CellML is an XML-based exchange format developed by the University of Auckland in collaboration with Physiome Sciences, Inc. CellML 1.1 has a component-based architecture allowing a modeller to build complex systems of models that expand and reuse previously published models. CellML Metadata is a format for encoding contextual information for a model. CellML 1.1 can be used in conjunction with CellML Metadata to provide a complete description of the structure and underlying mathematics of biological models. A repository of over 200 electrophysiological, mechanical, signal transduction, and metabolic pathway models is available at www.cellml.org.
SUMMARYThere are a number of situations where the deformed configuration of a body is known and it is necessary to determine the reference state. Previous methods developed to calculate the reference state involve the formulation of the finite elasticity equations in terms of the deformed configuration. This paper demonstrates that the undeformed reference state can be accurately determined from a deformed configuration and the associated loading conditions, by using conventional finite elasticity balance equations together with a solution procedure that treats the reference configuration as the unknowns. The mathematical theory behind the solution method is described, validated with an analytical solution, and verified using experimental studies on gel phantoms. The practical utility of this method is then demonstrated in the field of breast biomechanics.
We describe a neurobehavioural modeling and visual computing framework for the integration of realistic interactive computer graphics with neural systems modelling, allowing real-time autonomous facial animation and interactive visualization of the underlying neural network models. The system has been designed to integrate and interconnect a wide range of computational neuroscience models to construct embodied interactive psychobiological models of behaviour. An example application of the framework combines models of the facial motor system, physiologically based emotional systems, and basic neural systems involved in early interactive behaviour and learning and embodies them in a virtual infant rendered with realistic computer graphics. The model reacts in real time to visual and auditory input and its own evolving internal processes as a dynamic system. The live state of the model which generates the resulting facial behaviour can be visualized through graphs and schematics or by exploring the activity mapped to the underlying neuroanatomy.
*The development of autonomous interactive virtual agents and social robots is a developing area of research aiming to recreate naturalistic human behaviour in computer graphic or humanoid robotic form. A key idea behind making humanlike digital characters and robots more realistic in appearance and behaviour is that in doing so we open up many more natural channels of communication -we begin to share the same appearance and signaling mechanisms, making for a more fluid interaction between man and machine, whether it is for entertainment or functionality. However creating realistic appearance and behaviour is challenging
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