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The outbreak of COVID-19 has led to a global health crisis and caused huge emotional swings. However, the positive emotional expressions, like self-confidence, optimism, and praise, that appear in Chinese social networks are rarely explored by researchers. This study aims to analyze the characteristics of netizens' positive energy expressions and the impact of node events on public emotional expression during the COVID-19 pandemic. First, a total of 6,525,249 Chinese texts posted by Sina Weibo users were randomly selected through textual data cleaning and word segmentation for corpus construction. A fine-grained sentiment lexicon that contained POSITIVE ENERGY was built using Word2Vec technology; this lexicon was later used to conduct sentiment category analysis on original posts. Next, through manual labeling and multi-classification machine learning model construction, four mainstream machine learning algorithms were selected to train the emotional intensity model. Finally, the lexicon and optimized emotional intensity model were used to analyze the emotional expressions of Chinese netizens. The results show that POSITIVE ENERGY expression accounted for 40.97% during the COVID-19 pandemic. Over the course of time, POSITIVE ENERGY emotions were displayed at the highest levels and SURPRISES the lowest. The analysis results of the node events showed after the outbreak was confirmed officially, the expressions of POSITIVE ENERGY and FEAR increased simultaneously. After the initial victory in pandemic prevention and control, the expression of POSITIVE ENERGY and SAD reached a peak, while the increase of SAD was the most prominent. The fine-grained sentiment lexicon, which includes a POSITIVE ENERGY category, demonstrated reliable algorithm performance and can be used for sentiment classification of Chinese Internet context. We also found many POSITIVE ENERGY expressions in Chinese online social platforms which are proven to be significantly affected by nod events of different nature., Author(s): Wenhao Pan [sup.1] , Yingying Han [sup.1] , Jinjin Li [sup.2] , Emily Zhang [sup.3] , Bikai He [sup.4] Author Affiliations: (1) https://ror.org/0530pts50, grid.79703.3a, 0000 0004 1764 3838, School [...]

With the development of the gear transmission system towards complexity, multiple transmission types and high reliability, it becomes more and more important to assign the reliability of the gear transmission system quickly and accurately. In this study, aiming at the problems of incomplete consideration factors, inconsistent range of changes in different allocation methods for the same parameter, and inconvenient digital software development in existing reliability allocation methods, an improved advisory group on reliability of electronic equipment (AGREE) allocation method is proposed, the scoring allocation method is extended, and the digital characteristics of reliability allocation method are discussed. The basic reliability model and task reliability model of the complex gear transmission system are established, and the traversal algorithm of the automatic reliability model generation is studied. A digital platform for rapid reliability allocation of fixed axle gear train, planetary gear train and hybrid gear train is developed. Four independent modules, namely input module, calculation module, result display module and output module, are designed. The accuracy of the calculation results of the software is verified by comparing with the results of examples. The parametric modeling and the automatic generation of the example report for the reliability allocation of the gear transmission system are realized, and the accuracy and efficiency of the reliability allocation model are raised.

We experimentally demonstrate the tuning of accidental bound states in the continuum (A-BICs) in silicon nanodisk arrays. The A-BIC emerges of the destructive interference of multipoles, which are the dominating out-of-plane electric dipole and in-plane magnetic dipole, and weak electric quadrupole and magnetic quadrupole. We further show that the spectral and angular position of the A-BIC can be conveniently tuned by varying the nanodisk size or the lattice period. Remarkably, the angular position can be tuned even to 0°, suggesting an interesting transition of the A-BIC from an off-Γ-BIC to an at-Γ-BIC. Our work provides a new strategy for light trapping with high quality factors, and the obtained tunable A-BICs can find potential applications in low-threshold lasing, enhanced nonlinear optics, and optical sensing.

