What's new

When high-speed railway lines are located close to transmission corridors, train-induced vibration may affect the dynamic response of transmission towers. To investigate the event-level vibration response characteristics of a transmission tower adjacent to a high-speed railway under short-term field monitoring conditions, this study takes a transmission tower in Shenzhen, China, as the research object. Train passage events were constructed and analyzed using horizontal acceleration, inclination, background wind speed, and train timetable data. First, train events and single- or double-train conditions were identified according to the timetable. Then, the east-west and north-south acceleration components were used to calculate the resultant horizontal acceleration, and the peak response time within each recorded event minute was determined using a 1 s moving root-mean-square method. Finally, a 20 s event window, including 10 s before and 10 s after the peak response time, was established to extract event-level features related to acceleration, inclination, wind speed, and train type. The results show that 226 actual train events were obtained from November 6 to November 11, 2025, of which 170 non-boundary events were used as the main analysis samples. The maximum RMS response and peak acceleration of double-train events were generally higher than those of single-train events, although the differences were limited. The acceleration response in the higher wind-speed group was also generally greater than that in the lower wind-speed group. However, because the wind-speed groups were partly coupled with the monitoring dates, this result should be interpreted as a tendency rather than a causal conclusion. Furthermore, response state classification was conducted based on the event-level features. The random forest model achieved relatively good identification performance, with an F1-score of 0.788 and a ROC-AUC of 0.854. Feature importance analysis indicated that maximum inclination variation, mean wind speed, and peak offset time made relatively large contributions to response state identification. The results provide a reference for short-term monitoring data analysis and event-level response assessment of transmission towers adjacent to high-speed railways.

To address the difficulty of fully characterizing both local impacts and time-frequency information in bearing vibration signals from automated logistics sorting equipment using a single representation, this study develops a channel-attention-based time-frequency dual-branch fault diagnosis model. Each vibration window is represented both as a normalized one-dimensional time-series input and a two-dimensional continuous wavelet transform (CWT) time-frequency map. A temporal convolutional network (TCN) branch extracts local waveform and temporal variation features, while a multi-scale convolutional neural network (CNN) branch captures time-frequency textures at different receptive fields. Channel attention is introduced separately into the two branches to reweight informative features, and the two representations are concatenated for classification of normal, inner-race, outer-race, and rolling-element conditions. Experiments are conducted using bearing vibration records collected at 1200 r/min, with non-overlapping time windows used to construct training, validation, and held-out evaluation subsets. The proposed model achieves the highest mean accuracy and Macro-F1 among the baselines considered, and component ablation further supports the combined use of the dual-branch architecture, channel attention, and multi-scale feature extraction. The method provides an experimentally supported reference for bearing condition monitoring in warehouse logistics equipment.

Paralysis is defined as the complete loss of mobility and inability to perform movement in a specific area of body. In facial paralysis, muscles exhibit lost of mobility or muscular hypotonia, which may be accompanied by decreased salivar flow and impairment of the perioral jugal muscles. The objective of this study was to diagnose oral health status of patients using Decayed, Missing and filled teeth index, and to evaluate whether there is an association between the side of facial paralysis and a higher rate of plaque dental. We compared the paralysis side with the healthy side. Patients from the Facial Nerve Sector of the Otology and Otoneurology Disciplines at the Federal University of São Paulo were screened. Based on the inclusion and exclusion criteria, 15 patients were analyzed. Dental plaque was evaluated using the O’Leary index, and overall oral health was assessed via the DMFT index. The majority of the sample was female (53.3 %), with a traumatic etiology (60.0 %), right-sided facial paralysis (53.3 %), and grade V severity (53.3 %). The mean age was 37 years. The average O'Leary index score was 16.1 %, ranging from 0 % (lowest) to 28.6 % (highest). When analyzing the sides separately, the right side showed a slightly higher average plaque accumulation (16.8 %) compared to the left side (15.2 %). The mean DMFT index value was 13.6. The correlation between the side with greater plaque accumulation and the side of facial paralysis resulted in a poor Kappa concordance coefficient of 0.071. The association test between the side with a higher O'Leary index and the side of facial paralysis was not statistically significant (p> 0.999), indicating that these two variables are not associated.In conclusion, dental plaque accumulation is independent of the side of facial paralysis presented by the patient.

This study develops an impact-acoustic framework for classifying predefined surface-damage states on steam-turbine blades, identifying one of three damage regions, and estimating class-dependent severity parameters. Impact signals were recorded for 5 s at 22,050 Hz under controlled impact and microphone angles. After event screening, each signal was converted into a 13-coefficient W-MFCC map that combines continuous-wavelet time-frequency localization, Mel-scale subband mapping, and cepstral compression. A hybrid ResNet-50-Transformer-PANet-CMTL network was designed to extract hierarchical local features, model long-range dependencies, fuse multi-scale information, and produce conditional multi-task outputs. The dataset contained 1,200 training samples and 300 validation samples covering crack, crack-erosion, and crack-abrasion conditions in Areas 1-3. On the reported validation split, W-MFCC correctly classified 296 of 300 samples (98.67 %), compared with 89.33 % for MFCC and 87.33 % for wavelet input, and its loss curves showed more stable convergence. The full multi-scale configuration also exhibited smoother training behavior than the ResNet-50 + Transformer baseline. These findings demonstrate the feasibility of combining W-MFCC representation learning with multi-scale conditional prediction for controlled turbine-blade condition assessment.

