Search Results (706)

Biological muscles generate tension from the combined contribution of the passive elastic recoil and the actively controlled contractile mechanisms. Understanding and replicating these passive and active tensions is necessary and beneficial for designing soft robotic actuators that emulate muscle-like behavior. In the current work, the aim is to develop a mathematical framework for modeling both the passive and active tensions in a biological muscle as functions of muscle length and contraction velocity. We will describe the passive tension by a nonlinear monotonically increasing function of length with threshold behavior in order to capture the experimentally observed stiffening occurring in stretched biological muscles. We will model the active tension using the superposition of Gaussian functions that relate bell-shaped tension-length with a flat plateau over the optimal length of the sarcomere. The parameters of this Gaussian representation of the active tension-length relation are determined from formulating a least-squares optimization problem, such that a Characteristic (indicator) function is approximated globally over the optimal length range of the sarcomere by summation of some Gaussian functions. The closed-form formulations for the required integrals are derived using the integral of the product of two Gaussian functions over ${\mathbb{R}}^n$ as well as the error function which enables efficient parameter identification. We will also propose a symmetric tension–velocity relation that distinguishes three phases of concentric, eccentric and isometric contractions, and is parametrized directly by measurable quantities of isometric tension and maximum shortening velocity. The passive and active tensions are finally combined into a unified comprehensive tension model in which the exponentially modeled passive tension is added up to the active contribution, formulated as the product of the activation level, a normalized length-dependent factor and a normalized velocity-dependent factor. The resulting model reproduces canonical tension-length and tension-velocity relations and provides an analytically tractable comprehensive tension model that can be embedded in the dynamics of soft and continuum robot actuators inspired by biological muscles. Full article

In underwater reconnaissance and patrol, AUV has to sense and judge traversability in cluttered areas that include reefs, cliffs, and seabed infrastructure. A narrow sonar field of view, occlusion, and current-driven disturbances leave the vehicle with local, time-varying information, so decisions are made with incomplete and uncertain observations. A path-planning framework is built around two coupled components: spatiotemporal graph neural network prediction and conditional normalizing flow (CNF)-based probabilistic environment reconstruction. Forward-looking sonar and inertial navigation system (INS) measurements are fused online to form a local environment graph with temporal encoding. Cross-temporal message passing captures how occupancy and maneuver patterns evolve, which supports path prediction under dynamic reachability and collision-avoidance constraints. For regions that remain unobserved, CNF performs conditional generation from the available local observations, producing probabilistic completion and an explicit uncertainty output. Conformal calibration then maps model confidence to credible intervals with controlled miscoverage, giving a consistent probabilistic interface for risk budgeting. To keep pace with ocean currents and moving targets, edge weights and graph connectivity are updated online as new observations arrive. Compared with Informed Random Tree star (RRT*), D* Lite, Soft Actor-Critic (SAC), and Graph Neural Network-Probabilistic Roadmap (GNN-PRM), the proposed method achieves a near 100% success rate at 20% occlusion and maintains about an 80% success rate even under 70% occlusion. In dynamic obstacle scenarios, it yields about a 4% collision rate at low speeds and keeps the collision rate below 20% when obstacle speed increases to 3 m/s. Ablation studies further demonstrate that temporal modeling improves success rate by about 7.1%, CNF-based probabilistic completion boosts success rate by about 13.2% and reduces collisions by about 17%, while conformal calibration reduces coverage error by about 6.6%, confirming robust planning under heavy occlusion and time-varying uncertainty. Full article

