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Stiffness degradation of track–bridge systems under earthquake excitations can lead to track dynamic irregularity, impacting the safety of train operations post-earthquake. In this paper, the nonlinear time-history analysis of CRTS II track–bridge system model established by ANSYS finite element analysis software is carried out under the action of transverse random earthquake. The train–track–bridge system model considering the stiffness degradation caused by earthquake is established by MATLAB, and the earthquake-induced track dynamic irregularity sample library is constructed. The probability distribution mode of the power spectral density sample of the earthquake-induced track dynamic irregularity is explored and the calculation method based on the probability guarantee rate is proposed. The influence of structural damping ratio, train running speed and train type on the power spectral density curve of the earthquake-induced track dynamic irregularity is analyzed. The results show that the power spectrum samples of track dynamic irregularity conform to the hypothesis test of a normal distribution. The power spectral density of earthquake-induced dynamic irregularity primarily consists of medium and low-frequency components. When the structural damping ratio increases from 0.03 to 0.04, 0.04 to 0.05, 0.05 to 0.06, and 0.06 to 0.07, the variation gradients are 0.1701, 0.1240, 0.1034 and 0.0999, respectively, which indicates that the structural damping ratio has a significant effect on the power spectral density of earthquake-induced irregularity, and the impacts of train speed and train type on the power spectral density of near-fault earthquake-induced irregularity are minimal. [ABSTRACT FROM AUTHOR]

The machine tool spindle supported by oil-lubricated hydrostatic bearings suffers from high temperature rise when running at high speed. To overcome this issue, an improved motorized spindle supported by water-lubricated hydrodynamic spiral groove bearings is proposed in this study. The thermal model for the motorized spindle including heat generation model and heat dissipation model is established by aid of finite element method. A test prototype for the motorized spindle and an experimental device are developed to carry out the test study of the spindle thermal behavior. The temperature field and thermal deformation field of the motorized spindle are investigated by numerical simulation and experimental measurement. Finally, a comparative study is made from the thermal behavior of the proposed spindle with herringbone groove journal bearings (HGJB) and the replacement spindle with plain journal bearings (PJB), and a comparative study of HGJB lubricated by the water and by the oil is carried out. The result indicates that using the water-lubricated hydrodynamic spiral groove bearings can decrease the temperature rise of motorized spindle, and the thermal design for the proposed motorized spindle can reduce the axial thermal displacement of the spindle front end to a low level. [ABSTRACT FROM AUTHOR]

In order to study the dynamic response of high-speed railway bridge and its deformation law under the coupling effect of vibration load and shield tunneling, a coupling model of shield tunneling and train load is established based on the actual case of tunneling under an adjacent bridge. The deformation characteristics and dynamic response of the bridge are investigated by analyzing the deformation under different tunneling conditions and train running speeds. The results show that the maximum disturbance of the original stress field around the bridge is caused when the shield penetrates to the near side of the bridge structure, at which time, the damping effect of the ground and bridge system on the vibration load is weakened, thus intensifying the dynamic response of the bridge system, and the additional deformation caused by the vibration load is the largest; the presence of train loads during the shield excavation slightly attenuates the differential settlement of the bridge, but increases the cumulative settlement of the bridge, in addition, the additional deformation of the bridge will increase with the increase of the train running speed; the additional deformation caused by the train load within 2 m of the shield crossing on both sides of the bridge is large, so the construction should be avoided as much as possible when the train is running in this construction section. [ABSTRACT FROM AUTHOR]

The effects of plyometric training (PT) versus resistance training (RT) on running economy and performance are unclear, especially in middle‐aged recreational runners. We examined (1) the efficacy of PT versus RT on running economy and performance in middle‐aged recreational runners and (2) the relationships between the main training outcomes. Twenty middle‐aged recreational runners were randomly allocated to a PT or RT group (n = 10/group). Training was conducted twice/week for 10 weeks combined with daily running. PT included the countermovement jump (CMJ), rebound jump, hurdle hop, and drop jump. RT consisted of leg press, leg curl, and calf raise with 50%–90% of one‐repetition maximum (1RM). Before and after the intervention, 1RM of the three lifting tasks, CMJ and drop jump performances, oxygen cost at 8–12 km/h, and 5 km running time were assessed. PT enhanced 1RM of leg curl only (8.5% and p = 0.007), whereas RT increased 1RM of the three lifting tasks (19.0%–21.1% and p < 0.001). Both groups improved CMJ height (6.4%–8.3% and p = 0.016) and drop jump performance (height: 9.7%–19.4%, p = 0.005, height/contact time: 11.4%–26.3% and p = 0.009) and oxygen cost regardless of running velocity (2.0% and p = 0.001) without significant group differences. However, neither group changed the 5‐km running time (p ≥ 0.259). A significant correlation was found between the changes in calf raise 1RM and oxygen cost (r = −0.477 and p = 0.046) but not between the other measured variables. These results suggest that for middle‐aged recreational runners, PT and RT can similarly improve running economy albeit not necessarily the 5‐km running time, and enhancing plantarflexion strength may particularly contribute to improving running economy. [ABSTRACT FROM AUTHOR]

Understanding the exercise behaviors of urban residents in green open spaces is crucial for optimizing future urban spatial planning and improving residents' quality of life. This study provides an in-depth analysis of residents' running behaviors across 87 green open spaces in Nanchang City. Running data collected from the exercise platform Keep, coupled with urban geographic data and field research, reveals the spatial distribution and temporal variations of running activities, including running flow, distance, time, and pace. A set of indicator systems, such as total area, landscape form index, surrounding residential land area, and road conditions, is used to analyze its relationship with the environmental elements of green open spaces. The research results show that the running flow, running distance, and running time in green open spaces in Nanchang City are significantly influenced by different objective elements, while running pace shows little correlation with these environmental elements. Specifically, the study highlights the significant impact of elements such as total area and road length, as well as the number of nearby bus stops and population density, on residents' running behaviors in Nanchang City's green open spaces. [ABSTRACT FROM AUTHOR]

Accidental vessel collisions pose a threat to the safety of train operations on navigable bridges. The CRH2 high-speed train, operating on a four-span continuous girder bridge, is selected as a research prototype to study the effects of vessel impact loads on the responses of the train-track-bridge (TTB) system and train running safety. The TTB model subjected to vessel collision is developed using the finite element software ANSYS and the multi-body system software SIMPACK. The influences of load intensity and train speed on the critical indicators of train running safety are discussed. Safety thresholds based on train running speed are proposed through comprehensive parametric analysis. The results indicate that the impact load has a significant effect on the dynamic responses of both bridge and track structures. The interaction between piles and soil (PSI) has a significant impact on the dynamic responses of the TTB system. The track structure undergoes significant overall deformation under the vessel impact load. The train running safety indices ascend with the increase in impact load intensity and train speed. As the impact load intensity increases from 0 to 24.25 MN, the speed limit for ensuring train running safety decreases from 350 km/h to 250 km/h. [ABSTRACT FROM AUTHOR]

One of the important applications of real-time crash prediction analysis lies in the field of proactive traffic management, where instantaneous crash risk evaluation and dynamic decision-making are prerequisites. This research proposes an integrated and advanced real-time crash risk prediction framework for Variable Speed Limits (VSL) and Hard Shoulder Running (HSR) implemented freeways considering their operational periods. Statistical methods are utilized to identify the significant crash contributing factors (related to traffic, roadway geometry, and weather conditions) and explain their relationships with crashes. Time-Embedded Transformer models are proposed to predict the likelihood of real-time crash events. The sensitivity and false alarm rate of the proposed AM peak model are found to be 0.76 and 0.27, respectively, whereas the values are 0.78 and 0.24, respectively for the PM peak model. Additionally, the results indicate substantial improvements in model prediction performance (i.e., an increment of sensitivity values by 7.04% and 8.33% in the AM and PM models, respectively) after incorporating the general safety condition of a freeway segment as an input feature while estimating real-time crash prediction models. Practitioners and policymakers could apply this method to obtain a more accurate real-time crash likelihood estimation, identify important crash precursors, dynamically update algorithms, and enhance safety aspects while operating traffic management strategies on freeways. [ABSTRACT FROM AUTHOR]

