Pectin methylesterase (PME) plays a vital role in the growth and development of plants. Their genes can be classified into two types, with Type-1 having an extra domain, PMEI. PME genes in foxtail millet (Setaria italica L.) have not been identified, and their sequence features and evolution have not been explored. Here, we identified 41 foxtail millet PME genes. Decoding the pro-region, containing the PMEI domain, revealed its more active nature than the DNA encoding PME domain, easier to be lost to produce Type-2 PME genes. We inferred that the active nature of the pro-region could be related to its harbouring more repetitive DNA sequences. Further, we revealed that though whole-genome duplication and tandem duplication contributed to producing new copies of PME genes, phylogenetic analysis provided clear evidence of ever-shrinking gene family size in foxtail millet and the other grasses in the past 100 million years. Phylogenetic analysis also supports the existence of two gene groups, Group I and Group II, with genes in Group II being more conservative. Our research contributes to understanding how DNA sequence structure affects the functional innovation and evolution of PME genes.

The purpose of this study is to study the spread of COVID-19, establish a predictive model, and provide guidance for its prevention and control. Considering the high complexity of epidemic data, we adopted an ARIMA-LSTM combined model to describe and predict future transmission. A new method of the ARIMA-LSTM model paralleling by weight of regression coefficient was proposed. Then, we used the ARIMA-LSTM model paralleling by weight of regression coefficient, ARIMA model, and ARIMA-LSTM series model to predict the epidemic data in China, and we found that the ARIMA-LSTM model paralleling by weight of regression coefficient had the best prediction accuracy. In the ARIMA-LSTM model paralleling by weight of regression coefficient, MSE = 4049.913, RMSE = 63.639, MAPE = 0.205, R2 = 0.837, MAE = 44.320. In order to verify the effectiveness of the ARIMA-LSTM model paralleling by weight of regression coefficient, we compared the ARIMA-LSTM model paralleling by weight of regression coefficient with the SVR model and found that ARIMA-LSTM model paralleling by weight of regression coefficient has better prediction accuracy. It was further verified with the epidemic data of India and found that the prediction accuracy of the ARIMA-LSTM model paralleling by weight of regression coefficient was still higher than that of the SVR model. In the ARIMA-LSTM model paralleling by weight of regression coefficient, MSE = 744,904.6, RMSE = 863.079, MAPE = 0.107, R2 = 0.983, MAE = 580.348. Finally, we used the ARIMA-LSTM model paralleling by weight of regression coefficient to predict the future epidemic situation in China. We found that in the next 60 days, the epidemic situation in China will become a steady downward trend.

At present, the problem of an aging population in China is severe. The integration of existing healthcare services with elderly care services is inefficient and cannot meet the needs of the elderly. As such, China urgently needs the concerted efforts of various social forces to cope with the increasingly serious problem of aging. In accordance with Andersen’s behavioral model, a survey was conducted in Tangshan City among seniors 60 years of age and older. Using logistic regression models, decision tree models, and random forest models, we examined the factors impacting senior people’s desire to choose the integrated medical care and nursing care model. The results of the three models displayed that the elderly’s propensity to choose the combined medical care and nursing care model is significantly influenced by the amount of insurance, life care needs, and healthcare needs. Moreover, the study found that the willingness of the elderly in Tangshan to improve the combined medical and nursing care service system is low. The government should appeal to the community to participate in multiple developments to improve the integrated medical and nursing service system.

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The effect of the concentration and chain length of the copolymer AB with sequence length τ = 8 on the interfacial properties of the ternary mixtures A10/AB/B10 are investigated by the dissipative particle dynamics (DPD) simulations. It is found that: i) As the copolymer concentration varies from 0.05 to 0.15, increasing the copolymer enrichment at the center of the interface enlarges the interface width ω and reduces the interfacial tension. However, as the concentration of the sequence copolymers further increases to 0.2, because the interface has formed micelles and the micellization could lower the efficiency of copolymers as a compatibilizer, the interfacial tension exhibits a slightly increase; ii) elevating the copolymer chain length, the copolymer volumes vary from a cylinder shape to a pancake shape. The blends of the copolymer with chain length Ncp = 24 exhibit a wider interfacial width w and a lower interfacial tension γ, which indicates that the sequenced copolymer Ncp = 24 exhibits a better performance as the compatibilizers. This study illustrates the correlations between the reduction in interfacial tension produced by the sequence copolymers and their molecular parameters, which guide a rational design of an efficient compatibilizer.