Search Results (6,724)

The detection of bolt preload force is of vital importance for ensuring the structural reliability of equipment under extreme operating conditions. Traditional ultrasonic transducers based on bulk piezoelectric materials suffer from poor long-term coupling stability and high brittleness of the material, which limits their practical applications. In this work, AlN piezoelectric thin films were fabricated by RF magnetron sputtering, and the effects of RF power and target-to-substrate distance on film morphology, crystal structure, and ultrasonic response were investigated. The results show that increasing RF power increased the film thickness and deposition rate, reduced the detected O content on the film surface, and changed the XRD response. The film deposited at 900 W generated ultrasonic longitudinal wave echoes with a relatively high signal amplitude among the tested RF powers. Among the tested target-to-substrate distances, the film deposited at 60 mm showed a relatively higher deposition rate and generated an ultrasonic longitudinal wave echo with a relatively higher amplitude. The measured d₃₃ value of this film was approximately 4.8 pC/N. The AlN thin-film ultrasonic transducers prepared under the selected deposition conditions were directly deposited on bolts, and the effects of temperature and axial load were calibrated using the ultrasonic TOF measurement method. There was a linear correlation between the TOF and the temperature (R² > 99.99%), as well as between the TOF and the axial load. These results indicate that the deposited AlN thin-film transducer has potential for bolt preload measurement in wind turbine bolts. Full article

To address the issue of persistent high-magnitude outlier interference affecting long-baseline (LBL) positioning systems in complex marine environments, this paper proposes a kinematic constraint-based Robust Interacting Multiple Model Kalman Filter algorithm. Combined with anchor point initialization and multi-step historical observations, the algorithm constructs a spatial Euclidean distance discriminant criterion. By further incorporating the maximum velocity constraint of the Autonomous Underwater Vehicle (AUV), dynamic decision thresholds are established, and final detection decisions are output to the positioning system. Within the Kalman Filter recursion process, a measurement mask matrix is introduced to instantly isolate measurement outliers, preventing abnormal data from participating in state updates and model probability evolution. Simulation results demonstrate that, compared with standard LBL positioning, conventional single outlier detection, and the conventional maximum correntropy criterion-based Kalman filter (MCC-KF) algorithm, the proposed approach enhances outlier identification and suppression—particularly under consecutive anomaly conditions—thereby improving the positioning accuracy of maneuvering targets in complex underwater scenarios. Full article

To mitigate driving risks from brake failure on long and steep downhill sections, this study designs three deployment schemes for radar–video fusion devices: a baseline scenario with no coverage, a scenario with partial coverage in high-risk areas, and a scenario with full coverage. Corresponding information service strategies are delivered via Human–Machine Interfaces (HMIs), forming an integrated active prevention and control framework from risk perception to preventive action. Driving simulation experiments focusing on the car-following process were conducted to collect vehicle operational data and extract characteristic indicators based on the Wiedemann model. A Generalized Linear Mixed Model was employed to comprehensively examine the effects of HMIs on car-following behavior to identify the optimal active prevention strategy. Results show that drivers exhibit greater caution under the partial coverage scheme, with time headway increasing by 47.63% compared to the scheme with no radar–video fusion devices to ensure safety. Under full coverage conditions, drivers can obtain real-time information about the leading vehicle’s status and the distance between the two vehicles in key risk sections. Drivers choose to follow the leading vehicle, balancing both safety in car-following and efficiency on long and steep downhill sections. As the level of accompanying services improves, drivers engage in self-regulation to avoid rear-end collisions. Particularly under the scheme with full coverage of radar–video fusion devices, the standing distance significantly increases by 219.37% compared to the partial coverage condition. Drivers demonstrate optimal vehicle control capabilities. Furthermore, there is an interaction effect between the accompanying service strategy and drivers’ attributes on car-following behaviors. Under different schemes, more experienced drivers exhibit a certain degree of aggressiveness, providing a basis for the targeted design of information services for different types of drivers. The findings support the deployment and application of risk perception and prevention devices on long and steep downhill sections, which can effectively enhance the comprehensive safety of such special roads in the connected vehicle environment. Full article

