The Metaverse requires persistent and non-intrusive authentication for avatars across heterogeneous virtual environments. An individual’s walking pattern, or gait, provides a continuous and comparatively spoof-resistant verification mechanism compared with face, voice, or iris biometrics. However, gait-based authentication in avatar-mediated Metaverse environments remains vulnerable to algorithmic and statistical attacks, including synthetic gait generation, exploitation of feature dependencies, behavioral imitation, replay, and model drift. Conventional machine-learning, deep-learning, and transformer-based models also exhibit limited robustness to environmental variation, sensor noise, session variability, and adaptive adversaries. To address these challenges, we propose a secure and adaptive ensemble gait-authentication framework for continuous avatar verification that integrates Bagging, Random Forest, Gradient Boosting, and Extra Trees classifiers through a Secure Majority-Voting Scheme (SMVS). The framework employs a dynamic per-session acceptance threshold that adjusts the required voting condition according to session-level gait dispersion, noise, pose variability, and feature stability, thereby reducing false accepts while preserving authentication usability. We also introduce MetaGait, a large Unity-simulated avatar-gait dataset grounded in biomechanical principles and designed to support realistic multi-session evaluation. Experimental validation is conducted on MetaGait, CASIA-B, and OU-ISIR-C using leakage-safe subject-disjoint grouped cross-validation, together with explicit cross-dataset transfer experiments in which models trained on MetaGait are tested on CASIA-B and OU-ISIR-C. The proposed framework achieves up to 97.2% accuracy, 94.1% precision, 99.7% recall, and 97.0% F1-score, while attaining a low Equal Error Rate (EER) of 3.3% and outperforming traditional machine-learning, deep-learning, and transformer-based authentication models. Furthermore, formal game-based security analysis with probabilistic bounds, supported by comprehensive empirical attack simulations, shows SMVS’s resilience against Adaptive Brute-Force Attacks (ABFA), Constrained Behavioral Attacks (CBA), and Model Drift Invasion Attacks (MDIA).
To improve the mechanical reliability of thin-walled lithium disilicate (LD) veneers, this study developed a strengthening strategy that integrates vat photopolymerization (VP) with a two-step ion-exchange (IE) process. VP was employed to fabricate thin-walled LD structures, eliminating machining-induced damage, while a sequential K+/Rb+ IE process achieved both sufficient IE depth and compressive stress, overcoming their conventional trade-off. The two-step IE process increased the flexural strength of LD by 52.0% to 448.6 +/- 31.5 MPa and improved the fracture toughness by 80.4% to 2.64 +/- 0.10 MPa m1/2 . The significant enhancement in mechanical performance was mainly attributed to a 349% increase in compressive stress (CS), reaching 141.9 +/- 4.4 MPa. The atomic force microscope revealed that the ultrahigh CS was attributed to the volumetric expansion of an amorphous phase. Under scratching loads of 100 mN above the brittle-ductile transition threshold (similar to 70mN), the coefficient of friction of IE-processed LD increased by nearly 50%, indicating a transition in energy dissipation from brittle crack initiation to localized plastic deformation. Overall, the VP-fabricated LD, after undergoing the two-step IE processing, exhibits markedly enhanced strength and toughness. This improved mechanical performance effectively resists crack initiation and propagation caused by sharp contacts, thereby contributing to the superior long-term reliability of the LD veneers in the oral masticatory environment. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
The building sector faces increasing pressure to reduce embodied carbon as operational emissions decline and life-cycle impacts of construction materials gain greater attention. Structural components such as roof purlins are widely used in industrial and commercial buildings and therefore represent an important opportunity for reducing material-related environmental burdens. This study presents a life-cycle environmental and economic assessment of alternative roof purlin systems manufactured from conventional and circular materials within a performance-based structural design framework. A life-cycle assessment and life-cycle cost analysis was conducted in accordance with EN 15804 + A2, covering Modules A1-A3 and C1-C4, with Module D benefits reported separately, using Australian life-cycle inventory datasets. Five purlin systems were evaluated, including recycled waste composite (RWP), cold-formed steel (CFS), timber (TP), fibre-reinforced polymer (FRP), and aluminium alloy (AAP). All systems were structurally optimised to achieve equivalent load-bearing capacity and serviceability over a 50-year service life, using 1 m2 of supported roof area as the functional unit. Results indicate that TP exhibits the lowest global warming potential (1.21 kg CO2-eq/m2), while RWP provides competitive environmental performance (6.96 kg CO2-eq/m2) and the lowest life-cycle cost (4.93 A$/m2). FRP and AAP exhibit the highest impacts under the primary Modules A-C comparison, although metallic systems show improved apparent performance when Module D benefits are reported separately. Integrated environmental-economic evaluation indicates that TP and RWP consistently outperform alternatives across multiple decision scenarios. The findings demonstrate that combining structural optimisation with appropriate material selection enables significant reductions in embodied carbon and cost and provides a decision-support framework for sustainable material selection under varying environmental and economic priorities.
