Search Results (1,203)

Oriented object detection constitutes a fundamental yet challenging task in Artificial Intelligence of Things (AIoT)-enabled maritime surveillance, where real-time processing of dense visual streams is imperative. However, existing detectors suffer from three critical limitations: sequential attention mechanisms that fail to capture coupled spatial–channel dependencies, unconstrained deformable convolutions that yield unstable predictions for elongated vessels, and center-based distance metrics that ignore angular alignment in sample assignment. To address these challenges, we propose JAOSD (Joint Attention-based Oriented Ship Detection), an anchor-free framework incorporating three novel components: (1) a joint attention module that processes spatial and channel branches in parallel with coupled fusion, (2) an adaptive geometric convolution with two-stage offset refinement and spatial consistency regularization, and (3) an orientation-aware Adaptive Sample Selection strategy based on corner-aware distance metrics. Extensive experiments on three benchmarks demonstrate that JAOSD achieves state-of-the-art performance—94.74% mAP on HRSC2016, 92.43% AP₅₀ on FGSD2021, and 80.44% mAP on DOTA v1.0—while maintaining real-time inference at 42.6 FPS. Cross-domain evaluation on the Singapore Maritime Dataset further confirms robust generalization capability from aerial to shore-based surveillance scenarios without domain adaptation. Full article

The combination of nanogenerator technology and traditional textile materials has given rise to textile-based triboelectric nanogenerators (T-TENGs) structured from fibers, yarns, and fabrics. Due to their lightweight, flexibility, washability, and cost-effectiveness, T-TENGs offer a promising platform for powering and sensing in next-generation wearable electronics, with particularly significant potential in smart healthcare and sports monitoring. However, the inherent electrical and structural limitations of textile materials often restrict their power output, signal stability, and sensing range, making it challenging to achieve both high electrical performance and high sensing sensitivity. This review focuses on the application of T-TENGs in smart healthcare and sports. It systematically presents recent developments in textile material selection, sensing structure, fabric design, working mechanisms, accuracy optimization, and practical application scenarios. Furthermore, it provides a critical analysis of the recurring structural and material limitations that constrain performance and offers constructive pathways to address them. Key challenges such as the low charge density of textile interfaces may be mitigated by selecting low-hygroscopicity materials, applying hydrophobic treatments, and optimizing textile structures to enhance contact efficiency and environmental stability. Issues of signal instability under dynamic deformation call for advanced structural designs that accommodate strain without compromising electrical pathways, coupled with robust signal processing algorithms. By providing a comparative analysis across materials and structures, this review aims to inform future designs and accelerate the translation of high-performance T-TENGs from laboratory research to real-world implementation. Full article

This article presents a systematic review on methods for quantifying three-dimensional, time-resolved (3D+t) deformation and motion of human arteries from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Scopus, Web of Science, IEEE Xplore, Google Scholar, and PubMed on 19 December 2025 for in vivo, patient-specific CT or MRI studies reporting motion or deformation of large human arteries. We included studies that quantified arterial deformation or motion tracking and excluded non-vascular tissues, in vitro or purely computational work. Thirty-five studies were included in the qualitative synthesis; most were small, single-centre observational cohorts. Articles were analysed qualitatively, and results were synthesised narratively. Across the 35 studies, the most common segmentation approaches are active contours and threshold, while temporal motion is tracked using either voxel registration or surface methods. These kinematic data are used to compute metrics such as circumferential and longitudinal strain, distensibility, and curvature. Several studies also employ inverse methods to estimate wall stiffness. The findings consistently show that arterial strain decreases with age (on the order of 20% per decade in some cases) and in the presence of disease, that stiffness correlates with geometric remodelling, and that deformation is spatially heterogeneous. However, insufficient data prevents meaningful comparison across methods. Full article

