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E-governance is capable of driving the transition of government from an administrative power allocation of public resources to a citizen-service-oriented governance model. However, during this transformation, various governmental bodies often face the challenge of "data silos" caused by factors such as cross-regional, cross-business, and cross-departmental operations. Without altering the existing information platforms, transparent access technology serves as a key solution for data access within egovernance systems. It enables convenient access to information resources stored in different mediums and formats, facilitating the sharing and consolidation of information and data within and between governmental departments, thereby addressing the issue of "data silos" and enhancing the comprehensive service capabilities of e-governance. This paper firstly provides an overview of the concept, levels, characteristics, and application scenarios of transparent access to government big data. Secondly, it conducts a comprehensive comparative analysis of transparent access technologies in the context of cloud computing and big data. Lastly, based on the requirements of various transparent access technologies and the application of transparent access to government big data, this paper proposes a visionary framework for transparent access to government big data based on cross-domain semantics and channel coupling. This framework includes modules for cross-domain semantic interoperability, coupling of heterogeneous information channels based on knowledge graph, and tracing of multi-source heterogeneous data, aiming to provide innovative solutions for achieving transparent access to government big data.

Abstract Background The gut microbiota of the giant panda (Ailuropoda melanoleuca), a global symbol of conservation, are believed to be involved in the host’s dietary switch to a fibrous bamboo diet. However, their exact roles are still largely unknown. Results In this study, we first comprehensively analyzed a large number of gut metagenomes giant pandas (n = 322), including 98 pandas sequenced in this study with deep sequencing (Illumina) and third-generation sequencing (nanopore). We reconstructed 408 metagenome-assembled genomes (MAGs), and 148 of which (36.27%) were near complete. The most abundant MAG was classified as Streptococcus alactolyticus. A pairwise comparison of the metagenomes and meta-transcriptomes in 14 feces revealed genes involved in carbohydrate metabolism were lower, but those involved in protein metabolism were greater in abundance and expression in giant pandas compared to those in herbivores and omnivores. Of note, S. alactolyticus was positively correlated to the KEGG modules of essential amino-acid biosynthesis. After being isolated from pandas and gavaged to mice, S. alactolyticus significantly increased the relative abundance of essential amino acids in mice jejunum. Conclusions The study highlights the unique protein metabolic profiles in the giant panda’s gut microbiome. The findings suggest that S. alactolyticus is an important player in the gut microbiota that contributes to the giant panda’s dietary adaptation by more involvement in protein rather than carbohydrate metabolism. Video Abstract

High-fiber, low-cost agricultural byproducts offer a sustainable alternative for mitigating the competition for crops between humans and livestock. Pigs predominantly utilize dietary fibers through the process of microbial fermentation within the gut. This study explored the gut microbiota and the capacity for carbohydrate degradation in 30 individual Lantang pigs, a breed indigenous to China. Through metagenomic analysis, a total of 671 metagenome-assembled genomes (MAGs) were assembled and assigned into 14 bacterial and 1 archaeal phylum, including 97 species from uncultured microbes. The phylum with the highest abundance were identified as Bacillota_A, Bacteroidota, and Bacillota. Remarkably, the investigation revealed nearly 10,000 genes implicated in the degradation of carbohydrates, with a pronounced prevalence within five principal bacterial genera: Prevotella, Cryptobacteroides, Gemmiger, Vescimonas, and Faecousia. Additionally, 87 distinct types of carbohydrate-degrading enzymes were exclusively identified within the gut microbiota of the Lantang pig. These insights not only enhance our understanding of the microbial diversity specific to native Chinese pig breeds but also augment the body of research regarding porcine fiber degradation capabilities. The implications of this study are twofold: it provides strategic directions for optimizing feed efficiency and reducing breeding costs, and it furnishes an expanded gene pool for the microbial synthesis of industrial enzymes in the future.

The gastrointestinal microbiota of swine harbors an essential but often overlooked component: the gut archaea. These enigmatic microorganisms play pivotal roles in swine growth, health, and yield quality. Recent insights indicate that the diversity of gut archaea is influenced by various factors including breed, age, and diet. Such factors orchestrate the metabolic interactions within the porcine gastrointestinal environment. Through symbiotic relationships with bacteria, these archaea modulate the host’s energy metabolism and digestive processes. Contemporary research elucidates a strong association between the abundance of these archaea and economically significant traits in swine. This review elucidates the multifaceted roles of gut archaea in swine and underscores the imperative for strategic interventions to modulate their population and functionality. By exploring the probiotic potential of gut archaea, we envisage novel avenues to enhance swine growth, health, and product excellence. By spotlighting this crucial, yet under-investigated, facet of the swine gut microbiome, we aim to galvanize further scientific exploration into harnessing their myriad benefits.

