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Purpose: This study examined whether physical demands during soccer matches differ between sea level and altitude, considering variations by playing position. Methods: Thirty-seven professional players were monitored during 22 matches (11 at sea level and 11 at altitudes of 2200–4090 m) with global navigation satellite systems. Independent mean differences were used to compare in-match physical demands (ie, total distance, distance covered at specific speed intervals, accelerations [ACCs] and decelerations [DECs], and maximal speed) between locations for 5 playing positions (central defenders, fullbacks, central midfielders, wide midfielders, and forwards). Results: At altitude, players covered shorter total distances (P <.001) and less distance in the 14.4- to 19.8-km/h (P <.001), 19.8- to 25.2-km/h (P <.001), and >25.2-km/h (P <.001) speed ranges. They also performed fewer ACCs (2.0–3.5 m/s2, P <.001; 3.5–6.0 m/s2, P <.001) and DECs (−3.5 to −2 m/s2, P <.001; −6.0 to −3.5 m/s2, P <.001) and achieved lower maximal speeds (P <.001). The impact of altitude varied by position: Central midfielders showed reduced performance in all variables, while central defenders (distance > 25.2 km/h, ACCs [2.0 and 3.5 m/s2], DECs [−3.5 and −2.0 m/s2], and maximal speed), fullbacks (distance > 25.2 km/h, ACCs, and DECs [−3.5 and −2.0 m/s2]), and forwards (distances [total, 19.8–25.2 km/h, and >25.2 km/h] and ACCs [−3.5 and −6.0 m/s2]) presented unclear differences (P >.05) between locations. Conclusion: Our study highlights the importance of considering playing positions when assessing the in-match activity profiles of sea-level resident soccer players competing at moderate to high altitudes. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chronic myofascial trigger points can identify differential metabolite changes through non targeted metabolomics techniques, helping to understand and further explore the pathophysiological processes and pathogenesis of chronic myofascial trigger points from the perspective of endogenous small molecule metabolites. OBJECTIVE: To investigate potential biomarkers and related metabolic pathways based on urine metabolomics in the rat model of chronic myofascial trigger points. METHODS: Sixteen Sprague-Dawley rats were randomly divided into a model group and a normal group. The model group was used to establish a chronic myofascial trigger point animal model by combining blunt hitting with centrifugal exercise (treadmill slope: -16°, running speed: 16 m/min, training time: 90 minutes each), once a week for 8 continuous weeks, with 4 weeks off. After 12 weeks of modeling, the metabolic cage method was used to collect urine from rats at 24 hours after modeling. Liquid chromatography-mass spectrometry non-targeted metabolomics technology was used to detect metabolic profiles in the urine samples, screen common differential metabolites, and conduct bioinformatics analysis. RESULTS AND CONCLUSION: Compared with the normal group, there were 32 differential metabolic markers in the model group, of which 21 were upregulated and 11 were downregulated. A total of 14 differential metabolites were identified as potential biomarkers based on the value of variable important in projection greater than 3. The enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes indicated that the formation of chronic myofascial trigger points is closely related to metabolic pathways such as primary bile acid biosynthesis and arachidonic acid metabolism. [ABSTRACT FROM AUTHOR]

Place and grid cells provide a neural system for self-location and tend to fire in sequences within each cycle of the hippocampal theta rhythm when rodents run on a linear track. These sequences correspond to the decoded location of the animal sweeping forward from its current location ("theta sweeps"). However, recent findings in open-field environments show alternating left-right theta sweeps and propose a circuit for their generation. Here, we present a computational model of this circuit, comprising theta-modulated head-direction cells, conjunctive grid × direction cells, and pure grid cells, based on continuous attractor dynamics, firing rate adaptation, and modulation by the medial-septal theta rhythm. Due to firing rate adaptation, the head-direction ring attractor exhibits left-right sweeps coding for internal direction, providing an input to the grid cell attractor network shifted along the internal direction, via an intermediate layer of conjunctive grid × direction cells, producing left-right sweeps of position by grid cells. Our model explains the empirical findings, including the alignment of internal position and direction sweeps and the dependence of sweep length on grid spacing. It makes predictions for theta-modulated head-direction cells, including relationships between theta phase precession during turning, theta skipping, anticipatory firing, and directional tuning width, several of which we verify in experimental data from anteroventral thalamus. The model also predicts relationships between position and direction sweeps, running speed, and dorsal-ventral location within the entorhinal cortex. Overall, a simple intrinsic mechanism explains the complex theta dynamics of an internal direction signal within the hippocampal formation, with testable predictions. • Shows how firing rate adaptation produces left-right theta sweeps in grid cells • Models the interaction between internal signals for direction and location • Explains how theta sweeps relate to theta skipping in direction cells • Predicts theta phase coding of turning angle in head-direction cells Ji, Chu et al. present a network model of direction and grid cells, which generates an internal direction signal comprised of alternating left-right sweeps of encoded location and direction, based on attractor dynamics, firing rate adaptation, and theta modulation. The model explains existing data from foraging rodents and makes testable predictions. [ABSTRACT FROM AUTHOR]

Traditional methods for collecting ground reaction forces (GRFs) mainly use lab force plates. Previous research broke this pattern by predicting GRFs with deep learning and data from IMUs like joint acceleration. Joint angle, as a geometric, is easier to collect than acceleration outdoors with cameras. LSTM is one of the deep learning models that have shown good performance in biomechanical studies. xLSTM, as an optimized version of LSTM, has not been used in biomechanical studies and no research has predicted GRFs during running solely using lower limb joint angles. This study collected lower-limb joint angle and vertical ground reaction force data at five speeds from 12 healthy male runners with Xsens sensors. Datasets including three joints and three planes were set as the inputs of four deep learning models for vertical-GRF prediction. CNN-xLSTM consistently performed best in the four deep learning models when different datasets were input (R2 = 0.909 ± 0.064, MAPE = 2.18 ± 0.09, rMSE = 0.061 ± 0.008), and the performance was at a relatively high level at the five speeds. The current findings may contribute to a new GRF measurement and provide a reference for future real-time motion detection and sport injury prediction. [ABSTRACT FROM AUTHOR]

