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EMOKINE is a software package and dataset creation suite for emotional full-body movement research in experimental psychology, affective neuroscience, and computer vision. A computational framework, comprehensive instructions, a pilot dataset, observer ratings, and kinematic feature extraction code are provided to facilitate future dataset creations at scale. In addition, the EMOKINE framework outlines how complex sequences of movements may advance emotion research. Traditionally, often emotional-'action'-based stimuli are used in such research, like hand-waving or walking motions. Here instead, a pilot dataset is provided with short dance choreographies, repeated several times by a dancer who expressed different emotional intentions at each repetition: anger, contentment, fear, joy, neutrality, and sadness. The dataset was simultaneously filmed professionally, and recorded using XSENS® motion capture technology (17 sensors, 240 frames/second). Thirty-two statistics from 12 kinematic features were extracted offline, for the first time in one single dataset: speed, acceleration, angular speed, angular acceleration, limb contraction, distance to center of mass, quantity of motion, dimensionless jerk (integral), head angle (with regards to vertical axis and to back), and space (convex hull 2D and 3D). Average, median absolute deviation (MAD), and maximum value were computed as applicable. The EMOKINE software is appliable to other motion-capture systems and is openly available on the Zenodo Repository. Releases on GitHub include: (i) the code to extract the 32 statistics, (ii) a rigging plugin for Python for MVNX file-conversion to Blender format (MVNX=output file XSENS® system), and (iii) a Python-script-powered custom software to assist with blurring faces; latter two under GPLv3 licenses. [ABSTRACT FROM AUTHOR]

The present work discusses the numerical simulation of the tapping process to validate the earlier postulates related to the influence of BOF vessel shape on vortex formation. Numerical experiments were conducted by varying the initial filling flow rates (FR 40 and 20 lpm), dwell times (DT 90 and 30 seconds), nozzle diameters (ND 2.14 and 1.04 cm), and initial liquid height (LH 14 and 11 cm). It was earlier reported that the vortex formation is mainly dependent on the nozzle diameter and the stability of the vortex relay on the residual motion in the draining liquids. The present numerical study provides insight into the vortex stability and elucidates the role of residual motion in the draining liquids under different process conditions. The delay in vortex formation for the case of higher residual motion is due to a delay in acceleration and alignment of angular momentum at the nozzle axis vicinity. Further, it is also observed from the numerical experiments that the vertical velocity component's magnitude exceeds the curl velocity's horizontal velocity component to establish the stable vortex. The findings of simulated results are in good agreement with the experimental results reported earlier. It also supports the theory of controlling the vortex formation in BOF vessels (by tilting front/back) without using an external device, such as a dart, a device to arrest the slag entering the ladle at the tapping end. [ABSTRACT FROM AUTHOR]

Background: The automatic detection of activities of daily living (ADL) is necessary to improve long-term home-based monitoring of Parkinson's disease (PD) symptoms. While most body-worn sensor algorithms for ADL detection were developed using laboratory research systems covering full-body kinematics, it is now crucial to achieve ADL detection using a single body-worn sensor that remains commercially available and affordable for ecological use. Aim: to detect and segment Walking, Turning, Sitting-down, and Standing-up activities of patients with PD using a Smartwatch positioned at the ankle. Method: Twenty-two patients living with PD performed a Timed Up and Go (TUG) task three times before engaging in cleaning ADL in a simulated free-living environment during a 3 min trial. Accelerations and angular velocities of the right or left ankle were recorded in three dimensions using a Smartwatch. The TUG task was used to develop detection algorithms for Walking, Turning, Sitting-down, and Standing-up, while the 3 min trial in the free-living environment was used to test and validate these algorithms. Sensitivity, specificity, and F-scores were calculated based on a manual segmentation of ADL. Results: Sensitivity, specificity, and F-scores were 96.5%, 94.7%, and 96.0% for Walking; 90.0%, 93.6%, and 91.7% for Turning; 57.5%, 70.5%, and 52.3% for Sitting-down; and 57.5%, 72.9%, and 54.1% for Standing-up. The median of time difference between the manual and automatic segmentation was 1.31 s for Walking, 0.71 s for Turning, 2.75 s for Sitting-down, and 2.35 s for Standing-up. Conclusion: The results of this study demonstrate that segmenting ADL to characterize the mobility of people with PD based on a single Smartwatch can be comparable to manual segmentation while requiring significantly less time. While Walking and Turning were well detected, Sitting-down and Standing-up will require further investigation to develop better algorithms. Nonetheless, these achievements increase the odds of success in implementing wearable technologies for PD monitoring in ecological environments. [ABSTRACT FROM AUTHOR]

Interest in the exploration of other planets has led to the success of Ingenuity (Mars helicopter)'s first flight in the Martian atmosphere. Despite this achievement, the flight of aircraft under ultra-low air density, such as Mars, is still limited. A flapping-wing aircraft that mimics nature's flyers can provide an alternative solution to conventional aircraft. Successful flapping flight on Mars, where the air density is very thin, requires an understanding of aerodynamics, and prediction of the dynamic changes of the flapping wing under very-low air density. In this paper, we constructed a simple dynamic model that can predict the changes in aerodynamics and dynamic behavior under various low air densities. The predicted changes were compared with the measured ones in a chamber that could simulate the low air density with a modified flapping-wing system based on our flapping-wing micro-air-vehicle (FW−MAV) models, the KUBeetle. Both prediction and measurement showed that when the air density decreased, the flapping frequency tended to increase due to drag reduction, even without consuming additional power. The model reasonably predicted a large decrease in the lift for the 10 % air density, where the flapping frequency increased by 10 %. Under the 50 % and 25 % low air densities, the measured lift coefficients did not change much. However, under the 10 % air density, the lift coefficient decreased by about 16 % due to less wing rotation and wing twist. While the aerodynamic power was predicted to decrease significantly due to the large decrease in aerodynamic forces under low air density, an increase in the angular velocity and peak angular acceleration caused an increase in the inertial power. Therefore, the amount of reduction in the measured mechanical power consumption under the 10 % air density was relatively small, compared to that under the 100 % air density. This work may provide insights into the design of an FW−MAV for the ultra-thin air density, such as Mars. • The proposed dynamic model reasonably predicted the flapping motion under low air density. • The measured flapping frequency increased by about 15 % under the 10 % air density, consuming about 9 % less power. • The reduction in measured power consumption under low air density was small, due to the large inertial power. • The measured lift coefficient decreased by about 16 % under the 10 % air density, due to less wing Q4 rotation and wing twist. [ABSTRACT FROM AUTHOR]

