Search Results (4,466)

Background/Objectives: On 6 June 2023, two varicella cases were reported at a highly vaccinated elementary school in Gyeonggi Province, Republic of Korea. We investigated the outbreak to describe its transmission dynamics; quantify attack rates in school, household, and private-academy settings; and assess the impact of coordinated control measures. Methods: A case-series study included 89 teachers and students who had contact with suspected patients. Using case definitions, laboratory tests, questionnaires, and environmental assessments, we evaluated exposures and factors facilitating spread. Results: Varicella developed in 23 of 89 contacts (25.8%); laboratory confirmation was obtained in 2 (8.7% of cases). The mean incubation period was 13 days. Epidemic-curve and network analyses indicated that the outbreak began with a single index case and extended through household contacts and private educational facilities, ultimately involving multiple schools. Conclusions: Breakthrough transmission can occur even when single-dose coverage exceeds 95%, particularly as vaccine-induced immunity may wane over time. Poorly regulated extracurricular facilities, such as private academies, act as bridging hubs that amplify spread across grades and even between schools. For timely detection and control, these venues should be incorporated into routine varicella surveillance, and rapid, coordinated infection-control measures are required across all educational settings. Full article

When faced with diverse types of image tampering and image quality degradation in real-world scenarios, traditional image tampering localization methods often struggle to balance boundary accuracy and robustness. To address these issues, this paper proposes a symmetric guided dual-branch image tampering localization network—FENet (Fusion-Enhanced Network)—that integrates adaptive feature fusion and edge attention mechanisms. This method is based on a structurally symmetric dual-branch architecture, which extracts RGB semantic features and SRM noise residual information to comprehensively capture the fine-grained differences in tampered regions at the visual and statistical levels. To effectively fuse different features, this paper designs a self-calibrating fusion module (SCF), which introduces a content-aware dynamic weighting mechanism to adaptively adjust the importance of different feature branches, thereby enhancing the discriminative power and expressiveness of the fused features. Furthermore, considering that image tampering often involves abnormal changes in edge structures, we further propose an edge-aware coordinate attention mechanism (ECAM). By jointly modeling spatial position information and edge-guided information, the model is guided to focus more precisely on potential tampering boundaries, thereby enhancing its boundary detection and localization capabilities. Experiments on public datasets such as Columbia, CASIA, and NIST16 demonstrate that FENet achieves significantly better results than existing methods. We also analyze the model’s performance under various image quality conditions, such as JPEG compression and Gaussian blur, demonstrating its robustness in real-world scenarios. Experiments in Facebook, Weibo, and WeChat scenarios show that our method achieves average F1 scores that are 2.8%, 3%, and 5.6% higher than those of existing state-of-the-art methods, respectively. Full article

This study analyzes how Vietnam’s Ministry of Culture, Sports and Tourism (MoCST) communicates policy implementation in tourism governance through 35 official responses to citizen petitions, using Heidbreder’s Multilevel Policy Implementation Strategies Framework (centralization, agencification, convergence, networking). Content coding, frequency analysis, co-occurrence network, and sentiment analysis reveal a dominant centralization pattern, with MoCST maintaining strong top-down control in decision-making and resource allocation. Convergence reflects increased inter-ministerial coordination, while agencification is limited, and networking with private or civil sectors remains weak. This weak networking limits participatory decision-making and hinders the development of adaptive, community-based tourism initiatives, which are crucial for sustainable tourism governance. Positive sentiment is more associated with centralized and convergent actions, indicating institutional trust. The study extends Heidbreder’s framework to a non-Western, centralized context and calls for stronger local agency roles and inclusive networks to enhance resilience and community ownership in policy implementation. Full article

