Uma rede é um conjunto de nós conectados entre si através de um conjunto de arestas. Redes podem representar qualquer conjunto de objetos que possuam relações entre si. Comunidades são conjuntos de nós relacionados de uma maneira significativa, provavelmente compartilhando propriedades e/ou atuando de forma similar dentro de uma rede. Quando a análise de redes é aplicada ao estudo de padrões de movimentação animal, as unidades epidemiológicas de interesse (propriedades, estabelecimentos, municípios, estados, países, etc) são representadas como nós, enquanto a movimentação animal entre elas é representada através das arestas de uma rede. Descobrir a estrutura de uma rede, e portanto as preferências e rotas comerciais, pode ser útil para um pesquisador ou gestor de saúde animal. Foi implementado um algoritmo de detecção de comunidades para encontrar grupos de propriedades que é consistente com a definição de circuito pecuário, assumindo que uma comunidade é um grupo de nós (fazendas, abatedouros) no qual um animal vai mais provavelmente permanecer durante sua vida. Este algoritmo foi aplicado na rede interna de movimentação animal de 2007 do Estado do Mato Grosso. Esse banco de dados contém informação sobre 87.899 propriedades e 521.431 movimentações durante o ano, totalizando 15.844.779 de animais movimentados. O algoritmo de detecção de comunidades encontrou uma partição da rede que mostra um claro padrão geográfico e comercial, duas importantes características para aplicações em medicina veterinária preventiva, além de possuir uma interpretação clara e significativa em redes de comércio onde ligações se estabelecem a partir da escolha dos nós envolvidos. / A network is a set of nodes that are linked together by a set of edges. Networks can represent any set of objects that have relations among themselves. Communities are sets of nodes that are related in an important way, probably sharing common properties and/or playing similar roles within a network. When network analysis is applied to study the livestock movement patterns, the epidemiological units of interest (farm premises, counties, states, countries, etc.) are represented as nodes, and animal movements between the nodes are represented as the edges of a network. Unraveling a network structure, and hence the trade preferences and pathways, could be very useful to a researcher or a decision-maker. We implemented a community detection algorithm to find livestock communities that is consistent with the definition of a livestock production zone, assuming that a community is a group of farm premises in which an animal is more likely to stay during its life time than expected by chance. We applied this algorithm to the network of within animal movements made inside the State of Mato Grosso, for the year of 2007. This database holds information about 87,899 premises and 521,431 movements throughout the year, totalizing 15,844,779 animals moved. The community detection algorithm achieved a network partition that shows a clear geographical and commercial pattern, two crucial features to preventive veterinary medicine applications, and also has a meaningful interpretation in trade networks where links emerge from the choice of trader nodes.

Uma rede é um conjunto de nós conectados entre si através de um conjunto de arestas. Redes podem representar qualquer conjunto de objetos que possuam relações entre si. Comunidades são conjuntos de nós relacionados de uma maneira significativa, provavelmente compartilhando propriedades e/ou atuando de forma similar dentro de uma rede. Quando a análise de redes é aplicada ao estudo de padrões de movimentação animal, as unidades epidemiológicas de interesse (propriedades, estabelecimentos, municípios, estados, países, etc) são representadas como nós, enquanto a movimentação animal entre elas é representada através das arestas de uma rede. Descobrir a estrutura de uma rede, e portanto as preferências e rotas comerciais, pode ser útil para um pesquisador ou gestor de saúde animal. Foi implementado um algoritmo de detecção de comunidades para encontrar grupos de propriedades que é consistente com a definição de circuito pecuário, assumindo que uma comunidade é um grupo de nós (fazendas, abatedouros) no qual um animal vai mais provavelmente permanecer durante sua vida. Este algoritmo foi aplicado