Search Results (351)

The unauthorized addition of silver nitrate and excessive heavy metals in hair dye creams poses serious health risks, creating an urgent need for rapid and sensitive detection methods. In this study, a spark discharge-enhanced fiber laser-induced breakdown spectroscopy (SD-LIBS) system was developed for the simultaneous detection of five heavy metal ions (Ag, Pb, Cd, As, Hg) in hair dye creams. The system combines three signal enhancement strategies: high-voltage spark discharge, Au nanoparticle-assisted enhancement, and analyte enrichment on a superhydrophobic–hydrophilic patterned graphite substrate. Hydrophilic micro-pits were fabricated by laser scanning on the superhydrophobic graphite surface to confine and concentrate analyte residues upon droplet drying. Under optimized discharge conditions of 22 nF and 2000 V, the spark discharge achieved a signal-to-noise ratio enhancement of approximately 12 times. Au nanoparticle enhancement further increased the signal intensity by 49.3%. The optimal pit diameter and sample loading volume were 0.1 mm and 30 μL, respectively. The calibration curves for all five elements showed good linearity with R² values close to 0.99, and the lowest detection limits reached 1.9 μg/L for Ag. The average spiked recovery was 82.07%. The method was applied to four commercial hair dye cream samples, and the Ag detection results agreed well with ICP-OES reference values with an average error of 16.41%. This work demonstrates that the proposed SD-LIBS system offers a low-cost, rapid, and sensitive approach for on-site screening of heavy metals in cosmetics and other consumer products. Full article

To investigate the effect of femtosecond laser scanning path on the surface integrity of 7075 aluminum alloy after paint removal, parallel, Z-shape, and loop-shape scanning were compared in terms of surface morphology, microstructure, chemical composition, roughness, wettability, and corrosion resistance. Parallel scanning effectively removed the paint while maintaining a surface roughness of 0.27 μm, close to that of the original substrate. The resulting regular unidirectional laser-induced periodic surface structures (LIPSS) yielded a water contact angle of 85°, consistent with the Wenzel wetting model. X-ray photoelectron spectroscopy (XPS) showed the lowest C 1s and O 1s peak intensities, the lowest lattice-oxygen fraction in Al₂O₃, the strongest metallic Al⁰ signal, and limited thermal oxidation. Electrochemical measurements showed the most positive corrosion potential (−0.974 V), the highest film resistance and charge-transfer resistance, and the best corrosion resistance for parallel scanning. By contrast, energy accumulation at the ends during Z-shape scanning and thermal accumulation at the corners and center during loop-shape scanning increased pit and recast-defect densities, oxidation, and corrosion degradation. Loop-shape scanning produced a surface roughness of 3.60 μm and a contact angle of 140.7°, indicating superhydrophobicity, but also the highest corrosion current density and the poorest corrosion resistance, showing that superhydrophobicity does not necessarily correspond to high corrosion resistance. The results show that scanning path affects LIPSS evolution, oxide-film integrity, and corrosion resistance through the spatial distribution of laser energy and thermal accumulation. Among the three paths, parallel scanning provided the best combination of paint removal, low substrate damage, and corrosion resistance, supporting its use in femtosecond-laser paint removal from aircraft aluminum alloy skins. Full article

The surface of nodular cast iron is susceptible to wear failure under high-load conditions. In this study, Fe-Cr-Ni wear-resistant coatings were developed on the surface of nodular cast iron using laser cladding technology. The influence of laser power (P), powder feeding rate (F), scanning speed (V), and overlapping rate (φ) on the microhardness and dilution rate of the coatings was analyzed by response surface methodology, while the model’s accuracy was evaluated through analysis of variance. Subsequently, the multi-objective particle swarm optimization algorithm was utilized to identify the optimal process parameters (P = 1350 W, V = 12.5 mm/s, F = 9 g/min, and φ = 45%) based on non-destructive testing results. The predictive model values closely matched the experimental results. The average microhardness of the Fe-Cr-Ni cladding layer was 620.3 HV, which was 2.8 times that of the nodular cast iron substrate. Importantly, the laser cladding layer demonstrated a significant improvement in wear resistance compared to the substrate. The wear mechanisms for the coating predominantly involved mild abrasive wear and adhesive wear, while the substrate primarily experienced severe adhesive wear. This study offers valuable insights for optimizing laser cladding process parameters for nodular cast iron. Full article

Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, has become an essential close-range remote sensing technique for high-precision engineering surveying, deformation monitoring, industrial inspection, and cultural heritage documentation. The geometric reliability of TLS point clouds strongly depends on the effective compensation of instrumental systematic errors through in situ self-calibration. However, conventional target-based self-calibration often suffers from strong coupling between calibration parameters and exterior orientation parameters, whereas recently developed coplanarity-constrained formulations generally require highly redundant target networks, limiting their field efficiency. To address this limitation, this study proposes a variance inflation factor (VIF)-driven minimal network design strategy for efficient in situ geometric self-calibration of TLS systems. Unlike the commonly used geometric dilution of precision, VIF provides a dimensionless statistical alternative that effectively resolves the dimensional inconsistency inherent in traditional GDOP when handling mixed angular and distance parameters. A differential evolution algorithm is employed to search for hybrid calibration networks that minimize parameter coupling while preserving the physical interpretability of the National Institute of Standards and Technology (NIST) 10-parameter instrumental error model. Five digital twin simulation experiments and a physical validation experiment using a Faro Focus 350 scanner were conducted to evaluate the proposed method. The results show that the optimized network substantially reduces the number of required targets while maintaining high calibration accuracy. The final configuration, which combines VIF-optimized target placement with a dual-station height-difference constraint, reduces the condition number of the normal equations to below 60 and yields a mean system VIF close to 10. The maximum parameter correlation coefficient among the key calibration parameters is constrained to approximately 0.75, indicating near-optimal parameter decoupling under the limited field-of-view geometry of the instrument. These findings demonstrate that the proposed VIF-driven network design provides a highly effective strategy for field-efficient TLS self-calibration and improves the geometric reliability of terrestrial LiDAR point clouds in high-precision remote sensing applications. Full article

Rock bolts are the primary ground support mechanism in underground mining. Yet verification of their installation is rarely captured in a spatially precise, retrievable form, leaving operators without an auditable as-built record for regulatory review or post-incident reconstruction. This paper presents an automated rock bolt detection process that closes this documentation gap using dense point clouds from an underground hard rock mine acquired by terrestrial laser scan. The method computes per-point ambient occlusion (AO) on closure plane-sealed chambers using a PCV implementation of the ShadeVIS principle, forms candidates from a multi-scale protrusion field, and segments them by prominence watershed before classifying each candidate with PCA-based geometric descriptors, without machine learning or training data. Installation perpendicularity is applied as a per-detection confidence cue, and detections are reported in confidence tiers that concentrate human review on the ambiguous minority. Validated against a database of 1447 bolts across 20 walls in two areas of an underground mine, the system achieved an overall recall of 83.7%, with human review completing the inventory to 100%. The physics-based design transfers across bolt types and mine geometries through parameter re-tuning rather than retraining, addressing the core limitation of deep learning methods, which require site-specific labelled datasets. Full article

Reliable aboveground biomass (AGB) estimates for woody crops are essential for carbon accounting and for Measurement, Reporting and Verification (MRV) frameworks. However, it remains unclear how LiDAR modality and sampling geometry influence plot-scale and tree-scale AGB predictions in intensively managed Mediterranean orchards. In this study, we benchmarked four LiDAR modalities, namely open national airborne laser scanning from the Spanish National Aerial Orthophotography Plan (PNOA/ALS), a dedicated Riegl airborne laser scanner (ALS), unmanned laser scanning (ULS) and mobile laser scanning (MLS), across three woody-crop sites in Córdoba (southern Spain): IFAPA, Doña María, and Villaseca. Plot-level LiDAR metrics (mean height, 95th height percentile, maximum height, and canopy-cover proxies) were extracted from normalized point clouds and related to field AGB using Random Forest and XGBoost regression models, together with an ensemble predictor, under an 80/20 train–test split. In parallel, TreeQSM-based Quantitative Structure Models (QSMs) were evaluated as an independent tree-level three-dimensional reconstruction approach. XGBoost achieved the lowest errors at IFAPA (RMSE = 0.400 Mg ha⁻¹; R² = 0.994) and Villaseca (RMSE = 0.872 Mg ha⁻¹; R² = 0.995), whereas PNOA/ALS was competitive at Doña María (RMSE = 0.725 Mg ha⁻¹; R² = 0.994). TreeQSM closely matched the field inventory at the low-biomass IFAPA site but tended to overestimate biomass at Doña María and Villaseca, and only 28% of scanned trees yielded usable reconstructions. The results support the use of cross-platform LiDAR for orchard AGB and carbon mapping and identify the conditions under which open national LiDAR can enable scalable MRV of Mediterranean woody crops. Full article