During breaks or playing period changes, players' accumulated workload, physiological alterations, body composition factors, sleep, and health-related qualities can factor into soccer performance. This research examined the impact of prolonged pauses, including breaks due to the 2022 FIFA World Cup and an earthquake tragedy, on running displacements and ball in-play duration during the 2022/23 Turkish Super League season. The secondary purpose was to determine the relationship between performance metrics and competition outcomes (i.e., wins, losses, or draws). 550 players from 19 Turkish Super League teams were included. Performance metrics such as running speed, accelerations/number of speed actions, total field coverage, and match outcomes (i.e., win, lose, or draw) were analyzed before and after significant pauses in play. We also explored correlations between running speed, number of speed actions, match duration, and total distance covered to understand their influence on soccer performance. Significant differences existed in performance metrics between periods, with higher total displacement and running observed after the World Cup (p < 0.05). Additionally, teams exhibiting more static behavior during matches were likelier to lose points, while those running at higher speeds (p = 0.007) and acceleration (p = 0.008) had a higher winning probability. The findings provide valuable insights into the factors affecting success or failure in soccer matches and have implications for training and preparation strategies in professional soccer. In addition, findings illustrate how breaks influence performance metrics and highlight the challenges coaches face in maintaining player readiness during unplanned pauses. This suggests minimizing such disruptions to support optimal training and preparation strategies in professional soccer. [ABSTRACT FROM AUTHOR]

Background: Since children's daily activities are mostly anaerobic, it is important to assess anaerobic performance as part of the physical assessment. Therefore, running speed, power, and heart rate during repetitive sprints were investigated. Method: A total of 118 children participated (mean age:11.5 range 9-14y; 48% boys, 52% girls) and performed the children's repetitive and intermittent sprinting performance (CRISP) test, which consists of six sprint runs performed at maximal speed over 30-meter with short recovery periods (10 s) between each run. GLM Repeated Measures were used to examine the effect of runs (within-subject factor) and age and sex (between-subject factor) and as well as possible interactions for running time, power, and heart rate. Results: Running times increased significantly across runs (p < 0.001, large effect size), showing a non-linear slowdown (p = 0.013). Also, a main effect of age, [p < 0.033] and sex [p < 0.011, medium effect size] emerged. However, interaction effects showed that girls fatigued more in the second half of the test, which led to larger differences with the boys in the later runs of the CRISP. Moreover, the interaction effect of age-by-run-by-sex was found. Eleven-year-old children had the longest running times. At the same time, young children, predominantly boys, showed less fatigue, as their last runs were comparable in time to the first ones. Analysis of the power showed a main effect of age, indicating more power in older children [p < 0.001, large effect size], especially after 11 years. No differences between sexes were found for power. Heart rate increased significantly during the repetitive sprinting [p < 0.001, large effect size]. No differences for age or sex were found for mean or peak heart rate. Conclusion: The CRISP test is sensitive to running fatigue [large effect size] and distinguishes between the performance characteristics of children according to age and sex. Running speed and power go up between 12 and 14 years. Girls run slower but generate comparable power over the runs. Yet they fatigue more in the second half of the test than boys. [ABSTRACT FROM AUTHOR]

Energy-efficient spikformer has been proposed by integrating the biologically plausible spiking neural network (SNN) and artificial transformer, whereby the spiking self-attention (SSA) is used to achieve both higher accuracy and lower computational cost. However, it seems that self-attention is not always necessary, especially in sparse spike-form calculation manners. In this article, we innovatively replace vanilla SSA (using dynamic bases calculating from Query and Key) with spike-form Fourier transform, wavelet transform, and their combinations (using fixed triangular or wavelets bases), based on a key hypothesis that both of them use a set of basis functions for information transformation. Hence, the Fourier-or-Wavelet-based spikformer (FWformer) is proposed and verified in visual classification tasks, including both static image and event-based video datasets. The FWformer can achieve comparable or even higher accuracies (0.4%–1.5%), higher running speed (9%–51% for training and 19%–70% for inference), reduced theoretical energy consumption (20%–25%), and reduced graphic processing unit (GPU) memory usage (4%–26%), compared to the standard spikformer. Our result indicates the continuous refinement of new transformers that are inspired either by biological discovery (spike-form), or information theory (Fourier or Wavelet transform), is promising. [ABSTRACT FROM AUTHOR]

Our movements result in predictable sensory feedback that is often multimodal. Based on deviations between predictions and actual sensory input, primary sensory areas of cortex have been shown to compute sensorimotor prediction errors. How prediction errors in one sensory modality influence the computation of prediction errors in another modality is still unclear. To investigate multimodal prediction errors in mouse auditory cortex, we used a virtual environment to experimentally couple running to both self-generated auditory and visual feedback. Using two-photon microscopy, we first characterized responses of layer 2/3 (L2/3) neurons to sounds, visual stimuli, and running onsets and found responses to all three stimuli. Probing responses evoked by audiomotor (AM) mismatches, we found that they closely resemble visuomotor (VM) mismatch responses in visual cortex (V1). Finally, testing for cross modal influence on AM mismatch responses by coupling both sound amplitude and visual flow speed to the speed of running, we found that AM mismatch responses were amplified when paired with concurrent VM mismatches. Our results demonstrate that multimodal and non- hierarchical interactions shape prediction error responses in cortical L2/3. [ABSTRACT FROM AUTHOR]

The article explores the metabolism of dinosaurs, particularly when running at maximum speed, by connecting their metabolism with kinetic energy. The methodology developed allows students to determine the maximum metabolism of dinosaurs, such as the Velociraptor, running at their fastest. The study provides insights into the lives of dinosaurs and engages students in understanding the complex relationship between metabolism, body mass, and locomotion speed. The research highlights the importance of considering the metabolic rates of animals when studying their locomotion and energy expenditure. [Extracted from the article]

Purpose: The water-lubricated hydrodynamic herringbone groove journal bearing (HGJB) is capable of running at high speed. However, when running at a low speed, it suffers from a low load-carrying capacity due to the weak hydrodynamic effect. To overcome this problem, this study proposes a hybrid water-lubricated HGJB and aims to investigate its dynamic characteristics. Design/methodology/approach: A hybrid lubrication model applicable to the hybrid water-lubricated HGJB is established based on the boundary fitted coordinate system, which considers the turbulent, thermal and tilting effects, and the finite difference method is used to calculate the dynamic characteristics of the hybrid water-lubricated HGJB. Findings: The result shows that the hybrid HGJB has larger dynamic coefficients and better system stability compared with the hydrodynamic HGJB when running at low speed. Furthermore, the stiffness of hybrid HGJB are mainly governed by the hydrodynamic effect rather than the hydrostatic effect when running at high speed. Originality/value: The proposed hybrid water-lubricated HGJB shows excellent dynamic characteristics at either low speed or high speed; and the hybrid water-lubricated HGJB has a large load-carrying capacity when running at low speed and has a good dynamic stability when running at high speed. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0233/ [ABSTRACT FROM AUTHOR]

