Search Results (3,898)

This study evaluated the crack-bridging capacity of textured coating systems across 60 test specimens using an adapted UEAtc test method, comparing analog dial gauges with two-dimensional Digital Image Correlation (2D-DIC) on acrylic and mortar substrates. Acrylic substrates achieved higher mean bridged crack widths (0.97 to 1.20 mm via dial gauges and 0.39 to 0.51 mm via DIC) than mortar prisms (0.30 to 0.42 mm via dial gauges and 0.21 to 0.36 mm via DIC). The elastomeric topcoat increased nominal crack-bridging by up to 46.2% in DIC measurements, although substrate type was the mechanically dominant factor in the ANOVA ($p<0.001$). Bland–Altman analysis indicated a systematic mean bias of $-0.38\mathrm{mm}$ and significant proportional bias ($y=-1.18x+0.28;R^2=0.61$), demonstrating close agreement for narrow cracks (<0.40 mm) and progressive divergence at larger openings due to mechanical contact seating effects ($ICC(2,1)=0.21$). The main limitations stem from the spatial disparity between discrete substrate fixtures and continuous surface tracking. In conclusion, DIC is a reliable, non-contact technique for mapping continuous strain fields and identifying initial microcracking, but it cannot directly replace mechanical contact gauges across large deformation ranges without bias compensation. Full article

This systematic review and meta-analysis investigated resisted sled training (RST) efficacy compared to unresisted sprint training (UST), alongside the moderating effects of sprint distance, sled load, and surface. Following PRISMA guidelines, PubMed, Web of Science, Scopus and SPORTDiscus were searched up to May 2026. Risk of bias was assessed via the PEDro scale. Twelve studies (N = 324) were included. Data were analyzed using Correlated Robust Variance Estimation (CRVE). Overall, RST reduced sprint times compared to UST (Hedges’ g = −0.250, p = 0.046; I2 = 0.0%). While time reductions were significant for early acceleration (≤10 m; g = −0.360, p < 0.001), and not for longer-distance outcomes (>10 m; g = −0.168, p = 0.293), the between-distance interaction was non-significant (p = 0.094). Moderate loads (g = −0.352, p = 0.062) and indoor gym floors (g = −0.495, p = 0.096) showed larger point estimates than natural grass (g = −0.180) and synthetic tracks (g = −0.197). In conclusion, no statistically significant moderating effects of distance, load, or surface were demonstrated. Because training surfaces influence the actual mechanical stimulus, prescribing sled loads based on velocity decrement (%Vdec) rather than percentage of body mass (%BM) is a promising hypothesis to standardize resistance across terrains, requiring confirmation via future prospective trials. PROSPERO: CRD420261415365. Full article

Prestressed and post-tensioned concrete structural elements constitute approximately 43.4% of modern bridge infrastructure, representing 58.2% of the total bridge surface area due to their long-span capabilities. Despite their structural efficiency, evaluating residual post-tensioning forces and diagnosing localized degradation within internally grouted tendons—such as localized stress corrosion cracking (SCC), grout voids, and moisture infiltration—remains a critical challenge due to geometric confinement and high material attenuation. This paper presents a non-destructive Structural Health Monitoring (SHM) methodology optimized for the continuous and periodic assessment of post-tensioned anchorage zones under operational traffic loads. The proposed Identification of Active Anomalies (IAA) system integrates the Acoustic Emission (AE) method with unsupervised machine learning to classify multi-mechanism structural degradation. By implementing a mathematically transparent k-means clustering framework initialized via the k-means++ heuristic, high-velocity multi-parameter AE data streams are partitioned within an n-dimensional Euclidean feature space. The scientific novelty of this work lies in its real-scale validation on an operational, highly complex cable-stayed bridge, establishing a previously unpublished acoustic signature database (the 2025 Signal Database). The empirical validity of the algorithm’s predictive boundaries was confirmed through forensic physical inspections and material sampling during a major structural rehabilitation in 2026, which corroborated the active corrosion states within heavily confined post-tensioned anchorage blocks. Furthermore, extracted AE pattern classes are explicitly correlated with structural crack opening widths, enabling real-time tracking of macro-defect propagation, anchorage slippage, and active micro-structural corrosion. Full article

