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This study aims to explore the relationships among leisure, heritage, and identity through the case study of Malaysian Chinese 24 Festive Drums Performance. Semi-structured interviews were conducted with 10 respondents who were members of the Chinese diaspora from Malaysia currently studying in China and practising 24 Festive Drums as their leisure activity. The findings showed that the three components are interrelated: (a) as identity carrier, heritage confirmed identity, while identity helped to spread the heritage; (b) identity served as a motivation for leisure, which in turn increased leisure participation and strengthened identity; (c) heritage was promoted as leisure practice, which further developed as serious leisure. This study has theoretical contributions in developing a triangular model of interrelationships between leisure, heritage, and identity. Furthermore, practical implications were discussed on demonstrating the potential of the role of leisure in heritage promotion and identity construction. [ABSTRACT FROM AUTHOR]

Background: In recent years, the physical fitness situation of college students is worrying in China. Exercise motivation is of great importance for the physical activity and physical fitness. However, existing studies have paid limited attention to the specific effect between exercise motivation, physical activity and physical fitness, and even less to the different genders and exercise motivation dimensions. This study aimed to investigate the promoting effect of sport motivation on physical fitness with different gender and dimension in college students. Methods: Physical fitness levels of 2544 college students in Wuhan and Jingzhou city were measured. Exercise motivation and physical activity was assessed using the Chinese version of the motives for physical activities measure-revised scale and the physical activity survey scale, respectively. Correlation analysis and structural equation model were used to explore the relationship between exercise motivation, physical activity and physical fitness. Bootstrap method was used to test the mediating effect. Multilevel regression analysis was used to examine the effects of different dimensions of exercise motivation on PF. Results: The exercise motivation of college students was directly related to physical fitness (effect value: 0.307) or indirectly related through the mediating effect of physical activity (effect value: 0.092). The mediation effect percentage of physical activity on exercise motivation and physical fitness in male (51.20%) was greater than female (27.18%), and the standardized regression coefficient of the health dimension to PF was β = 0.151, P < 0.001, and the competence dimension to PF was β = 0.189, P < 0.001. Conclusions: The exercise motivation of college students can directly influence PF or indirectly influence PF through the mediating effect of PA. The promoting effect of exercise motivation and PA on PF in college students is related to gender and dimensions of exercise motivation. Therefore, we can improve physical fitness levels of college students by promoting their exercise motivation (especially for health motivation and competence motivation) and increasing their participation in physical activity. This study provides new strategies for improving physical fitness in college students. [ABSTRACT FROM AUTHOR]

In this study, a coal-fired power plant with an integrated S-CO2 cycle is proposed to improve the system operational flexibility. To optimize the performance, a control strategy of variable load regulation is proposed. First, a dynamic mathematical model of the system is established based on the conservation of mass and energy principles, and then, dynamic verification of the model is carried out. In order to evaluate the performance of the proposed system, an exergy analysis is performed on the S-CO2 cycle, indicating that the exergy loss rate of the heater in the cycle is the highest. Finally, the dynamic performance of the system is simulated, and the dynamic response of the power generation load is analyzed. In addition, the system is evaluated based on the performance indicator of the flexibility of the power generation. It was found that the proposed system in this paper has a large load ramp rate which can quickly follow the load response. Meanwhile, compared with load downregulation, the system has greater potential for load upregulation. [ABSTRACT FROM AUTHOR]

Leaf numbers are vital in estimating the yield of crops. Traditional manual leaf-counting is tedious, costly, and an enormous job. Recent convolutional neural network-based approaches achieve promising results for rosette plants. However, there is a lack of effective solutions to tackle leaf counting for monocot plants, such as sorghum and maize. The existing approaches often require substantial training datasets and annotations, thus incurring significant overheads for labeling. Moreover, these approaches can easily fail when leaf structures are occluded in images. To address these issues, we present a new deep neural network-based method that does not require any effort to label leaf structures explicitly and achieves superior performance even with severe leaf occlusions in images. Our method extracts leaf skeletons to gain more topological information and applies augmentation to enhance structural variety in the original images. Then, we feed the combination of original images, derived skeletons, and augmentations into a regression model, transferred from Inception-Resnet-V2, for leaf-counting. We find that leaf tips are important in our regression model through an input modification method and a Grad-CAM method. The superiority of the proposed method is validated via comparison with the existing approaches conducted on a similar dataset. The results show that our method does not only improve the accuracy of leaf-counting, with overlaps and occlusions, but also lower the training cost, with fewer annotations compared to the previous state-of-the-art approaches.The robustness of the proposed method against the noise effect is also verified by removing the environmental noises during the image preprocessing and reducing the effect of the noises introduced by skeletonization, with satisfactory outcomes. [ABSTRACT FROM AUTHOR]