Purpose: This study investigated whether a running-adapted version of the cycling-based "step–ramp–step" (SRS) protocol would improve prediction of V ˙ O2 in treadmill exercise compared to the traditional prescriptive approach. Methods: Fourteen healthy individuals (6 females; 25 ± 6 years; 66.1 ± 12.7 kg) performed a treadmill-based SRS protocol including a ramp-incremental test to task failure followed by two constant-speed bouts within the moderate-(MODstep—below estimated lactate threshold; θLT), and heavy-intensity domains (HVYstep—between θLT and respiratory compensation point; RCP). Using the uncorrected V ˙ O2-to-speed relationship from the ramp exercise, three constant-speed bouts were performed at 40–50% between: baseline and θLT (CSEMOD); θLT and RCP (CSEHVY); and RCP and peak (CSESEV). For CSEMOD, CSEHVY, and CSESEV measured end-exercise V ˙ O2 was compared to predicted V ˙ O2 based on the: (i) "SRS-corrected" V ˙ O2-to-speed relationship (where MODstep and HVYstep were used to adjust the V ˙ O2 relative to speed); and (ii) linear "uncorrected" data. Results: Average treadmill speeds for CSEMOD and CSEHVY were 7.8 ± 0.8 and 11.0 ± 1.4 km·h−1, respectively, eliciting end-exercise V ˙ O2 of 1979 ± 390 and 2574 ± 540 mL·min−1. End-exercise V ˙ O2 values were not different compared to SRS-predicted V ˙ O2 at CSEMOD (mean difference: 5 ± 166 mL·min−1; p = 0.912) and CSEHVY (20 ± 128 mL·min−1; p = 0.568). The linear "uncorrected" estimates were not different for CSEMOD (− 91 ± 172 mL·min−1; p = 0.068) but lower for CSEHVY (− 195 ± 146 mL·min−1; p < 0.001). For CSESEV (running speed: 13.8 ± 1.7 km·h−1), the end-exercise V ˙ O2 was not different from peak V ˙ O2 achieved during the ramp (3027 ± 682 vs. 2979 ± 655 mL·min−1; p = 0.231). Conclusion: In healthy individuals, the SRS protocol more accurately predicts speeds for a target V ˙ O2 compared to traditional approaches. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effect of motor suspension parameters, specifically damping and stiffness, on the bifurcations of a bogie system. A motor bogie model with a nonlinear smooth equivalent conicity function is established. The study includes qualitative analyses of the stability and the Hopf bifurcation of the equilibrium, with the running speed as the single parameter. Furthermore, the generalised Hopf bifurcation and Hopf-Hopf bifurcation of the equilibrium, based on two motor suspension parameters, are also analysed. The paper delves into the codimension-1 and codimension-2 bifurcations of the limit cycles generated by the Hopf bifurcation, including Neimark–Sacker bifurcation, fold bifurcation, cusp bifurcation, 1:3 resonance, and 1:4 resonance. Analytical investigations reveal that the cusp bifurcation alters the type of fold bifurcation (subcritical or supercritical), and the fold bifurcation influences the stability and bifurcation direction of the limit cycle. Additionally, resonance occurs between the motor and the bogie frame. Since the subcritical (supercritical) Neimark–Sacker bifurcation produces an unstable (a stable) torus, the resonance points associated with the subcritical Neimark–Sacker bifurcation will lead to the instability of the motor bogie. The bifurcation analysis on the motor suspension parameters in this paper offers a theoretical reference for enhancing the stability of the motor bogie. [ABSTRACT FROM AUTHOR]

In the construction process of construction engineering, there exist a complex construction site layout and multiequipment collaborative work. If a reasonable construction plan cannot be made quickly and accurately, the investment in construction costs will be increased. Aiming at the construction material distribution, this study proposed a construction plan planning method under the multinode and multivehicle scene. Firstly, a mathematical model of the material distribution planning problem in the multinode multivehicle scene was established. The basic assumptions, objective functions, and constraints were proposed. The triangular scalar variables and 'unitization' processing methods were incorporated into the mathematical model. In order to solve the problem of material distribution planning, a heuristic neural network algorithm was designed. A 'gene-chromosome-individual' representation method and a 'two-step' calculation concept were defined. The specific implementation steps of the algorithm were given. Fully considering the type and quantity of vehicles and the length of the path, a method of establishing the mapping relationship between the construction scheme and the construction cost was proposed. The feasibility of the proposed theoretical method was verified by a cable truss structure model experiment. A calculation method with high fitting degree and fast running speed was established. According to the experiment model, the best construction scheme was formed. The results showed that the optimal construction scheme had a high vehicle loading rate and a clear distribution path, which effectively saved the construction cost under the premise of ensuring smooth construction. [ABSTRACT FROM AUTHOR]

The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms. • Smith Predictor is introduced into maglev control system to mitigate the adverse impact from TD. • Analyzed application value of Smith Predictor in levitation control system with time delay. • Provided suggestions for the broader implementation of Smith Predictor in practical engineering. [ABSTRACT FROM AUTHOR]

This study investigated the impact of six high-intensity interval training (HIIT) running sessions on 1% or 10% slopes on various physiological and performance parameters in 25 men. The participants underwent assessments of VO2max, time to exhaustion on 1% slope (TLim1%), and time to exhaustion on 10% slope (TLim10%) in the initial three visits. They were then randomly assigned to control (CON), HIIT on 1% slope (GT1%), or HIIT on 10% slope (GT10%) groups. Over three weeks, participants performed six HIIT sessions with equalized workload based on their individual maximal oxygen uptake (vVO2max). The sessions comprised 50% of TLim, with a 1:1 ratio of exercise to recovery at 50% vVO2max. The results indicated significant improvements in VO2max and peak velocity (VPeak) after HIIT on both slopes. Heart rate (HR) differed between sessions for GT1%, while no significant differences were observed for GT10%. Ratings of perceived exertion (RPE) were significantly reduced for GT1% after the third session, with a similar trend for GT10%. In summary, six HIIT sessions on a 1% or 10% slope effectively enhanced VO2max and VPeak, but there was no improvement in TLim performance, suggesting no adaptive transfer between training groups. [ABSTRACT FROM AUTHOR]

