Search Results (333)

The 2021 eruption of Cumbre Vieja on La Palma, Canary Islands, produced extensive lava flows and major landscape transformation, providing an opportunity to evaluate remote sensing approaches for mapping the extent of an emplaced lava flow. This study assessed direct spectral, classic Rao’s quadratic entropy (RaoQ), and multidimensional RaoQ approaches using satellite observations acquired before and after the eruption. Optical, radar, thermal infrared, and night-time radiance datasets were evaluated within a common change-detection framework implemented in Google Earth Engine. Difference maps were converted into binary change maps using a histogram-based thresholding procedure calibrated on the reference delineation and evaluated against the Copernicus Emergency Management Service (CEMS) lava-flow reference and no-change validation areas derived from ESA WorldCover using multiple accuracy metrics. Because the change reference is the final CEMS lava-flow delineation and the no-change samples lie outside a 100 m buffer around it, the accuracy figures reported here quantify the mapping of lava-flow extent and not of other eruption-related effects such as ash deposition or vegetation damage beyond the flow margins. Among the direct spectral approaches, the NHI_SWIR index achieved the highest overall classification performance. Among the individual Sentinel-2 bands, B12 achieved the highest overall accuracy, whereas B8A achieved the highest true skill statistic; both exceeded the multidimensional RaoQ configurations in mean prevalence-independent discrimination. Within the classic RaoQ approach, MIRBI produced the strongest single-variable heterogeneity-based results. The best multidimensional configurations combined Sentinel-2 B8A and B12 with Sentinel-1 VV, demonstrating that radar backscatter provided complementary information to optical observations. Although multidimensional RaoQ did not surpass the best direct spectral variables, it produced competitive and spatially coherent representations of lava-flow disturbance. The evaluated thermal infrared and night-time radiance products did not provide competitive discrimination under the selected spatial and temporal conditions for different reasons: a thresholding limitation in the case of the Landsat thermal product, and an unfavourable ratio of pixel size to flow width in the case of the night-time radiance products, while the MODIS product returned no valid validation points and could not be evaluated. These product-specific explanations rest on a small number of comparisons and are provisional. These results show that carefully selected Sentinel-2 SWIR variables remain the strongest benchmark for detailed mapping of fresh lava-flow disturbance, while multidimensional RaoQ provides a framework for optical–radar integration that requires no training data or prior classification. Because the evaluation covers a single eruption in a single landscape, transfer of the framework to other events and settings remains to be demonstrated. Full article

Climate change poses a threat to bryophytes with restricted distributions and strong dependence on humid habitats. We assessed the climatic suitability of the moss genus Tetrastichium across the Azores, Madeira, and the Canary Islands. We compiled 90 records each for Tetrastichium fontanum and Tetrastichium virens and fitted Boosted Regression Tree models using WorldClim 2.1 bioclimatic predictors. Future suitability was projected for 2061–2080 and 2081–2100 using two global climate models under SSP3-7.0 and SSP5-8.5. Model performance was good (AUC = 0.88, sTSS = 0.81, and sensitivity ≥ 0.94). Under current and future conditions, suitable areas were unevenly distributed among archipelagos. Climatically suitable areas generally increased in the Azores but contracted substantially in Madeira and the Canary Islands. Under UKESM1-0-LL, no suitable areas in the Canary Islands remained above the climatic-suitability threshold by the end of the century. Spatial overlap between current and future predictions declined under stronger climate forcing and longer time horizons, being consistently higher for T. virens. These findings reveal the high sensitivity of Tetrastichium to climate change, identifying Madeira and the Canary Islands as areas of conservation concern. Protecting extant populations and environmentally buffered habitats will be essential for the genus’s persistence under future climates. Full article