Measurement(s) train operation data of China high-speed railway network • locations of railway stations • weather and temperature and wind power Technology Type(s) web scraping with python • Geographic Information System Factor Type(s) high-speed train departure delay time • high-speed train arrival delay time • various external factors affecting train operation • bad weather exposure time of railway stations • railway station community size Sample Characteristic - Organism high-speed train Sample Characteristic - Environment railway system Sample Characteristic - Location China

Archaea are considered an essential group of gut microorganisms in both humans and animals. However, they have been neglected in previous studies, especially those involving non-ruminants. In this study, we re-analyzed published metagenomic and metatranscriptomic data sequenced from matched samples to explore the composition and the expression activity of gut archaea in ruminants (cattle and sheep) and monogastric animals (pig and chicken). Our results showed that the alpha and beta diversity of each host species, especially cattle and chickens, calculated from metagenomic and metatranscriptomic data were significantly different, suggesting that metatranscriptomic data better represent the functional status of archaea. We detected that the relative abundance of 17 (cattle), 7 (sheep), 20 (pig), and 2 (chicken) archaeal species were identified in the top 100 archaeal taxa when analyzing the metagenomic datasets, and these species were classified as the “active archaeal species” for each host species by comparison with corresponding metatranscriptomic data. For example, The expressive abundance in metatranscriptomic dataset of Methanosphaera cuniculi and Methanosphaera stadtmanae were 30- and 27-fold higher than that in metagenomic abundance, indicating their potentially important function in the pig gut. Here we aim to show the potential importance of archaea in the livestock digestive tract and encourage future research in this area, especially on the gut archaea of monogastric animals.

In humans and animals, probiotics are widely accepted as crucial for host health and growth. The investigation of the probiotic colonization and expression of probiotics in the host is beneficial for proper usage of probiotics and isolation of indigenous probiotics. In this study, we analyzed commonly used probiotic strains in the intestines/rumen of humans and animals by analyzing metagenomic and paired meta-transcriptomic data from the gut or rumen microbiome of humans (n = 13), pigs (n = 6), chickens (n = 6), cattle (n = 14), sheep (n = 10), and mice (n = 8). First, we generated an expression profile based on 192 selected representative probiotic strains from a published database. A total of 58 probiotic strains were not detected in any samples, while 3 strains were presented and expressed in all individuals. Overall, the probiotic expression of probiotics as detected by meta-transcriptome was significantly higher than the relative abundance of probiotic as detected by metagenomics in cattle, sheep, mice, and humans; however, this difference was not significant in pigs and chickens. In total, 17 (cattle), 21 (sheep), 22 (pig), 14 (chicken), 13 (mouse), and 3 (human) probiotic strains were identified as probiotic strains with significantly higher expression levels [Fold Change (FC) ≥ 2, False Discovery Rate (FDR) ≤ 0.05]. Among them, Clostridium butyricum TOA was found to be significantly expressed in the rumen or gut of all host species. In addition, network analysis based on the expression of probiotics as detected by meta-transcriptomics revealed that several probiotic strains were significantly negatively linked with Salmonella spp., Mycoplasma spp., and Escherichia coli. The results in this study provide a useful reference for developing indigenous probiotics.

With the increasing traffic of train communication network (TCN), real-time Ethernet becomes the development trend. However, Train Control and Management System (TCMS) is inevitably faced with more security threats than before because of the openness of Ethernet communication protocol. It is necessary to introduce effective security mechanism into TCN. Therefore, we propose a train real-time Ethernet anomaly detection system (TREADS). TREADS introduces a multiple streams clustering algorithm to realize anomaly detection, which considers the correlation between the data dimensions and adopts the decay window to pay more attention to the recent data. In the experiment, the reliability of TREADS is tested based on the TRDP data set collected from the real network environment, and the models of anomaly detection algorithms are established for evaluation. Experimental results show that TREADS can provide a high reliability guarantee, besides, the algorithm can detect and analyze network anomalies more efficiently and accurately.