Repetitive movements and the speed of upper limbs increase the risk of musculoskeletal disorders. This study aimed to analyse the risk of shoulder injuries in repetitive tasks by evaluating the humerus angle, angular velocity, and angular acceleration during simulated chicken wing cutting. The study was conducted in a laboratory simulating a real environment. Thirty-six healthy right-handed volunteers were assessed using an electromagnetic tracking device, TrakSTAR, integrated with MotionMonitor™ (Innovative Sports Training, Inc. Chicago, IL) and software to collect 3-D kinematic data developed in the research centre. The equipment measured the angles performed by the upper limbs during the entire movement. The humerus angles were automatically transformed into angular velocity (°·s−1) and angular acceleration (°·s−2). Maximum angular velocities were 27.39°·s−1 (men, right humerus) and 22.39°·s−1 (women, left humerus), both below the safe limit. Maximum accelerations were 25.32°·s−2 (men, left side) and 28.94°·s−2 (women, left side); safety values for these accelerations are not established. Monotony is a risk factor, especially for the dominant side. Future studies should evaluate risk factors simultaneously in repetitive tasks. Repetitiveness exceeds the safe limit according to the OCRA method. [ABSTRACT FROM AUTHOR]

A method for measuring multi-joint finger trajectories is proposed using MediaPipe. In this method, a high-speed camera is used to record finger movements. Subsequently, the recorded finger movement data are input into MediaPipe, where the system automatically extracts the coordinate data of the key points in the finger movements. From this, we obtain data pertaining to the trajectory of the finger movements. In order to verify the accuracy and effectiveness of this experimental method, we compared it with the DH method and the Artificial keypoint alignment method in terms of metrics such as MAPE (Mean Absolute Percentage Error), maximum distance error, and the time taken to process 500 images. The results demonstrated that our method can detect multiple finger joints in a natural, efficient, and accurate manner. Then, we measured posture for three selected hand movements. We determined the position coordinates of the joints and calculated the angular acceleration of the joint rotation. We observed that the angular acceleration can fluctuate significantly over a very short period of time (less than 100 ms), in some cases increasing to more than ten times the initial acceleration. This finding underscores the complexity of finger joint movements. This study can provide support and reference for the design of finger rehabilitation robots and dexterous hands. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management 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.)

This work reports a comprehensive multiphysics modeling and optimization of a MEMS-based piezoelectric inertial measurement unit (IMU) sensor using a single proof mass. The studied miniaturized sensor consists of a stick-shaped cylindrical proof mass with two concentric rings connected between them with joints where the stress is concentrated. The advantage of introducing this new piezoelectric IMU concept is the concurrent detection of all six degrees of freedom (DOFs), i.e., 3-axis linear accelerations and angular velocities, using a single seismic mass and only four electrodes. The piezoelectric IMU structure optimization was carried out using finite element analysis (FEA) in order to obtain the optimal dimensions and generate the maximum stress in the piezoelectric layer. In fact, the mechanical (displacement and stress) and electrical (potential and sensitivity) performance of the IMU structure was determined when 3-axis linear accelerations and 3-axis angular velocities were applied. The simulation results showed a sensitivity of 1 mV/g and 6.8 mV/g, respectively, for linear accelerations along the x-/y- and z-axes. Along these same axes, the angular velocity sensitivity was approximately 0.39 µV/rad/s and 1.7 mV/rad/s. Moreover, the simulation results claim that the proposed IMU has good performance in terms of cross-axis sensitivity of less than 0.88% for all six DOFs, which is due to its perfectly symmetric circular structure. Finally, a simple block diagram is presented to separate the outputs related to linear acceleration from those related to angular velocity from the four sensing electrodes. [ABSTRACT FROM AUTHOR]

Manual exploratory behaviors during object interaction that form the basis of tool use behavior, are mostly qualitatively characterized in terms of their frequency and duration of occurrence. To fully understand their functional and clinical significance, quantitative movement characterization is needed alongside their qualitative analysis. However, there are two challenges in quantifying them—(a) reliably classifying the type of movement and (b) performing this classification on a time series automatically. Here, we propose a machine learning-based classification method to address these challenges. We measured three common exploratory behaviors (object rotation, fingering, and throwing) in college-aged adults using "sensorized objects" that had wireless Inertial Measurement Units embedded in them. We then calculated several statistical features based on linear acceleration and angular velocity data to train machine learning classifiers to identify these behaviors. All classifiers identified the behaviors with a substantially higher accuracy (average accuracy = 84.95 ± 4.16%) than chance level (33.33%). Of all models tested, Support Vector Machine Quadratic, Support Vector Machine Medium Gaussian, and Narrow Neural Network were the best models in classifying the three behaviors (average accuracy = 89.34 ± 0.12%). This classification method shows potential for automating movement characterization of exploratory behaviors, thereby may aid early assessment of neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

