Search Results (439)

To address the inadequate balance between exploration and exploitation of existing algorithms in complex solution spaces, this paper proposes a novel mathematical metaheuristic optimization algorithm—the Perpendicular Bisector Optimization Algorithm (PBOA). Inspired by the geometric symmetry of perpendicular bisectors (the endpoints of a line segment are symmetric about them), the algorithm designs differentiated convergence strategies. In the exploration phase, a slow convergence strategy is adopted (deliberately steering particles away from the optimal region defined by the perpendicular bisector) to expand the search space; in the exploitation phase, fast convergence refines the search process and improves accuracy. It selects 4 particles to construct line segments and perpendicular bisectors with the current particle, enhancing global exploration capability. The experimental results on 27 benchmark functions, compared with 15 state-of-the-art algorithms, show that the PBOA outperforms others in accuracy, stability, and efficiency. When applied to 5 engineering design problems, its fitness values are significantly lower. For H-type motion platforms, the PBOA-optimized platform not only achieves high unidirectional motion accuracy, but also the average synchronization error of the two Y-direction motion mechanisms reaches ±2.6 × 10⁻⁵ mm, with stable anti-interference performance. Full article

Ultrawideband (UWB) radar has emerged as a compelling solution for noncontact human activity recognition. This study proposes a novel framework that leverages adaptive signal decomposition and video-based deep learning to classify human motions with high accuracy using a single UWB radar. The raw radar signals were processed by empirical wavelet transform (EWT) to isolate the dominant frequency components in a data-driven manner. These components were further analyzed using the Hilbert transform to produce time–frequency spectra that capture motion-specific signatures through subtle phase variations. Instead of treating each spectrum as an isolated image, the resulting sequence was organized into a temporally coherent video, capturing spatial and temporal motion dynamics. The video data were used to train the SlowFast network—a dual-path deep learning model optimized for video-based action recognition. The proposed system achieved an average classification accuracy exceeding 99% across five representative human actions. The experimental results confirmed that the EWT–Hilbert-based preprocessing enhanced feature distinctiveness, while the SlowFast architecture enabled efficient and accurate learning of motion patterns. The proposed framework is intuitive, computationally efficient, and scalable, demonstrating strong potential for deployment in real-world scenarios such as smart healthcare, ambient-assisted living, and privacy-sensitive surveillance environments. Full article

Objectives: We investigated the performance of a slow computed tomography (CT) protocol to reduce alignment errors arising from motion when using CT-on-rail (CTOR) for image guidance for patients receiving thoracic stereotactic body radiation therapy (SBRT). Methods: A Quasar lung phantom with a moving tumor was programmed with three breathing rates and three motion amplitudes. MIP and average 4DCT images were used for contouring and alignment, respectively. Ten CTOR images were obtained for each of the breathing rates and amplitudes, under both CT protocols. We used in-house CAT software for image guidance, centering the tumor in the lung window within the gross tumor volume contour. Longitudinal coordinate reproducibility was compared between the two protocols. We also retrospectively analyzed CBCT SBRT image guidance alignment data from 31 patients to evaluate the systematic error in the longitudinal direction between simulation and daily treatments. Results: The mean (standard deviation) alignments (mm) for the standard and slow CT protocol ranged from 0.7 (0.68) and 1.0 (0.0), respectively, for the 28 BPM breathing rate and 5 mm amplitude combination to 5.2 (2.0) and 1.6 (0.52) for the 8 BPM breathing rate and 15 mm amplitude combination. Our retrospective analysis of patient alignment data showed a notable systematic difference in the relative bone and gross tumor volume alignment between the simulation and daily cone beam CT datasets. The mean longitudinal difference was −0.19 cm (standard deviation, 0.17 cm; range, 0.28 cm to −1.14 cm). Therefore, the position of the vertebral body cannot be used as a surrogate for mean tumor position in the longitudinal direction. Longitudinal position must be accurately determined for each patient using multiple CT images. Conclusions: A slow CT protocol improved the alignment with slower breathing rates being more challenging. A 5 mm PTV is not sufficient for tumor motion greater than 9 mm. Averaging the coordinates from multiple CTOR images is recommended. Full article

