Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

A test-bed for the Correlation Center of Digital Services

For an e-business to be successful, companies need to formulate a business strategy, have informative strategic alliances, develop an international system, build a proactive infrastructure, internationalize their model, capture the residual value, exploit the international telecommunications liberalization, homogenize the data structure and globalize human resources. To achieve their objective, businesses need a more integrated automation system to speed up the process of establishing and conducting Internet-based services. In this paper, a component-based prototyping approach is used in developing a generic model and framework for a correlation center that provides entrepreneurs with a tool to quickly build and automate e-commerce linkages, thus enabling companies to establish their businesses over the Internet using a proven methodology

Mathematical investigation of normal and abnormal wound healing dynamics:local and non-local model

The movement of cells during (normal and abnormal) wound healing is the result of biomechanical interactions that combine cell responses with growth factors as well as cell-cell and cell-matrix interactions (adhesion and remodelling). It is known that cells can communicate and interact locally and non-locally with other cells inside the tissues through mechanical forces that act locally and at a distance, as well as through long non-conventional cell protrusions. In this study, we consider a non-local partial differential equation model for the interactions between fibroblasts, macrophages and the extracellular matrix (ECM) via a growth factor (TGF-β) in the context of wound healing. For the non-local interactions, we consider two types of kernels (i.e., a Gaussian kernel and a cone-shaped kernel), two types of cell-ECM adhesion functions (i.e., adhesion only to higher-density ECM vs. adhesion to higher-/lower-density ECM) and two types of cell proliferation terms (i.e., with and without decay due to overcrowding). We investigate numerically the dynamics of this non-local model, as well as the dynamics of the localised versions of this model (i.e., those obtained when the cell perception radius decreases to 0). The results suggest the following: (i) local models explain normal wound healing and non-local models could also explain abnormal wound healing (although the results are parameter-dependent); (ii) the models can explain two types of wound healing, i.e., by primary intention, when the wound margins come together from the side, and by secondary intention when the wound heals from the bottom up.</p

Multi-compartment poroelastic models of perfused biological soft tissues: implementation in FEniCSx

Soft biological tissues demonstrate strong time-dependent and strain-rate mechanical behavior, arising from their intrinsic visco-elasticity and fluid-solid interactions (especially at sufficiently large time scales). The time-dependent mechanical properties of soft tissues influence their physiological functions and are linked to several pathological processes. Poro-elastic modeling represents a promising approach because it allows the integration of multiscale/multiphysics data to probe biologically relevant phenomena at a smaller scale and embeds the relevant mechanisms at the larger scale. The implementation of multi-phasic flow poro-elastic models however is a complex undertaking, requiring extensive knowledge. The open-source software FEniCSx Project provides a novel tool for the automated solution of partial differential equations by the finite element method. This paper aims to provide the required tools to model the mixed formulation of poro-elasticity, from the theory to the implementation, within FEniCSx. Several benchmark cases are studied. A column under confined compression conditions is compared to the Terzaghi analytical solution, using the L2-norm. An implementation of poro-hyper-elasticity is proposed. A bi-compartment column is compared to previously published results (Cast3m implementation). For all cases, accurate results are obtained in terms of a normalized Root Mean Square Error (RMSE). Furthermore, the FEniCSx computation is found three times faster than the legacy FEniCS one. The benefits of parallel computation are also highlighted.Comment: https://github.com/Th0masLavigne/Dolfinx_Porous_Media.gi

Cortex tissue relaxation and slow to medium load rates dependency can be captured by a two-phase flow poroelastic model

This paper investigates the complex time-dependent behavior of cortex tissue, under adiabatic condition, using a two-phase flow poroelastic model. Motivated by experiments and Biot's consolidation theory, we tackle time-dependent uniaxial loading, confined and unconfined, with various geometries and loading rates from 1 micrometer/sec to 100 micrometer/sec. The cortex tissue is modeled as the porous solid saturated by two immiscible fluids, with dynamic viscosities separated by four orders, resulting in two different characteristic times. These are respectively associated to interstitial fluid and glial cells. The partial differential equations system is discretised in space by the finite element method and in time by Euler-implicit scheme. The solution is computed using a monolithic scheme within the open-source computational framework FEniCS. The parameters calibration is based on Sobol sensitivity analysis, which divides them into two groups: the tissue specific group, whose parameters represent general properties, and sample specific group, whose parameters have greater variations. Our results show that the experimental curves can be reproduced without the need to resort to viscous solid effects, by adding an additional fluid phase. Through this process, we aim to present multiphase poromechanics as a promising way to a unified brain tissue modeling framework in a variety of settings

Non-operable glioblastoma: Proposition of patient-specific forecasting by image-informed poromechanical model

