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Previous work introduced a lower-dimensional numerical model for the geometric nonlinear simulation and optimization of compliant pressure actuated cellular structures. This model takes into account hinge eccentricities as well as rotational and axial cell side springs. The aim of this article is twofold. First, previous work is extended by introducing an associated continuum model. This model is an exact geometric representation of a cellular structure and the basis for the spring stiffnesses and eccentricities of the numerical model. Second, the state variables of the continuum and numerical model are linked via discontinuous stress constraints on the one hand and spring stiffness, hinge eccentricities on the other hand. An efficient optimization algorithm that fully couples both sets of variables is presented. The performance of the proposed approach is demonstrated with the help of an examples.
For more than ten years now, many efforts have been done to identify and characterize nature of obstructed diffusion in model and cellular lipid membranes. Amongst all the techniques developed for this purpose, FCS, by means of determination of FCS d
Brain tissue is a heterogeneous material, constituted by a soft matrix filled with cerebrospinal fluid. The interactions between, and the complexity of each of these components are responsible for the non-linear rate-dependent behaviour that characte
von Willebrand Factor is a mechano-sensitive protein circulating in blood that mediates platelet adhesion to subendothelial collagen and platelet aggregation at high shear rates. Its hemostatic function and thrombogenic effect, as well as susceptibil
The ongoing effort to detect and characterize physical entanglement in biopolymers has so far established that knots are present in many globular proteins and also abound in viral DNA packaged inside bacteriophages. RNA molecules, on the other hand,
Electron Cryo-Tomography (ECT) enables 3D visualization of macromolecule structure inside single cells. Macromolecule classification approaches based on convolutional neural networks (CNN) were developed to separate millions of macromolecules capture