Dynamic Wireless Power Transfer (DWPT) is attracting increasing interest as a promising solution to extend the operating range of battery electric vehicles while reducing stationary charging needs. In this study, a DWPT system for Electric Vehicle charging is investigated through a comparative simulation-based case study focused on the Italian A4 highway, a strategic transport corridor characterized by high traffic intensity and long-distance mobility demand. The proposed system is based on a segmented magnetic coupling architecture with planar circular coils installed along the roadway and a vehicle-side pickup coil. Under common roadway, vehicle, and magnetic coupling assumptions, a benchmark Tesla Model 3 Long Range traveling at a constant speed of 90 km/h and characterized by an estimated energy consumption of 0.129 kWh/km is considered. Two compensation solutions are comparatively assessed, namely the Series–Series (SS) topology and the Inductor-Capacitor-Capacitor (LCC) topology. The methodology evaluates the two topologies under the same benchmark conditions in terms of peak power, average transferred power, transferred energy per kilometer, and effect on vehicle State Of Charge (SOC). The SS topology provides a peak power of 22.52 kW, an average power of 12.30 kW, and an energy transfer of 0.14 kWh/km, whereas the LCC topology reaches a peak power of 20.44 kW, an average power of 13.47 kW, and an energy transfer of 0.15 kWh/km. Starting from an initial SOC of 30%, the final SOC after traveling through the usable electrified highway section reaches 37.48% with SS compensation and 44.28% with LCC compensation. The results show that both topologies enable effective dynamic charging, with the LCC solution exhibiting better energy transfer capability and higher operational stability, while the SS topology delivers higher instantaneous power peaks. From a comparative simulation perspective, the study supports the technical feasibility of DWPT deployment in highway environments and provides useful design insights for selecting compensation topologies in dynamic electric vehicle charging applications. Full article

The electrification of long-haul freight transport requires a comprehensive public charging infrastructure along motorways. This study presents a framework combining multi-agent transport simulation (MATSim) with evolutionary bi-objective optimization (NSGA-II) to determine the number and spatial distribution of high-power charging (HPC) points for battery-electric trucks (BETs) on the German motorway network. Beyond infrastructure sizing, the approach also quantifies the impact of BET charging on the duration and distance of long-haul truck trips. The optimization simultaneously addresses the perspectives of two key stakeholders: charge point operators (CPOs), who seek to maximize charger utilization, and logistics operators, who aim to minimize waiting times. The results yield a range of Pareto-optimal configurations balancing the two objectives. A multi-iteration replanning step further lets trucks adapt their routes to experienced waiting times for a more realistic performance assessment, reducing mean waiting times by up to 92%. We evaluate five electrification levels from 1% to 20% across two charging network scenarios with 347 and 779 potential locations, respectively. For the balanced solutions—the knee-point configurations that best reconcile both objectives—at a 10% electrification level, the optimized network reaches a temporal charger utilization of 23% to 32% at mean waiting times of about 1.4 to 1.9 min per charging process. Compared with an internal combustion engine truck (ICET) reference, BET trip durations increase by only 0.9% to 1.3% due to charging detours. Overall, the fast-charging network planned by the German federal government appears sufficient for the HPC demand at electrification levels up to 10% to 15%, whereas additional low-power charging (LPC) infrastructure beyond the planned locations will be needed to cover overnight charging requirements. Full article

In satellite-denied environments such as urban canyons, tunnels, and underground parking facilities, achieving high-precision autonomous positioning for vehicles remains a critical challenge. Although high-precision inertial measurement units (IMUs) can provide accurate dead reckoning, their deployment is limited by cost, size, and power consumption, making low-cost, microelectromechanical systems IMUs (MIMUs) an attractive alternative solution. However, the single MIMU suffers from substantial measurement noise and bias instability, leading to rapid error divergence that cannot sustain long-term autonomous navigation. To address the above issues, this paper proposes an autonomous positioning system based on a wheel-mounted MIMU array (Wheel-AINS). The system adopts a differential layout in which multiple low-cost MIMU chips are installed at the center of each of the left and right rear wheels, forming redundant sensor arrays. By differentially fusing symmetrically mounted chips, common-mode noise and zero bias are effectively canceled while the wheel rotation provides natural rotational modulation. The fused gyroscope outputs and known wheel radius are then used to estimate the vehicle forward speed, replacing traditional odometers. The estimated wheel speed and vehicle kinematic constraints are then integrated within a Kalman filter framework to suppress the error divergence of the inertial navigation system. A dedicated embedded hardware prototype with multi-chip synchronous acquisition and wireless transmission was developed. Three groups of urban road tests with total distances of 0.85 km, 2.14 km, and 2.49 km were conducted. The results indicate that the average position drift rate of the Wheel-AINS is 0.50%, and the average heading RMSE is 12.2°. The closure error of the 2.49 km trajectory is 10.43 m, reduced by approximately 80% compared with a single MIMU. The ablation experiment reveals that the MIMU array fusion module is the primary source of accuracy improvement, reducing the position RMSE from 155.0 m to 10.1 m, while the dual-wheel distance constraint further optimizes the position RMSE to 8.2 m, but increases the heading RMSE from 13.3° to 13.6°. This demonstrates that the proposed method can substantially improve autonomous positioning accuracy while maintaining a notably low system cost, providing a viable technical pathway for long-endurance vehicle navigation in satellite-denied environments. Full article