The parameter identification of Autonomous Underwater Vehicles (AUVs) serves as a fundamental basis for achieving high-precision motion control, state monitoring, and system development. Currently, AUV parameter identification typically relies on the complete motion information obtained from onboard sensors. However, in practical applications, it is often challenging to accurately measure key state variables such as velocity and angular velocity, resulting in incomplete measurement data that compromises identification accuracy and model reliability. This issue is particularly pronounced in vertical motion tasks involving low-speed, large pitch angles, and highly maneuverable conditions, where the strong coupling and nonlinear characteristics of underwater vehicles become more significant. Traditional hydrodynamic models based on full-state measurements often suffer from limited descriptive capability and difficulties in parameter estimation under such conditions. To address these challenges, this study investigates a parameter identification method for AUVs operating under vertical, large-amplitude maneuvers with constrained measurement information. A control autoregressive (CAR) model-based identification approach is derived, which requires only pitch angle, vertical velocity, and vertical position data, thereby reducing the dependence on complete state observations. To overcome the limitations of the conventional Recursive Least Squares (RLS) algorithm—namely, its slow convergence and low accuracy under rapidly changing conditions—a Multi-Innovation Least Squares (MILS) algorithm is proposed to enable the efficient estimation of nonlinear hydrodynamic characteristics in complex dynamic environments. The simulation and experimental results validate the effectiveness of the proposed method, demonstrating high identification accuracy and robustness in scenarios involving large pitch angles and rapid maneuvering. The results confirm that the combined use of the CAR model and MILS algorithm significantly enhances model adaptability and accuracy, providing a solid data foundation and theoretical support for the design of AUV control systems in complex operational environments. Full article

We advance a mathematical framework for collective conviction by deriving a continuum theory from the network-based model introduced by us recently. The resulting equation governs the evolution of belief through a degenerate anisotropic logistic–diffusion process, where diffusion slows as conviction saturates. In one spatial dimension, we prove global well-posedness, demonstrate spectral front pinning that arrests the spread of influence at finite depth, and construct explicit traveling-wave solutions. In two dimensions, we uncover a geometric mechanism of curvature–induced quenching, where belief propagation halts along regions of low effective mobility and curvature. Building on this insight, we formulate a variational principle for optimal control under resource constraints. The derived feedback law prescribes how to spatially allocate repression effort to maximize inhibition of front motion, concentrating resources along high-curvature, low-mobility arcs. Numerical simulations validate the theory, illustrating how localized suppression dramatically reduces transverse spread without affecting fast axes. These results bridge analytical modeling with societal phenomena such as protest diffusion, misinformation spread, and institutional resistance, offering a principled foundation for selective intervention policies in structured populations. Full article

This study aimed to investigate the influence of different walking speeds on shoulder and elbow joint kinematics, specifically focusing on range of motion, angular velocity, and angular acceleration during arm swing. The natural rhythm of human gait was studied to develop an effective mechanical interface, particularly with respect to joint impedance and force controllability. The independent variable in this study was walking speed, operationalized at four levels—3.6 km/h (slow), 4.2 km/h (preferred walking speed, PWS), 5.4 km/h (normal), and 7.2 km/h (fast)—and defined as a within-subject factor. The dependent variables consisted of quantitative kinematic parameters, including joint range of motion (ROM, in degrees), peak and minimum joint angular velocity (deg/s), and peak and minimum joint angular acceleration (deg/s²). For each subject, data from twenty gait cycles were extracted for analysis. The kinematic variables of the shoulder and elbow were analyzed, showing increasing trends as the walking speed increased. As walking speed increases, adequate arm swing contributes to gait stability and energy efficiency. Notably, the ROM of shoulder was slightly reduced at the PWS compared to the slowest speed (3.6 km/h), which may reflect more natural and coordinated limb movements at the PWS. Dynamic covariation of torque patterns in the shoulder and elbow joints was observed, reflecting a synergistic coordination between these joints in response to human body movement. Full article

