Search Results (165,718)

Digital technology has been recognized as a pivotal force in optimizing land use patterns, particularly in enhancing the green utilization efficiency of urban land. In this study, panel data from 219 cities across China covering the 2013–2023 period are used to investigate the impact of urban digital transformation (UDT) on land green use efficiency (LGUE) and the underlying mechanisms involved. The spatiotemporal evolution of LGUE demonstrates a clear upward trend over time and hot spots of LGUE are mainly concentrated in coastal cities. The findings reveal that UDT significantly enhances LGUE, a conclusion that remains robust across multiple checks and an instrumental variable approach. Mechanism analyses indicate that a market-oriented allocation of data elements, green technological innovation, and optimization of the labor skill structure serve as plausible channels driving this improvement. Importantly, spatial Durbin model analysis confirms a significant positive spatial spillover effect, indicating that local digital transformation also radiates to benefit the green land utilization of neighboring cities. Finally, heterogeneity analyses reveal that the positive effects of digital transformation on LGUE are notably more pronounced in larger cities and those with advanced internet development. Furthermore, the impacts exhibit structural divergence across specific digital dimensions, with economic digitalization significantly driving LGUE, whereas social digitalization exerts a negative effect. Full article

To address the challenges of susceptibility to interference and limited accuracy inherent in conventional gas flow rate measurement methods, this paper proposes and investigates a laser Doppler gas flow rate measurement method based on synchronous three-point velocity measurement. This method simultaneously measures the flow velocities at three characteristic points within the pipeline cross-section, subsequently fits and reconstructs the velocity distribution across the entire profile, and ultimately achieves high-precision flow measurement. The feasibility of selecting the center point, the quarter-width point, and the near-wall point as the three characteristic measurement positions is analyzed through computational fluid dynamics simulations, and the full-profile velocity distribution is fitted accordingly. A three-point synchronous velocity-flow rate measurement system is designed and constructed, employing a transmitting optical path based on the “three beam splitters and two mirrors” scheme and a receiving optical path based on the “multi-lens independent reception” scheme, and experimental validation is conducted. Experimental results demonstrate that the system operates stably with good repeatability. In contrast to the flow calculation method using a single-point Pitot tube combined with an empirical formula, the proposed system, which directly fits the velocity profile and integrates it for flow calculation, effectively avoids the significant model errors caused by using fixed empirical coefficients in non-circular pipe flows, and is inherently more universally applicable in principle. Through comparison with the TSI reference standard (3D LDV), the measurement results of the proposed system are in close agreement with the reference values, with relative errors all below −0.8%. This paper provides an effective solution for high-precision gas flow measurement in square pipelines. Full article

Background/Objectives: The optimal surgical approach for Percutaneous KyphoPlasty (PKP) in patients with recent single-level Osteoporotic Vertebral Compression Fractures (OVCFs) remains controversial. Most available previous meta-analyses included studies with variable heterogeneity, often mixing unilateral and bilateral MIS approaches, differing surgical techniques, and various fracture patterns, which limited the reliability of their conclusions. This meta-analysis aimed to compare the efficacy and safety of unilateral versus bilateral PKP exclusively in patients with recent single-level OVCFs only. Methods: A systematic review was conducted according to the PRISMA 2020 guidelines. PubMed, Scopus, Cochrane Library, and ScienceDirect were searched for comparative studies published between 2000 and 2025. Randomized Controlled Trials (RCTs), prospective, and retrospective comparative studies comparing unilateral and bilateral PKP for recent single-level OVCFs were included. Clinical and radiological outcomes as well as perioperative complications and safety outcomes were analyzed using random-effects meta-analysis. Predefined subgroup analyses according to study design and sensitivity analyses were performed. Results: Eleven studies involving 1374 patients (705 unilateral and 669 bilateral PKP) met the inclusion criteria. No significant differences were observed between the two surgical approaches regarding short- or long-term pain relief, cement leakage, number of adjacent vertebral fractures, or overall clinical outcomes. Bilateral PKP demonstrated statistically significant, but clinically negligible, advantages in anterior vertebral body height restoration and kyphosis correction. Unilateral PKP required an insignificantly lower cement volume. For operative time, the overall pooled estimate favored unilateral PKP by approximately 10 min but showed extreme heterogeneity (I² = 98.5%). Importantly, the two RCTs showed no statistically significant between-group difference (MD = +1.2 min, 95% CI −4.5 to +6.8), indicating that the apparent overall effect was largely driven by observational evidence. Similar discrepancies between randomized and retrospective studies were observed for several other outcomes, underscoring the importance of considering study design when interpreting the results. Conclusions: Current evidence does not demonstrate clinically meaningful superiority of either unilateral or bilateral PKP for the treatment of recent single-level OVCFs. Bilateral PKP may provide small advantages in selected radiographic outcomes, whereas unilateral PKP uses modestly less bone cement; however, the relevance of these differences remains clinically uncertain. Surgical approach selection may therefore be individualized according to vertebral morphology, pedicle anatomy, fracture characteristics, surgeon experience, and technical feasibility rather than expectations of superior clinical outcomes. Further adequately powered randomized trials with standardized outcome reporting and long-term follow-up are warranted. Full article