na rede interna de movimentação animal de 2007 do Estado do Mato Grosso. Esse banco de dados contém informação sobre 87.899 propriedades e 521.431 movimentações durante o ano, totalizando 15.844.779 de animais movimentados. O algoritmo de detecção de comunidades encontrou uma partição da rede que mostra um claro padrão geográfico e comercial, duas importantes características para aplicações em medicina veterinária preventiva, além de possuir uma interpretação clara e significativa em redes de comércio onde ligações se estabelecem a partir da escolha dos nós envolvidos. / A network is a set of nodes that are linked together by a set of edges. Networks can represent any set of objects that have relations among themselves. Communities are sets of nodes that are related in an important way, probably sharing common properties and/or playing similar roles within a network. When network analysis is applied to study the livestock movement patterns, the epidemiological units of interest (farm premises, counties, states, countries, etc.) are represented as nodes, and animal movements between the nodes are represented as the edges of a network. Unraveling a network structure, and hence the trade preferences and pathways, could be very useful to a researcher or a decision-maker. We implemented a community detection algorithm to find livestock communities that is consistent with the definition of a livestock production zone, assuming that a community is a group of farm premises in which an animal is more likely to stay during its life time than expected by chance. We applied this algorithm to the network of within animal movements made inside the State of Mato Grosso, for the year of 2007. This database holds information about 87,899 premises and 521,431 movements throughout the year, totalizing 15,844,779 animals moved. The community detection algorithm achieved a network partition that shows a clear geographical and commercial pattern, two crucial features to preventive veterinary medicine applications, and also has a meaningful interpretation in trade networks where links emerge from the choice of trader nodes.

L'étude de structures de communautés dans les réseaux devient de plus en plus une question importante. La connaissance des modules de base (communautés) des réseaux nous aide à bien comprendre leurs fonctionnements et comportements, et à appréhender les performances de ces systèmes. Une communauté dans un graphe (réseau) est définie comme un ensemble de nœuds qui sont fortement liés entre eux, mais faiblement liés avec le reste du graphe. Les membres de la même communauté partagent les mêmes centres d'intérêt. La plupart des travaux qui existent dans ce domaine se scindent en deux grandes thématiques: la détection de communautés et l'analyse de communautés. La détection de communautés consiste à trouver les communautés dans un réseau donné, sans connaître à priori ni la taille ni le nombre des communautés. La partie analyse de communautés, quant à elle, consiste à étudier les propriétés structurelles et sémantiques des communautés détectées et de celles du réseau étudié. Dans cette thèse, nous nous intéressons à l'étude de structures de communautés dans les réseaux. Nous contribuons dans les deux parties, analyse et détection de communautés. Dans la partie analyse de communautés, nos contributions sont l'étude des communautés dans les réseaux de communication et l'étude des communautés dans les services Web. D'une part, nous étudions l'émergence de communautés dans les réseaux de communication. Nous proposons une classification de structures de communautés émergées dans un réseau de communication donné. Nous modélisons les réseaux par les graphes et nous les caractérisons par un ensemble de paramètres. Nous concluons par une corrélation directe entre le réseau initial et les types de structures de communautés émergées. D'autre part, nous étudions les communautés dans les logs de services Web. Nous analysons les historiques d'exécution (les fichiers logs) afin de découvrir les protocoles métiers de services (séquences de messages échangés entre le service et le client pour aboutir à un but donné). Nous modélisons les logs par les graphes, et nous cherchons l'ensemble de conversations (communautés) issues de notre graphe de messages (le graphe de messages est un graphe induit