Reviving the Roman Odeon of Aphrodisias: Dynamic Animation and Variety Control of Crowds in Virtual Heritage

In this paper we propose a new method for rendering crowds of virtual humans with dynamicallydeformed skeletons with levels of detail using two simple caching schemes for animations and geometry. Weshow how the virtual heritage project ERATO pushed for these innovations as we did not find any off-theshelfproducts for the purpose. We also show how to create a large variety in appearance using graphicsalgorithm techniques that run on graphics cards with a fixed function pipeline support like the one ofOpenGL 1.

From biochemical reaction networks to 3D dynamics in the cell: The ZigCell3D modeling, simulation and visualisation framework

Systems-oriented research accelerates our understanding of biological processes and helps in identifying novel drug candidates. However, development of good models and our intuition is hampered by the biological complexity. To be able to see how candidate models evolve in front of the user in an interactive virtual 3D cell at various zoom levels, therefore is a crucial aspect and a challenging problem. The motivation for creating the ZigCell3D software, is thus a holistic view ranging from being able to change model parameters, see how they affect 3D versions of the cell at molecular levels, while at the same time being able to verify the simulated model against a real experimental fluorescence microscopy image. ZigCell3D is a virtual 3D whiteboard approach to chemical reaction modelling. It aims to provide a realtime interactive environment, where complex biophysics research is turned into a creative and game-like 3D environment. The complete system entails modelling, simulation and visualisation as part of a unified framework. The core visualisation is based on a multi-core parallel C/C++ ray tracing engine, that builds a complete 3D iso-surface model of the cell, its organelles and molecules down to the atomic level using PDB files. The simulator itself is based on coarse-grained Brownian motion of the individual molecules, which is visualised in detail in a tightly coupled manner. Using a virtual fluorescence microscope the virtual simulation environment can be benchmarked against real life experimental data

From microscopy data to in silico environments for in vivo-oriented simulations

ABSTRACT: : In our previous study, we introduced a combination methodology of Fluorescence Correlation Spectroscopy (FCS) and Transmission Electron Microscopy (TEM), which is powerful to investigate the effect of intracellular environment to biochemical reaction processes. Now, we developed a reconstruction method of realistic simulation spaces based on our TEM images. Interactive raytracing visualization of this space allows the perception of the overall 3D structure, which is not directly accessible from 2D TEM images. Simulation results show that the diffusion in such generated structures strongly depends on image post-processing. Frayed structures corresponding to noisy images hinder the diffusion much stronger than smooth surfaces from denoised images. This means that the correct identification of noise or structure is significant to reconstruct appropriate reaction environment in silico in order to estimate realistic behaviors of reactants in vivo. Static structures lead to anomalous diffusion due to the partial confinement. In contrast, mobile crowding agents do not lead to anomalous diffusion at moderate crowding levels. By varying the mobility of these non-reactive obstacles (NRO), we estimated the relationship between NRO diffusion coefficient (Dnro) and the anomaly in the tracer diffusion (α). For Dnro=21.96 to 44.49 μm2/s, the simulation results match the anomaly obtained from FCS measurements. This range of the diffusion coefficient from simulations is compatible with the range of the diffusion coefficient of structural proteins in the cytoplasm. In addition, we investigated the relationship between the radius of NRO and anomalous diffusion coefficient of tracers by the comparison between different simulations. The radius of NRO has to be 58 nm when the polymer moves with the same diffusion speed as a reactant, which is close to the radius of functional protein complexes in a cell