To support the early identification of potential drowning-risk states and improve rescue response efficiency, this paper proposes a UAV-oriented dual-scale detection-pose cascade for frame-level drowning-risk recognition. The framework first performs high-recall preliminary detection on wide-field input images to identify potential drowning targets. The detected target regions are subsequently extracted and resized to construct localized inputs for the second-stage pose-based verification. This software-based target-region refinement simulates the localized high-resolution observation that could be provided by a telephoto camera in a future physical dual-camera UAV implementation. By focusing subsequent analysis on the localized target regions, the second-stage pose model can exploit finer-scale human structural information for drowning-risk state verification, thereby providing decision support for potential drowning detection. To address the challenges of small target scales and severe background interference in wide-field images, a lightweight YOLOv8n-based detection model is developed. An enhanced edge-feature-guided residual convolutional block attention module (EGRCBAM) is introduced, together with a recall-oriented FPIoU loss function designed for hard sample optimization, improving the recall of the drowning category by 17%. For localized target verification, an enhanced YOLOv8n-Pose model is constructed by incorporating a coordinate-aware pose head, spatial attention mechanism, and skeletal structure constraints to enhance human-region localization and pose-based drowning-versus-swimming recognition. The model improves Box mAP@0.5 from 0.768 to 0.816. Comparative experiments on the self-collected dataset demonstrate the effectiveness of the proposed detection and pose-based verification framework. The proposed framework provides a lightweight vision-based solution or UAV-oriented frame-level drowning-risk recognition and offers a potential algorithmic basis for future integration with physical dual-camera UAV platforms. Full article

To mitigate clay hydration and wellbore instability during deepwater drilling, a pH/temperature dual-responsive graft copolymer, hyperbranched polyethylenimine-g-poly(2-(dimethylamino)ethyl methacrylate) (HPEI-g-PDMAEMA), was designed and synthesized via free radical polymerization. Optimized synthesis at an HPEI/DMAEMA mass ratio of 1:2 with 2.4% AIBN at 70 °C for 10 h yielded a grafting ratio of 35.2% and a molecular weight of 84.3 kDa. The copolymer exhibits a tunable lower critical solution temperature (LCST) of approximately 48 °C at pH 8, decreasing with increasing pH due to tertiary amine deprotonation. Zeta potential measurements confirm that the polymer retains a positive charge (+5 mV at pH 8) under weakly alkaline conditions, enabling strong electrostatic anchoring onto negatively charged clay surfaces. Above the LCST, dynamic light scattering reveals a sharp increase in hydrodynamic diameter from ~30 nm to >200 nm, confirming a hydrophilic-to-hydrophobic transition of PDMAEMA segments that drives the formation of a hydrophobically associated gel barrier. This thermally triggered gelation is fully reversible, as evidenced by repeated heating–cooling cycles with almost complete transmittance recovery. The gel barrier drastically reduces water uptake, with inhibition performance against clay swelling at 60 °C being 18.5 percentage points higher than that at 25 °C. Hot-rolling tests demonstrate that with only 1.5 wt% inhibitor, shale recovery reaches 94.1% at 150 °C (8.8 percentage points higher than unmodified HPEI) and remains above 60% even in 20 wt% CaCl₂ or MgCl₂ brines, highlighting exceptional resistance to divalent cations. Water contact angle on treated clay surfaces increases from 18.5° to 52.6°, confirming effective surface hydrophobization. This work provides a molecular-level gel-engineering strategy where pH governs electrostatic anchoring and temperature triggers reversible hydrophobic gelation, enabling on-demand switching of clay wettability and hydration resistance under high-temperature, high-salinity conditions. Full article

