To investigate the impact of digital literacy on the health of older adults, based on the four-wave micropanel data from the China Family Panel Studies, a digital literacy indicator system was constructed using the factor analysis method. The health of older adults was characterized from the perspectives of overall health levels and internal health inequalities among older adults, and the theoretical mechanism was empirically examined through fixed-effects regression, threshold, and moderating-effects models. Policy recommendations are proposed to accelerate the construction of a digital literacy cultivation system for the elderly, promote digitally empowered public health services, and encourage age-appropriate upgrading of digital health facilities. The results show that for every 1-unit increase in digital literacy, the overall self-assessed health level of the elderly increases by approximately 0.052 units on average, and the health relative deprivation index, which reflects health inequalities of older adults, decreased by about 0.013 units on average. There was heterogeneity in the effect of digital literacy on the health of the elderly, which was more significant among rural-dwelling elderly people, those aged more than 65 years, and females. The mechanism analysis shows that the variables reflecting medical experience and health management awareness play a moderating role in channels through which digital literacy affects older adults’ health.

To tackle the path planning problem, this study introduced a novel algorithm called two-stage parameter adjustment-based differential evolution (TPADE). This algorithm draws inspiration from group behavior to implement a two-stage scaling factor variation strategy. In the initial phase, it adapts according to environmental complexity. In the following phase, it combines individual and global experiences to fine-tune the orientation factor, effectively improving its global search capability. Furthermore, this study developed a new population update method, ensuring that well-adapted individuals are retained, which enhances population diversity. In benchmark function tests across different dimensions, the proposed algorithm consistently demonstrates superior convergence accuracy and speed. This study also tested the TPADE algorithm in path planning simulations. The experimental results reveal that the TPADE algorithm outperforms existing algorithms by achieving path lengths of 28.527 138 and 31.963 990 in simple and complex map environments, respectively. These findings indicate that the proposed algorithm is more adaptive and efficient in path planning.

This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations, aiming to enhance rail transit operational efficiency and inform station planning and development. Data from 159 metro stations in Nanjing, collected over a 14-d period, were analyzed to identify changes in weekday and weekend ridership patterns. The analysis included explanatory variables grouped into three categories: urban spatial variables, socioeconomic variables, and transit service variables. A geographically and temporally weighted regression (GTWR) model was developed, and its performance was compared with that of ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment. In addition, the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions, revealing distinct patterns. Notably, the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays. These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.

By analyzing the bus operation environment and accounting for prediction uncertainties, a bus arrival interval prediction model was developed utilizing a gated recurrent unit (GRU) neural network. To reduce the impact of irrelevant data and boost prediction accuracy, an attention mechanism was integrated into the point model to concentrate on important input sequence information. Based on the point predictions, the lower upper bound estimation (LUBE) method was used, providing a range for the bus interval times predicted by the model. The model was validated using data from 169 bus routes in Nanchang, Jiangxi Province. The results indicated that the attention-GRU model outperformed neural network, long short-term memory and GRU models. Compared with the Bootstrap method, the LUBE method has a narrower average interval width. The coverage width-based criterion (CWC) was reduced by 8.1%, 2.2%, and 5.7% at confidence levels of 85%, 90%, and 95%, respectively, during the off-peak period, and by 23.2%, 26.9%, and 27.3% at confidence levels of 85%, 90%, and 95%, respectively, during the peak period. Therefore, it can accurately describe the fluctuation range in bus arrival times with higher accuracy and stability.

To investigate the distribution characteristics and influencing factors of bicycle detour behavior, this study accurately identified detour behavior using global positioning system (GPS) track data from shared bicycles. Factors such as travel time, road conditions, public transportation facilities, and land use types were considered in constructing a detour behavior influence model based on the CatBoost machine learning algorithm. The interpretability of the machine learning framework was enhanced via Shapley additive explanations (SHAP), enabling an analysis of the impact of each factor on detour behavior. The results indicated that the CatBoost model effectively recognized detour behavior with high accuracy. The frequency of detour behavior increased with higher road levels, greater distances to crossing facilities, wider bike lanes, and an increased number of bus stops, subway stations, and leisure and entertainment facilities, while it decreased with a higher number of office commuting facilities. In addition, detour behavior was more prevalent on weekends, during off-peak hours, and under conditions involving physical central lane separation and physical bike lane separation. These findings offer a novel approach for identifying bicycle riding behaviors and analyzing their influencing factors, providing effective technical support for non-motorized traffic management and infrastructure optimization.

Shaking table tests are widely used to evaluate seismic effects on railway structures, but accurately measuring rail displacement remains a significant challenge owing to the nonlinear characteristics of large displacements, ambient noise interference, and limitations in displacement meter installation. In this paper, a novel method that integrates the Kanade-Lucas-Tomasi (KLT) feature tracker with an extended Kalman filter (EKF) is presented for measuring rail displacement during shaking table tests. The method employs KLT feature tracker and a random sample consensus algorithm to extract and track key feature points, while EKF optimally estimates dynamic states by accounting for system noise and observation errors. Shaking table test results demonstrate that the proposed method achieves an acceleration root mean square error of 0.300 m/s² and a correlation with accelerometer data exceeding 99.7%, significantly outperforming the original KLT approach. This innovative method provides a more efficient and reliable solution for measuring rail displacement under large nonlinear vibrations.

