Search Results (251)

Accurate and efficient 3D reconstruction of trees is of paramount importance for studying forest spatial structures and dynamic resource patterns, optimizing forest management, protecting environments, and analyzing carbon cycles. Currently, Light Detection and Ranging (LiDAR) remains the dominant method for generating 3D models of forest scenes. However, with advancements in computer vision, photogrammetry has emerged as a crucial tool for forest inventory and 3D reconstruction due to its cost-effectiveness. Nevertheless, in practical forestry applications, traditional photogrammetry often suffers from low reconstruction efficiency and poor quality during feature extraction and matching. These issues stem from the complex structure of forest scenes, severe occlusion, and repetitive texture patterns. To address these challenges, this paper proposes an improved 3D tree reconstruction approach based on images, integrating deep learning-based methods. In the sparse reconstruction stage, we utilize the ALIKED (A LIghter Keypoint and descriptor Extraction network with Deformable transformation) algorithm and construct an image pyramid to extract multi-scale robust features. Furthermore, by combining the LightGlue matching algorithm with a neighborhood search constraint strategy, we enhance the stability of camera pose recovery while reducing redundant computations. Experimental results demonstrate that our method outperforms traditional algorithms in both accuracy and robustness regarding image matching. Compared to baseline models, the proposed approach increases the number of feature points by approximately 50% with a more widespread distribution, improves matching accuracy by 4% to 8%, and achieves a 100% image registration rate. Consequently, under the condition of maintaining equivalent re-projection errors, the subsequent sparse point clouds exhibit an average track length increase of 0.6 to 1.4 and a density increase of up to 1.2 times. Notably, this method effectively mitigates artifacts and spurious reconstructions caused by pose drift in forest photogrammetry. Full article

Selective laser melting (SLM) offers significant potential for fabricating lightweight 316L stainless steel lattice structures (LSs), while forming defects and microstructural heterogeneity remain challenging, especially in fine struts. In this study, response surface methodology (RSM) and analysis of variance (ANOVA) were employed to quantify the coupled effects of geometric parameters (forming angle, FA; rod diameter, RD) and processing parameters (laser power, LP; scanning speed, SS; hatch spacing, HS) on the mass deviation (MD) of fine struts. The results show that FA and RD are the dominant factors affecting MD within the investigated parameter range, whereas LP and SS exhibit comparatively weaker effects. Representative samples with different FA and RD were further characterized by SEM, XRD, and EBSD to examine the associated microstructural evolution. The observations indicate that changes in FA and RD are accompanied by variations in solidification morphology, defect distribution, crystallographic texture, and GND density. Higher FA is associated with lower MD and stronger texture alignment along the building direction, whereas larger RD tends to promote columnar growth and enhanced texture intensity. These results suggest that geometric parameters can serve as effective design variables for tailoring forming deviation and representative microstructural characteristics of fine struts in SLM-fabricated 316L lattice structures. Full article

Coal liquefaction residues (CLRs), including both indirect (ICLR) and direct (DCLR) variants, represent industrial by-products whose conventional landfill disposal raises environmental concerns. This study comparatively analyzes ICLR and DCLR properties against limestone fine aggregates through physicochemical characterization. Results indicate that ICLR contains predominant SiO₂ crystalline phases (50.05%) with trace Fe-Ti-Al-Mg oxides, demonstrating higher Vickers hardness (615 HV vs. 246 HV for limestone) and elastic modulus (98 GPa vs. 81 GPa for limestone), while its apparent relative density (2.612) closely matches that of limestone (2.783). Conversely, DCLR features abundant carbonaceous components (75.9% C) with olefinic/aromatic structures (asphaltene content 66.2%), exhibiting lower mechanical strength (Vickers hardness 21 HV) but enhanced asphalt affinity, as indicated by strong C=C (1591 cm⁻¹) and aromatic C–H (744 cm⁻¹) absorption peaks in FTIR. Both CLRs share comparable gradation curves and micromorphological characteristics with limestone aggregates, including uniform surface scaly textures. While pore-size distributions differ minimally between CLRs, both present finer porosity than limestone and show no leachate toxicity risks, confirming their viability as sustainable alternatives to asphalt fine aggregates. Full article