Multivariate time series forecasting requires modeling both hierarchical temporal dynamics and complex inter-variable dependencies, a dual requirement that often degrades predictive performance and incurs high computational costs in standard Transformer architectures. Unlike current channel-independent models that ignore vital cross-variable synergies, or dense-attention frameworks that suffer from quadratic computational noise, our approach extracts structurally sparse dependencies. To address these specific limitations, this study introduces the FCA-Transformer. The proposed framework integrates a Feature Pyramid Network (FPN) to isolate macroscopic trends from high-frequency localized fluctuations via hierarchical downsampling. Concurrently, a structured Transformer-based Cross-Attention (TCA) mechanism employs Dimensional Segmentation with Weighting (DSW) and a Two-Stage Attention (TSA) layer to map topological variable interactions, effectively extracting robust cross-variable pathways and mitigating distributional noise. Extensive empirical evaluations across three real-world multivariate benchmarks (ETTh1, Electricity, and Exchange Rate) demonstrate that the FCA-Transformer achieves an average reduction of up to 4.39% in MSE and 5.11% in MAE compared to leading baselines. These findings indicate that the proposed architecture successfully reconciles multi-scale feature extraction with lightweight dependency modeling, enhancing structural generalization and providing a scalable framework for real-time temporal analysis in complex industrial environments. Full article

Multi-product production systems require effective coordination among production, intermediate storage, downstream processing, and customer demand, particularly under stochastic operating conditions and finite capacity. Unlike existing analytical studies that mainly examine either single-product push–pull systems or multi-product manufacturing systems separately, this work develops an exact CTMC framework that jointly captures product variety, shared buffering, downstream parallelization, sequence-dependent setups, and machine unreliability. The system comprises an unreliable upstream machine with sequence-dependent setup changes, a finite intermediate buffer, a distribution center modeled as a pooled processing resource with (M) identical reliable channels, and dedicated finished-goods buffers serving product-specific demand. A high-dimensional continuous-time Markov chain is formulated, and a systematic algorithm is developed to construct the infinitesimal generator matrix and compute steady-state performance measures. Numerical experiments examine intermediate buffer capacity, downstream processing capacity, priority rules, and upstream machine reliability. Increasing buffer capacity from 0 to 20 increases total throughput from 0.5937 to 1.0988, whereas further expansion to 100 yields only 1.1606, while average work-in-process reaches 19.8524. Downstream capacity exhibits similar diminishing performance gains, while priority rules and machine reliability affect product-level and overall throughput. These findings highlight throughput–inventory trade-offs and demonstrate the framework’s applicability for evaluating alternative configurations. Full article

