Estudos relacionados à microestrutura óssea de elementos fósseis surgiram no século XVIII, porém começaram a desenvolver-se mais profundamente somente nas últimas décadas. Hoje, a Paleohistologia é uma das áreas mais promissoras dentro da Paleontologia, pois nos possibilita acessar uma série de características do espécime fóssil que complementam nosso conhecimento sobre o animal. Assim como outros clados, os Dicynodontia vêm sendo estudados por esse viés há muito tempo, e hoje conhecemos os padrões ósseos e de crescimento de um grande número de espécies. A presente dissertação traz a descrição ósteo-histológica de alguns elementos fósseis de Dinodontosaurus turpior, uma espécie de dicinodonte de grande porte do Mesotriássico, encontrada em afloramentos da Formação Santa Maria. Os ossos analisados apresentam majoritariamente uma matriz do tipo fibrolamelar, com alguns subtipos da matriz em dois fragmentos, ausência de linhas de crescimento nos espécimes juvenis e presença destas em fragmentos de espécimes adultos, possibilidade de EFS em um fragmento de adulto, reconstrução secundária surgindo apenas em estágios mais avançados e córtex razoavelmente espesso. Tais características não divergem do padrão já descrito para o grupo como um todo, cujas interpretações para a biologia do animal incluem um metabolismo mais acelerado e uma rápida osteogênese, quando comparada com a de terápsidos mais basais. / Studies related to bone microstructure of fossil elements started about the 18th century, however, they began to significantly grow only in the past few decades. Today, paleohistology is one of the most promising areas inside paleontology, because permits to access several characteristics of the fossil specimen which complement our knowledge about the animal. As in other clades, Dicynodontia has been studied in this subject for long time, and now we know about bone growth and microstructure patterns in a variety of species. The present study shows a osteohistological description of some fossil elements of Dinodontosaurus turpior, a medium-to-large size dicynodont species from Middle Triassic of Rio Grande do Sul, Brazil, founded in outcrops of the Santa Maria Formation. The bones analyzed present a fibrolamelar type of bone tissue as major matrix, with some subtypes appearing in a couple of fragments. Growth lines are absent in all juvenile fragments, but appears in the adult ones. One of the adult fragments seems to have an EFS. Also, it was observed secondary reconstruction in adult sample and a thick cortex in all slides that RBT can be calculated. All these features were already been observed in the Dicynodontia clade, whose biological interpretations include an accelerated metabolism and rapid osteogenesis, when compared with basal therapsids.

Urbanisation has had a profound impact in sub-Saharan Africa and can be attributed to the complex human-environment interaction. Knowledge on long-term urbanisation processes in sub-Saharan Africa is lacking. Besides, understanding the urbanisation process in sub-Saharan Africa necessitates to go beyond the global scale to the local scale to unravel the idiosyncrasies in the growth of each city. The perennial lack of data (or data meeting required specifications) is a bottleneck to such studies. Very often, the nature of the available data might present challenges to existing classification algorithms. Moreover, availability of adequate and well-curated reference datasets presents a bottleneck to the generation of accurate land-cover maps. The main aim of this research was to conduct a long-term analysis of urbanisation patterns in Central Africa by developing methodologies based on deep learning, a class of Artificial Intelligence. To this end, we address the main research question: “How can we understand long-term urbanisation patterns by applying deep learning on digital aerial images in Central Africa?” We used case-studies from three cities in Central Africa namely Goma and Bukavu in The Democratic Republic of Congo and Bujumbura in Burundi, to aid in understanding the urbanisation process in sub-Saharan Africa. We generate baseline data from an archive of historical panchromatic orthomosaics that allow for the capturing of the urbanisation before the onset of rapid urbanisation that was characteristic of Countries in sub-Saharan Africa after gaining independence from colonialism.The main contribution of this thesis is the 60-year long-term analysis of urbanisation patterns for three cities in Central Africa using a unique dataset of historical orthomosaics. The growth patterns and driving forces are analysed using spatial and qualitative data. The results show that social triggers such as wars drive urban expansion. On the contrary, biophysical drivers such as