Search Results (42,870)

LiDAR SLAM relies on reliable geometric constraints to estimate sensor motion and maintain consistent maps in complex three-dimensional environments. Planar features are commonly used for LiDAR registration, but repeatedly fitting local planes from neighboring points brings extra computation and may be sensitive to noisy observations. Voxel-plane maps address this issue by storing planar structures in voxel cells, yet most existing methods still construct planes and assign points to voxels according to the nominal point coordinates. When LiDAR measurement noise and pose prediction errors are ignored, plane parameters may be biased and points may be associated with unsuitable voxels. This paper presents UVP-LIO, an uncertainty-aware voxel-plane mapping method for LiDAR-inertial odometry. The measurement uncertainty of each LiDAR point and the uncertainty from state estimation are jointly propagated to the world frame to obtain a point-wise covariance. This covariance is then used in uncertainty-aware voxel association and covariance-weighted incremental plane updating. Plane thickness is further introduced to weight point-to-plane residuals during registration. Experiments in a LiDAR-only configuration on KITTI and in a LiDAR-inertial configuration on M3DGR show that UVP-LIO improves trajectory consistency and mapping robustness, especially in scenes with weak or ambiguous geometric constraints, while maintaining real-time performance. Full article

Knowledge of the time-dependent behavior of polyvinyl alcohol (PVA) gel polymer electrolytes (GPEs) is essential for their application in structural supercapacitors (SSCs) at lower degrees of integration (DoI). Due to the soft, viscoelastic nature of GPEs, their mechanical response under compressive and transient loading is critical for maintaining necessary long-term electrode contact. To enable reliable structural design configurations, a tailored PVA GPE, prepared via a freeze–thaw method, was examined using compressive stress-relaxation testing. The mechanical response was modeled using a novel, non-linear viscoelastic constitutive framework, which couples a time-dependent elastic modulus for the non-linear loading phase with a Prony series for accurate relaxation prediction. The parameters for this practical framework were successfully derived from one single stress-relaxation experiment. Experimental results confirmed pronounced viscoelastic relaxation and up to 10% cyclic hardening. Implemented via finite-element method (FEM) analysis, the non-linear model achieved high accuracy (0.8% average relative deviation), significantly outperforming a linearized model (1.36% deviation). This validated framework is crucial for optimizing the mechanical stability of SSC assemblies and predicting the GPE’s short-time response under transient loading events. Full article

To address the degradation of low-probability-of-intercept (LPI) radar waveform recognition caused by noise dispersion and the masking of modulation-dependent structures in low-SNR Choi–Williams distribution (CWD) images, this paper proposes RepNRS-LPI-Net, an integrated framework for robust recognition and lightweight deployment. CWD converts each received waveform into a two-dimensional time–frequency image that characterizes temporal evolution, frequency variation, and localized energy distribution. The proposed RepDW block integrates 3 × 3, 1 × 3, and 3 × 1 depthwise branches with an identity branch during training to capture joint time–frequency, temporal-direction, and frequency-direction responses while preserving informative features. These branches are then algebraically fused for efficient deployment. In addition, NRS-ECA combines channel recalibration with channel-dependent soft shrinkage to attenuate weakly supported noise-like activations without assuming that all weak responses are noise. Focal modulation and label smoothing are conservatively adopted as auxiliary training strategies to address difficulty imbalance and confidence regularization. Experimental results show that RepNRS-LPI-Net achieves 79.553350% overall accuracy and 49.137529% low-SNR accuracy, while the deployment form reduces the parameter count to 37,142 and the learned-layer computation to 15,722,496 MACs. These results indicate that RepNRS-LPI-Net improves measured recognition performance while substantially reducing deployment complexity under the modeled multipath, Rayleigh-fading, Doppler, and AWGN conditions. Full article

