Temporal-spatial dynamic functional connectivity analysis in schizophrenia classification.

With the development of resting-state functional magnetic resonance imaging (rs-fMRI) technology, the functional connectivity network (FCN) which reflects the statistical similarity of temporal activity between brain regions has shown promising results for the identification of neuropsychiatric disorders. Alteration in FCN is believed to have the potential to locate biomarkers for classifying or predicting schizophrenia (SZ) from healthy control. However, the traditional FCN analysis with stationary assumption, i.

Bending losses of trench-assisted few-mode optical fibers.

A semianalytical method based on the perturbation theory is developed to calculate the bending losses of individual modes of few-mode fibers (FMFs); it is applicable for optical fibers with arbitrary circularly symmetric index profile, especially for trench-assisted fibers. The bending performance of trench-assisted step-index FMFs and parabolic-index FMFs are investigated with three key parameters (i.e.