Hierarchical structure and diagenesis of Sauropod long bones using advanced characterization techniques

Sauropod dinosaurs are one of the most fascinating animals, mainly because of the extreme size that they could reach. This gigantism led to the hypothesis that sauropod long bones adopted an optimized hierarchical structure to resist the high loads caused by their heavy weight in excess of 100 tons. The present work aims at evaluating this hypothesis with the following objectives: (1) Investigate modifications linked to diagenesis at different hierarchical levels of the sauropod fossil using new techniques and methods. (2) Analyze the structure of bone samples in terms of crystallographic orientation, crystal size as well as the general arrangement of fibrolamellar (FBL) and secondary bone observed in sauropod cortical bone. In the first part, diagenetic effects appearing during fossilization process were studied with different techniques. Synchrotron-X-Ray fluorescence was used for the first time on fossil material, allowing investigations of considerably higher resolution compared to conventional techniques. Furthermore, a combination of X-Ray diffraction and energy dispersive X-Ray analysis during scanning electron microscopy (SEM-EDX) as well as transmission electron microscopy (TEM-EDX) was used to evaluate diagenetic changes at different hierarchical levels of fossil bones. Infillings of secondary minerals were mostly detected in natural pores of bones (vascular canals and osteocyte lacunae). The combination of the different analysis techniques applied in this study revealed that although seemingly unaffected at the histological level, the sauropod fossils endured strong diagenetic changes. Additionally, pronounced differences concerning the diagenesis and secondary mineral infillings between bone samples of a same postmortem burial environment could be observed. In the second part, crystallographic investigations were carried out in an ontogeny series of Apatosaurus sp.. The basic crystallographic orientation of sauropod bones as measured by X-Ray diffraction is shown to be a texture, where the c-axes of the crystals are aligned parallel to the longitudinal axis of the bone. This texture, which was also accounted for in bones of recent animals, indicated that these long bones are mainly loaded in compression. The remodeling and consecutive lamellar bone reconstruction does not seem to be affected by the general crystallographic orientation. A pronounced texture found in sauropod and elephant bone seems to be linked to the comparatively large weight of these animals. Crystal size in long bones of Apatosaurus sp. was additionally investigated, but the observations are made difficult by postmortem alterations that these bones are submitted to, as crystal size generally increases in fossil bones. The results obtained in this study failed to show an increase of the crystal size and aspect ratio along with the growth of the sauropod. Based on these findings, the nanostructure of FBL bone and secondary lamellar bone were further analyzed using TEM methods. The observed crystallographic organization is different between the two bone tissues: Even if the crystals of primary bone seem to be randomly oriented the texture is present in the first stage of development along the sauropod cortical bone, as shown with diffraction experiments. The secondary lamellar bone observed in the sauropod bone, on the other hand, display different crystallographic orientations in a rotate plywood model, similar to observations of recent bones. The results obtained in the present study do not confirm the initial hypothesis that sauropod bone exhibits a superior high-strength structure compared to bones of recent large mammals

On the discrete harmonic wavelet transform

The discrete harmonic wavelet transform has been reviewed and applied towards given functions. The absolute error of reconstruction of the functions has been computed

A Laplace Transform Finite Difference Scheme for the Fisher-KPP Equation.

© The Author(s) 2021. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)This paper proposes a numerical approach to the solution of the Fisher-KPP reaction-diffusion equation in which the space variable is developed using a purely finite difference scheme and the time development is obtained using a hybrid Laplace Transform Finite Difference Method (LTFDM). The travelling wave solutions usually associated with the Fisher-KPP equation are, in general, not deemed suitable for treatment using Fourier or Laplace transform numerical methods. However, we were able to obtain accurate results when some degree of time discretisation is inbuilt into the process. While this means that the advantage of using the Laplace transform to obtain solutions for any time t is not fully exploited, the method does allow for considerably larger time steps than is otherwise possible for finite-difference methods.Peer reviewedFinal Published versio

Mathematical Model for Cartilage Tissue-Growth Using a Quadriphasic Mixture and Finite Element Analysis

The goal of this thesis is to build a clear model of biological tissues growth, especially cartilage. But because tissues are complicated, simplifications and assumptions have to be made. In experiments, engineered tissues are often using hydrogels, because of their ability to mimic the real system. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a quadriphasic formulation (solid, fluid, unbound matrix molecules, enzymes) based on a single chondrocyte releasing extracellular matrix molecules and enzymes within a degrading hydrogel. This model describes the key players of the biological system within the hydrogel encompassing different length scales. Different mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix molecules transport. Numerical results show the competition between the diffusion of the matrix molecules and the the diffusion of the enzymes degrading the scaffold