Purpose: The few previous researches on the impact of calf compression garments (CG) on running performance while assessing physiological and perceptual factors. Therefore, this study investigated how the clothing pressure of two types of Calf CG, CG1 and CG2, affects muscle fatigue and activation during running. Design/methodology/approach: Five healthy amateur runners(three female and two male)were recruited for a 30-min running trial. They wear a Calf CG on their right leg (CG group), but not on their left leg(CON group). After obtaining the clothing pressure of Calf CG on the gastrocnemius lateral head (GL), gastrocnemius medial head (GM) and tibialis anterior(TA) of the right leg, surface electromyography (sEMG)of four muscles of GL, GM, TA and rectus femoris (RF) of the left and right legs were measured during running, and heart rate, cardiopulmonary rate, and human RPE were also measured. Blood bleed oxygen before and after the running trial were measured. The root mean square (RMS) of the characteristic values was selected as an index for the analysis of sEMG signals, and the data were analyzed using statistical and computational methods. Findings: The results showed that the indexes of heart rate, blood oxygen, and RPE were significantly increased, indicating that the subjects had reached the fatigue level. The comparison of mean clothing pressure at GL, GM and TA locations reveals that the TA location consistently exhibits the highest pressure for both types of CG. When wearing CG1, the mean clothing pressure at the GL and GM test points is greater than that of CG2(CG1-GL = 0.2059 kPa > CG2-GL = 0.148 kPa; CG1-GM = 0.1633 kPa > CG2-GM = 0.127 kPa). This is attributed to the double-layered fabric on the sides of CG1, which precisely covers the GL and GM areas, thereby resulting in higher mean clothing pressure at these locations compared to CG2. Conversely, the mean clothing pressure at the TA location for CG1 is lower than that for CG2(CG1-TA = 0.3852 kPa < CG2-TA = 0.426 kPa). The pressure exerted by the CG1 on the lower limb test areas has both positive and negative effects, though neither are statistically significant. The pressure exerted by CG2 alleviates fatigue at the directly affected locations GL and GM, but exerts excessive pressure on TA, resulting in a negative effect. Additionally, CG2 pressure alleviates fatigue at the indirectly affected location RF on the same side. Based on the specific clothing pressure data, it is concluded that when the pressure at the GM location is 0.127 kPa, 30 min of running has a fatigue-relieving effect. However, the pressure should not be excessively high, at 0.1633 kPa it exhibits an insignificant adverse effect. At the TA location, a garment pressure mean between 0.3852 and 0.426 kPa does not alleviate fatigue after 30 min of running, and the negative effect becomes more pronounced as the pressure increases. The pressure exerted by the CG at GL, GM, TA and RF locations shows significant changes from the previous time period during the 15–18 min interval after running. Therefore, in the design of CG, attention should be paid to the changes in clothing pressure effects on muscles during this specific time period. Originality/value: The few previous researches on the impact of calf compression garments (CG) on running performance while assessing physiological and perceptual factors. Therefore, this study investigated how the clothing pressure of two types of Calf CG, CG1 and CG2, affects muscle fatigue and activation during running. [ABSTRACT FROM AUTHOR]

Fabricated ballastless track has witnessed increasingly wide application in large-span bridges of municipal railways. The current ballastless track standard is applicable to bridges with a main span of 200 m to 400 m. For the main span is longer than 400 m, it is necessary to ensure the travelling safety and comfort on the fabricated tracks. In this study, static and dynamic analysis models of train-track-bridge are established to explore the influence of complex ambient temperature changes and concrete shrinkage and creep on bridge deformation, followed by the analysis of the deformation coordination between long-span bridge and fabricated ballastless tracks, thereby revealing the dynamic response of the train-track-bridge system under the complex influence of temperature. The results show that when a train runs at a speed of 160 km/h, the existing ballastless track design standard is still applicable to a bridge span of 688 m. Compared with CRTS type III track, the adoption of the novel prefabricated ballastless track on long-span urban bridges provides higher safety and greater comfort, with comprehensive power performance improved by more than 10%. This design comprehensively takes into account the deformation coordination and dynamic performance of the rail bridge, providing a basis for the design and application of fabricated ballastless tracks on long-span bridges of urban railways. [ABSTRACT FROM AUTHOR]

The research aimed to evaluate the modified model of wave periodization efficiency in running speed tests conducted among soccer players aged 12 to 16. Participants included prospective players of a leading Polish top league soccer club. The research was carried out from 2018 to 2022 in June (Testing A) and December (Testing B) of each year. The test involved 30-m straight line running with 5-, 10-, and 30-m split time measurements. For this purpose, electronic photocells were used (FITLIGHT, Canada). The six-month training intervention increased the athletes' speed as there was a considerable decrease in the running time over the distance of 5 m (F = 7.86; p < 0.001), 10 m (F = 73.99; p < 0.001) and 30 m (F = 127.55; p < 0.001). Analysis of running performance of young soccer players aged 12-16 showed a significant improvement in speed at distances of 5, 10 and 30 m, confirming training effectiveness based on the wave periodization model. The negative correlation between testing year and performance suggests the influence of biological development on players' speed. The COVID-19 pandemic has impacted training, which was reflected in reduced differences between test scores. Improving initial running technique can contribute to better match results, which emphasizes the need for an individual approach to the physical preparation of players. [ABSTRACT FROM AUTHOR]

Running biomechanics have traditionally been analysed in laboratory settings, but this may not reflect natural running gait. Wearable technology has the potential to enable precise monitoring of running gait beyond the laboratory. This study aimed to evaluate the analytical validity and intra-session reliability of temporal running gait outcomes measured by the ViMove2 wearable system in healthy adults. Seventy-four healthy adults (43 males, 31 females, aged 18–55 years) wore the inertial device, ViMove2 on the tibia. Participants ran on a treadmill for one minute at various speeds (8, 10, 12, 14km/hr), completed in a standardised shoe (Saucony Guide Runner). Running gait was measured with the ViMove2 wearable and 3D motion capture (Vicon). Temporal running gait outcomes included ground contact time (GCT) and cadence (steps/min). GCT and cadence from the ViMove2 had face validity with expected changes in outcome with different running speeds, but ViMove2 tended to over-estimate GCT, and under-estimate cadence compared to the reference, especially at slower speeds. GCT demonstrated moderate to good agreement to the reference at speeds >10km/hr, but poor agreement at 8km/hr and within female runners. Cadence had moderate to excellent agreement across speeds compared to the reference. GCT and cadence had excellent reliability across speeds, but at 8km/hr GCT had good agreement between trials. Overall, temporal gait outcomes of GCT and cadence can be measured with the ViMove2, but accuracy and reliability are impacted at slow running speeds and within female runners. Future work is needed to clarify sex or speed-dependent corrections to algorithms / outcomes to aid interpretation and application. [ABSTRACT FROM AUTHOR]

Vehicle–track beam coupling resonance greatly influences the vibration response of the suspended permanent (SPML) system. Therefore, the study established the coupled dynamic model of the SPML train and the track beam using. The model is used to analyze the dynamic response of SPML trains when passing through the long-span flexible track beam at resonance speed. The accuracy of the model was verified by field tests, which simulated and compared the dynamic responses of maglev train and track beam systems at different running speeds. Furthermore, the coupled vibration response of the train and track beam at resonant speed are investigated to gain insight into the mechanism and vibrational properties of the SPML system in a resonant background. It shows that the dominant frequency of the train, suspension frame, and track beam is 6.74Hz. They result in resonance in the SPML system at 30km/h. Further analysis shows that adjusting the vertical distance between the mass center of the vehicle and the track beam can effectively alleviate the resonance between the vehicle and the track. Additionally, deformation at the ends of the long-span track beams affects the levitation force and gap of the suspension frame, offering valuable guidance for SPML system design. [ABSTRACT FROM AUTHOR]

The foot structure is associated with different running mechanics. The central nervous system is responsible for using the muscles through synergies during locomotion. The purpose of the present study was to examine the effect of foot structure on the electromyography factors and the synergy of the selected muscles of the lower extremity. Tibialis anterior, extensor digitorum longus, peroneus longus, soleus, biceps femoris, vastus lateralis, gastrocnemius lateralis and medialis muscles activity of 60 barefoot recreational runners with different foot structures was recorded while running at a speed of 3.3 m/s. Muscle activity was measured in the running cycle. Besides, muscle synergies were extracted using non-negative matrix factorization algorithm. The results showed that there were differences between groups with different foot type in muscle activity under different phases of running in some muscles. Furthermore, the findings indicated that the number of synergies was similar in different groups and the relative weight of muscles was not different across groups. In conclusion, despite the difference in muscle activity under different phases of the running cycle, muscle synergies are similar among the groups. This can indicate similar control by the central nervous system in runners with different arch structures while running and the observed changes in muscle activity can be attributed to the type of forces exerted on the body, the length-tension relationship, and changes in the direction of the lower limbs in people with different arch structures. [ABSTRACT FROM AUTHOR]