TATB (1,3,5-triamino-2,4,6-trinitrobenzene) crystals exhibit strong thermoelastic anisotropy, making crystallographic texture a key factor in the thermal-stress response of TATB-based polymer-bonded explosives (PBXs). In this study, computational micromechanics combined with statistical analysis is used to quantify thermal-expansion-induced internal stresses in TATB-textured PBXs at the mesoscale. The results show that the spatial distribution of internal stress is strongly influenced by grain misorientation between neighboring grains, with larger misorientations leading to more severe stress concentrations. Statistical analysis further reveals that the internal stress distributions are generally asymmetric and unimodal. As texture intensity increases, the probability density peak rises, whereas both the mode stress and the average stress decrease. The maximum-to-minimum ratios of these three statistical characteristics reach up to 5.8, 8.9, and 6.1, respectively, indicating that texture intensity can regulate the stress field over a broad range. Gaussian mixture modeling is further employed to characterize the probability distributions of three stress measures. The distribution of maximum principal stress can be adequately described using two Gaussian components, whereas the von Mises and Tresca stress distributions require three components. These findings provide a quantitative basis for understanding and mitigating thermoelastic internal stress in PBXs through texture tailoring. Full article

The critical metal lithium (Li) is increasingly sourced from spodumene and petalite pegmatite deposits due to their relatively high grades, lower mining environmental impacts and widespread global distribution. However, there are numerous gaps in our understanding of their genesis and the formation of unzoned or poorly zoned Li pegmatites is particularly difficult to explain. To investigate this, both spodumene-bearing and non-mineralized pegmatites and aplites are studied in the Moylisha segment of the Leinster pegmatite belt of SE Ireland, which were emplaced within the East Carlow Deformation Zone (ECDZ). Trace element modeling suggests that granite melts can achieve Li concentrations high enough (~5000 ppm) to crystallize spodumene. However, once crystallization begins, Li levels will drop rapidly below this threshold. While Li could be replenished by incoming melts, there is no supporting textural evidence for this, such as internal magmatic contacts, crosscutting relationships, or mingling. We test the hypothesis that low viscosity, Li-rich fluids from underlying reservoirs, most likely almost fully crystallized granite magmas or mush, continuously migrate through the heterogeneously crystallizing pegmatite-forming melts by percolative reactive flow, refertilizing interstitial melt by diffusion under favorable geochemical gradients. The flow of fluids is likely maintained due to their low relative density and periodic shearing within the ECDZ. Fluids with >10,000 ppm Li, derived by >95% crystallization (Rayleigh fractionation) of a granite magma, are shown to be capable of refertilizing a pegmatitic crystal mush after its emplacement. Supporting evidence includes macro- and micro-textures indicative of paragenetically late spodumene crystallization along apparent fluid flow pathways in mineralized pegmatites and aplites. Similar features are common in spodumene pegmatites worldwide and suggest that Li upgrading by fluid flow through crystallizing spodumene pegmatites may be a key process in enhancing Li grades and in some cases in producing economically favored low-Fe spodumene. Full article

This study evaluates the performance of foamed geopolymer concrete (FGC) incorporating rigid polyurethane (PU) waste as a partial sand replacement and aluminum powder (AP, 1%) as a foaming agent. The mixtures were based on metakaolin, fly ash, and silica fume. Fresh and hardened properties were assessed, including workability, setting time, density, compressive strength, flexural strength, splitting tensile strength, elastic modulus, water absorption, porosity, gas permeability, and chloride ion penetration. Microstructural characteristics were examined using scanning electron microscopy (SEM). The results show that moderate PU incorporation significantly enhances mechanical performance. The optimal mixture (PU30) achieved a compressive strength of 47.25 MPa at 180 days, representing a 15.6% increase compared to the control. Flexural and splitting tensile strengths improved by 19.9% and 16.7%, respectively, while the elastic modulus increased by 33.8% to 0.95 GPa. These improvements are attributed to enhanced particle packing and more efficient stress transfer within the matrix. In contrast, higher PU contents (>30%) reduced mechanical performance due to increased total porosity and weakened interfacial bonding. Durability-related properties indicated that mixtures PU20–PU30 exhibited reduced permeability and optimized pore structure, characterized by lower pore connectivity. SEM observations confirmed a denser matrix with uniformly distributed pores at optimal PU levels. Additionally, the integration of Random Forest regression with GLCM-based texture analysis demonstrated strong capability in predicting mechanical properties from SEM images. Overall, the combined use of PU waste and AP enables the production of lightweight, structurally efficient, and sustainable FGC with improved mechanical and durability performance. Full article