geohazards did not limit urban growth only slowing down settlements for a short time span of the analysis. As urbanisation levels increased, constraining effects of natural environment such as relief on urban expansion weakened. In addition, we make some methodological developments based on deep learning to generate land-cover from historical panchromatic orthomosaics (i.e. 1m spatial resolution) and sub-metric RGB aerial images (i.e. 0.175m). Results show that deep learning methods generally have high accuracy metrics, compared to standard machine learning baselines, but at the cost of high demand for a large and accurate, labelled dataset and computational resources. In addition, accurate and sufficient labelled data are still needed to guarantee accurate land-cover maps from deep learning algorithms and novel strategies need to be pursued in approaches investigating insufficient reference data. / L’urbanisation a eu un impact profond sur l’Afrique subsaharienne et peut être attribuée à l’interaction complexe entre l’homme et l’environnement. Les connaissances sur les processus d’urbanisation sur des temps longs font défaut. En outre, pour comprendre le processus d'urbanisation en Afrique subsaharienne, il faut aller au-delà de l'échelle mondiale et s'intéresser à l'échelle locale pour comprendre les particularités de la croissance de chaque ville. L'éternel manque de données (ou de données répondant aux spécifications requises) constitue des limitations de telles études. Très souvent, la nature des données disponibles peut présenter des défis pour les algorithmes de classification existants. De plus, la disponibilité d'ensembles de données de référence adéquats et fiables constitue un goulot d'étranglement pour la création de cartes précises de l'occupation des sols.L'objectif principal de cette recherche était de mener une analyse sur des temps longs des différentes modes d'urbanisation en Afrique centrale en développant des méthodologies basées sur le deep learning, une forme d'intelligence artificielle. A cette fin, nous répondons à la question de recherche suivante :"Comment pouvons-nous comprendre les modes d'urbanisation sur des temps longs en appliquant des approches de deep learning sur des images aériennes numériques en Afrique centrale ?". Nous avons étudié trois villes d'Afrique centrale, à savoir Goma et Bukavu en République démocratique du Congo et Bujumbura au Burundi, de manière à comprendre le processus d'urbanisation en Afrique subsaharienne. Nous pouvons générer des données de base à partir de mosaïques d'orthophotographies aériennes panchromatiques historiques qui permettent de saisir l'urbanisation avant le début de l'urbanisation rapide ayant caractérisé les pays d'Afrique subsaharienne depuis leur indépendance.La principale contribution de cette thèse est l'analyse, sur 60 ans, des modes d'urbanisation pour trois villes d'Afrique centrale en utilisant un ensemble unique d'orthomosaïques historiques. Les modes et les facteurs de croissance y sont analysés en utilisant des données spatiales et qualitatives. Les résultats montrent que les déclencheurs sociaux tels que les guerres étaient positivement corrélé à l'expansion urbaine. Au contraire, les facteurs biophysiques tels que les risques associés aux catastrophes naturelles n'ont pas empêché la croissance urbaine mais ont seulement ralenti les nouvelles implantations pendant une courte période de l'analyse. Par ailleurs, à mesure que les niveaux d'urbanisation augmentent, les effets contraignants de l'environnement naturel tels que le relief sur l'expansion urbaine s'affaiblissent.De plus, certaines avancées méthodologiques ont été accomplies en explorant et en développant une méthodologie basée sur le deep learning pour générer une carte de la couverture du sol à partir d’orthomosaïques panchromatiques historiques (1m) et d'images aériennes RVB sub-métriques (0.175m). Les résultats montrent que les méthodes de deep learning présentent généralement des indicateurs de précision élevés par rapport aux méthodes standard basée sur machine learning, mais au prix d'une grande demande en matière de données étiquetées et de ressources informatiques. En outre, des données étiquetées précises et en quantité suffisante sont toujours nécessaires pour garantir l'exactitude des cartes de l’occupation du sol établies par les algorithmes de deep learning, et de nouvelles stratégies doivent être mises en œuvre dans le cas de travaux ne disposant que de données de référence insuffisantes / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