The present research proposes novel swept-curved bioinspired blades for Darrieus wind turbine. The design was influenced by the curved flippers of the bottle-nose dolphin. The proposed model was designed using the Solidworks software, empirically tested for power improvement, later fine-tuned adopting high fidelity numerical modeling. An in-depth analysis comparing the traditional H-bladed turbine with the new-bladed design was performed using OpenFOAM. Further, an elaborate experimental observations on the proposed design suggest that the model with 0.6 c forward sweep outperformed the rest. The efficiency of the curved blade was notably enhanced by 14.41%, in contrast to the conventional model, and the numerical analysis endorses this observation. The modified turbine blades have the maximum wind streamlines that converge toward the center of the blade's trailing edge due to the lateral shift, and the resulting convergence reduces blade tip losses. The modified blade models demonstrated improved angular acceleration at a given wind speed, indicating enhanced efficiency and superior self-starting capabilities. Notably, these improvements were evident even at a lower wind speed of 4.2 m / s compared to the traditional H-model. [ABSTRACT FROM AUTHOR]

Featured Application: The machine learning model predicts Minimum Foot Clearance heights to prevent tripping falls. Integrated into exoskeletons or other assistive devices, it offers real-time interventions for vulnerable populations, enhancing safety with quick and accurate foot clearance adjustments. Tripping is the largest cause of falls, and low swing foot ground clearance during the mid-swing phase, particularly at the critical gait event known as Minimum Foot Clearance (MFC), is the major risk factor for tripping-related falls. Intervention strategies to increase MFC height can be effective if applied in real-time based on feed-forward prediction. The current study investigated the capability of machine learning models to classify the MFC into various categories using toe-off kinematics data. Specifically, three MFC sub-categories (less than 1.5 cm, between 1.5 and 2.0 cm, and higher than 2.0 cm) were predicted to apply machine learning approaches. A total of 18,490 swing phase gait cycles' data were extracted from six healthy young adults, each walking for 5 min at a constant speed of 4 km/h on a motorized treadmill. K-Nearest Neighbor (KNN), Random Forest, and XGBoost were utilized for prediction based on the data from toe-off for five consecutive frames (0.025 s duration). Foot kinematics data were obtained from an inertial measurement unit attached to the mid-foot, recording tri-axial linear accelerations and angular velocities of the local coordinate. KNN, Random Forest, and XGBoost achieved 84%, 86%, and 75% accuracy, respectively, in classifying MFC into the three sub-categories with run times of 0.39 s, 13.98 s, and 170.98 s, respectively. The KNN-based model was found to be more effective if incorporated into an active exoskeleton as the intelligent system to control MFC based on the preceding gait event, i.e., toe-off, due to its quicker computation time. The machine learning-based prediction model shows promise for the prediction of critical MFC data, indicating higher tripping risk. [ABSTRACT FROM AUTHOR]

To provide the necessary theoretical models of sphere–soil interaction for the structural design, motion control, and simulation of spherical robots, this paper derives analytical expressions for traction force and driving torque when spherical robots slide and sink into sandy terrain, based on terramechanics and multibody dynamics. Furthermore, orthogonal experimental analysis identifies the load, joint angular acceleration, and maximum joint angular velocity of spherical robots as influencing factors, highlighting that the load significantly affects their longitudinal motion performance. Experimental results indicate that rolling friction and additional resistance on sandy terrain cannot be ignored. The corrected theoretical model effectively replicates the temporal variation of driving torque exerted by spherical robots on sandy terrain. Numerical computations and experimental analyses demonstrate that increasing the radius of the sphere shell, the load, and the slip ratio all lead to increased traction force and driving torque. However, traction force and driving torque begin to decrease once the slip ratio reaches approximately 0.5. Therefore, in the design of spherical robot structures and control laws, appropriate parameters such as load and slip ratio should be chosen based on the established sphere–soil interaction theoretical model to achieve high-quality longitudinal motion performance on sandy terrain. [ABSTRACT FROM AUTHOR]

Kinematic analysis is the first task that needs to be solved for further real-life problems such as machine dynamics and durability, machine balancing, and optimization, chemistry, etc. Currently, there are many methods to analyze the kinematic problem, for instance: vector graphics method, vector-analytic method, or Dennavit-Hartenberg-Craig matrix method. Although each method has its advantages, they have mostly encountered difficulties in establishing equations associated with complicated spatial structures. This research proposed a novel method, entitled "'perpendicular projection method" to solve the problem of spatial structural kinematic analysis. This is an approximate solution method that combines the use of generalized coordinates and direction cosine matrices. With this method, the problem of kinematic analysis of spatial structures will be solved simply and easily by establishing connection equations as well as simulating the motion of spatial structures. This method was then applied in conducting the kinematic analysis of a spatial mechanism with 1 rotating joint (R), 1 ball joint (S), 1 translational joint (P), and one cylindrical joint (C). The calculated results, including the velocity, acceleration of generalized coordinates, angular velocity, angular acceleration of the links, velocity, and acceleration of the center of mass of the links, showed the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department 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.)

Conventional angular acceleration estimation methods generate non-negligible errors when the control surface rapidly deflects; hence, the estimated angular acceleration cannot be used for aerodynamic parameter identification directly. This paper proposes an angular acceleration estimation method based on angular velocity equivalent model. The angular acceleration of the angular velocity equivalent model, whose angular velocity response is consistent with the flight test data, is used as the estimated angular acceleration. Firstly, the equivalent angular velocity model is established by combining the generic aerodynamic model with the rotational dynamic equations of aircraft. Secondly, the angular velocity data and the control surface deflection data are synchronized. Finally, the angular velocity response of the equivalent model is used as the predictor, and the estimated angular acceleration is obtained by extended Kalman filter. The aerodynamic parameter identification and validation are carried out using the estimated angular acceleration of a large civil aircraft flight test data. The results show that the angular acceleration obtained through the proposed angular acceleration estimation method meets the accuracy requirement of aerodynamic parameter identification. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica 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.)