This study presents a hybrid geodetic validation framework for assessing the geometric consistency of the axis of a steel lattice transmission tower determined from terrestrial laser scanning (TLS) data using an independently established tachymetric reference. Unlike previous investigations that focused on the influence of TLS scanner characteristics, registration strategies, or internal consistency of TLS-derived axes, the proposed approach introduces an external geodetic reference, enabling direct external assessment of TLS-based geometric axis estimation. The reference axis was determined at fourteen height levels, while the TLS axis was estimated from horizontal cross-sections of a point cloud acquired from multiple scanning stations and registered using a cloud-to-cloud method without control points. To enable direct comparison, both datasets were transformed into a common reference system using a seven-parameter Helmert transformation. The transformation was applied solely to remove differences between the independent local coordinate systems prior to the geometric comparison. Axis consistency was evaluated using residual vectors and three-dimensional distances between corresponding points. The mean deviation was 0.031 m, the RMS value was 0.033 m, and the maximum deviation reached 0.078 m. Larger discrepancies occurred predominantly in the upper sections of the structure, in a pattern consistent with the combined influence of TLS registration uncertainty, non-uniform point-cloud coverage, and local geometric conditions. A comparison of TLS axis estimators (centroid, LS-R regression, and PCA) showed that PCA produced an RMS value close to that of the centroid estimator, whereas LS-R produced a higher RMS value; the maximum deviation was lowest for the centroid estimator and highest for PCA. Regression analysis revealed a statistically significant linear trend in the X direction (p = 0.019), indicating residual systematic geometric drift after coordinate-system integration. The obtained discrepancies should be interpreted in the context of a rapid engineering TLS workflow performed without registration targets or a control network, rather than as the intrinsic accuracy of the TLS instrument itself. The proposed hybrid validation framework provides an objective quality-control methodology for evaluating TLS-derived geometric axes against independent geodetic observations and may support reliability assessment of TLS-based inventories and deformation monitoring of slender engineering structures. Full article

Accurate estimation of forest structural attributes over operational scales remains challenging because unmanned laser scanning (ULS) provides extensive spatial coverage but limited representation of internal stem structure, whereas terrestrial and mobile laser scanning (TLS/MLS) provide detailed stem measurements over relatively small areas. This study investigates a calibration-transfer framework in which small areas of terrestrial or fused LiDAR are used to improve diameter at breast height (DBH) estimation across much larger regions surveyed only by ULS. ULS, TLS, MLS and fused laser scanning (FLS) datasets were analysed for radiata pine and eucalyptus plantations. TreeLS-derived DBH measurements from terrestrial and fused point clouds were used as reference data to evaluate several distribution-aware and voxel-based imputation approaches for correcting regression-derived ULS estimates. Across the study sites, the best-performing imputation methods reduced stand-level mean DBH differences by as much as 95% relative to the uncorrected ULS regression estimates, resulting in substantially improved agreement with field-observed stand means while simultaneously producing DBH distributions that more closely matched the corresponding TreeLS-derived reference distributions. Voxel-based imputation performed particularly well for radiata pine and remained competitive for eucalyptus, while several distribution-based approaches achieved comparable or better performance in particular stands. These findings demonstrate the potential for transferring information from relatively small terrestrial LiDAR calibration areas to larger ULS-only acquisitions, improving stand-level DBH distribution estimates without requiring complete terrestrial coverage. Because validation was performed using stand-level field summary statistics rather than matched individual trees, the reported performance should be interpreted as demonstrating the potential of the approach under the conditions evaluated rather than universal individual-tree accuracy. Full article

Exploiting the complementary views of ground-based and aerial laser scanning requires co-registering their point clouds, which is difficult in closed tropical forest where Global Navigation Satellite System (GNSS) reception fails. We co-registered handheld Simultaneous Localization and Mapping (SLAM) LiDAR and UAV LiDAR without per-tree GNSS, using girth-identity anchors inherited from a companion inventory, over an open dry dipterocarp forest (DDF) and a closed dry evergreen forest (DEF) at the SERS, northeastern Thailand. Coarse-to-fine registration reduced the residual to a mean absolute distance of 0.17–0.18 m, and the clouds sampled complementary strata-stems and understory to about 25–30 m, emergent canopy to about 37 m. The co-registered data give each tree a ground-measured stem diameter and an aerially measured height, which we used to test whether diameter can instead be inferred from the canopy. It cannot: both a height-based and a best-case crown-and-height model saturated near 50 cm while measured stems reached about 100 cm, so UAV-only individual-tree carbon did not track the field reference; supplying the ground-measured diameter restored agreement (R² = 0.91), validated against reflective-tape anchor trees. The horizontal offset between a stem base and its crown apex further explains why position-only stem-to-crown matching fails and why girth-identity linkage is needed. We conclude that credible individual-tree carbon in closed tropical forest requires ground measurement of stem diameter, made possible by GNSS-independent SLAM-UAV co-registration; the aerial platform contributes height and coverage, not diameter. Full article

