Search Results (6,966)

Reinforced concrete (RC) buildings are the most common structural system in urbanising regions. In many cases, architectural constraints and uneven distribution of structural elements often create eccentricity between the centre of mass (CM) and the centre of rigidity (CR). This eccentricity may induce torsional effects during earthquakes that can significantly influence structural response and increase seismic vulnerability. This study investigates the impact of in-plan irregularity on the seismic performance of RC buildings using nonlinear numerical analyses. Three-dimensional models of four- and six-storey RC buildings with moment resisting frames were developed in OpenSees, where different levels of irregularity were introduced by artificially shifting the lumped mass to generate controlled eccentricities without modifying the structural configuration. Seismic performance was evaluated using nonlinear incremental dynamic analysis (IDA) based on forty ground motion records under bidirectional excitation. The results indicate that increasing CM–CR eccentricity amplifies inter-storey drift demands and elevates the probability of damage due to intensified torsional stresses. The adverse effect is most pronounced when eccentricity aligns with the direction of lower stiffness, whereas eccentricity in the stiffer direction has a limited impact on severe damage states, particularly for taller buildings. These findings provide valuable insights for risk-informed assessment, retrofitting, and prioritisation of existing plan-irregular RC buildings. Full article

Brush seals, as a fundamental dynamic sealing technology in the aerospace and energy propulsion industries, require performance enhancement through instantaneous adjustment of the friction coefficient and force analysis of brush filaments. This paper establishes an instantaneous friction coefficient correction method based on the open volume between bristles and the backing plate. The downstream section of the double-row brush wire (2.6 mm) was quantitatively identified as the maximum leakage point, and it was found that the vortex characteristic length in the downstream area is approximately 1–3 times the bristle gap, with an increasing pressure ratio enhancing downstream turbulence and reducing gas leakage. A cantilever beam structural model was developed to assess the motion, force, and hysteresis properties of a single filament. Additionally, a porous medium model was utilized to elucidate the flow field and temperature distribution within the seal. The results suggest that the lag angle increases linearly over the first one-third of the brush wire’s length from the free end to the fixed end and is directly proportional to the pressure difference ΔP, reaching a maximum of 10.18°. The viscous drag causes the radial force y-component F_xy to increase and then decrease near the free end. The rear baffle contact force, F_b, shows variable peaks at two-thirds of the filament length. The displacement at the brush filament’s free end, the deflection angle, and the bending moment are directly proportional to the pressure differential. As pressure increases, the deformed region propagates toward the fixed end, and the maximum displacement at the free end of the brush wire reaches 13.04 mm. The leakage rate increases nearly linearly with ΔP and its deformation, reaching a maximum of 0.00849 m²/s. The pressure gradient growth rates of 164%, 73%, and 29% at the front baffle corner demonstrate that adding pressure chambers on front and rear baffles is optimal for high-pressure scenarios (ΔP > 0.3 MPa), while the formation of vortices between bristles and rotor reduces tip friction force and front-row turbulent disturbance, providing design guidance for extending seal service life. Full article

Protected horticulture moves fragile pots, plug trays, seedlings, harvested products, and carriers through narrow, humid, and crowded spaces. Transport robots must therefore integrate locomotion, perception, localization, handling, placement, scheduling, and human–robot interaction rather than operate as simple carts. This structured narrative review reorganizes evidence from seedling transplanting, nursery operations, harvest support, manipulation, perception, and autonomous navigation around the complete transport chain: target recognition, pickup, loading, loaded navigation, docking, unloading or placement, payload protection, and workflow feedback. The synthesis covers mobile platforms, payload support, perception and localization, motion control, gentle handling, digital support, and fleet coordination. Three barriers remain: short laboratory tests rarely provide season-long evidence; many prototypes are too specialized for variable workflows; and benchmarks seldom combine motion accuracy, handling reliability, payload quality, and resilience. Progress will require modular platforms, robust sensing, payload-safe control, standardized interfaces, and closer co-design between robotics and horticultural operations. Full article

