Use of behavioural patterns to analyze transport stress in piglets and young bulls. The influence of individual coping characteristics in stress response.

In modern farm systems the economic interests make reducing the risks related to transport practice an important goal. An increasing attention is directed to the welfare of animals in transit, also considering the new existing facilities. In recent years the results coming from the study of animal farm behaviour were used as tool to assess the welfare. In this thesis were analyzed behavioural patterns, jointly with blood variables, to evaluate the stress response of piglets and young bulls during transport. Since the animal behaviour could be different between individuals and these differences can affect animal responses to aversive situations, the individual behavioural characteristics were taken in account. Regarding young bulls, selected to genetic evaluation, the individual behaviour was investigated before, during and after transport, while for piglets was adopted a tested methodology classification and behavioural tests to observe their coping characteristics. The aim of this thesis was to analyse the behavioural and physiological response of young bulls and piglets to transport practice and to investigate if coping characteristics may affect how piglets cope with aversive situations. The thesis is composed by four experimental studies. The first one aims to identify the best existent methodology classification of piglets coping style between those that were credited in literature. The second one investigated the differences in response to novel situations of piglets with different coping styles. The last studies evaluated the stress response of piglets and young bulls to road transportation. The results obtained show that transport did not affect the behaviour and homeostasis of young animals which respond in a different way from adults. However the understanding of individual behavioural characteristic and the use of behavioural patterns, in addition to blood analyses, need to be more investigated in order to be useful tools to assess the animal response in aversive situation.

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Structural patterns for document engineering: from an empirical bottom-up analysis to an ontological theory

This thesis aims at investigating a new approach to document analysis based on the idea of structural patterns in XML vocabularies. My work is founded on the belief that authors do naturally converge to a reasonable use of markup languages and that extreme, yet valid instances are rare and limited. Actual documents, therefore, may be used to derive classes of elements (patterns) persisting across documents and distilling the conceptualization of the documents and their components, and may give ground for automatic tools and services that rely on no background information (such as schemas) at all. The central part of my work consists in introducing from the ground up a formal theory of eight structural patterns (with three sub-patterns) that are able to express the logical organization of any XML document, and verifying their identifiability in a number of different vocabularies. This model is characterized by and validated against three main dimensions: terseness (i.e. the ability to represent the structure of a document with a small number of objects and composition rules), coverage (i.e. the ability to capture any possible situation in any document) and expressiveness (i.e. the ability to make explicit the semantics of structures, relations and dependencies). An algorithm for the automatic recognition of structural patterns is then presented, together with an evaluation of the results of a test performed on a set of more than 1100 documents from eight very different vocabularies. This language-independent analysis confirms the ability of patterns to capture and summarize the guidelines used by the authors in their everyday practice. Finally, I present some systems that work directly on the pattern-based representation of documents. The ability of these tools to cover very different situations and contexts confirms the effectiveness of the model.