Application of the nonlinear methods in pneumocardiogram signals.

In this work, the pneumocardiogram signals of nine rats were analysed by scale index, Boltzmann Gibbs entropy and maximum Lyapunov exponents. The scale index method, based on wavelet transform, was proposed for determining the degree of aperiodicity and chaos. It means that the scale index parameter is close to zero when the signal is periodic and has a value between zero and one when the signal is aperiodic. A new entropy calculation method by normalized inner scalogram was suggested very recently. In this work, we also used this method for the first time in an empirical data. We compared the both methods with maximum Lyapunov exponents and observed that using together the scale index and the entropy calculation method by normalized inner scalogram increases the reliability of the pneumocardiogram signal analysis. Thus, the analysis of the pneumocardiogram signals by those methods enables to compare periodical and/or nonlinear aspects for further understanding of dynamics of cardiorespiratory system.

Polarization-insensitive beam splitters using all-dielectric phase gradient metasurfaces at visible wavelengths.

Beam splitters play important roles in several optical applications, such as interferometers, spectroscopy, and optical communications. In this study, we propose and numerically examine polarization-insensitive beam splitters utilizing two-step phase gradient all-dielectric metasurfaces in the visible spectrum. The metasurface is made of periodically arranged binary unit cells, and phase difference between neighboring unit cells on the surface is 180 deg. The metasurface is shown to have a special phase gradient whose sign changes periodically. The angle of the split beams on both sides and the corresponding total transmission value at 532 nm wavelength are found to be ±46.8° and 0.90, respectively.

Study of Weak Periodic Signals in the EEG Signals and Their Relationship With Postsynaptic Potentials.

In this paper, weak periodic signals detected in the EEG signals were analyzed for each region of the brain, and its relationships with postsynaptic potentials were investigated. For this, EEG signals were collected from 16 different channels according to the international standard channel 10/20 system in the scalp of two patients, one epileptic and one non-epileptic. In our recent work, we have detected weak periodic signals in the EEG signals using a Duffing oscillator system. In this paper, we have used a compact method by combining the Duffing oscillator system with scale index, which is based on a wavelet analysis in order to make the determination of the weak periodic signals more straightforward in practice. A number of weak periodic signals were detected in the range of frequencies 4.7-16 Hz in all channels, and however, these were less observed in epileptic EEG signals than non-epileptic. This methodology illustrates that weak periodic signals can be used to distinguish epileptic EEG signals from non-epileptic EEG signals. We have revealed some findings that the weak periodic signals are the postsynaptic potentials of the brain. Therefore, we can measure some frequencies values of the postsynaptic potentials within the EEG signals with this methodology.