While it is now widely accepted that new firms growth is essential for the foundation of economic dynamism, knowledge about this early growth is still scattered. Indeed, very little is known about how new firms grow and develop over time. What types of distinct growth patterns do those firms exhibit? How do these growth patterns and corresponding firms differ from each others in terms of development and strategic choices? To better understand the process of new firm growth, recent entrepreneurship research stresses that there is a strong need for a new conceptual scheme and new longitudinal research methods. This is actually one of the main entrepreneurship research challenges. In this context, our aim is to provide new insights regarding the process of new firm growth. In this research, we develop and test an original methodology allowing the empirical taxonomy of early growth trajectories across multiple sectors, integrating both the multidimensional and dynamic aspects of growth. Our approach applies principal component and cluster analysis to a large sample of firms, using financial and demographic data collected over time to identify in a systematic way distinct growth stages. We use then sequence analysis and a Markov chain approach to extract and compare the trajectories of individual firms over time. This allows the identification of a limited number of typical growth trajectories, which are adopted by the majority of firms in our sample. Finally, internal replication is performed to validate the growth trajectories identified and bivariate analysis is used to examine the link between the identified growth trajectories and the demographic characteristics of the corresponding firms. We have applied our methodology to a sample of 741 Belgian firms created between 1992 and 2002 and which have grown above micro-firm size. Our approach allowed identifying four distinct growth stages and seven typical growth trajectories, which remain valid for the six first years of the majority of the firms in our sample. This taxonomy of early growth trajectories is consistent with individual patterns already identified in the literature and appears not to be sector-dependent. The major contribution of this doctoral thesis is that, based on empirical evidence, early growth appears to be neither a continuous (or life cycle based) nor idiosyncratic (or completely random) process. It can be adequately described through a limited number of typical growth trajectories, valid across sectors. Thus, our research brings insight regarding how new firm evolve over time and therefore contributes to our understanding and appreciation of the heterogeneity of the growth trajectory phenomenon. Next, our research provides also an original methodological approach allowing the systematic analysis of growth trajectories, which deals with key limitations identified in the literature regarding the need for a multidimensional and dynamic study of growth across multiple sectors. Our findings indicate that this novel systematic approach is useful for taxonomy development and therefore contributes to reduce the gap between the complexity of new firm growth process and the standard approaches often mobilised to deal with it. Finally, while our findings provide empirical and methodological support in early development of new firms study, they also provide many implications to entrepreneurial research and practices. Further researches are needed to improve our understanding of the dynamic growth process of new ventures. It should explore which endogenous and exogenous factors might explain why a majority of start-ups follow the seven identified typical growth trajectories. It could be also highly relevant to refine our taxonomy by examining the relationship between innovative and technological sources and growth trajectories, both in high and low technological industries. Finally, we should test the accuracy of the proposed taxonomy across countries as well as beyond the early stage of new firm development.

Artist Statement The organic patterns all around me are what intrigues and inspires my textile, glass, and painting compositions. I find beauty within the natural growth patterns of things both large and small. My work references the reverberated growth processes in living things from the macroscopic observation of a plant to the microscopic viewpoint of its cells. Like the beauty found within these organic configurations, my process begins with creating serendipitous marks with a reference to natural patterns. Then, I intuitively respond to what I see in front of me. As I work, I use repetitious lines and shapes and a vibrant, non-naturalistic color palette. My choices of colors are personally motivated, and the combinations and manipulations are intuitive. Pattern and color are both visual languages that affect individuals differently. While my use of both is in response to my own experiences, my works allow the viewer to respond and connect in their own way.