Climate change is increasingly reshaping species habitat suitability worldwide. Primula L., the largest genus in Primulaceae, comprises 404 species in China (including 296 endemic species) and is characterized by high endemism and numerous rare and endangered taxa. However, global warming has intensified habitat fragmentation and loss, while its distribution patterns and key environmental drivers remain insufficiently understood. We compiled 7647 occurrence records of 404 wild Primula species in China and integrated 60 environmental variables (climatic, topographic, and soil factors). Using the MaxEnt model combined with ArcGIS spatial analysis, we assessed current and future habitat suitability, identified dominant environmental drivers, and quantified conservation gaps under multiple climate scenarios. Species richness is highly concentrated in Sichuan (186 species), Yunnan (177 species), and Xizang (165 species), with the Hengduan Mountains and eastern Himalayas representing the core distribution area and showing clear peripheral differentiation. The optimized MaxEnt model performed well (AUC = 0.858), identifying temperature seasonality (bio4, 39.8%) and elevation (27.1%) as the main limiting factors. The total suitable habitat area is 268.52 × 10⁴ km², with high-suitability areas mainly distributed in the Hengduan Mountains, southeastern Qinghai–Xizang Plateau, and the Central Mountain Range of Taiwan. Under three shared socioeconomic pathway (SSP) scenarios (SSP126, SSP245, and SSP585), suitable habitat shows a persistent decline, most pronounced under SSP585 in the 2090s (−20.73%), accompanied by a 25.86% reduction in low-suitability areas. Localized expansion of high-suitability habitats suggests that the Hengduan Mountains and southeastern Qinghai–Xizang Plateau may act as potential climatic refugia. Habitat loss consistently exceeds habitat gain, while the distribution centroid shifts westward and northwestward, with migration distances increasing under higher-emission scenarios. Conservation gap analysis indicates that 90.01% of high-suitability habitats lie outside the current protected area network, revealing a strong mismatch between biodiversity hotspots and conservation coverage. These findings highlight the urgent need to expand protected areas and establish micro-reserves in key gap regions (southwestern Sichuan, northwestern Yunnan, southeastern Xizang, and southern Gansu), and to integrate climate-driven migration corridors into conservation planning to support long-term alpine plant persistence under climate change. Full article

Drawing on diffusion of innovation theory, this cross-national study examines the association between cultural dimensions and artificial intelligence (AI) capability on a 78-country sample. This cross-country, worldwide approach enables a more comprehensive understanding of differences in cross-national AI capability, providing cultural explanations for a new perspective on the diffusion of novel technologies. Our main findings reveal that individualism demonstrates the most stable positive association across model specifications. Uncertainty avoidance and motivation towards achievement and success are significant in the baseline SEM, but the results become sensitive after adding country-level control variables. Long-term orientation is significant in some OLS models but not in the baseline SEM. Power distance and indulgence are not supported in the baseline SEM. Results suggest that cultural values should be considered alongside economic, infrastructural, and regional conditions when analyzing cross-national differences in AI capability. Our findings provide a contextual perspective for policymakers and managers that are developing strategies for achieving competitive advantage. Considering the turbulence of the business and social environments, we argue that cultural adaptive capabilities are essential for global competitiveness. Full article

This paper presents a comprehensive numerical investigation into the transient thermo-structural response of axial bellows during start-up and shutdown cycles in long-distance heating pipelines. Using ANSYS-based transient thermal–structural coupling finite element analysis under the pure linear elasticity and constant internal pressure, the spatio-temporal evolution mechanisms of temperature fields, axial deformation, and equivalent stress are systematically analyzed. The results demonstrate the highly synchronized evolution between temperature and deformation fields, with maximum axial deformation and equivalent stress consistently concentrated at the convolution root and transition arcs. Under steady-state high-temperature conditions (130 °C), the maximum equivalent stress reaches 332.78 MPa. However, after complete cooling and unloading, minimal residual deformation (≤0.001 mm) and residual stress (8.86 MPa) are observed, satisfying the pressure vessel shakedown criteria and confirming the inherent self-limiting nature of thermal secondary stresses. A specific decoupling phenomenon is revealed during the high-temperature steady-state holding period, where the deformation stabilizes while the stress undergoes secondary redistribution. The comparative analysis of different temperature change rates indicates that the fast start-up/shutdown (0.55 °C/s) induces severe transient temperature gradients, causing a nearly 50% increase in the maximum equivalent stress compared to the slow start-up/shutdown (0.275 °C/s). This study provides theoretical foundations for the service safety assessment of axial bellows and recommends gradual heating/cooling operation strategies (≤0.3 °C/s) to mitigate structural thermal shock risks. Full article