To address sustained deviation from coverage lanes when an unmanned surface vehicle (USV) executes a complete boustrophedon coverage path under current disturbances, this study proposes an adaptive current-aware line-of-sight (ACA-LOS) guidance method based on online current estimation. The local current is estimated online from the kinematic velocity relationship between the USV and the surrounding water, and its path-normal component is extracted. The estimated path-normal current is used both to construct a current-compensating heading correction and, together with the cross-track error, to adjust the LOS lookahead distance and generate the desired ACA-LOS heading. Complete-path simulations are conducted under constant, time-varying, and spatially varying currents with different current speeds and directions. Relative to conventional LOS, ACA-LOS reduces the mean cross-track root mean square error (RMSE) by 40.80%, increases the tolerance-band compliance rate ($R_b$) by 27.48 percentage points, and reduces the cumulative cross-track deviation area ($A_{\mathrm{d}}$) by 68.68%. ACA-LOS suppresses sustained lane deviation caused by current disturbances and improves lane keeping throughout complete boustrophedon path execution. The method supports the extension of USV operation from single-trajectory tracking to long-duration, continuous coverage execution and provides a reference for unmanned and intelligent waterborne operational equipment. Full article

To improve the yaw-stability tracking accuracy and torque smoothness of distributed-drive electric vehicles (DDEVs) under high-speed double-lane-change maneuvers and crosswind disturbances, this paper proposes a multi-agent-system (MAS)-based direct yaw moment control (DYC) method using full-order terminal sliding mode (FOTSM) control. First, based on the vehicle yaw dynamics model and the vector superposition principle, the whole-vehicle yaw-rate and sideslip-angle responses are decomposed into the local contributions of four wheel agents. A leader–follower MAS tracking framework is then established, in which the yaw-stability reference model acts as the virtual leader, and the four wheel agents act as followers. Second, the yaw-rate error and sideslip-angle error are combined into an aggregated tracking error, thereby transforming yaw-stability control into a second-order nonlinear MAS tracking problem. A FOTSM DYC law is designed, and Lyapunov analysis proves that the closed-loop error system reaches the sliding surface and converges within finite time. Finally, hardware-in-the-loop experiments are conducted under double-lane-change maneuvers with and without crosswind disturbance. Compared with the uncontrolled case and a conventional MAS-based linear sliding mode controller, the proposed method reduces yaw-rate and sideslip-angle deviations, improves trajectory-tracking performance, maintains yaw stability under crosswind disturbance, and suppresses wheel-driving-torque chattering. Full article

Battery-management systems observe current, terminal voltage, limited temperature measurements, and operating setpoints, but not the internal variables of electrochemical theory, so routine signals generally cannot identify a unique mechanism. We present a human-guided, generative-AI-assisted methodology that translates physics-based expectations into deterministic, auditable screening rules: human scientific authority fixes the physical assumptions, evidence requirements, and permissible claims, artificial intelligence supports development, and runtime evaluation is non-generative. LiFePO₄ is the test case. A Zeng–Bazant current-dependent plateau approximation supplies a physics-based reference, and a bivariate representational precedent motivates a composite, reference-dependent voltage residual that is not identified as thermodynamic work. Eleven observable screens return present, absent within resolution, indeterminate, or unavailable. Four evidence forms are separated. Digitized model curves show the reduced plateau relation tracks its parent phase-field simulation through moderate rates, with a high-rate limitation. Published temperature-conditioned discharge profiles show stable plateau elevation and flattening from 268 to 298 K across 0.5C–2C, with mixed 2C curvature. Measured replicates of a commercial cylindrical cell at two ambient setpoints resolve a within-run surface-temperature depression whose integrated first-law balance is heat-rejection-dominant and compatible with, but not uniquely attributed to, a literature-bounded reversible contribution. Controlled synthetic cases verify deterministic feature recovery and abstention without establishing a mechanism. Full article

Synthetic Aperture Radar (SAR) backscatter serves as a key tool for tracking surface water dynamics; however, single-source data dependencies introduce systematic bias tied to the specific physical limitations of the signal. A primary challenge in SAR analysis is the backscatter ambiguity created by ‘water look-alike’ surfaces, which frequently result in false-positive water detections. We show that integrating interferometric repeat-pass coherence significantly enhances the robustness of hydrological mapping in environments where backscatter is prone to signal ambiguity. Using global-scale C-band Sentinel-1 (S1) VV-polarized one-year mosaics (December 2019 to November 2020), we first analyzed normalized backscatter and coherence signatures across major land cover and land use (LULC) classes. To benchmark the complementary value of these data streams, a tile-based minimum-error thresholding approach was applied to detect permanent water surfaces across five challenging global test sites. This evaluation was conducted without post-processing or masking to isolate the fundamental strengths of each dataset. The results indicate that coherence is an optimal complement to backscatter in arid and bare soil regions, where it vastly outperforms backscatter in mapping inland water surfaces. Crucially, since the spatial overlap of False Positives and False Negatives between datasets is minimal, the inherent complementarity of the datasets is proven here via a logical AND fusion rule, which significantly mitigates commission errors and yields substantial improvements in the aggregated F1-score and IoU performance. Analysis-ready L-band NISAR products could contribute to a more comprehensive approach for operational, large-scale surface water assessments. Full article

