Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction.

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We constructed a flexible solid-state supercapacitor based on carbon fiber cloth on which a graphene quantum dot-reduced graphene oxide solution and an aqueous polyaniline solution are alternatively sprayed. An acidic gel is used as both the electrolyte and the binder, by which two plates of electrodes are glued together, forming a symmetrical capacitor. The graphene quantum dot-reduced graphene oxide modifies the hydrophobic nature of carbon fiber cloth, which enhances the interactions between carbon fiber cloth and polyaniline. Additionally, under the strong electrostatic forces between the electropositive polyaniline and the electronegative graphene quantum dot-reduced graphene oxide, a self-assembled three-dimensional fiber-like network on carbon fiber cloth is observed. The fabricated solid-state supercapacitor shows a maximum capacitance of 82.9 mF cm −2 (1036 F g −1 ) at a 0.1 mA cm −2 current density referenced to the active materials on the electrodes, with a high stability of 97.7% retention after 10000 charge and discharge cycles, because of the strong interaction between polyaniline and the modified carbon fiber cloth. Moreover, the capacitance is unchanged upon bending. This facile layer-by-layer self-assembly spraying technique shows great advantages of easy operation, good controllability, and versatility and can be used universally for the fabrication of foldable and wearable photoelectric devices.

The three-dimensional (3D) printing technology combined with bone tissue engineering has become one of the major methods for mandibular reconstruction. However, the key factor retarding mandible reconstruction is the barrier of understanding and achieving the complex 3D gridwork formed by the trabeculae. This study innovatively constructed a low-temperature 3D printing silk fibroin/collagen/hydroxyapatite (SF/COL/HA) composite scaffold with a stable structure and remarkable biocompatibility. We designed three kinds of six-layer scaffolds with mixed fiber cross-angle structures (FCAS) of [0°/90°/0°/90°/0°/90°], [0°/45°/90°/135°/180°/225°] and [0°/30°/60°/90°/120°/150°]. Material properties of these scaffolds such as porosity, water absorption rate, X-ray diffraction, Fourier transform infrared spectroscopy, and compression performance were detected. Then, the MC3T3-E1 cells were seeded on these scaffolds and the adhesion, proliferation, and differentiation were investigated. To be more convincing, the same experiments were performed on another polycaprolactone/hydroxyapatite scaffold. The results suggested that the changes of FCAS affected the mechanical properties of 3D printed scaffolds and performance of seeded cells. Besides, the 90° FCAS significantly enhanced the compressive modulus in two groups and were more conducive to the cell proliferation and osteogenesis, which provided evidence for exploring the influence of FCAS on the properties of scaffolds and the application of two composite scaffolds in tissue regeneration.