Archaea are considered a “keystone” of the gut microbiome and are linked with the host’s energy harvest and health. Although a few studies have investigated the gut archaea in pigs, especially piglets, little is known about the effects of weaning on archaeal structure and function. In this study, we explored the effects of weaning on the longitudinal changes of archaeal composition, diversity, and functional potential in pigs overtime by re-analyzing a recently published metagenomic dataset that included 176 fecal samples collected from commercial pigs on days 7, 14, 21, 28, 35, 70, and 140 after birth. Overall, the richness and diversity of archaeal species showed an increasing trend, and weaning significantly affected the richness of archaeal species. Methanobrevibacter A smithii significantly decreased and was replaced by Methanobrevibacter A sp900769095 within 2 weeks after weaning. For the functional potential, the richness of KEGG KOs increased over time. LEfSe analysis identified 18 KOs, including for example, ko04623 (cytosolic DNA-sensing pathway), ko00500 (starch and sucrose metabolism), and so on, significantly enriched in the weaning pigs, suggesting the involvement of archaea in the piglets’ adaptation to the new diet after weaning. Correlation analysis based on Random Forest regression and Pearson correlation showed that archaeal species richness was significantly associated with pig bodyweight on both days 70 and 140. Methanobrevibacter A sp900769095 (R = 0.405, p = 0.040) and Methanobrevibacter A smithii (R = 0.535, p = 0.004) were positively linked with pigs’ bodyweight on days 70 and 140, respectively. Our results revealed the dynamic changes of archaeal diversity and functions and demonstrated the effects of weaning on the gut archaea of pigs, suggesting archaea might play essential roles in swine nutrition, metabolism, and growth performance, especially during the critical weaning process.

Train station delay prediction is always one of the core research issues in high-speed railway dispatching. Reliable prediction of station delay can help dispatchers to accurately estimate the train operation status and make reasonable dispatching decisions to improve the operation and service quality of rail transit. The delay of one station is affected by many factors, such as spatiotemporal factor, speed limitation or suspension caused by strong wind or bad weather, and high passenger flow caused by major holiday. But previous studies have not fully combined the spatiotemporal characteristics of station delay and the impact of external factors. This paper makes good use of the train operation data, proposes the multiattention mechanism to capture the spatiotemporal characteristics of train operation data and process the external factors, and establishes a Multiattention Train Station Delay Graph Convolution Network (MATGCN) model to predict the train delay at high-speed railway stations, so as to provide references for train dispatching and emergency plan. This paper uses real train operation data coming from China high-speed railway network to prove that our model is superior to ANN, SVR, LSTM, RF, and TSTGCN models in the prediction effect of MAE, RMSE, and MAPE.

Archaea are an essential class of gut microorganisms in humans and animals. Despite the substantial progress in gut microbiome research in the last decade, most studies have focused on bacteria, and little is known about archaea in mammals. In this study, we investigated the composition, diversity, and functional potential of gut archaeal communities in pigs by re-analyzing a published metagenomic dataset including a total of 276 fecal samples from three countries: China (n = 76), Denmark (n = 100), and France (n = 100). For alpha diversity (Shannon Index) of the archaeal communities, Chinese pigs were less diverse than Danish and French pigs (p < 0.001). Consistently, Chinese pigs also possessed different archaeal community structures from the other two groups based on the Bray–Curtis distance matrix. Methanobrevibacter was the most dominant archaeal genus in Chinese pigs (44.94%) and French pigs (15.41%), while Candidatus methanomethylophilus was the most predominant in Danish pigs (15.71%). At the species level, the relative abundance of Candidatus methanomethylophilus alvus, Natrialbaceae archaeon XQ INN 246, and Methanobrevibacter gottschalkii were greatest in Danish, French, and Chinese pigs with a relative abundance of 14.32, 11.67, and 16.28%, respectively. In terms of metabolic potential, the top three pathways in the archaeal communities included the MetaCyc pathway related to the biosynthesis of L-valine, L-isoleucine, and isobutanol. Interestingly, the pathway related to hydrogen consumption (METHANOGENESIS-PWY) was only observed in archaeal reads, while the pathways participating in hydrogen production (FERMENTATION-PWY and PWY4LZ-257) were only detected in bacterial reads. Archaeal communities also possessed CAZyme gene families, with the top five being AA3, GH43, GT2, AA6, and CE9. In terms of antibiotic resistance genes (ARGs), the class of multidrug resistance was the most abundant ARG, accounting for 87.41% of archaeal ARG hits. Our study reveals the diverse composition and metabolic functions of archaea in pigs, suggesting that archaea might play important roles in swine nutrition and metabolism.