures design
Get PDFAdditive 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
On the role of Computational Logic in Data Science: representing, learning, reasoning, and explaining knowledge
Get PDFIn this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys-
tem can be reified into actual software technology and extended towards many DS-related directions
Towards Unstructured Knowledge Integration in Natural Language Processing
Get PDFIn the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep learning. In particular, purely data-driven approaches have opened to a wide variety of successful applications due to the large availability of data. Nonetheless, the integration of prior knowledge is still required to compensate for specific issues like lack of generalization from limited data, fairness, robustness, and biases.
In this thesis, we analyze the methodology of integrating knowledge into deep learning models in the field of Natural Language Processing (NLP). We start by remarking on the importance of knowledge integration. We highlight the possible shortcomings of these approaches and investigate the implications of integrating unstructured textual knowledge.
We introduce Unstructured Knowledge Integration (UKI) as the process of integrating unstructured knowledge into machine learning models. We discuss UKI in the field of NLP, where knowledge is represented in a natural language format. We identify UKI as a complex process comprised of multiple sub-processes, different knowledge types, and knowledge integration properties to guarantee. We remark on the challenges of integrating unstructured textual knowledge and bridge connections with well-known research areas in NLP.
We provide a unified vision of structured knowledge extraction (KE) and UKI by identifying KE as a sub-process of UKI.
We investigate some challenging scenarios where structured knowledge is not a feasible prior assumption and formulate each task from the point of view of UKI. We adopt simple yet effective neural architectures and discuss the challenges of such an approach.
Finally, we identify KE as a form of symbolic representation. From this perspective, we remark on the need of defining sophisticated UKI processes to verify the validity of knowledge integration. To this end, we foresee frameworks capable of combining symbolic and sub-symbolic representations for learning as a solution