Search Results (362)

In this study, corrections to the dispersion relation in Kaluza–Klein theory with one extra compactified spatial dimension were analyzed in a static, spherically symmetric case. The Ricci scalar curvatures of spacetime and phase space in the Einstein conformal frame were studied with respect to the parameter space of the model and for different observers. The presence of a non-zero phase space curvature and/or shift vector modifies the Heisenberg uncertainty relation of massive particles, as well as their dispersion relation, leading to an effective mass. Full article

Desert highways have long been subjected to aeolian sand hazards, and sand accumulation on the pavement significantly weakens the surface texture and deteriorates skid resistance, which has become one of the core contributing factors to traffic accidents on desert road sections. Current research predominantly focuses on the attenuation law of the macroscopic friction coefficient of sand-covered pavements; however, the quantitative correlation mechanism between three-dimensional micro-texture characteristics and skid resistance has not been sufficiently revealed, and there is a lack of high-precision skid resistance prediction methods under multi-condition coupling scenarios. To address the above research deficiencies, this paper takes the asphalt pavement in the Tengger Desert region as the research object. A handheld three-dimensional texture scanning system was employed to acquire the three-dimensional pavement morphology parameters under different sand coverages, and the sideway force coefficient (SFC) was synchronously measured under the corresponding conditions. Through Pearson correlation analysis and dual multiple comparison correction using the FDR-BH and Bonferroni methods, the core influencing indicators were identified. Subsequently, a skid resistance prediction model based on a BP neural network optimized by the particle swarm optimization (PSO) algorithm was constructed and horizontally compared and validated with LSTM and PSO-SVM models. The research results show the following: ① under dry conditions, the root mean square height ($S_q$), peak density ($S_{pd}$), arithmetic mean peak curvature ($S_{pc}$), valley void volume ($V_{vv}$), root mean square slope ($S_{dq}$), and developed interfacial area ratio ($S_{dr}$) are significantly linearly correlated with the SFC, among which $S_q$, $S_{pd}$, $S_{pc}$, and $V_{vv}$ are the core controlling indicators, with the absolute values of their correlation coefficients all exceeding 0.73, and ② the constructed PSO-BP prediction model achieved a coefficient of determination $R^2$ of 0.86093 on the test set, and its prediction accuracy and generalization ability are both superior to those of the LSTM and PSO-SVM models, enabling it to effectively characterize the nonlinear mapping relationship between multiple texture parameters and skid resistance. This study can provide theoretical support and a technical basis for skid resistance evaluation, sand accumulation disaster warning, and scientific maintenance decision-making for desert highways. Full article

Distinguishing normative cross-sectional structural age differences from early neurodegeneration requires region-specific characterisation of cross-sectional age-related variation, yet findings remain sensitive to modelling strategy and intracranial volume (ICV) correction. T1-weighted MRI from 187 healthy adults (97 female, 90 male; aged 16.22–81.48 years) in the AgeRisk dataset were segmented using Vol2Brain. Multiple regression models applied to 19 predefined brain regions tested linear and quadratic age, sex, ICV, and signal-to-noise ratio (FDR-corrected within predictor families); hemispheric asymmetry indices were Bonferroni-corrected. Three hypothesis domains were preregistered: age associations, sex differences, and hemispheric asymmetry. Negative cross-sectional age associations were observed in subcortical (hippocampus, amygdala, caudate, putamen, and nucleus accumbens) and cortical regions (insula, temporal and occipital lobes; all $p_{\mathrm{FDR}}<0.05$). The parietal lobe showed significant quadratic curvature ($p_{\mathrm{FDR}}=0.008$); total cortical grey matter showed no age effect. White matter exhibited a positive linear rather than the hypothesised inverted-U relationship. After ICV adjustment, females showed greater grey-matter-dominant volumes and males greater cerebrospinal fluid volume (both $p_{\mathrm{FDR}}<0.05$). Sex-by-age interactions in four subcortical regions indicated shallower negative cross-sectional age associations in females (all $p_{\mathrm{FDR}}\le 0.034$). Age was associated with reduced parietal and temporal hemispheric asymmetry (both $p<0.001$). Findings confirm regionally heterogeneous ageing, ICV-adjusted sex differences, and a selective negative cross-sectional association between age and hemispheric asymmetry, consistent with the broader lifespan literature. Full article