Myelodysplastic syndromes (MDS) are regarded as clonal disorders of haematopoietic stem cells (HSC). Recent evidence demonstrates that stromal microenvironment, in addition to HSC defects, plays a particular role via its direct contact with haematopoietic precursor cells (HPC). This thesis aims at evaluating the putative growth deficiencies of mesenchymal stromal cells (MSC) from MDS individuals compared with normal controls, exploring their adhesion profile, assessing the adhesion process-involved molecular substrates, and establishing correlations with their growth patterns and HPC dysfunctions. Functional assays revealed that MSC from MDS are intrinsically pathological, show a continuous decline of proliferation over a 14-day culture and a reduced clonogenic capacity in the absence of signals from HPC. MSC growth defects significantly correlate with decreased CD44 and CD49e expression. Moreover, stroma-dependent adhesion mechanisms control HPC clonogenic potential and CD49e might be one of the molecules involved in this process. Qualitative and quantitative abnormalities of focal adhesion (FA) proteins paxillin and pFAK [Y397] and of two regulatory proteins, HSP90αβ and p130CAS were identified via immunofluorescence analysis. Paxillin, pFAK [Y397] and HSP90αβ increased expression, besides its stronger nuclear colocalization in MSC from RAEB correlates with a consistent proliferative advantage and has a negative impact on HPC clonogenic capacity. These results open interesting opportunities, e.g. HPC-to-MSC interactions involve FA proteins signalling, and, as FAK is an HSP90αβ-client protein, it may enhance the utility of HSP90αβ inhibitors as adjuvant therapy in MDS

Les syndromes myélodysplasiques (SMD) sont considérés comme des maladies clonales des cellules souches hématopoïétiques (CSH). Le microenvironnement joue un rôle important par ses contacts direct avec les cellules progénitrices hématopoïétiques (CPH). Notre objectif était d'évaluer les défauts de croissance des cellules stromales mésenchymateuses (CSM) dans les MDS, d’explorer les molécules d’adhérence impliquées, et d'effectuer des corrélations avec leurs dysfonctionnements de croissance et les anomalies des CPH. Les CSM de MDS sont intrinsèquement pathologiques, montrant une baisse continue de la prolifération pendant 14 jours de culture et une capacité clonogénique réduite. Ces anomalies sont corrélés à une diminution des molécules d'adhérence CD44 et CD49e. Par ailleurs, le potentiel clonogénique des CPH est contrôlé par des mécanismes d'adhérence dépendant du stroma, CD49e pouvant être une des molécules impliquées. L’analyse en immunofluorescence des protéines d'adhérence focale (FA), paxilline et pFAK [Y397], et des deux protéines régulatrices, HSP90αβ et p130CAS permet l'identification d’anomalies qualitatives et quantitatives. Une expression accrue de paxilline, pFAK et HSP90αβ et leur forte co-localisation nucléaire dans les CSM d'anémie réfractaire avec excès de blastes (AREB) sont corrélées avec un avantage prolifératif et un impact négatif sur la capacité clonogénique de CPH. Ces résultats ouvrent des possibilités intéressantes : la signalisation via les protéines FA pourrait être impliquée dans les interactions HPC-MSC ; par ailleurs, FAK étant une protéine cliente d’HSP90, les inhibiteurs d’HSP90 sont une potentielle thérapie adjuvante dans les myélodysplasies / Myelodysplastic syndromes (MDS) are regarded as clonal disorders of haematopoietic stem cells (HSC). Recent evidence demonstrates that stromal microenvironment, in addition to HSC defects, plays a particular role via its direct contact with haematopoietic precursor cells (HPC). This thesis aims at evaluating the putative growth deficiencies of mesenchymal stromal cells (MSC) from MDS individuals compared with normal controls, exploring their adhesion profile, assessing the adhesion process-involved molecular substrates, and establishing correlations