du graphe de logs). Notre contribution dans la partie détection de communautés, est la proposition d'un algorithme de détection de communautés basé sur les motifs utilisant l'optimisation spectrale. Nous définissons une matrice de modularité motif (particulièrement, le triangle), et nous utilisons l'algorithme de décomposition et d'optimisation spectrale pour détecter les communautés basées sur des motifs. Nous montrons l'apport des communautés basées sur les motifs en appliquant notre algorithme sur des réseaux sociaux connus dans la littérature et en comparant les communautés basées sur les motifs trouvées avec les communautés classiques. / The study of the sub-structure of complex networks is of major importance to relate topology and functionality. Understanding the modular units (communities) of graphs is of utmost importance to grasping knowledge about the functionality and performance of such systems. A community is defined as a group of nodes such that connections between the nodes are denser than connections with the rest of the network. Generally, the members of one community share the same interest. Many efforts have been devoted to the analysis of the modular structure of networks. The most of these works are grouped into two parts: community detection and community analysis. Community detection consists on finding communities in networks whithout knowing there size and number. While the community analysis deals the study of the structural and semantic properties of the emerged communities, and the understanding of the functionality and the performance of the network. In this thesis, we are interested on the study of the community structures in networks. We give contributions in both community analysis and community detection parts. In the community analysis part, we study the communities of communication networks and the communities in web services. On the one hand, we study the community emergence in communication networks. We propose a classification of the emerged community structures in a given network. We model the networks by graphs and we characterize them by some parameters (network size, network density, number of resources in the network, number of providers in the network, etc.). We give also a direct correlation between the network parameters and the emerged community structures. On the other hand, we study the communities in the web service logs. We aim to discover the business protocol of services (sequences of messages exchanged between the service and a client to achieve a given goal). We analyze the log files and we model them by graphs. In our final tree graph (message graph), the paths represent the conversations (communities). In the community detection part, the main goal of our contribution is to determine communities using as building blocks triangular motifs. We propose an approach for triangle community detection based on modularity optimization using the spectral algorithm decomposition and optimization. The resulting algorithm is able to identify efficiently the best partition in communities of triangles of any given network, optimizing their correspondent modularity function.

Οι κρατήρες διαφυγής ρευστών (pockmarks) είναι βυθίσματα σε μαλακά ιζήματα του βυθού, στα παράκτια και πελαγικά οικοσυστήματα. Μελετώνται παγκοσμίως τις τελευταίες τέσσερις δεκαετίες και στον ελληνικό χώρο έχουν εντοπιστεί κυρίως στη Δυτική Ελλάδα. Εξ αυτών, οι περισσότεροι είναι κρατήρες μεθανίου και μόνο στον Ελαιώνα Αιγίου και στον όρμο του Πρίνου έχουν βρεθεί κρατήρες γλυκού νερού. Έως τώρα, η μελέτη της βιολογίας των κρατήρων έχει εστιάσει κυρίως την περίπτωση των κρατήρων μεθανίου. Για τους κρατήρες γλυκού νερού δεν υπάρχουν εργασίες σχετικά με τη βιολογία τους, εκτός από μια η οποία αφορά τη μικροβιακή δράση στο ίζημα. Στον Ελαιώνα οπτική παρατήρηση έδειξε την ύπαρξη πληθώρας βενθικών οργανισμών, οι οποίοι απουσιάζουν από τον ευρύτερο πυθμένα. Το φαινόμενο αυτό έχει παρατηρηθεί σε πολλούς κρατήρες παγκοσμίως και θεωρείται ότι σχετίζεται κυρίως με τη φύση του υποστρώματος στο εσωτερικό της δομής των κρατήρων. Γενικά, υπάρχει πολύ περιορισμένη πληροφορία για το αβιοτικό και βιοτικό περιβάλλον των κρατήρων, ιδιαίτερα στη στήλη του νερού, ενώ δεν είναι σαφές το αν οι δομές αυτές μπορούν να αποτελέσουν διαταραγμένα περιβάλλοντα ή οάσεις οργανισμών. Η παρούσα