Background/Objectives: Although scoliosis is essentially a three-dimensional (3D) deformation of the spine and has been reported to be associated with muscle activations around the vertebrae, no study has demonstrated the 3D structural deformations of the spine in relation to asymmetrical muscle activation nor revealed the neuromuscular characteristics associated with scoliosis. The purpose of this study was to investigate the association between asymmetrical muscle activation and three-dimensional spinal deformity in adolescent idiopathic scoliosis (AIS) of thoracic origin. Methods: Thirty-one patients with IS of thoracic origin (double major [DM] and single thoracic [ST] types) and 39 normal controls were included. Surface electromyographic (SEMG) signals were obtained in several back muscles while the patients were in a writing posture. 3D analyses of spinal curves with EOS imaging system were performed, and “AR_main” (indicative of axial rotation of the vertebral column), “ΔAR” (indicative of lateral bending), and “AK_max” (indicative of maximal angle of kyphosis) were evaluated. Results: Asymmetrical activations were observed in the middle trapezius with rhomboids, and the T6-7 and T12 paraspinalis muscles, with higher activation on the convex side of the scoliosis curve. On EOS 3D analysis, “AR_main” was 8.94° [IQR, 0.00–14.00] and 26 of 31 patients had AR_main ≥ 0°. “ΔAR” was 21.90° [IQR, 6.00–39.00]. As the AR_main increased, the Cobb angle became closer to the maximal angle of kyphosis (“AK_max”). Conclusions: Asymmetrical activations of several back muscles while patients were in a writing posture were observed. These asymmetrical muscle activation patterns were associated with axial rotation and lateral bending of the thoracic spine in patients with thoracic-origin AIS. Full article

Background: In adult spinal deformity (ASD) surgery, appropriate rod length determination is crucial, as excessive cranial rod length can lead to skin problems, especially in thin elderly patients if proximal junctional kyphosis (PJK) develops. In adolescent idiopathic scoliosis (AIS), correction is primarily performed in the coronal plane, and rod length changes are relatively predictable. Moreover, PJK is uncommon in AIS, making excess rod length rarely a clinical concern. In contrast, ASD correction involves more complex three-dimensional realignment, including restoration of lumbar lordosis (LL), which makes it challenging to predict postoperative changes in rod trace length (RTL). Furthermore, because PJK occurs more frequently in ASD surgery, appropriate rod length selection becomes clinically important. This study aimed to quantitatively evaluate changes in RTL before and after posterior correction. Method: Thirty patients with ASD who underwent staged lateral lumbar interbody fusion (LLIF) followed by posterior corrective fusion from T9 to the pelvis were retrospectively analyzed. RTL before posterior correction (Pre-RTL) was estimated from the planned screw insertional point on axial CT after LLIF, and postoperative RTL (Post-RTL) was measured from screw head centers on post-operative CT. LL and Cobb angle were assessed before and after posterior correction. Correlations between RTL change and alignment change were evaluated. Results: Postoperative RTL was shortened in all patients, with an average reduction of approximately 16–17 mm. RTL shortening demonstrated significant correlations with LL correction (R = 0.51, p = 0.003) and Cobb angle correction (R = 0.70, p = 0.00001). Greater shortening of RTL was observed on the convex side in patients with preoperative Cobb angle ≥ 10° (p = 0.04). Conclusions: Greater coronal deformity, particularly on the convex side, was associated with increased RTL shortening. These findings suggest that routine preparation of excessively long rods may be unnecessary. Consideration of anticipated RTL shortening may help avoid excessive cranial rod length and potentially reduce the risk of skin complications associated with PJK, particularly in thin elderly patients. Full article

Multimessenger constraints tightly bound the gravitational-wave speed to be luminal, posing a strong filter for modified gravity. This paper develops a symmetry-selected Palatini framework with torsion in which exact luminality at quadratic order is achieved by construction rather than by parameter tuning. Two ingredients shape the observable sector: (i) a scalar PT projector that keeps scalar densities real and parity-even, and (ii) projective invariance implemented via a non-dynamical Stueckelberg compensator that enters only through its gradient. Under an explicit posture (A1–A6), we establish three structural results: (C1) algebraic uniqueness of torsion to a pure-trace form aligned with the compensator gradient; (C2) bulk equivalence, modulo improvements, among a rank-one determinant route, a closed-metric deformation, and a PT-even CS/Nieh–Yan route; and (C3) a coefficient-locking identity that enforces $K=G$ for tensor modes on admissible domains; hence, $c_T=1$ with two propagating polarizations. Beyond leading order, the framework yields a distinctive, falsifiable next-to-leading correction $\delta c_T^2\left(k\right)=b{k}^2/{\mathrm{\Lambda }}^2$ (for $k\ll \mathrm{\Lambda }$), predicting slope 2 in log–log fits across frequency bands (PTA/LISA/LVK). The analysis is formulated to be reproducible, with a public repository providing figure generators, coefficients, and tests that directly validate (C1)–(C3). Full article