Vehicle vibration and noise are predominantly driven by road-surface excitation, making robust prediction of these phenomena based on pavement roughness a central challenge in automotive development. This paper presents a fully automated pipeline that begins with high-resolution laser-triangulation scans of actual test tracks to produce centerline elevation profiles. These profiles are processed and classified by a MATLAB routine using ISO 8608-based power-spectral-density analysis to extract the Gh₀ roughness coefficient. Concurrently, in-service acoustic and chassis-vibration data, collected at two representative speeds, are transformed into feature vectors comprising statistical PSD descriptors. A regression model then learns the mapping from these features to Gh₀, evaluating the feasibility of mapping vehicle-borne signatures to roughness metrics. Predicted Gh₀ values drive a profile-synthesis algorithm to generate two-dimensional height grids, which are exported as CRG files and imported into a multibody simulation software (MSC ADAMS) as well as driver-in-the-loop platforms. Simulation results closely reproduce the primary excitation characteristics of the physical tracks, demonstrating a preliminary proof-of-concept pipeline for virtual road surface generation. While the cross-validated regression model indicates limited generalization on the current small dataset ($R^2=-0.2783$), the end-to-end workflow establishes the baseline integration required for future data-driven NVH simulation. To extend applicability beyond a single test vehicle, a set of Vehicle Calibration Transforms is proposed to adapt power-spectral-density features from arbitrary vehicles into the calibrated feature domain. The complete workflow promises to streamline virtual NVH validation, reduce prototype testing, and support full NVH simulator engineering in future research. Full article

Efficient laser cleaning of glazed ceramic tiles requires the ink layer to be removed without damaging the brittle glaze. We investigated the removal of acrylic ink using a 1064 nm, 10 ns Nd:YAG laser operating at 1 Hz. The lens-to-sample working distance L, pulse energy, and pulse number were varied, and the cleaned regions were evaluated by optical microscopy (OM), scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM–EDS), theoretical analysis, and COMSOL simulation. At L = 20 cm, the sample was close to the nominal focal plane, and the high local fluence removed the ink rapidly, but it also produced whitening, depressions, micro-pits, and glaze damage. Increasing L to 25–30 cm enlarged the measured spot diameter, lowered the average fluence, and widened the controllable cleaning range. Two low-damage conditions were identified at L = 30 cm: 30.80 J/cm² with 3 pulses and 41.00 J/cm² with 2 pulses. SEM–EDS showed that cleaning quality cannot be judged from exposed area or carbon content alone; morphology, preservation of the native glaze microstructure, the C/O ratio, and recovery of substrate-related elements must be considered together. Under the stated model assumptions, the calculated local temperature exceeded the acrylic decomposition temperature, and the thermoelastic stress reached tens to hundreds of MPa. These results make thermal decomposition and stress-assisted interfacial separation physically plausible. However, the present data do not separate thermoelastic stress from pressure-wave loading. Likewise, visible air breakdown and non-monotonic cleaning at high pulse energy only suggest possible plasma-related attenuation because plasma density and transmitted laser energy were not measured. The reported combinations should therefore be regarded as a system-specific process window rather than a universal optimum. Full article

This study evaluates the rapid tooling feasibility and structural significance of utilizing digital light processing (DLP)-printed alumina as a near-net-shape ceramic mold-insert preform route for replication of curved polymer optics. While conventional production tooling for precision optics demands immediate optical-grade tolerances, the fundamental mechanisms governing polymer replication close to additively manufactured ceramic interfaces remain insufficiently understood. To isolate these multi-factor processing signatures, alumina specimens incorporating concave and convex parabolic surfaces were synthesized via lithography-based ceramic manufacturing. Our design acts as a geometric control lens, ensuring that thermal shrinkage trends, slicing kinematics, and interfacial replication behaviors are clearly exposed and quantified under uniform boundary conditions. Following debinding and sintering, exploratory hot-pressing cycles were executed to evaluate gross profile transfer and surface inheritance on poly(methyl methacrylate) (PMMA) replicas. Quantitative laser scanning confocal microscopy confirmed successful gross curvature generation and revealed geometry-dependent post-sintering shrinkage trends. The convex inserts exhibited an average peak-to-valley (PV) error of 123.48 ± 3.30 µm and an RMS error of 29.76 ± 1.23 µm, whereas the concave alumina inserts showed an average PV error of 137.98 ± 5.80 µm and an RMS error of 34.68 ± 1.20 µm. The PMMA replicas also showed substantial form deviation, with an average PV error of 163.72 ± 15.64 µm and RMS error of 27.37 ± 2.03 µm. Our work presents a route for producing near-net-shape ceramic mold-insert preforms that transforms complex processing variations into a predictable, mathematically addressable roadmap. A geometry-specific CAD pre-compensation can then be performed while the remaining precision gap can be selectively closed via targeted post-polishing depending on the desired optical application tier. Full article