In response to the escalating challenges of global climate change and extreme meteorological events, this study addresses the critical issue of low disaster resistance in socialist-built heritage (SBH, i.e., built cultural heritage constructed during China’s socialist construction stage from 1949 to 1978). Focusing on Henan Province, China, with meteorological observation datasets spanning 1990–2023 and 1362 SBH sites constructed from 1949 to 1978, we innovatively construct a four-dimensional risk assessment model integrating Meteorological–Environmental Hazard (H), Exposure (E), Vulnerability (V), and Ecological Resilience (R). By synthesizing Spearman correlation analysis, Variance Inflation Factor (VIF) diagnostics, and piecewise regression, this research elucidates the spatial differentiation and driving mechanisms of meteorology-induced compound disaster risks. Key findings identify Zhengzhou and Kaifeng as core high-risk zones and precisely quantify a critical hazard threshold of 0.4 with a 95% breakpoint confidence interval [0.372, 0.428], passing the Chow test p < 0.001 and validated via historical heritage damage records (R² = 0.78). Variable-importance analysis proves that extreme precipitation (32.7%) and annual strong-wind days (28.1%) are the dominant meteorological–environmental drivers, alongside the significant buffering effect of ecological resilience. Ultimately, this study refines the disaster risk assessment framework for SBH, providing robust theoretical support and a decision-making basis for adaptive conservation strategies in similar regions. The average disaster risk of SBH in Henan is 0.421 ± 0.153; for each 0.1 growth of H-E-V coupling term above the threshold of 0.4, disaster risk rises by 37.2%. Full article

Overtourism is often assessed through visitor intensity, although its effects also depend on infrastructure performance, resource demand, spatial development, and evidence availability. This study develops a comparative diagnostic framework and applies it to Mykonos, Patmos, and Spetses, representing three contrasting Greek island tourism models. Ten indicators were classified according to their analytical role. Seven indicators were scored within three dimensions—resource pressure, infrastructure system, and tourism demand—while coastal water quality was treated as environmental-state evidence and built-up and coastal development as descriptive spatial evidence. Evidence confidence was assessed separately. Sensitivity analysis included leave-one-indicator-out tests, omission of indicators based on shared tourism data, threshold variation, and alternative standardization. Mykonos recorded the highest resource-pressure (4.00) and tourism-demand (3.50) scores, together with extensive built-up and coastal development, but its centralized wastewater treatment system operated within reported compliance limits. Patmos recorded lower tourism pressure but documented wastewater treatment underperformance, while Spetses lacked centralized wastewater treatment and had important monitoring gaps. The Mykonos results are consistent with pressure-specific infrastructure buffering, although the available data do not support causal attribution. The framework provides a comparative diagnosis without producing a single overtourism score and helps identify areas where further monitoring and assessment are needed. Full article

Early detection of tree-seedling establishment is essential for monitoring regeneration success in coastal-dune plantations, where conventional field assessments remain labour-intensive and spatially limited. This study presents a deep-learning workflow for detecting early-stage Pinus pinaster seedlings using multispectral UAS-derived point clouds. Field surveys in the Quiaios National Forest, Portugal, mapped approximately 1500 seedlings using RTK GNSS positioning, biometric measurements, and field photographs. Multispectral imagery acquired with a DJI Mavic 3 Multispectral platform was processed through Structure-from-Motion to generate calibrated orthomosaics, terrain products, and dense point clouds. Training-data preparation combined pine-centred buffers, spectral conditioning, manual refinement and point-cloud class assignment. Point Transformer V3 models were trained in ArcGIS Pro and evaluated using field-mapped buffers withheld from model training within plantation-line areas. The Baseline high-recall model achieved 88% object-level recall at the operational threshold of at least three classified Pine-Seedling points per buffer. The refined hard-negative model retained 84% recall while reducing off-buffer detections from 243 to 41. False-negative analysis showed that omissions were associated with reduced crown diameter and limited branch development under the adopted buffer-based retrieval framework. These results support transformer-based multispectral point-cloud classification for scalable monitoring of early-stage pine regeneration in heterogeneous coastal environments. Full article

