Search Results (3,628)

Accurately assessing dynamic water resource carrying capacity (WRCC) is essential and challenging, particularly in regions like the Gansu sections of the Yellow River Basin (GSYRB), a core water source protection zone in the arid northwest of China, due to its pressing challenge of balancing water resources for socioeconomic needs and ecological security. This study proposes a novel integrated computational assessment framework named SD-VIKOR to address the complexities arising from nonlinear interactions within the “water resources–socioeconomic–ecological environment” (W–S–E) system. The core of this framework is the tight coupling of a system dynamics (SD) simulation model with a VIKOR multi-criteria evaluation module, where indicator weights are objectively–subjectively determined via an Analytic Hierarchy Process (AHP)–entropy weight method. This integrated SD-VIKOR engine enables dynamic, scenario-based WRCC trajectory simulation. To move beyond simulation and enable mechanistic insight, the framework further incorporates a diagnostic suite: a Geodetector module quantifies dominant drivers and their interactions; an obstacle degree model pinpoints key limiting factors; and a coupling coordination degree model evaluates subsystem synergies. Together, they form a closed-loop “dynamic simulation → multi-criteria assessment → driving mechanism analysis and constraint diagnosis → subsystem coordination analysis” workflow. Applied to the GSYRB from 2012 to 2030 under five development scenarios, the framework demonstrated high efficacy. It successfully captured path-dependent WRCC evolution, revealing that the ecological-priority scenario (B2), which shifts system drivers from economic-scale expansion to resource-efficiency and environmental governance, yielded optimal WRCC and the highest system coordination. In contrast, business-as-usual and single-minded economic expansion scenarios underperformed. Six key obstacle factors were quantitatively identified, linking WRCC constraints to natural endowments, economic patterns, and domestic demand. The results reveal pronounced spatial–temporal heterogeneity in WRCC across the GSYRB, with socioeconomic development, water resource use efficiency, and ecological conditions acting as the primary joint drivers of WRCC evolution. Critically, several key indicators are identified as persistent constraints on regional water sustainability. In contrast to conventional static evaluations, the integrated framework captures the complex dynamics and multi-subsystem interactions governing WRCC, offering a more robust diagnostic of resource–environment systems. These insights provide a transferable analytical basis for designing sustainable water management strategies in arid river basins. Full article

Urban expansion is a key driver of land-use change and environmental pressure in rapidly urbanizing regions. Existing assessments of urban expansion often rely on predefined indicator systems and fixed weighting schemes, which limits their adaptability to evolving research priorities and regional contexts. This study develops an adaptive framework for urban expansion assessment by integrating a transformer-based language model with multi-source spatial data. A BERT-based semantic extraction process is used to identify relevant indicators and derive their relative weights from the scientific literature, enabling the construction of a literature-driven Urban Expansion Index (UEI). The framework is applied to the Central Plains Mega-city Region (CPMR), China, to examine spatial patterns and temporal dynamics of urban expansion between 2010 and 2020. Results show that UEI is primarily driven by land-use expansion indicators, while socioeconomic, infrastructure, and environmental indicators jointly reflect the multidimensional nature of expansion processes. Spatial patterns reveal a persistent concentration of high expansion intensity in core cities, alongside heterogeneous environmental responses and gradual outward growth. Changes in UEI display weaker spatial coherence than static levels, indicating differentiated local expansion dynamics. Local spatial autocorrelation analysis further identifies shifting clusters of urban expansion intensity, suggesting a reorganization of expansion centers within the agglomeration over time. By linking transformer-based indicator extraction with spatial analysis, this study advances urban expansion assessment beyond outcome-oriented mapping toward a more adaptive and knowledge-informed approach. The proposed framework is transferable to other mega-city regions and provides a useful tool for supporting territorial spatial planning and sustainable urban development. Full article