This study explores the use of the Global Navigation Satellite System (GNSS) precise point positioning (PPP) technology to determine the natural vibration periods of towering structures through simulations and field testing. During the simulation phase, a GNSS receiver captured vibration waveforms generated by a single-axis motion simulator based on preset signal parameters, analyzing how different satellite system configurations affect the efficiency of extracting vibration parameters. Subsequently, field tests were conducted on a high-rise steel single-tube tower. The results indicate that in the simulation environment, no matter the PPP positioning data under single GPS or multisystem combination, the vibration frequency of single-axis motion simulator can be accurately extracted after frequency domain analysis, with multisystem setups providing more precise amplitude parameters. In the field test, the natural vibration periods of the main vibration modes of high-rise steel single-tube tower measured by PPP technology closely match the results of the first two modes derived from finite element analysis. The first mode period calculated by the empirical formula is approximately 6% higher than those determined through finite element analysis and PPP. This study demonstrates the potential of PPP for structural vibration analysis, offering significant benefits for assessing dynamic responses and monitoring the health of towering structures.

A buckling-restrained steel plate shear wall (BRSPSW) structure with butterfly-shaped links on the lateral sides is introduced to improve the cooperative performance between the BRSPSW and the boundary frames.A one-span two-story concrete-filled steel tube (CFT) column frame specimen equipped with lateral-side butterfly-shaped linked BRSPSWs (LBL-BRSPSWs) is evaluated under low-cycle reversed loading.A finite element (FE) model is developed and validated based on the test results.This FE model accurately simulates the failure modes and load-displacement curves.Parametric analyses are conducted on the butterfly-shaped links.The results show that the interactions between the CFT column frame and LBL-BRSPSWs are significantly influenced by the width ratio of the butterfly-shaped links, while the taper ratio and aspect ratio have relatively minor influences.Compared with traditional steel shear walls with four-sided connections, LBL-BRSPSWs reduce the additional axial forces and bending moments in the frame columns by 28% to 73% and 17% to 87%, respectively, with only a 9% to 30% decrease in the lateral resistance.The experimental and parametric analysis results indicate that setting butterfly-shaped links on the lateral sides of BRSPSWs can significantly enhance their cooperative performance with the boundary frame.The butterfly-shaped link width ratio has a linear relationship with the lateral-resistance performance of the specimens and the additional internal forces in the frame columns.To ensure that LBL-BRSPSW fails prior to the column frames, the link width ratio should be optimized.

Transmission towers, serving as the support structure of transmission lines, are significant for the functionality of an electric transmission system. Bolt joint loosening is one of the critical factors that can affect the safety and stability of transmission towers. In this study, the effects of bolt joint loosening on the dynamic characteristics of a 220-kV angle steel transmission tower are the main topic of concern. First, the mechanical properties of typical joints subjected to different degrees of bolt loosening are studied by finite solid-element simulation, based on which a finite hybrid-element modeling method is developed for a tower structure suffering varying loose degrees in the joints. Taking a 220-kV angle steel transmission tower as the object, the influence of the position and degree of loosening on the tower’s natural frequencies and mode shapes are simulated and discussed. The results demonstrate that the main-member splice joint and the main diagonal-horizontal member gusset plate joint account for the dominant impact on the dynamic characteristics of the tower. In addition, the dominant joint shifts from the main-member splice joint to the main diagonal-horizontal member gusset plate joint as the considered modal order increases. In the case of double joints loosening simultaneously, the loosening of nondominant joints has nonnegligible effects on the tower as well.

To investigate the effects of the spraying process and different fibers on the mechanical properties and failure patterns of ultrahigh performance concrete (UHPC), three types of fibers were used. These fibers were formed using both spraying and molding methods. Uniaxial compression tests were conducted, and two nondestructive monitoring techniques, acoustic emission (AE) and digital image correlation, were employed to monitor the uniaxial compression tests. The results indicated that the compressive strength of UHPC with single steel fibers and hybrid fibers increased by about 19% and 14% compared with those of UHPC with polyoxymethylene fibers. In comparison with molded UHPC, sprayed UHPC showed a slight improvement in compressive strength. Specimens containing steel fibers exhibited better post-cracking ductility, whereas those with only polyoxymethylene fibers displayed a certain degree of brittle failure. In sprayed UHPC, the onset of significant internal damage was delayed, which was related to the redistribution of internal fibers. The failure of UHPC was characterized by primary tensile cracks, supplemented by shear cracks. The spraying process can better restrict the development of tensile cracks in UHPC. Sprayed UHPC typically exhibited multiple crack developments leading to failure, whereas molded UHPC generally failed in the form of a single main crack penetrating the specimen. The addition of steel fibers delayed the occurrence of local stress concentration zones, aligning well with AE monitoring data.