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

The remote sensing monitoring of land use changes and future scenario simulation hold crucial significance for accurately characterizing urban expansion patterns, optimizing urban land use configurations, and thereby promoting coordinated regional development. Through the integration of multi-source data, this study systematically analyzes the spatiotemporal trajectories and driving forces of land use changes in the Pearl River Delta urban agglomeration (PRD) from 1990 to 2020 and further simulates the spatial patterns of urban land use under diverse development scenarios from 2025 to 2035. The results indicate the following: (1) During 1990–2020, urban expansion in the Pearl River Delta urban agglomeration exhibited a “stepwise growth” pattern, with an annual expansion rate of 3.7%. Regional land use remained dominated by forest (accounting for over 50%), while construction land surged from 6.5% to 21.8% of total land cover. The gravity center trajectory shifted southeastward. Concurrently, cropland fragmentation has intensified, accompanied by deteriorating connectivity of ecological lands. (2) Urban expansion in the PRD arises from synergistic interactions between natural and socioeconomic drivers. The Geographically and Temporally Weighted Regression (GTWR) model revealed that natural constraints—elevation (regression coefficients ranging −0.35 to −0.05) and river network density (−0.47 to −0.15)—exhibited significant spatial heterogeneity. Socioeconomic drivers dominated by year-end paved road area (0.26–0.28) and foreign direct investment (0.03–0.11) emerged as core expansion catalysts. Geographic detector analysis demonstrated pronounced interaction effects: all factor pairs exhibited either two-factor enhancement or nonlinear enhancement effects, with interaction explanatory power surpassing individual factors. (3) Validation of the Patch-generating Land Use Simulation (PLUS) model showed high reliability (Kappa coefficient = 0.9205, overall accuracy = 95.9%). Under the Natural Development Scenario, construction land would exceed the ecological security baseline, causing 408.60 km² of ecological space loss; Under the Ecological Protection Scenario, mandatory control boundaries could reduce cropland and forest loss by 3.04%, albeit with unused land development intensity rising to 24.09%; Under the Economic Development Scenario, cross-city contiguous development zones along the Pearl River Estuary would emerge, with land development intensity peaking in Guangzhou–Foshan and Shenzhen–Dongguan border areas. This study deciphers the spatiotemporal dynamics, driving mechanisms, and scenario outcomes of urban agglomeration expansion, providing critical insights for formulating regionally differentiated policies. Full article

This study evaluates the performance of nine satellite and model-based daily surface soil moisture products, encompassing sixteen algorithm versions across mainland China to support sustainable land and water management. The assessment utilizes 2018 in situ measurements from over 2400 stations in China’s Automatic Soil Moisture Monitoring Network. All products were standardized to a 0.25° × 0.25° grid in the WGS-84 coordinate system through reprojection and resampling for consistent comparison. Daily averaged station observations were matched to product pixels using a 10 km radius buffer, with the mean station value as the reference for each time series after rigorous quality control. Results reveal distinct performance rankings, with SMAP-based products, particularly the SMAP_IB descending orbit variant, achieving the lowest unbiased root mean square deviation (ubRMSD) and highest correlation with in situ data. Blended products like ESA CCI and NOAA SMOPS, alongside reanalysis datasets such as ERA5 and MERRA2, outperformed SMOS and China’s FY3 products. The SoMo.ml product showed the broadest spatial coverage and strong temporal consistency, while FY3-based products showed limitations in spatial reliability and seasonal dynamics capture. These findings provide critical insights for selecting appropriate soil moisture datasets to enhance sustainable agricultural practices, optimize water resource allocation, monitor ecosystem resilience, and support climate adaptation strategies, therefore advancing sustainable development across diverse geographical regions in China. Full article

This study proposes a computational framework that transforms eye-tracking analysis from statistical description to cognitive structure modeling, aiming to reveal the organizational features embedded in the viewing process. Using the designers’ observation of a traditional Chinese landscape painting as an example, the study draws on the goal-oriented nature of design thinking to suggest that such visual exploration may exhibit latent structural tendencies, reflected in patterns of fixation and transition. Rather than focusing on traditional fixation hotspots, our four-dimensional framework (Region, Relation, Weight, Time) treats viewing behavior as structured cognitive networks. To operationalize this framework, we developed a data-driven computational approach that integrates fixation coordinate transformation, K-means clustering, extremum point detection, and linear interpolation. These techniques identify regions of concentrated visual attention and define their spatial boundaries, allowing for the modeling of inter-regional relationships and cognitive organization among visual areas. An adaptive buffer zone method is further employed to quantify the strength of connections between regions and to delineate potential visual nodes and transition pathways. Three design-trained participants were invited to observe the same painting while performing a think-aloud task, with one participant selected for the detailed demonstration of the analytical process. The framework’s applicability across different viewers was validated through consistent structural patterns observed across all three participants, while simultaneously revealing individual differences in their visual exploration strategies. These findings demonstrate that the proposed framework provides a replicable and generalizable method for systematically analyzing viewing behavior across individuals, enabling rapid identification of both common patterns and individual differences in visual exploration. This approach opens new possibilities for discovering structural organization within visual exploration data and analyzing goal-directed viewing behaviors. Although this study focuses on method demonstration, it proposes a preliminary hypothesis that designers’ gaze structures are significantly more clustered and hierarchically organized than those of novices, providing a foundation for future confirmatory testing. Full article