Achieving high-accuracy path following remains challenging for an unmanned surface vehicle (USV) in narrow waterways with time-varying curvature and straight–curve transitions; fixed-parameter line-of-sight (LOS) guidance can cause delayed response, overshoot, and steady-state cross-track error. This paper proposes a curvature-coupled adaptive vector-field integral LOS (AVFILOS) guidance law. It incorporates curvature-adaptive guidance: a lookahead distance regulated by curvature and cross-track error and a field-source radius that contracts with curvature to strengthen centripetal correction in high-curvature regions. A fuzzy adaptive proportional–integral–derivative (PID) controller tracks surge speed and heading. A stability analysis establishes local exponential stability for straight and constant-curvature paths and local ISS with local uniform ultimate boundedness for time-varying curvature under a bounded-rate condition. Across six elliptical and sinusoidal cases, AVFILOS achieved an average root mean square error (RMSE($y_e$)) of 0.1325 m, reducing RMSE($y_e$) by 90.6%, 63.6%, and 37.2% compared with LOS, time-varying LOS (TLOS), and vector-field integral LOS (VFILOS), respectively. Its average maximum absolute cross-track error (Max($|y_e|$)) was 0.3478 m, with reductions of 88.2%, 48.2%, and 30.7%. The ablation and sensitivity results indicate that coupled adaptive mechanisms improve curved-path tracking and reduce overshoot. The simulations indicate that AVFILOS is promising for cross-track-error-sensitive USV navigation. Full article

Aircraft fuselage corrosion inspection requires both image-domain recognition and metric physical-surface localization for maintenance execution. This study develops a camera-calibrated vision measurement framework that combines PWDE-YOLOv8n-based corrosion perception, original-image coordinate restoration, lens-distortion compensation, ray-based surface mapping, and detector-center bias correction. The perception dataset comprised 2143 images and 5941 corrosion annotations and was partitioned at the physical-specimen, acquisition-session, or source-group level into 1500 training images, 429 validation images, and 214 independent detector-test images. Detailed physical localization was evaluated on a six-image metrology cohort acquired in six sessions, containing 21 corrosion boxes and 84 axial coordinates. A six-fold leave-one-image-out procedure was adopted; in each fold, the center-shift parameters were estimated from the other five images and applied unchanged to the held-out image. The proposed method achieved a mean absolute axial error of 0.641 mm (95% image-cluster bootstrap confidence interval: 0.571–0.708 mm), an RMSE of 0.809 mm, a maximum error of 3.262 mm, and a projected physical-plane bounding-box IoU of 87.12%. The expanded uncertainty of the manually established reference coordinates was 0.374 mm at k = 2, and Monte Carlo propagation produced a mean absolute error of 0.656 mm with a 95% interval of 0.618–0.693 mm. The proposed method reduced the MAE by 97.91% relative to local pixel-to-millimeter scaling and by 70.58% relative to conventional calibrated camera mapping, while producing accuracy comparable to planar homography mapping. Within ρ ≥ 1500 mm, W ≤ 150 mm, and θ ≤ 20°, the estimated curvature-induced additional axial error did not exceed 0.683 mm. A separate ten-image deployment evaluation produced a mean axial error of 2.448 mm and an average processing time of 53.35 ms/image. Full article

We investigate null geodesics, photon spheres and black hole shadows for the static spherically symmetric non-Schwarzschild black hole solution of Einstein–Weyl gravity, a higher-derivative extension of General Relativity containing a quadratic Weyl-curvature term. Such higher-curvature theories are motivated by attempts to formulate a quantum theory of gravity, where they improve the ultraviolet behaviour of the gravitational interaction, and also arise naturally as effective descriptions in approaches such as string theory. We employ the numerical black hole solution obtained by Lü et al. to compute the photon sphere, the shadow radius and the angular size of the shadow as observed by static observers. We show that, for black holes of equal mass, the photon sphere, shadow radius and angular size are consistently larger than those of the corresponding Schwarzschild black hole, with the deviations increasing monotonically with the higher-curvature coupling parameter $\alpha$. Motivated by the Event Horizon Telescope observations of M87* and Sagittarius A*, we further compare the predicted shadow size with current observational uncertainties and derive phenomenological upper bounds on the dimensionless coupling $\alpha /m^2$. These results demonstrate that black hole shadow observations provide a promising avenue for testing Einstein–Weyl gravity and constraining quantum-motivated higher-curvature corrections to General Relativity. Full article

