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The prediction of the rheological properties of concentrated suspensions is of great importance both in industrial processes (ceramics, cements, and pharmaceutics) and natural phenomena (debris flow, soil erosion). In a previous paper, we presented a new m ...
Carcinogenesis is commonly described as a multistage process, in which stem cells are transformed into cancer cells via a series of mutations. In this article, we consider extensions of the multistage carcinogenesis model by mixture modeling. This approach ...
Dissolved organic matter (DOM) is a complex mixture of ill-defined components,which makes the quantitative understanding ofDOMfunctions in aquatic systems a challenging task.The traditional approach for studying such complex mixtures involves their separat ...
We present three different prepn. methods for CdSe colloidal nanoparticles that, when carried out into the Ostwald ripening regime, lead to the development of complex spectral patterns resulting from the overlap of several distinct components corresponding ...
The work accomplished during the second period of the project mainly focused on the experimental evaluation of the prechamber system comparing its performance regarding emissions and efficiency to standard spark ignition mode. Further instrumentation of th ...
Predicting the disinfection performance of a full-scale reactor in drinking water treatment is associated with considerable uncertainty. In view of quantitative risk analysis, this study assesses the uncertainty involved in predicting inactivation of Crypt ...
Bayesian inference of posterior parameter distributions has become widely used in hydrological modeling to estimate the associated modeling uncertainty. The classical underlying statistical model assumes a Gaussian modeling error with zero mean and a given ...
The measurement of scalar (J) couplings by solid-state NMR is a field of great interest, since this interaction is a rich source of local structural information, complementary to dipolar and chemical shift interactions. Here, we first demonstrate that J-co ...
The spectral density function plays a key role in fitting the tail of multivariate extremal data and so in estimating probabilities of rare events. This function satisfies moment constraints but unlike the univariate extreme value distributions has no simple ...
We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the probability density functions of both regions within the optimization process ...