With the increasing penetration of distributed generation and the diversification of electrical equipment, distribution networks face issues like three-phase unbalance and harmonic currents, while the voltage stability and inertia of the grid-connected system also decrease. A certain amount of energy storage is needed in a Distribution Static Synchronous Compensator (DSTATCOM) to manage power quality and actively support voltage and inertia in the network. This paper first addresses the limitations of traditional $dq0$ compensation algorithms in effectively filtering out negative-sequence twice-frequency components. An improved $dq0$ compensation algorithm is proposed to reduce errors in detecting positive-sequence fundamental current under unbalanced three-phase conditions. Second, considering the impedance ratio characteristics of the distribution network, while reactive power voltage regulation is common, active power regulation is more effective in high-resistance distribution networks. A grid-forming model-based active and reactive power coordinated voltage regulation method is proposed. This method uses synchronous control to establish a virtual three-phase voltage internal electromotive force, forming a comprehensive compensation strategy that combines power quality improvement and active voltage support, exploring the potential of energy storage DSTATCOM applications in distribution networks. Finally, simulation and experimental results demonstrate the effectiveness of the proposed control method. Full article

In the last 20 years, NRTK GNSS CORS networks have been designed, developed, and employed in Sicily (Italy) for research purposes. Following a comprehensive description of the CORS networks in this region, this study aims to compare results obtained from multiple reference points with known coordinates. The analysis will not only account for the various CORS networks to which these points belong but also examine the different correction streams applied in NRTK surveys. The assumption of a normal distribution, which is often assumed for the positioning errors, is generally confirmed by applying the areal stream corrections (FKP, MAX, iMAX), but still, a multimodal distribution is evident when punctual corrections (Nearest and VRS) are applied. The representation of the results in a GIS environment allows for showing the different patterns for some differential correction streams. A statistical approach allowed confirming the trends of the different distribution frequencies of the residuals of the coordinates and quantifying separately the correlation with parameters involved in the analysis. The correlation retrieved is predominantly weak and very weak for all CORS, except for one of those analyzed, for which the correlation is moderate. The correlation became strong for the same CORS, if all parameters are included, for both planimetric and plano-altimetric components (r = 0.6 and r = 0.7, respectively). Full article

The yak (Bos grunniens) has exceptional hypoxia resilience, making it an ideal model for studying high-altitude adaptation. Here, we investigated the effects of oxygen concentration on yak cardiac fibroblast proliferation and the underlying molecular regulatory pathways using RNA sequencing (RNA-seq) and metabolic analyses. Decreased oxygen levels significantly inhibited cardiac fibroblast proliferation and activity. Intriguingly, while the mitochondrial DNA (mtDNA) content remained stable, we observed coordinated upregulation of mtDNA-encoded oxidative phosphorylation components. Live-cell metabolic assessment further demonstrated that hypoxia led to mitochondrial respiratory inhibition and enhanced glycolysis. RNA-seq analysis identified key hypoxia adaptation genes, including glycolysis regulators (e.g., HK2, TPI1), and hypoxia-inducible factor 1-alpha (HIF-1α), with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighting their involvement in metabolic regulation. The protein–protein interaction network identified three consensus hub genes across five topological algorithms (CCNA2, PLK1, and TP53) that may be involved in hypoxia adaptation. These findings highlight the importance of metabolic reprogramming underlying yak adaptation to hypoxia, providing valuable molecular insights into the mechanisms underlying high-altitude survival. Full article