To analyze the band gap characteristics of phononic crystals, a two-dimensional phononic crystal plate model with an elastic foundation was first established. The plane wave expansion method was used to compute the dispersion curves of this phononic crystal model, and the results were compared with those from the finite element method to verify their accuracy. Subsequently, a parameter study explored the effects of the elastic foundation coefficient and coverage ratio on the band gap. The results indicate that as the coverage ratio of the elastic foundation increases, the band gap significantly expands, reaching its maximum value at 100% coverage. Additionally, as the elastic foundation stiffness increases, the band gap gradually widens and converges toward fixed boundary conditions. The study also investigated the band gap of phononic crystal plates with defects, finding that the vibrational energy concentrates at the defect unit cell. Furthermore, the defect band frequency can be effectively modulated by adjusting the coefficient of the elastic foundation, providing a theoretical basis for achieving efficient energy conversion.

The traditional detailed model of the dual active bridge (DAB) power electronic transformer is characterized by the high dimensionality of its nodal admittance matrix and the need for a small simulation step size, which limits the speed of electromagnetic transient (EMT) simulations. To overcome these limitations, a novel EMT equivalent model based on a generalized branch-cutting method is proposed to improve the simulation efficiency of the DAB model. The DAB topology is first decomposed into two sub-networks through branch-cutting and node-tearing methods without the introduction of a one-time-step delay. Subsequently, the internal nodes of each sub-network are eliminated through network simplification, and the equivalent circuit for the port cascade module is derived. The model is then validated through simulations across various operating conditions. The results demonstrate that the model avoids the loss of accuracy associated with one-time-step delay, the relative error across different conditions remains below 1%, and the simulation acceleration ratios improve as the number of modules increases.

A novel bidirectional tuned rolling mass damper (Bi-TRMD) device is proposed, and its dynamic characteristics and vibration reduction performance are investigated. The device achieves the performance goal of bidirectional vibration reduction for a tuned rolling mass damper with a single concave structure. First, the Bi-TRMD device is introduced, and its three-dimensional (3D) mechanical model is established. The motion equations of the model are derived using the Gibbs-Appell equation, and a trajectory prediction method for the sphere and structure within the model is developed. This method demonstrates that the rolling motion of the sphere around orthogonal axes is nearly independent within a limited range, enabling the simplification of the 3D model into a two-dimensional (2D) model. The accuracy of this simplification is validated through case analysis. The vibration reduction parameters are optimized using the 2D model and Den Hartog theory, leading to the derivation of mathematical expressions for the optimal frequency ratio and damping ratio. Subsequently, the bidirectional vibration reduction performance of the Bi-TRMD is analyzed. The results show that under white noise excitation, the Bi-TRMD achieves a bidirectional peak acceleration reduction rate that is 9.92% and 7.79% higher than that of translational tuned mass dampers (TMD) with the same mass. These findings demonstrate that the proposed Bi-TRMD effectively achieves two-directional vibration reduction with a single concave structure, offering superior vibration reduction performance.

The deployment of reconfigurable intelligent surfaces (RISs) can enhance the coverage ability of millimeter wave (mmWave) communication systems.However, the typical strong line-of-sight (LoS) far-field propagation between a base station (BS) and an RIS reduces channel rank, thus affecting multiuser spatial multiplexing.To address this issue, we propose an RIS subarray-assisted mmWave multiuser transmission scheme.To increase channel rank, RIS is divided into multiple subarrays with adjustable spacing, and the channel is modeled using a hybrid spherical- and planar-wave model.To minimize interuser interference, the RIS subarrays are deployed in the discrete Fourier transform (DFT) direction of the BS antenna array.To maximize signal efficiency, the BS precoder, the RIS reflection coefficients, and the user’s combiner are jointly designed.Numerical simulations were conducted to verify the effectiveness of the proposed RIS subarray deployment strategy and the performance of the wireless transmission scheme.In a four-user equipment (UE) communication scenario in the mmWave band, the effective rank of the BS-RIS channel approaches full rank, and the spectral efficiency of each UE is improved by at least 3 bit/(s·Hz).

To improve the seismic performance of unreinforced masonry (URM) buildings in the Himalayan regions, including Western China, India, Nepal, and Pakistan, a low-cost bonded scrap tire rubber isolator (BSTRI) is proposed, and a series of vertical compression and horizontal shear tests are conducted. Incremental dynamic analyses are conducted for five types of BSTRI-supported URM buildings subjected to 22 far-field and 28 near-field earthquake ground motions. The resulting fragility curves and probability of damage curves are presented and utilized to evaluate the damage states of these buildings. The results show that in the base-isolated (BI) URM buildings under seismic ground motion at a peak ground acceleration (PGA) of 1.102g, the probability of exceeding the collapse prevention threshold is less than 25% under far-field earthquake ground motions and 31% under near-field earthquake ground motions. Furthermore, the maximum average vulnerability index for the BI-URM buildings, which are designed to withstand rare earthquakes with 9° (PGA = 0.632g), is 40.87% for far-field earthquake ground motions and 41.83% for near-field earthquake ground motions. Therefore, the adoption of BSTRIs can significantly reduce the collapse probability of URM buildings.