εργασία διερευνά το πλαγκτικό στοιχείο στους κρατήρες γλυκού νερού του Ελαιώνα και αποτελεί την πρώτη σχετική αναφορά σε διεθνές επίπεδο, τουλάχιστον σε ότι σχετίζεται με το ζωοπλαγκτόν. Για τη μελέτη συλλέχθηκε μικρο- και μεσοζωοπλαγκτόν, έτσι ώστε να διερευνηθεί όλο το εύρος μεγέθους των οργανισμών από 50 μm έως 20 mm. Οι κρατήρες που μελετήθηκαν παρουσίασαν μικρή εκροή γλυκού νερού. Μετρήσεις θρεπτικών ιόντων και χλωροφύλλης -α έδειξαν ότι οι κρατήρες δεν επηρέασαν φυσικοχημικά το θαλάσσιο περιβάλλον. Ωστόσο, παρατηρήθηκε αύξηση της Chl-a κοντά στο στόμιο του κρατήρα και της φαιοφυτίνης (προϊόν αποδόμησης της Chl-a) και των θρεπτικών στο εσωτερικό του κρατήρα. Ως προς το ζωοπλαγκτόν, οι κρατήρες βρέθηκαν να συγκεντρώνουν μεγαλύτερες αφθονίες πελαγικών προνυμφών βενθικών οργανισμών που εγκαθίστανται στο εσωτερικό τους, όπως έχει επιβεβαιωθεί με οπτική παρατήρηση, καθώς και ειδών Αρπακτικοειδών και Ποικιλοστοματοειδών Κωπηπόδων (ενηλίκων, κωπηποδιτών, ναυπλίων). Τα εν λόγω κωπήποδα πιθανόν να σχετίζονται με την παρουσία αυξημένου αιωρούμενου οργανικού υλικού στους κρατήρες και ζελατινοειδών διηθηματοφάγων οργανισμών (κωπηλατών, βυτιοειδών) σε αυτούς. Επιπλέον, η αυξημένη συγκέντρωση ναυπλίων και κωπηποδιτικών σταδίων υποθέτουμε ότι μπορεί να σχετίζεται με την αυξημένη παρουσία αυγών κωπηπόδων, εφόσον η δομή του κρατήρα μπορεί να τα συγκεντρώνει. Επειδή η παρούσα μελέτη πραγματοποιήθηκε σε μια περίοδο ανάμιξης του νερού και μια περίοδο ασθενούς θερμοστρωμάτωσης, θεωρούμε ότι οι παρατηρήσεις μας για το ζωοπλαγκτόν δεν εμφανίζουν έντονο ‘’σήμα’’ και προτείνεται επανάληψη της έρευνας σε περίοδο έντονης θερμοστρωμάτωσης. / Pockmarks are seabed depressions on soft sediments, found in coastal and pelagic ecosystems. They have been studied for the last four decades and in Greece they can be found mainly in the western parts of the country. Most of the pockmarks are methane formatted, while groundwater formatted pockmarks have been found in Greece only in Elaionas bay and Prinos bay. So far, only methane pockmarks have been studied, concerning their biological components, and there are no references for the groundwater formatted ones, except one that focused on the microbial activity in the sediments. In Elaionas bay optical observations revealed the presence of an extensive benthic community that lacks from the surrounding seabed. This has been observed in a number of pockmarks worldwide and is believed to be co occurring with the presence of hard substrates in the pockmarks. Generally, there is little information of the biotic and abiotic environment of the pockmarks, especially in the water column, while it is not yet clear if these depressions should be considered as disturbed environments or local oasis for the organisms in the area. This study is focusing on the planktonic component of the pockmark field at Elaionas bay and to our knowledge it is the first attempt internationally, at least when it comes to zooplankton. Mesozooplankton and microzooplankton samples were collected in order to investigate the whole basic size range of the zooplankton community (50 μm to 20 mm). The studied pockmarks exhibited slight groundwater flow. Nutrient and chlorophyll a concentrations showed no physicochemical ‘’signal’’ in the pockmarks. However, there was a trend of increase of Chl –a near the opening of the pockmark and of phaeophytin and nutrients inside the pockmark. As for zooplankton, there is evidence that greater abundances of pelagic larvae of benthic organisms are concentrated in the pockmarks (the presence of the adults has been confirmed by divers and ROV), as well as some species of the Order Harpacticoida and Poecilostomatoida (adults, copepodites, nauplii). These copepods may be related to the increase of dissolved organic matter in the pockmark and the presence of tunicates (appendicularians, doliolids) also found concentrated in the pockmarks. Increased abundance of nauplii and copepodite stages in the pockmark is believed to result from the increase of copepod eggs, assuming that the pockmark can gather and retain them. Repetition of the sampling procedure at the pockmark field on a different season is necessary, because the lack of a strong thermocline suggests that any strong differences between the pockmark and the surrounding environment are being less detectible.