Purpose: The current study aimed to assess the protective performance of helmets equipped with multi-directional impact protection system (MIPS) under various oblique impact loads. Methods: Initially, a finite element model of a bicycle helmet with MIPS was developed based on the scanned geometric parameters of an actual bicycle helmet. Subsequently, the validity of model was confirmed using the KASK WG11 oblique impact test method. Three different impact angles (30°, 45°, and 60°) and 2 varying impact speeds (5 m/s and 8 m/s) were employed in oblique tests to evaluate protective performance of MIPS in helmets, focusing on injury assessment parameters such as peak linear acceleration (PLA) and peak angular acceleration (PAA) of the head. Results: The results demonstrated that in all impact simulations, both assessment parameters were lower during impact for helmets equipped with MIPS compared to those without. The PAA was consistently lower in the MIPS helmet group, whereas the difference in PLA was not significant in the no-MIPS helmet group. For instance, at an impact velocity of 8 m/s and a 30° inclined anvil, the MIPS helmet group exhibited a PAA of 3225 rad/s2 and a PLA of 281 g. In contrast, the no-MIPS helmet group displayed a PAA of 8243 rad/s2 and a PLA of 292 g. Generally, both PAA and PLA parameters decreased with the increase of anvil angles. At a 60° anvil angles, PAA and PLA values were 664 rad/s2 and 20.7 g, respectively, reaching their minimum. Conclusion: The findings indicated that helmets incorporating MIPS offer enhanced protection against various oblique impact loads. When assessing helmets for oblique impacts, the utilization of larger angle anvils and rear impacts might not adequately evaluate protective performance during an impact event. These findings will guide advancements in helmet design and the refinement of oblique impact test protocols.

The micro inertial measurement unit (MIMU) is widely used in various fields such as aerospace, automotive industry, smartphones, and wearable devices. Field calibration is the key to ensuring measurement accuracy and reliability. To address the complex problem of solving calibration parameters for MIMU system errors in nonlinear optimization calibration methods, an alternating minimization algorithm based on soft thresholding updates was proposed in this paper. An accelerometer error model was established regarding gravity, and the gyroscope error model was established on the basis of the calibrated acceleration and rotation angular velocity in this method. Finally, the error models were used in convex optimization to design a simplified solution process. Compared with the Gauss-Newton algorithm, the scale factor calibration accuracy was improved by one order of magnitude, and in the nonorthogonal error and bias error calibration, the accuracy was improved by one to two orders of magnitude. Compared with the calibration method using a high-precision turntable with an accuracy of 0.001 °/s, the proposed method achieved an accuracy of 10-3 through manual calibration. It can still maintain stability with initial values of different orders of magnitude, and ultimately, the global optimal solution for the error was obtained. [ABSTRACT FROM AUTHOR]

Storytelling is one of the most important learning activities for children since reading aloud from a picture book stimulates children's curiosity, emotional development, and imagination. For effective education, the procedures for storytelling activities need to be improved according to the children's level of curiosity. However, young children are not able to complete questionnaires, making it difficult to analyze their level of interest. This paper proposes a method to estimate children's curiosity in picture book reading activities at five levels by recognizing children's behavior using acceleration and angular velocity sensors placed on their heads. We investigated the relationship between children's behaviors and their levels of curiosity, listed all observed behaviors, and clarified the behavior for estimating curiosity. Furthermore, we conducted experiments using motion sensors to estimate these behaviors and confirmed that the accuracy of estimating curiosity from sensor data is approximately 72%. [ABSTRACT FROM AUTHOR]

• Why was this study conduted? • Some study investigated probe motion in simulated settings, but few in a clinical setting during second trimester scans. We hypothesized that probe trajectory might differ according to operator's level, fetal presentation (e.g., cephalic or breech) or patient body mass index (BMI). • What does this study add? • In a clinical setting, some differences in the path metrics (velocity, acceleration, jerk and working volume) were noticed according to participant level. However, angular metrics, i.e., the quantity of rotation applied to the probe, were not affected by operator's level, fetal presentations nor patient's BMI. This study aims to investigate probe motion during full mid-trimester anomaly scans. We undertook a prospective, observational study of obstetric sonographers at a UK University Teaching Hospital. We collected prospectively full-length video recordings of routine second-trimester anomaly scans synchronized with probe trajectory tracking data during the scan. Videos were reviewed and trajectories analyzed using duration, path metrics (path length, velocity, acceleration, jerk, and volume) and angular metrics (spectral arc, angular area, angular velocity, angular acceleration, and angular jerk). These trajectories were then compared according to the participant level of expertise, fetal presentation, and patient BMI. A total of 17 anomaly scans were recorded. The average velocity of the probe was 12.9 ± 3.4 mm/s for the consultants versus 24.6 ± 5.7 mm/s for the fellows (p = 0.02), the average acceleration 170.4 ± 26.3 mm/s2 versus 328.9 ± 62.7 mm/s2 (p = 0.02), and the average jerk 7491.7 ± 1056.1 mm/s3 versus 14944.1 ± 3146.3 mm/s3 (p = 0.02), the working volume 9.106 ± 4.106 mm3 versus 29.106 ± 11.106 mm3 (p = 0.03), respectively. The angular metrics were not significantly different according to the participant level of expertise, the fetal presentation, or to patients BMI. Some differences in the probe path metrics (velocity, acceleration, jerk and working volume) were noticed according to operator's level. [ABSTRACT FROM AUTHOR]