with their growth patterns and HPC dysfunctions. Functional assays revealed that MSC from MDS are intrinsically pathological, show a continuous decline of proliferation over a 14-day culture and a reduced clonogenic capacity in the absence of signals from HPC. MSC growth defects significantly correlate with decreased CD44 and CD49e expression. Moreover, stroma-dependent adhesion mechanisms control HPC clonogenic potential and CD49e might be one of the molecules involved in this process. Qualitative and quantitative abnormalities of focal adhesion (FA) proteins paxillin and pFAK [Y397] and of two regulatory proteins, HSP90αβ and p130CAS were identified via immunofluorescence analysis. Paxillin, pFAK [Y397] and HSP90αβ increased expression, besides its stronger nuclear colocalization in MSC from RAEB correlates with a consistent proliferative advantage and has a negative impact on HPC clonogenic capacity. These results open interesting opportunities, e.g. HPC-to-MSC interactions involve FA proteins signalling, and, as FAK is an HSP90αβ-client protein, it may enhance the utility of HSP90αβ inhibitors as adjuvant therapy in MDS

Wildland fire behavior research in the last 100 years has largely focused on understanding the physical phenomena behind fire spread and on developing models that can predict fire behavior. Research advances in the areas of live-fuel combustion and combustion modeling have highlighted several weaknesses in the current approach to fire research. Some of those areas include poor characterization of solid fuels in combustion modeling, a lack of understanding of the dominant heat transfer mechanisms in fire spread, a lack of understanding regarding the theory of live-fuel combustion, and a lack of understanding regarding the behavior of flames near slopes. In this work, the physical properties, chemical properties and burning behavior of the foliage from ten live shrub and conifer fuels were measured throughout a one-year period. Burn experiments were performed using different heating modes, namely convection-only, radiation-only and combined convection and radiation. Models to predict the physical properties and burning behavior were developed and reported. The flame behavior and associated heat flux from fires near slopes were also measured. Several important conclusions are evident from analysis of the data, namely (1) seasonal variability of the measured physical properties was found to be adequately explained without the use of a seasonal parameter. (2) ignition and burning behavior cannot be described using single-parameter correlations similar to those used for dead fuels, (3) moisture content, sample mass, apparent density (broad-leaf species), surface area (broad-leaf), sample width (needle species) and stem diameter (needle) were identified as the most important predictors of fire behavior in live fuels, (4) volatiles content, ether extractives, and ash content were not significant predictors of fire behavior under the conditions studied, (5) broadleaf species experienced a significant increase in burning rate when convection and radiation were used together compared to convection alone while needle species showed no significant difference between convection-only and convection combined with radiation, (6) there is no practical difference between heating modes from the perspective of the solid—it is only the amount of energy absorbed and the resulting solid temperature that matter, and (7) a radiant flux of 50 kW m-2 alone was not sufficient to ignite the fuel sample under experimental conditions used in this research, (8) the average flame tilt angle at which the behavior of a flame near a slope deviated from the behavior of a flame on flat ground was between 20° and 40°, depending on the criteria used, and (9) the traditional view of safe separation distance for a safety zone as the distance from the flame base is inadequate for fires near slopes.