The modal behaviour of the wooden bridge over the Rhine described by Julius Cæsar in the De Bello Gallico is analysed by a simple analytical model, i.e., a Kirchhoff–Love (KL) plate. The overall structure is indeed modelled as a thin plate, representing the walking surface, resting on elastic supports that approximate the compliance of the underlying structure. Firstly, these elastic constraints are represented by linear springs; in a refined step, beam elements with equivalent stiffness and mass are adopted. The system complexity arises from the consequent non-trivial boundary conditions and is tackled by selecting suitable auxiliary functions to operate with discretised equations of motion, in a Galërkin-like approach. MATLAB helped to develop in-house scripts capable of reconstructing the flexural behaviour as the governing parameters vary, without repeated experimental tests. The analytical results are compared with theoretical predictions and between the two assumed elastic supports, allowing verification of model consistency and explanation of differences in the bridge behaviour. The ease of implementation of these codes also enables the evaluation of the structural potential of historical constructions, the investigation of modular characteristics and connections between subcomponents, and the assessment of the effects of external loads. The study of historical structure dynamics is thus relevant not only for reconstruction, but also for modern mechanical design, with potential applications in civil, mechanical, materials, and naval engineering. Full article

In biomass pellet combustion, the formation of ash layers on particle surfaces severely hinders combustion reactions and heat transfer, while the key parameters governing particle motion behavior and ash pre-separation in rotating cone burners remain insufficiently understood. To address these challenges and to optimize particle mixing and ash separation performance, this study adopts a combined numerical approach. The discrete element method (DEM) coupled with the Hertz–Mindlin (no-slip) contact model is employed to simulate particle motion and mixing dynamics, while a separate cold-state computational fluid dynamics (CFD) model based on the Realizable k-ε turbulence model and the discrete phase model (DPM) with Rosin–Rammler particle size distribution is established to investigate ash separation mechanisms. The Lacey mixing index is used to quantify mixing uniformity, and grid independence verification is performed to ensure numerical reliability. Key findings reveal that the rolling regime (rotational speed: 1.7–11 r/min), a uniform particle size of 25 mm, and a cone inclination angle of 45° collectively optimize particle mixing. Rotational speed is identified as the dominant factor affecting mixing effectiveness. Furthermore, an optimal secondary-to-primary air ratio of approximately 7:3 (within the tested range) balances enhanced centrifugal separation with flow field stability by mitigating backflow and excessive turbulence. This work not only fills the knowledge gap regarding the coupled effects of operational and structural parameters on particle behavior in rotating cone burners but also provides novel, quantitative guidance for the rational design and parameter tuning of such burners to improve combustion efficiency and operational stability. Full article

A comprehensive numerical method was developed to ensure energy-efficient operating modes of a linear motion module powered by an induction motor. The proposed approach is based on minimizing inertial torque, accounting for the inertial properties of the drive components and the load carriage, followed by structural-parametric optimization and dynamic modeling. For the optimization of the drive system, comprising an intermediate gear stage and a primary ball screw mechanism, a normalization-based method combined with numerical parameter sweep was employed. The optimization process yielded optimal values of the screw lead and the number of gear teeth, which were further validated in terms of Pareto optimality. The carriage design was optimized with respect to mass, strength constraints, and dynamic stiffness using the finite element method. For the developed linear motion module, dynamic behavior was simulated by means of a system of nonlinear differential equations, taking into account the electromagnetic characteristics of the induction motor and the nonlinearities of the gear mesh. As a result of the comprehensive approach, the kinematic, force, and energy characteristics of the linear motion module, which was optimized at the design stage, were determined. Full article

