Modelling and analysis of influenza A (H1N1) on networks

Network modelling is a useful tool for studying the transmission of H1N1 in China, capturing the main features of the spread of H1N1. The paper calculates the basic reproduction number and studies the effects of various immunization schemes. The final size relation is derived for the network epidemic model. While a uniform, mass-immunization strategy helps control the prevalence, a targeted immunization strategy focusing on specific groups with given connectivity may better control an epidemic

Hydrophobically associating polymers for enhanced oil recovery – Part B: A review of modelling approach to flow in porous media

Polymer flow in porous media represents an entirely different scenario compared to bulk flow analysis using viscometers. This is due to the geometry and configuration of the medium which is made up of converging-diverging flow paths. In this article, a review of the single-phase flow of hydrophobically associating polymers in porous media is presented. Hydrophobic association between these polymer chains have been reported to occur and vary under reservoir conditions (temperature, salinity, and ion concentration). However, under these conditions, the critical aggregation concentration of associating polymers has been observed to change and the extent of change is a function of the hydrophobe make-up of the polymer. The outcome of this would indicate that polymer injectivity and its oil recovery efficiency are affected. As such, an understanding of the mechanism, propagation and sustainability of these hydrophobic interactions in reservoirs remains a critical focus of research. This becomes even imperative as the in-situ rheological profile associated with the different flow regimes may be affected. A numerical approach to investigating the real-time hydrophobic interactions between associating polymer chains during flow in porous media remains the viable option. However, this would require modifying existing time-independent models to accurately predict the various flow regimes and the dispersion of associating polymers to account for hydrophobic interactions

Reconstructing B-spline curves from point clouds – a tangential flow approach using least squares minimization

We present a novel algorithm based on least-squares minimization to approximate point cloud data in 2D plane with a smooth B-spline curve. The point cloud data may represent an open curve with self intersection and sharp corner. Unlike other existing methods, such as the moving least-squares method and the principle curve method, our algorithm does not need a thinning process. The idea of our algorithm is intuitive and simple — we make a B-spline curve grow along the tangential directions at its two endpoints following local geometry of point clouds. Our algorithm generates appropriate control points of the fitting B-spline curve in the least squares sense. Although presented for the 2D case, our method can be extended in a straightforward manner to fitting data points by a B-spline curve in higher dimensions. 1

Particle–based T-Spline Level Set Evolution for 3D object reconstruction with Range and Volume Constraints

We consider an evolution process for implicitly defined surfaces, which are represented as the zero–levels of T-spline functions. The paper presents two novel contributions. First, we will use particles on the evolving surface in order to discretize the evolution equation. In particular we describe criteria for local and global resampling, which are needed in order to maintain a sufficiently uniform distribution of the particles. Second, we discuss volume and range constraints which can be added to the framework. More precisely, it is possible to specify a fixed volume (volume constraint) or to define a region which should or should not be contained in the final object (range constraint). These constraints can also be regarded as a priori knowledge of the data