Work funding with a grant fromLuxembourg National Research Fund (FNR) grant number INTER/ANR/21/16399490 and from Réseau Santé des Arts et Métiers.We propose a novel image-informed glioblastoma mathematical model within a reactive multiphase poromechanical framework. Poromechanics offers to model in a coupled manner the interplay between tissue deformation and pressure-driven fluid flows, these phenomena existing simultaneously in cancer disease. The model also relies on two mechano-biological hypotheses responsible for the heterogeneity of the GBM: hypoxia signaling cascade and interaction between extra-cellular matrix and tumor cells. The model belongs to the category of patient-specific image-informed models as it is initialized, calibrated and evaluated by the means of patient imaging data. The model is calibrated with patient data after 6 cycles of concomitant radiotherapy chemotherapy and shows good agreement with treatment response 3 months after chemotherapy maintenance. Sensitivity of the solution to parameters and to boundary conditions is provided. As this work is only a first step of the inclusion of poromechanical framework in image-informed glioblastoma mathematical models, leads of improvement are provided in the conclusion. Statement of significance: In this study, we employ mechanics of reactive porous media to effectively model the dynamic progression of a glioblastoma. Traditionally, glioblastoma tumors are surgically removed a few weeks post-diagnosis. To address this, we focus on a non-operable clinical scenario which allows us to have sufficient time points for the calibration and subsequent validation of our mathematical model. It is paramount to underscore that the tumor’s evolution is significantly influenced by chemotherapy and radiotherapy. These therapeutic effects find incorporation within our mathematical framework. Notably, the approach we present is distinctive for two key reasons: Firstly, the mathematical model inherently captures the complex multiphase and hierarchical nature of brain tissue. Secondly, our constitutive laws factor in the ever-changing properties of cells and tissues, mirroring the local phenotypic alterations observed within the tumor. This work constitutes an initial stride towards systematically integrating multiphase poromechanics into patient-specific glioblastoma growth modeling. As we look ahead, we acknowledge areas for potential enhancement in pursuit of advancing this promising direction

Oncology and mechanics: landmark studies and promising clinical applications

Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena, allowed by favorable biological conditions, emerge via mechanical signaling at the cellular scale and via mechanical forces at the macroscale. Mechanical phenomena in cancer have been studied in-depth over the last decades, and their clinical applications are starting to be understood. If numerous models and experimental setups have been proposed, only a few have led to clinical applications. The objective of this contribution is to propose to review a large scope of mechanical findings which have consequences on the clinical management of cancer. This review is mainly addressed to doctoral candidates in mechanics and applied mathematics who are faced with the challenge of the mechanics-based modeling of cancer with the aim of clinical applications. We show that the collaboration of the biological and mechanical approaches has led to promising advances in terms of modeling, experimental design and therapeutic targets. Additionally, a specific focus is brought on imaging-informed mechanics-based models, which we believe can further the development of new therapeutic targets and the advent of personalized medicine. We study in detail several successful workflows on patient-specific targeted therapies based on mechanistic modeling

Contraintes psychosociales et organisationnelles : analyse qualitative auprès de 51 médecins hospitaliers

Introduction : les taux de burnout et de mortalité par suicide sont significativement plus élevés chez les médecins comparés à ceux observés dans la population générale. Peu d’études ont cherché à déterminer les facteurs professionnels pouvant être en cause dans l’altération de la santé psychique des médecins. L’objectif de cette étude est d’identifier, par une approche qualitative, les contraintes psychosociales et organisationnelles (CPO) perçues par les médecins hospitaliers.Matériel et méthodes : des entretiens semi-dirigés individuels et collectifs ont été conduits au sein d’un centre hospitalier du Sud de la France. Une analyse manuelle du contenu des entretiens a été réalisée puis complétée par une analyse syntaxique informatisée. Une comparaison du discours a été réalisée entre les sous-groupes de médecins répartis selon le genre, la spécialité et l’expérience professionnelle.Résultats : au total, 51 médecins ont participé à l’étude comportant 37 entretiens individuels et 3 discussions en groupe. Leur discours est globalement homogène et diverge peu entre les sous-groupes. La plupart des médecins rapportent être satisfaits de leur travail tout en estimant que ce dernier a un impact délétère sur leur santé. L’analyse manuelle et informatisée a permis d’identifier 5 thématiques de CPO perçues : 1. Des relations et une communication au travail satisfaisantes avec l’ensemble du personnel médical et paramédical mais détériorées avec l’administration 2. Un statut professionnel insatisfaisant 3. Une structure organisationnelle priorisant des objectifs financiers et limitant leur pouvoir décisionnel dans l’organisation des soins 4. Des horaires trop étendus, un rythme et une charge de travail excessifs 5. Des conditions matérielles insatisfaisantes, en particulier une dysfonction du matériel informatique, une déficience des interfaces logicielles et un emploi excessif des outils connectés.Conclusion : le travail en équipe apparait être une source de satisfaction des médecins hospitaliers. La communication avec l’administration et l’implication de ces derniers dans l’organisation des soins semblent à promouvoir. Un effort pourrait être porté sur l’adaptation des outils informatiques à leur activité et sur la limitation de l’utilisation des outils connectés

