Search Results (67)

Coastal continuous girder bridges are exposed to coupled environmental and seismic hazards during long-term service, including chloride-induced corrosion, freeze–thaw damage, scour, near-field ground motions, and structural irregularity. These factors can progressively reduce structural capacity, amplify seismic demand, redistribute component responses, and affect post-earthquake functionality and recovery. This paper reviews recent advances in the time-dependent seismic vulnerability and resilience assessment of reinforced concrete and prestressed concrete coastal continuous girder bridges. Based on 229 screened publications, the review first summarizes deterioration mechanisms and modelling approaches for chloride corrosion, freeze–thaw damage, and scour, with emphasis on their effects on material degradation, component capacity, foundation restraint, and seismic fragility. The demand-side effects of near-field vertical excitation and pulse-like ground motions are then discussed, followed by the seismic response characteristics of irregular continuous girder bridges, including curved alignments, unequal pier heights, and skewed supports. Existing studies indicate that environmental deterioration can shift fragility curves toward lower intensity levels, near-field vertical excitation can modify axial force, bearing contact state, girder–bearing separation, and impact response, while structural irregularity may concentrate seismic demand in critical components. Furthermore, the review clarifies the transition from time-dependent fragility analysis to functionality loss, recovery modelling, and lifecycle resilience assessment. The main research gaps include simplified deterioration representation, insufficient coupling of deterioration–hazard–irregularity effects, limited validation of time-dependent fragility models, and weak integration between component damage, bridge functionality, recovery trajectories, and resilience indicators. Future studies should develop more unified, uncertainty-informed, and lifecycle-oriented frameworks for coastal bridge vulnerability and resilience assessment. Full article

Due to their higher installation position and smaller diameter compared to conductors, DC overhead ground wires are more susceptible to severe icing during cold waves. To investigate the icing growth characteristics of ultra-high voltage (UHV) DC ground wires under the coupled effect of flow and electric fields, this study considers the unique operational conditions of UHV DC ground wires. Based on the physical processes of charged droplet motion, flow-around, collision, and freezing around the ground wire, a numerical model for simulating icing under the coupled flow-electric field interaction is established. The influence of factors such as wind speed, droplet size, and icing morphology on icing development under the coupled field is numerically analyzed. Furthermore, observations of icing morphology on UHV ground wires under natural conditions were conducted. The results indicate that under icing conditions, charged droplets of different sizes exhibit significant differences in trajectory deviation during flow-around and collision with the ground wire, with larger droplets being more significantly affected by the electric field force. Under the influence of the electric field, the local droplet collision coefficient on the ground wire surface can increase by 3.4% to 128.9%. Compared to uncharged conditions, icing coverage under charged conditions extends from the windward side to the leeward side, and the icing rate increases accordingly. Natural observations reveal that icing on the ground wire surface under the DC electric field often forms protruding ice tips, which enhance electric field concentration, leading to increased local droplet collision coefficients and icing rates. This, in turn, further promotes the formation of irregular and rough ice accretion. The findings of this study provide technical insights for predicting and simulating icing on UHV DC ground wires. Full article

Rear-view human tracking and re-identification remain critical challenges for robotic visual sensing in unmanned vehicles, particularly under adverse weather conditions and severe occlusion. Conventional deep learning models often suffer from feature contamination and trajectory drift under dynamic illumination. To overcome these bottlenecks, we propose a lightweight tracking framework driven by spatiotemporal prediction and multimodal feature fusion. Specifically, an ego-motion-aware Kalman prediction mechanism maintains temporal continuity during complete occlusions. Upon target reappearance, a multi-factor descriptor—fusing color histograms with geometric constraints—is employed within a dynamic Mahalanobis search region. This is coupled with a specular-reflection-penalized adaptive learning rate (η_k) that actively freezes template updates during severe environmental degradation conditions. Evaluated on a custom Mecanum-wheeled robot, the proposed method achieves a peak precision of 94.2% and a tracking success rate of 93.4%. Extensive experiments in extreme rainy night scenarios demonstrate a 35% reduction in average tracking error, maintaining a Center Location Error (CLE) below 11 pixels. Furthermore, the system achieves a rapid target re-identification response of 72.83 ms during occlusion phases. Ultimately, this framework delivers a highly robust and real-time solution for autonomous navigation in complex dynamic environments. Full article

