Search Results (78)

Soil moisture (SM) mediates land–atmosphere water and energy exchanges and is therefore central to evapotranspiration, drought evolution, and hydroclimate extremes. The SM drydown timescale (τ), typically derived from exponential decay fits following rainfall or snowmelt rewetting, provides a compact measure of near-surface “memory” and drying rate. Despite the availability of microwave satellite SM products, their reliability for drydown characterization over the Tibetan Plateau remains uncertain, and systematic evaluations of drydown events and τ against in situ networks are still limited. Here, we integrate five Tibetan Plateau (TP) soil moisture sensor networks with SMAP to (i) assess consistency in drydown event detection and τ estimation across observation systems and (ii) map TP-wide τ patterns and identify dominant controls using SMAP (2016–2025). SMAP-derived τ is generally smaller than in situ τ, indicating a faster drying signal in the satellite product; this may be attributed to differences in effective sensing depth and spatial representativeness between satellite footprints and point measurements. TP SMAP τ exhibits a pronounced southeast-to-northwest decreasing gradient, with the shortest τ over the arid interior. Partial least squares regression identifies elevation, sand fraction, and vegetation conditions as primary drivers of spatial τ variability. This research provides observational constraints for understanding land-surface hydrological processes and land–atmosphere coupling in alpine regions. Full article

Neural field dynamics in the cerebral cortex exhibit complex spatiotemporal patterns inadequately captured by classical integer-order diffusion models that assume exponentially decaying spatial interactions. This study establishes a stochastic fractional FitzHugh–Nagumo framework incorporating power-law spatial correlations through fractional Laplacian operators, providing explicit parameterization of non-local cortical connectivity characteristics. The inverse problem of estimating fractional orders and model parameters from electroencephalographic data is addressed through multi-objective optimization with rigorous train–test validation. Systematic sensitivity analysis across the parameter space $({\alpha }_u,{\alpha }_v)\in [1.0,2.0]\times [1.0,2.0]$ identifies optimal subdiffusive characteristics at ${\alpha }_u={\alpha }_v=1.5$, corresponding to power-law spatial kernels $C\left(x\right)\sim {\left|x\right|}^{-1.5}$ consistent with anatomical connectivity measurements. The optimized model achieves out-of-sample performance $R^2=0.973$ on held-out test data, approaching the measurement noise ceiling. While classical FitzHugh–Nagumo models achieve comparable test accuracy, the fractional framework provides enhanced interpretability through explicit spatial interaction parameterization. The fractional orders serve as quantitative biomarkers of cortical network organization, enabling data-driven characterization across brain states and neurological conditions. The methodology establishes computational foundations for clinical applications in epilepsy monitoring, neurodegenerative disease detection, and brain–computer interfaces. Full article

This study presents and systematizes a high-reliability measurement and technological dataset suitable for prediction-based validation of the Spent Fuel Interim Storage Facility (SFISF) of the Paks Nuclear Power Plant. The primary objective of this dataset is not the validation of a general-purpose software tool, but to establish a reproducible experimental basis for the objective and quantitative validation of a three-dimensional, facility-scale heat transfer and buoyancy-driven flow model of the SFISF, developed using the finite difference method (FDM), in a passively cooled system where heat conduction, thermal radiation, and natural convection simultaneously occur. The applied measurement systems (SMAS, CTRS, and the in-house developed CFEPR), their spatial arrangement, accuracy characteristics, as well as data post-processing and the generation of model execution inputs are described in detail. Special emphasis is placed on the functional separation of the available data into initialization data, model execution data, and independent validation datasets, ensuring that model assessment does not rely on calibration or parameter fitting. Furthermore, the estimation of decay heat generated by the stored fuel assemblies is presented using both a standard correlation method (ANSI/ANS-5.1) and isotope inventory-based calculations, and the discrepancies between these approaches are treated as input uncertainties and sensitivity analysis factors. The spectral solar load is considered based on the ASTM G-173 reference spectrum, while during cloudy periods an effective irradiance estimation derived from on-site lux measurements is applied. The results indicate that the available measurement and technological information is sufficient for supporting reproducible, transparent, and quantitative validation studies of the three-dimensional numerical model of the SFISF, as well as for assessing the impact of dominant input uncertainties. Full article