A miniature label-free biosensor based on a chemically etched single-mode optical fiber (SMF) is reported for the detection of matrix metalloproteinase-8 (MMP-8), a salivary biomarker of active periodontitis with a clinical decision threshold of 20 ng/mL. Fibers etched in 48% hydrofluoric acid to a waist diameter of 16.0 ± 1.4 µm gave a mean refractive index (RI) sensitivity of 376.8%/RIU and an RI limit of detection (LOD) of 5.9 × 10⁻⁴ RIU. Fibers were tested with MMP-8 spiked into phosphate-buffered saline (PBS) and into saliva over 0–200 ng/mL using a post-rinse protocol with per-fiber matrix subtraction. Dose–responses followed a Langmuir isotherm (Kd = 7.1 ng/mL in PBS, 12.7 ng/mL in saliva), with cohort LODs of 0.043 and 0.52 ng/mL, both well below the threshold. MMP-9 (100 ng/mL) and human serum albumin (1 mg/mL) gave negligible responses (≤2.7%, versus 68.2% for MMP-8 at 100 ng/mL); antibody immobilization was confirmed by confocal immunofluorescence. A commercial sandwich ELISA on the same spike series gave a matched-matrix LOD of 41.1 ng/mL, nearly two orders of magnitude higher. This performance requires no metal coating, nanostructuring, label, or signal amplification, only a single wet-etching step on stock telecommunications fiber. Full article

This study aims to address the limitations of conventional summer-resort suitability evaluation, which fails to characterize the nonlinear responses of multi-factor variables and suffers from subjectivity in linear weighting, by constructing, based on observational records from 101 meteorological stations across Shaanxi Province spanning 1981–2024, an evaluation system that covers four dimensions (physiological thermal comfort, environmental amenity, extreme-weather risk and climatic stability) with 13 indicators. Group-based principal component analysis (PCA) is applied for dimensionality reduction. A multi-dimensional joint distribution is further established by integrating the empirical cumulative distribution function (ECDF) and the C-vine copula function to derive the Standardized Summer-Resort Index (SSRI). Independent external validation is implemented using outputs of the Universal Thermal Climate Index (UTCI) from ERA5-HEAT, and leave-one-out cross-validation (LOOCV) is adopted to assess the generalization performance and responses to extreme climates. The results reveal that the C-vine copula effectively captures the conditional dependence and nonlinear structures among multi-dimensional climatic variables (AIC = −4490.36, CvM test p = 0.175). The SSRI exhibits a significant positive correlation with the fraction of days without thermal stress derived from UTCI (Kendall’s τ = 0.289, p < 0.001), and the average year-to-year classification accuracy of LOOCV reaches 66.3%. Plains are dominated by wind-driven heat dissipation, whereas high-altitude mountainous regions are sensitive to temperature–humidity variations, and statistical buffering signals induced by vegetation can be detected. The SSRI in Shaanxi presents a “three-high and two-low” spatial pattern: high-value clusters occur in the Qin-Ba Mountains, the northern slope of the Daba Mountains and the Huanglong Forest Region, while low-value areas are distributed in the Guanzhong Basin and the wind-sand zones of northern Shaanxi. Relatively high suitability within forested areas during extreme high-temperature events can be statistically identified, which is jointly modulated by altitude–terrain–vegetation interactions, with a balanced accuracy of 0.771. The complete modelling workflow of this study can provide methodological references for other complex terrain regions. Nevertheless, all Shaanxi SSRI parameters, normalisation thresholds and classification criteria are trained on Shaanxi-specific datasets and cannot be directly transferred; local observational data must be used for refitting and calibration when applying this index to other regions. Full article

