Search Results (830)

It is of great significance to construct a networked energy-saving driving strategy method and application framework to solve the problems of traffic disorder, speed fluctuations, and high energy consumption caused by frequent acceleration, deceleration, and lane changing of vehicles in road sections with variable traffic flow. Considering the mixed traffic scenario where autonomous vehicles and manually driven vehicles interact and infiltrate, a hybrid traffic flow vehicle energy-saving driving model was established, and the Dueling Double Deep Q-Network (D3QN) was used to optimize and solve the energy-saving driving model; Selecting Qingdao urban intersections as application scenarios, energy-saving driving strategy application facilities were constructed in simulation experiments to carry out simulation verification of energy-saving driving strategies for mixed traffic flow in the context of vehicle networking. The simulation results show that in different scenarios with different proportions of CAVs, the energy-saving strategy based on D3QN deep reinforcement learning algorithm can achieve fuel savings of 8.41%~6.67% compared to conventional strategies. Compared with the ordinary reinforcement learning algorithm Q-learning, its fuel saving rate is increased by 1.94%~1.5%, and the energy-saving effect becomes more significant with the increase of traffic density; From the perspective of dynamic characteristics, the speed stability under the control of D3QN algorithm is superior to Q-learning algorithm, and significantly better than conventional strategies, further highlighting the comprehensive advantages of D3QN algorithm in optimizing traffic flow status and energy consumption control. The energy-saving driving strategy in the networked environment can reduce fuel consumption caused by speed fluctuations and traffic flow frequency disturbances, and optimize the stability of traffic flow operation. Full article

In response to the growing safety challenges posed by large-scale and specialized freight transportation on China’s rapidly expanding highway network, this study investigates the operational characteristics of trucks in interchange diverging areas—a critical segment with elevated accident risks. Leveraging high-frequency trajectory data collected from 16 interchanges, we analyze speed profiles and acceleration behavior of heavy trucks across key sections: the diversion influence zone, preparation zone, transition segment, and deceleration lane. A key contribution of this work is the development of a continuous speed prediction model based on Partial Least Squares Regression, which integrates road geometric parameters and driving behavior features to estimate speeds at four critical cross-sections of the diverging process. Furthermore, we propose a comprehensive safety evaluation framework incorporating three novel indicators: longitudinal speed consistency, lateral stability, and deceleration comfort. The model demonstrates strong performance, with all mean absolute percentage errors below 10% during validation using data from four independent interchanges. Comparative analysis with existing safety standards confirms the practical applicability and accuracy of the proposed methodology. This research offers three major contributions: (1) a systematic approach for processing large-scale trajectory data and predicting truck speeds in diverging areas; (2) a safety assessment framework tailored for geometric design consistency evaluation; and (3) empirical support for optimizing traffic safety facilities in interchange design and operation. The findings address a significant gap in current highway design guidelines and provide actionable insights for enhancing safety in truck-dominated transportation environments. Full article

The estimation of the area susceptible to rock failure and the prediction of its movement process are pivotal for hazard mitigation, yet they are also challenging. In this study, we proposed a novel integrated method combining field investigation, remote sensing, and three-dimensional discrete element method (DEM) simulation to achieve our goal. The field investigation and remote sensing analysis are used for the purpose of ascertaining the deformation phenomenon and the structure of the rock slope, identifying the potential failure position and area of the slope. Subsequently, a three-dimensional DEM simulation is employed to quantitatively assess the potential rock failure-affected area and movement process, based on the above potential failure information. The simulation results demonstrate that potential rock failure persists for approximately 30 s, and its movement process can be categorized into two distinct stages: acceleration and deceleration. The initial acceleration stage is characterized by a duration of 10 s, culminating in a peak average velocity of 13 m/s. The subsequent deceleration stage extends for a duration of 20 s. Notably, the maximum attainable velocity for the segment of rock mass under consideration is estimated to be 50 m/s. Furthermore, the model demonstrates the variation in fracture energy, friction energy, and kinetic energy over time. The potential affected area is 140,000 m², and approximately 8000 m² of residential construction will be destroyed if a rock failure occurs. It is imperative to implement measures aimed at the prevention of rock failure in order to mitigate the risk of such an occurrence. Full article