Through-going structures are widely distributed in rock masses of underground engineering, and their dip angles act as the core factor affecting the stress field and mechanical response of surrounding rock. To reveal the mechanical mechanism of rock masses containing through-going structures with different dip angles, this study adopts a combined method of theoretical derivation, indoor model testing and numerical simulation. Firstly, a plane strain mechanical model is established to classify Tectonically-induced Stress, Residual Gravitational Stress and engineering-induced stress, and the theoretical formulas for stress components, stress residual coefficient and stress deflection angle are derived. Secondly, rock-like specimens with through-going structures of various dip angles are prepared and biaxial compression tests are carried out to monitor mechanical parameters such as surrounding rock strain and peak strength. Finally, a large-scale numerical model is built by FLAC2D (version 7.0) software to simulate the whole process of stress equilibrium and excavation unloading of rock mass under a normal stress of 20 MPa. Then the data of principal stress, stress components, stress residual coefficient and deflection angle under different dip angles are extracted. The results show that the dip angle of through-going structure exerts a prominent regulatory effect on the rock mass stress field. With the increase of the dip angle, the Tectonically-induced Stress decreases continuously while the Residual Gravitational Stress rises gradually. The variation trend of stress deflection angle is highly consistent with structural dip angle, and the influence of Residual Gravitational Stress on deflection angle is limited. Due to the differences in loading modes and model sizes between indoor tests and numerical simulations, the evolution laws of stress residual coefficient show opposite trends, but both results verify the dominant effect of structural dip angle. Combined with theoretical, experimental and numerical results, the proposed theoretical system can effectively describe the stress evolution law of rock masses with through-going structures, which provides theoretical reference and technical support for the stability analysis of surrounding rock in similar underground engineering. Full article

Accurate finite element models are essential for structural condition assessment, yet nominal material properties and idealized boundary conditions can produce systematic discrepancies between numerical and measured dynamics. This study proposes a physics-constrained sparse response-surface framework that combines Elastic Net basis selection, mechanically prescribed monotonicity, adaptive sample enrichment, and identifiability-aware uncertainty assessment within a transparent finite element model-updating procedure. A scaled steel truss was tested using millimeter-wave radar, and the first three vertical natural frequencies were identified by stochastic subspace identification. The resulting sparse polynomial surrogate was independently validated before bounded inversion and ANSYS back-substitution. The mean frequency error decreased from 5.55% to 0.82%. Jacobian and bootstrap analyses further showed that several combinations of material and boundary parameters can reproduce similar modal responses, so the updated parameters are best interpreted as a coupled equivalent calibration state rather than unique direct measurements. The proposed framework therefore improves physical consistency and computational efficiency while explicitly retaining the uncertainty associated with weakly identifiable parameter directions. Full article

Reliable electricity supply in Colombia’s Non-Interconnected Zones requires sustainable and low-cost energy technologies. Vertical-axis hydrokinetic turbines are promising for this purpose; however, their relatively low power coefficient remains a major challenge. This study combines transient 2D and 3D $k$–$\omega$ SST computational fluid dynamics (CFD) simulations with hydraulic channel experiments to investigate a hybrid Darrieus–Savonius turbine. A 27-case Design of Experiments (DoE) based on 2D CFD was first applied to screen the effects of rotor radius ratio (RR), attachment angle (AA), and water velocity. Within the investigated design space, the configuration with $\mathrm{R}\mathrm{R}=0.5$ and $\mathrm{A}\mathrm{A}=0^{\circ }$ produced the most favorable average performance. The selected configuration was subsequently analyzed using 3D CFD and experimentally evaluated at TSR values of 1.0, 1.1, and 1.2. At TSR = 1.0, the 3D model predicted ${\mathrm{C}}_{\mathrm{P}}=0.1525$, closely matching the experimental value of 0.1541 with a relative error of 1.05%. The results demonstrate that 2D CFD is useful for computationally efficient parameter screening and qualitative trend identification, but it overpredicts absolute performance because it neglects blade tip vortices, spanwise flow, and volumetric wake interactions. Three-dimensional CFD is therefore required for reliable performance prediction and analysis of the complex flow structures governing hybrid hydrokinetic turbine behavior. Full article

