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. Hence, they found solace in excessive watching of television and movies, which could lead to post-series depression. The purpose of this study is to investigate the relationship between life satisfaction (LS), post-series depression (PSD), and positive mental health (PMH) and inquire about the mediation effect of satisfaction of life and PSD. A total of 2,572 participants who were voluntarily recruited from various media platforms completed self-report questionnaires, including the Satisfaction with life scale, Post-series depression scale, and Positive Mental Health Scale. This study was assessed using the PLS-SEM approach. The findings of this research discovered (i) a significantly positive effect of LS on PMH; (ii) a significantly negative effect of PSD on PMH; (iii) a significantly negative effect of LS on PSD, and (iv) a significant indirect effect of LS on PMH through PSD. The study provided additional evidence to the relationship between life satisfaction and PMH of individuals. Besides, the negative effects of PSD, which is a non-clinical term for feeling down that frequently appears after individuals finish their much-loved film and TV series, on individuals' PMH is proved, especially in the COVID-19 pandemic context in which Vietnamese people must remain in their current location.

Mediation Effects of Premarital Sexual Permissiveness on the Relationship Between Expectations for Marriage and Marital Intention of Vietnamese Undergraduate Students.

Purpose: The purpose of this study was to investigate the direct and indirect effects of expectations for marital relationships and premarital sexual permissiveness on intent to marry of Vietnamese emerging adults. Patients and Methods: Our cross-sectional study was focused on emerging adults including 344 participants, undergraduate students from universities in Viet Nam. This study was assessed by using the PLS-SEM approach. Results: The main findings demonstrated that (i) sexual orientation have a significant effect on marital intention; (ii) individuals' expectations for marital relationship have a direct effect on marital intention; and (iii) premarital sexuality permissiveness mediates the relationship between expectations for marital relationship and marital intention. Conclusion: Our results contribute important documents and clearer understanding of emerging adults' expectations and requirements in a relationship for the marriage decision-making process.

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. Its architecture is a combination of: 1) an encoder extracting motion-texture coherence from each video frame and 2) two decoders that separately reconstruct the input as well as predict its typical motion from the estimated coherence. We also introduce an encoding block, which is specifically designed for the task of anomaly detection. The optimization is performed on only data of normal events, and the network is expected to determine the ones that are unusual, i.e., have not been seen before. According to the experiments on eight benchmark datasets of different environments with various anomalous events, the performance of our network is competitive or outperforms current state-of-the-art approaches.

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

The extract from Cnidium officinale 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 SiO2 and SiO2 was performed to isolate the major metabolites from the active fraction. The chemical structures were resolved on the basis of spectroscopic data, including NMR, IR, MS, and circular dichroism (CD) data. The isolated phthalide glycosides were assessed for their recovery effect on damaged otic hair cells in neomycin-treated zebrafish. Three new phthalide glycosides were isolated, and their chemical structures, including stereochemical characteristics, were determined. Two glycosides (0.1 µM) showed a recovery effect (p < 0.01) on otic hair cells in zebrafish affected by neomycin ototoxicity. Repeated column chromatography led to the isolation of three new phthalide glycosides, named ligusticosides C (1), D (2), and E (3). Ligusticoside C and ligusticoside E recovered damaged otic hair cells in zebrafish.

Aurones and Flavonols from Coreopsis lanceolata 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 Coreopsis lanceolata flowers (CLFs) contained high flavonoid structure content; (2) Methods: CLFs were extracted in aqueous methanol (MeOH:H2O = 4:1) and fractionated into acetic ester (EtOAc), normal butanol (n-BuOH), and H2O 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 (1), leptosin (2), isoquercetin (3), and astragalin (4), respectively. This is the first report for isolation of 2-4 from CLFs. High-performance liquid chromatography (HPLC) analysis determined the content levels of compounds 1-4 in the MeOH extract to be 2.8 ± 0.3 mg/g (1), 17.9 ± 0.9 mg/g (2), 3.0 ± 0.2 mg/g (3), and 10.9 ± 0.9 mg/g (4), respectively. All isolated compounds showed radical scavenging activities and recovery activities in Caco-2, RAW264.7, PC-12, and HepG2 cells against reactive oxygen species. MeOH extract, EtOAc fraction, and 1-3 suppressed NO formation in LPS-stimulated RAW 264.7 cells and decreased iNOS and COX-2 expression. Furthermore, all compounds recovered the pancreatic islets damaged by alloxan treatment in zebrafish; (4) Conclusions: The outcome proposes 1-4 to serve as components of CLFs in standardizing anti-oxidant, pro-inflammatory inhibition, and potential anti-diabetic agents.

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. Experiments on the whole body, as well as the lower limbs, were also considered to assess the usefulness of upper body information in this task. The potential of our method was demonstrated with a dataset of 97,200 depth maps of nine different walking gaits. An ROC analysis for abnormal gait detection gave the best result ( AUC = 0.958 ) compared with other related studies. The experimental results provided by our method confirm the contribution of upper body in gait analysis as well as the reliability of approximating average gait symmetry index without explicitly considering individual gait cycles for asymmetry detection.

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. The sequence of such histograms is then separated into two sequences of sub-histograms representing two half-bodies. A cross-correlation technique is finally applied to provide values describing gait symmetry indices. The evaluation was performed on 9 different gait types to demonstrate the ability of our approach in assessing gait symmetry. A comparison between our system and related methods, that employ different input data types, is also provided.

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. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%.