La Nouvelle-Calédonie qui présente une biodiversité à la fois exceptionnelle et très menacée, fait partie des points chauds de biodiversités définis à l'échelle globale comme zones prioritaires pour la conservation. Les incendies, d'origines anthropiques et constituant l'une des principales menaces pesant sur les écosystèmes naturels néo-calédoniens, conduisent à un recul des forêts denses humides (forêts par la suite) principalement au profit des savanes sur substrats volcano-sedimentaires. Au cours de cette thèse, les processus écologiques mis en jeu dans les dynamiques des forêts et des savanes, liés aux variations du régime d'incendie, ont été étudiés à différentes échelles spatiales et temporelles. L'analyse de la distribution spatio-temporelle des forêts et des savanes à l'échelle du paysage a mis en évidence différents facteurs dirigeant la dynamique paysagères et identifié des zones de recolonisation forestière. Différents modèles de succession secondaire et cortèges d'espèces pionnières ont été identifiés à partir de l'analyse de ces zones de recolonisation. La mesure de traits fonctionnels et l'utilisation de modèles semi-physiques de dommages causés par les incendies ont révélé une faible tolérance aux incendies de ces espèces. Enfin, une analyse multivariée de la structure, de la composition floristique et des conditions micro-climatiques des zones clés de transitions entre la savane et la forêt a permis de mieux comprendre les processus d'expansion et de contraction forestière. / New Caledonia, which presents both an exceptional and highly endangered biodiversity, is one of the worldwide biodiversity hotspots for conservation priority. Human-induced fires, which are one of the main threats to natural ecosystems in New Caledonia, lead to the expansion of savannas on volcano-sedimentary substrates at the expense of rainforests. In this thesis, the ecological processes, which are involved in the dynamics of rainforests and savannas and related to changes in fire regime, have been studied at different spatial and temporal scales. The analysis of the spatio-temporal distribution of rainforests and savannas across the landscape allowed us to both point-out the different drivers of their dynamics and to identify areas of rainforest recolonization. Different secondary succession patterns and pioneer species assemblages were identified from the analysis of these areas of recolonization. The analysis of measured functional traits and the use of semi-physical models of fire-caused damages highlighted the low tolerance of these pioneer species to fire. Finally, a multivariate analysis of the structure, the floristic composition and the micro-climatic conditions of transitional zones between savanna and rainforest, has allowed us to better understand the processes of rainforest's expansion and contraction. This thesis opens a new field of research in New Caledonia with important implications in rainforest's restoration and sustainable management.