Foam concrete is a lightweight material characterized by low density and moderate mechanical strength, which can be combined with aluminum alloys to form a novel type of column. Such composite members enable rapid assembly, disassembly, and functional reconfiguration in prefabricated structures. However, research on the axial compressive performance of this new column system remains limited. This study investigates the axial behavior of aluminum alloy-foam concrete short columns through a combination of numerical simulation, theoretical analysis, and machine learning prediction enhanced by the SHAP (SHapley Additive exPlanations) interpretability method. A three-dimensional finite element model was developed in ABAQUS to examine the effects of frame thickness, foam concrete strength, and section dimension on load-bearing capacity. The results indicate that the column sectional dimensions have a significant influence on the axial compressive capacity. The foam concrete strength and frame thickness have relatively smaller effects. In addition, the frame thickness can effectively restrain lateral deformation and delay buckling. Based on the confinement mechanism, polynomial fitting, Mander’s model, and a composite column formulation were proposed for axial capacity prediction. Furthermore, eleven machine learning models were trained on 64 simulation datasets 64 independent computational experiments, among which the Gradient Boosting Decision Tree (GBDT) demonstrated the best performance (R² = 0.9984, MAE = 5.97, RMSE = 7.51). SHAP analysis further revealed the relative contributions of key features, showing that section dimension is the most influential parameter, followed by foam concrete strength, while frame thickness contributes the least. These findings not only enhance the theoretical understanding of the load-transfer mechanism of columns but also provide reliable predictive models and analytical formulations for their application in lightweight prefabricated structures. Full article

The development of sustainable materials for additive manufacturing (AM) has positioned starch as a compelling alternative to conventional thermoplastics. However, the successful implementation of starch in 3D printing (3DP) relies on precise control of its supramolecular organization, rheological behavior, and processing conditions. This article analyzes starch-based hydrogels for extrusion-driven AM, establishing explicit links between molecular architecture, gelatinization, and viscoelastic performance. The influence of key rheological parameters on extrudability and shape fidelity is examined in parallel with critical processing conditions. Chemical and physical modification routes of starch are compared in terms of their structural impact and printability enhancement. The integration of additives such as polysaccharides, proteins, and inorganic salts is discussed as a strategy to overcome intrinsic mechanical limitation. Emerging non-food application in drug delivery, tissue engineering, or conductive/intelligent hydrogels demonstrates the expanding technological relevance of starch-based formulation. Remaining challenges include predictive, rheology-based design, and the development of multifunctional 4D-printing capabilities. Progress in this field is crucial for positioning starch as a robust platform for sustainable AM, but, despite this progress, a systematic and quantitative framework linking starch molecular architecture and rheological behavior to printing-process parameters and outcomes is still lacking, thus constituting the central gap addressed in this review. Full article

The configuration of AUTOSAR Basic Software (BSW) modules relies on verbose AUTOSAR XML (ARXML) files that are complex, error-prone, and costly to produce manually—particularly for safety-critical modules governed by ISO 26262. This paper presents a two-stage approach to automating BSW configuration generation that generalizes to any ECU Configuration (ECUC)-based module: a fine-tuned large language model (LLM) generates a compact JSON intermediate representation capturing only semantically meaningful parameters, which a deterministic expansion function reconstructs into schema-conformant ARXML. We fine-tune three open-weight models (Qwen3-8B, Ministral-3-8B-Instruct, Llama 3.1 8B) with Quantized Low-Rank Adaptation (QLoRA) on 6050 compositionally generated Watchdog Manager (WdgM) samples spanning five complexity tiers with 30+ prompt templates, and introduce a hierarchical evaluation pipeline combining schema validation with referential integrity, structural completeness, parameter accuracy, and semantic constraint satisfaction. The compact representation reduces output tokens by approximately 8–10× compared to full ARXML. All three models achieve closely comparable performance (0.815–0.836 overall score), with Llama 3.1 8B scoring highest (0.836) and every model reaching ≥93% schema validity and ≥72% parameter accuracy—an 8.4× improvement over zero-shot baselines. Decomposing generation into LLM-driven semantic capture and deterministic expansion is an effective strategy for verbose, schema-governed configuration formats, extensible to other AUTOSAR modules beyond WdgM. Full article

This work proposes a Characteristic Mode Theory (CMT)-guided method for the co-design of radiation and scattering performance of a low-scattering dual-band metasurface array antenna. Conventional design approaches generally treat radiation design and RCS reduction as two separate targets. In contrast, the proposed method leverages the differences in the spatial distributions of radiation and scattering characteristic modes. Dual-band radiation modes are constructed and excited within the central region of the metasurface, while the edge and corner regions are locally reconfigured to suppress dominant scattering modes without significantly perturbing the radiation-mode current distributions. In this way, dual-band radiation and broadband RCS reduction are simultaneously realized within a single metasurface aperture. A systematic radiation–scattering co-design workflow driven by characteristic-mode parameters is established. Modal significance (MS), radiation-mode current distributions, and modal radiation patterns are used to regulate the target radiation modes and determine the feeding configuration. Modal weighting coefficients (MWCs) under plane-wave illumination are used to identify the dominant scattering modes, while the corresponding scattering-mode current distributions are used to determine the structural modification regions and corresponding modification strategies. The antenna developed using the proposed method integrates dual-band radiation and broadband RCS reduction within a single low-profile configuration. Measured results demonstrate that the antenna covers two operating bands of 3.08–3.10 GHz and 3.12–3.18 GHz, with peak gains of 16.0 dBi and 16.4 dBi, respectively. Within the 6.5–10.5 GHz band, more than 10 dB monostatic RCS reduction is achieved under both x- and y-polarized plane-wave illumination. Full article

