Micromechanics-Supported Conversion of Computer Tomographic (CT) Images into Anisotropic and Inhomogeneous Finite Element Models of Organs: the Case of a Human Mandible

We here present a strategy for reliable prediction of elastic properties from X-ray attenuation coefficients visualized in Computer Tomographic images, as basis for Finite Element models. By example, we show the distribution of the axial normal stress throughout a human mandible, due to a bite on the leftmost premolar. Remarkably, this distribution is not heavily altered if we replace the inhomogeneous material distribution by one discerning merely cortical and trabecular bone, but it is strongly affected by the consideration of material anisotropy. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

“Assessing the RAFT Equilibrium Constant via Model Systems: An EPR Study”—Response to a Comment

We have presented an EPR‐based approach for deducing the RAFT equilibrium constant, K_eq, of a dithiobenzoate‐mediated system [Meiser, W. and Buback M. Macromol. Rapid Commun. 2011 , 32, 1490]. Our value is by four orders of magnitude below K_eq from ab initio calculations for the identical monomer‐free system. Junkers et al. [Macromol. Rapid Commun. 2011 , 32, 1891] claim that our EPR approach would be model dependent and our data could be equally well fitted by assuming slow addition of radicals to the RAFT agent and slow fragmentation of the so‐obtained intermediate radical as well as high cross‐termination rate. By identification of all side products, our EPR‐based method is shown to be model independent and to provide reliable K_eq values, which demonstrate the validity of the intermediate radical termination model.     

Component importance based on dependence measures

We discuss the construction of component importance measures for binary coherent reliability systems from known stochastic dependence measures by measuring the dependence between system and component failures. We treat both the time-dependent case in which the system and its components are described by binary random variables at a fixed instant as well as the continuous time case where the system and component life times are random variables. As dependence measures we discuss covariance and mutual information, the latter being based on Shannon entropy. We prove some basic properties of the resulting importance measures and obtain results on importance ordering of components.