This paper investigates the random response of hysteretic nonlinear oscillators described by the Volterra integral model, which captures material memory effects via a convolution kernel under Gaussian white noise excitation. The Gaussian basis function (GBF) approximation technique is utilized to estimate the system's steady-state probability density function (PDF). The approximately stationary probability density function is represented as a weighted sum of Gaussian basis functions in this method. The optimal weighting coefficients are determined by minimizing the residual of the stationary Fokker-Planck-Kolmogorov (FPK) equation using the least squares method with Lagrange multipliers, yielding the steady-state joint probability density function. The computed results show excellent agreement with Monte Carlo simulations (MCS), confirming the accuracy and reliability of the Gaussian basis function method and demonstrating the influences of various parameters on the hysteresis loop and the system response.

Traumatic peripheral facial paralysis is a disabling condition that may compromise facial expression, mastication, swallowing, speech, and quality of life. Although several rehabilitation approaches have been proposed, evidence regarding the long-term outcomes of oral proprioceptive stimulation remains limited. A 68-year-old man developed traumatic peripheral facial paralysis following surgery for a cerebellopontine angle tumor in 2003. After several unsuccessful rehabilitation attempts, a hyperboloid-based oral proprioceptive rehabilitation protocol was initiated in 2010. The patient performed intraoral exercises three times daily and underwent clinical follow-up for 12 years. Clinical improvement was first documented approximately 45 days after treatment initiation, with restoration of lip competence. Subsequent improvements included reduced drooling and liquid leakage, better mastication and oral bolus control, improved speech intelligibility and facial symmetry, and increased social participation. Functional gains were maintained throughout the long-term follow-up period with individualized maintenance exercises. This case describes sustained functional improvements observed during long-term follow-up after rehabilitation using a hyperboloid-based oral proprioceptive protocol. Although stimulation of the stomatognathic system may have contributed to the observed functional recovery, treatment effectiveness cannot be established from a single case. Further prospective studies using standardized outcome measures are needed to investigate the potential role of this therapeutic approach.

This research investigates the dynamic stress–strain behavior of a railway bridge beam superstructure subjected to moving train loads using advanced computational modeling. The study employs MIDAS Civil software to develop a comprehensive three-dimensional finite element model of a typical railway bridge superstructure, incorporating realistic boundary conditions, material properties, and geometric configurations. The analysis examines the temporal variation of stresses, displacements, and internal forces as multiple train axles traverse the bridge at various operational speeds. The investigation reveals critical zones experiencing maximum dynamic amplification factors, which significantly exceed those predicted by static analysis methodologies. Dynamic load allowance coefficients are calculated for different train speeds, demonstrating a nonlinear relationship between velocity and structural response amplification. The model accounts for complex phenomena including moving load effects, inertial forces, and structural damping characteristics. Results indicate that dynamic effects become particularly pronounced at specific resonance frequencies, where vertical deflections and bending moments reach peak magnitudes. The findings provide essential insights for bridge design optimization, maintenance planning, and safety assessment protocols. This comprehensive dynamic analysis framework enables engineers to accurately predict structural behavior under realistic operational conditions, ensuring adequate service life and structural integrity of railway bridge infrastructure systems while maintaining required safety margins for contemporary high-speed rail applications.

To investigate the dynamic impact response of frozen rocks, this study performed dynamic compression tests on yellow sandstone, white sandstone, and granite under various low temperatures and impact intensities using a modified split Hopkinson pressure bar (SHPB) system, and analyzed the strength, deformation, and energy dissipation characteristics of the three rock types. The results show that low temperature significantly enhances the dynamic compressive strength of the two sandstones, with yellow sandstone being the most strongly affected by temperature. The strength of the specimens exhibits a strain rate effect. The peak stress of yellow sandstone shows a linear relationship with impact pressure and is most significantly affected by temperature, while that of white sandstone follows a quadratic growth pattern, and that of granite also shows a linear relationship. Under impact loading, the three rocks exhibit differences in energy distribution. For yellow sandstone, the proportion of reflected energy is the highest, whereas that of transmitted is energy the lowest, and the dissipated energy increases with decreasing temperature. For white sandstone, both the proportions of transmitted and dissipated energies increase as temperature decreases, and both reflected and transmitted energies show low-temperature sensitivity. For granite, the proportion of reflected energy is the lowest, energy is mainly transmitted through the specimen, and the influence of temperature is weak. The three rocks have different water absorption capacities. The water-ice phase change caused by low temperature alters the rock structure and increases the wave impedance, leading to different temperature sensitivities in energy distribution under impact loading. The low-temperature strengthening mechanism originates from the filling of pores by ice, intergranular cementation, and microcrack closure caused by differential thermal contraction of minerals. The research findings can provide a theoretical basis and experimental reference for the stability evaluation and protective engineering design of rock masses of different lithologies subjected to dynamic loads in cold regions.