Modeling the mechanics of amorphous solids at different length and time scales

We review the recent literature on the simulation of the structure and deformation of amorphous glasses, including oxide and metallic glasses. We consider simulations at different length and time scales. At the nanometer scale, we review studies based on atomistic simulations, with a particular emphasis on the role of the potential energy landscape and of the temperature. At the micrometer scale, we present the different mesoscopic models of amorphous plasticity and show the relation between shear banding and the type of disorder and correlations (e.g. elastic) included in the models. At the macroscopic range, we review the different constitutive laws used in finite element simulations. We end the review by a critical discussion on the opportunities and challenges offered by multiscale modeling and transfer of information between scales to study amorphous plasticity.Comment: 58 pages, 14 figure

Learning How To Recognize Faces In Heterogeneous Environments

Face recognition is a mature field in biometrics in which several systems have been proposed over the last three decades. Such systems are extremely reliable under controlled recording conditions and it has been deployed in the field in critical tasks, such as in border control and in less critical ones, such as to unlock mobile phones. However, the lack of cooperation from the subject and variations on the pose, occlusion and illumination are still open problems and significantly affect error rates. Another challenge that arose recently in face recognition research is the ability of matching faces from different image domains. Use cases encompass the matching between Visual Light images (VIS) with Near infra-red images (NIR), Visual Light images (VIS) with Thermograms or Depth maps. This match can occur even in situations where no real face exists, such as matching using sketches. This task is so called Heterogeneous Face Recognition. The key difficulty in the comparison of faces in heterogeneous conditions is that images from the same subject may differ in appearance due to changes in image domain. In this thesis we address this problem of Heterogeneous Face Recognition (HFR). Our contributions are four-fold. First, we analyze the applicability of crafted features used in face recognition in the HFR task. Second, still working with crafted features, we propose that the variability between two image domains can be suppressed with a linear shift in the Gaussian Mixture Model (GMM) mean subspace. That encompasses inter-session variability (ISV) modeling. Third, we propose that high level features of Deep Convolutional Neural Networks trained on Visual Light images are potentially domain independent and can be used to encode faces sensed in different image domains. Fourth, large-scale experiments are conducted on several HFR databases, covering various image domains showing competitive performances. Moreover, the implementation of all the proposed techniques are integrated into a collaborative open source software library called Bob that enforces fair evaluations and encourages reproducible research

Análise de multidões usando coerência de vizinhança local

Large numbers of crowd analysis methods using computer vision have been developed in the past years. This dissertation presents an approach to explore characteristics inherent to human crowds – proxemics, and neighborhood relationship – with the purpose of extracting crowd features and using them for crowd flow estimation and anomaly detection and localization. Given the optical flow produced by any method, the proposed approach compares the similarity of each flow vector and its neighborhood using the Mahalanobis distance, which can be obtained in an efficient manner using integral images. This similarity value is then used either to filter the original optical flow or to extract features that describe the crowd behavior in different resolutions, depending on the radius of the personal space selected in the analysis. To show that the extracted features are indeed relevant, we tested several classifiers in the context of abnormality detection. More precisely, we used Recurrent Neural Networks, Dense Neural Networks, Support Vector Machines, Random Forest and Extremely Random Trees. The two developed approaches (crowd flow estimation and abnormality detection) were tested on publicly available datasets involving human crowded scenarios and compared with state-of-the-art methods.Métodos para análise de ambientes de multidões são amplamente desenvolvidos na área de visão computacional. Esta tese apresenta uma abordagem para explorar características inerentes às multidões humanas - comunicação proxêmica e relações de vizinhança - para extrair características de multidões e usá-las para estimativa de fluxo de multidões e detecção e localização de anomalias. Dado o fluxo óptico produzido por qualquer método, a abordagem proposta compara a similaridade de cada vetor de fluxo e sua vizinhança usando a distância de Mahalanobis, que pode ser obtida de maneira eficiente usando imagens integrais. Esse valor de similaridade é então utilizado para filtrar o fluxo óptico original ou para extrair informações que descrevem o comportamento da multidão em diferentes resoluções, dependendo do raio do espaço pessoal selecionado na análise. Para mostrar que as características são realmente relevantes, testamos vários classificadores no contexto da detecção de anormalidades. Mais precisamente, usamos redes neurais recorrentes, redes neurais densas, máquinas de vetores de suporte, floresta aleatória e árvores extremamente aleatórias. As duas abordagens desenvolvidas (estimativa do fluxo de multidões e detecção de anormalidades) foram testadas em conjuntos de dados públicos, envolvendo cenários de multidões humanas e comparados com métodos estado-da-arte