Urban waterfront spaces play an increasingly important role in mitigating urban heat and supporting climate-resilient urban development. However, previous studies have primarily focused on individual waterfront sites or local microclimatic simulations, with comparatively limited understanding of how waterfront morphology is associated with land surface temperature across different urban functional districts and spatial scales. This study evaluates the thermal characteristics of fifty representative waterfront samples in Chengdu, China, covering five urban functional districts: commercial, office, residential, park, and suburban areas. Land surface temperature (LST) data for the period from 1 June to 30 September 2023 were integrated with GIS-derived morphological indicators, including river width, water area ratio, green space ratio, building density, and distance to water. Thermal conditions were analysed within the 200 m waterfront zone and across 500 m, 1000 m, and 2000 m buffer zones. Correlation analysis, standardized multiple linear regression, and spatial autocorrelation analysis were used to assess bivariate relationships, independent predictor effects, and the robustness of the statistical results. The results show significant thermal differences among waterfront typologies. Commercial waterfronts exhibited the highest LST, whereas suburban waterfronts showed the lowest temperatures within the immediate waterfront zone. Standardized multiple regression analysis confirmed building density as the strongest independent positive predictor of LST across all spatial scales after accounting for intercorrelations among predictors, with adjusted R² values ranging from 0.384 to 0.582. River width and the water area ratio were negatively associated with LST mainly within the immediate waterfront zone, whereas the green space ratio showed no statistically significant independent association with LST. Cooling-related thermal contrasts also varied among waterfront typologies across buffer distances; however, inter-typology differences at the 2000 m scale were not statistically significant and should therefore be regarded as preliminary. Spatial autocorrelation analysis further indicated that the principal morphology–LST relationships remained broadly stable after accounting for spatial dependence. These findings suggest that waterfront thermal conditions are strongly associated with the combined configuration of blue, green, and built-environment characteristics rather than with water-body size alone. The multi-scale analytical framework provides a practical basis for evaluating waterfront thermal conditions, while the planning implications should be interpreted as directional rather than as fixed design thresholds. Full article

Coordinating production–living–ecology (PLE) land use requires an accurate account of how PLE functions interact, yet most studies treat these interactions as static attributes and report their thresholds in isolation. We instead treat them as dynamic states conditioned by their driving factors. For the karst region of southwest China, we identified the leading natural and the leading anthropogenic factors of the PLE functions with Geodetector, fixed one natural and one anthropogenic conditioning axis for each function pair by a pair-level rule, and reconstructed the 2010 and 2019 Pareto frontiers of each pair along those two gradients; curve tipping points distinguished reversal-type from buffer-type thresholds, from which regulation zones follow directly. Production–ecology and living–ecology are trade-offs over the fitted range, whereas the production–living boundary rises over most of the production range. Total benefit at the equal-weight reference optimum rose in all three pairs (0.552 to 0.636, 0.701 to 0.726, and 0.823 to 0.872), with no decrease in any of 1000 block bootstrap resamples. Boundaries also differed between areas of rising and of falling constraint function, but the two groups are unbalanced in terms of elevation and population density, so this contrast is reported as a descriptive comparison only. Along the elevation gradient the living–ecology interaction shows one reversal-type threshold in each year, at 595 and 756 m, whose confidence intervals define a precautionary management envelope of 498 to 939 m; along the population density gradient no threshold survived at the sub-watershed scale. The framework gives an operable basis for differentiated regulation in fragile regions. Full article

Lightning poses localized risks to signaling, communication, and traction-power systems along high-speed railways, yet most nowcasting products are generated on regular grids rather than operational line segments. This study developed a grid-to-segment machine-learning framework for next-hour lightning warning along the Jinan West–Tai’an corridor. Ground-based lightning observations, hourly ERA5 fields, temporal variables, and engineered historical lightning features and spatial-neighborhood features were organized on a 0.25° grid. Data from 2014 to 2018 were used for training, 2019 for validation, and 2020 for independent testing. Grid probabilities were converted into warnings for six railway segments using 10 km buffers and maximum-probability aggregation. In 2020, the full extreme gradient-boosting (XGBoost) model, a tree-based ensemble-learning algorithm, achieved grid-level probability of detection (POD), false-alarm ratio (FAR), and critical success index (CSI) values of 0.55, 0.50, and 0.36; segment-level verification yielded 0.60, 0.39, and 0.43. To examine transfer to forecast-driven application, the trained model and threshold were fixed, and ERA5 meteorological inputs were replaced by short-lead ECMWF HRES forecasts for July 2025. POD decreased from 0.85 to 0.80 and CSI from 0.60 to 0.57, while FAR remained nearly unchanged. Under a predefined non-zero rule, HRES litota1 achieved 0.62, 0.71, and 0.25. ML-HRES therefore showed higher CSI and lower FAR than the direct litota1 baseline. Full article