Studies have shown that in open-skill sports the executive function of high-performing players is significantly higher than that of the control group. However, whether participation in soccer effectively improves executive function is unclear because previous studies lacked baseline measurements of executive function. Furthermore, agility, mostly developed in early childhood, is the most demanding component of physical fitness in open-skill sports, requiring sudden changes in body direction while running at full speed. However, no studies have examined the improvement in agility of young children participating in open-skill sports through comparison with a control group. This study aimed to clarify whether instruction in soccer, an open-skill sport, can effectively improve the executive function and agility of kindergarteners compared to a control group. In April 2020, 31 five-year-old children enrolled in kindergarten K in H prefecture in Japan were targeted as the intervention group and received soccer instruction for 12 weeks. In April 2020, a control group was established, consisting of 39 five-year-old children enrolled at the same kindergarten. Participants in both groups were measured for agility, inhibition, and working memory before and after (pre–post) soccer instruction for the intervention group. For each item, a two-way ANOVA of the group (intervention group・control group) x measurement period (pre–post) was performed, showing no significant interactions for working memory and agility. Because only the inhibition effect was significant, simple main effects were tested. Regarding inhibition, although the intervention group (M = 0.18, SD = 0.01) and the control group (M = 0.17, SD = 0.01) did not differ significantly in performance pre-intervention, the intervention group (M = 0.23, SD = 0.01) showed significantly better performance post-intervention compared to the control group (M = 0.19, SD = 0.01) (p <.01). Thus, soccer instruction improved kindergarteners' inhibition, to a level significantly higher than that of the control group. Still, no differences were found between groups regarding working memory and agility. [ABSTRACT FROM AUTHOR]

In order to improve the automatic production efficiency of the textile workshop and reduce the labor cost and error rate, this study designed a multi label recognition model YoloColor-Net based on deep learning, which aims to realize the automatic detection and recognition of the bobbin shape and yarn color on the yarn frame in the textile workshop. Firstly, according to the research needs, a dataset sample containing 12,173 textile bobbin images was collected and constructed independently. Then, the traditional yolov5 model is improved by designing the convolution network of yarn color recognition, which solves the problem of missing detection of the bobbin when detecting the bobbin shape and yarn color at the same time. Secondly, the lightweight DSConv module is used to replace the ordinary convolution of the Backbone layer to reduce the parameters of YoloColor-Net and improve the running speed. Finally, the improved attention mechanism (ICBAM) is added to the Backbone and Neck layers of YoloColor-Net to improve the accuracy of bobbin recognition. The experimental results show that the detection accuracy of the improved YoloColor-Net model is 99.3%, the number of model parameters is reduced by 10.4%, and the GFLOPS is reduced by 17.1%. FPS increased from 43.13 to 67.23, an increase of 55.9%. Therefore, the proposed model can basically meet the task of bobbin automatic detection and recognition, and consider the initial localization deployment. [ABSTRACT FROM AUTHOR]

The achievement of rapid and reliable image object tracking has long been crucial and challenging for the advancement of image-guided technology. This study investigates real-time object tracking by offering an image target based on nuclear correlation tracking and detection methods to address the challenge of real-time target tracking in complicated environments. In the tracking process, the nuclear-related tracking algorithm can effectively balance the tracking performance and running speed. However, the target tracking process also faces challenges such as model drift, the inability to handle target scale transformation, and target length. In order to propose a solution, this work is organized around the following main points: this study dedicates its first part to the research on kernelized correlation filters (KCFs), encompassing model training, object identification, and a dense sampling strategy based on a circulant matrix. This work developed a scale pyramid searching approach to address the shortcoming that a KCF cannot forecast the target scale. The tracker was expanded in two stages: the first stage output the target's two-dimensional coordinate location, and the second stage created the scale pyramid to identify the optimal target scale. Experiments show that this approach is capable of resolving the target size variation problem. The second part improved the KCF in two ways to meet the demands of a long-term object tracking task. This article introduces the initial object model, which effectively suppresses model drift. Secondly, an object detection module is implemented, and if the tracking module fails, the algorithm is redirected to the object detection module. The target detection module utilizes two detectors, a variance classifier and a KCF. Finally, this work includes trials on object tracking experiments and subsequent analysis of the results. Initially, this research provides a tracking algorithm assessment system, including an assessment methodology and the collection of test videos, which helped us to determine that the suggested technique outperforms the KCF tracking method. Additionally, the implementation of an evaluation system allows for an objective comparison of the proposed algorithm with other prominent tracking methods. We found that the suggested method outperforms others in terms of its accuracy and resilience. [ABSTRACT FROM AUTHOR]

Extensive research has delved into the impact of environmental circumstances on the pacing and performance of professional marathon runners. However, the effects of environmental conditions on the pacing strategies employed by marathon participants in general remain relatively unexplored. This study aimed to examine the potential associations between various environmental factors, encompassing temperature, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and the pacing behavior of men and women. The retrospective analysis involved a comprehensive dataset comprising records from a total of 668,509 runners (520,521 men and 147,988 women) who participated in the 'Berlin Marathon' events between the years 1999 and 2019. Through correlations, Ordinary Least Squares (OLS) regression, and machine learning (ML) methods, we investigated the relationships between adjusted average temperature values, barometric pressure, humidity, precipitation, sunshine, cloud cover, wind speed, and dew point, and their impact on race times and paces. This analysis was conducted across distinct performance groups, segmented by 30-minute intervals, for race durations between 2 hours and 30 minutes to 6 hours. The results revealed a noteworthy negative correlation between rising temperatures and declining humidity throughout the day and the running speed of marathon participants in the 'Berlin Marathon.' This effect was more pronounced among men than women. The average pace for the full race showed positive correlations with temperature and minutes of sunshine for both men and women. However, it is important to note that the predictive capacity of our model, utilizing weather variables as predictors, was limited, accounting for only 10% of the variance in race pace. The susceptibility to temperature and humidity fluctuations exhibited a discernible increase as the marathon progressed. While weather conditions exerted discernible influences on running speeds and outcomes, they did not emerge as significant predictors of pacing. [ABSTRACT FROM AUTHOR]

Objective: To describe the relationship between bilateral electrical activity in the biceps femoris and the variation of triaxial acceleration in three 50 m sprints. Methods: Biceps femoris muscle activation and acceleration in the anterior–posterior, mediolateral, and superior–inferior axes were measured in three 50 m sprints in nine national-level sprinters. Results: There was significant asymmetry between both legs, and the variations between axes were significant between the anterior–posterior with respect to the lateral and superior–inferior, and between the lateral and superior–inferior (p < 0.05). Conclusions: Increased biceps femoris activation during running increases speed regardless of asymmetry in force application. In the maintenance of horizontal velocity, acceleration of the anterior–posterior axis is the most relevant and depends on the flexion-extension muscle actions contained in the lateral axis. [ABSTRACT FROM AUTHOR]

This study presents the validation of a dynamic test system to simulate a high‐speed train passing bridges under seismic excitation. The system comprises scaled models of a CRH380A high‐speed train and an 11‐span simply supported bridge on a shake table array. This innovative apparatus combines seismic loading with the moving train load to replicate train‐track‐bridge interaction (TTBI) during earthquakes. It allows investigation of various train speeds and seismic excitations, providing invaluable insights into TTBI. First, the detailed similarity design principle based on the equations of motion was discussed, and its applicability to the wheel‐rail contact relationship was verified. Then, the dynamic characteristics of the scaled model were identified, and the impact of the error between the scaled model and the theoretical model on the TTBI response was assessed. Furthermore, the comparison of the dynamic test model and the numerical simulation in acceleration responses validated the accuracy of the rigid‐flexible coupling model method for the actual TTBI system. Test cases without external excitation, with simple harmonic excitation and with seismic excitation were conducted on the dynamic test system. Results showed that the influence of track irregularity and running speed on train response aligns with the classical train‐bridge interaction theory. The successful implementation of this test system marks a significant advance in understanding TTBI mechanics and has significant implications for seismic safety enhancement of railway infrastructure. [ABSTRACT FROM AUTHOR]

