Search Results (2,783)

This study investigates the spatial patterns and drivers of carbon emissions across China’s three major urban agglomerations—Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)—from 2011 to 2020. A sequential analytical framework was employed to examine emission inequality, spatial dependence, dynamic transitions, and multi-scale drivers. Specifically, the Gini and Theil indices were used to quantify and decompose regional disparities. Spatial clustering patterns and heterogeneity were then identified through global and local Moran’s I analysis. Following this, spatial Markov chains modeled state transitions and neighborhood spillover effects. Finally, the Spatial Durbin Model (SDM) was applied to distinguish between the direct and indirect effects of key socioeconomic drivers. The findings reveal that disparities in emissions are largely driven by factors within each region. In BTH, heavy industrial lock-in accounts for 47.1% of the within-group inequality. By contrast, the YRD and PRD show noticeable convergence, achieved through industrial synergy and technological restructuring, respectively. The mechanisms of spatial spillover also differ across regions. In the YRD, emissions exhibit strong clustering tied to geographic proximity, with Moran’s I consistently above 0.6. In BTH, policy linkages play a more central role in shaping emission patterns. Meanwhile, in the PRD, widespread technological diffusion weakens the conventional distance-decay effect. The influence of key drivers varies notably among the urban agglomerations. Economic growth has the strongest scale effect in the PRD, reflected by a coefficient of 0.556. Industrial transformation significantly lowers emissions in the YRD, with a coefficient of −0.115. Technology investment reduces emissions in BTH (−0.124) and the PRD (−0.076), but is associated with a slight rebound in the YRD (0.037). Overall, these results highlight the persistent path dependence and distinct spatial interdependencies of carbon emissions in each region. This underscores the need for tailored mitigation strategies that are coordinated across administrative boundaries. Full article

This study focuses on the calibration and verification of a large-scale coupled numerical model to simulate the complex hydrodynamic–wave–sediment transport processes in the coastal and estuarine regions of the Mekong River Delta (MRD), Vietnam. Using the MIKE 21/3 modeling system, the research integrates Hydrodynamics (HD), Spectral Wave (SW), and Mud Transport (MT) modules across a computational domain of 270 × 300 km. The models were rigorously tested using field measurement data from three distinct periods: May 2004 (dry season calibration), September 2017 (first verification), and June 2024 (second verification). The results from the hydrodynamic model demonstrated high accuracy in predicting water levels, with the average Root Mean Square Error (RMSE) values ranging between 4.4% and 5.8%. The wave spectral model showed reliable performance, with the average RMSE values for wave height ranging from 15.1% to 18.0%. Furthermore, the Mud Transport module successfully captured suspended sediment concentrations (SSC), yielding average RMSE values between 26.0% and 32.1% after the fine-tuning of site-specific parameters such as critical shear stress for erosion and deposition. The study highlights the critical importance of utilizing site-specific sedimentological parameters to accurately predict morphological changes in highly dynamic estuarine environments. This validated model provides a robust tool for assessing coastal erosion and developing protection measures in regions that are increasingly vulnerable to climate change and human activities. Full article