Multi-object tracking (MOT) in satellite videos is a challenging task due to the small size and blurry features of objects, which often lead to intermittent detection and tracking instability. Many existing object detection and tracking models often struggle with these issues, as they are not designed to effectively handle the unique characteristics of satellite videos. To address these challenges, we propose LocaLock, a joint detection and tracking framework for MOT that incorporates feature matching concepts from single object tracking (SOT) to enhance tracking stability and reduce intermittent tracking results. Specifically, LocaLock utilizes an anchor-free detection backbone for efficiency and employs a local cost volume (LCV) module to perform precise feature matching in the local area. This provides valuable object priors to the detection head, enabling the model to "lock" onto objects with greater accuracy and mitigate the instability associated with small object detection. Additionally, the local computation within the LCV module ensures low computational complexity and memory usage. Furthermore, LocaLock incorporates a novel motion flow (MoF) module to accumulate and exploit temporal information, further enhancing feature robustness and consistency across frames. Rigorous evaluations on the VISO dataset demonstrate the superior performance of LocaLock, surpassing existing methods in tracking accuracy and precision within the demanding satellite video analysis domain. Notably, LocaLock achieved state-of-the-art performance on the VISO benchmark, achieving a multi-object tracking accuracy (MOTA) of 62.6 while ensuring fast running speed. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the influence of training status on the percentage of maximum oxygen consumption, heart rate and velocity (%VO2max, %HRmax and %Vmax) at which ventilatory threshold 1 and ventilatory threshold 2 occur (VT1 and VT2, respectively), in males and females separately considering age, during a ramp incremental treadmill test. Methods: 791 males (36.8 ± 9.9 years) and 301 females (33.9 ± 11.0 years) performed a ramp incremental exercise test until fatigue where VT1 and VT2 were determined. Participants were classified as low, medium or high training status combining the oxygen consumption at VT1, VT2 and VO2max by clustering analysis. Results: VO2max is poorly correlated with the %VO2max, %HRmax and %Vmax at which VT1 and VT2 occur (r < 0.3), in contrast, there is a positive correlation between oxygen consumption at VT1 and VT2 with the %VO2max, %HRmax and %Vmax at which VT1 and VT2, respectively, occur in males and females (r = 0.203–0.615). Furthermore, we observed the %VO2max, %HRmax and %Vmax at which thresholds occur were greater the higher the training status (all p < 0.003). Conclusion: The physiological determinants of the percentage of maximum at which VT1 and VT2 occur are more related to oxygen consumption at VT1 and VT2, respectively, than to VO2max. Moreover, due to the higher percentage of maximum at which VT1 and VT2 occur in individuals with a higher training status, the common strategy consisting of establishing exercise intensity as a fixed percentage of maximum might not be effective to match intensity across individuals with different training status. Clinical trial registration: NCT06246760. [ABSTRACT FROM AUTHOR]

The purpose of this study was to compare the activity profile of elite Gaelic football referees (GFR) between the National Football League (NFL) and the All-Ireland Championship (AIC), and across the four divisions of the NFL and three phases of the AIC. Match activity data was collected during 125 NFL and 201 AIC games using 10-Hz global positioning system technology from 41 elite GFR. Game duration, total distance, very low-speed movement (<0.70 m·s−1), walking (≥0.70–1.65 m·s−1), low-speed running (≥1.66–3.27 m·s−1), moderate-speed running (≥3.28–4.86 m·s−1), high-speed running (≥4.87–6.48 m·s−1), very high-speed running (≥6.49 m·s−1) distance, and peak running speed were compared between competitions. Games in the AIC were longer than in the NFL (ES = 0.59) but the total distance was similar between the NFL (119.6 ± 9.5 m·min−1) and AIC (122.6 ± 8.4 m·min−1, ES = 0.11). No other differences were found between the NFL and AIC or across the four divisions of the NFL and three phases of the AIC, except for a higher peak running speed during the All-Ireland Series (6.93 ± 0.52 m·s−1) than the All-Ireland Qualifiers (6.65 ± 0.46 m·s−1, ES = 0.35). This information can be used to design specific conditioning programmes to ensure optimal physical development of GFR at all competitive levels. [ABSTRACT FROM AUTHOR]

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This study aimed to investigate the relationship between overground sprint performance and rates of force development (RFDs) in ground reaction forces (GRF) during the entire acceleration phase. Thirty-one male sprinters performed 60-m sprints during which the GRF from the start to the 50-m mark were measured. The vertical, braking and propulsive RFDs at each step were calculated as the average rate of change in GRF. Average values for each four steps during the acceleration phase were calculated to examine relationships between running speed or average horizontal external power (AHEP) and RFD values. The RFD values ranged from 859.8 ± 191.1 to 1682.0 ± 258.2 N/s/kg for vertical force, −502.6 ± 215.7 to −1033.8 ± 196.2 N/s/kg for braking force, and 97.2 ± 11.7 to 185.4 ± 32.3 N/s/kg for propulsive force. There were associations of running speed with vertical RFD at the 21st–24th step section (r = 0.385) and with propulsive RFD at the 1st–4th step section and from the 13th–16th to 21st–24th step sections (r = 0.386–0.559). Moreover, AHEP was correlated with vertical RFD from the 13th–16th to 21st–24th step sections (r = 0.442–0.523), with braking RFD at the 17th–20th and 21st–24th step sections (r = − 0.423 and − 0.448), and with propulsive RFD at every step section (r = 0.374–0.856). In conclusion, greater propulsive RFD throughout the acceleration phase, along with higher braking and vertical RFD during the later acceleration section, may indicate better sprint performance. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the affective responses to running with imposed velocity or self-selected time trials in runners, as well as the effects on volume load (VL) and training impulse (TRIMP). Anxiety was also determined. We established the level of association between the dependent variables. Methods: Three visits were carried out. The 1st visit consisted of a maximum running effort test (VO2Max). In the 2nd and 3rd visits, participants were divided between the time limit (TLim) or time trial 1000 m running at self-selected intensity (T1000). Participants responded to the felt arousal, feeling, and anxiety SUDS scale before, during, and after TLim and T1000. Results: TLim vs. T1000 (p < 0.001) and VPeak × V1000 (p = 0.013) showed differences, but did not influence VLTLim vs. VL1000 (3181.34 ± 872.22 vs. 3570.60 ± 323.3; p = 0.062). TRIMP showed no differences (p = 0.068). Arousal did not differ between the pre-exercise (p = 0.772) and post-exercise (p = 0.083) conditions but was different during (p = 0.035). There were differences between groups in the pre-exercise (p = 0.012), during (p < 0.001), and post-exercise (p < 0.001) conditions for feeling and anxiety scores. The correlation between TRIMP and affective scores showed an association with TLim (r = 0.46; p = 0.043). Conclusion: The self-selected exercise generated positive affective responses, but the same did not occur for the imposed TLim. VL and TRIMP presented equality. There was association between TRIMP and the TLim feeling scale. TLim significantly increased anxiety scores. [ABSTRACT FROM AUTHOR]