Pulmonary delivery of anti-tuberculosis drugs has emerged as a promising alternative for increasing local drug concentrations whilst minimising side effects. Natural polymers—polysaccharides capable of forming polyelectrolyte complexes (PECs) through electrostatic interactions—show great promise in this field. In this study, mucoadhesive chitosan-gellan gum nanoparticles were developed for the controlled release of isoniazid using the polyelectrolyte complex coacervation method. Parameters such as the chitosan-to-gellan gum ratio and the medium pH were investigated to achieve suitable particle size, polydispersity, surface charge, drug loading and encapsulation efficiency. The morphology of the produced nanoparticles was determined using transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA), which confirmed the formation of nanoscale spherical particles. The mucoadhesive properties were tested on ovine lung tissue using fluorescence retention analysis, whilst in vitro drug release was studied under physiological conditions. Antimycobacterial activity against Mycobacterium tuberculosis H37Rv was assessed using the Mycobacteria Growth Indicator Tube (MGIT) system, followed by subculturing on Löwenstein–Jensen medium. The produced nanoparticles exhibited high mucoadhesion, maintaining prolonged retention on lung tissue. Drug release showed an initial burst followed by sustained release over 24 h. These results demonstrate that CSGG–INH nanoparticles possess sustained drug release, good mucoadhesion to the lungs and high antimycobacterial activity, supporting their further development as potential carriers for pulmonary delivery of anti-tuberculosis drugs. Full article

In this paper, an ultra-local model-based finite-time sliding mode control (ULM-FTSMC) method is developed for tracking quadrotor position and attitude in the presence of uncertainties and external disturbances. Based on an ultra-local model technique, the proposed ULM-FTSMC scheme consists of an adaptive neural network observer (ANNO) and a non-singular fast terminal sliding mode controller (NFTSMC). The ultra-local model is employed to approximate complex quadrotor dynamics, thereby reducing the complexity of controller design. The ANNO is designed to estimate the state variables required for subsequent control design and compensate for the lumped disturbances. Furthermore, an improved reaching law incorporating a variable exponent and multiple power terms is developed for the nonsingular fast terminal sliding surface, based on which an NFTSMC is constructed to achieve accurate trajectory tracking within finite time. The stability of the closed-loop system and the finite-time convergence of the tracking errors are rigorously established using Lyapunov theory. Finally, comparative numerical simulations with several existing controllers are conducted to demonstrate the effectiveness and superiority of the proposed method. Full article

To address time-varying communication topology, actuator response delay, and limited inter-UAV communication resources in the multi-UAV approach of a maneuvering target, this paper proposes a cooperative rendezvous/tracking control law combining a prescribed-time extended state observer (PTESO) with a dynamic event-triggered mechanism (DET). A three-state PTESO is designed whose observation error converges, within a prescribed time independent of the initial error, into a compact set related to the disturbance upper bound. Along the line-of-sight (LOS) direction, the remaining flight times of the UAVs are driven to consensus within a prescribed time toward a specified arrival instant via a threshold-adaptive DET; along the LOS normal direction, prescribed-time convergence of the elevation and azimuth angle errors is achieved through a time-varying-gain sliding surface. The guidance gains are designed from the worst-case algebraic connectivity of the candidate topology set, ensuring uniform validity under arbitrary switching. After accounting for first-order autopilot inertial dynamics, the command tracking error is proven uniformly ultimately bounded. Simulations of four UAVs cooperatively approaching a maneuvering non-cooperative object under periodic topology switching and actuator delay show an arrival-time deviation below 0.01 s, a terminal position error under 0.08 m, and 75–91 average inter-UAV triggers, outperforming existing prescribed-time/fixed-time cooperative guidance methods. Full article