Background: The progression of idiopathic pulmonary fibrosis (IPF) involves distal airway remodeling and bronchiolization; however, the mechanisms driving these changes, particularly the contributions of epithelial stem cells, are not fully understood. K13⁺ hillock cells, normally quiescent in proximal airways, were examined for their potential contribution to IPF pathogenesis. Methods: Spatial immunofluorescence was used to profile K13 expression along the airway axes in IPF and control lungs. Multiplex staining complemented by ex vivo culture assays was used to test expression stability. Single-cell RNA-sequencing (scRNA-seq) data were re-analyzed to identify cell subclusters and pathway enrichments. Meanwhile, cell–cell communication was inferred by using CellChat. Results: K13 was ectopically upregulated in IPF honeycomb cysts, triggering a proximal-like pseudostratified phenotype. This shift was marked by surges in K13⁺ regionally overlapping expression patterns (K5⁺, ~9%; CC10⁺, ~53%; ACE-TUB⁺, ~44%; MUC5AC⁺, ~23%) and a decline in SOX2 expression (~95% to ~64%), with ~70% of residual SOX2^low cells exhibiting elevated K13. Accompanying the expansion of K13⁺ subclusters (basal: 1.8% to 41.5%; club: 10.7% to 31.5%), it was observed that the profibrotic markers (K17, S100A2, LGALS7, IGFBP6) and ontologies related to RNA processing, stress response, and senescence were also enriched. These subclusters also amplified pro-fibrotic signaling (e.g., TGF-β, SEMA3, and GALECTIN-9) associated with epithelial subtypes and HAS1^high fibroblasts. Conclusions: Here, we demonstrate that K13⁺ cell activation is a pivotal event, driving the dysregulated proximalization of distal airways in IPF through fate reprogramming and epithelial-mesenchymal crosstalk. Thus, elucidating these K13-mediated fate dynamics provides a critical framework for understanding IPF pathogenesis. Full article

Bangka’s mangroves contribute to Indonesia’s species-rich coastal ecosystems, yet they have experienced substantial degradation, largely driven by human activities such as tin mining. Establishing long-term records of mangrove extent is essential for understanding distribution dynamics, assessing impacts, and guiding conservation strategies. In this study, we applied change detection techniques, a random forest classifier, and the LandTrendr algorithm to analyze Landsat time-series data from 1994 to 2023 across Bangka Island. We quantified multi-decadal changes in mangrove extent, periods of disturbance and recovery, and discrepancies between local and global datasets. Mangrove dynamics were spatially heterogeneous, with both expansion and loss observed across regions in landward and seaward settings. Over the 30-year period, total gains reached 4956.39 ha (10.30% of the baseline), yet the net change indicated an overall loss of 1055.85 ha. LandTrendr analysis further revealed sustained mangrove expansion since 1989. Observed changes reflect the combined influence of natural processes, including accretion and erosion, and human pressures, particularly tin mining. Although net area loss aligns with national trends, the drivers in this mining-dominated region differ from those elsewhere, and some mangrove areas remain absent from global datasets. These findings emphasize the need to better capture local gain–loss dynamics to support effective management and conservation. Full article

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven. Full article

The spatiotemporal evolution of landscape patterns represents the most direct manifestation of land use change and remains a pivotal focus within landscape ecology research. Taking Huangshan City—a typical mountainous tourism city—as the study area, this research systematically analyzes the spatiotemporal evolution characteristics and driving mechanisms of landscape patterns over the past three decades. Based on land use data from 1992, 2002, 2012, and 2022, the study employs an integrated methodological framework including land use transition matrices, landscape pattern indices, moving window analysis, and the geographical detector (Geodetector) model, supported by ArcGIS and FRAGSTATS platforms. The results indicate that (1) during the study period, the landscape structure in Huangshan City exhibited a general trend characterized by “a stable foundation of forest land, continuous contraction of cropland, and significant expansion of construction land.” (2) From 1992 to 2012, cropland served as the primary source of transfer, mainly being converted into forest land; conversely, between 2012 and 2022, the reciprocal transformation between cropland and forest land became the dominant transition process. (3) At the landscape level, overall diversity enhanced and spatial distribution tended toward uniformity, whereas landscape fragmentation persisted in localized areas. (4) The driving force analysis revealed that “distance to the urban center” was the primary driving factor shaping landscape pattern changes, with its explanatory power continuously increasing. Furthermore, significant synergistic enhancement effects were observed between natural and socio-economic factors. These findings provide a scientific basis for ecological protection, restoration, and sustainable development strategies in Huangshan City within the context of rapid urbanization and tourism development. Full article