The lactate threshold (LT) and the associated running velocities are important markers used to define physical readiness and prescribe exercise intensity in athletes. This study examined blood LT during maximal cardiopulmonary exercise testing using four methods: visual inspection, log-to-log transformation, the Dmax method, and the 4 mmol/L fixed blood lactate accumulation (FBLA) method. The participants included 96 soccer players, comprising 52 professional (27.37 ± 5.67 years) and 44 elite youth players (16.20 ± 0.8 years). A total of 554 capillary blood lactate samples were analyzed. Bland–Altman and ICC analyses for running velocities, determined using the four LT detection methods, demonstrated poor agreement in both groups. Results indicated that the youth players had significantly (p < 0.05) higher V̇O2 max (59.89 ± 5.6 mL·kg−1·min−1) compared to the professional players (56.43 ± 4.81 mL·kg−1·min−1). However, the professional players had significantly better running performance and running economy. A two-way ANOVA revealed a main effect of playing standard, with professional players exhibiting significantly higher 4 mmol/L FBLA LT compared to youth players. A mixed-design ANOVA indicated a significant (p < 0.01) interaction, with the youth exhibiting higher lactate accumulation only after completing the 18 km/h stage. Therefore, youth and professional players should not use the different LT concepts interchangeably. Additionally, the 4 mmol/L FBLA LT method appears to be more robust for youth soccer players. [ABSTRACT FROM AUTHOR]

This study aimed to examine the relationships between isometric mid-thigh pull maximal force (IMTPF), sprint mechanics, and performance. Fifteen national-level track and field athletes (sprinters and hurdlers) performed three maximal-effort isometric mid-thigh pulls on a force plate and two 30 m sprints. The IMTPF, the sprint mechanical variables (theoretical maximum horizontal force (F0), velocity (v0), and power (Pmax)), as well as the sprint performance data at 5 m distance intervals, were collected. Pearson's product–moment correlation analysis revealed large linear associations between IMTPF and v0 (r = 0.65, R2 = 0.42, p = 0.009), as well as negative linear relationships between IMTPF and sprint times of 15 m (r = −0.53, R2 = 0.28, p = 0.043), 20 m (r = −0.55, R2 = 0.30, p = 0.033), 25 m (r = −0.57, R2 = 0.33, p = 0.025), and 30 m (r = −0.60, R2 = 0.36, p = 0.019). The F0, Pmax, and sprint times to 5 m and 10 m were not significantly correlated with the IMTPF (p < 0.05). The study results highlight that during the late acceleration phase (>15 m), the capacity to generate horizontal force at high running velocities is related to the ability to develop maximal force during isometric contractions. [ABSTRACT FROM AUTHOR]

The purpose of this work was to provide a fundamental, in-depth analysis of kinematics and kinetics of the bobsleigh push phase to establish a basis for performance analysis and enhancement. Fifteen elite male athletes performed maximal effort push starts, while ground reaction forces (GRF) and 3D marker trajectories were simultaneously recorded for ground contacts of different sub-sections of the push phase (start acceleration phase: first and second ground contact after the initial push-off from the start block, acceleration phase: 10 m and high-velocity phase: 30 m). To obtain a comprehensive view of the push phase, whole-body kinematics as well as joint kinetics were analysed and compared across the push phase. The results showed that propulsion during the start acceleration was hip extensor dominant. With increasing running speed, the contribution to propulsion increased at the ankle and decreased at the knee. In contrast to unresisted sprinting, bobsleigh athletes relied more on mechanical energy generation at the hip than at the ankle, especially during start acceleration. These findings should be considered for the strength and conditioning of bobsleigh athletes and further investigated in relation to a suitable performance measure. [ABSTRACT FROM AUTHOR]

The precise and effective identification of track irregularity is of great significance in ensuring the safety of train operations. The study proposes a novel deep learning model BiLSTM-AM, Bi-directional Long Short-Term Memory (BiLSTM) model incorporating attentional mechanisms (AM), for indirectly identifying track irregularity by utilizing in-service vehicle acceleration responses. The BiLSTM containing a forward LSTM network and a backward LSTM network is employed to capture the dependence of vehicle acceleration and track irregularities at different locations. The joining of AM can further improve the accuracy and robustness of the model by emphasizing the importance of the key information that has a substantial impact on the identification results. The identification precision is verified by comparing the different types of identified track irregularities with the true values, and its applicability and robustness are further investigated by parameter study for the effects of key parameters, including the number of inputting acceleration responses, running speed, noise level and bridge damping ratio. The results indicate that the model applies to the identification of track irregularity in several complex scenarios, even for the speed running at 350 km/h, bridge damping ratios of 0.05, and noise levels up to 20%. Besides, the great significance of the proposed model is that only one vehicle acceleration is required to obtain satisfactory recognition accuracy in practical applications. [ABSTRACT FROM AUTHOR]

For overcoming space limitations and load-bearing defects of traditional conjugate cam shedding on looms, a novel cam shedding system with double-shaft was developed by incorporating mechanism analysis, theoretical calculations, modeling and simulation, and experimental verification. The lifting motion of the heald frame is controlled by the cosine acceleration law, with MATLAB compiling the reverse program of the cam theoretical profile. A functional digital prototype is created in ADAMS/View using planar rod groups, gear transmission, and conjugate cam mechanism. The simulation results of considering yarn tension exhibited highly consistent swing arm and heald frame motion curves with numerical calculations, and the dynamic performance of the shedding system is affected by yarn tension, which leads to an increase in motor torque and acceleration oscillation in the low-frequency domain. Furthermore, an experimental proportional model was produced using 3D printing technology and tested for motion performance at varying rotational speeds, verifying the design's theoretical accuracy and practical feasibility, indicating that this mechanism runs smoothly and reliably in lifting and returning the heald frame by cam; meanwhile, the yarn deformation and shed characteristics are apparent, meeting the requirements of the shedding weaving process of plain fabric. The work in this paper effectively solves the problem of contact wear between the cam and rotor, which is conducive to design innovation and performance improvement of the conjugate cam shedding on high-speed looms. [ABSTRACT FROM AUTHOR]