The current study aimed to assess the protective performance of helmets equipped with multi-directional impact protection system (MIPS) under various oblique impact loads. Initially, a finite element model of a bicycle helmet with MIPS was developed based on the scanned geometric parameters of an actual bicycle helmet. Subsequently, the validity of model was confirmed using the KASK WG11 oblique impact test method. Three different impact angles (30°, 45°, and 60°) and 2 varying impact speeds (5 m/s and 8 m/s) were employed in oblique tests to evaluate protective performance of MIPS in helmets, focusing on injury assessment parameters such as peak linear acceleration (PLA) and peak angular acceleration (PAA) of the head. The results demonstrated that in all impact simulations, both assessment parameters were lower during impact for helmets equipped with MIPS compared to those without. The PAA was consistently lower in the MIPS helmet group, whereas the difference in PLA was not significant in the no-MIPS helmet group. For instance, at an impact velocity of 8 m/s and a 30° inclined anvil, the MIPS helmet group exhibited a PAA of 3225 rad/s2 and a PLA of 281 g. In contrast, the no-MIPS helmet group displayed a PAA of 8243 rad/s2 and a PLA of 292 g. Generally, both PAA and PLA parameters decreased with the increase of anvil angles. At a 60° anvil angles, PAA and PLA values were 664 rad/s2 and 20.7 g, respectively, reaching their minimum. The findings indicated that helmets incorporating MIPS offer enhanced protection against various oblique impact loads. When assessing helmets for oblique impacts, the utilization of larger angle anvils and rear impacts might not adequately evaluate protective performance during an impact event. These findings will guide advancements in helmet design and the refinement of oblique impact test protocols. [ABSTRACT FROM AUTHOR]

INTRODUCTION: To detect early cognitive impairment in community‐dwelling older adults, this study explored the viability of artificial intelligence (AI)‐assisted linear acceleration and angular velocity analysis during walking. METHODS: This cross‐sectional study included 879 participants without dementia (female, 60.6%; mean age, 73.5 years) from the 2011 Comprehensive Gerontology Survey. Sensors attached to the pelvis and left ankle recorded the triaxial linear acceleration and angular velocity while the participants walked at a comfortable speed. Cognitive impairment was determined using Mini‐Mental State Examination scores. Deep learning models were used to discern the linear acceleration and angular velocity data of 12,302 walking strides. RESULTS: The models' average sensitivity, specificity, and area under the curve were 0.961, 0.643, and 0.833, respectively, across 30 testing datasets. DISCUSSION: AI‐enabled gait analysis can be used to detect signs of cognitive impairment. Integrating this AI model into smartphones may help detect dementia early, facilitating better prevention. Highlights: Artificial intelligence (AI)‐enabled gait analysis can be used to detect the early signs of cognitive decline.This AI model was constructed using data from a community‐dwelling cohort.AI‐assisted linear acceleration and angular velocity analysis during gait was used.The model may help in early detection of dementia. [ABSTRACT FROM AUTHOR]

The hybrid system can extend the range of special vehicles and meet the electrical requirements of on-board equipment. In this paper, the driving force plummet problem of a new two-gear power-split hybrid system was studied during gear switches in a hybrid mode. The dynamic model of a hybrid electric system was established, and the effects of the engine angular acceleration and angular jerk on vehicle power and ride performance were obtained. The optimal ratio of the torque change rate of the motor and engine in the mode switch process was proposed. Considering the battery limitation and the external characteristics of the engine, the method of determining the target speed of the engine during shifting was proposed. Considering the response characteristics of each power source, the dynamic coordinated control strategy of multiple power sources in the mode switch process was proposed. The vehicle dynamics model was established based on the Matlab/Simulink 2020b and verified by simulation and a hardware-in-the-loop (HIL) test. The results show that the dynamic coordinated control strategy can reduce the peak impact by 80.33%, effectively improve the vehicle power and ride performance, and prevent the occurrence of high-current battery charging. [ABSTRACT FROM AUTHOR]

In large-scale satellite constellations, the efficiency of inter-satellite communication is paramount. Traditional topology control strategies, such as the Manhattan configuration, provide stable links but can result in indirect communication paths, affecting the efficiency of information transfer. This paper addresses this issue by proposing an innovative "3 + 1" dynamic topology control scheme. The scheme retains three static links determined by the relative angular velocity and acceleration while introducing a dynamic link based on distance and angular velocity constraints to optimize the link duration and overall network communication efficiency. To address the complexity of matching dynamic links, this paper introduces an elite strategy-based maximum weighted matching algorithm for general graphs. Compared to traditional greedy algorithms, our proposed algorithm significantly improves the link duration and topological stability. Through simulation experiments comparing communication delays between Xiamen and Los Angeles, our results show that the proposed dynamic link scheme substantially reduces the average delay, enhancing the efficiency and flexibility of inter-satellite communication. This research not only extends the duration of inter-satellite links but also provides new perspectives and methodologies for further studies on inter-satellite topology control strategies. [ABSTRACT FROM AUTHOR]

In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device's maximum travel speed and minimizing the banana bunch's oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption. [ABSTRACT FROM AUTHOR]

The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

AbstractThe inertial motion unit (IMU) is an effective tool for monitoring and assessing gait impairment in patients with lumbar disc herniation(LDH). However, the current clinical assessment methods for LDH gait focus on patients’ subjective scoring indicators and lack the assessment of kinematic ability; at the same time, individual differences in the motor function degradation of the healthy and affected lower limbs of LDH patients are also ignored. To solve this problem, we propose an LDH gait feature model based on multi-source adaptive Kalman data fusion of acceleration and angular velocity. The gait phase is segmented by using an adaptive Kalman data fusion algorithm to estimate the attitude angle, and obtaining gait events through a zero-velocity update technique and a peak detection algorithm. Two IMUs were used to analyze the gait characteristics of lumbar disc patients and healthy gait people, including 12 gait characteristics such as gait spatiotemporal parameters, kinematic parameters, gait variability and stability. Statistical methods were used to analyze the characteristic model and verify the biological differences between the healthy affected side of LDH and healthy subjects. Finally, feature engineering and machine learning technology were used to identify the gait pattern of inertial movement units in patients with lumbar intervertebral disc disease, and achieved a classification accuracy of 95.50%, providing an effective gait feature set and method for clinical evaluation of LDH. [ABSTRACT FROM AUTHOR]

