Electromagnetic properties of a thermoplastic natural rubber (TPNR), a lithium–nickel–zinc (Li–Ni–Zn) ferrite and a TPNR–ferrite composite subjected to transverse electromagnetic (TEM) wave propagation were investigated. The incorporation of the ferrite into the matrix of the TPNR was found to reduce the dielectric loss but the magnetic loss increased. The absorption characteristics of all the samples subjected to a normal incidence of TEM wave were investigated based on a model of a single-layered plane wave absorber backed by a perfect conductor. It is evident from a computer simulation that the ferrite is a narrowband absorber, whereas the polymeric samples show broadband absorption characteristics. Minimal reflection of the microwave power or matching condition occurs when the thickness of the absorbers approximates an odd number multiple of a quarter of the propagating wavelength. This is discussed as due to cancellation of the incident and reflected waves at the surface of the absorbers. The Li–Ni–Zn ferrite exhibits another matching condition at low frequency when the magnitude of the complex relative dielectric permittivity ${\mathrm{(\epsilon }}_r^{*})$ equals that of the complex relative magnetic permeability ${\mathrm{(\mu }}_r^{*}\mathrm{).}$ The specular absorber method provides a simple theoretical graphic aid for determining the absorption characteristics and the location of the matching conditions in the frequency domain. The result for the ferrite sample was tested and confirmed directly from terminated one-port measurements.

Research suggests that white noise may facilitate auditory working memory performance via stochastic resonance. Stochastic resonance is quantified by plotting cognitive performance as a function of noise intensity. The plot would appear as an inverted U-curve, that is, a moderate noise is beneficial for performance whereas too low and too much noise attenuates performance. However, knowledge about the optimal signal-to-noise ratio (SNR) needed for stochastic resonance to occur in the brain, particularly in the neural network of auditory working memory, is limited and demand further investigation. In the present study, we extended previous works on the impact of white noise on auditory working memory performance by including multiple background noise levels to map out the inverted U-curve for the stochastic resonance. Using functional magnetic resonance imaging (fMRI), twenty healthy young adults performed a word-based backward recall span task under four signal-to-noise ratio conditions: 15, 10, 5, and 0-dB SNR. Group results show significant behavioral improvement and increased activation in frontal cortices, primary auditory cortices, and anterior cingulate cortex in all noise conditions, except at 0-dB SNR, which decreases activation and performance. When plotted as a function of signal-to-noise ratio, behavioral and fMRI data exhibited a noise-benefit inverted U-shaped curve. Additionally, a significant positive correlation was found between the activity of the right superior frontal gyrus (SFG) and performance in 5-dB SNR. The predicted phenomenon of SR on auditory working memory performance is confirmed. Findings from this study suggest that the optimal signal-to-noise ratio to enhance auditory working memory performance is within 10 to 5-dB SNR and that the right SFG may be a strategic structure involved in enhancement of auditory working memory performance.