The key difference between visible light communication (VLC) and radio frequency (RF) communication is the former's line-of-sight (LOS) transmission nature, and hence a relay node has to be adopted for VLC to extend its coverage. Physical-layer network coding (PNC) has the advantage of doubling the throughput of a two-way relay network (TWRN), where two end nodes exchange information via the help of a relay, compared with the conventional store-and-forward routing strategy. Although PNC has been studied for VLC in the literature, the state-of-the-art schemes are highly inefficient, requiring tight phase synchronization between the two end nodes, and hence difficult to realize. This paper proposes the application of a deep neural network (DNN) to a PNC VLC system, named DP-VLC, that enables misaligned phases and can deal with the light channel gains and noises in a satisfactory manner without introducing additional computation complexities. We implement DP-VLC using the universal software radio peripheral (USRP) software radio platform and a self-developed VLC optical front-end using commercial off-the-shelf (COTS) light-emitting diodes (LEDs) and photo-diodes (PDs). We find that irregular constellations generated by DP-PNC can be transmitted and recovered in a 1.5 m VLC link effectively. Experimental results show that our DP-PNC prototype performs better than conventional PNC VLC system when the signal-interference-to-noise ratio (SINR) of received optical signals is larger than 13.63 dB and can achieve a throughput of up to 77.38 Mbps in a 20 MHz channel under PNC scheme when the SINR is 22.86 dB. More importantly, we find that DP-VLC performs even better than fixed-constellation PNC system in the saturated SINR regime (e.g., 20–25 dB) where non-linear effects may happen compared with moderate SINR regimes (e.g., 10–20 dB), showing its adaptability to unpredictable impairments in optical links. Our first attempt at realizing DNN-based optical PNC in a TWRN has paved the way for future PNC-enhanced VLC systems. [ABSTRACT FROM AUTHOR]

