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Register a new userAnalysis of the Effect of Atherosclerosis with the Changes of Hematocrit: A Computational Study on the Hemodynamics of Carotid Artery
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Atherosclerosis is a state wherein plaque (fat, cholesterol, and different substances) develops inside the veins that in the end prompts carotid artery stenosis which is a phase of narrowing in the huge courses situated on either side of the neck that convey blood to the brain, face, and head. Carotid stenosis is regularly connected with perpetual injury of an aspect of the brain (strokes) because of loss of its blood flexibly. For instance, ischemia generally brings about serious handicap or demise. Hematocrit or pressed cell volume (PCV) is the volume of red blood corpuscles according to that of entire blood. The reason for our exploration is to carry out a Computational Fluid Dynamics (CFD) investigation of blood stream with the rate changes of hematocrit to examine the hemodynamic and physiological conduct of atherosclerosis. Our examination a developed 2D calculation model that has been investigated utilizing Finite volume technique (FVM) for interesting phases of atherosclerosis. The point of this investigation is to investigate the social bits of knowledge into the velocity slope, wall shear stress, and pressure gradient of carotid corridor under various rates of hematocrit and various phases of atherosclerosis. The investigation introduced convincing distinction in these boundaries which can be utilized to recognize the atherosclerosis development.
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Optimal hematocrit $H_o$ maximizes oxygen transport. In healthy humans, the average hematocrit $H$ is in the range of 40-45$%$, but it can significantly change in blood pathologies such as severe anemia (low $H$) and polycythemia (high $H$). Whether the hematocrit level in humans corresponds to the optimal one is a long standing physiological question. Here, using numerical simulations with the Lattice Boltzmann method and two mechanical models of the red blood cell (RBC) we predict the optimal hematocrit, and explore how altering the mechanical properties of RBCs affects $H_o$. We develop a simplified analytical theory that accounts for results obtained from numerical simulations and provides insight into the physical mechanisms determining $H_o$. Our numerical and analytical models can easily be modified to incorporate a wide range of mechanical properties of RBCs as well as other soft particles thereby providing means for the rational design of blood substitutes. Our work lays the foundations for systematic theoretical study of the optimal hematocrit and its link with pathological RBCs associated with various diseases (e.g. sickle cell anemia, diabetes mellitus, malaria, elliptocytosis).
Cardiovascular simulations are increasingly used for non-invasive diagnosis of cardiovascular disease, to guide treatment decisions, and in the design of medical devices. Quantitative assessment of the variability of simulation outputs due to input uncertainty is a key step toward further integration of cardiovascular simulations in the clinical workflow. In this study, we present uncertainty quantification in computational models of the coronary circulation to investigate the effect of uncertain parameters, including coronary pressure waveform, intramyocardial pressure, morphometry exponent, and the vascular wall Youngs modulus. We employ a left coronary artery model with deformable vessel walls, simulated via an ALE framework for FSI, with a prescribed inlet pressure and open-loop lumped parameter network outlet boundary conditions. Stochastic modeling of the uncertain inputs is determined from intra-coronary catheterization data or gathered from the literature. Uncertainty propagation is performed using several approaches including Monte Carlo, Quasi MC, stochastic collocation, and multiwavelet stochastic expansion. Variabilities in QoI, including branch pressure, flow, wall shear stress, and wall deformation are assessed. We find that uncertainty in inlet pressures and intramyocardial pressures significantly affect all resulting QoIs, while uncertainty in elastic modulus only affects the mechanical response of the vascular wall. Variability in the morphometry exponent has little effect on coronary hemodynamics or wall mechanics. Finally, we compare convergence behaviors of statistics of QoIs using several uncertainty propagation methods. From the simulation results, we conclude that the multi-wavelet stochastic expansion shows superior accuracy and performance against Quasi Monte Carlo and stochastic collocation methods.
We show that the recoils of the body caused by cardiac motion and blood circulation provide a noninvasive method capable to display the motions of the heart muscle and the propagation of the pulse wave along aorta and its branches. The results are compared with the data obtained invasively during a heart catheterization. We show that the described noninvasive method is able to determine the moment of a particular heart movement or the time when the pulse wave reaches certain morphological structure.
Recent study reported that an aerosolised virus (COVID-19) can survive in the air for a few hours. It is highly possible that people get infected with the disease by breathing and contact with items contaminated by the aerosolised virus. However, the aerosolised virus transmission and trajectories in various meteorological environments remain unclear. This paper has investigated the movement of aerosolised viruses from a high concentration source across a dense urban area. The case study looks at the highly air polluted areas of London: University College Hospital (UCH) and King Cross and St Pancras International Station (KCSPI). We explored the spread and decay of COVID-19 released from the hospital and railway stations with the prescribed meteorological conditions. The study has three key findings: the primary result is that it is possible for the virus to travel from meters up to hundred meters from the source location. The secondary finding shows viruses released into the atmosphere from entry and exit points at KCSPI remain trapped within a small radial distance of < 50m. This strengthens the case for the use of face coverings to reduce the infection rate. The final finding shows that there are different levels of risk at various door locations for UCH, depending on which door is used there can be a higher concentration of COVID-19. Although our results are based on London, since the fundamental knowledge processes are the same, our study can be further extended to other locations (especially the highly air polluted areas) in the world.
We report a correlative microscopy study of a sample containing three stacks of InGaN/GaN quantum dots (QDs) grown at different substrate temperature, each stack consisting of 3 layers of QDs. Decreasing the substrate temperature along the growth axis leads to the proliferation of structural defects. However, the luminescence intensity increases towards the surface, in spite of the higher density of threading dislocations, revealing that the QD layers closer to the substrate behave as traps for non-radiative point defects. During atom probe tomography experiments combined with in-situ micro-photoluminescence, it was possible to isolate the optical emission of a single QD located in the topmost QD stack, closer to the sample surface. The single QD emission line displayed a spectral shift during the experiment confirming the relaxation of elastic strain due to material evaporation during atom probe tomography.
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