Since the widely used Hidden Markov model (HMM) in speech recognition is first order Markov model, it can not fully model the temporal dependence of speech signal.

Gray matter on the poles of the temporal lobes was significantly denser in the subjects who had scored high on reward dependence than in the subjects who had not.

By assuming a Gaussian temporal shape of laser pulse, some numerical results of the threshold dependence on pulse duration are presented.