Conductive hydrogels have emerged as promising candidates for flexible strain sensors owing to their high water content, low elastic modulus, and intrinsic ionic conductivity. However, conventional hydrogel networks often suffer from an inherent trade-off among conductivity, mechanical robustness, and long-term stability, which limits their practical deployment in wearable sensing scenarios. The introduction of metal–ligand coordination bonds into hydrogel networks offers a versatile strategy to address these challenges: dynamic coordination cross-links can dissipate energy under deformation and reform upon unloading, thereby enhancing toughness, enabling self-healing, and contributing to ionic transport. This review focuses on metal-ion-coordinated conductive hydrogels designed for strain-sensing applications. Representative coordination systems based on Fe³⁺, Ca²⁺, Zn²⁺, Al³⁺, Cu²⁺, Ti⁴⁺, and Zr⁴⁺ are surveyed, with emphasis on their characteristic polymer matrices, ligand chemistries, and network-construction strategies. Key sensing-relevant properties—including ionic conductivity, mechanical stretchability, self-healing capability, interfacial adhesion, freezing resistance, and resistance to dehydration—are discussed in relation to coordination network design. Typical application demonstrations in large-deformation motion monitoring and subtle physiological signal detection are reviewed. Unlike existing reviews that survey conductive hydrogels broadly by conductive mechanism or sensor type, this review takes metal-ion coordination as the central organizing principle and systematically traces its influence across the full design chain—from ion–ligand coordination chemistry through network architecture to macroscopic sensing output. By comparatively analyzing seven representative metal-ion systems within a unified framework, this work aims to clarify how the choice of metal ion governs the interplay among conductivity, mechanical robustness, self-healing, and strain sensitivity—a perspective that has not yet been systematically addressed in prior reviews. Finally, current challenges—including the conductivity–mechanics coupling bottleneck, insufficient long-term stability, biosafety concerns for skin-contact deployment, the lack of standardized evaluation protocols, and device-integration barriers—are identified, and future directions for this field are outlined. Full article

Background/Objectives: Gated cardiac positron emission tomography (PET) synchronizes PET data to the cardiac cycle based on an electrocardiogram (ECG) signal, providing left ventricular (LV) functional and geometrical parameters. Nevertheless, image artifacts, due to cardiac-, breathing-, and/or patient-motion occurring during image acquisition, undermine the reliability and clinical utility of these parameters. This study aims to elucidate the effect of two motion correction (MC) tools, CardioFreeze (CF) and a data-driven motion correction (DDMC) prototype, on LV functional and geometrical parameters. Methods: ECG-gated rest/stress [¹³N]NH₃ PET/CT scans from forty patients with myocardial ischemia and thirty-nine patients with normal myocardial perfusion were included. The following four reconstructions were performed for each patient scan: without motion correction (NMC), with CF, DDMC, and DDMC & CF. Images were processed with Cedars-Sinai QPET software. Results: End-diastolic volume (EDV) in rest and stress increased significantly using DDMC. End-systolic volume (ESV) increased significantly, while LV ejection fraction (LVEF) decreased significantly using any MC tool, regardless of the phase. Shape index end-systole (SI ES) and shape-index end-diastole (SI ED) increased significantly when using MC, except for SI ED in rest, where DDMC did not cause any difference. Eccentricity index end-systole (ECC ES) in rest and stress increased significantly in patients with normal myocardial perfusion, while it did not differ in ischemic patients after applying MC. Conclusions: MC tools significantly increase ESV values and decrease EF values. The highest effect is observed with the combined use of DDMC & CF. Image quality is greatly improved when using MC, regardless of the method, particularly in patients with the highest myocardial displacement. Full article