Surgical resection remains a cornerstone in the multidisciplinary management of central nervous system (CNS) tumors, particularly diffuse gliomas. Traditionally, the role of surgery has been evaluated primarily through quantitative metrics such as extent of resection and its association with survival outcomes. However, despite maximal and radiologically complete resections, recurrence remains nearly universal in malignant CNS tumors, suggesting that surgical cytoreduction alone does not fully account for post-surgical disease dynamics. Emerging biological and molecular evidence indicates that surgery represents not merely a technical intervention, but a biologically active event that profoundly reshapes tumor evolution and treatment response. In this review, we propose a conceptual framework that redefines surgery as a key biological driver in CNS tumor progression. We synthesize evidence demonstrating that surgical trauma induces inflammation, hypoxia, vascular remodeling, immune modulation, and extracellular matrix reorganization, collectively reprogramming the residual tumor microenvironment. These changes create selective pressures that favor the survival and expansion of adaptive tumor cell subpopulations, including invasive and stem-like phenotypes. From an evolutionary perspective, surgical resection functions as an acute selective bottleneck acting on heterogeneous tumor ecosystems, contributing to clonal selection and molecular divergence at recurrence. We further examine the dissociation between surgical (anatomical) margins and molecular (biological) margins, highlighting how biologically active tumor cells infiltrate beyond radiologically defined boundaries. This discrepancy provides a biological explanation for marginal and distant recurrences and challenges anatomy-based paradigms of surgical completeness. Importantly, we discuss how surgery-induced biological changes influence postoperative radiotherapy and systemic therapies, affecting radiosensitivity, target delineation, and therapeutic vulnerability. Finally, we outline future directions toward surgery-integrated precision neuro-oncology, emphasizing the potential of spatial profiling, liquid biopsy, advanced imaging, and artificial intelligence to capture perioperative tumor evolution. By reframing surgery as a biological inflection point rather than a neutral prelude to adjuvant treatment, this review advocates for a dynamic, biology-driven continuum of care aimed at anticipating tumor adaptation and improving long-term disease control in CNS tumors. Full article

Distributed acoustic sensing (DAS) in pipeline safety warning systems confronts multiple challenges during technological evolution and application expansion, primarily including recognition accuracy, real-time performance, and the identification of weak signals for pipeline third-party intrusion (TPI) detection in complex environments. So, this paper proposes a Pipeline Fiber Optic Warning-Mixture of Experts (PFOW-MoE) method to address challenges in DAS systems. The proposed method is innovative in the sense that: (1) Multi-modal feature perception expert model design: Different intrusion behaviors are unique in the time, spatial, and frequency domains; (2) Efficient decision framework with dynamic gating mechanism: It evaluates input signal features in real time. (3) Robustness enhancement mechanism for weak signal perception: A weak signal detection branch is added to dynamic gating. Experimental validation on actual pipeline datasets shows PFOW-MoE achieves 98.27% accuracy on the entire sample set. On weak signal samples, it achieves 96.00%. The single-sample inference time is only 0.78 ms, meeting practical real-time engineering needs. Full article

With the acceleration of global climate change and urbanization, air pollution, particularly ozone pollution, has become a critical environmental issue, especially in the Beijing–Tianjin–Hebei region of China. This study investigates the spatiotemporal distribution of ozone pollution and its precursors, focusing on formaldehyde as a key indicator of volatile organic compounds. Utilizing high-resolution remote sensing data from the China High-Resolution Air Pollutants dataset and TROPOMI HCHO observations from 2013 to 2022, we employed advanced techniques such as the Kolmogorov–Zurbenko filter and high-value area identification to analyze ozone pollution trends, meteorological influences, and the spatial distribution of HCHO concentrations. Our findings reveal a significant increase in ozone concentrations across BTH, with an annual growth rate of 2.51 μg/m³, peaking during the summer months. The KZ filter decomposition highlighted that short-term and seasonal variations dominate ozone fluctuations, driven by meteorological factors such as solar radiation and temperature. Furthermore, the identification of HCHO HVAs demonstrated that urban agglomeration and expansion zones exhibit higher HCHO concentrations, with VOCs-limited zones showing the most pronounced HCHO levels. The study also introduced the PHV (Percentage Higher than Vicinity) index to quantify anomalous HCHO emissions, providing a robust tool for pinpointing pollution hotspots. Based on these insights, we propose targeted emission control strategies for key regions, including urban expansion zones in Zhangjiakou and non-urban zones in Qinhuangdao, to mitigate ozone pollution effectively. This research offers valuable scientific support for regional air quality management and the formulation of precise pollution control measures in the Beijing–Tianjin–Hebei region. Full article