Maintenance of undifferentiated, long-lived, and often quiescent stem cells in the basal compartment is important for homeostasis and regeneration of multiple epithelial tissues, but the molecular mechanisms that coordinately control basal cell fate and stem cell quiescence are elusive. Here, we report an epithelium-intrinsic requirement for Zeb1, a core transcriptional inducer of epithelial-to-mesenchymal transition, for mammary epithelial ductal side branching and for basal cell regenerative capacity. Our findings uncover an evolutionarily conserved role of Zeb1 in promoting basal cell fate over luminal differentiation. We show that Zeb1 loss results in increased basal cell proliferation at the expense of quiescence and self-renewal. Moreover, Zeb1 cooperates with YAP to activate Axin2 expression, and inhibition of Wnt signaling partially restores stem cell function to Zeb1-deficient basal cells. Thus, Zeb1 is a transcriptional regulator that maintains both basal cell fate and stem cell quiescence, and it functions in part through suppressing Wnt signaling.

Breast cancer is a heterogenous disease that can be classified into multiple subtypes including the most aggressive basal-like and triple-negative subtypes. Understanding the heterogeneity within the normal mammary basal epithelial cells holds the key to inform us about basal-like cancer cell differentiation dynamics as well as potential cells of origin. Although it is known that the mammary basal compartment contains small pools of stem cells that fuel normal tissue morphogenesis and regeneration, a comprehensive yet focused analysis of the transcriptional makeup of the basal cells is lacking. We used single-cell RNA-sequencing and multiplexed RNA in-situ hybridization to characterize mammary basal cell heterogeneity. We used bioinformatic and computational pipelines to characterize the molecular features as well as predict differentiation dynamics and cell-cell communications of the newly identified basal cell states. We used genetic cell labeling to map the in vivo fates of cells in one of these states. We identified four major distinct transcriptional states within the mammary basal cells that exhibit gene expression signatures suggestive of different functional activity and metabolic preference. Our in vivo labeling and ex vivo organoid culture data suggest that one of these states, marked by Egr2 expression, represents a dynamic transcriptional state that all basal cells transit through during pubertal mammary morphogenesis. Our study provides a systematic approach to understanding the molecular heterogeneity of mammary basal cells and identifies previously unknown dynamics of basal cell transcriptional states.

Background and objectives: The role of N-methyl-D-aspartate receptor 2B (GRIN2B) single nucleotide polymorphisms (SNPs) in influencing the risk and progression of Parkinson's disease (PD) is still unclear. This study aimed to assess the impact of GRIN2B genotype status on PD susceptibility and symptom progression. Methods: We enrolled 165 individuals with sporadic PD and 154 healthy controls, all of whom had comprehensive clinical data available at the start and during follow-up. We used chi-squared (χ2) analysis to compare the allele and genotype frequency distributions between the patient and control groups. Linear mixed-effect models were employed to investigate the link between the GRIN2B genotype and the progression of motor and cognitive symptoms. Results: The prevalence of the GG + GT genotype and G allele was higher in patients compared to controls (p = 0.032 and p = 0.001, respectively). Subgroup analysis revealed that the GG + GT genotype and G allele were significantly more frequently observed in late-onset PD (LOPD) patients compared to early-onset PD (EOPD) patients (p = 0.014 and p = 0.035, respectively). Notably, individuals with the GG + GT genotype exhibited an estimated annual progression rate of 6.10 points on the Unified Parkinson's Disease Rating Scale (UPDRS), which is significantly higher than that of the TT genotype carriers. Furthermore, the GG + GT carriers showed a markedly rapid progression in rigidity. In addition, the GG + GT carriers demonstrated significantly faster progression rates in rigidity (1.83 points/year) and axial impairment (1.2 points/year) compared to the TT carriers. Notably, the GG genotype carriers exhibited a more rapid decline in recall function. Conclusion: The GRIN2B rs219882 G allele is associated with increased PD susceptibility, particularly in LOPD. The carriers of the GG + GT genotype exhibited more rapid motor symptom progression, with a pronounced impact on rigidity and axial impairment. [ABSTRACT FROM AUTHOR]