Human trajectories can be tracked by the internal processing of a camera as an edge device. This work aims to match peoples' trajectories obtained from cameras to sensor data such as acceleration and angular velocity, obtained from wearable devices. Since human trajectory and sensor data differ in modality, the matching method is not straightforward. Furthermore, complete trajectory information is unavailable; it is difficult to determine which fragments belong to whom. To solve this problem, we newly proposed the SyncScore model to find the similarity between a unit period trajectory and the corresponding sensor data. We also propose a Likelihood Fusion algorithm that systematically updates the similarity data and integrates it over time while keeping other trajectories in mind. We confirmed that the proposed method can match human trajectories and sensor data with an accuracy, a sensitivity, and an F1 of 0.725. Our models achieved decent results on the UEA dataset. [ABSTRACT FROM AUTHOR]

This study proposes the slope of the engine speed trend line (SlopeESTL) as a new misfire detection index for a four-cylinder engine, not limited to four-cylinder engines. SlopeESTL is defined as angular acceleration between the first and the last teeth of each cylinder in the cycle. SlopeESTL is flat and near 0 when the cylinder is normally combusted. A misfire leads to an abrupt decrease under the threshold. While it is affected by post oscillation just after misfires, there is enough margin between SlopeESTL of the misfired cylinder and post-oscillated SlopeESTL. The mean misfire detection and detection fault rates of the SlopeESTL were over 97% and under 1% in this study, making it a good misfire detection index. However, most of the first misfired cylinder on dual cylinder misfire can seldom be detected as a misfire at the high engine speed over 5000 rpm in the single cylinder misfire pattern. This is caused by the inertia force of the crankshaft system and is a demerit for the misfire detection index. It is one of the two RPM slopes used to calculate the Gap and ΔGap slopes proposed by the author. SlopeESTL can be used with Gap and ΔGap slopes, because they have their specific characteristics as misfire detection indices and their combination logic should be studied more. Furthermore, SlopeESTL can be affected by the machining tolerance of the teeth in the sensor wheel, torsional vibration, and non-uniformity in the stroke operation of the piston. However, it uses the tooth time measured using the existing crankshaft position sensor; an additional sensor is not required, which makes it economical. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate walking independence in acute-care hospital patients using neural networks based on acceleration and angular velocity from two walking tests. Forty patients underwent the 10-m walk test and the Timed Up-and-Go test at normal speed, with or without a cane. Physiotherapists divided the patients into two groups: 24 patients who were monitored or independent while walking with a cane or without aids in the ward, and 16 patients who were not. To classify these groups, the Transformer model analyzes the left gait cycle data from eight inertial sensors. The accuracy using all the sensor data was 0.836. When sensor data from the right ankle, right wrist, and left wrist were excluded, the accuracy decreased the most. When analyzing the data from these three sensors alone, the accuracy was 0.795. Further reducing the number of sensors to only the right ankle and wrist resulted in an accuracy of 0.736. This study demonstrates the potential of a neural network-based analysis of inertial sensor data for clinically assessing a patient's level of walking independence. [ABSTRACT FROM AUTHOR]

The self-starting performance of vertical-axis wind turbines (VAWTs) is crucial for their widespread utilization. Conventional evaluation methods using the static torque coefficient (CTS) or self-starting time have limitations. "The minimum 1st derivative of angular acceleration in the lift acceleration state" is proposed to serve as a suitable indicator for the completion of self-starting. Understanding the behavior of the self-starting process in VAWTs is crucial for optimizing power output. A comprehensive methodology is used that integrates experiments and computational fluid dynamics (CFD). Wind tunnel experiments are conducted to evaluate the self-starting and power output performance of the turbines. CFD is employed utilizing the Fluent 6DOF module to investigate the torque and flow field characteristics during the self-starting process. Additionally, the objectives of our study are to investigate the effect of static evaluation methods on the dynamic start-up process and to explore the effects of airfoil type, pitch angle, and inlet wind speed on the self-starting behavior of turbines. The results indicate that a high CTS ensures initial rotation, but the subsequent self-starting time remains independent of this factor. Increasing the pitch angle enhances the self-starting performance. At an inlet speed of 5 m/s, for the NACA2418 airfoil turbine, the self-starting times for pitch angles of 10° and 5° are reduced by 20% and 12%, respectively, compared to that for 0°. The NACA0018 airfoil turbines with pitch angles of 0° and 5° fail to complete selfstarting. The airfoil type also plays a crucial role, with the NACA2418 airfoil demonstrating superior self-starting performance and power performance. Furthermore, the minimum self-starting wind speed of the NACA0018 airfoil turbine was explored and determined be between 5.5 m/s and 6 m/s. The utilization of this novel self-starting evaluation method addresses the limitations of traditional approaches, providing a more universally applicable interpretation of the characteristics of turbine self-starting behavior. [ABSTRACT FROM AUTHOR]

To solve the problems of excessive impact and low efficiency in conventional polynomial curve planning caused by frequent start and stop during the operation of palletizing robots, with the SP-120 series palletizing robots as the research object, the D-H coordinate system for the robot was established by using an improved D-H method, and the forward and inverse kinematic solution was analyzed. A trajectory planning method based on Fourier series expansion was used for point-to-point continuous trajectory planning from the starting point to the target point, and simulation analysis was carried out with MATLAB software. The simulation results show that the angular displacement, angular velocity and angular acceleration curves of each joint based on Fourier series expansion are continuous and stable, and the running trajectory of workspace is smooth, the problem of excessive impact under palletizing conditions. Compared with the quintic polynomial interpolation algorithm, a larger peak angular velocity and a constant peak angular acceleration are obtained, which solves the problem of low efficiency of conventional polynomial curve planning. [ABSTRACT FROM AUTHOR]