This study presents a comprehensive review of more than 100 research papers on sign language recognition (SLR) published between 2020 and 2026. The analysis focuses on deep learning approaches applied to video-based SLR, including spatiotemporal feature extraction, temporal modeling, attention mechanisms, motion-based representations, hybrid frameworks, transfer learning methods and other methods. Particular attention is given to how these methods model spatiotemporal dynamics and capture subtle gesture characteristics in sign language communication. The review highlights several recent developments, such as the introduction of specialized datasets, the emergence of real-time recognition systems, and the integration of multimodal fusion strategies. At the same time, persistent challenges remain, including data scarcity in low-resource sign languages, limited linguistic standardization of datasets, and insufficient model interpretability. The findings underline the importance of developing scalable and generalizable models capable of handling diverse datasets and user variability. The distinct contributions of this review are fourfold: (1) a comprehensive synthesis of over 100 studies published between 2020 and 2026, covering the full spectrum of deep learning architectures for video-based SLR; (2) a structured six-category taxonomy enabling systematic cross-architectural comparison; (3) a comprehensive focus on low-resource sign languages, which remain underrepresented in the existing literature; and (4) a critical analysis of the current benchmark landscape for low-resource sign languages, identifying key gaps and outlining strategic directions for future dataset development. These contributions are intended to guide further research toward more robust, inclusive, and universally applicable SLR systems. Full article

Background: Promoting physical activity in early childhood is essential for supporting motor, cognitive, and socio-emotional development. Outdoor environments rich in natural stimuli may further enhance these benefits. Recent approaches suggest that integrating movement with narrative contexts may provide additional developmental opportunities by engaging cognitive and affective processes. This study examined the associations between three outdoor motor activity approaches—Storytelling in Motion, Free Play, and Traditional Motor Instruction—and motor competence and inhibitory control in preschool children. Methods: Eighty-seven preschool children (M_age = 5.32 ± 0.60 years) participated in a quasi-experimental pretest–posttest study conducted in outdoor educational settings in Northern Italy, including a natural environment, a structured playground, and a school courtyard. Participants were assigned at the class level to three groups of unequal size (Storytelling in Motion n = 36, Free Play n = 22, Traditional Motor Instruction n = 29). All groups completed ten weekly sessions lasting approximately 60 min. Motor competence was assessed using selected tasks derived from the Test of Motor Competence and the Movement Assessment Battery for Children-2, while inhibitory control was evaluated using the Day/Night Test. Results: Significant Time × Group interactions were observed for several outcomes. The Storytelling in Motion group showed numerically greater improvements at a descriptive level in dynamic balance (Heel-to-Toe Walking: p < 0.001, η²p = 0.229) and fine motor control (Bicycle Trail: p < 0.001, η²p = 0.194) compared to the other groups. The Free Play group showed greater improvements in coordination-related tasks and upper-body strength. No significant differences between groups were observed for inhibitory control. These differences remained significant after adjustment but should be interpreted cautiously due to the non-randomized design. Accordingly, these findings should be considered preliminary and hypothesis-generating (ANCOVA, p < 0.05). Conclusions: Narrative-based outdoor motor activities may represent a potentially relevant approach; however, no firm conclusions can be drawn from the present design. Given the quasi-experimental nature of the study and the contextual differences between intervention settings, the findings should be interpreted with caution. Future research using randomized controlled designs and standardized environments is needed to clarify the independent and combined effects of instructional and environmental factors. Full article

To address the challenge that existing soft grippers have difficulty achieving fine manipulation comparable to the human finger’s “circular twisting” motion, this paper proposes a four-chamber spatial bending soft actuator based on the principle of virtual work. The actuator incorporates an internal cross-shaped restricting layer that divides its cross-section into four independent pneumatic chambers. Through independent regulation of the pressure in each chamber, continuous and controllable bending in arbitrary spatial directions is achieved, replicating the bending and abduction/adduction degrees of freedom (DoFs) of a human finger and their composite motions on a single actuator. Based on the Yeoh hyperelastic constitutive model and the principle of virtual work, a static deformation model of the actuator is established. By introducing an engineering assumption of “deformation vector superposition” and correction coefficients fitted from experimental data, high-precision prediction from multi-chamber pressure input to spatial bending output is realized. Furthermore, a three-finger soft gripper is constructed based on this actuator, successfully demonstrating fingertip pinching and enveloping grasping. Through open-loop programmed control, the fine “circular twisting” manipulation is demonstrated (exemplified by light bulb installation). This study provides an effective structural design and modeling method for soft actuators to achieve decoupled multi-DoF motion control, showcasing their application potential in adaptability and dexterous manipulation. Full article