The bioconversion of semiconductor processing sludge (SPS) is conventionally bottlenecked by highly cross-linked extracellular polymeric substances (EPSs) that sequester concentrated inorganic salts. Forcible EPS deconstruction in single-stage anaerobic digestion triggers an abrupt release of these ions, inducing acute osmotic shock and systemic metabolic failure. To overcome this coupled thermodynamic and kinetic barrier, this study proposes a spatiotemporal decoupling framework utilizing waste resource sludge (WRS) as a physicochemical buffering matrix with a proposed ion-hydration/dielectric contribution. An engineered two-stage system was evaluated using controlled laboratory-scale anaerobic batch assays at 41 °C to segregate the initial acidogenic deconstruction from the subsequent methanogenic mineralization. Baseline single-stage digestion suffered severe paralysis, characterized by an electrical conductivity (EC) surge to 46.9 mS/cm and a negligible methane yield (14.5 mL CH₄/g VS). Conversely, the decoupled strategy effectively buffered the peak ionic stress to a safe threshold (15.8 mS/cm) and enhanced macromolecular liquefaction, achieving a 3.4-fold increase in soluble chemical oxygen demand. Consequently, the methanogenic stage delivered a maximum methane potential of 294.6 mL CH₄/g VS with a significantly shortened lag phase of 3.2 days. Molecular and taxonomic analyses confirmed that this enhanced performance was driven by structural EPS dismantling and a targeted microbial succession—transitioning from a robust Lactobacillaceae-dominated consortium for initial deconstruction to a diverse bacterial syntrophic network associated with methanogenic conversion. These findings establish the mechanistic feasibility of the proposed approach under controlled laboratory-scale batch conditions. Continuous-flow validation is nevertheless required to determine long-term process stability and engineering-scale applicability. Ultimately, this microenvironmental buffering approach provides a resilient, mild intervention pathway for extreme industrial waste, providing a potential mechanistic framework for future cross-industry resource circularity. Full article

Rainfall characteristics, differences in catchment storage, soil moisture dynamics, and geophysical properties influence spatial and temporal variability of runoff generation thresholds. This study addresses two questions: (1) Are there nonlinear thresholds of rainfall or antecedent moisture that trigger abrupt changes in agricultural catchments’ hydrological response? (2) What physical characteristics determine runoff generation? We analyzed precipitation and streamflow variability during the 2025–2026 hydrological year at three agricultural catchments (36.4–70.8 km²) in central Chile. Relying on high-resolution observational data and statistical segmented regression, this study focuses on how rainfall, soil moisture, and physical characteristics trigger runoff activation after exceeding specific thresholds. Based on 63 rainfall events, runoff occurred in only 16 events, demonstrating a strong nonlinear response governed by antecedent moisture. Segmented regression revealed consistent activation thresholds across all catchments when combined precipitation and deep soil moisture (PTOT + ASM100) exceeded ~505 mm, evidencing strong subsurface control. However, runoff efficiency diverged sharply along the land-use gradient. The most intensively agricultural catchment exhibited the highest specific peak discharge and a unique rainfall intensity threshold (14.6 mm/h), indicating rapid infiltration-excess runoff driven by degraded soil permeability. Conversely, catchments with higher headwater or riparian forest cover buffered these rapid flows, sustaining baseflow and extending recession times. Full article

