Elderly tourism management: A bibliometric approach

Elderly tourism constitutes an important sector within the sustainable development of the tourism industry, attracting an increasing body of research focused on market development. This study aims to outline the progression of elderly tourism research within the past five years (2019–2023) and determine prospective research trajectories and opportunities in the subject. Employing CiteSpace visual analysis technology, this investigation constructs knowledge graphs of authors, institutions, and countries from 332 English-language academic articles from the Web of Science and culminates a keyword co-occurrence knowledge graph. Next, cluster and burst analyses revealed the prevailing trends and focal points in elderly tourism research. The results underscore that while many researchers have been drawn to elderly tourism, the collaborative relationships between these scholars remain tenuous, resulting in the relatively disparate study and the absence of a lead author group. China dominates the field, producing a far greater quantity of studies than other nations. Hence, this study encourages different countries, higher education institutions and disciplines to strengthen cooperation in the management and development of elderly tourism, especially paying attention to the importance of elderly tourism services, quality management and technology integration for the sustainable development of elderly tourism

Oral microbiota: A new view of body health

Oral microbiota is an important part of the human microbiota. Oral microbes can be colonized into the intestine in various ways. Oral microbiota is associated with a variety of oral diseases. Recently, increasing evidence has shown that the oral microbiota is closely related to the physical state of humans, such as diabetes, obesity, and cancer. In the future, oral microbiota will become a new target for improving the physical state of humans. Keywords: Oral microbiota, Oral disease, Systematic disease

The impact of green credit on energy efficiency from a green innovation perspective: Empirical evidence from China based on a spatial Durbin model

Green credit plays a pivotal role in maintaining a balance between energy demand and the transition to low-carbon energy sources while considering energy conservation, emission reduction and the 'dual carbon' goal strategies. The SE-SBM model and the spatial Durbin model were used in this study to understand how green credit affects energy efficiency. The empirical approach was based on provincial panel data collected in China from 2005 to 2020. The results indicated that green credit significantly enhanced energy efficiency and had a substantial positive spatial spillover effect beyond the immediate region. Therefore, the enforcement of green credit policies could enhance energy efficiency within the region and concurrently encourage an improvement in energy efficiency in adjacent regions. Furthermore, the study unveiled significant regional disparities in the impact of green credit on the improvement of energy efficiency across the eastern, central and western regions. The green credit policies should be customized to align with the unique circumstances of different regions. Green innovation serves as the primary conduit through which green credit enhances energy efficiency. These insights offer a valuable reference for policymakers seeking to enhance energy efficiency via green credit policies

Social media sentiment of hydrogen fuel cell vehicles in China: Evidence from artificial intelligence algorithms

Hydrogen energy is significant in the energy consumption, especially in Hydrogen Fuel Cell Vehicles(HFCVs) market. Social media data is critical for exploring public perceptions of HFCVs. To find hot topics and understand the public sentiment of HFCVs, we employ a computational model, which combines Kmeans algorithm, Latent Dirichlet Allocation (LDA), and SnowNLP. The training data consists of 42,063 comments sourced from Bilibili-a popular Chinese social media platform. The analysis has identified 12 clusters, each with distinct topics and sentiments. The results reveal that the Chinese public generally holds a neutral stance on the hydrogen energy market, while some stakeholders maintain a positive on the technology and development of HFCVs, but some concerns about the transportation and safety of hydrogen fuel. Furthermore, this study offers suggestions for the technological, operational, and strategic advancement of HFCVs

DNA Barcoding for Efficient Species- and Pathovar-Level Identification of the Quarantine Plant Pathogen <i>Xanthomonas</i>

<div><p>Genus <i>Xanthomonas</i> comprises many economically important plant pathogens that affect a wide range of hosts. Indeed, fourteen <i>Xanthomonas</i> species/pathovars have been regarded as official quarantine bacteria for imports in China. To date, however, a rapid and accurate method capable of identifying all of the quarantine species/pathovars has yet to be developed. In this study, we therefore evaluated the capacity of DNA barcoding as a digital identification method for discriminating quarantine species/pathovars of <i>Xanthomonas</i>. For these analyses, 327 isolates, representing 45 <i>Xanthomonas</i> species/pathovars, as well as five additional species/pathovars from GenBank (50 species/pathovars total), were utilized to test the efficacy of four DNA barcode candidate genes (16S rRNA gene, <i>cpn60</i>, <i>gyrB</i>, and <i>avrBs2</i>). Of these candidate genes, <i>cpn60</i> displayed the highest rate of PCR amplification and sequencing success. The tree-building (Neighbor-joining), ‘best close match’, and barcode gap methods were subsequently employed to assess the species- and pathovar-level resolution of each gene. Notably, all isolates of each quarantine species/pathovars formed a monophyletic group in the neighbor-joining tree constructed using the <i>cpn60</i> sequences. Moreover, <i>cpn60</i> also demonstrated the most satisfactory results in both barcoding gap analysis and the ‘best close match’ test. Thus, compared with the other markers tested, <i>cpn60</i> proved to be a powerful DNA barcode, providing a reliable and effective means for the species- and pathovar-level identification of the quarantine plant pathogen <i>Xanthomonas</i>.</p></div

Neighbor-joining tree based on <i>cpn60</i>.

<p>Bootstrap values (>50%) are shown above the branches. Identical sequences are represented only once. Numbers following taxon names indicate the number of isolates. Red dots indicate quarantine <i>Xanthomonas</i> species/pathovars. Species/pathovars that were successfully identified are shown on the right.</p

Histograms of the frequencies (y-axes) of pairwise intra-species/pathovar (dark gray bars) and inter-species/pathovar (light gray bars) divergences based on the uncorrected K2P distance (x-axes) for each candidate gene.

<p>Histograms of the frequencies (y-axes) of pairwise intra-species/pathovar (dark gray bars) and inter-species/pathovar (light gray bars) divergences based on the uncorrected K2P distance (x-axes) for each candidate gene.</p

Neighbor-joining tree based on <i>gyrB</i>.

<p>Bootstrap values (>50%) are shown above the branches. Identical sequences are represented only once. Numbers following taxon names indicate the number of isolates. Red dots indicate quarantine <i>Xanthomonas</i> species/pathovars. Species/pathovars that were successfully identified are shown on the right.</p

Identification success based on “best close match” method.

<p>Identification success based on “best close match” method.</p

Neighbor-joining tree based on 16S rRNA gene.

<p>Bootstrap values (>50%) are shown above the branches. Identical sequences are represented only once. Numbers following taxon names indicate the number of isolates. Red dots indicate quarantine <i>Xanthomonas</i> species/pathovars. Species/pathovars that were successfully identified are shown on the right.</p