Cervical spine (c-spine) injuries are a prominent concern in sporting activities, and dynamic axial (i.e., head-first) impacts are associated with a high risk of c-spine trauma. This methodology study implanted pressure sensors in post-mortem human subject (PMHS) cervical intervertebral discs (CIVDs) to assess biomechanical response and disc pressure changes during dynamic injurious axial impacts. Two fresh frozen male head–neck PMHS (cephalus with complete c-spine) were instrumented with miniature pressure sensors (Model 060S, Precision Measurement Company, Ann Arbor, MI, USA) at three CIVD levels (upper, middle, and lower c-spine). Experiments replicated the Nightingale et al. studies, simulating a rigid unconstrained head vertex (0°) axial impact. PMHS were raised to a drop height of 0.53 m to reach the desired impact velocity of ~3.2 m/s and were allowed to drop vertically. Results showed characteristic c-spine deformations/buckling motion patterns and marked CIVD pressure differences between CIVD levels. The more cranial (C2–C4) and caudal (C6–T1) CIVD exhibited greater and more comparable pressure values than those of the mid-spine (C4–C6), and the pressure in upper/lower levels was at least ~four to six times higher than that of the middle. This study establishes the feasibility and assesses the potential of CIVD pressure as a biomechanical metric for assessing injurious axial loading and contributes a novel experimental framework for future injury tolerance research and model validation. Full article

This study examines the longitudinal shortening of clay blanks during extrusion and introduces a hybrid soft sensor framework for early prediction of ceramic roof tile performance. Targeted properties include shrinkage, water absorption, and saturation. The models integrate real-time process data collected after vacuum extrusion and pressing with clay-specific descriptors such as carbonate content and granulometry, alongside additional variables including moisture, firing temperature, and length reduction. Partial Least Squares (PLS) regression was adopted as the core method due to robustness against multicollinearity and ease of industrial integration. In contrast to complex machine learning pipelines, PLS-based soft sensors enable lightweight edge deployment without reliance on IoT infrastructure. Complementary regression and machine learning models were used to benchmark predictive accuracy and explore nonlinear effects. The results confirm reliable prediction of key performance indicators and reveal mechanistic links between extrusion-induced deformation and downstream behavior. Although developed for clay systems, the framework is generalizable and can be adapted to other traditional ceramic processes or industries seeking interpretable, locally deployable solutions for process control. Full article

Surface deformation induced by the extraction of natural resources constitutes a non-stationary spatiotemporal process. Modeling surface deformation time series obtained through Interferometric Synthetic Aperture Radar (InSAR) technology using deep learning methods is crucial for disaster prevention and mitigation. However, the complexity of model hyperparameter configuration and the lack of interpretability in the resulting predictions constrain its engineering applications. To enhance the reliability of model outputs and their decision-making value for engineering applications, this study presents a workflow that combines a Tree-structured Parzen Estimator (TPE)-based Bayesian optimization approach with ensemble inference. Using the Rhineland coalfield in Germany as a case study, we systematically evaluated six deep learning architectures in conjunction with various spatiotemporal coding strategies. Pairwise comparisons were conducted using a Welch t-test to evaluate the performance differences across each architecture under two parameter-tuning approaches. The Benjamini–Hochberg method was applied to control the false discovery rate (FDR) at 0.05 for multiple comparisons. The results indicate that TPE-optimized models demonstrate significantly improved performance compared to their manually tuned counterparts, with the ResNet+Transformer architecture yielding the most favorable outcomes. A comprehensive analysis of the spatial residuals further revealed that TPE optimization not only enhances average accuracy, but also mitigates the model’s prediction bias in fault zones and mineralize areas by improving the spatial distribution structure of errors. Based on this optimal architecture, we combined the ten highest-performing models from the optimization stage to generate a quantile-based susceptibility map, using the ensemble median as the central predictor. Uncertainty was quantified from three complementary perspectives: ensemble spread, class ambiguity, and classification confidence. Our analysis revealed spatial collinearity between physical uncertainty and absolute residuals. This suggests that uncertainty is more closely related to the physical complexity of geological discontinuities and human-disturbed zones, rather than statistical noise. In the analysis of super-threshold probability, the threshold sensitivity exhibited by the mining area reflects the widespread yet moderate impact of mining activities. By contrast, the fault zone continues to exhibit distinct high-probability zones, even under extreme thresholds. It suggests that fault-controlled deformation is more physically intense and poses a greater risk of disaster than mining activities. Finally, we propose an engineering decision strategy that combines uncertainty and residual spatial patterns. This approach transforms statistical diagnostics into actionable, tiered control measures, thereby increasing the practical value of susceptibility mapping in the planning of natural resource extraction. Full article