Mechano-biology of tumor growth with the aim of clinical : applications, a reactive multiphase poromechanical approach

The basis of this work is the reactive multiphase poromechanical model developed since 2013 by Sciumè et al. A porous system is modelled as a porous solid saturated by two or three fluid phases, interstitial fluid, healthy cells and tumor cells respectively. These fluids have their own constitutive relationships, designed by the same authors. The porous system mimic a living tissue by the addition of a reactive species, denoted nutrient, but solely considered as oxygen. Indeed, the acute deprivation of oxygen - also known as hypoxia - due to the tumor cells proliferation will cause the necrosis of the tumor phase, changing its properties. This model were enhanced in 2014 by the same authors with a deformable porous solid, then allowing for modeling the interplay between extra-cellular matrix (ECM) and tumor cells. The model outputs were qualitatively compared to in vitro experiments of Chignola et al. and histological cuts of skin cancer of Chung et al., showing promising results. Additionally, by replacing the tumor phase by a non-proliferative cell phase under hypoxic condition, the model could qualitatively reproduced the mechanism of diabetic foot. Thus, this model proved its potential in cancer modeling and translation in other tissue pathologies.The motivation of this thesis was the translation of the model of Sciumè et al. into a clinical context.We begun with a wide state of the art of collaboration between mechanics and clinical oncology. The research were driven by two questions: which mechanical phenomena are of interest? How to translate mechanical-based modeling into clinical applications? Regarding the first question, we selected the mechanically-inhibited tumor growth and, as a consequence of stroma mechano-biology, the mechanically-induced phenotype switch. Regarding the second, we chose the image-informed modeling framework, firstly designed in 2002 by Swanson et al., enhanced by Yankeelov et al. since 2013 and thereafter intensively used. During the first year of the thesis, we quantitatively validated the model against the in vitro experiment of Alessandri et al. in, termed as cellular capsule technology. With these first results in our hands, we were honored to start a collaboration with the Toulouse Neuro-imaging center and M.D. Lubrano, neurosurgeon. The aimed clinical application would be the modeling of a non-operable glioblastoma common subtype, the isocitrate dehydrogenase wild-type. At this stage, the SRAS-Cov2 pandemic started to impact the progress of our work. Imaging staff were transferred to pandemic-related tasks, non-essential clinical collaboration were shut down. During this period, our first move were to build a model of healthy brain tissue, using literature and ex-vivo experiments to validate it. To build a code of image-informed modeling, we used public atlases. M.D. Lubrano and his collaborators managed to provide us a patient imaging dataset with two time points, the first at diagnosis, the second after 6 weeks of concomitant radio-chemotherapy. This allowed for testing our hypotheses, now adapted to brain tissue, on hypoxia and cell-ECM interaction, and proposed a calibration of our model. This work was only a first step of the inclusion of poromechanics in patient-specific brain cancer modeling. We hope this inspiring framework will lead to new understanding i n the physical description of cancer.Ce travail est basé sur le modèle poromécanique multiphasique développé par Sciumè et al. depuis 2013. Un système poreux est modélisé par un solide poreux saturé par deux ou trois phases fluides, le fluide interstitiel, les cellules saines et les cellules tumorales respectivement. Ces fluides ont leur propres lois constitutives développées par les mêmes auteurs. Ce système poreux reproduit un tissu vivant par l’addition d’espèce chimique réactive, nommées nutriments, mais seul l’oxygène est explicitement considéré. En effet, un manque aigu d’oxygène – ou hypoxie – dû à la prolifération des cellules tumorales provoque leur nécrose et change les propriétés de ces cellules. Ce modèle fut amélioré en 2014 par les mêmes auteurs avec l’addition d’un solide poreux déformable, permettant ainsi la modélisation des interactions entre la matrice extra-cellulaire et les cellules tumorales. Le modèle fut évalué qualitativement avec les expériences in vitro et des coupes histologiques, montrant des résultats prometteurs. De plus, en changeant la phase tumorale par une phase non-proliférative dans des conditions d’hypoxie, ce modèle put reproduire qualitativement les mécanismes du pied diabétique. Ainsi, ce modèle a prouvé son potentiel dans la modélisation du cancer et sa transportabilité vers d’autres pathologies.Le but de cette thèse fut la traduction de ce modèle dans un contexte clinique. Nous commençâmes par une large revue de littérature sur les applications de la mécanique dans l’oncologie clinique. Nos recherches furent guidées par deux questions : quels phénomènes mécaniques sont d’intérêt cliniques ? Si oui, comment peut-on les traduire par une modélisation mécanique ? Pour la première question, nous sélectionnâmes l’inhibition mécanique de la croissance tumorale et, comme conséquence des interactions avec le stroma, l’initiation mécanique du changement de phénotype. Pour la seconde, nous choisîmes la modélisation informée par imagerie, mis au point par Swanson et al. en 2002, augmenté par Yankeelov et al. en 2013 et depuis lors largement utilisé. La première année de thèse fut occupés à valider quantitativement le modèle avec l’expérience in vitro d’Alessandri et al., appelée technologie d’encaspulation cellulaire. Ces premiers résultats en main, le centre de neuro-imagerie de Toulouse et le neurochirurgien Dr. Lubrano nous firent l'honneur d'acceper de collaborer avec nous. L’application clinique choisie fut la modélisation de cas non-opérable de glioblastome isocitrate déshydrogénase type naturel. A ce stade, la pandémie de SRAS-Cov2 impacta la progression de notre travaille. Le personnel de l’imagerie fut transféré vers des tâches liées à la pandémie et les collaborations non-essentielle furent arrêtées. Durant cette période, nous construisîmes un modèle de tissue cérébral sain, utilisant la littérature et des expérimentations ex-vivo pour le valider. Pour construire un code de modèle informé par imagerie, nous utilisâmes des atlas publiques. Dr Lubrano et ses collaborateurs réussirent à nous procurer des données patients à deux points temporels, l’un au diagnostic, l’autre après six semaines de radio-chemo-thérapie concomitante. Cela nous permit de tester nos hypothèses, maintenant adaptées au tissu cérébral, sur l’hypoxie et sur l’interaction cellu les-stroma, et de proposer une calibration de notre modèle. Ce travail n’est qu’une première étape pour l’inclusion de la poromécanique dans la modélisation informée par imagerie du glioblastome. Nous espérons que ce cadre prometteur amènera de nouveaux éléments de compréhension dans la description physique du cancer