Urban trees are increasingly deployed as nature-based infrastructure to mitigate heat and manage stormwater, yet quantitative guidance on how species traits and site context shape transpiration remains fragmented. We conducted a systematic metadata analysis of seven field studies that measured daily transpiration rate in urban settings using heat-pulse methods. The units and spatial scales reported were harmonized with the sap flow density across active sapwood (J_s, g H₂O/${\mathrm{cm}}^2$/day) by converting reported stand transpiration and the outer 2 cm of sapwood sap flux using established Gaussian radial distribution functions for angiosperms and gymnosperms, which account for the non-linear decline in sap flux from the vascular cambium to the heartwood boundary. We then summarized distributions and tested group differences with Kruskal–Wallis and Dunn post hoc comparisons across wood anatomy, climate, soil texture, and planting configuration. Conifers exhibited significantly lower median $J_s$ (39.76 g/${\mathrm{cm}}^2$/day) than angiosperms, while the ring-porous group (median $J_s$ = 92.25 g/${\mathrm{cm}}^2$/day) and diffuse-porous groups (median $J_s$ = 96.70 g/${\mathrm{cm}}^2$/day) had similar distributions overall. Climate-modulated responses within wood anatomy groups differed, with diffuse-porous species exhibiting the highest median $J_s$ (152.59 g/${\mathrm{cm}}^2$/day) in semi-arid regions, ring-porous species maintaining comparatively stable median $J_s$ across climates (varying slightly between 80.72 and 99.32 g/${\mathrm{cm}}^2$/day), and conifers reaching their highest median $J_s$ (69.90 g/${\mathrm{cm}}^2$/day) in humid continental sites. Soil texture effects were consistent with moisture availability: sandy loam generally reduced $J_s$ relative to loam or silt loam for conifers and diffuse-porous species. Across anatomies, single trees transpired more than clustered trees or closed canopies. For example, planting as single trees increased median $J_s$ by 86% in conifers (from 33.01 to 61.37 g/${\mathrm{cm}}^2$/day) and by 45% in diffuse-porous species (from 81.31 to 118.25 g/${\mathrm{cm}}^2$/day). These results provide actionable ranges and contrasts to inform species selection and planting design for urban greening and runoff reduction, while highlighting data gaps for future research. Ultimately, by matching specific wood anatomies and planting configurations to local soil and climatic conditions, urban planners and ecohydrologists can strategically optimize urban forests to maximize targeted ecosystem services. Full article

Naked mole-rats are extremely long-lived rodents with a lifespan of up to 40 years, during which cellular and tissue aging is rarely observed. In this study, we analyzed the extracellular matrix (ECM) of naked mole-rat skin at the molecular level to elucidate the molecules involved in anti-aging and their localization. Raman spectroscopy and Fourier transform infrared spectroscopy were applied to investigate the hierarchical structure of the ECM, showing that, whereas the epidermis of aged mice had thinned, the epidermis of naked mole-rats became thickened and hyaluronic acid (HA) was distributed under the basement membrane. Furthermore, naked mole-rat skin had a regular skin texture and flexibility, allowing the maintenance of a youthful appearance. Hyaluronic acid in naked mole-rats characteristically exists as clusters (chain HA) in skin tissue, where it is thought to permit moisture retention and maintain elasticity, contributing to the skin’s youthful appearance. These results suggested that not only the density of ECM but also its spatial distribution and topographic properties are important for skin anti-aging. Our findings may contribute to the elucidation of skin disease pathology, the development of therapeutic gel scaffolds, and the control of aging. Full article

Remote sensing images are highly susceptible to spatially non-uniform haze under complex atmospheric conditions, leading to contrast degradation and structural detail loss. Moreover, remote sensing scenes usually exhibit complex spatial structures, highly uneven haze distribution, and significant statistical variability, which further increases the difficulty of haze removal. To address this issue, we revisit the haze degradation mechanism of remote sensing imagery and propose a dynamic histogram-sorted Transformer dehazing method from the perspectives of statistical distribution modeling and region-adaptive restoration. Specifically, a Histogram-Sorted Adaptive Attention is designed to map spatial features into the statistical distribution domain through a dynamic histogram sorting mechanism, enabling explicit discrimination and precise modeling of regions with different haze densities. Meanwhile, a Perception-Adaptive Feed-Forward Network is constructed, which incorporates a stable routing-based mixture-of-experts mechanism to adaptively select restoration strategies according to local texture characteristics and global haze density, thereby significantly enhancing the adaptability of the model in complex remote sensing scenarios. Extensive experimental results demonstrate that the proposed method achieves superior performance over existing approaches across multiple remote sensing benchmark datasets, effectively improving both visual quality and robustness of remote sensing imagery. Full article