Background and Rationale: Tinospora crispa (L.) Hook.f. & Thomson (T. crispa) is a climbing medicinal plant with long-standing ethnopharmacological use, particularly in inflammatory and hepatic disorders and cancer-related conditions. There is a knowledge gap regarding how wild versus cultivated ecotypes differ in chemotype, bioactivity, and safety, and how this might support or refine traditional use. Study Objectives: This study aimed to compare wild and cultivated ecotypes of T. crispa from the Nile Delta (Egypt) in terms of quantitative and qualitative phytochemical profiles; selected in vitro biological activities (especially antioxidant and cytotoxic actions); genetic markers potentially associated with metabolic variation; and short-term oral safety in an animal model. Core Methodology: Standardized extraction of plant material from wild and cultivated ecotypes. Determination of total phenolics, total flavonoids, and major phytochemical classes (alkaloids, tannins, terpenoids). Metabolomic characterization using UHPLC-ESI-QTOF-MS, supported by NMR, to confirm key compounds such as berberine, palmatine, chlorogenic acid, rutin, and borapetoside C. In vitro bioassays including: Antioxidant activity (e.g., radical-scavenging assay with EC₅₀ determination). Cytotoxicity against human cancer cell lines, with emphasis on HepG2 hepatoma cells and calculation of IC₅₀ values. Targeted genetic analysis to detect single-nucleotide polymorphisms (SNPs) in the gen1 locus that differentiate ecotypes. A 14-day oral toxicity study in rats, assessing liver and kidney function markers and performing histopathology of liver and kidney tissues. Principal Results: The wild ecotype showed a 43–65% increase in total flavonoid and polyphenol content compared with the cultivated ecotype, as well as substantially higher levels of key alkaloids, particularly berberine (around 12.5 ± 0.8 mg/g), along with elevated chlorogenic acid and borapetoside C. UHPLC-MS and NMR analyses confirmed the identity of the main bioactive constituents and defined a distinct chemical fingerprint for the wild chemotype. Bioassays demonstrated stronger antioxidant activity of the wild extract than the cultivated one and selective cytotoxicity of the wild extract against HepG2 cells (IC₅₀ ≈ 85 µg/mL), being clearly more potent than extracts from cultivated plants. Genetic profiling detected a C → T SNP within the gen1 region that differentiates the wild ecotype and may be linked to altered biosynthetic regulation. The 14-day oral toxicity study (up to 600 mg/kg) revealed no evidence of hepatic or renal toxicity, with biochemical markers remaining within physiological limits and normal liver and kidney histology. Conclusions and Future Perspectives: The wild Nile-Delta ecotype of T. crispa appears to be a stress-adapted chemotype characterized by enriched levels of multiple bioactive metabolites, superior in vitro bioactivity, and an encouraging preliminary safety margin. These findings support further evaluation of wild T. crispa as a candidate source for standardized botanical preparations targeting oxidative stress-related and hepatic pathologies, while emphasizing the need for: More comprehensive in vivo efficacy studies. Cultivation strategies that deliberately maintain or mimic beneficial stress conditions to preserve phytochemical richness. Broader geographical and genetic sampling to assess how generalizable the present chemotypic and bioactivity patterns are across the species. Full article

Offshore wind energy is a key enabler of the global net-zero transition. As nearshore fixed-bottom projects reach maturity, floating offshore wind turbines (FOWTs) are becoming the next major focus for large scale deployment. To accelerate this development and reduce construction costs, it is essential to optimize mooring systems through a systematic and performance driven framework. This study focuses on the mooring assessment of the Taiwan-developed DeltaFloat semi-submersible platform supporting a 15 MW turbine at a 70 m water depth offshore Hsinchu, Taiwan. A full-chain catenary mooring system was designed based on site specific metocean conditions. The proposed framework integrates ANSYS AQWA (version 2024 R1) and Orcina OrcaFlex (version 11.5) simulations with sensitivity analyses and performance-based fitness metrics including offset, inclination, and line tension to identify key parameters governing mooring behavior. Additionally, an analysis of variance (ANOVA) was conducted to quantitatively evaluate the statistical significance of each design parameter. Results indicate that mooring line length is the most influential factor affecting system performance, followed by line angle and diameter. Optimizing these parameters significantly improves platform stability and reduces tension loads without excessive material use. Building on the optimized symmetric configuration, an asymmetric mooring concept with unequal line lengths is proposed. The asymmetric layout achieves performance comparable to traditional 3 × 1 and 3 × 2 systems under extreme environmental conditions while demonstrating potential reductions in material use and overall cost. Nevertheless, the unbalanced load distribution highlights the need for multi-scenario validation and fatigue assessment to ensure long-term reliability. Overall, the study establishes a comprehensive and sensitivity-based evaluation framework for floating wind mooring systems. The findings provide a balanced and practical reference for the cost-efficient design of floating offshore wind farms in the Taiwan Strait and other shallow-water regions. Full article

Emergency supplies policies are a key component of regional risk governance, yet their design coherence has received limited systematic examination. Focusing on the Yangtze River Delta (YRD), this study conducts a design-oriented evaluation of emergency supplies policy design by integrating policy text mining with the Policy Modeling Consistency (PMC) index model. Based on a corpus of 212 emergency supplies–related policy documents, the study first examines the structural features and thematic emphases of the regional policy system and constructs a PMC-based evaluation framework within a mission–structure–mechanism perspective. On this basis, 16 provincial- and municipal-level policies issued between 2019 and 2023 are identified as core, system-defining policy texts and subjected to in-depth PMC evaluation. The results indicate that the evaluated core emergency supplies policies exhibit an overall “good” level of design coherence. Mission-oriented dimensions, including normative orientation and policy objectives, are generally well articulated, whereas mechanism-oriented dimensions—particularly linkage response and allocation arrangements—are specified less consistently. Observed interjurisdictional differences reflect institutional roles and governance traditions rather than variations in administrative capacity. By shifting analytical attention from implementation outcomes to design-stage coherence in core policy texts, this study provides a structured diagnostic approach for assessing emergency supplies policy design and offers insights for strengthening regional coordination and institutional resilience. Full article