High-temperature proton-exchange membrane fuel cells (HT-PEMFCs) generate useful thermal energy that can be recovered for additional power production. This study investigates an integrated HT-PEMFC–organic Rankine cycle (ORC) system by combining response surface methodology (RSM) with thermodynamic energy analysis. A 17-run response-surface design was used to quantify the effects of pressure, temperature, and current density on polarization voltage. Power density was derived directly from the RSM-predicted voltage using P_d = iE to preserve physical consistency. The electrochemical model was benchmarked against published phosphoric-acid-doped polybenzimidazole HT-PEMFC polarization data under comparable conditions. The constrained optimization identified an operating condition of 400 kPa, 443 K, and approximately 1.198 A cm⁻², giving a predicted voltage of 0.5395 V and a power density of approximately 0.6462 W cm⁻². This represents a 12.9% increase in power density relative to the adopted reference condition. Separately, the reference thermodynamic case produced 13.08 kW of gross HT-PEMFC stack electrical power and 15.45 kW of thermal output assumed available to the ORC. The available legacy R409A reference case was evaluated at an evaporator pressure of 2 MPa, yielding approximately 1.24 kW of ORC net power and a net thermal efficiency of about 8.02%. The resulting combined modeled electrical output was approximately 14.32 kW before unmodeled balance-of-plant auxiliary power consumption, with the ORC contribution corresponding to about 9.5% of the gross HT-PEMFC stack output. The results demonstrate the complementary potential of physically consistent HT-PEMFC operating-condition optimization and waste-heat recovery, while the ORC results remain specific to the retained R409A reference dataset. Full article

Despite the robust mechanical and chemical stability that make hollow flat-sheet ceramic membranes highly attractive for membrane bioreactors (MBRs), the fundamental relationship between their structural design, specifically pore size and structural symmetry, and biological fouling behavior remains elusive. To decouple the effects of membrane architecture on fouling mechanisms, a series of symmetric and asymmetric hollow flat-sheet alumina membranes were systematically engineered. Symmetric architectures with tunable pore sizes were fabricated by controlling aggregate particle sizes, whereas asymmetric counterparts featuring distinct separation layer thicknesses were developed via a tailored dip-coating process. Long-term operational evaluations treating municipal wastewater uncovered a counterintuitive phenomenon. Asymmetric membranes, despite yielding superior retention, experienced markedly accelerated transmembrane pressure evolution and severe cake layer fouling compared to the symmetric supports. Resistance-in-series analysis coupled with classical filtration models demonstrated that thicker separation layers and larger pore sizes were associated with shifts in the dominant fouling mechanism toward rapid and dense cake layer formation, which significantly exacerbated irreversible biological fouling. Furthermore, advanced spectroscopic and high-throughput sequencing techniques revealed that structurally complex asymmetric layers were associated with shifts in extracellular polymeric substances and specific fouling-associated bacterial phyla at the membrane interface. Ultimately, these findings underscore the necessity of architectural optimization to mitigate biofouling and prolong the operational lifespan of ceramic membranes, highlighting the sustainable advantages of symmetric structures. Full article

The spatial distribution of different hard magnetic phases is a key factor affecting the coercivity of dual-main-phase rare-earth permanent magnets. However, the underlying relationship between main-phase distribution and magnetization reversal behavior in Nd₂Fe₁₄B/Dy₂Fe₁₄B magnets remains unclear. In this work, micromagnetic simulations based on MuMax3 and OOMMF are performed to systematically investigate the effects of main-phase spatial arrangement on the magnetic properties and magnetization reversal mechanisms of Nd₂Fe₁₄B/Dy₂Fe₁₄B exchange-coupled magnets. First, single-phase Nd₂Fe₁₄B and Dy₂Fe₁₄B models are constructed to clarify the intrinsic magnetic characteristics of the two phases. The calculated demagnetization curves show that, although the magnetocrystalline anisotropy field H_A of Nd₂Fe₁₄B is lower than that of Dy₂Fe₁₄B, its higher saturation magnetization M_S results in a slightly larger anisotropy constant K, according to K = ${\displaystyle \frac{1}{2}}$µ₀·H_A·M_S. Nevertheless, Dy₂Fe₁₄B exhibits a stronger resistance to magnetization reversal, as reflected by its higher nucleation field H_N and coercivity H_C. This indicates that the resistance to magnetization reversal is more directly associated with H_A than with K alone. Subsequently, three types of exchange-coupled dual-main-phase Nd₂Fe₁₄B/Dy₂Fe₁₄B magnet models, including cubic, cylindrical, and sandwich structures, are constructed with identical size fractions of the two phases to investigate the influence of phase spatial distribution on magnetization reversal behavior. The calculated results demonstrate that placing the Dy₂Fe₁₄B phase in the outer region leads to higher H_Nand H_C than the reverse phase arrangement, owing to its higher H_A, which strengthens the resistance against magnetization reversal. Further analysis of the in-plane magnetic-moments and angular distributions reveals that magnetic-moment deviation is initially activated in the Nd₂Fe₁₄B region with lower H_A, followed by gradual propagation through exchange coupling at the phase interface. This effect of phase spatial distribution is not limited to Nd₂Fe₁₄B/Dy₂Fe₁₄B exchange-coupled magnets. In Nd₂Fe₁₄B/La₂Fe₁₄B and Nd₂Fe₁₄B/SmCo exchange-coupled magnets, placing the phase with the higher H_A in the outer region likewise results in higher H_Nand H_C than the reverse phase arrangement. In addition, for all the dual-main-phase exchange-coupled magnets considered above, the coercive field decreases with increasing magnet size. These findings provide theoretical insights into the regulation of coercivity through spatial phase distribution in dual-main-phase rare-earth permanent magnets. Full article