In this study, active packaging films were developed by incorporating nano TiO2 and pomegranate peel extract (PPE) into high-amylose corn starch (HCS)/konjac glucomannan (KG) matrix for the first time. The aim of present work was to investigate the influence of nano TiO2 and PPE on physicochemical and functional properties of HCS/KG-based films. The films were characterized by XRD, FT-IR and SEM, and the tensile, antibacterial and antioxidant properties were evaluated. The results showed that the crystallinity of the composite films was increased and the microstructure was more uniform and dense after adding TiO2 and PPE, and the intermolecular hydrogen bonds were formed between TiO2, PPE, and film matrix. Incorporation of TiO2 and PPE significantly improved tensile properties and decreased water solubility and water vapor permeability of the composite films (p < 0.05). HCS/KG films incorporated with TiO2 and PPE presented remarkable antibacterial activity against Escherichia coli and Staphylococcus aureus, and exhibited strong antioxidant activity due to the polyphenol compounds in PPE. All films properties not only changed with the content of TiO2 and PPE, but also improved synergistically when they were added together. The developed composite films were used as coating for the preservation of Agaricus bisporus, and the weight, firmness and total soluble solids of A. bisporus were significantly maintained and browning was effectively inhibited during storage. Therefore, HCS/KG composite film/coating containing TiO2 and PPE has great potential as an attractive commercialization technology to ensure the quality and extend the shelf life of foods. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to investigate the prevalence of Internet addiction (IA) and explore its related factors among undergraduates during widespread online learning in China. Design and Methods: The online survey was conducted in April 2020. The Young diagnostic questionnaire and academic burnout scale were respectively used to measure IA and academic burnout. Findings: A total of 28.4% of 7562 participants developed IA, which correlated with academic burnout. Additionally, positive attitude and practice towards COVID‐19 and exercise were protective factors of it. Practice Implications: IA was associated with academic burnout, and better cognition of COVID‐19 and positive lifestyles might reduce its risk. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is associated with altered gut microbiota. However, there has been little consensus on the altered bacterial species and studies have had small sample sizes. We aimed to identify the taxonomic composition and evaluate the changes in the fecal microbiota in Chinese children with ASD by using a relatively large sample size. We conducted a case–control study of 101 children with ASD and 103 healthy controls in China. Demographic information and fecal samples were collected, and the V3‐V4 hypervariable regions of the bacterial 16S ribosomal RNA (rRNA) gene were sequenced. The alpha and beta diversities between the two groups were significantly different. After correcting for multiple comparisons, at the phylum level the relative abundances of Actinobacteria and Proteobacteria in the case group were significantly higher than those in the control group. The relative abundance of the Escherichia‐Shigella genus in the case group was significantly higher than that of the control group, and the relative abundance of Blautia and unclassified_f__Lachnospiraceae in the control group were higher than that of the case group. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States analysis showed that children with ASD may have disturbed functional pathways, such as amino acid metabolism, cofactor and vitamin metabolism, and the AMP‐activated protein kinase signaling pathway. This study revealed the characteristics of the intestinal flora of Chinese children with ASD and provided further evidence of gut microbial dysbiosis in ASD. Lay Summary: This study characterized the gut microbiota composition of 101 children with ASD and 103 healthy controls in China. The altered gut microbiota may contribute significantly to the risk of ASD, including significant increases in the relative abundances of Actinobacteria, Proteobacteria and Escherichia‐Shigella and significant decrease of Blautia and unclassified_f__Lachnospiraceae. This study provided further evidence of gut microbial dysbiosis in ASD. [ABSTRACT FROM AUTHOR]

Background: The long-term mental health effects of coronavirus disease 2019 (COVID-19) in children are rarely reported. We aimed to investigate the progression of depressive and anxiety symptoms among a cohort of children in the initial epicenter of COVID-19 in China. Methods: Two waves of surveys were conducted in the same two primary schools in Wuhan and Huangshi, Hubei province: Wave 1 from 28 February to 5 March, 2020 (children had been confined to home for 30–40 days) and Wave 2 from 27 November to 9 December, 2020 (schools had reopened for nearly 3 months). Depressive and anxiety symptoms were estimated using the Children's Depression Inventory – Short Form (CDI-S) and the Screen for Child Anxiety Related Emotional Disorders (SCARED), respectively. ΔCDI-S and ΔSCARED scores between Wave 2 and Wave 1 were calculated and further categorized into tertiles. Multivariable linear regression and multinomial logistic regression models were then applied. Results: A total of 1,224 children completed both surveys. The prevalence of mental health outcomes at Wave 2 increased significantly compared to Wave 1, specifically depressive symptoms (age-standardized prevalence rates: 37.5 vs. 21.8%) and anxiety symptoms (age-standardized prevalence rates: 24.0 vs. 19.6%). Higher ΔSCARED scores were observed in females and children in Wuhan, and children with experience of neglect had higher ΔCDI-S (β = 1.12; 95% CI = 0.67–1.58) and ΔSCARED (β = 6.46; 95% CI = 4.73–8.19) scores compared with those without experience of neglect. When the Δ scores were further categorized into tertiles, similar results were found. Conclusions: The prevalence of depressive and anxiety symptoms after schools resumed was increased compared with that during the home quarantine period, even though the COVID-19 pandemic was under control. Females and children in Wuhan, and also children with experience of neglect were at increased risk of mental health disorders. [ABSTRACT FROM AUTHOR]