Rapid advances in digital technologies are reshaping value creation and the trade landscape of global financial services, yet the channels through which they influence the spatial evolution of financial services global value chains (GVCs) remain insufficiently identified. Using a global panel of 52 countries over 2013–2021, we estimate a dynamic Spatial Durbin Model (SDM) to identify overall effects and quantify spatial spillovers and temporal dynamics. We then combine Geographically and Temporally Weighted Regression (GTWR) with spatial mediation models to examine heterogeneity and underlying mechanisms. Our findings show that digital technology significantly drives the spatial evolution of financial services GVCs. Its influence is dominated by spatial diffusion, exhibiting a dynamic pattern of a strong short-run boost followed by long-run reallocation. This dynamic effect is not homogeneous; rather, it reflects a pronounced dual-driver structure: the momentum is more robust when human capital and R&D output reinforce each other, whereas increases in innovation level alone are unlikely to translate into sustained impetus for spatial restructuring. Crucially, digital technologies reshape GVC geography through three core channels: attenuating distance decay, strengthening spatial proximity, and amplifying spatial heterogeneity. These forces deepen the domestic diffusion of knowledge, capital, and technology and extend their spillovers to neighboring and connected economies. The results provide robust empirical evidence on financial geography in the digital era and have clear implications for policies that facilitate cross-border financial services and strengthen regional coordination in support of the 2030 Agenda for Sustainable Development, particularly SDG 8 (financial inclusion) and SDG 10 (global financial governance). Full article

Back focal plane (BFP) imaging has emerged as a widely used technique for investigating various nanoscale optical devices. The ability to provide the full angular distribution of emitted light has enabled the engineering of precise radiation patterns, enabling new advances in nanophotonics. Continuous improvements in the BFP imaging technique, including wavelength, polarization, and phase-resolved signal detection, have allowed us to gain crucial insights into the various optical and material properties of nanophotonic devices. In this study, we introduce a fluorescence lifetime-resolved BFP imaging configuration, which uses a spatial filtering technique in the Fourier plane to discriminate between different emission directions. Uniform silver film (45 nm) with a PMMA matrix layer of about 20 nm containing Rhodamine 6G fluorescent molecular dye was prepared and measured using total internal reflection ellipsometry (TIRE). A coupled oscillator model was used, and strong coupling was observed with a coupling strength of 160 meV. Time-correlated single-photon counting was used for the estimation of fluorescence lifetime in the sub-nanosecond regime, and a direction-dependent lifetime was observed in the BFP imaging configuration. This modified fluorescence-lifetime-resolved BFP microscopy method is essential for directly correlating the collective quantum dynamics (lifetime/decay rate) with the far-field radiation pattern (angle/coherence). It offers a critical tool for designing and optimizing quantum nanophotonic devices, such as polariton-based components and highly directional single-photon emitters, where controlling both excited-state dynamics and spatial coherence is paramount. Full article

Cultural tourism has become an increasingly significant phenomenon in urban areas, especially in cities rich in heritage sites. However, when the number of visitors exceeds sustainable capacity thresholds, both the physical and psychological comfort and safety of individuals may be compromised. A higher number of visitors inside historic buildings leads to elevated concentrations of carbon dioxide (CO₂), particularly in poorly ventilated enclosed or confined spaces, primarily as a result of human respiration. Such conditions not only accelerate the deterioration processes affecting heritage materials but also introduce potential health risks for visitors. Parameters such as CO₂ concentration, indoor air temperature, and relative humidity represent key measurable parameters for assessing environmental Indoor Air Quality (IAQ) within heritage buildings. Digital real-time monitoring of these parameters plays a crucial role in preventive heritage conservation, sustainable site management, and in ensuring visitors’ comfort and well-being. This paper presents a procedure and methodology that use digital technological tools to efficiently estimate and monitor the Visitor Carrying Capacity (VCC) of enclosed/confined heritage spaces, especially Heritage Building Information Modelling (HBIM) and Sensor Technology. These kinds of spaces require particular attention due to their spatial characteristics. In order to do so, it is necessary to know the geometry of the site, and to consider IAQ conditions. This study also considers the number of People at One Time (PAOT) and Visitor Occupancy (VO). The results focus on the procedural development of the analysis and emphasise the role of digital tools not only due to their efficiency and accuracy in spatial analysis for estimating VCC, but especially for the real-time monitoring of visitors and surveying specific environmental parameters. The experimental phase of this study uses the Chapel of the Holy Chalice of the Valencia Cathedral (Spain) as a pilot case. Monitoring this space reveals how quickly high CO₂ levels are reached with continuous visitor presence, and how long it takes for them to decay in absence of people and under passive ventilation conditions. The outcome of this research is a detailed methodological framework designed to assess and monitor Visitor Carrying Capacity (VCC) in enclosed/confined heritage sites by integrating digital technologies, thereby enhancing sustainable management, planning and decision-making processes. Full article