As a core functional component of the prosthetic system, the prosthetic socket’s adaptability to the residual limb is directly correlated with the prosthetic’s performance, comfort level, and safety profile. Although traditional sockets can satisfy basic suspension requirements, they commonly suffer from inherent drawbacks in practical applications, including uneven pressure distribution, poor air permeability, and inadequate adaptability to the morphological variations of individual residual limbs. To enhance socket adaptability across multi-task scenarios, this study proposes an intelligent physiological adaptation-based optimal design method for active upper-limb prosthetic sockets. Specifically, this method first employs a dynamic force optimization algorithm for multi-contact units oriented to prosthetic manipulation tasks, which real-timely optimizes the output force of each unit under varying external loads to achieve stable socket suspension with minimal interface pressure. Second, biomechanical experiments are conducted to obtain the pain threshold distribution characteristics of forearm soft tissues under compressive loads, thereby providing a physiological basis for the spatial layout of the contact units. Furthermore, the mechanical performance of different socket structures is evaluated under various representative task scenarios, with peak normal force, mean normal force, and force distribution variance adopted as the key comfort evaluation indices. The results demonstrate that the proposed active multi-unit socket, particularly the double-layered eight-unit symmetric radial staggered configuration, enables a robust balance between comfort and stability across diverse task scenarios, thereby establishing an effective and scalable design paradigm for long-term adaptive upper-limb prosthetic sockets. Full article

Small bowel obstruction (SBO) in dogs is most commonly caused by foreign bodies or neoplasia; however, SBO secondary to transmural fibroplasia remains a rare clinical complication of canine chronic enteropathy. This report describes the complex case of mechanical SBO caused by transmural ileal fibroplasia and inflammation at the ileocolic junction in a 9-year-old mixed-breed dog with concomitant hyperadrenocorticism (HAC). The primary presentation involved chronic severe weight loss and intermittent anorexia, contrasting with the acute presentation typical of most SBO cases. Imaging studies revealed severe, circumferential thickening up to 10 mm of the small intestine wall at the ileocolic junction (ICJ), resulting in complete luminal stricture and marked proximal dilation. Surgical intestinal resection and anastomosis were performed for alleviation of the obstruction, and histopathology confirmed severe mural and serosal enteritis with extensive fibroplasia extending into the adjacent mesentery, thereby excluding neoplastic processes. Quantitative PCR analysis demonstrated a significant upregulation of mRNA expression for PDGFRB and FGFR compared to normal tissue. Postoperative recovery was rapid; although soft feces persisted for one month, normal stool consistency was subsequently restored, and the patient achieved significant weight gain. This case underscores the diagnostic and therapeutic challenges associated with non-neoplastic, inflammation-driven SBO and suggests that activation of the PDGFR-β/FGFR pathways may play a key role in fibroplasia-related intestinal strictures, offering a novel molecular perspective beyond conventional SBO etiologies. Full article

Urban airborne laser scanning (ALS) point clouds cover extensive geographical areas, rendering dense point-level annotation economically prohibitive and limiting the feasibility of fully supervised learning. In weakly supervised settings for urban ALS data, the natural long-tailed class distribution—where ground and building points dominate and smaller objects are rare—combined with the use of fixed pseudo-label thresholds under sparse annotations exacerbates confirmation bias and increases prediction uncertainty. This ultimately restricts the effective utilization of unlabeled data during training. To overcome these challenges, we propose a pseudo-label confidence-calibrated curriculum learning framework designed for weakly supervised ALS point cloud classification. The framework introduces a confidence-aware self-adaptive soft gating (CSS) mechanism that dynamically adjusts category-specific thresholds online using exponential moving average statistics and scene-aware normalization, eliminating the need for manual scheduling while improving pseudo-label quality. In addition, a reliability-driven soft selection (RSS) constraint is incorporated, in which each point is assigned a comprehensive reliability score that integrates prediction confidence, entropy clarity, and cross-augmentation consistency, enabling adaptive soft weighting to replace hard pseudo-label selection and achieve more balanced sample utilization. These components are further integrated into a unified pseudo-label confidence-calibrated curriculum learning framework (P3CL) that progressively shifts the model’s focus from high-certainty samples to more ambiguous ones, effectively mitigating confirmation bias. Extensive experiments on three public ALS benchmarks demonstrate that the proposed method consistently outperforms existing weakly supervised approaches and achieves competitive performance compared with several fully supervised models. Full article