Ultralong optical fields are highly desirable for optical manipulation, precision manufacturing, and all-optical magnetization engineering. However, existing approaches generally rely on complex pupil filters or amplitude-phase modulation, increasing system complexity and limiting practical flexibility. Here, we propose a filter-free vectorial focusing strategy for engineering ultralong optical and inverse-Faraday magnetization combs and needles by tightly focusing an azimuthally polarized Airy vortex beam in reflective and non-reflective geometries. The combined effects of Airy-beam autofocusing and high-numerical-aperture vectorial interference generate ∼80λ comb-like structures in the reflective configuration and needle-like counterparts in the non-reflective geometry. Furthermore, the vortex topological charge serves as a deterministic degree of freedom for continuously transforming both optical and magnetization structures from bright-core to hollow-core morphologies, accompanied by an enlarged central dark region and increased peak separation. This strategy establishes a general filter-free framework for deterministic engineering of ultralong optical and inverse-Faraday magnetization structures, offering new opportunities for all-optical magnetic recording, magnetic microscopy, and structured-light-enabled spintronic devices.
The Monash-Peradeniya-Kodikara (MPK) framework interprets the volumetric behaviour of compacted unsaturated soils in the void ratio - moisture ratio - net stress (e - ew -p) space without requiring suction as an independent constitutive variable. Nevertheless, explicit knowledge of suction distributions within this volumetric space can provide additional insight into hydromechanical behaviour and facilitate comparison with conventional suction-based frameworks. This paper reconstructs continuous suction surfaces on and inside the Loading Wetting State Boundary Surface (LWSBS) within the MPK space by combining suction topology inferred from published experimental datasets with a constrained mathematical reconstruction methodology consistent with MPK principles. The reconstruction is divided into three regions relative to the Line of Optimums (LOO). At the wet side of the LOO, suction contours on the LWSBS are reconstructed using effective stress relationships and semilogarithmic compression relationships. At the dry side of the LOO, suction contours are reconstructed from Soil Water Characteristic Curves (SWCCs) extended towards the dry condition using cubic Bezier curves. Suction contours inside the LWSBS are reconstructed on constant net stress planes using fifth-order Bezier curves to generate smooth, continuous, and nonintersecting suction surfaces. Application to kaolin and Merri Creek soils produces suction profiles consistent with reported experimental trends, including suction reduction during constant moisture loading and a distinct transition in contour curvature across the LOO. The reconstructed suction surfaces preserve the fundamental structure of the MPK framework while providing the first explicit continuous hydraulic representation of suction within the MPK volumetric state space. They enable estimation of suction at intermediate soil states where direct measurements are unavailable, facilitate comparison with conventional suction-based interpretations, and establish a foundation for future constitutive, numerical, and coupled hydromechanical modelling within the MPK framework.