Understanding the advance ticket purchase behavior of air–rail intermodal passengers is essential for travel demand forecasting, schedule coordination optimization, and revenue management. Using actual booking data, this study investigates passengers’ advance purchase time (APT) decisions. A Bayesian network (BN) model integrating expert knowledge and data-driven learning is established, with socioeconomic attributes and ticket characteristics as input variables and APT as the output variable. Based on this BN, group analysis is conducted across four routes of varying distances: Tianjin–Shanghai, Tianjin–Changsha, Tianjin–Guangzhou, and Tianjin–Sanya. The results indicate that socioeconomic and ticket attributes influence advance purchase behavior both directly and indirectly through interactive effects. Inferential analysis reveals that elderly passengers, male travelers, morning departures, and longer-distance trips are associated with earlier ticket purchases. Sensitivity analysis shows that fare, transfer time, and age exert heterogeneous effects across routes. Compared with short- and medium-haul journeys, airfare, rail travel time, and transfer time impose stronger impacts on long-haul intermodal trips. Finally, targeted revenue management strategies are proposed to improve air–rail ticket sales. Full article

Short-term captivity is widely used in experimental studies but may unintentionally alter host-associated microbiomes, potentially confounding biological interpretation of experimental outcomes. Here, we evaluated the effects of 35 days of captivity on the gut microbiome of Fundulus heteroclitus collected from Long Island Sound (Milford, CT, USA) using 16S rRNA gene sequencing. Comparisons between Field Control (FC) and short-term Captive Treatment (CT) groups revealed a marked reduction in microbial diversity under captive conditions. Observed richness decreased approximately five-fold (Field Control: 1026 features; Captive Treatment: 221 features), and Shannon diversity declined from 8.89 to 5.93. Beta diversity analyses based on UniFrac distances demonstrated clear separation between groups, indicating substantial shifts in community composition. Taxonomic profiling revealed reduced community complexity in captive fish, with increased dominance of Proteobacteria and loss of diverse environmental taxa. Predicted enrichment of pathways associated with stress response, altered respiration, and metabolic flexibility in captivity reflects inferred functional potential rather than direct functional activity. Given the use of pooled samples with limited biological replication, these findings should be interpreted as strong community-level patterns rather than population-level inference. Collectively, these results indicate that short-term captivity alters the F. heteroclitus gut microbiome. Full article

Underwater communication is essential for marine research, yet saline environments pose significant challenges as electromagnetic waves suffer from severe attenuation and optical systems face scattering. Consequently, acoustic transmission remains the most practical method for medium- to long-range communication. This study investigates the impact of salinity, transmission frequency, and propagation distance on signal integrity, specifically focusing on the feasibility of using a square-wave carrier with On-Off Keying (OOK) modulation as a simpler, low-cost alternative to traditional sinusoidal frequency-shift keying (FSK). Experiments were conducted in a custom glass tank and analyzed via MATLAB. The results reveal that increased salinity and higher frequencies led to greater signal distortion and attenuation, which complicates reliable binary recovery. However, despite these environmental hurdles, the study demonstrates that square-wave OOK allows for successful binary data recovery over short distances. The findings suggest that simplified modulation schemes could potentially be used for short-range underwater communication in controlled environments, particularly where minimizing system complexity is of concern. Ultimately, the work provides valuable insights into how environmental factors influence acoustic signal integrity, offering a preliminary basis for future development of accessible and efficient underwater communication platforms targeted to shallow water communication. Full article

Background/Objectives: Advanced implant anchorage techniques are increasingly used to manage severe maxillary bone deficiency and to avoid extensive bone augmentation procedures. This case series report aimed to describe the canine bypass anchorage technique and to evaluate the short- to medium-term clinical outcomes and survival of implants placed using this approach. Materials and Methods: Thirteen patients presenting with missing maxillary premolars or posterior segments and insufficient alveolar bone height for conventional axial implant placement were treated using the canine bypass technique. A total of 19 long one-piece implants were inserted palatally to the canine root, engaging distant cortical bone of the nasal cavity and/or palatal alveolar process. Pre- and postoperative cone-beam computed tomography (CBCT) examinations were performed to assess implant positioning and anchorage. Patients were followed up to 3.5 years. Results: The mean follow-up period was 26.1 ± 10.8 months. Nasal cortical anchorage was achieved in 84.2% of implants, and palatal cortical anchorage in 73.7%; both anchorage types were obtained simultaneously in 57.9% of cases. The mean distance between the implant and canine root was 1.27 ± 1.4 mm (range: −1.0 to 4.5 mm), including cases of direct implant–tooth contact and periodontal ligament space transgression. All implants remained functional throughout the observation period, yielding a cumulative survival rate of 100%. Canine pulp vitality was preserved in all non-endodontically treated teeth. Conclusions: Within the limitations of this case series report, the canine bypass anchorage technique appears to be a feasible and minimally invasive treatment option for maxillary rehabilitation with implant-supported restoration in selected patients with severe bone deficiency, potentially allowing avoidance of sinus augmentation procedures. Further prospective studies with larger patient cohorts and longer follow-up periods are required to confirm the long-term safety, predictability, and clinical applicability of this approach. Full article