The accurate measurement and optimization of spatial vitality inside commercial complexes has become crucial for sophisticated urban governance as urban growth moves from rapid expansion to quality-oriented stock augmentation. This research creates a multifaceted assessment methodology that incorporates systemic connectedness (transportation synergy), spatial performance (public activity and social efficacy), and spatial supply (human–land linkages and arrangement). We used a stratified purposive sample of 20 business complexes spread across eight districts in Guangzhou, a typical high-density megacity. In order to understand the underlying mechanisms of spatial vitality, we measured important indicators including the Polycentricity Index (α) and the Spatial Performance Index (β) using a mixed-methods approach that included K-means clustering, multinomial logit regression, and Structural Equation Modeling (SEM). Four important insights are shown by our findings. 1. The paradox of density and efficiency: The notion that high-density development inevitably ensures lively public space is called into question by the lack of a significant linear correlation between the Floor Area Ratio (FAR) and spatial performance (r = 0.32, p > 0.05), despite a core–periphery gradient in development intensity. 2. Structural Supply Demand Mismatch: Although overall spatial performance is strong (β = 0.81 ± 0.07), there is a notable shortfall in cultural and artistic venues, where young adults’ demand (0.27) is 145% greater than supply (0.11). 3. Polycentric Networking vs. Transport Polarization: While spatial structures show a networked polycentric pattern (mean α = 6.40), transportation synergy is affected by core–periphery polarization, which results in “vitality islands” in the periphery. 4. Dual-Path Driving Mechanisms: According to SEM results, cultural spaces have a considerable indirect impact (39.7% mediation) by boosting brand uniqueness and “cultural capital,” while composite plaza spaces have a strong direct effect on commercial performance (γ = 0.682). Based on these findings, we suggest distinct optimization strategies: aging projects need climate-responsive design interventions; growing areas should create family-oriented consumption ecosystems; and core districts should give priority to cultural “IP” integration. For the planning and revitalization of commercial land use in high-density global environments, this study offers a solid analytical framework and practical insights. Full article

Amid the accelerating global pursuit of carbon neutrality, the regulatory role of forest ecological security in carbon sink function has emerged as a critical issue in achieving climate goals. This study developed a forest ecological security evaluation index system based on the Driving Force–Pressure–State–Impact–Response–Management (DPSIRM) framework. The forest ecological security comprehensive index for 31 Chinese provinces from 2007 to 2022 was calculated using the entropy weight method, and forest carbon sinks were estimated through the volume expansion method. Spatial econometric models and a mediation effect model were employed to empirically examine the impact of forest ecological security on forest carbon sinks and their underlying mechanisms. The results indicated the following: (1) Improvements in forest ecological security exerted significant positive direct and spatial spillover effects on forest carbon sinks. (2) The enhancing effect of forest ecological security on carbon sinks was significant in western regions, resource-based provinces, and economically underdeveloped areas. (3) Forest area transition and forest age structure transition served as key mediators in the relationship between forest ecological security and carbon sinks. In contrast, the mediating effects of forest species structure transition and forest origin structure transition were not significant, likely constrained by long-term ecological thresholds and socioeconomic inertia. Full article

With increasing demand for wellness tourism, identifying the key factors influencing emotional perceptions is essential for optimizing destination planning and management. Although Anhui Province has experienced rapid growth in wellness tourism destinations in recent years, scientific understanding of tourists’ emotional perceptions and their driving mechanisms has lagged behind this rapid expansion, a gap that can be addressed by integrating big data with spatial analysis to provide a scientific perspective for optimizing destination planning and informing regional wellness tourism policy. To address this gap, this study conducts a sentiment analysis of wellness bases in Anhui Province using user-generated content (UGC) data. Sentiment scores were quantified via SnowNLP, while kernel density, time-series, and multivariate statistical analyses were applied to examine spatial distributions, temporal dynamics of sentiments and review volumes, and emotional driving factors. The results indicate a spatial pattern of higher density in the south, lower density in the north, and dual-core agglomeration, closely linked to natural resource endowments. Temporally, sentiment scores rise in spring and summer and decline in winter, while review volumes peak in spring and autumn. Overall regression analyses reveal a significant positive effect of green coverage and a negative effect of accommodation prices. In the typological analysis, sentiment scores of Forest Wellness Bases (FWBs) relate to green coverage and negative ions, while Hydrological Wellness Bases (HWBs), Traditional Chinese Medicine Wellness Bases (TCMWBs), and Wellness Towns (WTs) are driven by the combined effects of facility services, locational price, and ecological environment. These findings provide a scientific basis for the sustainable development and differentiated management of wellness tourism destinations. Full article

