Dual projection generalized sidelobe canceller based on mixed signal subspace for ultrasound imaging.

In this paper, we propose a dual projection generalized sidelobe canceller (DPGSC) based on mixed subspace (MS) for ultrasound imaging, which aims to improve the speckle signal-noise-ratio (sSNR) and decrease the dark-region artifacts. A mixed signal subspace based on the correlation between the desired steering vector and the eigenvectors is constructed to further optimize the desired steering vector and the final weight vector. The simulated and experimental results show that the proposed method can greatly improve the speckle uniformity. In the geabr_0 experiment, the standard deviation of background and sSNR of MS-DPGSC can be improved by 48.07% and 58.49% more than those of eigenspace-based generalized sidelobe canceller (ESGSC). Furthermore, for a hyperechoic target, the maximal improvement of contrast ratio is 95.29%. In terms of anechoic cyst, the contrast-to-noise ratio of MS-DPGSC is increased by 123.08% than that of ESGSC. The rat mammary tumor experimental data show that the proposed method has better comprehensive imaging effect than traditional generalized sidelobe cancellers and ESGSCs.

Tunable mechanical, self-healing hydrogels driven by sodium alginate and modified carbon nanotubes for health monitoring.

Conductive hydrogels featuring a modulus similar to the skin have flourished in health monitoring and human-machine interface systems. However, developing conductive hydrogels with self-healing and tunable force-electrical performance remains a problem. Herein, a hydrogen bonding cross-linking strategy was utilized by incorporating silk sericin-modified carbon nanotubes (SS@CNTs) into sodium alginate (SA) and polyvinyl alcohol (PVA). Hydrogels synthesized with desirable tensile strength and self-healing ability (67.2 % self-healing efficiency in fracture strength) assembled into strain sensors with a low detection limit of 0.5 % and a gauge factor (GF) of 4.75 (0-17 %). Additionally, as-prepared hydrogels exhibit high sensitivity to tiny pressure changes, allowing recognition of complex handwriting. Notably, resulting hydrogels possess self-powered property, generating up to 215 V and illuminating 100 commercial green LEDs. This work stems from the pressing need for multifunctional hydrogels with prospective applications in human motion sensing and energy harvesting.