This systematic review maps and compares experimental strategies for estimating residual expansion in concrete elements affected by internal expansive reactions (IER), with emphasis on cores extracted from in-service structures. It adopts an operational taxonomy distinguishing achieved expansion (deformation already occurred, inferred through DRI/SDT or back-analysis), potential expansion (upper limit under free conditions), and residual expansion (remaining portion estimated under controlled temperature, T, and relative humidity, RH), in addition to the free vs. restrained condition and the diagnostic vs. prognostic purpose. Seventy-eight papers were included (PRISMA), of which 14 tested cores. The limited number of core-based studies is itself a key outcome of the review, revealing that most residual expansion assessments rely on adaptations of laboratory ASR/DEF protocols rather than on standardized methods specifically developed for concrete cores extracted from in-service structures. ASR predominated, with emphasis on accelerated free tests ASTM/CSA/CPT (often at 38 °C and high RH) for reactivity characterization, and on Laboratoire Central des Ponts et Chaussées (LCPC) No. 44 and No. 67 protocols or Concrete Prism Test (CPT) adaptations to estimate residual expansion in cores. Significant heterogeneity was observed in temperature, humidity, test media, specimen dimensions, and alkali leaching treatment, as well as discrepancies between free and restrained conditions, limiting comparability and lab-to-field transferability. A minimum reporting checklist is proposed (type of IER; element history; restraint condition; T/RH/medium; anti-leaching strategy; schedule; instrumentation; uncertainty; decision criteria; raw data) and priority gaps are highlighted: standardization of core protocols, leaching control, greater use of simulated restraint, and integration of DRI/SDT–expansion curves to anchor risk estimates and guide rehabilitation decisions in real structures. Full article

Background/Objectives: Three-dimensional virtual surgical planning (VSP) is increasingly central to contemporary orthognathic surgery, enhancing diagnostic precision and enabling more reliable forecasts of postoperative outcomes. NemoFAB (Nemotec, Madrid, Spain) is a recently developed digital platform that integrates CBCT data, digital dental models, and facial photographs into a single workflow. Despite its growing clinical use, independent validation of its predictive accuracy remains limited. This study evaluated how closely NemoFAB virtual predictions corresponded to actual postoperative results using standardized cephalometric parameters. Methods: Forty adult patients with dento-maxillofacial deformities requiring combined orthodontic–surgical treatment were included. Eleven cephalometric variables—common to both WebCeph (2D) and NemoFAB (3D)—were measured preoperatively, virtually in NemoFAB, and postoperatively. AI-assisted landmark placement was manually verified by two orthodontists. Statistical analyses included repeated-measures ANOVA, paired t-tests, Bland–Altman plots, and intraclass correlation coefficients (ICC) to evaluate agreement and predictive accuracy. Results: Overjet, overbite, maxillary incisor inclination, maxillary incisor exposure, mandibular incisor projection to the True Vertical Line, and occlusal plane angulation all showed statistically significant changes after surgery (p < 0.05). Bland–Altman analysis demonstrated the narrowest limits of agreement in Nemo–Post comparisons, indicating strong predictive alignment. ICC values showed excellent agreement for incisor angulation (ICC = 0.921–0.984) and Pogonion projection (ICC = 0.943). Consistently poor pre-Nemo agreement reflected expected discrepancies between initial anatomy and planned surgical correction. Conclusions: When predicting skeletal and dentoalveolar changes brought about by orthognathic surgery, NemoFAB showed a high degree of agreement, especially for parameters that are directly impacted by jaw repositioning. Its strong concordance with postoperative outcomes supports its reliability for virtual planning, interdisciplinary coordination, and surgical execution. Advances in soft-tissue modeling and AI-driven automation may further enhance predictive accuracy. Full article