This research combines the NAO robot platform to develop three single scene modes (visual line-following navigation, object location and grabbing, and moving object tracking and obstacle avoidance), and finally through the frame based expert system to form a knowledge base of each mode, and uses the inference engine to achieve multi-mode fusion. In the development of visual line-following navigation, the proposed fast path extraction processing method can not only accurately extract the path information in the case of noisy interference, but also improve the running speed to ensure the real-time performance of the robot. A slope compensation PID controller is proposed to control the parameters of the robot during walking, which ensures low error and high stability when the robot follows the navigation line. In the development of object positioning and grabbing, a monocular localization algorithm is proposed using the characteristics of QR code, then the kinematics of the robot arm is modeled. Finally, the end effector of the robot is moved to the specified position according to the three-dimensional coordinates of the QR code to grasp the target object. In the development of moving object tracking and obstacle avoidance, the NaoMark marker is used to simplify the characteristics of the moving target, and the parameters of the robot walking are controlled according to the central position of the marker in the image. In order to avoid the collision of the robot with the obstacle during the movement, the obstacle avoidance is realized by combining the ultrasonic sensor measurement and the artificial potential field algorithm. Finally, the implementation methods of each part of the above three modes are formed into a knowledge base in the form of a framework based expert system, and the knowledge is combined by the inference engine to realize the fusion of multiple modes to complete tasks that require multiple modes. This research has presented an original solution, as a model, which can enable robots to perform complex service tasks consisting of multiple connected actions in a dynamic environment. This proposed methodology can let the intelligent operation of the robot serve in different scenes and fast response based on its actual requirements. This studying will enhance the prototype robot vision function and development of additional value for consolidation robot mobility based on multi-mode fusion to increase service robots in the home environment of intelligent control capability. In future, it will be extended to the hospital medical care and public safety, and other professional purpose. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to evaluate the effect of an Athletic Performance Program (APP), implemented as a complement to the usual training routines of a professional football team, on match performance variables in professional football players. The APP was designed to target mobility, stability, strength, multidirectional and sprint skills, which are critical for performance during competitive matches. Methods: A prospective quasi-experimental study was conducted over three consecutive seasons. Fifty-four professional football players were randomly allocated into a control group (CG, n = 25) and an experimental group (EG, n = 29). During the in-season period, both groups followed the standard training routines prescribed by the coaching staff. Additionally, the CG performed a general supplementary physical fitness program five times per week, while the EG undertook the APP with the same frequency. The APP included indoor track sessions and micro-doses of on-field stimuli, focusing on specific performance attributes. The interventions lasted 10 weeks. Performance metrics were assessed pre- and post-intervention using GPS to measure match-related variables (total running distance, sprint distance, number of sprints, and peak running speed) and countermovement jump tests to evaluate vertical jumping ability. A two-way ANOVA (2 × 2; group and time) was employed to analyze the effects of the interventions and their interaction. Results: Significant group × time interaction effects were observed for total running distance (F = 51.853, P < 0.001), sprint distance (F = 197.610, P < 0.001), number of sprints (F = 86.923, P < 0.001), and peak running speed (F = 81.351, P < 0.001) during matches. Post-hoc pairwise comparisons revealed that only the EG showed improvements across all performance variables: total running distance (117.5 ± 5.20 to 123.1 ± 3.5 m/min, P < 0.001), sprint distance (6.45 ± 1.43 to 8.35 ± 1.22 m/min, P < 0.001), number of sprints (0.14 ± 0.03 to 0.16 ± 0.03 sprint/min, P < 0.001), and peak running speed (31.1 ± 1.3 to 32.1 ± 1.0 km/h, P < 0.001). Conversely, the CG exhibited significant declines in these metrics post-intervention (P < 0.001). Discussion: The findings demonstrate that integrating a 10-week multicomponent Athletic Performance Program into traditional training routines is effective in enhancing match performance variables, particularly in high-intensity actions such as sprints and running speed. The APP's focus on mobility, stability, strength, and sprint-specific skills likely contributed to these improvements, highlighting the importance of targeted supplementary training for optimizing athletic performance in professional football players. The observed decline in the CG emphasizes the need for specialized interventions to maintain and improve performance during the season. [ABSTRACT FROM AUTHOR]

We are currently developing a suit that assists human running motion based on the Smart Suit (SS). The SS is a wearable assistive device that intervenes in trunk kinetic chain movements by linking trunk rotation to hip flexion and extension through elastic belts. By intervening in the trunk kinetic chain, our goal is to enhance stiffness, thereby improving running economy and speed. The purpose of this study is to acquire fundamental insights into the changes in leg and trunk rotational stiffness induced by the SS, as well as the underlying mechanisms. We defined the SS torque intervention rate p ss , which focuses on the magnitude of force, and the peak time difference index, e lag , between SS and humans, which focuses on the timing of force, and analyzed the relationship between the stiffness change rate due to SS wearing. The results of the analysis suggest that SS affects human running sensitively rather than mechanically. We also confirmed that the degree of adaptation to SS, assessed by the timing gap between SS exertion and human exertion, contributes significantly to changes in trunk rotation stiffness. [ABSTRACT FROM AUTHOR]

Our aim was to validate a sacral-mounted inertial measurement unit (IMU) for reconstructing running kinematics and comparing movement patterns within and between runners. IMU data were processed using Kalman and complementary filters separately. RMSE and Bland–Altman analysis assessed the validity of each filtering method against a motion capture system. Running data from 24 recreational runners were analyzed using Fourier transform coefficients, PCA, and k-means clustering. High agreement was found for Kalman-filtered data in the frontal, sagittal, and transverse planes, with a Bland–Altman bias of ~2 mm on average, compared to a bias of ~10.5 mm for complementary-filtered data. Pelvic angles calculated from Kalman-filtered data had superior agreement, with systematic biases of ~0.3 versus 3.4 degrees for complementary-filtered data. Our findings suggest that inertial sensors are viable alternatives to motion capture for reconstructing pelvic running kinematics and movement patterns. In the second part of our study, negligible intra-individual differences were observed with changes in speed, while inter-individual differences were large. Two clusters of runners were identified, each showing distinct movement patterns and ranges of motion. These observations highlight the potential usefulness of inertial sensors for performance analysis and rehabilitation as they may permit the use of individual-specific and cluster-specific practice programs. [ABSTRACT FROM AUTHOR]