Quasi-resonant (QR) DC–DC converters with PWM control achieve soft switching by shaping the commutation transient through a local resonant process. This paper proposes a symmetry-based unified perspective on classical QR converters by interpreting zero-voltage switching (ZVS) and zero-current switching (ZCS) as dual commutation symmetries: ZVS restores voltage symmetry at turn-on, whereas ZCS restores current symmetry at turn-off. Building on this viewpoint, we organize QR Buck, Boost, and Buck–Boost converters through two complementary forms of symmetry: (i) commutation symmetry (ZVS vs. ZCS) and (ii) topological duality (Buck ↔ Boost and the self-dual nature of Buck–Boost). The framework is anchored in normalized parameter spaces commonly used in QR analyses and is illustrated using representative ZVS and ZCS Buck cases, including waveform-stage symmetry and loss/stress implications. Furthermore, we discuss the “cost of symmetry” via stress and conduction-loss metrics, highlighting how soft-switching conditions trade voltage and current stresses in dual fashions. The proposed organization offers a compact conceptual map that links operating regimes, design degrees of freedom, and expected stress/loss trends across the main classical QR-PWM converter families. Full article

Background/Objectives: Synovial sarcoma (SS) is a rare and aggressive soft-tissue malignancy characterized by complex molecular alterations and poor prognosis, highlighting the need for targeted immunotherapeutic strategies. This study aimed to design a rational multi-epitope vaccine targeting the FKBP10 oncoprotein to elicit effective immune responses against SS. Methods: Transcriptomic data from the GEO dataset GSE144190, comprising 10 tumor and 9 normal tissue samples, were analyzed to identify differentially expressed genes (DEGs). Results: Our findings revealed significantly upregulated FKBP10 with a log2 fold change of 3.55, baseMean expression of 1521.84, and adjusted p-value of 8.37 × 10⁻²⁶. Mutational analysis across 7782 sarcoma samples indicated a low alteration frequency of ~1.5%, primarily missense variants. Functional mapping showed FKBP10 as a hub interacting with multiple collagen chains and chaperone proteins, implicating its role in extracellular matrix organization and protein folding. Linear B-cell epitope prediction identified 17 epitopes (6–21 amino acids), while T-cell mapping yielded 10 MHC class I and 9 MHC class II high-affinity epitopes, all antigenic (VaxiJen > 0.5) and non-allergenic. A multi-epitope vaccine was constructed incorporating a 50S ribosomal protein L22 adjuvant, linkers, and a 6× histidine tag. Physicochemical analysis showed a molecular weight of 36.43 kDa, pI 6.97, instability index 31.79, aliphatic index 64.88, and GRAVY −0.509, indicating stability and hydrophilicity. Structural modeling validated 82.5% residues in favored regions. Molecular docking revealed strong binding with TLR4 (−9.7 kcal/mol) and TLR9 (−9.4 kcal/mol), and 200 ns molecular dynamics simulations confirmed stable RMSD trajectories, low RMSF at binding residues (<4 Å), persistent hydrogen bonding, compact radius of gyration (38–42 Å for TLR4; ~20 Å for TLR9), favorable total energy (−1400 to −1500 kcal/mol for TLR4; −650 to −720 kcal/mol for TLR9), and stable SASA (~52,000–54,000 Ų). Conclusions: These findings demonstrate that the FKBP10 multi-epitope vaccine is structurally stable, immunogenic, and capable of engaging key innate immune receptors, supporting its potential as a promising immunotherapeutic candidate for synovial sarcoma. Full article

