https://www.selleckchem.com/products/7-12-dimethylbenz-a-anthracene-dmba.html Consequently, dual-mode luminescence with multi-color outputs can be achieved in the pre-designed core-shell nanostructure under the excitation of a 980 nm near-infrared laser and 254 nm UV light. The designed nanoarchitecture with bright dual-mode emissions and tunable colors greatly improves the ability of modern anti-counterfeiting, demonstrating its promising applications in anti-fake and optical multiplexing.Objective Statistical methods that simultaneously model temporal and spatial variations of fMRI data are promising tools for dynamic functional connectivity (FC) estimation. Although different approaches are available, they need to manually set the parameters, or may disregard some important fMRI features such as the autocorrelation. In addition, no reliable method exists for the validation of dynamic FC analysis models. Approach In the present study, we have proposed an autoregressive dynamic conditional correlation model to deal with the temporal autocorrelation and non-stationarity in fMRI time-series. This model assumes that the brain time courses follow a multivariate Gaussian distribution, and that the conditional mean, variance and covariances change in an autoregressive form. Also, we proposed a new measurement index for the evaluation of the statistical consistency between the inferred dynamic functional connectivity and the real fMRI data. The performance of our model was tested in both simulated and real fMRI data. Main results The model was associated with independent Gaussian residuals, and identified the dynamic connectivity patterns with high precision. Applying the model to the fMRI data from typically developing and attention deficit hyperactivity disorder subjects, brain connectivities were significantly different between the two groups. Significance Prominent features of our model were the consideration of the fMRI autocorrelation, no need to adjust the window l