Objective: This study aims to evaluate the effects of a 20-week endurance and strength training program on running economy and physiological, spatiotemporal, and neuromuscular variables in trained runners. Methods: A total of 18 runners (13 males and 5 females) completed a running economy test (2 bouts of 5 min at 3.06 m·s−1 for females and at 3.61 m·s−1 for males) and a graded exercise test (5 min at 2.78 m⋅s−1, with speed increasing by 0.28 m⋅s−1 every 1 min until volitional exhaustion). During the training program, the participants completed different low-intensity continuous running sessions, high-intensity interval running sessions, and auxiliary strength training sessions. Results: Running economy, measured as oxygen cost and energy cost, increased by 4% (p = 0.011) and 3.4% (p = 0.011), respectively. Relative maximal oxygen uptake (VO2max) increased by 4.6%. There was an improvement in the speed associated with the first (VT1) and the second ventilatory threshold and with the maximal aerobic speed by 9.4, 3.7, and 2.8% (p = 0.000, p = 0.004, and p = 0.004, respectively). The %VO2max value of VT1 increased by 4.8% (p = 0.014). Conclusions: These findings suggest that a 20-week endurance and strength training program significantly improves performance and physiological factors without changing the runner's biomechanics. [ABSTRACT FROM AUTHOR]

The variable universe fuzzy controller can realize the continuous control of the whole operation process of the independent metering control excavator, which significantly improves the operation performance and energy saving. However, VUFC fuzzy rules are designed according to expert experience and debugging many times. VUFC design process lacks of effective design methods, and has great randomness. The optimal state of VUFC fuzzy rules and relevant parameters such as universe cannot be ensured. Artificial neural network is a parallel distributed system, which overcomes the defects of traditional artificial intelligence based on logical symbols in processing intuitive and unstructured information. It also has the advantages of self-adaptation, self-organization and real-time learning. In this paper, the neural network learning algorithm is introduced into the fuzzy inference system to optimize the structure and parameters of the fuzzy controller. ANFIS is trained according to the input and output data of the system to obtain a fuzzy controller. Compared to traditional fuzzy controller, ANFIS can reduce the influence of subjective factors in the design process on the controller. Through the simulation model of 37-ton IMC excavator, the ANFIS controller is verified to have better control performance than VUFC. In the process of lifting and lowering the boom, the ANFIS controller has a more stable running speed, significantly reduces pressure and flow fluctuation amplitude. [ABSTRACT FROM AUTHOR]

To solve the torque distribution problem of pure electric commercial vehicles driven by dual motors, the fuzzy control strategy based on particle swarm optimization (PSO) was proposed. The physical model of the vehicle power system was established in Simulink/Stateflow software, and the vehicle torque was distributed based on PSO algorithm. Due to the large amount of calculation and being not suitable for the real vehicles, according to the calculation results of PSO algorithm and the traditional project experience, the fuzzy controller with real-time parameter adjustment was designed to carry out torque distribution with high running speed and basically global optimization effect of PSO. The verification and analysis results show that compared with the original single motor power system, the energy consumption of the dual motor power system is reduced by 12.08%. Compared with the average distribution control strategy, the total motor loss is reduced by 13.09% in dual motor power system. [ABSTRACT FROM AUTHOR]

Runners often reduce their pace during inclined running to maintain a constant metabolic workload, known as iso-efficiency speed (a speed-incline combination with the same metabolic intensity as level running). This study investigates changes in lower extremity (LE) joint work profiles when running on an incline at iso-efficiency speed. Eleven collegiate distance runners completed a treadmill running task under three conditions (0%, 4%, and 8% incline). Running velocity was reduced with increasing incline to ensure a consistent metabolic workload across conditions. An 8-camera motion capture system and an instrumented treadmill collected kinematics and ground reaction forces. Visual 3D was used to calculate ankle, knee, and hip joint powers, while custom software (MATLAB) calculated ankle, knee, and hip joint positive and negative work values. A significant increase in LE total positive work was attributed to greater ankle and hip joint positive work with steeper inclines. Reduced LE total negative work resulted from lower knee and hip joint negative work as incline increased. Results suggest that at iso-efficiency speeds, inclined treadmill running increases eccentric demands on the ankle joint and concentric demands on the ankle and hip joints, benefiting training programmes to optimize cardiorespiratory stimuli while reducing mechanical demand on specific extremity structures. [ABSTRACT FROM AUTHOR]

Aiming at the problems of insufficient lightweight and slow running speed of vehicle and pedestrian detection model in autonomous driving scenarios, a vehicle and pedestrian detection algorithm based on improved YOLOv8 (You Only Look Once version 8) was proposed to realize an intelligent, safe, and efficient autonomous driving system. First, FasterBlock in FasterNet replaces the Bottleneck in C2f, which reduces the number of parameters in the model and improves the model's real-time detection performance. Second, the EMA attention mechanism is used to fuse with C2f-Faster to improve the feature fusion ability of the model, and a new C2f-Faster-EMA module is designed to replace part of C2f. Then, the object detection head Dynamic Head based on the attention mechanism is introduced, and the deformable convolutional DCNV3 is used to replace the deformable convolutional DCNV2 in Dynamic Head. A new Dyhead-DCNV3 module is designed to replace the original detection head Detect. Finally, the ablation experiment verifies the function of each module of the improved model, and each module's contribution to the target detection performance is analyzed. Experimental results show that compared with the original model, the mAP of the improved model in the customized automatic driving scene data set is increased by 1.4%; the parameters of the model are reduced by 5.7%; and the running speed of the model is up to 178.6 FPS, which is very competitive with other algorithms. [ABSTRACT FROM AUTHOR]

The present study examined the effects of gastric emptying rate and intestinal cell damage following a single session of endurance exercise under "hypoxic" or "normoxic" conditions at the same relative intensity. Eleven healthy males performed two trials on different days, consisting of a 60 min run on a treadmill at 70% maximal running velocity (vMax) while inspiring hypoxic (FiO2: 14.5%; HYP) or normoxic air (FiO2: 20.9%; NOR). The average running velocity was 11.4 ± 0.7 km/h in NOR and 10.8 ± 0.5 km/h in HYP, respectively. Venous blood samples were collected to evaluate plasma intestinal fatty acid binding protein (I-FABP) as an indicator of exercise-induced intestinal cell damage. The gastric emptying rate was determined by the 13C-sodium acetate breath test. Running velocities at 70% vMax and arterial oxygen saturation were significantly lower under HYP than NOR (p < 0.001). Peak heart rate and rating of perceived exertion during exercise did not differ significantly between the trials. Maximum 13C excretion time (an indication of the gastric emptying rate) was significantly delayed in the HYP (NOR: 38.5 ± 5.0 min, HYP: 45.5 ± 9.6 min; p = 0.010). Furthermore, the score of nausea increased slightly, but increased significantly after exercise only in the HYP (p = 0.04). However, exercise-induced changes in plasma I-FABP, adrenaline, and noradrenaline concentrations did not differ significantly between the two trials. These results suggest that endurance exercise under hypoxic conditions impairs digestive function in the stomach compared to exercise under normoxic conditions performed at the same relative intensity. [ABSTRACT FROM AUTHOR]

