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Abstract This paper focuses on the optimal power and gas flow (OPGF) in the electricity-gas coupled networks (EGCN) and proposes two mixed-integer linear programming (MILP) formulations via piecewise linear approximations (PWL) for solving the OPGF problem. The direct current power flow formulation is employed to model the electricity network. The special order sets (SOSs) and a two-stage PWL strategy combining incremental model and SOSs are developed to address the non-convex Weymouth gas flow equations. The two MILP formulations obtained are tractable and identify the global solutions. Numerical results investigate the performances of proposed two MILP formulations. [ABSTRACT FROM AUTHOR]

Huangjiu brewing workshop is a small ecosystem with complex microbial community growth. This micro ecosystem is the main provider of microorganisms in the process of Huangjiu fermentation. Its existence may greatly affect the quality and flavor of Huangjiu. Environmental microbial communities of the same brewing workshop in different historical periods were collected. Full-length High-throughput sequencing and Source Tracker were used to study the correlation between brewing raw materials, fermented mash and brewing environment, and to explore the involvement of environmental microorganisms in the fermentation process. The resident functional fungi in fermented Huangjiu mash were the main components of the fungal community detected in the environment. The wheat koji, tool and interior environment contributed greatly to the source of fermented fungi in Huangjiu. Compared with the bacterial community, the environmental origin of the fungal community in fermented mash was clearer. For bacteria, the increased contribution of community aggregation was attributed to the role of deterministic processes, and community structure became more stable, showing its unique role in fermentation. This study could be implemented in a more abundant natural fermentation environment, which was of great significance to control the natural fermentation process of Huangjiu. • Analyzing the microbial community structure in fermentation environment of Huangjiu. • The bacterial community was stable and fungal community was in a dynamic equilibrium. • The fungi in the workshop environment mainly came from wheat koji and mash. [ABSTRACT FROM AUTHOR]

Online education has become the new normal for higher education. Online Learning Readiness (OLR) is a prerequisite for learners' effective learning and academic achievement. However, at present, China still lacks an instrument to effectively measure nursing students' online learning readiness under the new information technology innovation. This study determined the validity and reliability of the Chinese version of Online. Learning Readiness Scale (OLRS) developed by Tang and the online learning readiness (OLR) of nursing students in China. A descriptive cross-sectional study was used. A public medical university in southeast China. This study included 465, nursing students from freshmen to seniors who attended at least one online course with the final assessment completed. This study adopted OLRS (Tang), which was translated with the Brislin model (translation, back translation, and integration) following the authorization of the developer. Expert analysis was taken for content validity. Confirmatory Factor Analysis (CFA) was used to test the structural validity. As to the convergence validity, this study employed the Pearson correlation coefficient between OLRS (Tang) and OLRS (Hung). Besides, Cronbach's alpha coefficient was taken to evaluate the internal consistency. The instrument showed satisfactory content validity (I-CVI = 0.80–1.00, S-CVI = 0.97). According to CFA, the structure with five factors (technology readiness, learner control, online communication self-efficacy, self-directed learning, motivation for learning) showed acceptable model fit (χ2/df 3.46, CFI 0.90, IFI 0.90, RMSEA 0.07 and SRMR 0.03). Convergence validity (r = 0.67, P < 0.01), and internal consistency (Cronbach's alpha = 0.95). In addition, the OLR of Chinese nursing students is moderate. The Chinese version of OLRS (Tang) proved to be an effective, reliable and relatively concise measurement instrument. • The Chinese version of OLRS showed to be a valid and reliable instrument with a five-factor structure. • Undergraduate nursing students demonstrate moderate online learning readiness. • The learning motivation subscale scored the highest, and the technology readiness subscale scored the lowest. [ABSTRACT FROM AUTHOR]

Background: Non-coding RNA is a key epigenetic regulation factor during skeletal muscle development and postnatal growth, and miR-542-3p was reported to be conserved and highly expressed in the skeletal muscle among different species. However, its exact functions in the proliferation of muscle stem cells and myogenesis remain to be determined. Methods: Transfection of proliferative and differentiated C2C12 cells used miR-542-3p mimic and inhibitor. RT-qPCR, EdU staining, immunofluorescence staining, cell counting kit 8 (CCK-8), and Western blot were used to evaluate the proliferation and myogenic differentiation caused by miR-542-3p. The dual luciferase reporter analysis and rescued experiment of the target gene were used to reveal the molecular mechanism. Results: The data shows overexpression of miR-542-3p downregulation of mRNA and protein levels of proliferation marker genes, reduction of EdU+ cells, and cellular vitality. Additionally, knocking it down promoted the aforementioned phenotypes. For differentiation, the miR-542-3p gain-of-function reduced both mRNA and protein levels of myogenic genes, including MYOG, MYOD1, et al. Furthermore, immunofluorescence staining immunized by MYHC antibody showed that the myotube number, fluorescence intensity, differentiation index, and myotube fusion index all decreased in the miR-542-3p mimic group, compared with the control group. Conversely, these phenotypes exhibited an increased trend in the miR-542-3p inhibitor group. Mechanistically, phosphatase and tensin homolog (Pten) was identified as the bona fide target gene of miR-542-3p by dual luciferase reporter gene assay, si-Pten combined with miR-542-3p inhibitor treatments totally rescued the promotion of proliferation by loss-function of miR-542-3p. Conclusions: This study indicates that miR-542-3p inhibits the proliferation and differentiation of myoblast and Pten is a dependent target gene of miR-542-3p in myoblast proliferation, but not in differentiation. [ABSTRACT FROM AUTHOR]

This study explores the application of the fully convolutional network (FCN) algorithm to the field of meteorology, specifically for the short-term nowcasting of severe convective weather events such as hail, convective wind gust (CG), thunderstorms, and short-term heavy rain (STHR) in Gansu. The training data come from the European Center for Medium-Range Weather Forecasts (ECMWF) and real-time ground observations. The performance of the proposed FCN model, based on 2017 to 2021 training datasets, demonstrated a high prediction accuracy, with an overall error rate of 16.6%. Furthermore, the model exhibited an error rate of 18.6% across both severe and non-severe weather conditions when tested against the 2022 dataset. Operational deployment in 2023 yielded an average critical success index (CSI) of 24.3%, a probability of detection (POD) of 62.6%, and a false alarm ratio (FAR) of 71.2% for these convective events. It is noteworthy that the predicting performance for STHR was particularly effective with the highest POD and CSI, as well as the lowest FAR. CG and hail predictions had comparable CSI and FAR scores, although the POD for CG surpassed that for hail. The FCN model's optimal performances in terms of hail prediction occurred at the 4th, 8th, and 10th forecast hours, while for CG, the 6th hour was most accurate, and for STHR, the 2nd and 4th hours were most effective. These findings underscore the FCN model's ideal suitability for short-term forecasting of severe convective weather, presenting extensive prospects for the automation of meteorological operations in the future. [ABSTRACT FROM AUTHOR]