Self-supervised monocular depth estimation from oblique UAV videos is crucial for enabling autonomous navigation and large-scale mapping. However, existing self-supervised monocular depth estimation methods face key challenges in UAV oblique video scenarios: depth discontinuity from geometric distortion under complex viewing angles, and spatial ambiguity in weakly textured regions. These challenges highlight the need for models that combine global reasoning with geometric awareness. Accordingly, we propose RMTDepth, a self-supervised monocular depth estimation framework for UAV imagery. RMTDepth integrates an enhanced Retentive Vision Transformer (RMT) backbone, introducing explicit spatial priors via a Manhattan distance-driven spatial decay matrix for efficient long-range geometric modeling, and embeds a neural window fully-connected CRF (NeW CRFs) module in the decoder to refine depth edges by optimizing pairwise relationships within local windows. To mitigate noise in COLMAP-generated depth for real-world UAV datasets, we constructed a high-fidelity UE4/AirSim simulation environment, which generated a large-scale precise depth dataset (UAV SIM Dataset) to validate robustness. Comprehensive experiments against seven state-of-the-art methods across UAVID Germany, UAVID China, and UAV SIM datasets demonstrate that our model achieves SOTA performance in most scenarios. Full article

In recent years, the rapid expansion of urban rail transit has significantly improved travel efficiency, yet it has also exacerbated spatial inequality in service coverage. Accessibility, as a fundamental metric for evaluating the equity of service distribution, remains limited by three major shortcomings in current assessment methods: the neglect of actual road network characteristics, reliance on a single static scale, and the absence of quantitative mechanisms to assess accessibility equity. These deficiencies hinder a comprehensive understanding of how equity evolves with the spatiotemporal dynamics of rail systems. To address the aforementioned issues, this study proposes an innovative spatiotemporally dynamic and multi-scale analytical framework for evaluating urban rail accessibility and its equity implications. Specifically, we develop a network-based buffer decay model to refine service population estimation by incorporating realistic walking paths, capturing both distance decay and road network constraints. The framework integrates multiple spatial analytical techniques, including the Gini coefficient, Lorenz curve, global and local spatial autocorrelation, center-of-gravity shift, and standard deviation ellipse, to quantitatively assess the equity and evolutionary patterns of accessibility across multiple spatial scales. Taking the central urban area of Hangzhou as a case study, this research investigates the spatiotemporal patterns and equity changes in metro station accessibility in 2019 and 2023. The results indicate that the expansion of the metro network has partially improved overall accessibility equity: the Gini coefficient at the TAZ (Traffic Analysis Zone) scale decreased from 0.56 to 0.425. Nevertheless, significant inequality remains at finer spatial resolutions (grid-level Gini coefficient = 0.404). In terms of spatial pattern, the core area (e.g., Wulin Square) forms a ‘high-high’ accessibility agglomeration area, while the urban fringe area (e.g., northern Yuhang) presents a ‘low-low’ agglomeration, and the problem of local ‘accessibility depression’ still exists. Additionally, the accessibility centroid has consistently shifted northwestward, and the long axis of the standard deviation ellipse has rotated from an east–west to a northwest-southeast orientation, indicating a growing spatial polarization between core and peripheral zones. The findings suggest that improving equity in urban rail accessibility cannot rely solely on expanding network size; rather, it requires coordinated strategies involving network structure optimization, branch line development, multimodal integration, and the construction of efficient transfer systems to promote more balanced and equitable spatial distribution of rail transit resources citywide. Full article

This study delves into the spatial characteristics of solutions for a specific class of evolution equations that incorporate biharmonic operators. The process begins with the construction of an energy function. Subsequently, by employing an integro-differential inequality method, it is deduced that this energy function satisfies an integro-differential inequality. Resolving this inequality enables us to establish an estimate for the spatial decay of the solution. Ultimately, the finding affirms that the spatial exponential decay is reminiscent of Saint-Venant-type estimates. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

Urban heritage materials face accelerated decay due to the synergistic effects of air pollution and climate change. Dose–response functions (DRFs) have emerged as a key tool to quantify and predict these risks. This review synthesizes the scientific development of DRFs, their application in Europe and China, and their role in policy and heritage management. European initiatives have refined DRFs to incorporate multi-pollutant and climate interactions, providing spatial risk maps and informing pollution control measures. In China, recent applications adapt European insights to local contexts, revealing strong influences of particulate matter. While DRFs offer clear quantitative estimates, their empirical nature and simplified assumptions necessitate complementary methods, including sensor networks, remote sensing, and machine learning models. Future research should integrate multivariate modelling, expand empirical data, and couple DRFs with real-time monitoring to better protect urban heritage materials amid environmental change. Full article

