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This study uses a fixed effect model to examine the impact based on a sample of non-financial A-share listed companies in the Shanghai Stock Exchange and Shenzhen Stock Exchange from 2010 to 2019. The empirical results show that regional fintech development has a significantly positive effect on enterprise innovation, while heterogeneity analysis results indicate that this effect is more significant for small and medium-sized enterprises and secondary industry fields. Further research finds that regional fintech development not only has significant spatial autocorrelation, but it also has spillover effects on enterprise innovation. Additionally, the mechanism test shows that financing constraints are part of the mediating factor between regional fintech and enterprise innovation. We conclusively present three recommendations for enriching the development of regional fintech, thus allowing for increased innovation potential and the sustainable growth of companies. [ABSTRACT FROM AUTHOR]

Background: The microbiota and metabolites in the gastrointestinal tracts of female animals at different reproductive periods are very important to the growth, development, and health of themselves and their offspring. However, the changes in the gastrointestinal microbiota and metabolites throughout reproductive period of different sheep breeds and their effects on the growth and development of offspring lambs are still unclear. Hence, this study presents an assessment of the reproductive hormone levels, immune levels, rumen microbiota, and metabolites in Hu sheep and Suffolk ewes at different reproductive periods and their effects on the growth and development of offspring lambs. Results: Hu sheep and Suffolk during non-pregnancy, pregnancy, and lactation were used as the research objects to determine reproductive and immune indexes of ewes at different periods, analyze rumen microbiome and metabolome, and track the growth performance and development of offspring lambs. The results showed that the reproductive hormone and immune levels of Hu sheep and Suffolk underwent adaptive changes across different reproductive periods. Compared with non-pregnancy, the microbial energy metabolism and lipid metabolism function decreased during Hu sheep pregnancy, and energy metabolism function decreased during lactation. In Suffolk, energy metabolism, glycan biosynthesis, and metabolism function were enhanced during pregnancy, and the metabolism of cofactors and vitamins was enhanced during lactation. Prevotella increased in Suffolk during pregnancy and lactation (P < 0.05) and was positively correlated with the birth weight and body size of the lambs (P < 0.05). Moreover, the abundances of Butyrivibrio and Rikenellaceae_RC9_gut_group during pregnancy were positively correlated with the intestinal immunity of the offspring lambs (P < 0.05), thereby regulating the intestinal immunity level of the lambs. Metabolomic analysis revealed that the protein digestion, absorption, and amino acid metabolism of Hu sheep were enhanced during pregnancy, which provided amino acids for the growth and development of pregnant ewes and fetuses and was significantly correlated with the birth weight, body size, and intestinal immunity of lambs (P < 0.05). Simultaneously, there was an increase in acetate and propionate during the pregnancy and lactation period of both Hu sheep and Suffolk, providing energy for ewes during reproductive period. Moreover, the microbiota during the lactation period was significantly correlated with the milk quality and lambs daily gain (P < 0.05). Conclusions: This study revealed the characteristic succession changes in the rumen microbiota and its metabolites at different reproductive periods in sheep breeds and their regulation of reproductive hormone and immune levels and identified their potential effects on the growth and development of offspring lambs. The findings provide valuable insights into the health and feeding management of different sheep breeds during the reproductive stage. Cnu7uEJBESQuA-vs1kGzfa Video Abstract [ABSTRACT FROM AUTHOR]

Common ZnO particles was used to improve the flame retardancy of piperazine pyrophosphate/melamine polyphosphate (PPAP/MPP) in PP composites. 0.5 wt% ZnO exhibited an exceptional synergism by analyzing LOI determination, UL-94 test, and CCT. The LOI increased from 29.9% (no ZnO) to 32.3%. The corresponding flame-retardant rating was improved from UL-94 V-2 to V-0. Additionally, ZnO significantly inhibited the formation of the smoke and CO during the combustion process. The TGA, the component and the structure of the heated FRPP and CCT residues were studied by FTIR, EDS, SEM, Raman spectra and 31P Nuclear Magnetic Resonance, revealing that PPAP/MPP was dominant in the flame retardant process by condensed phase actions. Furthermore, ZnO obviously promoted the formation of the char layer and increased its graphitization degree. Thus, the thermal stability and the strength of the intumescent char layer were improved and then to reinforce the flame retardancy of flame retardant PP (FRPP).

