A coupled SPH-DEM approach to model the interactions between multiple red blood cells in motion in capillaries

Red blood cells (RBCs) are the most common type of blood cells in the blood and 99% of the blood cells are RBCs. During the circulation of blood in the cardiovascular network, RBCs squeeze through the tiny blood vessels (capillaries). They exhibit various types of motions and deformed shapes, when flowing through these capillaries with diameters varying between 5 10 µm. RBCs occupy about 45 % of the whole blood volume and the interaction between the RBCs directly influences on the motion and the deformation of the RBCs. However, most of the previous numerical studies have explored the motion and deformation of a single RBC when the interaction between RBCs has been neglected. In this study, motion and deformation of two 2D (two-dimensional) RBCs in capillaries are comprehensively explored using a coupled smoothed particle hydrodynamics (SPH) and discrete element method (DEM) model. In order to clearly model the interactions between RBCs, only two RBCs are considered in this study even though blood with RBCs is continuously flowing through the blood vessels. A spring network based on the DEM is employed to model the viscoelastic membrane of the RBC while the inside and outside fluid of RBC is modelled by SPH. The effect of the initial distance between two RBCs, membrane bending stiffness (Kb) of one RBC and undeformed diameter of one RBC on the motion and deformation of both RBCs in a uniform capillary is studied. Finally, the deformation behavior of two RBCs in a stenosed capillary is also examined. Simulation results reveal that the interaction between RBCs has significant influence on their motion and deformation.

Numerical modelling of deformation behaviour of red blood cells in microvessels using the coupled SPH-DEM method

This thesis developed an advanced computational model to investigate the motion and deformation properties of red blood cells in capillaries. The novel model is based on the meshfree particle methods and is capable of modelling the large deformation of red blood cells moving through blood vessels. The developed model was employed to simulate the deformation behaviour of healthy and malaria infected red blood cells as well as the motion of red blood cells in stenosed capillaries.

Do small-aperture presbyopic corrections influence the visual field?

Purpose To explore the effect of small-aperture optics, designed to aid presbyopes by increasing ocular depth-of-focus, on measurements of the visual field. Methods Simple theoretical and ray-tracing models were used to predict the impact of different designs of small-aperture contact lenses or corneal inlays on the proportion of light passing through natural pupils of various diameters as a function of the direction in the visual field. The left eyes of five healthy volunteers were tested using three afocal, hand-painted opaque soft contact lenses (www.davidthomas.com). Two were opaque over a 10 mm diameter but had central clear circular apertures of 1.5 and 3.0 mm in diameter. The third had an annular opaque zone with inner and outer diameters of 1.5 and 4.0 mm, approximately simulating the geometry of the KAMRA inlay (www.acufocus.com). A fourth, clear lens was used for comparison purposes. Visual fields along the horizontal meridian were evaluated up to 50° eccentricity with static automated perimetry (Medmont M700, stimulus Goldmann-size III; www.medmont.com). Results According to ray-tracing, the two lenses with the circular apertures were expected to reduce the relative transmittance of the pupil to zero at specific field angles (around 60° for the conditions of the experimental measurements). In contrast, the annular stop had no effect on the absolute field but relative transmittance was reduced over the central area of the field, the exact effects depending upon the natural pupil diameter. Experimental results broadly agreed with these theoretical expectations. With the 1.5 and 3.0 mm pupils, only minor losses in sensitivity (around 2 dB) in comparison with the clear-lens case occurred across the central 10° radius of field. Beyond this angle, sensitivity losses increased, to reach about 7 dB at the edge of the measured field (50°). The field results with the annular stop showed at most only a slight loss in sensitivity (≤3 dB) across the measured field. Conclusion The present theoretical and experimental results support earlier clinical findings that KAMRA-type annular stops, unlike circular artificial pupils, have only minor effects on measurements of the visual field.

Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling

Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.