Background: The off-season is often characterized by a significant decrease or even a complete cessation of training. If this reduction is not planned properly, it can result in detraining. Despite numerous studies examining the effects of HIIT in football players, its specific role in mitigating detraining and maintaining aerobic and anaerobic performance during the off-season in adolescent female football players remains underexplored. Therefore, this study evaluated the effects of a 4-week off-season high-intensity training (HIIT) program on aerobic performance level and sprint endurance ability in Under-15 (U-15) female football players. Methods: Fifteen U-15 female football players from a professional club completed an experimental protocol consisting of two HIIT formats: Small-Sided Games (SSGs) and Repeated Sprint Training (RST), each performed twice weekly. Before and after the intervention period, participants performed the Yo-Yo Intermittent Recovery Level 1 (YYIR1) test to gauge aerobic performance and the 30-seconds sprint test to assess sprint endurance. The internal training load was monitored via heart rate (HR) and blood lactate concentration ([La]⁺), while external training load metrics included the total distance (TD), moderate-speed distance (MSD), high-speed distance (HSD), acceleration distance (≥3 m·s⁻²; ACC), and deceleration distance (≤−3 m·s⁻²; DEC). Results: YYIR1 improved by 57% (p = 0.0001; d = 1.12; 95% CI: 121.94–224.71) and the 30-s test performance increased by 13% (p = 0.004; d = 0.91; and 95% CI: 14.46–25.53) following the intervention period. A very large correlation between time spent at 90–95% HRmax and the 30-s test (r = 0.90, p = 0.0001) and YYIR1 (r = 0.81, p = 0.0001) performance was observed. Very large and nearly perfect correlations between DHS and YYIR1 (r = 0.82, p = 0.0001) and the 30-s test performance (r = 0.94, p = 0.0001), respectively, were found. Conclusions: In U-15 female football players, a four-week off-season HIIT program improved both aerobic performance and sprint endurance ability, indicating that a HIIT regime attenuates the off-season detraining, thus supporting a better-conditioned return to play. Coaches may implement 4-week high-intensity off-season programs to enhance aerobic performance and start the pre-season with a satisfactory level of aerobic fitness and sprint endurance. Full article

This study investigates the creep behavior of Wenzhou marine soft soil through 1D and triaxial creep tests, revealing that the secondary consolidation coefficient initially increases then stabilizes with stress level, decreases with OCR, increases with time, and reduces with depth. The e-lgt curves show four-phase deformation (instantaneous, primary consolidation, secondary compression, and accelerated creep), while triaxial tests identify three creep stages (decelerated, steady, and accelerated), with higher confining pressure increasing the deviatoric stress threshold for accelerated creep. Nonlinear stress–strain isochrones shift toward the strain axis with increasing confining pressure. The proposed structural parameter inversely correlates with the secondary consolidation coefficient, demonstrating that enhanced interparticle cementation and soil structure improve long-term creep resistance in coastal soft soil foundations. Full article

This study examines the alignment between the European Union’s climate policy rhetoric and the actual fossil fuel consumption behaviours of its Member States. By combining long-term and short-term time-series data with machine learning classification techniques, the analysis captures dynamic national energy trends and decarbonisation signals. Key innovations include the use of slope acceleration metrics and the identification of label reversals to detect volatility, acceleration, or stagnation in transition trajectories. The results show that, while some countries such as France and Denmark demonstrate consistent structural progress, others show deceleration or reversal, particularly in the use of gas and liquid fuels. This indicates that the relationship between EU-level policy ambition and national implementation is asymmetric and conditionally aligned. This study concludes that ongoing empirical monitoring and targeted diagnostics are essential to prevent conflating symbolic commitments with material change, and provides practical insights for improving climate policy accountability and adaptability across the EU. Full article

International tourism has helped numerous economies and regions over the years in achieving the objective of long-term sustainable economic growth. The “Association of Southeast Asian Nations (ASEAN)” is the rising hub for international tourism due to its rich history, rich vibrant culture, pleasant weather conditions, and beautiful landscape. However, research evidence about the tourism-growth relationship in the context of ASEAN economies is indeed very scarce. Accordingly, this research paper focuses on the members of the ASEAN region to examine the true influence that international tourism has on economic growth. Relevant econometric technique such as the “Fixed Effects (FEF)” is chosen for analysis based on the Hausman test, “Feasible Generalized Least Squares (FGLS)” is used for robustness, and “Two Stages Least Squares (2SLS)” is employed for tackling the likely endogeneity issue. The results show that international tourism has contributed positively to the economic growth of the ASEAN economies. Similarly, openness to global trade and education have also helped the ASEAN economies in securing long run sustainable economic growth. Lastly, the inflation rate has decelerated the pace of economic growth, while government expenditures have accelerated the pace of economic growth among ASEAN members. Our empirical findings are robust to alternative model specifications and alternative econometric estimations. Therefore, we expect our empirical findings to help the policymakers of the ASEAN economies in developing suitable policy responses regarding the growth performance of their economies through the channel of international tourism. Full article

