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Spatio-temporal data analysis is crucial in many research fields. However, modelling large-scale spatio-temporal data presents challenges such as high computational demands, complex correlation structures, and the separation of mixed sources. To address these issues, we are developing 4DModeller (fdmr), a robust and user-friendly R package designed to model spatio-temporal data within a Bayesian framework. The software package offers a comprehensive solution for visualizing, analyzing and modelling different types of spatio-temporal data in various disciplines. By incorporating Bayesian hierarchical models, "fdmr" allows for the flexible integration of prior knowledge and data uncertainty into the modelling process. By utilizing the Integrated Nested Laplace Approximations (INLA) algorithm and the stochastic partial differential equations (SPDE) method for model inference, "fdmr" significantly reduces the computational complexity of handling high-resolution, highdimensional spatio-temporal data. Furthermore, "fdmr" provides intuitive and interactive visual analytics tools that facilitate the exploration of data patterns across both space and time. This paper aims to introduce the "fdmr" package, and outline its core modelling framework through an example study on the spread of COVID-19 infection rates in England from 19 December, 2020 to 20 March, 2021.

This study combines the latest vague set similarity measurement method with the entropy weight TOPSIS method; furthermore, it applies the grey relational analysis method to establish a model for the synergistic development of supply and demand in the health industry, and it empirically analyzes the development status, synergy level, and synergistic development level of China's health industry supply and demand from 2013 to 2021. The findings reveal that: (1) China's health industry supply maintains steady growth, while demand grows rapidly. However, the overall level of supply and demand development is generally low, indicating significant potential for future development. Moreover, the development of the supply lags behind that of the demand, leading to an increasing gap year by year. (2) The level of synergy between supply and demand in China's health industry is relatively high but is decreasing year by year. Although the degree of synergistic development between supply and demand continues to increase, it remains at a low level, indicating that high coordination between supply and demand comes at the cost of a low development level. (3) There exists a significant regional imbalance in the development of China's health industry, with the overall difference showing a widening trend year by year. Regional disparities are the main source of the overall difference. [ABSTRACT FROM AUTHOR]

Microbial metabolites play an important role in regulating intestinal homeostasis and immune responses. Propofol is a common anesthetic in clinic, but it is not clear whether it affects intestinal metabolites in rats. Tail vein puncture was performed after adaptive feeding for 1 month in eight 2-month-old rats and they were given continuous intravenous infusion of propofol for 3 h. The feces of rats were divided into different groups based on time periods, with before and after anesthesia with propofol on days 1, 3 and 7 labeled as groups P, A1, A3 and A7, respectively. The effect of continuous intravenous infusion with propofol on rat fecal metabolites was determined using the non-targeted metabolomics technique gas chromatography coupled with a time-of-flight mass spectrometer analysis. The types and contents of metabolites in rat feces were changed after continuous intravenous infusion with propofol, but the changes were not statistically significant. The contents of the metabolites 3-hydroxyphenylacetic acid and palmitic acid increased from day 3 to 7, and it was shown that the two metabolites were positively correlated at a statistically significant level. Linoleic acid decreased to its lowest level on day 3, and it returned to pre-anesthesia level on day 7. At the same time, linoleic acid metabolism was a metabolic pathway that was co-enriched 7 days after infusion with propofol. Spearman correlation analysis showed that there was significant correlation between some differential metabolites and differential microorganisms. It was observed that zymosterol 1, cytosin and elaidic acid were negatively correlated with Alloprevotella in the A3 vs. P group. In the A7 vs. P group, cortexolone 3 and coprostan-3-one were positively correlated with Faecalibacterium, whilst aconitic acid was negatively correlated with it. In conclusion, the present study revealed statistically insignificant effects of continuous intravenous propofol on the intestinal metabolites in rats. [ABSTRACT FROM AUTHOR]