Short-term power load forecasting is the basis for ensuring the safe and stable operation of the power system. However, because power load forecasting is affected by weather, economy, geography, and other factors, it has strong instability and nonlinearity, making it difficult to improve the accuracy of short-term power load forecasting. To solve the above problems, a load forecasting method combining empirical modal decomposition (EMD) and long short-term memory neural network (LSTM) has been proposed. The original signal is first decomposed into a series of eigenmode functions and a residual quantity using the EMD algorithm. Subsequently, all the components are fed into the LSTM network. To further improve the load prediction accuracy, a self-attention mechanism is introduced for large component signals to further explore the internal correlation of the data, and the Sparrow Optimisation Algorithm (SSA) is used to optimize the LSTM hyperparameters. Combining EMD, LSTM, self-attention mechanism (SAM), and SSA, the EMD-SSASAM -LSTM method for short-term power load forecasting is further proposed. The results show that the coefficient of determination (R2) of the method is 0.98, the mean absolute error (MAE) is 0.013, the root mean square error (RMSE) is 0.018, and the mean absolute percentage error (MAPE) is 2.57%, which verifies that the proposed model can improve the accuracy of load forecasting, and has a certain application prospect. [ABSTRACT FROM AUTHOR]

Loss of plant diversity with increased anthropogenic nitrogen (N) deposition in grasslands has occurred globally. In most cases, competitive exclusion driven by preemption of light or space is invoked as a key mechanism. Here, we provide evidence from a 9-yr N-addition experiment for an alternative mechanism: differential sensitivity of forbs and grasses to increased soil manganese (Mn) levels. In Inner Mongolia steppes, increasing the N supply shifted plant community composition from grass-forb codominance (primarily Stipa krylovii and Artemisia frigida, respectively) to exclusive dominance by grass, with associated declines in overall species richness. Reduced abundance of forbs was linked to soil acidification that increased mobilization of soil Mn, with a 10-fold greater accumulation of Mn in forbs than in grasses. The enhanced accumulation of Mn in forbs was correlated with reduced photosynthetic rates and growth, and is consistent with the loss of forb species. Differential accumulation of Mn between forbs and grasses can be linked to fundamental differences between dicots and monocots in the biochemical pathways regulating metal transport. These findings provide a mechanistic explanation for N-induced species loss in temperate grasslands by linking metal mobilization in soil to differential metal acquisition and impacts on key functional groups in these ecosystems.

This study examines the relationship between science and technology insurance (S&T insurance) and regional innovation from a macro innovation input-output perspective. Based on provincial panel data from 2010–2019, the impact of S&T insurance on regional innovation is examined using a dynamic panel regression model. The results indicate that S&T insurance has a significant promotion effect on innovation inputs with a lagged effect but a negative effect on innovation outputs. Further, there is regional and subject heterogeneity in the role of S&T insurance. S&T insurance has a significant effect on innovation input in the central and eastern regions, but not in the western regions; S&T insurance has a significant effect on innovation in enterprises, but not on non-enterprise organisations. This study also examines whether there is a spillover effect of S&T insurance on regional innovation. The results show a spillover effect on innovation inputs but no spillover effect on innovation outputs. Finally, the authors suggest promoting the development of the S&T insurance market to improve regional innovation capacity. [ABSTRACT FROM AUTHOR]