Zinc oxide nanoparticles (ZnO NPs) are widely used in biomedical, agricultural, and industrial applications, raising concerns about their potential hepatotoxicity. This study investigated the effects of 28-day oral ZnO NP exposure on hepatic function, oxidative stress, apoptosis, inflammatory signaling, and microRNA expression in rats. Sixty male Wistar albino rats were allocated to three groups (n = 20 each),control, low dose (30 mg/kg), and high dose (100 mg/kg), and treated by oral gavage. The administered material had a nominal particle size of 50 nm and a supplier-stated purity of 99.9%. Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST), hepatic malondialdehyde (MDA) and reduced glutathione (GSH), histopathology, immunohistochemistry, mRNA expression, and hepatic microRNAs were assessed. ZnO NPs induced dose-related liver injury: ALT increased from 31.26 ± 2.5 to 75.48 ± 12.3 IU/L, while AST increased from 32.47 ± 4.1 to 85.57 ± 18.9 IU/L. Hepatic MDA increased, whereas GSH increased at the low dose but was depleted at the high dose. Histopathology demonstrated sinusoidal congestion, hepatocellular necrosis, and inflammatory infiltration. Immunohistochemistry indicated reduced B-cell lymphoma 2 (Bcl-2) and increased caspase-3 and tumor necrosis factor-alpha (TNF-α) immunoreactivity. Interleukin-6 (IL-6) and heme oxygenase-1 (HO-1) were upregulated, whereas superoxide dismutase 2 (SOD2) was downregulated. At the high dose, miR-122-5p, miR-34a-5p, and miR-21-5p increased by 8.74-, 6.53-, and 4.38-fold, respectively (all p< 0.05). Their expression levels were also strongly and positively correlated with biochemical, oxidative, and histopathological indicators of liver injury. These findings indicate that ZnO NP exposure is associated with oxidative, inflammatory, apoptotic, and microRNA responses; the altered hepatic microRNAs may represent candidate tissue indicators of ZnO NP-induced liver injury. Full article

Robot mobile fulfillment systems (RMFSs), as human–robot collaborative smart warehouses, transform the traditional person-to-goods order picking mode into a goods-to-person mode. Order picking optimization is a core decision-making challenge in RMFSs to improve the efficiency of the system, which needs to jointly optimize pod selection, robot scheduling, station assignment, and manual picking. Although recent studies have widely investigated integrated operational optimization in RMFSs, most of them rely on deterministic transportation and processing time and ignore uncertainties in practical human–robot collaborative operations. It remains challenging to jointly optimize these coupled decisions under uncertain operation times. To address this challenge, we model the concerned problem with the objective of minimizing fuzzy makespan and design an adaptive large-neighborhood-based variable neighborhood descent algorithm to efficiently solve it. The algorithm adopts three-dimensional coupling encoding and multi-stage heuristic decoding mechanisms. It further integrates a learning-based adaptive destroy operator selection method and a variable neighborhood descent search strategy to enhance its exploration and exploitation abilities. In a large number of systematic experiments, ALVND achieved great performance in solving the concerned problem. The objective function value obtained by it was 5.6–25.1% lower than its competitors, demonstrating its effectiveness in uncertain human–robot collaborative warehouse scenarios. Full article