Objectives: Dendrobium officinale polysaccharide (DOP) is the main active ingredient in a valuable traditional Chinese medicine, which exerts several pharmacological activities including hepatoprotection and hypoglycemic effects. However, the effects of DOP on obesity-associated insulin resistance (IR) and lipid metabolism remain unknown. This study aimed to investigate the role of DOP in IR and abnormal lipid metabolism in obese mice. Methods: IR models were established using 3T3-L1 adipocytes, C2C12 myocytes, and primary cultured hepatocytes exposed to palmitate acid. After treatment with DOP, insulin-stimulated glucose uptake, glucose release, and AKT phosphorylation was detected. Fasting blood glucose, fasting serum insulin, the glucose tolerance test (GTT), and the insulin tolerance test (ITT) were measured to evaluate IR of obese mice. Lipid analysis was conducted to evaluate the effects of DOP on lipid metabolism in obese mice. Results: In vitro , DOP treatment ameliorated palmitic acid-induced IR in adipocytes, myocytes, and hepatocytes. DOP regulated cellular insulin sensitivity via the peroxisome proliferator-activated receptor-γ (PPAR-γ). Furthermore, administration of DOP significantly reduced the IR and visceral adipose tissue (VAT) inflammation of diet-induced obese (DIO) and the genetically-induced obesity mice (ob/ob) mouse models. In addition, DOP treatment attenuated the high-fat diet (HFD)-induced liver lipid accumulation by reducing liver triglycerides (TG), plasma free fatty acid (FFA), serum cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels, while increasing HDL-C levels. Conclusion: DOP could improve obesity-associated IR and abnormal lipid metabolism through its activities on PPAR-γ, and may serve as a potential therapeutic agent for obesity-associated insulin resistance and lipid metabolism disorder. [ABSTRACT FROM AUTHOR]

Although recent genome‐wide association studies have identified risk loci that strongly associates with autism spectrum disorder (ASD), how to pinpoint the causal genes remains a challenge. We aimed to pinpoint the potential causal genes and explore the possible susceptibility and mechanism. A convergent functional genomics (CFG) method was used to prioritize the candidate genes by combining lines of evidence, including Sherlock analysis, spatio‐temporal expression patterns, expression analysis, protein–protein interactions, co‐expression and association with brain structure. A higher score in the CFG approach suggested that more evidence supported this gene as an ASD risk gene. We screened genes with higher CFG scores for candidate functional single nucleotide polymorphisms (SNPs). A genotyping experiment (602 ASD children and 604 healthy sex‐matched children) and the dual‐luciferase reporter gene assay were followed to validate the effects of SNPs. We identified three genes (MAPT, ZNF285, and TIGD5) as candidate causal genes using the CFG approach. The genotyping experiment showed that TIGD5 rs75547282 was associated with an increased risk of ASD under the dominant model (OR = 1.37, 95% CI = 1.09–1.72, P = 0.006) though the statistical power was limited (5.2%). The T allele of rs75547282 activated the expression of TIGD5 compared with the C allele in the dual‐luciferase reporter assay. Our study indicates that such comprehensive integrative analyses may be an effective way to explore promising ASD susceptibility variants and needs to be further investigated in future research. Genotyping experiments should, however, be based on a larger population sample to increase statistical power. Lay Summary: We set out to pinpoint the potential causal genes of ASD and explore the possible susceptibility and mechanism by combining lines of evidence from different analyses. Our results show that TIGD5 rs75547282 is associated with the risk of ASD in the Han Chinese population. In addition, a similar framework to seek promising ASD risk variants could be further investigated in future research Autism Res 2021, 14: 631–644. © 2021 International Society for Autism Research and Wiley Periodicals LLC [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Ki-67 is one of the most important biomarkers of breast cancer traditionally measured invasively via immunohistochemistry. In this study, deep learning based radiomics models were established for preoperative prediction of Ki-67 status using multiparametric magnetic resonance imaging (mp-MRI).Materials and Methods: Total of 328 eligible patients were retrospectively reviewed [training dataset (n = 230) and a temporal validation dataset (n = 98)]. Deep learning imaging features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (T1+C). Transfer learning techniques constructed four feature sets based on the individual three MR sequences and their combination (i.e., mp-MRI). Multilayer perceptron classifiers were trained for final prediction of Ki-67 status. Mann-Whitney U test compared the predictive performance of individual models.Results: The area under curve (AUC) of models based on T2WI,T1+C,DWI and mp-MRI were 0.727, 0.873, 0.674, and 0.888 in the training dataset, respectively, and 0.706, 0.829, 0.643, and 0.875 in the validation dataset, respectively. The predictive performance of mp-MRI classification model in the AUC value was significantly better than that of the individual sequence model (all p< 0.01).Conclusion: In clinical practice, a noninvasive approach to improve the performance of radiomics in preoperative prediction of Ki-67 status can be provided by extracting breast cancer specific structural and functional features from mp-MRI images obtained from conventional scanning sequences using the advanced deep learning methods. This could further personalize medicine and computer aided diagnosis. [ABSTRACT FROM AUTHOR]