Recent advances in non-thermal and hybrid extraction technologies—such as pulsed electric field (PEF), ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and enzymatic treatments—have been widely reviewed in the context of general food processing. However, the current literature lacks a critical evaluation of how these modalities reshape the molecular fingerprints, authenticity markers, and cultivar-specific phenolic baselines of olive products, particularly within the Greek production landscape. Existing studies primarily emphasize extraction yield, operational parameters, or sustainability aspects, leaving important gaps regarding molecular consequences, including shifts in secoiridoids, lignans, pigments, oxidation markers, and the composition of by-products such as olive mill wastewater and pomace. This commentary addresses these gaps by integrating emerging extraction technologies with Greece’s omics-enabled analytical capacity (FoodOmicsGR_RI), highlighting how processing innovations may influence authenticity claims, phenolic integrity, and circular economy valorization routes. We discuss mechanistic pathways, molecular-level effects, and technology-specific limitations and propose a structured framework for developing national databases of processing-induced molecular markers. By linking technological mechanisms with cultivar-dependent molecular responses, this commentary aims to support coordinated Greek research efforts toward robust authenticity assurance, sustainable processing, and high-value valorization of olive by-products under evolving climatic and industrial pressures. Full article

Background/Objectives: Vesicourethral anastomosis (VUA) is one of the most technically demanding steps of robot-assisted radical prostatectomy (RARP) and may influence perioperative outcomes and early urinary continence recovery. Objective assessment of technical performance during the learning curve remains limited. We evaluated the learning curve and technical performance of a standardized VUA technique among novice robotic surgeons using a structured video-based assessment. Methods: In this retrospective single-center study, 100 consecutive patients undergoing RARP performed by four novice robotic surgeons were analyzed. All surgeons used the same standardized VUA technique. Operative videos were reviewed and assessed using a modified Robotic Anastomosis Competency Evaluation (RACE) score. Learning-curve trends were analyzed using LOWESS smoothing and mixed-effects regression models. The primary outcome was VUA time. Secondary outcomes included technical performance, anastomosis-related complications, catheterization duration, and urinary continence recovery. Results: A total of 100 procedures were included (25 per surgeon). Increasing surgical experience was significantly associated with shorter VUA time (β = −6.93, 95% CI −7.42 to −6.44; p < 0.001) and higher modified RACE scores (β = 4.99, 95% CI 4.55–5.43; p < 0.001). Median VUA time decreased from 32 min (IQR 29–37) during the early phase to 19 min (IQR 18–20.3) during the late phase (p < 0.001), while median RACE score improved from 13 (IQR 11–15) to 22 (IQR 21–23) (p < 0.001). Positive leak tests decreased from 37.5% to 12.5% (p = 0.03), and the need for additional stitches decreased significantly (p < 0.001). Catheterization time was reduced from 8 to 6 days (p < 0.001). Early urinary continence improved from 37.5% to 65% at 30 days (p = 0.025) and from 60% to 85% at 90 days (p = 0.04), whereas differences were no longer significant at longer follow-up. Conclusions: Novice robotic surgeons performing a standardized VUA technique showed progressive improvements in procedural efficiency and technical performance during their early learning curve. These findings describe technical progression within a standardized operative framework but do not establish an independent effect of standardization itself. Enhanced technical proficiency was accompanied by improved perioperative parameters and a faster recovery of early urinary continence. Video-based assessment may represent a valuable tool for objective monitoring of skill acquisition during robotic surgical training. Full article