In response to the deterioration of path-tracking accuracy and driving stability encountered by intelligent vehicles under dynamically varying operating conditions, a multi-objective optimization strategy integrating soft actor-critic (SAC) reinforcement learning with variable-parameter Model Predictive Control (MPC) is proposed in this paper to achieve online adaptive adjustment of path-tracking controller parameters. Based on a three-degree-of-freedom vehicle dynamics model, a linear time-varying (LTV) MPC controller is constructed to jointly optimize the front wheel steering angle. An SAC agent is developed utilizing the actor-critic framework, with a comprehensive reward function designed around tracking accuracy and control smoothness to enable online tuning of the MPC weighting matrices (lateral error weight, heading error weight, and steering control weight) as well as the prediction horizon parameter, thereby realizing adaptive balance between tracking accuracy and stability under different operating conditions. Based on the simulation results, it can be concluded that under normal operating conditions, the proposed integrated SAC-MPC control scheme demonstrates superior tracking performance, with the maximum absolute lateral error and mean lateral error reduced by 44.9% and 67.2%, respectively, and the maximum absolute heading error reduced by 23.5%. When the system operates under nonlinear conditions during the transitional phase, the proposed control scheme not only enhances tracking accuracy—evidenced by reductions of 43.4% and 23.8% in the maximum absolute lateral error and maximum absolute heading error, respectively—but also significantly improves system stability, as indicated by a 20.7% reduction in the sideslip angle at the center of gravity. Experimental validation further confirms these findings. The experimental results reveal that, compared with the fixed-parameter MPC, the maximum absolute value and mean value of the lateral error are reduced by approximately 36.2% and 78.1%, respectively; the maximum absolute heading angle error is decreased by 24.3%; the maximum absolute yaw rate is diminished by 19.6%; and the maximum absolute sideslip angle at the center of gravity is reduced by 30.8%. Full article

The use of horses for sport is under scrutiny due to evidence that common practices such as tight nosebands may impair horse welfare. Restrictive nosebands prevent horses from performing normal comfort behaviour such as coughing and yawning. To address these concerns, the International Society for Equitation Science (ISES) developed a noseband tightness-checking device, the ISES “taper gauge,” along with a validated method that assesses how far the device can be inserted beneath the noseband at the dorsal midline of the nasal planum. However, citing concerns about the reliability of dorsal midline measurements, MacKechnie-Guire and co-authors evaluated three alternative sites: lateral to the nasal bone, the maxilla, and the mandible. They concluded that the lateral maxilla was a suitable substitute for the dorsal midline. The methods and interpretation of the findings of this study have raised concerns that measuring noseband laxity at the lateral maxilla may underestimate tightness because of the substantial volume of soft tissue at that location. This could expose horses to the welfare risks associated with overly tight nosebands. This commentary outlines the authors’ concerns and offers recommendations for how future studies might address avoid the issues raised here. Full article

Falls are a leading cause of bone fractures among the elderly, particularly hip fractures resulting from side falls. This research deals with the feasibility of application of shear-thickening fluids (STFs) to design self-protective wearable devices to rapidly respond to sudden impact due to falls. The device consists of a lightweight, flexible foam structure embedded with STF-filled compartments, which remain soft during normal movements but stiffen upon sudden impact, effectively dissipating energy and reducing force trans-mission to the bones. First, a foam-based sandwich panel filled with STF is fabricated and subjected to several falling scenarios through a ball drop test. The induced strain of the device with and without STF is measured using Fiber Bragg Grating (FBG) sensors. Then, the effect of localized STF is explored by fabricating a soft 3D-printed (TPU) sandwich panel filled with STF at selected cavities. It was observed that the application of STF reduces the induced strain by approximately 50% for the TPU skin device and 30% for the foam-based device. This adaptive response mechanism offers a balance between comfort and protection, ensuring wearability for daily use while significantly lowering fracture risks. The proposed solution aims to enhance fall-related injury prevention for the elderly, improving their quality of life and reducing healthcare burdens associated with fall-related fractures. Full article