Emergencies can occur unexpectedly and require immediate action, especially in aviation, where time pressure and uncertainty are high. This study focused on improving emergency evacuation in airport and aircraft scenarios using real-time decision-making support. A system based on the Asynchronous Advantage Actor–Critic (A3C) algorithm, an advanced deep reinforcement learning method, was developed to generate faster and more efficient evacuation routes compared to traditional models. The A3C model was tested in various scenarios, including different environmental conditions and numbers of agents, and its performance was compared with the Deep Q-Network (DQN) algorithm. The results showed that A3C achieved evacuations 43.86% faster on average and converged in fewer episodes (100 vs. 250 for DQN). In dynamic environments with moving threats, A3C also outperformed DQN in maintaining agent safety and adapting routes in real time. As the number of agents increased, A3C maintained high levels of efficiency and robustness. These findings demonstrate A3C’s strong potential to enhance evacuation planning through improved speed, adaptability, and scalability. The study concludes by highlighting the practical benefits of applying such models in real-world emergency response systems, including significantly faster evacuation times, real-time adaptability to evolving threats, and enhanced scalability for managing large crowds in high-density environments including airport terminals. The A3C-based model offers a cost-effective alternative to full-scale evacuation drills by enabling virtual scenario testing, supports proactive safety planning through predictive modeling, and contributes to the development of intelligent decision-support tools that improve coordination and reduce response time during emergencies. Full article

National parks serve as critical spatial units for conserving ecological baselines, maintaining genetic diversity, and delivering essential ecosystem services. However, accelerating socio-economic development has increasingly intensified the conflict between ecological protection and transportation infrastructure. Ecologically sustainable transportation planning is, therefore, essential to mitigate habitat fragmentation, facilitate species migration, and conserve biodiversity. This study examines the Giant Panda National Park and its buffer zone, focusing on six mammal species: giant panda, Sichuan snub-nosed monkey, leopard cat, forest musk deer, rock squirrel, and Sichuan takin. By integrating Maxent ecological niche modeling with circuit theory, it identified ecological source areas and potential corridors, and employed a two-step screening approach to design species-specific wildlife crossings. In total, 39 vegetated overpasses were proposed to serve all target species; 34 underpasses were integrated using existing bridge and culvert structures to minimize construction costs; and 27 canopy bridges, incorporating suspension cables and elevated pathways, were designed to connect forest canopies for arboreal species. This study established a multi-species and multi-scale conservation framework, providing both theoretical insights and practical strategies for ecologically integrated transportation planning in national parks, contributing to the synergy between biodiversity conservation and sustainable development goals. Full article

Wind power is a core component of a clean energy system. The efficiency of a wind power system evolves through coordinated interactions. These interactions occur among three regional subsystems: resource subsystem, technology subsystem, and economy subsystem. To reveal the operational mechanisms of its internal subsystems, this study analyzes the comprehensive efficiency of the wind power system in China from 2010 to 2022. The two-stage EBM model, the Tobit regression model and the feedforward neural network model are employed in combination. The results show that: (1) The comprehensive efficiency of the wind power system has gradually improved, but shows spatiotemporal variations due to uneven subsystem coordination. (2) The improvement of efficiency is characterized by stages. The optimization of technology subsystems drives the development stage, while economic scaling dominates the operation stage (though operation and maintenance technologies remain deficient). (3) The correlation between development and operation stages is suboptimal, and the coordination of subsystems remains weak. (4) Technology innovation and electricity demand boost comprehensive efficiency, while human resources hinder it. Extreme weather exerts either a contributing or an interfering effect on the system. (5) Future projections show continued efficiency growth. The study concludes with cross-system coordination strategies to enhance the contribution of wind power in clean energy. Full article

Sperm freezability exhibits marked individual variability, yet the mechanisms remain unclear. Using bulls as the experimental model, we integrated proteomic (sperm) and metabolomic (seminal plasma) analyses of high-freezability (HF) and control (CF) bulls to identify key biomarkers associated with sperm freezability. Post-thaw motility and membrane integrity were significantly higher in HF bulls (p < 0.05). Sperm proteome analysis revealed upregulated antioxidant proteins (PRDX2, GSTM4), heat shock proteins (HSP70, HSP90), and key enzymes in arginine and proline metabolism (PRODH, LAP3). Seminal plasma metabolomics revealed elevated spermine in HF bulls. Meanwhile, we found that spermine abundance was positively correlated with post-thaw motility, as well as with the expression levels of both PRODH and LAP3 (r > 0.6, p < 0.05). Functional validation demonstrated that 200 μM spermine supplementation in cryopreservation extenders enhanced post-thaw motility, kinematic parameters (VAP, VSL, VCL), membrane integrity, and acrosome integrity (p < 0.05). Concurrently, spermine enhanced antioxidant enzyme (SOD, CAT, GSH-Px) activity and reduced ROS and MDA levels (p < 0.05). Our study reveals a spermine-driven antioxidant network coordinating sperm–seminal plasma synergy during cryopreservation, offering novel strategies for semen freezing optimization. Full article