Rapid socioeconomic development has continuously driven urban land expansion at the expense of other land types, leading to significant changes in land use and environment. However, existing studies still lack fine-resolution, long-term projections of urban land. Using seven periods of land use data from 1990 to 2020, this study projects urban land in the Yangtze River Delta (YRD) region under the framework of Shared Socioeconomic Pathways (SSPs). A multiple linear regression model and the land use change scenario simulation model (GeoSOS-FLUS) were employed to make projection at a high spatial resolution of 1 km. The findings are as follows: (1) From 1990 to 2020, the rate of urban land expansion in the study area showed a pattern of initial acceleration followed by deceleration, with the average annual expansion rate decreasing from 1.36 × 10³ km² to 0.24 × 10³ km². The center of gravity shifted toward the southeast. (2) Future urban land expansion is projected to increase by 14 × 10³ km² (SSP3) to 48 × 10³ km² (SSP5). The northern and central parts of the region will experience more significant growth, and the center of gravity is projected to shifting northwest. (3) Under SSP2 and SSP5, the urban land will increase continuously. The findings can offer a valuable insight for regional planning and sustainable development. Full article

Background and Objectives: Changes in the environment and physiology may be associated with an increased or decreased risk of cancer. Our study aims to evaluate the strength and the direction of the selection acting on oncosuppressor genes in association with phenotypic changes. Methods: We calculated the relative evolutionary rate (RER) using the converge method and linear regression on branches of phylogenetic trees. The association between changes in the evolutionary rate of oncosuppressors (DNA repair and cell cycle control genes) and trait selection was studied. The evolutionary rates of single oncosuppressor genes and pathways were evaluated. We studied two types of traits: those that are characteristic of vertebrates, such as homeothermy (the ability to maintain a constant body temperature), flight, and amnions; and those that are characteristic of mammals, such as high body mass and lifespan, an underground lifestyle, and hibernation. The analysis included 19,445 genes; 100 vertebrates and 46 mammalian species. We studied ancestral branches individually and all the clades having a trait. Results: Oncosuppressor genes accelerated in association with the ability to fly; p-value = 0.03 (positive or relaxed negative selection) and decelerated in homeothermic species; p-value = 0.04 (stabilizing selection). DNA repair genes were significantly accelerated in ancestral branches and in all clades of amniotic, homeothermic, and high-body-mass mammals (p-value < 0.05, FDR correction). Cell cycle control genes were under stabilizing selection in homeothermic animals, high-body-mass, long-lived, and underground mammals (p-value < 0.05, FDR correction). Data on the evolution of oncosuppressors are crucial for understanding the origin of cancer and will be important for future studies of tumor pathogenesis, pathomorphosis, and microevolution. Conclusions: The selection of traits associated with changes in cancer risk leads to positive/relaxed negative and stabilizing selection of oncosuppressor genes. Full article

This study examined muscle coordination during cutting movements in athletes with a history of groin pain. A total of 15 athletes who had experienced groin pain in the past two years (GP) and 14 healthy controls (CON) participated. Electromyography (EMG) and ground reaction force (GRF) data were collected, and EMG was analyzed using non-negative matrix factorization to extract muscle synergies. Three synergies were identified in both groups: Synergy 1 (landing), Synergy 2 (deceleration), and Synergy 3 (acceleration). No group differences were observed in GRF. However, compared with the CON, the GP demonstrated a 58.1% greater contribution of the latissimus dorsi and a 31.5% greater contribution of the erector spinae (SES) in Synergy 1, suggesting excessive trunk involvement during landing. In Synergy 2, SES contribution was 97.0% lower in the GP. In Synergy 3, the external oblique contribution decreased by 118.4%, while rectus abdominis contribution increased by 54.3%. These muscles are critical for pelvic stability, and their altered contributions indicate disrupted neuromuscular coordination in athletes with GP. Full article

This paper addresses the modeling challenge of significant asymmetry between acceleration and deceleration processes in car-following behavior by proposing an Asymmetric Acceleration and Deceleration Car Following (AAD-CF) model. The model characterizes driving decisions using both desired speed and desired spacing, and incorporates an asymmetric correction factor to capture differences in acceleration and deceleration behavior. Based on real vehicle trajectory data from the I-80 dataset, the model was compared at the microscopic level against classical models such as Gipps in terms of trajectory fitting error. The results show that the AAD-CF model consistently achieves lower trajectory fitting errors across different simulation time-steps, with error reduction exceeding 10%. At the macroscopic traffic flow level, the model successfully reproduced three-phase traffic flow states—free flow, synchronized flow, and wide moving jams. By implementing both startup and emergency braking scenarios, it was further revealed that braking waves propagate approximately 40% faster than startup waves, demonstrating asymmetric wave propagation. This study provides quantitative evidence for understanding the intrinsic relationship between microscopic driving behavior and macroscopic traffic phenomena, and the proposed model can support traffic simulation systems and theoretical analysis. Full article