Background/Objectives: Corneal power has the largest impact on the variability of intraocular lens (IOL) power predictions, and corneal data from different biometers cannot be used interchangeably. We quantified the systematic differences between the Zeiss IOLMaster 700 (IOLM) and the Heidelberg Engineering Anterion and derived strategies for using both devices interchangeably in IOL power calculation. Methods: In this retrospective single-centre study, 837 eyes of 837 cataract patients were measured preoperatively with both biometers. Harmonic mean corneal front and back surface radii were derived from the flat and steep meridians, and corneal power referenced to the front apex plane was expressed as spherocylindrical power vectors (spherical equivalent, SEQ; astigmatic components C0 and C45). Three mapping strategies were compared using Bland–Altman and double-angle plots: linear regression of corneal radii without (MR) and with (MRI) intercept and multivariate linear regression of the power vector components (MMV). Results: Corneal front surface radii agreed well between devices (MR slope 1.000), whereas the IOLM reported systematically flatter posterior radii (MR slope 0.943), giving a systematically higher total corneal power (43.105 D versus 42.760 D). MRI mapping largely removed the systematic offset in the corneal radii but did not fully correct the astigmatic centroids, whereas MMV mapping aligned both the SEQ and the astigmatic centroids at the origin and yielded smaller confidence ellipses. Conclusions: Measurements from the two devices are not directly interchangeable, primarily because of systematic discrepancies in the reported posterior corneal curvature. Where identical IOL calculation concepts and formula constants are used across devices, conversion of corneal data is mandatory, and multivariate power vector mapping provides superior harmonisation compared with radius-based approaches. Full article

This work aims to explore the gravitational consequences of a recently proposed black hole solution previously introduced, which incorporates quantum gravitational corrections of General Relativity. We initiate our analyses by taking into account the horizon structure, focusing on both the event and Cauchy horizons. Subsequently, we examine the quasinormal modes by considering all types of perturbations—scalar, vector, tensor, and spinorial. To strengthen these results, we also compute the time domain for each perturbation. Next, we turn to the study of optical properties of the black hole. In particular, we investigate null geodesics, the photon sphere and its stability, and the corresponding black hole shadows. Following this, we analyze gravitational lensing phenomena in two regimes: the weak-field limit, utilizing the Gauss–Bonnet theorem, and the strong deflection limit, employing Tsukamoto’s approach. In addition, we address the lensing observables with Event Horizon Telescope (EHT) data for $SgrA*$ and $M87*$. Finally, constraints on the parameter $\xi$—which is introduced by higher-order curvature–scalar gravity, thereby differing from the Schwarzschild solution—are estimated using Solar System measurements such as the precession of Mercury’s orbit, gravitational light bending, and time delay (or the Shapiro effect). Full article

Owing to its efficient energy recovery capability, the pump as turbine (PAT) has attracted considerable attention and has been widely applied in micro hydropower systems. However, under off-design conditions, large-scale helical vortex ropes are readily induced in the draft tube, causing severe hydraulic losses and flow instability. Because existing theoretical models do not account for the slip effect at the impeller outlet, this study combines vortex dynamics theory with numerical simulation and introduces a correction coefficient to develop a Burgers vortex-based analytical wake vortex model for a PAT with splitter blades. The model is verified by its ability to predict the peak tangential velocity and radial decay trend of the vortex core. In addition, the influence of draft tube configuration on vortex rope evolution is revealed using the Liutex vortex identification method and enstrophy analysis. The results show that the geometric curvature of the elbow draft tube induces vortex rope breakup and high energy dissipation. Finally, entropy production theory is used to quantitatively evaluate the vortex suppression benefit and hydraulic loss caused by deflector plates. The results indicate that the transverse deflector plate (TDP) provides a significantly better suppression effect than the longitudinal deflector plate (LDP) by disrupting the circumferential continuity of the vortex rope. Although increasing the insertion depth of the deflector plate improves vortex suppression, it induces non-negligible local high-entropy production on the upstream-facing surface (US). This study clarifies the physical mechanism of wake vortices in a PAT with splitter blades and provides theoretical guidance for efficient PAT operation and wake vortex control. Full article

