Mediation effects of post-series depression on the relationship between life satisfaction and positive mental health of Vietnamese: A cross-sectional study in COVID-19 pandemic context.

Vietnam, a middle-income country, has been suffering four waves of the Coronavirus disease 2019 (COVID-19) pandemic and a massive lockdown to suppress the spread of this infectious disease. Consequently, COVID-19 has caused psychological ramifications and affected humankind's life satisfaction. Because of the lockdown period, numerous people had plentiful time.

Three New Phthalide Glycosides from the Rhizomes of and Their Recovery Effect on Damaged Otic Hair Cells in Zebrafish.

The extract from rhizomes was shown in a prior experiment to markedly recover otic hair cells in zebrafish damaged by neomycin. The current study was brought about to identify the principal metabolite. Column chromatography using octadecyl SiO and SiO was performed to isolate the major metabolites from the active fraction.

Aurones and Flavonols from L. Flowers and Their Anti-Oxidant, Pro-Inflammatory Inhibition Effects, and Recovery Effects on Alloxan-Induced Pancreatic Islets in Zebrafish.

(1) Background: Many flavonoids have been reported to exhibit pharmacological activity; a preparatory study confirmed that flowers (CLFs) contained high flavonoid structure content; (2) Methods: CLFs were extracted in aqueous methanol (MeOH:HO = 4:1) and fractionated into acetic ester (EtOAc), normal butanol (-BuOH), and HO fractions. Repeated column chromatographies for two fractions led to the isolation of two aurones and two flavonols; (3) Results: Four flavonoids were identified based on a variety of spectroscopic data analyses to be leptosidin (), leptosin (), isoquercetin (), and astragalin (), respectively. This is the first report for isolation of - from CLFs.

SmithNet: Strictness on Motion-Texture Coherence for Anomaly Detection.

Anomaly detection is a key functionality in various vision systems, such as surveillance and security. In this work, we present a convolutional neural network (CNN) that supports the detection of anomaly, which has not been defined when building the model, at frame level. Our CNN, named SmithNet, is structured to simultaneously learn commonly occurring textures and their corresponding motion.

Measurement of Human Gait Symmetry using Body Surface Normals Extracted from Depth Maps.

In this paper, we introduce an approach for measuring human gait symmetry where the input is a sequence of depth maps of subject walking on a treadmill. Body surface normals are used to describe 3D information of the walking subject in each frame. Two different schemes for embedding the temporal factor into a symmetry index are proposed.

Human gait symmetry assessment using a depth camera and mirrors.

It is proposed in this paper a reliable approach for human gait symmetry assessment using a Time-of-Flight (ToF) depth camera and two mirrors. The setup formed from these devices provides a sequence of 3D point clouds that is the input of our system. A cylindrical histogram is estimated for describing the posture in each point cloud.

Skeleton-Based Abnormal Gait Detection.

Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model.