The gross calorific value (GCV) of coal is an important parameter for evaluating coal quality, and regression analysis methods can be used to predict GCV. In this study, we proposed a GCV prediction model based on cubist regression. To develop a good regression model, feature selection of input variables was performed using a correlation analysis and a recursive feature elimination algorithm. Thus, in this study, we determined three sets of variables as the optimal combination for regression models: proximate analysis variables (Set 1: moisture, standard ash, and volatile matter), element analysis variables (Set 2: carbon, sulfur, and oxygen), and comprehensive index variables (Set 3: carbon, volatile matter, standard ash, sulfur, moisture, and hydrogen). Results for comparison with multiple linear regression, random forest regression, and numerous previous prediction models, such as gradient boosting regression tree, support vector regression (SVR), backpropagation neural networks, and particle swarm optimization–artificial neural network (PSO-ANN), indicate that these seven regression models have the best fitting effect on the comprehensive index variables among the three sets of input variables. The cubist model showed higher prediction accuracy and lower error than most other models (R2, mean absolute error, root mean square error, and average absolute relative deviation percentage values are 0.990, 0.476, 0.668, and 0.086% for the proximate analysis variables; 0.992, 0.381, 0.596, and 0.140% for element analysis variables; and 0.999, 0.161, 0.219, and 0.087% for comprehensive index variables, respectively). The cubist model combines the advantages of decision tree and linear regression, which not only enables it to perform well in terms of accuracy but also makes the model highly interpretable because it is based on multiple sublinear equations. In addition, the cubist model shows obvious advantages in terms of running speed, especially compared with SVR and PSO-ANN, which require complex parameter optimization. In summary, the cubist model considers the prediction accuracy, model interpretability, and computational efficiency as well as provides a new and effective method for GCV prediction. [ABSTRACT FROM AUTHOR]

Host–parasite relationships are important components of ecological systems that influence the evolution of both hosts and parasites. High levels of ectoparasitic infections can disrupt host homeostasis, causing adverse effects on health and performance. However, the effects of natural ectoparasite levels on host physiology are less understood, with most research designs implementing experimental or hormonal manipulations of hosts. In this study, we examined the interplay between tick parasitism and host characteristics on body condition and locomotor performance in Eastern fence lizards in natural settings. We found a higher frequency of tick infections in male lizards relative to females, with larger males being more likely to experience tick infection. Infected lizards had reduced locomotor performance, max sprint speed and 2-m run speed. Together this suggests an energetic trade-off between increased immune function and reduced locomotor performance, which is consistent with the immunocompetence–handicap hypothesis. Higher numbers of ticks on adult male lizards may be explained by age as well as the immunosuppressive effects of testosterone. Tick infection did not appear to reduce overall body condition of lizard hosts. Our findings shed light on the interplay between ectoparasitic infection, host characteristics, and locomotor performance under natural conditions. Such insights are crucial for understanding host–parasite dynamics and determining the trade-offs for hosts within ecological contexts. [ABSTRACT FROM AUTHOR]

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor's running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X2) does not have a significant effect on this rate. Similarly, the tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X2) does not. Furthermore, the linear speed of the conveyor chain (X2) and the linear speed of the inverting roller (X3) significantly impact the soil content rate, while the tractor's running speed (X1) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds. [ABSTRACT FROM AUTHOR]

This paper investigates the vibration response of a new part-screw pile composite foundation under moving train loads via a model test method. Based on the acceleration signals of the pile and the surrounding soil, a non-linear fitting method is used to establish the relationship between the dynamic attenuation coefficient and the depth of the foundation. Next, the effect of spatial location and train speed on the pile-soil dynamic interaction is investigated by introducing the pile-soil spectral amplitude ratio δ p − s . In addition, the dynamic susceptibility of the part-screw pile to damage under dynamic train loads is revealed with a wavelet packet energy distribution index E DIS . Afterwards, the cumulative deformation evolution characteristics of screw pile composite foundations under long-term train loading were revealed using the frequency domain integration method. The results of this work reveal that the faster the train runs, the larger the pile-soil spectrum amplitude ratio and the more prominent the 'dynamic concentration effect' of the part-screw pile. The change in cross-section of the part-screw pile results in a sudden change in the vibration energy transmitted from the top of the pile, which makes the variable section of the part-screw pile more likely to cause dynamic damage or even deformation. The cumulative deformation evolution process of soil between part-screw piles under long-term cyclic train loading can be divided into three stages: slow change period, fluctuation rising period and stable deformation period. The research results have important reference significance for the optimization design of high-speed railway part-screw pile composite foundation and the planning of railway running speed. [ABSTRACT FROM AUTHOR]

The train operates in special environments such as large bridges and elevated viaducts. The fluctuations of the aerodynamic loads of the high-speed train (HST) are more intense and the possibility of the train derailment and overturning will increase when the train is running on the bridge under the crosswind. Thus, it is of utmost importance to study both the aerodynamic characteristics and the running safety of the train in this situation. This study uses the IDDES method to investigate the aerodynamic characteristics of the train running on the double track bridge in both up and down train directions at different speeds. The differences in the impact of aerodynamic loads on the train's dynamic response indicators are discussed using the wind-vehicle coupling dynamic response calculation method. Based on these researches, the operational safety of the train under different operating conditions is evaluated from both flow field and dynamic perspectives. The results show that large-scale vortices fall off from the nose of the train and form a larger vortex structure on the leeward side and when the train is running under the crosswind. Its aerodynamic loads fluctuate intensely with time due to the complex wake flow of the train. The dominant frequencies of the unsteady aerodynamic loads are mostly concentrated in the range of 0–5Hz, which is close to the natural modal frequencies of the train. This will lead to the overturning of the train due to vehicle resonance. The derailment coefficient and wheel load reduction rate of the train increase with the speed. Their peak values exceed the limit of 0.8 while the peak duration of the derailment coefficient is less than 0.05s, which means the state of the leeward wheel will recover from a short derailment. However, the duration of derailment increases with speed. Therefore, appropriate measures should be taken to prevent accidents when the train is running at higher speed on the bridge to guarantee the operational safety of the HST. [ABSTRACT FROM AUTHOR]

The rotational speed vectors of the bearing balls affect their service life and running performance. Observing the actual rotational speed of the ball is a prerequisite for revealing its true motion law and conducting sliding behavior simulation analysis. To address the need for accuracy and real-time measurement of spin angular velocity, which is also under high-frequency and high-speed ball motion conditions, a new measurement method of ball rotation vectors based on a binocular vision system is proposed. Firstly, marker points are laid on the balls, and their three-dimensional (3D) coordinates in the camera coordinate system are calculated in real time using the triangulation principle. Secondly, based on the 3D coordinates before and after the movement of the marker point and the trajectory of the ball, the mathematical model of the spin motion of the ball was established. Finally, based on the ball spin motion model, the three-dimensional vision measurement technology was first applied to the measurement of the bearing ball rotation vector through formula derivation, achieving the analysis of bearing ball rolling and sliding characteristics. Experimental results demonstrate that the visual measurement system with the frame rate of 100 FPS (frames per second) yields a measurement error within ±0.2% over a speed range from 5 to 50 RPM (revolutions per minute), and the maximum measurement errors of spin angular velocity and linear velocity are 0.25 °/s and 0.028 mm/s, respectively. The experimental results show that this method has good accuracy and stability in measuring the rotation vector of the ball, providing a reference for bearing balls' rotational speed monitoring and the analysis of the sliding behavior of bearing balls. [ABSTRACT FROM AUTHOR]