The Pearl River Mouth Basin is a significant hydrocarbon basin in the northern part of the South China Sea, where deep hydrocarbon exploration has become increasingly important research in recent years. However, the current understanding of the source-to-sink and depositional systems of the Paleogene Zhuhai Formation is still limited, which restricts the exploration and discovery of large-scale sand bodies. Based on core observation, heavy mineral analysis, and well-seismic integrated analysis, this paper clarifies the development of a fan delta-tidal flat depositional and the source-to-sink systems of the Zhuhai Formation. The bedrock in the source region primarily consists of granite, Mesozoic sandstone, and tuff. The source region is divided into five parts (A1–A5), with seven main valleys (V1–V7) developed, supplying sediments to five depositional areas (S1–S5). Additionally, a fault-slope type coupled valley–fan depositional model is established for the study area, revealing the spatiotemporal distribution and main controlling factors of the fan delta system in a steeply dipping boundary fault environment. Catchment area, valley length, and cross-sectional area show a strong positive correlation with sedimentary system scale. Increased elevation difference enhances sediment transport potential energy, while reduced width-to-depth ratio strengthens hydrodynamic forces, promoting sedimentary sand body development and sedimentary system expansion. Full article

Changes in climate and ocean pollution has prioritized monitoring of ocean surface behavior. Ocean drifters, which are floating sensors that record position and velocity, help track ocean dynamics. However, environmental events such as oil spills can cause abnormal behavior, making anomaly detection critical. Unsupervised learning, combined with deep learning and advanced data handling, is used to detect unusual behavior more accurately on the NOAA Global Drifter Program dataset, focusing on regions of the West Coast and the Mexican Gulf, for time periods spanning 2010 and 2024. Using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), pseudo-labels of anomalies are generated to train both a one-dimensional Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. The results of the two models are then compared with bootstrapping with block shuffling, as well as 10 trials with bar chart summaries. The results show nuance, with models outperforming the other in different contexts. Between the four spatiotemporal domains, a difference in the increasing rate of anomalies is found, showing the relevance of the suggested pipeline. Beyond detection, data reliability and efficiency are addressed: a RAID-inspired recovery method reconstructs missing data, while delta encoding and gzip compression cut storage and transmission costs. This framework enhances anomaly detection, ensures reliable recovery, and reduces energy consumption, thereby providing a sustainable system for timely environmental monitoring. Full article

The Lower-Middle Jurassic Xishanyao Formation in the Nileke Sag of the Yili Basin contains substantial reserves of coal and coalbed methane (CBM). Elucidating its depositional evolution and the controlling factors of coal accumulation within a sequence-stratigraphic framework is crucial for guiding future exploration. This study integrates regional geological surveys, core observations, well-log analysis, and quantitative lithofacies statistics of the lower member to establish a sequence-stratigraphic framework and reconstruct the sedimentary paleogeography. Eleven minable coal seams are identified, exhibiting a depositionally controlled spatial thickness distribution. The coal is classified as low-rank bituminous (Rank I–II), characterized by high inertinite, low ash, medium-high volatile matter, and ultra-low sulfur content, indicating formation in a freshwater swamp influenced by seasonal droughts and floods. Three third-order sequences (SQ1–SQ3) are recognized. SQ2, deposited during peak transgression as a braided-river delta plain, provided the optimal environment for peat accumulation. In contrast, SQ3 is dominated by progradational deltas with coarser sediments, where coal accumulation weakened. The results demonstrate that coal accumulation was jointly controlled by tectonic subsidence (providing accommodation space), climate (causing peat oxidation and fine-clastic input), and sedimentation (with interdistributary bays on the delta plain being the most favorable sites). Coal accumulation in the Lower Xishanyao Member resulted from the coupling of tectonic, climatic, and sedimentary processes. This genetic model provides a theoretical basis for regional coal and CBM exploration. Full article