Ancient timber structures are important carriers of valuable cultural heritage, and their structural safety directly determines whether historic buildings can remain in safe service over time. Cracks represent one of the most widespread and important forms of damage in ancient timber structures. They can directly lead to cross-sectional weakening of structural members, degradation of load-bearing capacity, and the gradual development of overall structural safety risks. To address the limitations of existing crack assessment methods, such as strong subjectivity in weight determination, insufficient accuracy in grade boundary discrimination, and inadequate coupling with mechanical performance, this study proposes a crack safety assessment method for ancient timber structures based on an improved entropy–fuzzy matter-element model. A multi-dimensional evaluation index system is established, incorporating crack geometric characteristics, structural load-bearing capacity, and service time effects. A mechanically driven load-carrying capacity degradation index is introduced to quantitatively characterize the influence mechanism of crack propagation on structural performance deterioration. The entropy weight method is employed to objectively determine the weights of each indicator, and an asymmetric closeness degree is introduced to improve the traditional fuzzy matter-element model, thereby enhancing the stability and accuracy of safety grade classification. A case study of the Bawang Academy, Shenyang Jianzhu University, is conducted. Crack parameters are obtained using image recognition and three-dimensional laser scanning techniques, and a comprehensive structural safety assessment is performed. The results indicate that the proposed method can accurately reflect the actual damage distribution and deterioration level of the structure, providing a reliable theoretical basis and technical support for crack safety evaluation and preventive conservation of ancient timber structures. Full article

Electrostatic MEMS micromirrors provide a compact and low-power beam-steering solution for miniaturized laser communication terminals. However, when they are used for quasi-static beam pointing rather than resonant scanning, the nonlinear voltage–angle relationship, bidirectional actuation asymmetry, and terminal-level installation errors can significantly degrade pointing accuracy. In this paper, a nonlinear modeling and differential-voltage control method is investigated for a two-axis electrostatic MEMS micromirror used in a miniaturized laser communication terminal. The device under test is a bonded aluminum MEMS micromirror with a 5.0 mm aperture. Static and dynamic characterization results show that the micromirror achieves maximum mechanical deflection angles of 5.215° and 5.161° along the X and Y axes, respectively, with resonant frequencies of 317 Hz and 319 Hz. To improve the accuracy of quasi-static pointing, the differential-voltage actuation principle is analyzed, and a nonlinear voltage–angle model is established based on measured deflection data. Compared with a first-order linear model, the cubic nonlinear model reduces the root-mean-square fitting error from 0.142° to 0.0127° for the X axis and from 0.132° to 0.0109° for the Y axis. Furthermore, a terminal-level calibration architecture based on a quadrant detector is introduced to map the MEMS angular deflection to the received spot position. The proposed modeling and calibration approach provides an actuator-level basis for accurate beam pointing and closed-loop acquisition in miniaturized laser communication terminals. Full article

This study presents the diagnostic and conservation work carried out on the Roman mosaic of the South cubiculum in the Latomia dei Niccolini (Marsala, western Sicily). The mosaic, decorated with polychrome tesserae featuring a kantharos motif, presented severe structural damage, including fractures, subsurface voids, and progressive material loss. To assess the causes of deterioration and design an effective conservation strategy, an integrated approach combining non-invasive geophysical and 3D survey methods was applied. Ground-penetrating radar (GPR) was selected as the main diagnostic tool because it allows high-resolution subsurface imaging while preserving the integrity of the fragile mosaic surface. By utilizing high-frequency 2 GHz antennas and complementary video inspection, a significant subsurface cavity beneath the mosaic preparation layer was successfully mapped, determining its critical relationship with the main diagonal surface fracture. Simultaneously, laser scanning and close-range photogrammetry enabled the creation of accurate 3D models supporting both documentation and restoration planning. The conservation concluded with surface cleaning, mortar consolidation, and the successful structural detachment and relocation of the compromised section onto a lightweight support for future museum display. The findings demonstrate that integrating 3D digital and geophysical data provides a quantitative, low-risk roadmap for preserving highly vulnerable archaeological floorings, moving beyond qualitative technical documentation to establish a replicable preservation framework. Full article