Purpose: The aims of the present study were to investigate blood lactate kinetics following high intensity exercise and identify the physiological determinants of 800 m running performance. Methods: Fourteen competitive 800 m runners performed two running tests. First, participants performed a multistage graded exercise test to determine physiological indicators related to endurance performance. Second, participants performed four to six 30-s high intensity running bouts to determine post-exercise blood lactate kinetics. Using a biexponential time function, lactate exchange ability (γ1), lactate removal ability (γ2), and the quantity of lactate accumulated (QLaA) were calculated from individual blood lactate recovery data. Results: 800 m running performance was significantly correlated with peak oxygen consumption (r = −0.794), γ1 and γ2 at 800 m race pace (r = −0.604 and −0.845, respectively), and QLaA at maximal running speed (r = −0.657). V ˙ O2peak and γ2 at 800 m race pace explained 83% of the variance in 800 m running performance. Conclusion: Our results indicate that (1) a high capacity to exchange and remove lactate, (2) a high capacity for short-term lactate accumulation and, (3) peak oxygen consumption, are critical elements of 800 m running performance. Accordingly, while lactate has primarily been utilized as a performance indicator for long-distance running, post-exercise lactate kinetics may also prove valuable as a performance determinant in middle-distance running. [ABSTRACT FROM AUTHOR]

In order to comprehensively evaluate the driver's vibration comfort under different vibration conditions, eighteen subjects were required to drive a tractor at different speeds on field and asphalt roads respectively in the real vehicle experiment. The sEMG signals and vibration acceleration signals of the subjects were recorded. And the time-frequency domain analysis of sEMG signals and acceleration signals were used to determine the relationship among the characteristic indexes, tractor speed and road surfaces. The relevance analysis showed that there was a significant correlation between the integral electromyography (iEMG) and median frequency (MF) of the middle scalene muscle, erector spinae muscle and gastrocnemius muscle, the RMS of weighted acceleration (aw) of the neck, waist and legs, and the subjective comfort feelings. It was proven that the tractor speed had a significant impact on human body vibration based on the ANOVA result (p < 0.05). With the increase of running speed, the time domain indexes of sEMG signals including iEMG, RMS and the vibration acceleration signals of the testing body parts increased significantly, while the amplitudes of frequency domain indexes decreased. Therefore, a quantitative regression evaluation model for the comfort of the neck, waist and legs integrating the sEMG and vibration signals was established, and its relative errors were 5.05, 4.38 and 6.12% respectively. This proposed assessment model can combine characteristics of the partial and overall vibration response of human body effectively, predict the tractor driver's vibration comfort accurately, provide a theoretical basis for the evaluation of tractor cab vibration comfort. [ABSTRACT FROM AUTHOR]

One dominant approach for reducing response times in large-scale systems is Join-the-Shortest-Queue-d: whenever a job arrives, the dispatcher queries d servers at random and then assigns the job to the queried server with the shortest queue. While JSQ -d is known to perform quite well in systems where all servers run at the same speed, this is not the case in systems that exhibit heterogeneity with respect to server speeds. Unfortunately, there is no straightforward way to extend JSQ -d (or other so-called power-of-d policies) to heterogeneous systems. Should a job be assigned to the queried server with the shortest queue even if much faster servers were among those queried? Should a job be assigned to the queried server where it is expected to complete the soonest even if there is an idle, albeit slower, server available among those queried? And for that matter, should we query faster servers more often than their slower counterparts? Recent work has introduced a framework for developing strong dispatching policies by pairing suitably chosen querying and assignment rules. Within this framework, prior work has focused on finding strong-performing dispatching policies that use only the idle/busy statuses of the queried servers, rather than detailed queue length information. In this paper, we overcome the challenge of evaluating the performance of—and finding strong-performing—general scalable dispatching policies that make use of both server speed and detailed queue length information, through a combination of mean field analysis and a sequence of modified optimization problems. We find that well-designed length-aware dispatching policies can significantly outperform their idleness-based counterparts in large-scale heterogeneous systems. While the best policies of this kind are often complicated to describe, we find that in the vast majority of cases the relatively simple Shortest Expected Wait policy performs nearly as well, without the need for an especially sophisticated and time-consuming optimization procedure. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the effects of an 8 week targeted training program on speed, agility, and muscle asymmetries in soccer players. 32 elite soccer players were recruited for the study. Their age, body mass, and body height were 25.8 ± 7.3 years, 77.4 ± 11.1 kg, and 177.5 ± 9.8 cm, respectively. After the warm-up, participants performed two maximum 30 m sprints with a 5-minute rest interval between trials. After the linear sprint test, performed two repetitions of the COD randomized ZigZag test. The tests were performed at the beginning and at the end of the pre-season, which lasted for 8 weeks. EMG was measured bilaterally from the quadriceps, hamstrings, and gluteal muscles with shorts made of knitted fabric similar to elastic clothes. Athletes in the experimental group performed sport-specific targeted strength training based on movement patterns 4 times per week (Monday, Tuesday, Thursday, and Friday). The training included 6 bodyweight exercises (Bird Dog, Single-Leg Glute Bridge, Dead Bug, Side Plank, Reverse Lunge, and Clamshell), performed unilaterally in 5 sets of 10 repetitions of each exercise. The load progression included an additional set in each successive week of the experiment. The data analysis showed significant improvement in 5 m and 30 m sprints after applying the 8-week targeted training protocol. A statistically significant improvement in performance was also observed after the 8-week training period in case of COD, while the speed deficit also decreased significantly. The greatest improvements were observed during the COD test. As a result of repeated COD training over a period of 8 weeks, its technique was improved. Implementation of training methods, which target specific aspects of soccer in the pre-season training routines can improve key motor abilities for that sports discipline. A comprehensive training approach including speed, agility, and resistance training based on specific movement patterns should be applied by strength and conditioning practitioners in soccer teams to achieve peak physical performance and reduce injury risk due to the partial elimination of muscular asymmetries. [ABSTRACT FROM AUTHOR]

The use of a beneficiation machine for mineral soring can increase the content of target minerals, optimize resource utilization, and improve production efficiency, winch is of great significance and value in the mining field. However, during the soring process, the ore images obtained through X-ray transmission technology may have target adhesion and overlap, which will seriously affect the efficiency and accuracy of mineral soring. Obtaining an independent ore image is a necessary condition for using the method to identify, locate and sort the ore. To improve the accuracy and efficiency of mineral soring, a concave point detection and matching algorithm based on polygon fitting is proposed for segmenting adhesive ore images. Firstly, fitting a binary image of the ore into a polygon image and identifying concave points from the turning point of the image. Secondly, constructing a linear equation by using a turning point to form a detection area, searching the to-be-connected points of the concave points in the area, and completing concave point matching. Finally, the computer view is transferred from the binary image to the gray image, and the gray value of the region to be segmented is analyzed to determine whether the region is the actual adhesion between ores, so as to determine whether to execute the segmentation operation. The results show that the overall segmentation accuracy of the algorithm on the adhesive ore dataset is 93.60%, the concave noise rate is only 5.23%, and the average calculation time for processing images with a size of 281x336 is as low as 5.13 ms. Its noise concave filtering ability, concave detection accuracy, segmentation accuracy, and algorithm running speed are all better than those of similar algorithms. It shows strong segmentation stability for ore images with different adhesive quantities and forms. [ABSTRACT FROM AUTHOR]

With the continuous progress of society, people's living consumption needs are also constantly changing. The traditional vehicle positioning technology can no longer meet the new positioning needs of travelers, so a more accurate positioning system is urgently needed. This paper aims to study a more accurate positioning system and proposes a vehicle positioning system based on radio frequency identification (RFID). After comparing several common positioning methods, the use of LANDMARC positioning algorithm makes the vehicle positioning more accurate. This paper has effectively integrated advanced computer and artificial intelligence technology and applies it to control and management and finally established a comprehensive traffic positioning system that can effectively alleviate traffic congestion, reduce traffic accidents and quickly deal with traffic emergencies. The experimental results have shown that when the vehicle runs at a speed of 40 km/h and the communication rate is 860 kpbs, the average positioning accuracy of the improved algorithm is doubled compared with the traditional algorithm, and the error is reduced by nearly one. Therefore, compared with the traditional positioning system and artificial intelligence, the RFID vehicle positioning system under cloud computing has more accurate positioning information and more timely and convenient services. [ABSTRACT FROM AUTHOR]