Non-destructive estimation of high-temperature stress effects on tobacco plants is crucial for both scientific research and practical applications. Normalized difference vegetation index (NDVI), chlorophyll index, and spectra in the range of 900–1700 nm of Burley, Oriental, and Virginia tobacco plants under control and high-temperature stress conditions were measured using portable instruments. NDVI and chlorophyll index measurements indicate that young leaves of all tobacco types are tolerant to high temperatures. In contrast, the older leaves (the fifth leaf) showed increased sensitivity to heat stress. The chlorophyll content of these leaves decreased by 40 to 60% after five days of stress, and by the seventh day, the reduction reached 80% or more in all plants. The vegetative index of the fifth leaf also decreased on the seventh day of stress in all tobacco types. Differences in near-infrared spectra were observed between control, stressed, and recovered plants, as well as among different stress days, and among tobacco lines. The most significant differences were in the 1300–1500 nm range. The first characterization of heat-induced changes in the molecular structure of water in tobacco leaves using an aquaphotomics approach was conducted. Models for determining days of high-temperature treatment based on near-infrared spectra achieved a standard error of cross-validation (SECV) from 0.49 to 0.62 days. The total accuracy of the Soft Independent Modeling of Class Analogy (SIMCA) classification models of control, stressed, and recovered plants ranged from 91.0 to 93.6% using leaves’ spectra of the first five days of high-temperature stress, and from 90.7 to 97.7% using spectra of only the fifth leaf. Similar accuracy was obtained using Partial Least Squares–Discriminant Analysis (PLS-DA). Near-infrared spectroscopy and aquaphotomics can be used as a fast and non-destructive approach for early detection of stress and additional tools for investigating high-temperature tolerance in tobacco plants. Full article

Objective: To evaluate the impact of the menopausal transition on body composition across different body mass categories and to identify menopause-related changes in lean and fat tissue distribution. Methods: This retrospective cross-sectional study included 325 women whose clinical and body composition data were extracted from existing records. Participants were classified as premenopausal (controls), perimenopausal, or postmenopausal and further stratified by body mass index (BMI) into normal-weight, overweight, and obesity groups. Body composition had been assessed using bioelectrical impedance analysis. Results: Across all BMI categories, postmenopausal women demonstrated significantly lower lean body mass, soft lean mass, skeletal muscle mass, total body water, protein, and mineral content compared with premenopausal and perimenopausal women (p < 0.05). Total and visceral fat area (VFA), body fat percentage (BF), and waist-to-hip ratio were significantly higher, indicating a shift toward central adiposity. These changes were most pronounced in normal-weight women (VFA: 36.4 ± 17.0, 48.3 ± 22.3, and 55.7 ± 23.5 cm²; BF: 24.8 ± 5.3%, 27.2 ± 5.2%, and 28.8 ± 4.6% in pre-, peri-, and postmenopause, respectively), and less marked among overweight women (VFA: 91.5 ± 36.3, 106.1 ± 38.2, and 111.7 ± 28.6 cm²; BF: 36.0 ± 3.6%, 36.4 ± 3.9%, and 37.2 ± 3.2%) and with obesity (VFA: 180.3 ± 62.4, 212.6 ± 96.2, and 175.5 ± 54.4 cm²; BF: 44.5 ± 4.5%, 44.5 ± 5.7%, and 41.9 ± 3.3%), suggesting a relative attenuation of muscle loss at higher BMI. Conclusions: Postmenopausal women showed a clear shift toward lower lean mass and greater central adiposity across BMI categories. These patterns indicate a consistent deterioration in body composition during the menopausal transition. Assessment of visceral fat in postmenopausal women is crucial, as its accumulation is closely linked to cardiometabolic risk. Menopause-related hormonal changes favor central adiposity, supporting the use of visceral fat as a key indicator for early risk stratification and preventive interventions in midlife women. Full article