Despite substantial advances in genomic testing, many individuals with neurodevelopmental disorders remain without a molecular diagnosis, while others receive a genetic diagnosis that does not fully explain phenotypic variability, developmental trajectory or tissue-specific consequences. Artificial intelligence (AI)-assisted methods are increasingly used for phenotyping, variant prioritisation, splice prediction, protein modelling, DNA methylation episignature classification and multi-omic analysis. However, these approaches differ substantially in evidentiary status and are often applied as separate prediction tasks rather than as components of an explicit mechanistic model. In this targeted narrative review, focused primarily on rare and genetically enriched neurodevelopmental disorders, we examine how AI-assisted methods may contribute to systems-level interpretation while remaining anchored to established molecular diagnosis and variant-classification frameworks. We propose a hypothesis-generating load-capacity framework comprising regulatory load, network capacity, developmental buffering and regulatory network instability. These are treated as operationalisable but currently unvalidated constructs. Regulatory instability is distinguished from stable disease-associated dysregulation, and threshold-like behaviour is presented as an empirical possibility rather than an assumed property of neurodevelopmental disease. We formulate five falsifiable predictions, consider how genomic, transcriptomic, epigenomic, single-cell, spatial, imaging, neurophysiological and longitudinal phenotypic evidence can provide complementary mechanistic constraints, and outline an auditable workflow following nondiagnostic genomic testing. We distinguish clinically implemented approaches from translational, emerging and conceptual applications, and emphasise calibration, evidence traceability, domain validity, prospective validation and appropriate abstention. Finally, we describe the Instability Twin as a prospective architecture composed of independently testable patient-specific sub-models rather than an existing clinical platform. The central proposition is that systems neurogenomics should be evaluated by whether mechanistically constrained integration provides reproducible information beyond established gene-level and simpler multimodal approaches. Full article

To address motion blur and the degradation of object detection performance caused by variations in industrial conveyor-belt speed, this paper proposes OIL, a closed-loop periodic batch adaptation framework. First, the framework employs a YOLOv8 detector incorporating the Global Attention Mechanism (GAM) and uses the Classification Index Weight (CIW), which consists of detection confidence and the temporal consistency of predicted bounding boxes between adjacent frames. Second, the detection results are divided into three intervals according to the CIW and its constituent metrics: interval A, with a CIW below 0.3; interval B, with a CIW between 0.3 and 0.5; and interval C, with a CIW above 0.5. Results in interval A are treated as negative samples, those in interval B as ambiguous samples, and those in interval C as positive samples. Positive samples are used to train the candidate model, ambiguous samples are stored in a buffer and re-evaluated in subsequent cycles, and negative samples are excluded from the current model update. Finally, when the accumulated number of positive samples reaches a predefined threshold, the system trains a candidate model using the baseline data and newly collected samples. The candidate model is then compared with the currently deployed model on a fixed manually annotated evaluation set. The candidate model is deployed only when its overall performance improves; otherwise, a rollback is performed. Experiments on a coal conveyor line demonstrate that, at 25× speed, incorporating OIL into YOLOv8 + GAM improves Recall by 34.3 percentage points compared with the same detector without OIL. In the variable-speed experiments ranging from 5× to 25×, Recall remained above 64.3%, indicating that the proposed framework can effectively suppress missed detections under high-speed operating conditions. Full article

Soil acidification threatens agroecosystems, yet the coupled, soil-specific proton-buffering mechanisms in permanent-charge soils (PCSs) and variable-charge soils (VCSs) remain insufficiently quantified. This study systematically investigated surface cation exchange, vacant site H⁺ sorption, and mineral dissolution, using batch and kinetic incubation experiments. Results showed that H⁺ buffering in PCSs was dominated by rapid, stoichiometric surface ion exchange, whereas approximately 42% of the total exchangeable acidity increment in VCSs originated from specific H⁺ sorption on vacant, high-affinity surface sites. VCSs exhibited ~10-fold-higher Langmuir proton sorption affinity and Temkin acid-buffering capacity than PCSs, driven by their more homogeneous, pH-dependent surface properties favoring inner-sphere coordination. Base cation release followed Ca²⁺ ≫ Mg²⁺ ≫ Na⁺ ≈ K⁺ across all soils; VCSs showed a twofold-higher Mg²⁺ pseudo-second-order rate constant and a strong Mg²⁺-Mn²⁺ positive correlation (R² > 0.804, p < 0.0001), exposing them to dual risks of Mn phytotoxicity and Mg deficiency during acidification. The well-fitted parabolic diffusion model for Al³⁺ and Mn²⁺ release further indicated prolonged, diffusion-limited metal toxicity risk in VCSs. A critical soil organic carbon (SOC) threshold of 8.1 g kg⁻¹ was identified, exceeding this value effectively retarded acidification via enhanced cation exchange capacity (CEC) and base retention. These findings provided a mechanistic framework for developing soil-specific strategies to manage and mitigate agricultural soil acidification. Full article