Vision-based vehicle detection in adverse weather conditions such as fog, haze, and mist is a challenging research area in the fields of autonomous vehicles, collision avoidance, and Internet of Things (IoT)-enabled edge/fog computing traffic surveillance and monitoring systems. Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time. To evaluate vision-based vehicle detection performance in foggy weather conditions, state-of-the-art Vehicle Detection in Adverse Weather Nature (DAWN) and Foggy Driving (FD) datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle detection classes: cars, buses, motorcycles, and trucks. The state-of-the-art single-stage deep learning algorithms YOLO-V5, and YOLO-V8 are considered for the task of vehicle detection. Furthermore, YOLO-V5s is enhanced by introducing attention modules Convolutional Block Attention Module (CBAM), Normalized-based Attention Module (NAM), and Simple Attention Module (SimAM) after the SPPF module as well as YOLO-V5l with BiFPN. Their vehicle detection accuracy parameters and running speed is validated on cloud (Google Colab) and edge (local) systems. The mAP50 score of YOLO-V5n is 72.60%, YOLO-V5s is 75.20%, YOLO-V5m is 73.40%, and YOLO-V5l is 77.30%; and YOLO-V8n is 60.20%, YOLO-V8s is 73.50%, YOLO-V8m is 73.80%, and YOLO-V8l is 72.60% on DAWN dataset. The mAP50 score of YOLO-V5n is 43.90%, YOLO-V5s is 40.10%, YOLO-V5m is 49.70%, and YOLO-V5l is 57.30%; and YOLO-V8n is 41.60%, YOLO-V8s is 46.90%, YOLO-V8m is 42.90%, and YOLO-V8l is 44.80% on FD dataset. The vehicle detection speed of YOLO-V5n is 59 Frame Per Seconds (FPS), YOLO-V5s is 47 FPS, YOLO-V5m is 38 FPS, and YOLO-V5l is 30 FPS; and YOLO-V8n is 185 FPS, YOLO-V8s is 109 FPS, YOLO-V8m is 72 FPS, and YOLO-V8l is 63 FPS on DAWN dataset. The vehicle detection speed of YOLO-V5n is 26 FPS, YOLO-V5s is 24 FPS, YOLO-V5m is 22 FPS, and YOLO-V5l is 17 FPS; and YOLO-V8n is 313 FPS, YOLO-V8s is 182 FPS, YOLO-V8m is 99 FPS, and YOLO-V8l is 60 FPS on FD dataset. YOLO-V5s, YOLO-V5s variants and YOLO-V5l_BiFPN, and YOLO-V8 algorithms are efficient and cost-effective solution for real-time vision-based vehicle detection in foggy weather. [ABSTRACT FROM AUTHOR]

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Grounding temporal video segments described in natural language queries effectively and efficiently is a crucial capability needed in vision-and-language fields. In this article, we deal with the fast video temporal grounding (FVTG) task, aiming at localizing the target segment with high speed and favorable accuracy. Most existing approaches adopt elaborately designed cross-modal interaction modules to improve the grounding performance, which suffer from the test-time bottleneck. Although several common space-based methods enjoy the high-speed merit during inference, they can hardly capture the comprehensive and explicit relations between visual and textual modalities. In this article, to tackle the dilemma of the speed–accuracy tradeoff, we propose a commonsense-aware cross-modal alignment network (C2AN) that incorporates commonsense-guided visual and text representations into a complementary common space for fast video temporal grounding. Specifically, the commonsense concepts are explored and exploited by extracting the structural semantic information from a language corpus. Then, a commonsense-aware interaction module is designed to obtain bridged visual and text features by utilizing the learned commonsense concepts. Finally, to maintain the original semantic information of textual queries, a cross-modal complementary common space is optimized to obtain matching scores for performing FVTG. Extensive results on two challenging benchmarks show that our C2AN method performs favorably against states of the art while running at high speed. Our code is available at https://github.com/ZiyueWu59/CCA [ABSTRACT FROM AUTHOR]

The objective of the study was to examine the match-running load of female soccer players competing at distinct age groups (U15, U18 and senior cohorts) belonging to the same professional club, over a competitive season. The external load variables of the official matches were monitored with Global Positioning System (GPS) technology: total distance (TD), at >18 km·h−1 (running), at >21 km·h−1 (high-speed running, HSR) and at >24 km·h−1 (sprint, SPR) distances, efforts at >85% of the maximal sprint speed (>85% MSS), acceleration load (aLoaD), accelerations (ACC2 and ACC3, >2 and >3 m·s−2) and decelerations (DEC2 and DEC3 <−2 and <−3 m·s−2). Overall, distances covered at running, HSR and sprinting were greater for senior players than their younger peers (U15 and U18; p < 0.05). Regarding HSR and sprints, no difference was found for sprints accumulated by central defender (CD) players in comparison to U18 and U15 (p > 0.05). In addition, U18 and senior players engaged more often in ACC and DEC, >2 and >3 m·s−2, respectively, than U15 players (p < 0.05). In conclusion, older female soccer players are exposed to higher match load than their younger peers. These findings could be useful for soccer coaches to design specific speed development programmes across the long-term athletic development pathway. [ABSTRACT FROM AUTHOR]

Oxygen consumption (V˙O2) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use by consumers as they intervene with the user's physical integrity, and are expensive and difficult to operate. To circumvent these drawbacks, indirect estimation of V˙O2 using neural networks combined with motion features and heart rate measurements collected with consumer-grade sensors has been shown to yield reasonably accurate V˙O2 for intra-subject estimation. However, estimating V˙O2 with neural networks trained with data from other individuals than the user, known as inter-subject estimation, remains an open problem. In this paper, five types of neural network architectures were tested in various configurations for inter-subject V˙O2 estimation. To analyse predictive performance, data from 16 participants walking and running at speeds between 1.0 m/s and 3.3 m/s were used. The most promising approach was Xception network, which yielded average estimation errors as low as 2.43 ml×min−1×kg−1, suggesting that it could be used by athletes and running enthusiasts for monitoring their oxygen consumption over time to detect changes in their movement economy. [ABSTRACT FROM AUTHOR]

Urban flooding events have emerged as increasingly prevalent and severe natural hazards, owing to the influence of climate change and human-induced activities. However, pedestrian locomotion in floodwater diverges significantly from level ambulation due to the complex interaction between pedestrians and water. To systematically investigate this mechanism of interaction, we propose the integration of a drag force into the social force model to simulate pedestrian movement behavior under floodwater conditions. The modified social force model was conducted for sensitivity parameters analysis and calibrated by three controllable experiments. Based on this calibrated model, an in-depth investigation has been conducted to analyze the influence of water depth and water flow velocity on pedestrians’ movement speed. Simulation results suggest that as water depth gradually incrementally rises, the drop rate of speed in running conditions is notably faster than that of walking conditions no matter what water flow speed and direction was. In addition, we propose a mathematical model capable of predicting pedestrians’ movement speed under floodwater conditions. These findings will offer valuable insights into the risk assessment of pedestrian evacuation in flooding scenarios. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate: a) the differences in external load (EL) during microcycles with four (MIC4) and five training (MIC5) sessions, b) to explore the ratio of weekly training load to the load of the subsequent match, and c) to explore possible correlations between the EL of the MIC4 or MIC5 with the running performance of football players in the following match. The study involved 20 elite youth football players from a team that won the championship in their category that year (age, 16.4 ± 0.3 years). The EL was tracked via GPS in 8 MIC4 and 10 MIC5. Running performance in subsequent matches was also recorded. Two by two ANOVA was employed to compare parameters between MIC5 and MIC4 and Pearson correlation test was applied to examine potential correlations between the training load parameters. The results showed that MIC5 had significantly greater external load in distance parameters in zones 4 & 5, total distance, and decelerations. Differences in running performance in matches were observed only for accelerations (p = .028) and decelerations (p = .02). The ratio of training/match load was lower in all parameters in MIC4 compared to MIC5 but exceeded the match load. Large negative correlations were observed for accelerations and decelerations. In conclusion, additional training in MIC5 increases the load without affecting running performance in the match. Attention should be given to accelerations and decelerations, as their volume can easily increase with the use of small-sided games in training. [ABSTRACT FROM AUTHOR]