Convection-permitting simulations resolve the deep convective cells that organise Mediterranean tropical-like cyclones. They also generate localised pressure minima that can capture a conventional cyclone tracker and pull it away from the synoptic-scale centre. We introduce High-Resolution Multilevel Python-Based Algorithm for Cyclones’ Centroid Tracking (HIMPACT), an open-source Python algorithm developed by the corresponding author within the CETEMPS framework, that stabilises cyclone-centre identification by combining three elements: a multi-level geopotential analysis restricted to the 800–950 $\mathrm{hPa}$ layer, a percentile-based threshold that isolates the vortex core from convective perturbations, and a convex-hull centroid that depends on the geometry of a percentile-defined core rather than on a single extreme grid point, so that an isolated convective pressure deficit cannot displace the estimate by more than a fraction of the core radius. HIMPACT was evaluated in four tracking experiments across three Mediterranean cyclones at grid spacings from 2 to 28 $\mathrm{k}\mathrm{m}$ using WRF, ICON-DREAM and ERA5, while MPAS was additionally used to test portability and computational scaling on an unstructured Voronoi mesh. Across the three experiments in which the driving data resolve a coherent lower-tropospheric cyclone structure, the best five-level configurations reduce root-mean-square displacement errors by approximately 16–48% relative to the corresponding single-level configurations. Activating the absolute minimum alongside the centroid more than doubles the error variance when the pressure field is multi-modal. The 800–950 $\mathrm{hPa}$ window avoids both surface extrapolation artefacts below 950 $\mathrm{hPa}$ and mid-tropospheric steering signatures above 800 $\mathrm{hPa}$. A counterexample with an extratropical storm exposes a data-quality threshold: when the driving dataset does not resolve a vertically coherent cyclone structure, the multi-level weighted mean diverges, and single-level tracking becomes the safer choice. HIMPACT is model-agnostic, requires no format conversion, and runs on a single CPU core at approximately 9.8–41.3 s per time step for the recommended five-level configuration across the tested back-ends; substantially larger costs occur for high-level-count MPAS configurations. Full article

Dissimilar friction stir welding (FSW) of titanium alloys offers a route to spatially optimized aerospace structures, but the asymmetric thermomechanical environment produces heterogeneous microstructures and textures whose interaction with mechanical performance is not well characterized. A near-α/α+β combination of titanium alloys, Ti–6242 SG (advancing side, ADV) and Ti–54M (retreating side, RET), was welded across a matrix of rotation speeds (225–325 rpm) and traverse speeds (100–150 mm·min⁻¹), spanning rotation-to-traverse-speed ratios N/v of 1.80–2.75, which was used throughout as an empirical processing index that orders the conditions of this matrix rather than as a measure of specific heat input. Microstructure, phase identification, relative diffracted-intensity trends, and crystallographic textures were characterized by 2D-XRD at three cross-section locations (ADV, weld nugget center [CEN], RET) and correlated with transverse tensile properties and fracture locations. Partial pole figures were plotted in the simple-shear reference frame with ideal-orientation overlays, intensities in multiples of a random distribution (m.r.d.). The CEN develops the strongest textures, dominated by a basal {002}_α component (20–31 m.r.d.) with poles near the normal direction; this concentration lies away from the ideal shear fiber loci and is more readily explained by orientation inheritance during the β→α transformation on cooling than by direct shear, although unambiguous identification of variant selection would require orientation-resolved measurements. The RET develops {101}_α and {100}_α pole concentrations clustering near the ideal P-fiber loci, consistent with deformation-related texture development, intensifying with both rotation and traverse speed. The ADV shows mixed textures varying non-monotonically with parameters. Two conditions of nearly identical N/v obtained from different parameter combinations (225 rpm/125 mm·min⁻¹ and 275 rpm/150 mm·min⁻¹) nevertheless develop measurably different streak morphologies, microstructures, textures, and tensile responses, showing directly that N/v orders but does not determine the thermomechanical state. Yield strength is uniform (≈900–940 MPa) across the full matrix, consistent with a Schmid-factor estimate in which the basal-near-ND CEN texture gives a very low resolved shear stress on basal systems under transverse loading; joint efficiencies reach ≈90–96%. Ductility, in contrast, tracks consolidation quality rather than texture severity: fracture strain rises almost monotonically with N/v, from ≈0.6–1.4% at N/v ≈ 1.8 (defect-driven, erratic failure) to ≈5.4–6.0% at N/v = 2.60, despite the latter condition carrying the strongest RET pyramidal texture. Full-field strain measurement shows the weld nugget to carry the lowest strain and the highest apparent stiffness of any zone in every condition for which the load record is reliable, with strain accumulating on the advancing side. Consolidated conditions fracture on the advancing side where deformation concentrates, whereas the lowest N/v and longest-exposure conditions fracture in the nugget center; all fracture surfaces are ductile, with the crack path following continuous α layers at prior-β grain boundaries. A favorable processing range within the investigated parameter matrix is N/v ≈ 2.2–2.6, with the best overall combination at 325 rpm and 125 mm·min⁻¹ (N/v = 2.60: UTS ≈ 1010 MPa, ≈5.4–6.0% elongation). Within the parameter range examined here, consolidation quality is the first-order design variable for this dissimilar system, with the zonal texture architecture setting the yield strength level. Full article