The fatigue constitutive model under cyclic loading is of vital importance for studying the fatigue deformation characteristics of soft rocks. In this paper, based on the classical Bingham model, a modified Bingham fatigue model for describing the fatigue deformation characteristics of soft rocks under cyclic loading was developed. Firstly, the traditional constant-viscosity component was replaced by an improved nonlinear viscoelastic component related to the number of cycles. The elastic component was replaced by an improved nonlinear elastic component that decays as the number of cycle loads increases. Meanwhile, by decomposing the cyclic dynamic loads into static loads and alternating loads, a one-dimensional nonlinear viscoelastic-plastic Bingham fatigue model was developed. Furthermore, a rock fatigue yield criterion was proposed, and by using an associated flow rule compatible with this criterion, the one-dimensional fatigue model was extended to a three-dimensional constitutive formulation under complex stress conditions. Finally, the applicability of the developed Bingham fatigue model was verified through fitting with experimental data, and the parameters of the model were identified. The model fitting results show high consistency with experimental data, with correlation coefficients exceeding 0.978 and 0.989 under low and high dynamic stress conditions, respectively, and root mean square errors (RMSEs) below 0.028. Comparative analysis between theoretical predictions and existing soft rock fatigue test data demonstrates that the developed Bingham fatigue model more effectively captures the complete fatigue deformation process under cyclic loading, including the deceleration, constant velocity, and acceleration phases. With its simplified component configuration and straightforward combination rules, this model provides a valuable reference for studying fatigue deformation characteristics of rock materials under dynamic loading conditions. Full article

Flow dynamics were characterized and stable zones in diversions were quantified using physical modeling, in situ experiments, and 3D numerical simulations. ADV (1 cm spatial resolution) and water-level probes (0.01 cm spatial resolution) were used in the physical experiments in a rectangular channel. ADCP (resolution of 50 cm) was employed for in situ validation at a northern China hub. Numerical simulations using ANSYS 2022R2 Fluent software with RNG k-ε and VOF showed little error (<15%) compared to the experiments. The results quantified the diversion zone into four sub-regions: acceleration (length 0.8–1.2 h); stabilization (1.2–3.5 h); diffusion deceleration (3.5–5.0 h); and stagnation (localized eddies, diameter 0.3–0.8 d). The stable zone length was dominantly controlled by the nonlinear coupling of geometric (B_s/B_m, 42%) and hydraulic (Fr, 28%) parameters. Upstream and downstream stable zone empirical models showed high accuracy (R² = 0.83 and 0.76, p < 0.01), with an average relative error <15%. Based on the proposed zoning principles and flow characteristics, measurement facilities in the irrigation area are presented. These tools enhance irrigation diversion design and management for improved water efficiency. Full article

Virtual synchronous generators (VSGs) simulate the operating characteristics of conventional synchronous generators to provide inertia, voltage and frequency support for new-type power systems dominated by power electronics. However, in the event of grid faults, VSGs inevitably experience transient angle instability, which leads to great challenges to the safe and stable operation of the power system. To address the problem of transient instability so that VSGs can continue to support the power system during a grid fault, this paper firstly analyzes the adverse effect of a reactive power control (RPC) loop on the transient stability of the system and proposes a method for adding the variation in the power angle into RPC to increase the voltage reference of a VSG during grid faults, which can solve the transient instability problem under both equilibrium point existence and nonexistence by increasing the active power output of the VSG. The effect of the additional coefficient on the transient characteristics of the system is then analyzed using a small-signal model, and it is found that this method also enhances the frequency stability of the system. Finally, the feasibility of the proposed method and the correctness of the theoretical analysis are confirmed by a simulation platform. Full article

In-wheel motor (IWM)-driven electric vehicles (EVs) are susceptible to road excitation, which can induce eccentricity between the stator and rotor of the IWM. This eccentricity leads to unbalanced electromagnetic forces (UEFs) and electromechanical coupling (EMC) effects, severely degrading vehicle dynamic performance. To address this issue, this study first established an EMC system model encompassing UEF, IWM drive, and vehicle dynamics. Based on this model, four typical operating conditions—constant speed, acceleration, deceleration, and steering—were designed to thoroughly analyze the influence of EMC effects on vehicle dynamic response characteristics. The analysis results were validated through real-vehicle experiments. The results indicate that the EMC effects caused by motor eccentricity primarily affect the vehicle’s vertical dynamics performance (especially during acceleration and deceleration), leading to increased vertical body acceleration and reduced ride comfort, while having a relatively minor impact on longitudinal and lateral dynamics performance. Additionally, these effects significantly increase the relative eccentricity of the motor under various operating conditions, further degrading motor performance. To mitigate these negative effects, this paper designs an active suspension controller based on distributed model predictive control (DMPC). Simulation and experimental validation demonstrate that the proposed controller effectively improves ride comfort and body posture stability while significantly suppressing the growth of the motor’s relative eccentricity, thereby enhancing motor operational performance. Full article