Background: Patellar tendinopathy is a common musculoskeletal condition that may impair functional performance and limit physical activity. While structural and mechanical factors have been widely investigated, the role of proprioceptive function and its interaction with behavioral and central pain-related mechanisms remain unclear. This study aimed to investigate the relationship between knee joint position sense, kinesiophobia, and central sensitization in individuals with chronic patellar tendinopathy. Methods: A total of 42 recreational athletes with clinically diagnosed chronic patellar tendinopathy were included in this cross-sectional study. Knee joint proprioception was assessed using joint position sense testing at multiple knee flexion angles with a continuous passive motion device. Kinesiophobia and central sensitization were evaluated using the Tampa Scale of Kinesiophobia and the Central Sensitization Inventory, respectively. Joint position sense values of the involved and contralateral extremities were compared, and correlation analyses were performed to examine associations between joint position sense and psychosocial variables. Results: The involved extremity demonstrated significantly greater absolute angular error compared to the contralateral side at higher knee flexion angles (≥60°, p < 0.01), whereas no significant differences were observed at lower angles. A moderate positive correlation was found between joint position sense error and kinesiophobia at higher flexion angles (≥30°, p < 0.01). No significant association was identified between joint position sense error and central sensitization across any of the tested angles (p > 0.05). Conclusions: Proprioceptive function is impaired in individuals with chronic patellar tendinopathy, particularly under increased mechanical demand. The association between joint position sense deficits and kinesiophobia, but not central sensitization, suggests a potential relationship between movement-related fear and sensorimotor alterations. These findings highlight the importance of incorporating proprioceptive assessment and addressing kinesiophobia in the clinical management of patellar 36 tendinopathy. Full article

Object detection in optical remote sensing imagery faces persistent challenges from severe instance overlap, extreme spatial density, and motion or atmospheric blur. These degradations cause conventional detectors to over-mix neighboring instance features and fail to separate closely packed objects. To address these limitations, we propose SARC-DETR, a detection framework that augments the RT-DETR architecture with two complementary plug-in modules: Similarity Adaptive Convolution (SAC) and Receptive Field Cross Convolution (RCC). SAC introduces a reproducing-kernel-Hilbert-space (RKHS) motivated similarity gate that selectively suppresses responses inconsistent with local feature prototypes, thereby reducing cross-instance interference in overlapped and blurred regions. RCC constructs a large directional receptive field through orthogonal strip-based aggregation and content-adaptive fusion, enabling efficient long-range context capture without quadratic complexity overhead. Both modules can be integrated into existing DETR-style detectors without modifying the detection head or training protocol. On VisDrone2019-DET, SARC-DETR improves ${\mathbf{AP}}^{\mathbf{val}}$ from 29.7 to 34.8, ${\mathbf{AP}}_{50}^{\mathbf{val}}$ from 49.5 to 56.2, and ${\mathbf{AP}}_S^{\mathbf{val}}$ from 19.2 to 24.8. On DIOR, AP rises from 57.9 to 68.4, and on NWPU VHR-10, from 44.4 to 66.5, demonstrating robust cross-dataset generalization. After structural reparameterization, the additional overhead is less than 0.75 M parameters and 0.36 G FLOPs, confirming deployment suitability for UAV and satellite-based remote sensing applications. Full article