The velocity and acceleration of a soccer player varies depending on the specific demands of the field position as well as individual characteristics, establishing the need to determine relative profiles by position. A cross-sectional study was conducted in 18 semi-professional soccer players to determine (i) the specific demands of external load according to playing position, (ii) distances covered at different intensities and the number of sprints, and (iii) the number of accelerations at moderate and high intensity. GPS tracking systems were used to collect data, and the relative acceleration profiles were analyzed based on initial velocity (0–7 km/h; 7.1–14.3 km/h; >14.3 km/h), intensity (moderate 50–75% and high > 75% of maximal acceleration), number of sprints/accelerations, and distance covered. Additionally, relative speed profiles were evaluated through the distance covered at moderate intensity (40–60% Vmax), high intensity (60–75.5% Vmax), very high intensity (>75.5% Vmax), total distance, and number of sprints. Statistically significant differences were observed in the distance covered at moderate and high intensity (midfielders), distance covered sprinting (center backs), and acceleration at moderate and high intensity in all positions (p < 0.05). These findings will enhance the monitoring of external loading strategies and prescription of specific training exercises for soccer players based on their respective playing position, ultimately contributing to optimized performance. [ABSTRACT FROM AUTHOR]

AbstractThe surge in popularity of running has led to a multitude of designs in running shoe technology, notably, there is an increasing trend in toe spring elevation. However, the impact of this design on foot structures during running remains an essential exploration. To investigate the effects of toe spring on the foot during forefoot running, we employed finite element simulation to create two sole models with different toe spring heights (6.5 cm and 8 cm) and ground contact angles (5°, 10°, and 15°). We established and validated two foot-shoe coupling models and compared stress variations in metatarsal bones and the big toe under identical loading and environmental conditions. Higher toe spring resulted in lower peak stress and reduced stress concentration in metatarsal bones. The fourth and fifth metatarsals exhibited increasing stress trends with ground contact angle, with the fifth metatarsal experiencing the most significant stress concentration. In the case of low toe spring, stress on the fifth metatarsal increased from 15.917 MPa (5°) to 27.791 MPa (15°), indicating a rise of 11.874 MPa. Conversely, the first metatarsal showed lower stress, indicating relative safety but reduced functional significance. Moreover, higher toe spring running shoes exerted less pressure on the big toe, with an increasing trend in stress on the big toe with an increase in ground contact angle. Shoes with a higher toe spring design result in reduced pressure on the big toe. Therefore, it is advisable to avoid landing angles greater than 15° to prevent stress fractures resulting from repetitive loading. [ABSTRACT FROM AUTHOR]

Studies on advanced footwear technology (AFT) often investigate potential performance benefits for constraint populations, and high running speeds. This research compared running biomechanics, running economy and perception between males and females, when wearing three different AFT conditions at recreational running speeds. An innovation shoe sample (IM) at confirmation stage in the product creation process was compared to two commercial running shoes (MM, MF). Gender and shoe variable means were compared for main and interaction effects (p < 0.05) by a mixed 2 × 3 repeated measures analysis of variance (RM ANOVA), and effect size estimation. A main effect was seen for shoe condition, both the IM and MF showed higher vertical loading rates than MM, and higher peak vertical force 1. IM had less frontal plane rearfoot motion than both the MM and MF. At the MTPJ, IM had lower maximum dorsiflexion angle, dorsiflexion velocity leading to lower negative power and negative work than both the MM and MF. IM and MF showed significantly lower oxygen consumption than the MM. Perception measurements showed IM and MF to be significantly softer, responsive and had better propulsion than the MM. A main effect was seen for gender, females exhibited higher vertical loading rates, reduced frontal plane ankle motion and lower MTPJ motion, and lower oxygen consumption compared to males. There was no gender effect for perception. Despite biomechanical differences, both IM and MF showed improved performance compared to the MM. Males and females exhibit different biomechanics when wearing AFT, however this did not lead to differences in subjective perception. It is concluded that the specific AFT applied for IM samples in this research functions for both groups largely similarly. [ABSTRACT FROM AUTHOR]

The mdx mouse phenotype, aggravated by chronic exercise on a treadmill, makes this murine model more reliable for the study of Duchenne muscular dystrophy (DMD) and allows the efficacy of therapeutic interventions to be evaluated. This study aims to investigate the effects of photobiomodulation by light-emitting diode (LED) therapy on functional, biochemical and morphological parameters in treadmill-trained adult mdx animals. Mdx mice were trained for 30 min of treadmill running at a speed of 12 m/min, twice a week for 4 weeks. The LED therapy (850 nm) was applied twice a week to the quadriceps muscle throughout the treadmill running period. LED therapy improved behavioral activity (open field) and muscle function (grip strength and four limb hanging test). Functional benefits correlated with reduced muscle damage; a decrease in the inflammatory process; modulation of the regenerative muscular process and calcium signalling pathways; and a decrease in oxidative stress markers. The striking finding of this work is that LED therapy leads to a shift from the M1 to M2 macrophage phenotype in the treadmill-trained mdx mice, enhancing tissue repair and mitigating the dystrophic features. Our data also imply that the beneficial effects of LED therapy in the dystrophic muscle correlate with the interplay between calcium, oxidative stress and inflammation signalling pathways. Together, these results suggest that photobiomodulation could be a potential adjuvant therapy for dystrophinopathies. [ABSTRACT FROM AUTHOR]

When the tractor is undertaking the forestry carrying operation, due to the complex road conditions in the forest, it mostly runs at a low speed, has a high steering demand, and often has a load unit, so it pays more attention to its driving stability and steering sensitivity. In this paper, CarSim software is used to build the physical model and load unit model of the tractor, the control strategy of the tractor is designed based on Simulink software combined with the two-degree-of-freedom dynamic model, and the two-degree-of-freedom model of tractor is established. The braking torque feedback control is carried out by combining the yaw rate and the side deflection angle of centroid with the fuzzy control theory. In addition, the proportional control strategy of front and rear wheel angle is introduced according to the four-wheel steering mode of the tractor. Under the CarSim-Simlulink co-simulation platform, combined with the complex road conditions of forestry operations, the low-speed driving and steering experiments of tractor under different control strategies are carried out. The results show that the control strategy adopted in this paper can effectively reduce the steering radius of the tractor under complex road conditions, increase the steering speed, and limit the side deflection angle of centroid to a small range. The tractor has high stability, the steady state value of yaw rate is closer to the ideal state, and the steering is more sensitive. [ABSTRACT FROM AUTHOR]

Aiming to provide solutions for problems proposed by the inaccurate segmentation of long objects and information loss of small objects in real-time semantic segmentation algorithms, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment-and-fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model's awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses an NVIDIA GeForce RTX 3080 Laptop GPU experiment on the road street view Cityscapes and CamVid datasets, with the average simultaneously occurring ratios reaching 77.1% and 77.4%, respectively, and the running speeds reaching 127 frames/s and 112 frames/s, respectively. The experimental results show that the proposed algorithm can achieve a real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance. [ABSTRACT FROM AUTHOR]