Polymer electrolytes (PEs) provide enhanced safety for high–energy–density lithium metal batteries (LMBs), yet their practical application is hampered by intrinsically low ionic conductivity and insufficient electrochemical stability, primarily stemming from suboptimal Li⁺ solvation environments and transport pathways coupled with slow polymer dynamics. Herein, we demonstrate a molecular design strategy to overcome these limitations by regulating the Li⁺ solvation structure through the synergistic interplay of conventional Lewis acid–base coordination and engineered hydrogen bond (H–bond) networks, achieved by incorporating specific H–bond donor functionalities (N,N′–methylenebis(acrylamide), MBA) into the polymer architecture. Computational modeling confirms that the introduced H–bonds effectively modulate the Li⁺ coordination environment, promote salt dissociation, and create favorable pathways for faster ion transport decoupled from polymer chain motion. Experimentally, the resultant polymer electrolyte (MFE, based on MBA) enables exceptionally stable Li metal cycling in symmetric cells (>4000 h at 0.1 mA cm⁻²), endows LFP|MFE|Li cells with long–term stability, achieving 81.0% capacity retention after 1400 cycles, and confers NCM622|MFE|Li cells with cycling endurance, maintaining 81.0% capacity retention after 800 cycles under a high voltage of 4.3 V at room temperature. This study underscores a potent molecular engineering strategy, leveraging synergistic hydrogen bonding and Lewis acid–base interactions to rationally tailor the Li⁺ solvation structure and unlock efficient ion transport in polymer electrolytes, paving a promising path towards high–performance solid–state lithium metal batteries. Full article

Motion of dislocations is a common mechanism of plasticity in many materials. Acoustic emissions and stress bursts turned out to be integral parts of this mechanism. An adequate description of these processes is an important goal of the Materials Theory, which aims to describe the mechanical properties of materials and their reliability in service. In this article, a novel approach to dislocation plasticity capable of describing emission events and stress bursts is introduced, and computational experiments intended to model the processes of compressive creep and shock compression in samples of various makeup and sizes are discussed. It turns out that the emission events self-organize into dislocation avalanches, which propagate at a speed determined by the conditions of loading. In the compressive creep experiments, the avalanches arrange into slow-moving slip bands, while in the shock compression experiments the avalanches move faster than sound. Full article

Introduction: Elbow flexor spasticity is a common and debilitating consequence of stroke, significantly impacting patients’ quality of life. Botulinum toxin A (BoNT-A) injections have emerged as an effective treatment, but the optimal muscle selection strategy remains unclear. This study investigates the impact of different BoNT-A injection strategies targeting specific elbow flexor muscles in post-stroke patients. Materials and Methods: A non-randomized observational study was conducted on 52 participants with upper limb spasticity (pattern IV) following a stroke. Participants were divided into three groups based on the elbow flexor muscles injected with BoNT-A: biceps brachii (n = 15), brachialis (n = 9), and brachialis plus brachioradialis (n = 28). Assessments included spasticity angle, paresis angle, and active supination range of motion (ROM) measured using the Tardieu Scale and goniometry at baseline and at 4-week follow-up. Non-parametric statistical analyses were employed to compare outcomes between groups. Results: While all groups showed a general trend of decreased spasticity and improved motor control, analysis revealed statistically significant differences across the groups at baseline. The brachialis plus brachioradialis group demonstrated the most substantial improvement in paresis angle and active supination ROM. Notably, this group also exhibited greater capacity for the improvement of the paresis angle. The biceps brachii group showed comparable improvements in the paresis angle and the greatest effect on improving passive extension at slow velocity with increasing stroke onset but required higher pronator teres BoNT-A doses overall. Discussion: These findings suggest that individualized muscle selection strategies are crucial in BoNT-A treatment for elbow flexor spasticity. The superior outcomes observed in the brachialis plus brachioradialis group may be attributed to the synergistic action of these muscles in elbow flexion and forearm positioning. The higher pronator teres BoNT-A doses required in the biceps brachii group may reflect compensatory mechanisms or differences in muscle fiber recruitment patterns. Conclusions: Combining brachialis and brachioradialis muscles in BoNT-A injections appears to offer superior benefits for supination and motor control in post-stroke patients with elbow flexor spasticity, particularly those with significant elbow flexion and pronation. Full article