Industrial robot is a and multi‐output complex system with strong coupling and high nonlinearity. The motion control accuracy of the system is affected by many factors. To solve the difficulty in establishing the input and output characteristics of robot dynamics modeling, the robot motion model is established through the Lagrangian energy function. At the same time, the nonlinear relationship between angular velocity, angular acceleration, and robot torque is accurately expressed through improved cascaded neural network. In addition, the optimal time planning of the robot's trajectory in joint space is studied using multinomial interpolation method and the particle swarm optimization (PSO). In the simulation experiment, the effect of the proposed dynamic model fitting was outstanding. Under the mixed multinomial difference calculation planning, the angular position trajectories of the three joints changed very smoothly. In the data set application test, the average error of the PSO algorithm was 0.4061 mm and the average task time was 9.101 s, which were lower than other planning algorithms. Experiments showed that the Lagrangian dynamic model analysis based on genetic algorithm cascaded neural network and PSO trajectory scheduling method under mixed multinomial difference had better trajectory planning performance in handling tasks. [ABSTRACT FROM AUTHOR]

This contribution focuses on solving the inverse and forward kinematics in the kinematic analysis of a two-link manipulator model. It involves determining the trajectory of the end effector through fifth-degree polynomial interpolation. Furthermore, given initial and final arm angle values, it computes not only the end effector trajectory but also the angular parameters of individual actuators in both arms. Additionally, it calculates the variations of angular parameters such as rotation angle, angular velocity, and angular acceleration in each kinematic pair. The direct kinematics task is utilized to define the manipulator's workspace. The task is carried out using Matlab software, and the results are presented in the form of graphs and tables. [ABSTRACT FROM AUTHOR]

This study assessed the between-day reliability of change of direction (COD) biomechanics and speed in youth soccer players using inertial measurement units (IMUs) and high-speed video. A soccer-specific COD test including a 180° pivot turn was performed in both directions by 15 elite female (age: 15.3 ± 0.6 years; height 162.6 ± 5.5 cm; body mass: 56.7 ± 7.1 kg) and 22 elite male (age: 15.4 ± 0.5 years; height 169 ± 5.9 cm; body mass: 58.5 ± 8.5 kg) youth soccer players in two consecutive days. The reliability of the variables was quantified by using intra-class correlation coefficient (ICC) analysis with limits of agreement (LoA) and Bland–Altman plots. Based on the results, neither peak resultant acceleration (PRA) nor peak angular velocity (PAV) during final foot contact was sufficiently reliable for 180° pivot turn biomechanics (poor reliability, < 0.5), but the reliability of players' running time to turn and total time was between acceptable to good (0.9>; > 0.7). However, when analyzing females and males separately, the PRA and angular velocity ICC's for females had poor to acceptable reliability, when turning left, and were statistically different from males (Z -score > 1.96). Acceptable to good reliability with reasonable (max 15% difference) LoA implies that speed measures in different phases of COD could reliably reproduce individual differences in 180° pivot turn COD speed. Sex-related differences in repeatability of acceleration and angular velocity call for more comprehensive research in the future. PAV and PRA would not be recommended for the purpose of analyzing individual repeatability of specific steps of COD movement. [ABSTRACT FROM AUTHOR]

The study proposes a Kalman Filter Family-schemed algorithm to identify the vehicle's parameters and evaluate the road roughness simultaneously, based on the response of an adapted monitoring vehicle. The vehicle is simplified as a three-dimensional multi-body system consisting of the unsprung mass of wheels and the sprung mass of the car body, connected by springs and dampers that represent the suspension system. Accelerometers and a gyroscope measure the accelerations or angular velocity of different positions of the vehicle during vibrations. The Kalman filter (KF) with unknown inputs enables the prediction of the car body's accelerations from those of wheels. On the other hand, the Augmented KF can compute the accelerations of wheels based on the car body's accelerations. Thus, an inner-systemic objective function incorporating the vehicle's parameter is built between the predicted and measured accelerations and solved in an optimized manner with the Genetic Algorithm, so that an individual complicated impact test or bump test is avoided. The numerical examples carry out field tests on a 900 m long standardized test road under two scenarios of with and without a bump. The road roughness estimated by these two KF methods from different measurements is used to calculate the International Roughness Index (IRI) and further the Riding Quality Index, which are compared with those directly provided by a standardized laser IRI profilometer. Accordance in between confirms the accuracy of the proposed algorithm under different scenarios. The analysis underlines the measurements from unsprung wheels that contact directly with the road enable a more accurate estimation of road roughness than those from the sprung car body. In addition, a vehicle speed lower than 40 km/h can provide a better estimation of the road profiles. [ABSTRACT FROM AUTHOR]

Observations of wind distribution in the eye of tropical cyclones (TCs) are still limited. In this study, a method to derive atmospheric motion vectors (AMVs) for TCs is developed, where selection from multiple local rotation speeds is made by considering continuity among neighboring grid points. The method is applied to 2.5‐min interval image sequences of three TCs, Lan (2017), Haishen (2020), and Nanmadol (2022), observed by the Himawari‐8 satellite. The results are compared with AMVs derived from research‐based 30‐s Himawari‐8 special observations conducted for Haishen and Nanmadol, as well as with in‐situ dropsonde observations conducted for Lan and Nanmadol. In these storms, the AMVs obtained from the 2.5‐min interval images in the eye are found to be in good agreement with the dropsonde observations. Examinations of AMVs in the eye reveal transient azimuthal wavenumber‐1 features in all three TCs. These features are consistent with algebraically growing wavenumber‐1 disturbances, which transport angular momentum inward and accelerate the eye rotation. In the case of Lan, the angular velocity in the eye increased by approximately 1.5 times within 1 hr. This short‐term increase is further examined. Visualization of low‐level vorticity in the eye and angular momentum budget analysis suggest that angular momentum transport associated with mesovortices played an important role in the increase of tangential wind and the homogenization of angular velocity in the eye of Lan. Plain Language Summary: Observations of winds in the eye of tropical cyclones (TCs) are still limited. In this study, a new method is developed to derive the winds by objectively tracking the clouds in the eye of TCs using geostationary meteorological satellite imagery. The method is applied to 2.5‐min interval image sequences of three TCs observed by the Himawari‐8 satellite. The estimated winds in the eye are found to be in good agreement with in‐situ dropsonde observations. Examinations of asymmetric motions in the eye reveal transient azimuthal wavenumber‐1 features in all three TCs. These features contribute to the inward transport of angular momentum and acceleration of eye rotation. In the eye of Typhoon Lan (2017), the rotation speed increased by about 1.5 times within an hour. The study further examines this short‐term acceleration and suggests that angular momentum transport associated with mesoscale vortices played an important role in the measured increase in rotation speed and the homogenization of the rotation in the eye. Key Points: A novel cloud‐tracking method for deriving atmospheric motion vectors specifically for tropical cyclones has been developedThe low‐level winds in the eye of tropical cyclones were estimated from the Himawari‐8 satellite with an error of approximately 1–2 m/sA rapid increase in angular velocity was observed in an eye when the angular momentum transport associated with mesovortices was focused [ABSTRACT FROM AUTHOR]

