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"Li, Jinlin"
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The hospitality and tourism industry in ASEAN and East Asian destinations : new growth, trends, and developments
\"This new volume addresses the growing interest to understand tourism and hospitality in Southeast and South Asia, two regions that have seen tremendous growth in international tourists in recent years. It explores the current development of hospitality and tourism industry in the regions of Hong Kong, Macao and Taiwan as well as other key countries in Southeast and South Asia. The Hospitality and Tourism Industry in ASEAN and East Asian Destinations: New Growth, Trends, and Developments provides updated findings and case studies that highlight opportunities and issues of tourism and hospitality development in ASEAN. Chapters cover such diverse topics as online marketing strategies, sustainable hospitality development, diversification efforts of the tourism industry Innovations in independent hotels, wildlife tourism in urban destinations, the Vietnamese national park system, consumers' positive and negative images of certain destinations. While academicians will benefit from the updated research findings summarized by the respected scholars, hospitality professionals will also find the book a valuable source of information as the chapters delve into the most recent topical and industry focused issues.\"-- Provided by publisher.
Book
Stabilization of ε-iron carbide as high-temperature catalyst under realistic Fischer–Tropsch synthesis conditions
The development of efficient catalysts for Fischer–Tropsch (FT) synthesis, a core reaction in the utilization of non-petroleum carbon resources to supply energy and chemicals, has attracted much recent attention. ε-Iron carbide (ε-Fe
2
C) was proposed as the most active iron phase for FT synthesis, but this phase is generally unstable under realistic FT reaction conditions (> 523 K). Here, we succeed in stabilizing pure-phase ε-Fe
2
C nanocrystals by confining them into graphene layers and obtain an iron-time yield of 1258 μmol
CO
g
Fe
−1
s
−1
under realistic FT synthesis conditions, one order of magnitude higher than that of the conventional carbon-supported Fe catalyst. The ε-Fe
2
C@graphene catalyst is stable at least for 400 h under high-temperature conditions. Density functional theory (DFT) calculations reveal the feasible formation of ε-Fe
2
C by carburization of α-Fe precursor through interfacial interactions of ε-Fe
2
C@graphene. This work provides a promising strategy to design highly active and stable Fe-based FT catalysts.
ε-Fe
2
C has been identified as the highly active phase for Fischer-Tropsch synthesis (FTS), but is stable only at low-temperature. Here, the authors show that ε-Fe
2
C phase can be stabilized even at ~ 573 K by being encapsulated inside graphene layers, and retains high activity in FTS.
Journal Article
Multi-Teacher D-S Fusion for Semi-Supervised SAR Ship Detection
Ship detection from synthetic aperture radar (SAR) imagery is crucial for various fields in real-world applications. Numerous deep learning-based detectors have been investigated for SAR ship detection, which requires a substantial amount of labeled data for training. However, SAR data annotation is time-consuming and demands specialized expertise, resulting in deep learning-based SAR ship detectors struggling due to a lack of annotations. With limited labeled data, semi-supervised learning is a popular approach for boosting detection performance by excavating valuable information from unlabeled data. In this paper, a semi-supervised SAR ship detection network is proposed, termed a Multi-Teacher Dempster-Shafer Evidence Fusion Net-work (MTDSEFN). The MTDSEFN is an enhanced framework based on the basic teacher–student skeleton frame, comprising two branches: the Teacher Group (TG) and the Agency Teacher (AT). The TG utilizes multiple teachers to generate pseudo-labels for different augmentation versions of unlabeled samples, which are then refined to obtain high-quality pseudo-labels by using Dempster-Shafer (D-S) fusion. The AT not only serves to deliver weights of its own teacher to the TG at the end of each epoch but also updates its own weights after each iteration, enabling the model to effectively learn rich information from unlabeled data. The combination of TG and AT guarantees both reliable pseudo-label generation and a comprehensive diversity of learning information from numerous unlabeled samples. Extensive experiments were performed on two public SAR ship datasets, and the results demonstrated the effectiveness and superiority of the proposed approach.
Journal Article
Is Autophagy a Friend or Foe in SARS-CoV-2 Infection?