The short-term scaling exponent of detrended fluctuation analysis (DFAα1) applied to interbeat intervals may provide a method to identify ventilatory thresholds and indicate systemic perturbation during prolonged exercise. The purposes of this study were to (i) identify the gas exchange threshold (GET) and respiratory compensation point (RCP) using DFAα1 values of 0.75 and 0.5 from incremental exercise, (ii) compare DFAα1 thresholds with DFAα1 measures during constant-speed running near the maximal lactate steady state (MLSS), and (iii) assess the repeatability of DFAα1 between MLSS trials. Twelve runners performed an incremental running test and constant-speed running 5% below, at, and 5% above the MLSS, plus a repeat trial at MLSS. During 30-min running trials near MLSS, DFAα1 responses were variable (i.e., 0.27–1.24) and affected by intensity (p = 0.031) and duration (p = 0.003). No difference in DFAα1 was detected between MLSS trials (p = 0.597). In the early phase (~ 8 min), DFAα1 measures at MLSS (0.71 [0.13]) remained higher than the DFAα1 identified at RCP from the incremental test (0.57 [0.13]; p = 0.024). In addition, following ~ 18 min of constant speed running at MLSS, DFAα1 measures (0.64 [0.14]) remained higher than 0.5 (p = 0.011)—the value thought to demarcate the boundaries between heavy and severe exercise intensities. Accordingly, using fixed DFAα1 values associated with the RCP from incremental exercise to guide constant-speed exercise training may produce a greater than expected exercise intensity, however; the dependency of DFAα1 on intensity and duration suggest its potential utility to quantify systemic perturbations imposed by continuous exercise. [ABSTRACT FROM AUTHOR]

Purpose: We have previously shown that accelerated running on flat terrain is biomechanically equivalent to running uphill at a constant speed. This hypothesis was further investigated comparing the energy cost of running at a constant speed either uphill, or on flat terrain against an equivalent horizontal impeding force, mimicking acceleration. Methods: Steady-state O2 consumption and the corresponding energy cost (per unit body mass and distance) were determined on 12 male subjects during treadmill running at speeds between 2.11 and 2.89 m/s: (i) on the level, (ii) uphill at 10 or 20% incline (I ), or (iii) on the level against a horizontal traction force of 10 or 20% of the subject's body weight ( TF ). This allowed us to estimate the net efficiency ( n e t η ) of running against horizontal or vertical forces, as given by the ratio between the additional mechanical work output under TF , or the corresponding I condition, and the difference between the appropriate energy cost above that for running at constant speed on flat terrain. Results: The n e t η values when running uphill (I ) amount to 0.35–0.40, whereas those for running against an equivalent impeding force ( TF ) are about 10% greater (0.45–0.50), a fact that may be due to a greater recovery of elastic energy in the TF as compared to the I condition. Conclusion: Making allowance for these small differences, these data support the view of considering accelerated running on flat terrain biomechanically equivalent to running at a constant speed, up an equivalent slope. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Running-related knee injuries are associated with high and repetitive quadriceps contractions. Infrapatellar straps are commonly recommended for the prevention and management of those injuries. The effects of infrapatellar straps have been investigated in terms of quadriceps activations. However, these indexes cannot accurately characterize the quadriceps forces, which directly contribute to knee injuries. This study aimed to quantify quadriceps forces during running performed with and without infrapatellar straps based on OpenSim. Experimental data from 18 healthy participants were recorded using a 10-camera motion capture system and two force plates when they performed running at self-selected speeds with and without infrapatellar straps. OpenSim was used to estimate muscle forces, muscle activity, joint kinematics, and joint kinetics. The use of infrapatellar straps significantly reduced peak quadriceps forces (p < 0.001), accumulated forces of quadriceps (p < 0.001), and peak knee extension moments (p < 0.001). Among the four distinct muscles of the quadriceps, the vastus lateralis contributed the most to the reduction in quadriceps muscle forces. Strapping did not result in a significant change in rectus femoris forces (p > 0.05). The use of infrapatellar straps results in lower vastus muscle forces, and thus could be helpful in managing and preventing running-related knee injuries. However, infrapatellar straps may have little effect in people with an excessively forceful rectus femoris. [ABSTRACT FROM AUTHOR]

Background: Australian Rules Football athletes complete long preseasons, yet injuries occur frequently at early stages of the competitive season. Little is known about the high-speed running (HSR) prescription during a preseason or whether players are adequately prepared for competition. This study described absolute and relative preseason and in-season HSR demands of 2 professional Australian football teams. Hypothesis: HSR and sprinting volumes are significantly lower in elite Australian Rules football athletes during in-season compared with preseason. Study Design: Cohort study. Level of Evidence: Level 3. Methods: During the 2019 season, HSR volume was collected for 2 professional Australian football teams (n = 55). Individual maximum speeds (Vmax) were captured to calculate relative running speed thresholds, as reported in 5% increments from 70%Vmax to 100%Vmax. Results: Weekly volume of running above 70%Vmax (P = 0.01; r = 0.56) and 80%Vmax (P = 0.01; r = 0.58) was significantly greater in the preseason than the in-season. The weekly volume completed above 90%Vmax was not significantly greater in the preseason than the in-season (P = 0.10; r = 0.22). Individual variation in the distance completed at specific percentages of Vmax expressed as a coefficient of variation was reported as 51% at 71% to 80%Vmax, 39% at 81% to 90%Vmax, and 41% at 91% to 100%Vmax. Conclusion: The volume of HSR completed by athletes is far greater in the initial 4 weeks of the preseason than in any other point in preseason or competitive phases. At the individual level, there is substantial variation in the distance covered. This supports the concept of a heavily individualized approach to high-speed prescription and monitoring. Clinical Relevance: Practitioners should carefully consider individual variation regarding sprinting volume during both preseason and in-season when prescribing and monitoring training to improve on-field performance and reduce the risk of injury. [ABSTRACT FROM AUTHOR]

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To enhance athletic performance and reduce the risk of injury, load quantification has allowed for a better understanding of the individual characteristics of the physical demands on soccer players during training or competition. In this regard, it appears crucial to summarize scientific evidence to provide useful information and future directions related to the speed and acceleration profiles of male soccer players. This review aims to evaluate the findings reflected in the available literature on both profiles in football, synthesizing and discussing data from scientific articles, while providing insights into quantification methods, employed thresholds, tracking systems, terminology, playing position, and microcycle day. Therefore, it is hoped that this narrative review can support objective decision-making in practice for coaches, sports scientists, and medical teams regarding individualized load management and the appropriate selection of metrics, to explore current trends in soccer player profiles. [ABSTRACT FROM AUTHOR]