Persistence, coexistence, competitive exclusion, and global asymptotic stability (GAS) are closely related problems in mathematical epidemiology that are often treated by model-specific arguments. We develop a unified approach to GAS based on Perron–Volterra Lyapunov functions $L_p$, for multi-strain epidemic reaction networks. For bilinear m-strain models with irreducible rank-one infection blocks and block-diagonal next-generation structure, these functions yield a generic competitive-exclusion partition of parameter space into at most $m+1$ regions: either the disease free equilibrium is GAS, or exactly one dominant strain persists and its boundary endemic equilibrium is GAS; see non-generic tie surfaces on which the corresponding reproduction numbers coincide. We also prove a second complete GAS partition, for two-strain models with increasing concave incidence and scalar, non-interacting strain blocks, extending the Rahman–Zou result beyond rational saturating incidence. In this class, the disease-free, single-strain, and coexistence equilibria may all occur, and explicit Lyapunov functions provide the full exclusion/coexistence partition among the four possible equilibrium supports. The construction combines five ingredients: siphons, which determine forward-invariant boundary faces; triangular Jacobian structure on siphon faces; the Metzler property of transversal Jacobians and their Perron eigenvectors; regular next-generation splittings, whose spectral radii determine invasibility; and boundary transcritical invasion relays linking eigenvalue crossings to the emergence of equilibria on adjacent faces. The resulting Perron–Volterra functions combine Volterra entropy terms for resident variables with Perron-weighted linear functionals for absent strain blocks. These constructions are implemented in the Mathematica package EpidCRN, which computes siphons, transversal blocks, invasion data, Perron weights, and candidate Lyapunov functions. For the two model classes considered here, these candidates are proved to be genuine Lyapunov functions and yield complete generic GAS partitions. Full article

Water contamination with surface-active agents, such as sodium lauryl sulfate (SLS), represents a serious environmental concern, driving the need for efficient and low-cost alternative adsorbents as a step toward sustainable waste valorization. In this study, waste biomass derived from plum stones, date stones, and walnut shells was successfully transformed into activated carbons via chemical activation using potassium hydroxide (KOH) at 850 °C with a 1:1 impregnation ratio. The synthesized materials underwent comprehensive physicochemical characterization utilizing TG-DSC, elemental analysis, Boehm titration, SEM, TEM, and nitrogen physisorption (BET), whereas their adsorption performance was evaluated against aqueous SLS solutions across various concentrations. The obtained results reveal a predominantly microporous structure with a high specific surface area, reaching up to 1059.01 m²/g for ACdate. The equilibrium adsorption data were well described by the Langmuir isotherm model, which yielded model-estimated asymptotic adsorption capacities (q_m) of 219.70 mg/g for ACwalnut, 178.25 mg/g for ACdate, and 57.80 mg/g for ACplum. These values represent Langmuir-derived model parameters rather than experimentally attained adsorption capacities within the investigated concentration range. Notably, despite having a lower specific surface area than ACdate, ACwalnut exhibited the highest Langmuir-estimated q_m, which may be associated with its structural balance and well-developed mesoporous network (0.210 cm³/g), facilitating the intraparticle transport of SLS molecules. These findings highlight that high efficiency originates from a synergistic combination of accessible porosity, a mesoporous transport network, hydrophobic character, and specific surface functional groups, demonstrating the exceptional potential of these activated carbons for anionic surfactant wastewater remediation. Full article

The mechanical performance of hemp-containing denim fabrics depends not only on fibre selection but also on how fibre composition is translated into yarn and fabric structure. Substituting part of the cotton warp with hemp is one possible step toward more sustainable denim production, but this study makes no independent sustainability claim (i.e., no life-cycle assessment was performed) and instead focuses solely on mechanical behaviour. This study comparatively evaluated eleven denim fabrics produced with 100% cotton or cotton/hemp-blended (69/31) warp yarns and different rigid, elastane-core and PET/PTT+elastane dual-core weft yarns. Grab tensile strength and tear strength were assessed in warp and weft directions and interpreted together with structural parameters. The results showed that mechanical response was governed by the combined effect of warp composition, weft architecture and structural compactness rather than by fibre substitution alone. Fabrics containing hemp in the warp did not show a uniform mechanical gain or loss across the sample set; instead, their tensile and tear behaviour depended on the associated weft design and fabric construction. Core-engineered weft yarns, particularly dual-core structures, altered the balance between tensile and tear response, indicating that yarn architecture played an important role in load distribution and deformation behaviour. Overall, the findings show that the mechanical design of hemp-containing denim fabrics should be approached through an integrated fibre–yarn–fabric perspective. Full article