RESUMEN
Due to various unavoidable reasons or gross error elimination, missing data inevitably exist in global navigation satellite system (GNSS) position time series, which may result in many analysis methods not being applicable. Typically, interpolating the missing data is a crucial preprocessing step before analyzing the time series. The conventional methods for filling missing data do not consider the influence of adjacent stations. In this work, an improved Gaussian process (GP) approach is developed to fill the missing data of GNSS time series, in which the time series of adjacent stations are applied to construct impact factors, together with a comparison of the conventional GP and the commonly used cubic spline methods. For the simulation experiments, the root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (R) are adopted to evaluate the performance of the improved GP. The results show that the filled missing data of the improved GP are closer to the true values than those of the conventional GP and cubic spline methods, regardless of the missing percentages ranging from 5 to 30%, with an interval of 5%. Specifically, the mean relative RMSE and MAE improvements for the improved GP with respect to the conventional GP are 21.2%, 21.3% and 8.3% and 12.7%, 16.2% and 11.01% for the North (N), East (E) and Up (U) components, respectively. In the real experiment, eight GNSS stations are analyzed using improved GP, together with conventional GP and a cubic spline. The results indicate that the first three principal components (PCs) of the improved GP can perverse 98.3%, 99.8% and 77.0% of the total variance for the N, E and U components, respectively. This value is obviously higher than those of the conventional GP and cubic spline. Therefore, we can conclude that the improved GP can better fill in the missing data in GNSS position time series than the conventional GP and cubic spline because of the impacts of adjacent stations.
RESUMEN
BACKGROUND: Research on the gut microbiota has emerged as a new direction for understanding pathophysiologic changes in diseases associated with aging, such as sarcopenia. Several studies have shown that there are differences in the gut microbiota between individuals with sarcopenia and without sarcopenia. However, these differences are not consistent across regions and ethnic groups, and additional research is needed. METHODS: In this study, we collected fresh fecal samples from 31 Uyghur individuals with sarcopenia and 31 healthy controls. We used 16S rRNA sequencing to obtain fecal base sequences and analyzed the diversity, composition and function of the gut microbiota. RESULTS: There was no significant difference in alpha diversity between the sarcopenia group and the healthy control group (P > 0.05). There was a significant difference in beta diversity between the groups (P < 0.05). In the sarcopenia group, the abundances of Alloprevotella, un_f_Prevotellaceae, Anaerovibrio, Prevotellaceae_NK3B31_group, Mitsuokella, Prevotella and Allisonella were lower than those in the heathy control group, and the abundances of Flavobacteriales, Flavobacteriaceae, Catenibacterium, Romboutsia, Erysipelotrichaceae_UCG-003, GCA-900066575, Lachnospiraceae_FCS020_group, and un_f_Flavobacteriaceae were higher than those in the heathy control group. Linear discriminant analysis effect size (LEfSe) revealed that the microbial species in the control group that were significantly different from those in the sarcopenia group were concentrated in the genus Alloprevotella, while the species in the sarcopenia group were concentrated in the genus Catenibacterium. Functional prediction analysis revealed that D-alanine, glycine, serine, and threonine metabolism and transcription machinery, among others, were enriched in the sarcopenia group, which indicated that metabolic pathways related to amino acid metabolism and nutrient transport may be regulated to varying degrees in the pathophysiological context of sarcopenia. CONCLUSIONS: There were significant differences in the composition and function of the gut microbiota between Xinjiang Uyghur sarcopenia individuals and healthy individuals. These findings might aid in the development of probiotics or microbial-based therapies for sarcopenia in Uyhur individuals.