The rubber cylinder is the core sealing element of a compression packer, and its structural stability directly determines downhole sealing reliability. The rubber cylinder is made of HNBR, while the central tube, support rings, and casing are made of 35 CrMo steel. During axial compression, the rubber cylinder may undergo localized creasing instability characterized by sharp self-contacting folds, inducing severe stress concentration and degrading sealing performance. This paper presents a systematic finite element investigation of creasing behavior in rubber cylinders, focusing on meshing strategy, interfacial friction, and geometric parameters. A refined meshing strategy is proposed that captures creasing and self-contact, demonstrating that a mesh size less than 0.5 mm is required. A zone-specific friction model distinguishes the tribological roles of different interfaces: increasing friction at the support ring suppresses shoulder protrusion, while increasing friction at the central tube reduces contact stress. For the packer geometries and operating conditions investigated, the critical expansion ratio at which the crease initiates is approximately 1.13. Increasing rubber cylinder length and reducing radial clearance are identified as effective measures to suppress creasing. The logarithmic strain at crease nucleation is approximately −0.66, which is more negative than the Biot linear bifurcation threshold (−0.61). This deeper strain is mechanically attributed to bulging-induced curvature and superimposed bending compression, confirming the crease as a nonlinear instability. This work provides numerical references for the anti-creasing design of packer rubber cylinders under quasi-static setting. Full article

Water scarcity is a major constraint to wheat production in arid regions, highlighting the need for sustainable approaches to improve crop productivity and irrigation water-use efficiency (IWUE). Although Bacillus-based bioinoculants have been widely investigated, the potential of indigenous strains adapted to arid environments remains underutilized for the developing of site-specific bioinoculants. This study developed an integrated screening strategy combining plant growth-promoting (PGP) traits characterization, greenhouse evaluation, correlation analysis, and multivariate analyses to identify elite indigenous Bacillus strains capable of improving wheat performance under contrasting irrigation regimes. Fifty-one indigenous Bacillus strains representing 19 species, identified by 16S rRNA gene sequencing, were characterized for indole-3-acetic acid (IAA), ammonia (NH₃), siderophore production, and potassium-solubilizing activity and subsequently evaluated in greenhouse conditions under full (FI) and deficit (DI) irrigation. Plant growth was assessed at 85 days after sowing, while yield and yield-related traits were evaluated at physiological maturity (130 DAS). Significant variation was observed among the strains in both PGP traits and their effects on wheat performance. Selected strains increased vegetative growth traits by 22.2–53.7% under FI and 16.4–49.2% under DI, while improving yield-related traits and IWUE by 24.7–52.3% and 14.7–67.2%, respectively, compared with the uninoculated control. Correlation analysis identified IAA production as the PGP trait most strongly associated with wheat growth, grain yield, and IWUE, followed by NH₃ production, whereas siderophore production showed weak associations with most agronomic traits. Hierarchical cluster analysis and principal component analysis consistently identified Bacillus cereus A2, B. pumilus D2 and E3, and B. safensis D5 as the elite strains, while several additional indigenous strains also exhibited considerable potential under both irrigation regimes. This study demonstrates that the integrated screening approach enabled the identification of strain-level differences that could not be adequately captured by individual PGP traits alone, highlighting indigenous Bacillus strains as valuable resources for developing locally adapted bioinoculants to improve wheat productivity, IWUE, and drought resilience in arid and semi-arid agroecosystems. Full article

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