Facial Prior Guided Micro-Expression Generation.

This paper focuses on the facial micro-expression (FME) generation task, which has potential application in enlarging digital FME datasets, thereby alleviating the lack of training data with labels in existing micro-expression datasets. Despite obvious progress in the image animation task, FME generation remains challenging because existing image animation methods can hardly encode subtle and short-term facial motion information. To this end, we present a facial-prior-guided FME generation framework that takes advantage of facial priors for facial motion generation.

Ultra-stable perovskite quantum dot composites encapsulated with mesoporous SiO and PbBr(OH) for white light-emitting diodes.

Lead halide perovskite quantum dots (QDs) with high fluorescence efficiency and high color purity have a broad application prospect in the field of backlight display, but poor stability has been a key factor limiting their commercialization. Herein, we successfully synthesized CsPbBr QDs-KIT-6 (CsPbBr -K6) composite by using KIT-6 molecular sieve as the limited template with a simple high temperature solid-phase method. Further, the semi-protected CsPbBr QDs in KIT-6 frame will spontaneously hydrolyze when encountering water, and finally the double-encapsulated CsPbBr QDs-KIT-6@PbBr(OH) (CsPbBr -K6@PbBr(OH)) composite are obtained.

One-Step Hydrothermal Synthesis of MoO/MoS Nanocomposites as High-Performance Electrode Material for Supercapacitors.

By only changing the ratio of Mo to S source, a distinctive single phase MoO or MoS and MoO/MoS nanocomposites (NCs) are obtained through a simple one-step hydrothermal method based on CHNS as a sulfur source and (NH)MoO·4HO as a source of Mo in oxalic acid. The effect of ratio of Mo to S source on the composition, structure, and electrochemical performance are systematically researched. Due to its unique design, abundant macropores active sites in MoO/MoS NCs induce superior rate property (55.

CARes-UNet: Content-aware residual UNet for lesion segmentation of COVID-19 from chest CT images.

Purpose: Coronavirus disease 2019 (COVID-19) has caused a serious global health crisis. It has been proven that the deep learning method has great potential to assist doctors in diagnosing COVID-19 by automatically segmenting the lesions in computed tomography (CT) slices. However, there are still several challenges restricting the application of these methods, including high variation in lesion characteristics and low contrast between lesion areas and healthy tissues.

In-air self-reduction synthesis and luminescence properties from Mg Ca Na (PO ) :Eu -Eu excited using ultraviolet light.

A series of Mg Ca Na (PO ) :Eu -Eu phosphors was successfully synthesized using a high-temperature solid-state method in an air atmosphere. The phase structures and luminescence properties of the samples were studied in detail. The phosphors exhibited strong visible light emission under different wavelengths of ultraviolet light excitation.