Simple Summary: In the context of large-scale production, it is necessary to improve ewes health status and reproductive performance to promote newborns survival rate and later fattening performance. Previous studies have indicated that phenolic acids could change the host rumen microflora and inhibit pathogenic bacteria to ensure rumen health and host body health. However, there are few studies on isochlorogenic acid (ICGA) in ruminants. Therefore, based on regulating the rumen environment of breeding ewes during the whole physiological period, the experiment was conducted to study the effects of ICGA on rumen fermentation, microbial diversity and immunity of ewes at estrus, pregnancy and lactation stages. The experimental data obtained showed that adding ICGA could regulate ewes rumen fermentation mode, optimize microbial flora of different physiological stages by increasing Bacteroidota relative abundance while reducing Firmicutes relative abundance, maintain rumen microbial homeostasis at the pregnancy stage, and increase ewes blood immuneglobulin content, thereby improving ewes health. The effects of isochlorogenic acid (ICGA) on ewes rumen environment, microbial diversity, and immunity at different physiological stages (estrus, pregnancy and lactation) were studied in this experiment. Twenty healthy female Hu lambs of 1.5 months with similar body weight (17.82 ± 0.98 kg) and body condition were selected and randomly divided into two groups: the control group (CON) and the ICGA group (ICGA). The lambs of CON were fed a basal diet, while the lambs of ICGA were supplemented with 0.1% ICGA based on the basal diet. Lambs rumen fermentation characteristics, microbial diversity and immunity at estrus, pregnancy, and lactation stages were determined and analyzed, respectively. The results showed that the rumen pH in CON increased first and then decreased as lambs grew (p < 0.05). However, it showed the opposite change in ICGA. The content of ammonia nitrogen (NH3-N) showed the highest at estrus stage in both groups, but it was significantly higher in ICGA than that in CON (p < 0.05). The Acetic acid/propionic acid (A/P) ratio at estrus stage and the volatile fatty acids (VFAs) at pregnancy stage in ICGA were significantly higher than those of the CON (p < 0.05). The 16S rDNA sequencing analysis showed that the Shannon, Chao 1 and ACE indexes of the ICGA were significantly higher than those of the CON both at estrus and lactation stages (p < 0.05), while they showed higher at the pregnancy stage in CON (p > 0.05). Principal component analysis (PCA) showed that there were significant differences in rumen microorganism structure between CON and ICGA at all physiological stages (p < 0.01). At the phylum level, compared with the CON, Firmicutes relative abundance of three physiological stages decreased (p > 0.05) while Bacteroidota increased (p > 0.05). The relative abundance of Synergistota at estrus stage and Patescibacteria at the lactation stage increased significantly too (p < 0.05). At the genus level, compared with the CON, the relative abundance of Prevotella at three stages showed the highest (p > 0.05), while the relative abundance of Succiniclasticum, unclassified_Selenomonadaceae and Rikenellaceae_RC9_gut_group showed different abundances at different physiological stages in ICGA. Compared with the CON, the lambs of the ICGA showed higher blood IgG, IgM, and TNF- α contents at three physiological stages and higher IL-6 contents at pregnancy stage (p < 0.05). Conclusion: Adding ICGA could regulate ewes rumen fermentation mode at different physiological stages by increasing rumen NH3-N at estrus, VFAs at pregnancy, and the ratio of A/P at lactation. It optimizes rumen microbial flora of different physiological stages by increasing Bacteroidota relative abundance while reducing Firmicutes relative abundance, maintaining rumen microbial homeostasis at pregnant stage, increasing the number of beneficial bacteria in later lactating and ewes blood immunoglobulins content at three physiological stages. [ABSTRACT FROM AUTHOR]

Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community‐weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community‐weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community‐weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community‐weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community‐weighted trait means as well as their functional diversity across grassland ecosystems. [ABSTRACT FROM AUTHOR]

China's high-speed rail (HSR) construction provides an ideal 'quasi-natural experiment' in which regional issues are investigated. This study explores how HSR affects innovation efficiency and explores the mediating effect of urban form. Based on panel data comprising 280 cities in China from 2006 to 2016, this study uses a time-varying difference-in-differences method to analyze whether HSR affects regional innovation, and it explores the mediating effect of urban form. The results show the following. (1) HSR significantly promotes regional innovation. The parallel trend test shows that the treatment group and the control group have the same trend before HSR construction. (2) Knowledge spillovers are important manifestations through which HSR promotes regional innovation. HSR can significantly improve the level of total factor productivity and human capital. (3) Urban form mediates the impact of HSR on regional innovation significantly, which varies across the different indexes of different urban forms. [ABSTRACT FROM AUTHOR]

Improving soil fertility is one of the key approaches for ecological restoration of the wind-sand area in northwest Liaoning Province. Taking wind-sand area in northwest Liaoning Province as test object, we conducted a fertilization experiment with treatments of inorganic fertilizer (nitrogen, phosphorus and potassium fertilizers), organic fertilizer, combined application of organic and inorganic fertilizers, and organic fertilizer combined with a biologically organic matrix (γ-polyglutamic acid), and no fertilizer as control. We measured soil organic matter content and extractable cations concentrations, vegetation coverage, and biomass under different fertilization treatments and determine the suitable fertilization mode. The results showed that compared to the control, inorganic fertilizer rapidly increased vegetation coverage and biomass, but high levels of inorganic fertilizer (150 kg N ⋅ hm-2) led to soil acidification and Ca2+ leaching. Organic fertilizer increased soil organic matter content, exchangeable K+, Ca2+, and Mg2+ contents, as well as coverage and biomass vegetation, especially combined with γ-polyglutamic acid. Overall, the combination of low levels of inorganic fertilizer (50 kg N ⋅ hm-2) and moderate levels of organic fertilizer (30000 kg ⋅ hm-2) was the best fertilization practice for the rapid and stable restoration of grassland in wind-sand area. Moreover, the extra addition of γ-polyglutamic acid (60 kg ⋅ hm-2) could effectively improve soil fertility. [ABSTRACT FROM AUTHOR]

To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwestern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact. [ABSTRACT FROM AUTHOR]