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality globally. While multi-modal artificial intelligence (AI) models offer significant predictive potential, their translation into routine clinical practice is delayed by the “black box” nature of complex algorithms and the fragmentation of heterogeneous data. We present LANTERN-XGB, a hierarchical machine learning workflow designed to bridge this gap by generating interpretable “digital human avatars” for precision oncology. The methodology employs a multi-stage scalable tree boosting system (XGBoost) architecture utilizing shapley additive explanations (SHAP) for rigorous hierarchical feature selection, missing value management, and patient-specific decision support. The workflow was developed and benchmarked using a retrospective cohort of 437 patients with clinical N0 NSCLC, followed by validation on a prospective dataset (n = 100) and an independent external dataset (n = 100). The pipeline integrates diverse data modalities to predict occult lymph node metastasis (OLM). LANTERN-XGB identified a robust consensus signature driven by non-linear interactions among CT textural fragmentation, PET metabolic heterogeneity, tumor density distribution, and systemic clinical modulators. Exploratory transcriptomic pathway analysis (GSVA) revealed that high-risk predictions strongly correlate with systemic molecular dysregulation, such as the enrichment of immune-inflammatory signaling and metabolic stress pathways. The model achieved robust discrimination in external validation (AUC ≈ 0.77), performing comparably to state-of-the-art nomogram benchmarks. Crucially, the LANTERN-XGB framework demonstrated superior utility in handling diagnostic ambiguity; local force plots allowed for the correct reclassification of “borderline” prediction by visualizing feature interactions that standard linear models fail to capture. LANTERN-XGB provides a validated, open-source framework that successfully balances predictive power with clinical transparency. By empowering clinicians to visualize and verify the logic behind AI predictions, this workflow offers a pragmatic path for integrating reliable multi-modal avatars into daily medical decision-making. Full article

Laser powder bed fusion (LPBF) of AA7075 is severely constrained by a narrow process window and susceptibility to defect formation (hot cracking and porosity), which often dominates performance. In this study, 5 wt.% AlCoCrFeNi_2.1 high-entropy alloy (HEA) particles, volumetric energy density (VED = 74–222 J·mm⁻³), and subsequent T6 heat treatment were systematically investigated to reveal their combined effects on defect structure, crystallographic texture/substructure, and tensile behaviour. Quantitative EBSD shows a measurable grain refinement in the as-built state (average grain size 13.44 → 11.80 µm, ~12%) accompanied by a pronounced weakening of the <001> fibre texture (maximum MRD 4.94 → 2.38), indicating disrupted epitaxial growth and a more dispersed orientation distribution. After T6, the reinforced alloy retains a higher low-angle boundary fraction (31.62% vs. 24.17% in unreinforced AA7075) and a higher kernel average misorientation (0.80° vs. 0.60°), consistent with particle-stabilised substructure retention and retarded recovery. Across all VEDs, AA7075-HEA exhibits higher microhardness (compared with AA7075, the addition of HEA increases the hardness by roughly 20–50 HV) and tensile strength, with the intermediate VED (140.74 J·mm⁻³, T6 states) yielding the best performance. While macroscopic cracking is not fully eliminated, the results clarify that HEA-enabled texture/substructure modifications can contribute to enhanced defect tolerance and are more effectively translated into tensile performance when the as-built defect severity is controlled. These findings provide quantitative insights into defect–microstructure–property coupling in LPBF AA7075-HEA composites from as-built to T6 states. Full article

The effects of different finishing rolling temperatures on the microstructure and mechanical properties of a 580HE hole expansion steel were systematically investigated using optical microscopy, scanning electron microscopy, electron backscatter diffraction, and transmission electron microscopy. The results show that the yield strength increases with decreasing finishing rolling temperature, whereas the tensile strength and total elongation exhibit relatively small variations. Significant changes in phase fraction, grain size, spatial distribution, and NbC precipitation behavior are observed under different finishing rolling temperatures. The microstructure mainly consists of polygonal ferrite and granular bainite, while acicular ferrite is formed at higher finishing rolling temperatures. With decreasing finishing rolling temperature, the ferrite and bainite grains are markedly refined and become more uniformly distributed. Meanwhile, the ferrite fraction slightly increases, the crystallographic texture is weakened, and, more importantly, the number density of precipitates increases while their size is significantly reduced. The hole expansion ratio increases noticeably with decreasing finishing rolling temperature, which is mainly attributed to grain refinement, improved microstructural and strain homogeneity, and the selective strengthening effect of fine NbC precipitates. These factors effectively reduce stress concentration and hardness mismatch between soft and hard phases, thereby delaying crack initiation during hole expansion. Full article