In this study, a high-performance MoS₂-based strain-gauge pressure was sensor fabricated entirely below 80 °C, enabling direct integration onto flexible polyethylene terephthalate (PET) substrates. The sensor comprised a three-layer MoS₂ channel (~2 nm) patterned via dry transfer and O₂/Ar plasma etching, interfaced with Cr/Au electrodes. This wafer-scale and cost-effective fabrication route preserves the crystallinity of the film and prevents substrate degradation. The sensor achieved a gauge factor of ~104 under compression, representing a fifty-fold improvement over conventional metal foil gauges (~2), with a linear response across both compressive and tensile regimes. Mechanical robustness was confirmed through repeated bending and tape adhesion tests, with no degradation in electrical performance. When configured as a Wheatstone bridge, this device exhibits normalized sensitivity suitable for real-time monitoring, with response and recovery times below 200 ms. These results establish O₂/Ar-plasma-patterned MoS₂ architectures as a scalable, cost-effective platform for next-generation flexible sensors, outperforming metal-foil technology in applications including seat-occupancy detection, wearable physiological monitoring, and tactile interfaces for soft robotics. Full article

Background and Objectives: Soft tissue sarcomas account for approximately 7% of all malignant tumors in the pediatric population. Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) measurements may provide early functional biomarkers of treatment response by reflecting changes in tumor cellularity. This study evaluated whether ADC-derived parameters can serve as quantitative biomarkers of neoadjuvant chemotherapy response in pediatric rhabdomyosarcoma. Materials and Methods: This retrospective single-center study included 14 patients aged ≤18 years with histopathologically confirmed rhabdomyosarcoma who underwent MRI before treatment and after three cycles of chemotherapy. Twenty-five patients were initially identified; eleven were excluded due to imaging artifacts or absence of baseline examination. ADC maps were generated on 1.5T and 3T scanners. Regions of interest were placed over the entire lesion and areas with the lowest ADC signal. Relative ADC (rADC) was calculated by normalizing tumor ADC to adjacent healthy muscle. Paired t-tests were used to compare pre- and post-treatment values. Results: At baseline, 13/14 patients (93%) demonstrated diffusion restriction. Mean ADC increased from 1.11 × 10⁻³ mm²/s (SD ± 0.48) at baseline to 1.63 × 10⁻³ mm²/s (SD ± 0.67) after treatment. The paired t-test for rADC yielded t = −3.089 (p = 0.0086, 95% CI: −0.79 to −0.14), indicating a statistically significant change. There was a significant difference between the ADC values of the entire lesion and the areas with the lowest signal in tumors with a heterogenic structure, t = 2.862, p = 0.013. Conclusions: ADC and rADC increased significantly after neoadjuvant chemotherapy in pediatric rhabdomyosarcoma, suggesting potential utility as early functional biomarkers of treatment response. These preliminary findings require validation in larger multicenter prospective studies with correlation to histopathological response and clinical outcomes before clinical implementation. Full article

This study evaluated the reliability and inter-examiner agreement of the Implant Stability Test (IST) by Anycheck compared to the established Implant Stability Quotient (ISQ) by Osstell across different bone quality types. Seven dental hygienists with varying experience levels performed stability measurements using both devices on standardized implant models representing hard, normal, and soft bone qualities. Both IST and ISQ demonstrated excellent inter-examiner reliability (ICC > 0.90) across all bone quality types, with strong positive correlations (r > 0.85) between measurements regardless of bone density. No significant differences were found in measurement consistency between examiners with different experience levels for either device. The results demonstrate that IST provides comparable reliability to ISQ for implant stability assessment, with excellent inter-examiner agreement and accessibility for practitioners with varying experience levels. The IST system offers practical advantages including elimination of SmartPeg requirements, reduced abutment manipulation, and simplified measurement protocols, supporting its potential as a reliable and cost-effective alternative to traditional ISQ measurements under standardized experimental conditions. Full article