Background/Objectives: Freezing of gait (FoG) is a disabling motor manifestation of Parkinson’s disease (PD) associated with impaired neural control of locomotion and increased gait variability. Quantitative characterization of gait kinematics may provide biomechanical insight into FoG-related instability, particularly under different dopaminergic states. Methods: This pilot study evaluated sagittal-plane knee kinematics in healthy individuals (n = 27) and patients with PD. (n = 8) under OFF and ON dopaminergic medication conditions using two-dimensional videogrammetry (Kinovea^®). Knee flexion–extension trajectories were time-normalized to 0–100% of the gait cycle, and group ensemble profiles (mean ± SD) were computed. Results: Phase-specific range of motion (ROM), within-subject variability, and interlimb coordination were quantified. Interlimb coordination was assessed using Pearson’s correlation coefficients (r) and cross-correlation lag analysis computed per subject and summarized statistically across groups. Compared with healthy participants, PD patients in the OFF state exhibited significantly reduced knee ROM during stance and swing (p < 0.05), accompanied by increased kinematic variability and disrupted temporal coordination. Interlimb correlation was significantly lower in PD OFF compared to healthy gait groups (p = 0.010), with larger temporal lags, indicating impaired bilateral synchronization. Following medication intake (ON state), knee excursion increased and interlimb coordination partially improved; however, correlation values and timing symmetry did not fully normalize to healthy levels. Conclusions: These findings demonstrate that sagittal-plane knee kinematics and interlimb coordination metrics derived from low-cost 2D videogrammetry are sensitive to the dopaminergic state and reveal persistent neuromotor deficits in PD. The proposed framework provides an interpretable and accessible approach for characterizing gait organization in Parkinson’s disease and supports future integration with clinical assessment and longitudinal monitoring. Full article

Hollow hydrogels are promising for flexible electronics and bioengineering, yet their fabrication is limited by sacrificial templates, specialized equipment, and complex engineering processes. Herein, a facile wet-spinning strategy is developed to fabricate sodium alginate (SA) hollow hydrogels. Extruding SA/CaCO₃ precursor suspension into an acidic coagulation bath induces simultaneous ionic cross-linking and in situ CO₂ generation, driving the self-formation of hollow tubular architectures with tunable morphologies, mechanical performance, macroscopic architecture, and functional properties. Moreover, the introduction of secondary cross-linking enhances the SA hydrogels’ water retention and resistance to freezing conditions. Utilizing their intrinsic ionic conductivity, the hollow hydrogels demonstrate outstanding sensing performance, enabling reliable detection of both large-amplitude limb motions and subtle muscle activity in the human body. Furthermore, hollow hydrogel tubes with diverse geometries can be readily fabricated by simply modifying the spinning mold, thereby broadening their potential applications. In vitro cytotoxicity assessments further confirm that the SA hollow hydrogels exhibit excellent biocompatibility with minimal cytotoxicity, satisfying the fundamental criteria for bioengineering applications. The combination of a simple yet controllable fabrication strategy with the intrinsic multifunctionality of the SA hollow tubes confers substantial potential for their deployment in bioengineering and flexible electronic applications. Full article

Understanding the motion parameters of floating ice is very important for characterizing the ice water dynamics of rivers during freezing periods. Due to the low spatiotemporal resolution of satellite images, limited observation range of unmanned aerial vehicles, and deformation of shore-based camera images, it is difficult to simultaneously quantify the translational and rotational motion characteristics of floating ice and long-distance transportation. This study used the unmanned aerial vehicle GPS joint observation method to observe and obtain various motion parameters such as local translation, rotation, and long-distance transportation in the curved section of the upper reaches of the Yellow River and the straight section of the middle reaches of the Yellow River during the winter of 2024–2025 under conditions of ice density of 50–90%. The velocity field obtained by the drone shows an average ice velocity of 1.27 m/s at the bend and 1.18 m/s in the straight section, with lateral velocity gradients of −0.245 to 0.050 s⁻¹ and −0.141 to 0.222 s⁻¹, respectively. The angular velocity of a single floating ice block is 0.008–0.016 rad/s at bends and 0.010–0.036 rad/s in straight sections. The angular velocity is positively correlated with the local shear strength, and the rotation direction is consistent with the sign of the velocity gradient. GPS tracking provides long-distance transportation trajectories, and the average difference between the speeds obtained by GPS and drones is 0.10 m/s, confirming the reliability of speed estimation based on drones. These results indicate that integrated unmanned aerial vehicle GPS observation can quantitatively characterize local floating ice movement and long-distance floating ice transport behavior, providing on-site parameters for river ice water dynamics research and hazard assessment, and has the potential to be applied to rivers in other cold regions. Full article