As a critical sealing component in aero-engines, the segmented annular seal is prone to friction and wear during the running-in stage, which seriously impairs its sealing performance and service life. To address this issue, this study takes the three-petal segmented annular seal made of T482 graphite as the research object, adopting a combined method of high-speed ring-block friction and wear tests and thermal–fluid–solid coupling simulation to investigate its friction and wear mechanisms and optimize its structural design. The results show that the segmented annular seal undergoes more severe friction and wear in the low-speed running-in stage; the wear rate increases with the rise in loading force and decreases with the increase in rotational speed, and the variation trend of surface roughness is consistent with that of the friction coefficient. Frictional heat and wear-induced scratches intensify the deformation and leakage of the seal, thereby leading to the risk of seal failure. Optimizing the depth of radial dynamic pressure grooves can significantly improve the opening performance of the seal, while optimizing the width of axial grooves mainly affects the seal leakage. This research provides a theoretical basis for improving the service life and sealing performance of segmented annular seals in aero-engines. Full article

To improve the continuous chordwise bending performance of morphing wings, this study proposes a rigid–flexible coupled wing rib structure and its control strategy. Initially, the optimal rigid–flexible hybrid configuration was optimized via the mean camber line parameterization and genetic algorithm. For the flexible segment, topology optimization was conducted using the load path method, followed by subspace-based shape–size alternating optimization; bionic “longbow” curved beams and ‘S’-shaped substructures were adopted to enhance deformability. Biomimetic pneumatic muscles were used as actuators, and a fuzzy-adjusted PI sliding mode controller was designed to address the issue that traditional PI sliding mode controllers cannot achieve precise control under non-optimal parameters or when there is a significant difference in deformation targets. Experimental results show that when the flexible rib deflects by 15°, the three-rib wing box achieves a 30° deflection, with stresses within the allowable limit of 7075Al-T6 (540 MPa) and a deformation error of only 7.6%. For the 15° downward bending control, the adjustment time is 6.06 s, the steady-state error is 0.19°, and the overshoot is 1.8%. This study verifies the feasibility of the proposed rigid–flexible coupled structure and fuzzy PI-SMC, providing a technical reference for morphing aircraft. Full article

Differential speed rolling (DSR) has been recognized as a unique processing technique in recent years, which has been used to plastically deform Mg-based alloys and to investigate the role of dynamic recrystallization (DRX) and its influence on both microstructure and mechanical properties. In this study, Mg–2Al–0.5Ca–0.5Mn (AXM20504) was solution-heat-treated (T4 condition) and subjected to single-pass DSR at both 20 and 40% thickness reductions, followed by post-annealing at temperatures of 350, 400, and 450 °C for the durations of 20, 40, and 60 min to evaluate the onset and development of static recrystallization (SRX) and its overall effect on the formability of Mg-based alloys. The results demonstrate how post-annealing yields nearly complete SRX at 400 °C for 60 min and 450 °C for 40 min with a significant improvement in ductility, increasing from 5% to 12% while maintaining an average tensile strength above 200 MPa. Thus, the improvement in mechanical properties demonstrates that post-annealing can deliver significant potential in terms of the enhanced formability of Mg alloys used in sheet metal forming applications. Full article

The Axi gold deposit, a low-sulfidation epithermal deposit in the Western Tianshan, China, hosts over 50 t of gold resources and is widely regarded as the result of coupled processes of rock deformation, heat transfer, pore fluid flow, and chemical reactions. However, research on the ore-forming processes of this gold deposit from a coupled perspective remains limited, resulting in its ore-forming mechanisms being incompletely understood. In this paper, we use the concept of mineralization rate based on computational modeling to indicate the 3D spatial distribution of mineralization. The simulation results reveal the following: (1) temperature gradients play a key role in influencing mineral precipitation, whereas the effect of pore fluid pressure gradients is relatively negligible; (2) gold precipitation, characterized by a negative mineralization rate, predominantly took place along fault zones that exhibit vertical transitions from steep to gentle slopes or lateral bends, which are further distinguished by the accumulation of fluids and the presence of significant temperature gradients. Notably, this particular distribution pattern of gold precipitation closely mirrors the spatial arrangement of known gold orebodies. These findings suggest that the coupling of multiple physical and chemical processes at specific fault sites plays a critical role in ore formation, providing new insights into the mechanisms governing the development of the Axi gold deposit. Furthermore, based on these observations, it can be inferred that the deeper regions of the Axi gold deposit hold considerable mineralization potential. Full article