<p>  </p> <p>Plant roots form an intimate relationship with a diversity of soil microorganisms. Some soil-borne microbes cause harmful diseases on crops, but others promote plant growth and enhance host resilience against stressors. Beneficial bacteria have a high potential as a strategy for sustainable agricultural management, many of which have been recognized and commercialized for improving crop growth. Unfortunately, field inoculants of beneficial bacteria often give inconsistent results due to various environmental factors hindering their beneficial properties. Improving crop production utilizing beneficial bacteria requires two approaches: 1) breeding for crops with the enhanced association for beneficial bacteria and 2) improving formulation methods for producing more potent microbial products. To contribute to these goals, we address three critical questions utilizing the tomato root microbiome as a model system. First, we asked how beneficial root-associated bacteria could be efficiently identified. We developed a strategy to select beneficial bacteria from a novel collection of 183 bacterial endophytes isolated from roots of two field-grown tomato species. The results suggest that isolates with similar traits impact plant growth at the same levels, regardless of their taxonomic classification or host origin. Next, we asked whether host genetics contribute to the root microbiome assembly and response to beneficial microbes. An assessment of the root microbiome profile and plant binary interaction experiments suggested the role of host genetics in influencing root recruitment and response to beneficial bacteria. Subsequently, we asked whether root-associated bacteria induce physiological changes in root tissues in the host. We identified two isolates from our bacterial endophyte collection that significantly promoted the growth of tomato genotype H7996 (<em>Solanum lycopersicum</em>). Plant-binary interaction experiments suggested a significant increase of cell wall lignification in the root vasculature starting 96-hour post-inoculation with beneficial bacteria. Additional studies are needed to uncover a possible correlation between the induced vasculature lignification and the growth-promoting effects of the two isolates on H7996. Altogether, our findings highlight the multi-faceted role of root-associated bacteria in promoting plant growth and support the development of crop improvement strategies in optimizing host association with soil bacteria.</p>

[pt] Esta pesquisa de tese teve como objetivo explorar a análise de mídias sociais, especialmente as disponíveis em comunidades online de sites de redes sociais, a fim de realizar estudos sociais sobre questões de saúde. Com base em uma abordagem prática foi definido um processo para realizar esses estudos. Este processo contou com ferramentas computacionais adaptados para fornecer apoio em tarefas específicas, tais como recuperação de conteúdo, seleção e análise. Duas ferramentas que se destacam são apresentadas por causa de sua utilidade e a complexidade do processo em que a sua construção se baseou. Para o benefício da análise de comunidades online, o Mapa de Associação de Comunidades é um processo desenvolvido para apoiar especialistas em compreender os interesses dos usuários com base em suas associações dentro de suas comunidades. A outra ferramenta visa auxiliar analistas a selecionar discussões de fóruns online a serem analisados manualmente com técnicas de pesquisa qualitativa, por exemplo, análise de conteúdo e do discurso. Esta ferramenta, TorchSR, foi criada baseada em aprendizado de máquina não supervisionado, usando agrupamento hierárquico, para dar suporte na resolução do problema de seleção de conteúdo. Um estudo de caso exploratório mostra que esta ferramenta ajuda na resolução do problema. O processo proposto foi utilizado em dois estudos sobre questões relevantes de saúde (hepatite C e o abuso de drogas), que resultou em descobertas relevantes sobre saúde pública. Em conclusão, este trabalho apresenta a aplicação prática de ciência social computacional no campo da saúde, através do desenvolvimento de um processo e ferramentas utilizadas para apoiar os analistas e melhorar a sua aplicação. / [en] This research thesis is aiming to exploit valuable social media, especially those available in online communities of social network sites, in order to perform social studies about healthcare issues. Based on a practical approach, a process was defined to conduct such studies. This process relied on tailored computational tools to provide support for specific tasks such as contente retrieval, selection, and analysis. Two tools that stand out are presented because of their utility and the complexity of the process in which their development was based on. The first tool, for the benefit of online community analysis, is the Community Association Map, a process developed to support experts in understanding users’ interests based on their associations within their communities. Our second tool (TorchSR) aims to aid analysts in the selection of discussions from online forums to be manually analyzed by (qualitative) research techniques (e.g. content and discourse analysis). This task, which was defined as solving the content selection problem, was tackled with a tool based on unsupervised machine learning techniques, such as hierarchical clustering. An exploratory study case shows that TorchSR helps analysts in dealing with the problem. The proposed process was employed in two studies about relevant healthcare issues (i.e. hepatitis C and drug abuse) which resulted in interesting findings in the field of public health. In conclusion, this thesis presents a practical application of computational social science to the field of health, through development of a process and tools used to support analysts and improve its application.