ICCS 2019 Main Track (MT) Session 8
Time and Date: 14:20 - 16:00 on 14th June 2018
Chair: To be announced
|225|| Immersed boundary method halo exchange in a hemodynamics application [abstract]
Abstract: In recent years, highly parallelized simulations of blood flow resolving individual blood cells have been demonstrated. Simulating such dense suspensions of deformable particles in flow often involves a partitioned fluid-structure interaction (FSI) algorithm, with separate solvers for Eulerian fluid and Lagrangian cell grids, plus a solver - e.g., immersed boundary method - for their interaction. Managing data motion in parallel FSI implementations is increasingly important, particularly for inhomogeneous systems like vascular geometries. In this study, we evaluate the influence of Eulerian and Lagrangian halo exchanges on efficiency and scalability of a partitioned FSI algorithm for blood flow. We describe an MPI+OpenMP implementation of the immersed boundary method coupled with lattice Boltzmann and finite element methods. We consider how communication and recomputation costs influence the optimization of halo exchanges with respect to three factors: immersed boundary interaction distance, cell suspension density, and relative fluid/cell solver costs.
|John Gounley, Erik W. Draeger and Amanda Randles|
|370|| Future ramifications of age-dependent immunity levels for measles: explorations in an individual-based model [abstract]
Abstract: When a high population immunity already exists for a dis- ease, heterogeneities become more important to understand the spread of this disease. Individual-based models are suited to investigate the ef- fects of these heterogeneities. Measles is a disease for which, in many regions, high population immunity exists. However, different levels of immunity are observed for different age groups. For example, the gen- eration born between 1985 and 1995 in Flanders is incompletely vacci- nated, and thus has a higher level of susceptibility. As time progresses, this peak in susceptibility will shift to an older age category. Simultane- ously, susceptibility will increase due to the waning of vaccine-induced immunity. Older generations, with a high degree of natural immunity, will, on the other hand, eventually disappear from the population. Us- ing an individual-based model, we investigate the impact of changing age-dependent immunity levels (projected for Flanders, for years 2013 to 2040) on the risk for measles outbreaks. We find that, as time pro- gresses, the risk for measles outbreaks increases, and outbreaks tend to be larger. As such, it is important to not only consider infants when designing strategies for measles elimination, but to also take other age categories into account.
|Elise Kuylen, Lander Willem, Niel Hens and Jan Broeckhove|
|386|| Evolution of Hierarchical Structure & Reuse in iGEM Synthetic DNA Sequences [abstract]
Abstract: Many complex systems, both in technology and nature, exhibit hierarchical modularity: smaller modules, each of them providing a certain function, are used within larger modules that perform more complex functions. Previously, we have proposed a modeling framework, referred to as Evo-Lexis, that provides insight to some fundamental questions about evolving hierarchical systems. The predictions of the Evo-Lexis model should be tested using real data from evolving systems in which the outputs can be well represented by sequences. In this paper, we investigate the time series of iGEM synthetic DNA dataset sequences, and whether the resulting iGEM hierarchies exhibit the qualitative properties predicted by the Evo-Lexis framework. Contrary to Evo-Lexis, in iGEM the amount of reuse decreases during the timeline of the dataset. Although this results in development of less cost-efficient and less deep Lexis-DAGs, the dataset exhibits a bias in reusing specific nodes more often than others. This results in the Lexis-DAGs to take the shape of an hourglass with relatively high H-score values and stable set of core nodes. Despite the reuse bias and stability of the core set, the dataset presents a high amount of diversity among the targets which is in line with modeling of Evo-Lexis.
|Payam Siyari, Bistra Dilkina and Constantine Dovrolis|
|475|| Computational design of superhelices by local change of the intrinsic curvature [abstract]
Abstract: Helices appear in nature at many scales, ranging from molecules to tendrils in plants. Organisms take advantage of the helical shape to fold, propel and assemble. For this reason, several applications in micro and nanorobotics, drug delivery and soft-electronics have been suggested. On the other hand, biomolecules can form complex tertiary structures made with helices to accomplish many different functions. A particular well-known case takes place during cell division when DNA, a double helix, is packaged into a super-helix – i.e., a helix made of helices – to prevent DNA entanglement. DNA super-helix formation requires auxiliary histone molecules, around which DNA is wrapped, in a "beads on a string" structure. The idea of creating superstructures from simple elastic filaments served as the inspiration to this work. Here we report a method to produce ribbons with complex shapes by periodically creating strains along the ribbons. Ribbons can gain helical shapes, and their helicity is ruled by the asymmetric contraction along the main axis. If the direction of the intrinsic curvature is locally changed, then a tertiary structure results, similar to the DNA wrapped structure. In this process, auxiliary structures are not required and therefore new methodologies to shape filaments, of interest to nanotechnology and biomolecular science, are proposed.
|Pedro E. S. Silva, Maria Helena Godinho and Fernão Vístulo de Abreu|
|493|| Spatial modeling of influenza outbreaks in Saint Petersburg using synthetic populations [abstract]
Abstract: In this paper, we model influenza propagation in the Russian setting using a spatially explicit model and a detailed human agent database as its input. The aim of the research is to assess the applicability of this modeling method using influenza incidence data for 2010-2011 epidemic outbreak in Saint Petersburg and to compare the simulation results with the output of the compartmental SEIR model for the same outbreak. For this purpose, a synthetic population of Saint Petersburg was built and used for the simulation via FRED open source modeling framework. The parameters related to the outbreak (background immunity level and effective contact rate) are assessed by calibrating the compartmental model to incidence data. We show that the current version of synthetic population allows the agent-based model to reproduce real disease incidence.
|Vasiliy Leonenko, Alexander Lobachev and Georgiy Bobashev|