Natural waves are widely used in seismology and seismic exploration as tools for nondestructive testing of the surface layer. The study examines longitudinal and transverse vibrations of a polymer pipeline transporting petroleum products, which is modeled as a viscoelastic cylindrical shell filled with a viscous fluid. This work examines the longitudinal–transverse vibrations of a viscoelastic cylindrical shell filled with a viscous fluid, considering the viscous properties of both the fluid and the cylindrical shell during longitudinal–transverse oscillations. The differential equations governing the longitudinal–transverse vibrations of a cylindrical shell in contact with a viscous fluid are derived based on thin-shell equations satisfying the Kirchhoff–Love hypotheses, while the motion of the viscous fluid obeys the Navier–Stokes equations. The viscoelastic properties of the shell are described using the Boltzmann–Volterra hereditary integral. After applying the “freezing method” to the system of integro-differential equations, we obtain ordinary differential equations with complex coefficients, which are subsequently solved by the method of separation of variables and Godunov’s orthogonal sweep combined with Müller’s and Gauss’s methods in complex arithmetic. It is established that for small viscosity, the frequencies of both modes are close to each other in the low-frequency region, while at high frequencies, the phase velocity of the first mode tends toward the velocity of the dry shell. Full article

The blast-wave model with Boltzmann–Gibbs statistics is used to examine the transverse momentum spectra of ${K\ast }^0$ mesons generated at the Relativistic High-Energy Collider (RHIC) Beam Energies with mid-rapidity ($\left|y\right|<1$) in symmetric $Au-Au$ collisions. There is a clear correlation between the extracted kinetic freeze-out temperature ($T_0$) and transverse flow velocity (${\beta }_T$) in various collision centralities and center-of-mass energies ($\sqrt{s_{NN}}$). Since a larger initial energy density delays freeze-out and a shorter system lifetime limits cooling, $T_0$ is directly proportional to both $\sqrt{s_{NN}}$ and peripheral collisions. On the other hand, ${\beta }_T$ drops in peripheral symmetric collisions due to weaker collective expansion, while it rises with $\sqrt{s_{NN}}$ because of larger pressure gradients. The concurrence between the thermal and collective energy components in the expanding fireball is reflected in the obvious anti-correlation between $T_0$ and ${\beta }_T$. These findings support hydrodynamic predictions and offer important new information about QGP’s freeze-out behavior. Full article

The impact-freezing phenomenon of supercooled saline droplets on cold surfaces poses a serious threat to the operational stability and structural integrity of offshore wind turbines. Compared to freshwater droplets, numerical models for analyzing the impact-freezing behavior of saline droplets typically involve complex physical mechanisms, resulting in high computational costs. This study employs a simplified two-dimensional axisymmetric numerical model that integrates the Volume of Fluid (VOF) method with the enthalpy–porosity approach, enabling rapid analysis of the saline droplet impact-freezing process under marine environmental conditions. The model is validated by comparing the spreading factor curve of saline droplets with a salinity of 35‰ against existing experimental data. Results show that the salinity corresponding to the peak relative deviation shifts with varying impact parameters, depending on the competition between impact dynamics and solidification. Furthermore, the maximum spreading factor decreases with increasing supercooling degree and contact angle but increases with higher Weber number. These findings provide useful correction parameters for improving existing droplet motion and icing prediction models. Full article

Parkinson’s disease (PD) presents an association of motor and non-motor impairments that impact the independence and quality of life of individuals. Rehabilitation programs must address multiple domains, simultaneously maintaining patients’ adherence and the implications of the disease. Immersive virtual-reality-based rehabilitation (IVRBR) is a promising alternative tool, or can be used in conjunction with traditional or passive programs, using interactive tasks in valid environments with specific training programs adapted to each individual’s needs. This narrative review synthesizes the medical literature published in the last decade from PubMed, Scopus, and Web of Science, on the effectiveness, limitations, and implementations of IVRBR in PD patients. Evidence from RTCs and non-RTCs suggests that IVRBR can improve balance, motor learning, and dual task performance. At the same time, the evidence suggests that it can improve cognitive and emotional status. The integration of objective assessment tools (motion and posture analyses, wearable sensors, center of pressures and machine learning models capable of predicting freezing gait-FoG) enhances clinical and individualized rehabilitation programs. However, the evidence base remains limited, with a small sample size, heterogeneity in measured outcomes, and short follow-up duration. In general, reported adverse reactions were minor, but required standardized reporting patterns. Implementation is challenging due to the equipment cost and varying technological demands, but also due to patient selection and training of the medical personnel. IVRBR is a feasible and engaging alternative or can form part of an individualized rehabilitation program in PD patients; however, future large RTCs, long-term follow-up with standardized protocols, cost-effectiveness analyses, and integration of predictive modeling are essential for its broader clinical usage. Full article