Three-dimensional skip-reentry trajectory tracking is challenging for hypersonic glide vehicles because of strong nonlinearity, pronounced state oscillations, model parameter uncertainty, and bank-angle constraints. This paper develops a trajectory-tracking control method based on the drag-acceleration profile and piecewise nonsingular practical prescribed-time control. A three-dimensional point-mass model that accounts for the Earth’s curvature and rotation is first used with predictor–corrector guidance to generate a reference skip trajectory considering process constraints and terminal requirements. The longitudinal bank-angle magnitude and the lateral bank-angle sign are then obtained separately. Taking the cosine of the bank angle as the control input, the drag-tracking error is formulated as a second-order control-affine system. The proposed controller uses an odd cubic polynomial extension to remove the derivative singularity of low-order fractional powers near the origin, and combines a dual-power reaching law in the prescribed-time phase with a linear hyperbolic-tangent holding law after that phase. Using Dini derivatives, a cited predefined-time Lyapunov criterion, and an explicit target-entry-time estimate, it is shown that the sliding variable and the drag-tracking error enter prescribed neighborhoods within an upper time bound independent of the initial condition; positive invariance of the neighborhoods, ultimate boundedness of the second-order error, and the discretization-error correction condition are also obtained. Simulations show that the proposed method improves drag-acceleration tracking accuracy under nominal conditions and constant parameter perturbations, while keeping the closed-loop states bounded and satisfying the bank-angle constraint under random parameter perturbations and initial measurement errors. The method provides a feasible route to configurable-time tracking control for constrained skip trajectories of hypersonic glide vehicles. Full article

Star trackers commonly suffer from star point trailing during stellar imaging under dynamic observation conditions. Traditional non-blind deconvolution methods rely on a known Point Spread Function (PSF), whereas blind deconvolution approaches are plagued by a complex solution space and a high tendency to fall into local optima. These drawbacks make it difficult to meet the requirements of high-precision star centroid extraction. To address these challenges, this paper proposes a novel blind restoration method based on physical model guidance and alternating iterative optimization. Firstly, the parameters of the blurred PSF are blindly estimated using image moment analysis, and a motion blur physical model with controllable direction and length is constructed. Secondly, the iterative ideal physical model is embedded as a strong prior into curvature filtering to achieve guided denoising, which effectively suppresses noise while maintaining the original trailing structure. Finally, a dual-layer alternating optimization framework grounded in the ideal physical model was developed. The inner layer employs the Richardson–Lucy (RL) algorithm integrated with intelligent convergence criteria for high-precision image restoration. The outer layer utilizes a gradient descent algorithm equipped with a confidence-based full step-length strategy to optimize PSF parameters. This architecture establishes a self-correcting closed-loop mechanism characterized by iterative image restoration–model refinement cycles. The simulation results demonstrate that the proposed method generally maintains the star centroiding error below 0.1 pixel without prior knowledge of the PSF, with a maximum observed error of 0.105 pixel under the most challenging high-background condition. Its performance is close to non-blind restoration and significantly outperforms traditional blind deconvolution algorithms. It provides an effective solution for high-precision star centroiding under dynamic conditions. Full article

Internal responses of multilayer pavement structures are difficult to characterize using surface-based inspection alone. This study investigates a scaled multilayer pavement model instrumented with embedded quasi-distributed fiber Bragg grating (FBG) sensing lines to obtain baseline internal strain responses and FBG-derived relative vertical displacement distributions under controlled loading. Central single-point stepwise loading, symmetric two-point loading, and asymmetric two-point loading were applied, and FBG wavelength responses were converted into temperature-compensated strain and then into line-wise relative vertical displacement through strain–curvature conversion, curvature integration, and linear baseline correction. During loading, the ambient temperature ranged from 22.70 to 23.40 °C, and the maximum relative shift of the T-sensor was 0.008297 nm. Under 686 N central loading, SAL1 reached a maximum temperature-compensated strain of 1459.39 με and a maximum relative vertical displacement of 1.079 mm, whereas SAL2 reached 793.13 με and 0.583 mm. Under approximately 490 N asymmetric two-point loading, SAT2 reached 1699.48 με and 0.761 mm. Soil-base responses were substantially lower. Because no independent displacement measurement was acquired, the reconstructed quantity is interpreted as an FBG-derived relative deformation measure rather than an absolute displacement. The results establish intact baseline data for future, separately validated comparisons with abnormal conditions. Full article