Sri Lanka typically experiences anomalously wet conditions during the summer following El Niño events, but this response varies due to El Niño complexity. This study investigates the impact of post-El Niño conditions on Sri Lanka’s Monsoon rainfall, contrasting summers after fast- and slow-decaying El Niño events. Results indicate that fast-decaying El Niño events lead to wet and cool summers while slow-decaying events result in dry and warm summers. These contrasting responses are linked to sea surface temperature (SST) changes in the central to eastern Pacific. During the fast-decaying El Niño, the transition to La Niña generates strong easterlies in the central and eastern Pacific, enhancing moisture convergence, upward motion, and cloud cover, resulting in wetter conditions over Sri Lanka. During the fast-decaying El Niño, enhanced precipitation over the Maritime Continent acts as a diabatic heating source, inducing Gill-type easterly wind anomalies over the tropical Pacific. These winds promote coupled feedbacks that accelerate the transition to La Niña, strengthening moisture convergence and upward motion over Sri Lanka. Conversely, slow-decaying El Niño events are associated with cooling in the western North Pacific and warming in the Indian Ocean, which promotes the development of the western North Pacific anticyclone, suppressing upward motion and reducing cloud cover, leading to conditions over Sri Lanka. Changes in the Walker circulation further contribute to these distinct rainfall patterns, highlighting its influence on regional climate dynamics. These findings enhance our understanding of the seasonal predictability of rainfall in Sri Lanka during post-El Niño Summers. Full article

Introduction: Robotic-assisted (RA) spine surgery enhances pedicle screw placement accuracy through real-time navigation and trajectory guidance. However, the absence of traditional direct haptic feedback by freehand instrumentation remains a concern for some, particularly in minimally invasive (MIS) procedures where direct visual confirmation is limited. During RA spine surgery, navigation systems display three-dimensional data, but factors such as registration errors, intraoperative motion, and anatomical variability may compromise accuracy. This technical note describes a visuohaptic intraoperative phenomenon observed during RA spine surgery, its underlying mechanical principles, and its utility. During pedicle screw insertion with a slow-speed automated drill in RA spine procedures, a subtle and rhythmic variation in resistance has been observed both visually on the navigation interface and haptically through the handheld drill. This intraoperative pattern is referred to in this report as a cyclical insertional torque (CIT) pattern and has been noted across multiple cases. The CIT pattern is hypothesized to result from localized stick–slip dynamics, where alternating phases of resistance and release at the bone–screw interface generate periodic torque fluctuations. The pattern is most pronounced at low insertion speeds and diminishes with increasing drill velocity. CIT is a newly described intraoperative observation that may provide visuohaptic feedback during pedicle screw insertion in RA spine surgery. Through slow-speed automated drilling, CIT offers a cue for bone engagement, which could support intraoperative awareness in scenarios where tactile feedback is reduced or visual confirmation is indirect. While CIT may enhance surgeon confidence during screw advancement, its clinical relevance, reproducibility, and impact on placement accuracy have yet to be validated. Full article

This block-randomized crossover study investigated how a speed-modulated aquatic treadmill (AT) impacts the walking biomechanics of pediatric gait. Eight cerebral palsy (CP) and fifteen typically developing (TD) children walked at normal, slow, and fast treadmill speeds in AT and dry treadmill (DT) conditions. The joint angles of participants were calculated from inertial measurement units to derive sample entropy (SE) measures that quantified the regularity or complexity of motion. A hierarchical statistical model revealed that the CP group had lower SE values for the hip, knee, and ankle joints in the AT and at slower than faster treadmill speeds. Only the SE values of the knee and ankle joints were impacted for the TD group. The lower SE values suggest improved regularity for participants at slower speeds and in the AT environment. This study highlights the potential of AT to improve the walking biomechanics of children with CP in acute exposure, but further work is needed to investigate the AT condition as a gait rehabilitation environment. Full article