Wearable conductive hydrogel sensors, which are highly convenient, have attracted attention for their great potential in human motion monitoring and smart healthcare. However, the self−adhesive properties, sensing performance, and stability of traditional hydrogels are not ideal, which seriously hinders their use in monitoring and diagnosing joints throughout the human body. Here, CaCl₂ is used to crosslink PVA to improve its self−adhesive properties, and it is then combined with a CNT conductive network. Next, a cyclic freeze–thaw strategy is utilized to fabricate a wearable PVA−Ca−CNT hydrogel with excellent self-adhesive properties and stability. PVA−Ca−CNT hydrogels can adhere to various substrates, with a maximum self-adhesion strength of 398 kPa and a unit adhesion energy of as high as 305 μJ cm⁻². Furthermore, the CNT three−dimensional network enhances the tensile strength to 110 kPa, with almost no hysteresis. Based on resistance changes, PVA−Ca−CNT hydrogel exhibits a sensitivity of up to 11.11 as a strain sensor as well as a response to strain stimuli within 180 ms. When PVA−Ca−CNT hydrogel is adhered to the surface of human skin, it operates as a sensor for monitoring human movement. Not only can it accurately monitor the movement positions of major joints in the human body, it can also accurately identify tiny movements of the fingers and be used as a finger Morse code output device, which demonstrates the enormous potential of human motion monitoring systems based on self−adhesive hydrogel sensors in practical applications. Full article

The application of hydrogels in flexible sensing has received increasing attention, but the simultaneous preparation of hydrogels with good structural stability, strain sensing sensitivity, freezing resistance, and drying resistance remains a challenge. Based on this, a GG-nanocellulose/sodium alginate/polyacrylamide composite hydrogel with a hierarchical network structure was constructed by one-step synthesis by incorporating graphene oxide (GO) and glycerol into the hydrogel. The hydrogel remained structurally intact after 100 compression cycles. In addition, the hydrogel was dried at 30 °C for 24 h. The mass retention rate was 48%, the melting peak was as low as −13.87 °C, and the hydrogel remained flexible and stable at low temperatures. GO modulated the network structure arrangement of the hydrogel through various mechanisms, thereby conferring to the hydrogel an excellent sensing performance, with a sensitivity (GF) of 2.21. In conclusion, this hierarchical network hydrogel has good drying, freezing, and sensing properties, which provides a new viable strategy for monitoring motion signals. Moreover, the hydrogel is predicted to function as a dressing, thereby facilitating the absorption of heat from the skin’s surface, with the aim of alleviating the discomfort associated with joint and muscle injuries caused by strenuous exercise. Full article

Controversial number of phases in debris-flow masses involves almost all areas of debris-flow research. In this study, we experimentally investigated the number of phases in fully developed debris flows using six sediments with three maximum diameters of up to 30 mm from two representative debris-flow deposits in China. Fluid escape tests, displacement experiments, relative motion experiments, and rheometrical tests were conducted using 12 slurries prepared with the sediments. The results from four types of experiments show that debris flows are close to one-phase flow and far from two-phase flow. Under both gravity and artificial hydraulic and mechanical forcing, no relative motion of water or fluid composed of water and fine-grained particles and solids occurs in both the experimental flows and static slurries. This suggests that the water and solids in debris flows move together as a single fluid, and are deposited by “freezing”. The rheological behavior of the experimental debris flows is similar to that of Bingham materials. This indicates that debris flows may be approximated as continuous, homogeneous, isotropic fluids. In conclusion, debris flows behave more like monophasic flow, are far from biphasic flow, and should be treated as one- rather than as two-phase flow. Full article