Background/Objectives: Understanding the microstructure of ingestive behavior (IB) is critically important to the development and success of interventions to change eating rates and produce more optimal food energy intake outcomes. Detailed measurement of IB microstructure is needed to guide development of real-time sensing approaches that can support such interventions. This article summarizes novel measurement and inference strategies around both digital video and inertial motion sensors in a structured laboratory protocol. Methods: Digital video footage was annotated for chews and bites and analyzed with generalized additive models to assess differences in IB for each of four meal courses varying by food texture. Results: Significant differences were revealed in IB microstructure in the form of nonlinear patterns of annotated video footage and initial sensing tests, indicating an optimal sensor location over the jaw’s condyle bone. Conclusions: Findings of an intensive longitudinal multicourse full meal protocol reflect important differences in nonlinear trends of eating behavior for diverse texture foods. These differences inform further development of technology-aided measurement strategies, provide an experimental protocol for fieldwide IB inquiry, and reveal expected fundamental differences in ingestion rates. Further inquiry into the underlying causes of nonlinearities for high UPF foods, along with sensor measurements, is warranted. Full article

This paper investigates the impact of rotor–nacelle assembly (RNA) structural models on the dynamic response of a 15 MW monopile-supported offshore wind turbine (MOWT). Three RNA models, distributed parameter (DPM), multi-particle (MPM), and concentrated point mass (CPM), were established in ADINA. Model reliability was confirmed through verification against BModes and OpenFAST, covering natural frequencies, mode shapes, and responses under normal environmental loads. The analyses reveal the following: (1) RNA modeling significantly impacts higher-order modal frequencies, with the MPM/CPM exhibiting substantial errors (up to −20.3% and 9.5% for second-order tower mode) and failing to capture blade deformation modes; (2) under low-frequency dominated wave loads, the MPM/CPM predict peak responses within ±10% tolerance; (3) for seismic loads, the discrepancy in three models is governed by input motion spectral characteristics, showing smaller errors under far-field motions (fundamental mode dominated) but significant errors under near-field motions (higher-mode excited). These findings collectively provide theoretical guidance for RNA model selection in MOWTs. Full article

Tracking biomechanical changes associated with different training modalities remains a methodological challenge in applied sports science. This pilot longitudinal study examined stroke technique stability in seven junior rowers (aged 16.6 ± 0.5 years) across three measurement sessions (March, April, June), separated by two training mesocycles emphasising strength training and intensive rowing, respectively. Upper body angular velocity was recorded using a smartphone-based MEMS sensor fixed to the upper back during incremental ergometer exercise. Overall stroke duration and its standard deviation remained stable throughout the study period, whereas the durations of the two stroke phases corresponding to forward (drive) and backward (recovery) body motion changed systematically across mesocycles. Phase-specific changes were statistically significant in 10 of 12 paired comparisons (rank-sum test) and 7 of 12 within-subject comparisons (Wilcoxon signed-rank test) for phase durations, and in 9 and 5 of 12 comparisons for their standard deviations, respectively. These findings suggest that the internal structure of the rowing stroke is sensitive to training load specificity, even when overall stroke timing remains unchanged, and that smartphone-based angular velocity analysis provides a feasible tool for individualized biomechanical monitoring in young athletes. Full article

The rapid advancement of flexible electronics technology has endowed flexible sensors with significant application potential in fields such as wearable sensors, bionic skin, and human–machine interaction, owing to their excellent conformability, stretchability, and comfort. However, as application scenarios continue to expand and deepen, higher requirements are imposed on sensor performance in terms of sensitivity, stability, biocompatibility, environmental friendliness, and multifunctional integration. Polyurethane composites, leveraging their intrinsic characteristics, including tunable molecular structure, superior flexibility, and good biocompatibility, can effectively impart properties such as electrical conductivity, self-healing capability, and high sensitivity through compositing with various functional materials, thereby precisely aligning with the diverse demands of next-generation flexible sensors. This article systematically reviews the synthesis strategies of polyurethane composites; provides a detailed analysis of the roles of fillers—including carbon-based materials, polymers, and metal nanoparticles/nanowires—in enhancing the mechanical, electrical, and functional properties of the composites; and further summarizes the research progress of polyurethane composite-based flexible sensors in cutting-edge areas such as eco-friendly sensing, human motion monitoring, health monitoring, and bionic electronic skin. Future development trends are also discussed, aiming to provide insights for the design and development of high-performance flexible sensors. Full article