Cryopréservation des gamètes de mollusques bivalves

ThIs report describes is a preliminary study on oyster cryopreservation on cupped oysters : Crassostrea gigas. Cryopreservation will be used to make crosses and hybridize different species of  Crassostrea. Liquid nitrogen is used to freeze oyster sperm. The deep freezing of samples was made with a "Minicool LC 40" system which used liquid nitrogen to decrease the temperature of samples to -70°C at a speed of 4.7°C/mn. The samples were immersed into liquid nitrogen for storage. The sperm was obtained by stripping than deep frozen. Five cryoprotectors, Glycerol, Methanol, sucrose DMSO and PVP were tested AT differents concentrations from 5% to 15%, but none of them could be used alone. The association between DMSO at 10% and 15% with different concentrations of glycine from 0,2% to 5% were studied with different time of contact (from 5min to 60min) before freezing and 4 different ways of warming. The combination of DMSO 10% and Glycine 0,8% in contact for 15min with the oysters sperm an when the oysters sperm was in contact for 15 minutes with a mixture of DMSO at 10% and Glycine a 0.8%. After sperm is warned for 1min 15s at 35°C. The fertility is 13,21 % in compared to the control. It is the best protocol to cryopreserve oyster sperm in this study.Ce rapport constitue la base d'une étude sur la cryopréservation du sperme d'huîtres creuses Crassostrea gigas .La cryopréservation servira lors des croisements ou d'hybridations d'huîtres L'azote liquide est utilisée comme source de froid . La congélation des échantillons s'effectue grâce à "Minicool LC 40" qui utilise l'azote, pour descendre la température des échantillons à -70°C à une vitesse de 4.7°C/mn. Les échantillons sont alors plongés directement dans l'azote pour le stockage. Le sperme est obtenu par stripping, puis congelé. Cinq cryoprotecteurs, le glycérol, le méthanol, le sucrose, le DMSO et le PVP, sont testés à des concentrations variant de 5% à 15%, aucun n'est utilisable seul. L'association du DMSO à 10% et 15%, et d'une variation de glycine de 0.2% à 5% est étudiée, des temps de contact de 5mn à 60mn et 4 modes de réchauffement. La combinaison de 10% de DMSO et de 0.8% de glycine, mis en contact 15mn avec le sperme et réchauffé pendant 1mn15s à 35°C, fournit une fertilité optimale, 43.21% par rapport au témoin