Accurately grasping the relationship between science and technology finance efficiency (STFE) and carbon emission efficiency (CEE), and further exploring their interaction and synergistic development within the network structure are of great significance for promoting regional coordinated development, economic growth, and environmental issues. This article uses the super-efficient SBM model to measure the STFE and CEE in 30 provinces of China from 2011 to 2020, and innovatively introduces the Multi-Layer Network (MN) method to explore the characteristics of their network structure, synergistic evolution, and influencing factors. The results show that (1) the evolution of the MN structure is the result of synergistic development, which mainly forms the network pattern of the Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Qinghai–Gansu region with “triple-core, multi-zone”. (2) The STFE network plays a leading role in the MN structure by influencing the CEE network structure. (3) The layers of MN are connected in a disassortative way, while the network similarity is gradually increasing. (4) The number of communities of the MN is decreasing, and the agglomeration of the community structure is gradually increasing. (5) The performance of the MN structure has better robustness than the single-layer network under different strategies and different node retention levels of destruction. (6) The economic development level, government support rate, and industrial structure upgrading are the core factors affecting the value of weighted degree and closeness centrality, while betweenness centrality is mainly affected by the urbanization level and foreign direct investment level. Full article

This study proposes a novel framework for allocating CO₂ emission rights within the Yangtze River Delta (YRD) urban agglomeration, tackling the inter-city CO₂ transmission dynamics frequently neglected in conventional allocation models. Current emission allocation methods fail to capture the spatial spillover effects of CO₂ emissions driven by atmospheric transport, resulting in potential inequities. Leveraging the WRF model to simulate carbon emissions across 27 cities, we develop a two-stage network Data Envelopment Analysis (DEA) model that integrates both emission generation and governance capacities. Our findings highlight significant inter-city CO₂ transmission, with the wind direction and speed playing a pivotal role in emissions spread. In contrast to traditional models, our approach considers the regional interdependence of emissions, enhancing both fairness and efficiency in the allocation process. The results indicate that cities with stronger governance systems, including green technology investments and effective air quality management, are rewarded with higher carbon allowances. Moreover, our model demonstrates that policies prioritizing environmental governance over raw emission levels can foster long-term sustainability. This work provides a comprehensive methodology for achieving a balanced allocation of emission rights that integrates economic growth, environmental management, and equity considerations within complex urban agglomerations. Full article

Based on micro-level job seeker data from 41 cities in China’s Yangtze River Delta, this study employs threshold regression to examine how inter-city distance influences talent mobility. The results reveal that distance exerts a negative impact on mobility intention and moderates the relationship between a destination’s economic level and mobility. Notably, significant threshold effects are identified at 164.1 km and 271.5 km, delineating three spatial regimes. Short-distance flows (<164.1 km) show the highest intensity, driven by strong economic incentives and high mobility. In contrast, medium-distance flows (164.1–271.5 km) prove least attractive due to offsetting effects, while long-distance flows (>271.5 km) rebound slightly as talent selectively targets major economic hubs, with distance exhibiting only weak inhibition. Crucially, these nonlinear patterns remain robust after addressing endogeneity concerns via the 2SLS method, substituting spatial distance with temporal distance, and controlling for housing prices and cultural factors. Heterogeneity analysis further indicates that individuals with bachelor’s degrees, those above age 30, and talent in labor-intensive industries exhibit greater sensitivity to distance. Conversely, knowledge-intensive sectors and top-tier economic cities demonstrate broader spatial tolerance and stronger cross-regional attraction capabilities. These findings provide a quantitative basis for developing differentiated regional talent policies. Full article