Accurate water saturation estimation in deep shale reservoirs is complicated by clay-related additional conductivity and coupled pore, organic-matter, and structural effects. This study develops a feature-level physics-guided machine-learning framework, termed PhysML-Hybrid. Five mechanism-derived descriptor groups representing clay–water interfacial behavior, low-resistivity correction, pore connectivity, organic-pore development, and structural stress were integrated with conventional reservoir variables in a validation-weighted ensemble of random forest, XGBoost, and Bayesian neural network models. The framework was evaluated using 153 depth-matched samples from five wells in the Dingshan area of the Sichuan Basin. The data were divided into 107 training, 16 validation, and 30 independent test samples, and target-stratified five-fold cross-validation was conducted exclusively within the training set. Mean cross-validation $R^2$, MAE, and RMSE were $0.907\pm 0.009$, $1.69\%\pm 0.10\%$, and $2.25\%\pm 0.14\%$, respectively. On the independent test set, the corresponding values were 0.902, 1.77%, and 2.34%. PhysML-Hybrid outperformed Archie, SVM, ML-only, and Phy-XGB. SHAP and statistical analyses identified clay content, the curvature–clay interaction, TOC, pore connectivity, and structural descriptors as influential variables; candidate transitions were interpreted as dataset-specific rather than universal thresholds or causal relationships. Three blind-well cases provided supplementary evidence of cross-well applicability, although larger independent multi-basin datasets are required to assess transferability. Full article

Soybean seed variety identification is essential for seed quality control, germplasm management, and variety authentication. However, few-shot classification remains challenging because different varieties often exhibit highly similar one-dimensional hyperspectral signatures, and labeled samples are limited in practical seed-testing scenarios. This study proposes a Residual Derivative-Guided Spectral Fusion (RDSF) module to improve spectral representation under limited-sample conditions. RDSF uses the raw spectrum and its first- and second-order derivatives to characterize global reflectance patterns, local slope variations, and spectral curvature, respectively. The three representations are processed by separate branches and combined through bounded learnable residual fusion, with the raw spectrum serving as the primary representation and the derivatives providing complementary corrections. As a plug-and-play component, RDSF was integrated into Prototypical Network (ProtoNet), Relation Network (RelationNet), and Model-Agnostic Meta-Learning (MAML). The module was evaluated using spectra from 11,000 individual soybean seeds representing 11 varieties under known-class and strict class-disjoint unseen-class protocols. Under the representative known-class 3-way 10-shot setting with 15 query samples per class, RDSF increased the meta-test accuracy of RelationNet from 0.8898 ± 0.0201 to 0.9184 ± 0.0060. Under the unseen-class protocol, RDSF consistently improved ProtoNet and RelationNet across all evaluated shot settings; the largest gain was observed for ProtoNet in the 5-shot setting, with the meta-test accuracy increasing from 0.8848 ± 0.0253 to 0.9094 ± 0.0080. In contrast, RDSF did not consistently improve MAML under this protocol, indicating that its effectiveness depended partly on the underlying meta-learning mechanism. Ablation experiments and architecture comparisons further showed the complementary contributions of the derivative branches and the advantages of bounded residual fusion over a three-channel architecture and direct feature concatenation. Overall, RDSF provides an effective spectral representation module for metric-based few-shot classification of soybean seed varieties under the evaluated known-class and unseen-class conditions. Full article

This study examines the strongly nonlinear cross-media dynamics of a deep-sea umbilical cable–payload system during free-surface crossing under different sea states and lifting speeds. A two-dimensional time-domain lumped-mass model was established, in which the cable was discretized into node–axial elements. Morison-type hydrodynamic loading, added mass, and a continuous air–water parameter transition governed by an immersion factor were included for both the cable and the lower-end payload. To improve numerical robustness in long-duration simulations, a segmented ODE15s integration scheme was adopted, together with a smooth-start lifting–heave boundary condition and an adaptive lift-height correction procedure to ensure a stable cross-media response window. The results show a clear spatially segmented response: the upper cable remains nearly straight, whereas the middle and lower sections accommodate most of the lateral offset and curvature redistribution, which intensify under stronger environmental forcing. Top tension shows a gradually increasing mean component superimposed on quasi-periodic oscillations, while bottom tension, detrended vertical payload displacement, and vertical hydrodynamic force are more sensitive to sea-state severity and lifting speed. These results provide a comparative numerical basis for identifying response trends, screening lifting speed options, and interpreting cross-media load transfer mechanisms. Because the formulation is two-dimensional and has not yet been validated against model-scale or full-scale measurements, the results should not be interpreted as equipment-specific safety limits. Full article