Introduction: Currently, there is an ongoing debate regarding the benefits of kinematic alignment (KA) versus mechanical alignment (MA) in total knee arthroplasty (TKA). Robotic-assisted TKA has been shown to improve implant positioning and precision of the KA technique, enabling successful kinematic alignment. However, its impact on early postoperative and functional outcomes remains unclear. This study aims to examine how imageless, table-mounted, robotic-assisted KA-TKA compares with conventional MA-TKA. Methods: Registry data of all primary TKAs using ATTUNE™ cruciate-retaining implants (January 2021–December 2024) performed by a single, experienced surgeon in a high-volume arthroplasty center were retrospectively reviewed. A total of 64 patients who underwent robotic-assisted KA-TKA were compared to 39 patients who underwent conventional MA-TKA. The mean age was 70.3 ± 7.71 and 69.3 ± 9.47 in the KA-TKA group and the MA-TKA group, respectively, while the male proportion was 32.8% and 30.7%, respectively. Early postoperative outcomes (static/dynamic pain score, ambulation distance, length of stay) and 6-month functional outcomes (range of motion, Knee Society Score, Oxford Knee Score, SF-36, patient expectation/satisfaction scores) were analyzed. Delta changes in outcome scores and proportion of patients attaining a minimum clinically important difference (MCID) were studied. Results: Robotic-assisted KA-TKA displayed benefits in the majority of the early postoperative outcomes, with significant improvements in ambulation distance (23.3 vs. 14.7 m, p = 0.002) compared to conventional MA-TKA. Both groups showed significant improvements in the majority of the functional outcomes at 6 months. Robotic-assisted KA-TKA also shows significant improvements in selected mental health aspects of SF-36, namely vitality (p = 0.001), mental health (p = 0.048), mental component summary (MCS) (p = 0.004), and a larger proportion attaining SF-36 vitality MCID (p = 0.045). Following false discovery rate correction for multiple comparisons, postoperative ambulation distance, SF-36 vitality, and MCS remained statistically significant between groups. No significant differences in KSS, OKS, and satisfaction/expectation fulfillment were noted. Conclusions: Robotic-assisted KA-TKA demonstrated early rehabilitation and select mental health-related quality of life improvements compared to conventional MA-TKA. Further studies are needed to examine its long-term clinical outcomes. Full article

Deep reinforcement learning (DRL) has shown considerable potential in local path planning for autonomous robots. However, existing DRL methods still suffer from limited training efficiency, poor generalization, and weak sim-to-real transferability in complex environments. To address these issues, this paper proposes a Multi-Level Attention Dueling Double Deep Q-Network (MLA-D3QN) framework, which progressively enhances feature extraction, spatial perception, and modality fusion through three attention levels: rule-based attention for obstacle contour extraction, implicit neural multi-scale spatial attention for environment perception, and bidirectional cross-attention for multi-modal feature alignment. Simulation results show that MLA-D3QN outperforms baseline and comparison methods in terms of convergence speed and average reward. Real-world experiments are conducted on a Scout mini platform with 50 trials in simple task scenarios (sparse obstacles, short distance) and 50 trials in complex task scenarios (dense obstacles, long distance). The proposed method achieves success rates of 98% in simple tasks and 94% in complex tasks. Compared to CNN-D3QN and D3QN, MLA-D3QN improves success rates by 10 percentage points (vs. CNN-D3QN) and 38 percentage points (vs. D3QN) in simple tasks, and by 34 percentage points (vs. CNN-D3QN) and 84 percentage points (vs. D3QN) in complex tasks. Path costs are reduced by 24.0% (vs. CNN-D3QN) and 59.9% (vs. D3QN). These results validate the effectiveness of MLA-D3QN in improving generalization and sim-to-real transferability for local path planning in complex environments. Full article