Prosodic realization of focus has been a widely investigated topic across languages and modalities. Simultaneous focus strategies are intriguing to see how they interact regarding their functional and temporal alignment. We explored the multichannel (manual and nonmanual) realization of focus in Turkish Sign Language. We elicited data with focus type, syntactic roles and movement type variables from 20 signers. The results revealed the focus is encoded via increased duration in manual signs, and nonmanuals do not necessarily accompany focused signs. With a multichanneled structure, sign languages use two available channels or opt for one to express focushood.

A method for improving range resolution in passive radar system is to jointly use more than one transmission channel of the same illuminator of opportunity (IO). This paper specifically focuses on the exploitation of multiple adjacent digital video broadcasting-terrestrial (DVB-T) channels for achieving high-range resolution profiles with a passive radar system operating in air surveillance scenario. Firstly, we present an analysis of the ambiguity function obtained from a multichannel DVB-T source and a pre-processing technique able to improve the characteristics of the multichannel signal are presented. Afterwards, the experimental scenario is defined and detection results on aerial targets are shown.

With the advent of dense sensor arrays (64–256 channels) in electroencephalography and magnetoencephalography studies, the probability increases that some recording channels are contaminated by artifact. If all channels are required to be artifact free, the number of acceptable trials may be unacceptably low. Precise artifact screening is necessary for accurate spatial mapping, for current density measures, for source analysis, and for accurate temporal analysis based on single-trial methods. Precise screening presents a number of problems given the large datasets. We propose a procedure for statistical correction of artifacts in dense array studies (SCADS), which (1) detects individual channel artifacts using the recording reference, (2) detects global artifacts using the average reference, (3) replaces artifact-contaminated sensors with spherical interpolation statistically weighted on the basis of all sensors, and (4) computes the variance of the signal across trials to document the stability of the averaged waveform. Examples from 128-channel recordings and from numerical simulations illustrate the importance of careful artifact review in the avoidance of analysis errors.