ABSTRACT
A variational Bayesian approach to robust identification of switched auto-regressive exogenous models is developed in this paper. By formulating the problem of interest under a full Bayesian identification framework, the number of local-models can be determined automatically, while accounting for the uncertainty of parameter estimates in the overall identification procedure. A set of significance coefficients is used to assign proper importance weights to local-models. By maximizing the marginal likelihood of the identification data, insignificant local-models will be suppressed and the optimal number of local-models can be determined. Considering the fact that the identification data may be contaminated with outliers, t distributions with adjustable tails are utilized to model the contaminating noise so that the proposed identification algorithm is robust. The effectiveness of the proposed Bayesian approach is demonstrated through a simulated example as well as a detailed industrial application.
ABSTRACT
Intrinsic radiosensitivity of normal and tumour tissues has been shown to be an independent prognostic factor for patients' response to radiotherapy. This study compares the real-time cell-impedance sensing (RT-CES) assay with the conventional clonogenic assay in terms of in-vitro radiosensitivity. One objective in this study was to predict in-vivo response to gold nanoparticle (GNP) treatment on the basis of in-vitro RT-CES testing results. Four adenocarcinoma cancer cell lines were tested using both the RT-CES and the clonogenic assays. Cell-survival curves were plotted, and the mean SF2 values obtained by these two different assay methods were compared using ANOVA. Radiation sensitivities obtained in-vitro were then compared with the in-vivo results. On the basis of the measurement of cell colonies, the RT-CES assay has similar radiosensitivity to the clonogenic assay, but significantly shortens the testing time from 14-21 days to only 72 h. Intrinsic GNP enhanced radiation sensitivity using tumour volume (mm(3)) in vivo is comparable with that using RT-CES cell survival assay in vitro. Furthermore, the RT-CES system provides real-time information regarding the state of cell radiosensitivity that may give useful information towards personalizing radiotherapy. The RT-CES assay enables more reliable and time-efficient results in the evaluation of radiosensitivity.