Land use/cover change (LUCC) strongly regulates ecosystem carbon storage and provides a critical entry point for carbon-oriented territorial spatial governance. However, balancing carbon sequestration, food security, urban expansion, and ecological protection remains challenging in Southwest China’s Ecological Security Barrier Zone (ESBZ). In this study, we coupled the Patch-generating Land Use Simulation (PLUS) model with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) carbon module to reconstruct LUCC and carbon-storage dynamics during 1999–2024 and to project land-use patterns and carbon storage in 2049 under four scenarios: Natural Development (NDS), Urban Development (UDS), Cultivated land Protection (CPS), and Ecological Protection (EPS). Unlike most existing PLUS–InVEST studies focused on cities, watersheds, or single provinces, this study targets a national ecological security barrier and integrates land-use evolution, carbon-storage responses, scenario trade-offs, and zoning-oriented governance into one analytical framework. It therefore provides spatially explicit evidence not only for carbon-oriented land management but also for interprovincial ecological compensation and coordinated ecological security governance in ecologically fragile regions. The 2024 land system was dominated by forest land (56.40%), cultivated land (25.47%), and grassland (16.09%). From 1999 to 2024, forest land expanded by 1.966 × 10⁴ km², whereas cultivated land and grassland decreased by 9.738 × 10³ km² and 1.874 × 10⁴ km², respectively; 92.65% of construction-land expansion originated from cultivated land conversion. Correspondingly, total carbon storage followed a “fluctuation–decline–recovery” trajectory, decreasing from 3.833 × 10¹⁰ t in 1999 to 3.820 × 10¹⁰ t in 2014, before rebounding to 3.831 × 10¹⁰ t in 2024. Pronounced provincial heterogeneity was observed: Sichuan and Yunnan jointly contributed about 76% of regional carbon storage, while Chongqing and Guizhou remained relatively low. By 2049, EPS produced the highest carbon storage (3.854 × 10¹⁰ t), whereas CPS, UDS, and NDS all led to lower values than in 2024. These contrasts indicate that the four scenarios do not represent a simple ranking of “better” or “worse”, but rather different trade-offs among carbon sinks, cultivated land protection, urban development, and regional equity. Overall, the results support province-differentiated, zoning-based land governance and highlight the need to coordinate ecological protection, cultivated-land conservation, urban growth control, and interprovincial ecological compensation to enhance carbon sequestration and safeguard ecological security in the ESBZ. Full article

Ensuring a reliable and sustainable water supply in growing urban areas requires integrated planning that balances increasing demand with technical, economic, and operational constraints. This paper presents the development of a Planning Support System to support decision-making in the expansion of urban water distribution networks. The proposed framework links urban development strategies with future water demand assessment, spatial analysis, hydraulic modeling, and structured evaluation of alternative network expansion scenarios. Geographic Information Systems are used to identify potential growth areas and estimate future demand based on urban planning documents, while hydraulic simulations are performed using the Water Network Tool for Resilience to assess network performance under projected operating conditions. The generated variants are subsequently evaluated using selected Multi-Criteria Decision Analysis methods, considering factors such as investment costs, energy consumption, supply security, and network resilience. A case study demonstrates the applicability of the proposed Planning Support System and confirms its effectiveness in providing a transparent and replicable basis for supporting strategic decisions in water supply network sustainable development. Full article

As the largest urban agglomeration and a critical grain production base in northern China, the Beijing–Tianjin–Hebei (BTH) region faces a sharp conflict between rapid urbanization and cropland conservation. Urban expansion inevitably leads to the loss of high-quality agricultural land, posing dual threats to food security and the terrestrial carbon cycle. To accurately assess the ecological costs of this process, this study integrates the CASA model with a time-weighted cumulative model to quantify the spatiotemporal impacts of urban expansion on cropland NPP in the BTH region from 2001 to 2020. Furthermore, a Geographically Weighted Regression (GWR) model was employed to examine the spatially varying effects of key driving factors on cropland NPP loss. The results indicate that urban land in the BTH region expanded by 45.2% over the past two decades, with 91.04% originating from cropland. Despite an overall upward trend in regional cropland NPP driven by climate change and agricultural intensification, the time-weighted cumulative cropland NPP loss attributable to urban encroachment over 2001–2020 reached 29.24 Tg C, which is equivalent to 0.751× the annual total cropland NPP in 2020 (used as a reference benchmark). Crucially, this expansion exhibits distinct ecological selectivity toward high-quality cropland, meaning that urban development has disproportionately encroached upon highly productive land with productivity levels exceeding the regional average. This selective occupation has led to a structural decline in the region’s potential agricultural production capacity. Additionally, GWR results reveal significant spatial non-stationarity in the relationships between cropland NPP loss and its drivers, revealing differentiated response patterns between plains and mountainous areas in terms of socio-economic drivers and physical constraints. These findings expose the hidden threats of urban expansion to food security, providing a crucial scientific basis for formulating differentiated land management policies and coordinating regional urbanization with cropland protection. Full article