Against the backdrop of national policies promoting coordinated regional development and ecological civilization construction, the contradiction between ecological security and environmental carrying capacity in the Yangtze River Delta urban agglomeration has become increasingly prominent. However, the interaction mechanisms between these two systems remain insufficiently explored. This study constructs a comprehensive evaluation indicator system for ecological security and environmental carrying capacity in the Yangtze River Delta. A double exponential function is employed to examine the intensity of interaction pressure and reveal their nonlinear relationship. The coupling coordination model is applied to assess coordinated development trends, while a vector autoregression (VAR) model is used to identify the dynamic response relationships among system variables. The results indicate that the overall levels of both systems have improved, with core areas maintaining a leading position and southeastern, northeastern, and western regions remaining in a catching-up stage, accompanied by low-level convergence. Regional coordination exhibits a positive temporal evolution from imbalance to coordination, while its spatial pattern evolves from core dominance toward multi-regional convergence. Significant regional heterogeneity is observed in shock responses, with peripheral cities facing stronger industrial restructuring pressures showing greater ecological volatility. Overall, the dynamic interaction between ecological security and environmental carrying capacity demonstrates a stage-specific transition from mutual constraint to mutual promotion. This study provides empirical support for ecological restoration and regional sustainable development policymaking. Full article

Functional constipation (FC) is a common functional gastrointestinal disorder thought to arise from the brain–gut axis dysfunction, yet direct human neurophysiological evidence is lacking. We recorded high-density electroencephalography (EEG) data in 21 FC patients and 37 healthy controls across resting, cognitive, and defecation-related tasks. We observed that FC patients displayed a consistent, task-dependent signature compared with healthy controls. At the regional level, FC patients exhibited increased alpha during both resting and defecation-related tasks, reduced temporal gamma during defecation-related tasks, as well as elevated temporal theta during the cognitive task. At the global level, we found altered network properties, such as global efficiency in the delta and beta band networks during resting and defecation-related tasks. These findings establish a direct neurophysiological link between specific, condition-dependent perturbations in cortical rhythm activity and FC pathophysiology. Our work implicates the brain–gut axis in symptom generation and opens a path toward EEG-based biomarkers and targeted neuromodulatory therapies. Full article

Existing point-of-interest (POI) recommendation methods often fail to capture complex contextual dependencies and suffer from severe data sparsity in location-based social networks (LBSNs). To address these limitations, this study proposes a Context-Aware Knowledge Graph Learning (CKGL) method that integrates multi-dimensional semantic information, spatio-temporal dependencies, and social relationships into a unified knowledge graph framework. First, the Context-Aware Knowledge Graph Construction (CKGC) module builds a unified POI knowledge graph that captures heterogeneous relationships among users, POIs, regions of interest (ROIs), and social links. Then, the Context-Aware Knowledge Graph Embedding (CKGE) module, based on the Translational Distance Model with Relation-Specific Spaces (TransR), learns relation-specific embeddings of entities to preserve heterogeneous semantics. Next, a Spatio-Temporal Gated Graph Neural Network (STG-GNN) captures temporal dynamics and spatial dependencies in user check-in behaviors, while the Relation-Aware Graph Attention Network (RA-GAT) enhances multi-relational reasoning and information aggregation across heterogeneous relations. Extensive experiments on two real-world LBSN datasets, Gowalla and Brightkite, demonstrate that CKGL significantly outperforms several baseline models on Recall and Normalized Discounted Cumulative Gain (NDCG), validating its effectiveness in capturing contextual semantics and improving recommendation accuracy under sparse and complex scenarios. Full article

Rapid urbanization has profoundly impacted regional ecosystem services. However, most current studies have not paid enough attention to the implicit quality-of-life dimensions of urbanization, and few studies have been published on the dynamic interactions between urbanization and the evolution of ecosystem services. This study investigated the temporal and spatial dynamics of urbanization and ecosystem services value (ESV) in the Yangtze River Delta (YRD) region from 2010 to 2020 and their correlation. We conceptualized and measured the level of urbanization in two dimensions: Urbanization I (population, economy, and landscape) and Urbanization II (public services, education and spiritual life, and habitation environment construction). ESV was quantitatively evaluated by the equivalent factor method. The global and local spatial autocorrelation analysis was used to reveal the influence of urbanization dynamic evolution on ESV change. The results show the following: (1) the level of Urbanization I rose steadily, while the level of Urbanization II, though starting from a lower base, grew at a significantly faster rate, especially after 2017; (2) total ESV declined, with the largest decline in regulating services; (3) a significant negative spatial correlation was found between urbanization and ESV, with Urbanization I exerting a greater negative impact than Urbanization II; (4) spatially, “high-low” clusters (high urbanization, low neighboring ESV) dominate in the eastern coastal areas, while “low-high” clusters dominate in the western inland areas. The findings are of great significance for regional sustainable development and can provide a reference for other rapidly urbanizing regions in the world. Full article