TC4/Al₃Ti metal–intermetallic laminated (MIL) composites were fabricated by the vacuum hot-pressing process at 650 °C. The microstructure characteristics, i.e., grain boundary distribution, crystallographic orientation and Kernel Average Misorientation (KAM) map, were analyzed using EBSD. Meanwhile, the distribution of local strain and the fracture behavior of TC4/Al₃Ti MIL composites during tensile process were determined by Digital Image Correlation (DIC) and in situ tensile experiments, respectively. Results show that the TC4/Al₃Ti interfaces are well bonded and exhibit a distinct wavy morphology. The obvious Kirkendall pores and centerline are observed within the central region of the Al₃Ti layer. The texture components of (10-10) <0001> and (11-20) <10-10> are predominant in the TC4 layers; (100) <001> and (110) <001> are observed in the Al₃Ti layer. Additionally, the average geometrically necessary dislocation (GNDs) density is 2.53 × 10¹⁴ m⁻² in the TC4 layer, whereas it is 1.74 × 10¹⁴ m⁻² in the Al₃Ti layer. In the tensile test, the fracture resistance of TC4/Al₃Ti MIL composites is significantly improved by the plastic deformation of the TC4 layers and the suppression of crack-tip instability. It is found that the extrinsic toughening mechanisms contain crack deflection, crack blunting, crack bridging, multiple cracking modes, and the plastic deformation of ductile TC4 layers in TC4/Al₃Ti MIL composites. The real-time observation technique may provide more complete insights into the relationship between fracture behavior and enhanced toughness. Full article

Polymer powder bed fusion (PBF) is strongly influenced by powder chemistry and powder state, yet many studies discuss the materials and processing conditions in isolation. This review synthesises the literature using a powder-centred framework that connects polymer chemistry and powder production history to measurable powder descriptors, and then links these descriptors to processing windows, defect mechanisms, and application outcomes. Key descriptors include crystallinity and thermal transitions, additive packages, particle size distribution, morphology, and surface texture. Environmental sensitivities are also considered, including moisture uptake, temperature effects, and optical response. These factors are related to powder spreading, energy absorption, and melt solidification or sintering to explain how flowability, packing density, and melt dynamics govern porosity, lack of fusion, distortion, and degradation. Powder qualification is discussed together with lot-to-lot variability and lifecycle effects, including ageing, reuse, and refresh, using the indicators commonly reported in laboratory and production settings and supported by emerging in situ monitoring. Application case studies are consolidated to illustrate how powder state and process control translate into repeatable qualification targets as polymer PBF moves toward a predictable and transferable manufacturing practice. Full article

Adiabatic shear banding (ASB) is a critical failure mechanism in titanium alloys subjected to high-strain-rate deformation, and its initiation is strongly influenced by the initial crystallographic texture. The dynamic response and ASB sensitivity of extruded and annealed Ti-6Al-4V (TC4) alloy rods were investigated under dynamic compression of cubic specimens along the extrusion direction (ED) and the transverse direction (TD) at a strain rate of 2500 s⁻¹. Split Hopkinson pressure bar (SHPB) tests combined with digital image correlation (DIC) were employed to obtain the stress–strain response and the evolution of strain localization. A dislocation density-based crystal plasticity finite element model (CPFEM), incorporating the measured texture, was established to elucidate the correlation between texture and ASB behavior. The experimental results show that TD specimens exhibit a yield strength approximately 100 MPa higher than that of ED specimens, while both orientations display comparable post-yield hardening behavior. ASB initiation occurs earlier in TD (compressive strain ~0.13) than in ED (~0.23), indicating greater ASB sensitivity in the TD orientation. The CPFEM successfully reproduces the directional stress–strain responses and the observed localization morphology, enabling mechanistic interpretation in terms of slip activity and thermomechanical coupling. The simulations indicate that ED loading is dominated by prismatic ⟨a⟩ slip, resulting in lower flow stress and more dispersed strain localization. In contrast, TD loading is governed primarily by pyramidal ⟨c + a⟩ slip, leading to elevated flow stress and intensified localization. The higher ASB sensitivity in the TD orientation is therefore attributed to texture-controlled slip-mode partitioning, enhanced thermomechanical coupling, and a more concentrated crystallographic orientation distribution that facilitates intergranular slip transfer. These findings provide guidance for tailoring microtexture to mitigate dynamic failure in titanium alloys subjected to high-strain-rate loading. Full article