Coordinating development of land urbanization and population urbanization (CDLUPU) to enhance carbon emission efficiency (CEE) is a critical challenge for developing countries experiencing accelerated urbanization. The coupled coordination model and super efficiency SBM are employed to estimate the levels of CDLUPU and CEE across 276 prefecture-level cities from 2010 to 2021. Furthermore, we utilize kernel density estimation and Spatial Durbin Model (SDM) to explore the spatio-temporal distribution characteristics and spatial effects. The results indicate that CDLUPU levels exhibited a sustained upward trend with diminishing regional disparities, whereas CEE displayed a pattern of initial growth followed by decline. Spatial analyses revealed a consistent gradient structure for both CDLUPU and CEE, characterized by radiation decay from southeastern coastal hubs toward interior hinterlands. CDLUPU exerts a significant positive direct impact and spatial spillover effect and indicates that the spillover effects on peripheral regions are substantially stronger than local effects. Regional heterogeneity analysis reveals that CDLUPU negatively affects CEE in eastern China, the Yangtze River Delta (YRD) is more pronounced, but it positively impacts central and western China, as well as Beijing–Tianjin–Hebei (BTH) and Chengdu–Chongqing (CY). Regarding indirect effects, eastern China shows significant positive impact on CEE, and similarly in the YRD. However, central China exhibits a negative effect, whereas BTH shows the opposite trend. Western China and CY show statistically insignificant results. This study offers policy insights for China to coordinate new urbanization strategy and achieve the “dual carbon goal”. Full article

Urban parks are essential for enhancing public health and environmental sustainability, as they reduce urban heat, improve air quality, and provide spaces for physical activity. Inequalities in park allocation, however, lead to access discrepancies, disproportionately impacting populations already struggling socially. The spatial disparity between park supply and demand in Busan, South Korea, is examined in this study through a quantitative approach incorporating socio-economic indicators and GIS(Geographic Information System)-based analysis. First, we divided Busan into 100 m × 100 m grid cells and applied a modified Huff model, setting a kind of distance-decay exponent β, to estimate park supply against baseline demand (the planning standard of 6 m² per person), and overlaid a composite need index of six socio-economic indicators to pinpoint underserved areas. Our first stage grid-based arithmetic analysis revealed that 100 of Busan’s 205 communities are undersupplied. Given a composite need index of six socio-economic indicators, sixty-two cells remained imbalanced, and we finally identified the ten communities with the highest need for targeted park provision. The findings indicate that Busan’s park planning policies, aimed at enhancing per capita green space, do not adequately address localized disparities. Accordingly, as opposed to a uniform expansion plan, this study stresses the importance of prioritizing park provision according to community-specific needs. These results suggest that policymakers could enhance public health outcomes and advance social equity by considering socio-economic vulnerabilities when planning cities. Specifically, this research highlights the significance of including environmental justice in urban sustainability frameworks and gives actionable ideas for fair park allocation. Full article

Reforestation is widely promoted as a nature-based solution for climate change, yet its unintended consequences, such as deforestation leakage, remain under-investigated. This study provides empirical evidence of reforestation-induced leakage in the Brazilian Amazon, using municipality-level panel data from 2000 to 2023 and spatial Durbin panel models to estimate both the magnitude and spatial reach of agricultural displacement. Despite the positive local effects of reforestation projects, we found a significant displacement of deforestation to the vicinity of municipalities. We estimated a statistically significant deforestation leakage effect of approximately 12% from the reforested area, due to the agricultural displacement of cattle ranching activities. Spatial spillovers are strongest within a 150 km radius and within two years after reforestation onset. Sensitivity tests using alternative spatial weight matrices, including distance decay and land rent-weighted specifications, confirm the robustness of these findings. Livestock intensification, proxied by cattle stocking rates, does not significantly mitigate displacement effects, challenging assumptions about land sparing benefits. These results suggest that current carbon market protocols (e.g., Verra, ART-TREES) may improve their leakage analysis to avoid under- or over-estimating net carbon benefits. Incorporating spatial econometric evidence into offset methodologies and reforestation planning can improve climate policy integrity and reduce unintended environmental trade-offs. Full article

After entering deep mining, coal mines often experience various intense dynamic load phenomena due to increasingly complex geological conditions, which can lead to secondary disasters, where it is urgent to identify their sources and analyze their disaster-causing effects. This article takes the 3310 working face in Gu Cheng Coal Mine as the engineering background, and uses theoretical analysis, numerical simulation, on-site monitoring, and other methods to analyze the spatial and temporal distribution of dynamic load events during the mining period of this face. The study classifies dynamic load events based on this background into roof-type, fault-type, and coal pillar-type classes, revealing the differences in the spectra, waveforms, and disaster-causing effects of each class. The results show that the strong dynamic load events are mainly concentrated in the working face roof and fault zone areas. The first principal frequency of the three classes has an estimated boundary between 30 and 60 Hz. The waveform decay coefficients of the roof-type, coal pillar-type, and fault-type strong dynamic load events have average values of 4.53, 1.57, and 1.41, respectively. By adopting the above research methods, a theoretical basis can be provided for the source of dynamic loads, thereby achieving source-based prevention and control of rock burst. Full article