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Les plantes présentent une incroyable diversité de tailles, formes et couleurs, étroitement liée à certaines de leurs fonctions biologiques telles que la photosynthèse, la reproduction, etc. De ce fait, la façon dont ces organismes multicellulaires acquièrent des formes complexes est une question clé en biologie du développement. La morphologie des organes végétaux résulte en effet de la modulation, à l’échelle cellulaire, de patrons d’expression génétique, de croissance et de différenciation. Bien que la morphogénèse ait été largement étudiée d’un point de vue moléculaire, nous ne savons toujours pas comment ces réseaux génétiques sont traduits en formes biologiques. Le but de ce projet de recherche est donc d’étudier le développement des organes latéraux (feuilles juvéniles, feuilles caulinaires et organes floraux, id sépales, pétales et anthères) chez l’espèce modèle Arabidopsis thaliana. Afin d’approcher la question du rôle des interactions complexes entre cellules et organes lors du développement, nous nous intéressons à la variabilité entre les organes, mais aussi à la variabilité cellulaire intrinsèque de chaque organe. Nous avons donc testé (1) si la diversité de formes observées chez les organes latéraux résulte de modulations d’un programme développemental commun; (2) si la croissance et le développement des organes latéraux est un phénomène stochastique ou dépend de mécanismes sous-jacents spécifiques. Pour ce faire, nous utilisons une approche multidisciplinaire basée sur la génétique, la microscopie confocale et l’analyse d’images 3D pour extraire les patrons de croissance inhérents aux différents organes. Les résultats de la première étude (Chapitre 2) montrent que la forme des organes dépend de l’équilibre entre croissance et différentiation, dont la régulation précise permet l'acquisition de fonctions hautement spécialisées. La feuille caulinaire, par exemple, présente un retard de différenciation qui permet une activité morphogénétique prolongée et une redistribution de la croissance. À travers la suppression transitoire de la croissance lors des premiers stades de développement, la trajectoire développementale de la feuille caulinaire permet sa double fonction, à la fois protectrice et photosynthétique.\par La deuxième étude (Chapitre 3), quant-à-elle, s’intéresse aux comportements des cellules individuelles, dont la croissance, bien que contrôlée par des informations positionnelles, est souvent hétérogène. Cette variabilité résulte de la différenciation de cellules spécialisés, les stomates, qui suivent un programme de développement spécifique. Le comportement autonome de ces cellules, asynchrone, est la principale source de variabilité dans des tissus dont la croissance est autrement homogènes. Dans l’ensemble, cette thèse a permis de mettre en lumière l’importance de la temporalité lors du développement des organes végétaux. Que ce soit à l’échelle de l’organe, du tissu ou de la cellule, la modulation et la synchronisation de la croissance et de la différentiation sont nécessaires à l’acquisition des formes stéréotypiques des organes et à leur complexité fonctionnelle. / Plants display an incredible diversity of sizes, shapes, and colors, closely linked to some of their biological functions, such as photosynthesis, reproduction, etc. How these multicellular organisms acquire complex shapes is, therefore, a key question in developmental biology. The morphology of plant organs results from cell-level modulation of patterns of gene expression, growth, and differentiation. Although morphogenesis has been extensively studied from a molecular point of view, how genetic networks are translated into biological forms is still unclear. Thus, the aim of this research project is to study the development of lateral organs (rosette leaves, cauline leaves, and floral organs, i.e. sepals, petals, and anthers) in the model species Arabidopsis thaliana. To address the question of the role of complex cell-organ interactions during development, we are interested not only in variability between organs but also in the intrinsic cellular variability of each organ. We, therefore, tested (1) whether the diversity of shapes observed in lateral organs results from modulations of a common developmental program; (2) whether the growth and development of lateral organs is a stochastic phenomenon or depends on specific underlying mechanisms. To this end, we are using a multidisciplinary approach based on genetics, confocal microscopy, and 3D image analysis to extract the growth patterns inherent in the different organs. The results of the first study (Chapter 2) show that organ shape depends on the balance between growth and differentiation, which fine regulation enables the acquisition of highly specialized functions. The cauline leaf, for example, shows a delay in differentiation that allows for prolonged morphogenetic activity and growth redistribution. Through the transient growth suppression at early stages, the cauline leaf developmental trajectory allows for its dual function, from protection to photosynthesis. The second study (Chapter 3) focuses on the behavior of individual cells, whose growth, although controlled by positional information, is often heterogeneous. This variability results from the differentiation of specialized cells, the stomata, which follow a specific developmental program. The autonomous, asynchronous behavior of these cells is the main source of variability in tissues whose growth is otherwise homogeneous. Overall, this thesis has shed light on the importance of timing in plant organ development. Whether at the organ, tissue, or cell level, modulation and synchronization of growth and differentiation are necessary for the acquisition of stereotypic organ shapes and functional complexity.