Musculoskeletal fatigue precedes much of the injury burden in manufacturing, yet most monitoring schemes register an injury only once it has occurred, which becomes critical where operators share a workspace with collaborative robots. This paper presents a wearable sensing platform and a learning pipeline that track operator fatigue continuously during human–robot collaborative assembly, evaluated in silico. Eight surface electromyography (sEMG) channels, six inertial measurement units, and four force-sensitive resistors feed a 127-dimensional descriptor computed over 30 s windows. Eight classifiers were trained on 1536 simulated working hours from 24 anthropometrically diverse synthetic operators. Under leave-operators-out cross-validation, a 1D-CNN–LSTM hybrid reached 89.3% three-class accuracy and 87.1% balanced accuracy with 73.9 k parameters and 22 ms inference on a Jetson Nano; a CNN–BiLSTM–attention model gained 0.3 percentage points for 1.6 times the parameters, a difference that was not statistically significant. Ablation attributed 7.0 points of balanced accuracy to sEMG and 5.0 points to three contextual variables requiring no sensor. Alerts preceded severe fatigue by roughly 12 min, and alert-triggered task reallocation cut peak shoulder load by 43% while retaining 94% of baseline throughput. Every result characterizes a simulated environment: the study establishes internal consistency, latency feasibility, and design trade-offs, and prospective validation with human operators remains a prerequisite for deployment. Full article

A fractional graph-evolution model is formulated on a surface-derived thoracic-aortic branch tree and evaluated through multiresolution geometry and controlled joint-parameter experiments. A checksum-tracked source audit separates three model-specific MRI collections from a shared nominal wall surface and confirms that no validated MRI–STL transformation is available. The surface pipeline yields five terminal openings, three junctions, seven semantic branches, refined cross-sections, and an unapproved same-source candidate. Consequently, the instantiated operator is dimensionless and geometry normalized, rather than a calibrated pressure–flow operator. Graphs with 50, 100, 200, and 400 nodes preserve topology; relative to the internal 400-node discretization, the 200-node graph has a 9.20% 95th-percentile discrepancy in the first 12 positive eigenvalues and a 7.58° maximum principal angle for the first 10 modal subspaces. The analysis establishes a Caputo-consistent control-volume reduction, finite-horizon well-posedness for bounded forcing, non-normal augmented dynamics, observation leakage, finite-band phase conditions, and residual power-law stability. In 810 off-grid synthetic experiments, seven parameters are estimated jointly with repeated noise, multistart optimization, profile likelihood, and held-out testing. The median fractional-order error is 0.001304 and the median held-out complex NRMSE is 0.01086. The results support controlled synthetic practical identifiability on a shared nominal anatomy, not measured hemodynamic calibration or physiological-memory identification. Full article

In order to maintain stable formations of the underactuated unmanned surface vehicles (USVs) under ocean disturbances and reduce control chattering, a fuzzy adaptive super-twisting sliding mode control method combined with dynamic cooperative error correction is introduced in this paper. At the kinematic level, a dynamic cooperative error correction scheme is presented to include the relative positions of the neighboring vehicles. This results in a transition from independent tracking to interactive cooperation, thus improving the rigidity of the formation during maneuvers. Secondly, a composite inner-loop structure is designed by employing a nonlinear disturbance observer to counteract the effects of external loads. A fuzzy logic system is included to modify the super-twisting sliding mode gains in real-time. This approach effectively combines rapid error reduction with signal smoothness, addressing the trade-off between response speed and chatter suppression. Moreover, tracking differentiators and low-pass filters are utilized to obtain continuous control signals. The Lyapunov analysis indicates that the closed-loop system achieves semi-global uniform ultimate boundedness. Simulation results show that the proposed method can maintain high formation precision and obtain smooth control outputs with reduced chattering. Full article