As obligate parasites, viruses need to hijack resources from infected cells to complete their lifecycle. The interaction between the virus and host determines the viral infection process, including viral propagation and the disease’s outcome. Understanding the interaction between the virus and host factors is a basis for unraveling the intricate biological processes in the infected cells and thereby developing more efficient and targeted antivirals. Among the various fundamental virus–host interactions, autophagy plays vital and also complicated roles by directly engaging in the viral lifecycle and functioning as an anti- and/or pro-viral factor. Autophagy thus becomes a promising target against virus infection. Since the COVID-19 pandemic, there has been an accumulation of studies aiming to investigate the roles of autophagy in SARS-CoV-2 infection by using different models and from distinct angles, providing valuable information for systematically and comprehensively dissecting the interplay between autophagy and SARS-CoV-2. In this review, we summarize the advancements in the studies of the interaction between SARS-CoV-2 and autophagy, as well as detailed molecular mechanisms. We also update the current knowledge on the pharmacological strategies used to suppress SARS-CoV-2 replication through remodeling autophagy. These extensive studies on SARS-CoV-2 and autophagy can advance our understanding of virus–autophagy interaction and provide insights into developing efficient antiviral therapeutics by regulating autophagy.
Journal Article
How can green innovation promote the synergy of pollution reduction and carbon emission reduction in cities? Empirical evidence from 273 cities in China
Green innovation is the key endogenous driving force for enhancing the level of coordinated pollution reduction and carbon emission reduction governance. Based on the panel data of 273 prefecture-level and above cities in China from 2014 to 2023, this article constructs a city-level pollution reduction and carbon emission synergy index. Using a two-way fixed effects model, a mediating effect model, a threshold regression model, and a spatial Durbin model, this study systematically examines the impact of green innovation on pollution-carbon synergy and explores its underlying mechanisms. The results show that: (1) Green innovation significantly promotes the enhancement of the synergy effect of urban pollution reduction and carbon emission reduction, and the conclusion remains valid in multiple robustness tests. (2) The upgrading of industrial structure and the optimization of energy consumption structure play a significant mediating role in the process of green innovation influencing the synergistic effect of pollution reduction and carbon emission reduction. Green innovation, by promoting the high-endization of industries and the low-carbonization of energy, enhances the synergistic effect of emission reduction at a deeper level. (3) Green innovation has a significant dual threshold feature for the synergistic effect of pollution reduction and carbon emission reduction. Its promoting effect depends on the improvement of the cleanliness level of the industrial structure and energy consumption structure. (4) Green innovation has a significant spatial spillover effect. It not only enhances the collaborative governance level of local cities but also has a positive impact on surrounding cities through technology diffusion and regional linkage. Therefore, it is necessary to adhere to the governance approach of adapting measures to local conditions and advancing in phases, by improving the green innovation support system, consolidating structural basic conditions and strengthening regional coordination.
Journal Article
Optimizing Teleconsultation Scheduling with a Two-Level Approach Based on Reinforcement Learning
Using advanced communication and information technologies, teleconsultation can provide high-quality healthcare services to remote areas. To enhance service efficiency, this study develops a two-level dynamic scheduling model for teleconsultation, which prioritizes optimizing service frequency and incorporates downstream room utilization and overtime risk as considerations. The first-level model is a data-driven framework that optimizes the frequency by adjusting service start times. Based on the solutions of the first-level model, a second-level model is built to assign teleconsultation rooms to departments with demands and reduce the total overtime risk and and room opening cost. For solving, an integer programming (IP) solver is embedded in a deep reinforcement learning (DRL) approach. A presorting mechanism of interval constraints is proposed to improve the quality of solutions. For verification, actual teleconsultation data are used as samples. The experimental results demonstrate the effectiveness of the proposed two-level model, the embedded solving algorithm, and the interval constraint presorting mechanism. Compared with real schedules, the two-level model can reduce four service scheduling performance criteria, including demand average waiting time, number of services, risk of overtime, and number of rooms used. As a result, the efficiency of teleconsultation is improved to promote its development.