Myelodysplastic syndromes (MDSs) are a group of heterogeneous hematopoietic stem/progenitor cells clonal diseases, characteristic features with myeloid dysplasia, leading to abnormality of neutrophils. Recent studied have showed that neutrophils act not only as professional killers, but also as regulators of innate and adaptive immune in infection and inflammatory condition. The CD54highCD181low neutrophils are a kind of reverse-transmigrated neutrophils characterized proinflammatory phenotype. We investigated the frequency and functional properties of circulating CD54highCD181low neutrophils in patients with untreated MDS. Frequency of CD54highCD181low neutrophils was significantly increased in MDS patients and related to the severity of the disease. Furthermore, CD54highCD181low neutrophils suppressed CD8+ T cells functions in vitro. CD54highCD181low neutrophils lead to upregulation of PD1 on CD8+ T cells. Higher CD54highCD181low neutrophils were related to poor prognosis and more infections. The frequency of CD54highCD181low neutrophils decreased in high risk MDS patients who had response after treatment with decitabine. Overall, we identified CD54highCD181low neutrophils expanded in MDS. The exact mechanisms of increased CD54highCD181low neutrophils and its effect on immune function remain to be elucidated. [ABSTRACT FROM AUTHOR]

Background Depressive symptoms and anxiety symptoms of adolescents not only affect youth but also have wide-ranging impacts on the health of adults. The study was carried out to determine the epidemiological characteristics of depressive symptoms and anxiety symptoms and the associations between the two and health-risk behaviors in Chinese adolescents. Methods Participants were recruited from the junior and senior high schools in China. Data were collected by self-designed questionnaires. The questionnaires included questions about demographic characteristics, depressive symptom scales, anxiety symptom scales and nine categories of health-risk behaviors. Descriptive analysis and binary logistic regression were performed by SPSS 21.0 software. Results There were 4.4% of the participants with depressive symptoms. Approximately 32.0% of the participants had anxiety symptoms. Girls and general senior school students were risk factors for depressive symptoms and anxiety symptoms. Multiple health-risk behaviors were associated with depressive symptoms and anxiety symptoms in Chinese adolescents. Conclusion Depressive symptoms and anxiety symptoms were prevalent in Chinese adolescents. Their distribution was affected by certain health-risk behaviors. Multiple health-risk behaviors were associated with depressive symptoms and anxiety symptoms in Chinese adolescents. [ABSTRACT FROM AUTHOR]

The study on developmental dyslexia (DD) has fairly matured in the past decades, even when there is a lack of a standardized and convenient instrument for dyslexia in the Chinese population. The purpose of this study was to assess the reliability and validity of the Dyslexia Checklist for Chinese Children (DCCC), which was administered to Chinese students in primary school. A total of 545 students from grades 2 through 6 were recruited in Wuhan to participate in this study. We used confirmatory factor analysis (CFA) to evaluate the structure validity of the DCCC. Concurrent validity was determined via correlations between the DCCC and the verbal comprehension index (VCI), and Chinese achievement. The reliability of the DCCC was assessed via test-retest reliability and internal consistency. The CFA suggested that the first order model with eight factors and 55 items fit the data well (RMSEA = 0.057, CFI = 0.930, and TLI = 0.925). The DCCC was negatively associated with VCI (r = −0.218) and Chinese achievement (r = −0.372). The test-retest reliability of the DCCC was 0.734, and the internal consistency of all subscales was above 0.752. The DCCC thus proved to have adequate validity and reliability to screen Chinese dyslexia among students in grades 2 through 6. [ABSTRACT FROM AUTHOR]