This study employs molecular dynamics simulations to construct designed unit cells of organic montmorillonite (OMMT) modified with four types of quaternary ammonium salts. The effects of modifier type and quantity on the basal spacing of montmorillonite (MMT) were analyzed. Molecular motion, morphology, interaction energy (E_int), and hydrogen bonding interactions were investigated to elucidate the molecular-level mechanisms between modifiers and MMT. The results indicate that the organic modification of MMT proceeds in three distinct stages: the filled stage, saturated stage, and supersaturated stage. During the filled stage, the basal spacing remains largely unchanged while E_int increases rapidly. In the saturated stage, the basal spacing expands as the growth rate of E_int slows. In the supersaturated stage, the basal spacing continues to increase while E_int stabilizes. The transition from the filled to saturated stage is governed by the van der Waals space occupied by the modifiers. Within the MMT interlayer, the modifiers adopt a bilayer morphology, with the nitrogen atom heads adhering to the MMT surfaces and the tails self-assembling. These findings provide theoretical insights into the basal spacing expansion and organic modification mechanisms of MMT, thereby facilitating improved material compatibility. Full article

Methodologies to measure motion perception are vital for deepening our understanding of the vision system and the factors that influence it. While existing work has primarily focused on the fastest perceivable velocities, less attention has been paid to the lower threshold of motion (LTM; slowest perceivable velocities). In this study, we designed an optical system to measure LTM in a sample of healthy young adults and to assess the influence of retinal location (central vs. peripheral retina) and stimulus composition (broadband vs. mid-wave) on LTM. The system was based on a xenon light source and a fiber-optic cable that created a bright light stimulus that could be moved along a computer-controlled precision translation slide. The stimulus, exposed for one-second intervals at both a central (fovea) and a peripheral (33 deg) location, was moved at varying speeds to determine the slowest detectable speed. In all, 37 healthy young participants (M = 19.32 ± 1.97 years) were tested. We found substantial between-subject variability in LTM and an interaction between stimulus wavelength and retinal location. The measurement of LTM using this novel apparatus and methodology provides insights into the relationship between slow-moving, ecologically valid stimuli and perceptual detection at the slowest speeds. Full article

Coaches manipulate training variables to optimize and improve them, with intensity being crucial. Velocity-based training, measuring intensity by the movement speed, is advantageous over traditional methods. Flywheel training, offering concentric and eccentric loads, allows for supramaximal loading during the eccentric phase, enhancing muscle hypertrophy and performance and reducing injury risk. This study examines the specific effects of flywheel training on post-activation potentiation (PAP). Forty-one high-level male athletes performed flywheel half squats at fast (0.95–1.05 m/s), medium (0.65–0.75 m/s), and slow (0.35–0.45 m/s) speeds. Their drop jump performance was assessed at 30 s and 4, 8, and 12 min post-induction. Lower-limb kinematic data and ground reaction forces were recorded using infrared motion capture and force plates. Measures included peak collision force, peak extension force, knee joint extension moment, knee joint power, average power output, and vertical jump height. High-speed intensity significantly increased peak impact force, peak vertical ground reaction force, knee joint eccentric power, concentric power, and extension torque at 4, 8, and 12 min post-induction (p < 0.05). Fast- (0.95–1.05 m/s) and medium-speed (0.65–0.75 m/s) flywheel squats acutely improved lower-limb performance, especially vertical jump height, within 4–12 min post-stimulation. Fast-speed loading showed greater benefits for reactive strength and power output, while a medium speed also yielded meaningful gains. These findings support using movement velocity to guide flywheel training intensity. Full article