Journal Article
Impact of rating and praise campaigns on local government environmental governance efficiency: Evidence from the campaign of establishment of national sanitary cities in China
Ecological and environmental protection is essential to achieving sustainable and high-quality development, which highlights the important role of environmental governance. In terms of the practical actions of environmental governance, the central government in China has carried out continuous rating and praise campaigns, and local governments have actively promoted this effort. However, the related performance consequences have not been empirically investigated. We aimed to verify whether this incentive policy can improve the efficiency of environmental governance and whether this governance method has long-term effects. In addition, we sought to identify mechanisms through which the policy can improve environmental governance. We take the rating and praise campaign of the Establishment of National Sanitary Cities (EONSCs) as a quasi-natural experiment and use the panel data for 174 cities from 2004 to 2016 and the propensity score matching-difference in differences (PSM-DID) method to test the impact of rating and praise campaigns on environmental governance efficiency. EONSCs campaign can improve the efficiency of environmental governance by 0.7595 (p<0.01), which is significant at the 1% level; the effects are clearly significant during the evaluation process and the year in which cities are named National Sanitary Cities (NSCs) but decrease annually thereafter. The EONSCs campaign has a significant promoting effect on public services provision, such as public infrastructure investment, public transportation and education. (1) The rating and praise campaigns can effectively improve the efficiency of environmental governance; (2) the incentive effect is distorted and is not a long-term effect; (3) the impact of the rating and praise campaign of EONSCs on the efficiency of environmental governance is mainly realized through the provision of corresponding public services that are closely related to environmental protection. The findings of this paper provide empirical support for the effectiveness of the central government's rating and praise campaigns and could motivate local governments to actively participate in environmental governance. Moreover, the findings provide an important reference for further improving the rating and praise campaigns and the level of environmental governance.
Journal Article
Teleconsultation demand classification and service analysis
Background
To enhance teleconsultation management, demands can be classified into different patterns, and the service of each pattern demand can be improved.
Methods
For the effective teleconsultation classification, a novel ensemble hierarchical clustering method is proposed in this study. In the proposed method, individual clustering results are first obtained by different hierarchical clustering methods, and then ensembled by one-hot encoding, the calculation and division of cosine similarity, and network graph representation. In the built network graph about the high cosine similarity, the connected demand series can be categorized into one pattern. For verification, 43 teleconsultation demand series are used as sample data, and the efficiency and quality of teleconsultation services are respectively analyzed before and after the demand classification.
Results
The teleconsultation demands are classified into three categories, erratic, lumpy, and slow. Under the fixed strategies, the service analysis after demand classification reveals the deficiencies of teleconsultation services, but analysis before demand classification can’t.
Conclusion
The proposed ensemble hierarchical clustering method can effectively category teleconsultation demands, and the effective demand categorization can enhance teleconsultation management.
Journal Article
SF-1 mediates reproductive toxicity induced by Cerium oxide nanoparticles in male mice
Background
Cerium oxide nanoparticles (CeO
2
NPs) have potential application for use in biomedical and in various consumer products. However, it is largely unclear whether CeO
2
NPs have effects on male reproductive function.
Methods
In this study, male mice were examined for toxicity, if any, following chronic oral administration of CeO
2
NPs for 32 days. In each animal, epididymides were examined for sperm motility and DNA integrity. Bloods were tested for testosterone levels. Testicular tissues were collected to determine the element Ce content, the daily sperm production (DSP), marker enzymes such as ACP, G6PD, γ-GT and SDH, mRNA expression levels of steroidogenesis genes
Star, P450scc, P450c17, 3β
-
Hsd,
and
17β
-
Hsd
, as well as steroidogenic factor-1 (SF-1) gene/protein levels.
Results
The results showed that CeO
2
NPs (20 mg/kg and 40 mg/kg) increased the element Ce content in testis, the testis histopathological patterns and sperm DNA damage whereas decreased the testis weight, DSP and sperm motility. There were also remarkable reduction in testosterone levels and marker enzymes activities, down-regulated mRNA expression levels of several steroidogenesis genes such as
Star, P450scc, P450c17, 3β
-
Hsd,
and
17β
-
Hsd
, as well as altered gene and protein expressions of SF-1.
Conclusion
These results reveal the male reproductive toxicity of chronic exposure of CeO
2
NPs in mice, hinting that the utilization of CeO
2
NPs need to be carefully evaluated about their potential reproductive toxicity on the human health.
Journal Article