Despite strength training (ST) being well characterized by professional runners, little is known about the inclusion of ST models for recreational runners. Thus, the present study aimed to investigate the presence of ST in the training practices of recreational runners, with a focus on understanding its characteristics and the motivations of recreational athletes for including ST in their routines. To this end, 801 recreational runners (493 male and 308 female) completed a structured questionnaire regarding their training habits, the inclusion of ST, and its characteristics, concerning the type of ST, training volume, and the reasons for including ST in their training programs. To assess the possible associations between categorical variables, data were analyzed using the chi-square test for independent samples. Approximately 625 runners (78.1%) reported that they included ST in their training routine, with a statistically significant difference between the sexes (men: 73.5% vs. women: 85.4%; X2 = 14.09; p = 0.01). Traditional strength training (TST) was the predominant type of ST included (78.5%), with most participants performing 2–4 sets and 8–12 repetitions per set at a frequency of 3–4 sessions per week. The importance of ST was primarily attributed to performance improvement (85%). The results suggest that recreational runners incorporate different types of ST into their training routines, with TST being the predominant type perceived by runners as a valuable asset for improving running performance. [ABSTRACT FROM AUTHOR]

The pressure wave generated by an urban-rail vehicle when passing through a tunnel affects the comfort of passengers and may even cause damage to the train and related tunnel structures. Therefore, controlling the train speed in the tunnel is extremely important. In this study, this problem is investigated numerically in the framework of the standard k-ε two-equation turbulence model. In particular, an eight-car urban rail train passing through a tunnel at different speeds (140, 160, 180 and 200 km/h) is considered. The results show that the maximum aerodynamic drag of the head and tail cars is most affected by the running speed. The pressure at selected measuring points on the windward side of the head car is very high, and the negative pressure at the side window of the driver's cab of the tail car is also very large. From the head car to the tail car, the pressure at the same height gradually decreases. The positive pressure peak at the head car and the negative pressure peak at the tail car are greatly affected by the speed. [ABSTRACT FROM AUTHOR]

In this paper, we first collect massive data based on the Hadoop HDFS system and perform distributed data storage for it. Then, the massive data in the system is queried quickly by designing a secondary index and a parallel region query method based on Hilbert coding. Experiments are carried out to measure the efficiency of the Hadoop HDFS system in efficient data storage and querying, and to investigate its scalability. After completing the efficient storage and querying of data, the Spark DBSCAN algorithm is proposed to mine the data efficiently. The performance of the Spark DBSCAN algorithm is examined by comparing and analysing the clustering performance and running speed of the Spark DBSCAN algorithm with the traditional DBSCAN algorithm. The query performance of Hadoop HDFS is superior to that of Jena-Hbase and SHARD systems. The fast query time of Hadoop HDFS stays the same, and the scalability is nearly linear with the data size in the case of a slow query. The clustering accuracy of the Spark DBSCAN algorithm is slightly better than that of the traditional parallel DBSCAN algorithm, but the overall difference is small. The Spark DBSCAN algorithm runs significantly faster than the traditional parallel DBSCAN algorithm on different datasets. [ABSTRACT FROM AUTHOR]

Fall behavior is closely related to the high mortality rate of the elderly, so fall detection has become an important and urgent research area in human behavior recognition. However, the existing fall detection methods, suffer from the loss of detailed action information during feature extraction due to the downsampling operation, resulting in subpar performance when detecting falls with similar behaviors such as lying and sitting. To solve the challenges, this study proposes a high-resolution spatio-temporal feature extraction method based on a spatio-temporal coordinate attention mechanism. The method employs 3D convolutions to extract spatio-temporal features and utilizes gradual down-sampling to generate a multi-resolution sub-network, thus realizing multi-scale fusion and perception enhancement of details. In particular, this study designs a pseudo-3D basic block, which simulates the ability of 3D convolution, to ensure the running speed of the network while controlling the number of parameters. Further, a spatio-temporal coordinate attention mechanism is designed to accurately extract the spatio-temporal positional changes of key skeletal points and the interrelationships among them. Long-term dependencies in horizontal, vertical, temporal directions are captured through three one-dimensional global pooling operations. Then the long-range relationships and channel correlations among features are captured by cascading and slicing operations. Finally, the key information is effectively highlighted by performing dot-multiplication operations between the feature maps from the horizontal, vertical and temporal directions and the input feature maps. Experimental results on three typical public datasets show that the proposed method can better extract motion features and improve the accuracy of fall detection. [ABSTRACT FROM AUTHOR]

The aerodynamic performance of a high-speed train is intimately linked to its head shape. In order to reduce the aerodynamic drag during the operation of high-speed trains, five distinct head types with varying parameters are developed for double-arch trains and numerical calculation models for high-speed trains are established by modifying the cab height and front window transition shape of the double-arch high-speed train. The three-dimensional, steady, incompressible N-S equation and RNS method are used to simulate the flow field of five models running at a constant speed in open air, the influence of train cab height and front window transition shape on resistance characteristics of the double-arch train in the stable operation of the open air is comparatively analyzed. The following conclusions are drawn: under the same running conditions, the pressure difference in the flow field around the train mainly occurs in the transition area at the front window of the driver's cab and above, and the external geometric parameters of the driver significantly affect the aerodynamic drag of double-arch high-speed trains. The aerodynamic drag coefficient decreases as the height of the design position of the curvature transition of the front window of the train head increases, the maximum difference is 14.5%, and the distribution range of high pressure in the head car is reduced. The design inclination of the front window of the cab is reduced and the maximum pressure on the front window of the cab is lowered, resulting in a 13.4% decrease in the train's aerodynamic drag coefficient. When the plane is chosen to replace the curved surface as the transition surface of the train cab's front window, the positive pressure at the front window of the cab can be reduced, but the negative pressure above the cab will be intensified, and the aerodynamic drag coefficient of the train is decreased by only 3%. To achieve optimal drag reduction, it is recommended to raise the driver's cab height within a reasonable range and decrease the inclination of the front window surface on double-arch high-speed trains. [ABSTRACT FROM AUTHOR]

Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways. They can cause significant wheel-rail dynamic interactions, leading to wheel-rail noise, component damage, and deterioration. Few researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry irregularities. However, the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric shape. In this study, novel theoretical models were developed for three categories of rail weld irregularities, based on measurements of the high-speed railway from Beijing to Shanghai. The vertical dynamic forces in the time and frequency domains were compared under different running speeds. These forces generated by the rail weld irregularities that were measured and modeled, respectively, were compared to validate the accuracy of the proposed model. Finally, based on the numerical study, the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network (ANN), and the optimum combination of parameters for this model is found. The results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the literature. The ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time. [ABSTRACT FROM AUTHOR]