This paper highlights the need for intelligent analysis of students' behavioral states in physical education tasks. The hand-ring inertial data is used to identify students' motion sequence states. First, statistical feature extraction is performed based on the acceleration and angular velocity data collected from the bracelet. After completing the filtering and noise reduction of the data, we perform feature extraction by Back Propagation Neural Network (BPNN) and use the sliding window method for analysis. Finally, the classification capability of the model sequence is enhanced by the Hidden Markov Model (HMM). The experimental results indicate that the classification accuracy of student action sequences in physical education exceeds 96% after optimization by the HMM method. This provides intelligent means and new ideas for future student state recognition in physical education and teaching reform. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of mechanical arms, the time optimal trajectory planning method based on the B‑spline and whale optimization algorithm (WOA) is proposed. The Monte‑Carlo method is used to describe the workspace of the mechanical arms, and then the B‑spline is used to interpolate the given path points. According to the performance of each joint of the manipulator, the angular velocity and angular acceleration constraints are introduced, and the boundary conditions are added. After constructing the target function with optimal time, the WOA with inertia weight is used to optimize the running time of the mechanical arm. Finally, using Matlab for simulation, the results show that the algorithm presented is better than the traditional quintic polynomial method in terms of time optimization, and the angular velocity and angular acceleration curve are continuously smoothed, which verifies the validity and feasibility of the algorithm. [ABSTRACT FROM AUTHOR]

The properties of small size, low noise, high performance and no wear-out have made the hemispherical resonator gyroscope a good choice for high-value space missions. To enhance the precision of the hemispherical resonator gyroscope for use in tasks with large angular velocities and angular accelerations, this paper investigates the standing wave precession of a non-ideal hemispherical resonator under nonlinear high-intensity dynamic conditions. Based on the thin shell theory of elasticity, a dynamic model of a hemispherical resonator is established by using Lagrange's second kind equation. Then, the dynamic model is equivalently transformed into a simple harmonic vibration model of a point mass in two-dimensional space, which is analyzed using a method of averaging that separates the slow variables from the fast variables. The results reveal that taking the nonlinear terms about the square of the angular velocity and the angular acceleration in the dynamic equation into account can weaken the influence of the 4th harmonic component of a mass defect on standing wave drift, and the extent of this weakening effect varies with the dimensions of the mass defects, which is very important for steering the development of the high-precision hemispherical resonator gyroscope. [ABSTRACT FROM AUTHOR]

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis. [ABSTRACT FROM AUTHOR]

In this study, a novel model is developed to investigate the angular acceleration of the nonlinear misaligned rotor passing through the critical speeds under non-stationary operating conditions. The concerned rotor is modeled elastic with the effects of nonlinear inertia terms and flexible bearing. Nonlinear equations of motion are derived using the Lagrange method and solved with the finite element method. Effects of parameters such as shaft eccentricity, damping, and stiffness of the supports on the increase in the rotor angular speed passing through the critical speed are considered. The obtained results indicate that a small amount of eccentricity prevents exceeding the elastic critical speed of the rotor. According to the results, if the support parameters are not selected properly, the rotor will not even be able to pass its rigid critical speed. [ABSTRACT FROM AUTHOR]

The article considers the issue of dynamic and energy analysis of the rotary tiller with planetary transmission gear and vertical rotation axis designed for orchards and vineyards. In the result of investigations, analytical expressions have been derived, which enable to determine the resistance force factors of the cultivated medium affecting the rotary tiller and to set up their changing patterns during a single rotation of the rotor in conditions of forward movement of the aggregate/working unit. It has been confirmed that in case of binary symmetric blades located at 120 degree, the resistance forces transmitted from the tiller satellites to the rotor shaft mutually balance each other, as a result of which the traction resistance force of the unit receives the possible minimum value. As regard to the resistance moments transmitted from the tiller satellites to the rotor shaft and to their main moments, it should be noted that they change significantly during a single rotation of the rotor. Particularly, the extreme values of the main moment for each tiller satellite are obtained at the finite points of the rotor's diameter perpendicular to the forward movement of the tillage machine. Based on the driving and resistance force factors of the machine, as well as the differential equation of the motion, the term has been identified by means of the energy research of the rotary tiller, in case of which the angular acceleration of the rotor's shaft will be equal to zero and the machine will operate without oscillations and vibrations. [ABSTRACT FROM AUTHOR]

A meshfree orthotropic laminated shell model for geometrically nonlinear static and dynamic analysis based on the reproducing kernel particle method (RKPM) and the Mindlin-Reissner shell theory is proposed for the first time, suitable for dealing with the finite deformation of composite shell structures of arbitrary geometry in engineering. The Mindlin-Reissner shell theory is adopted to describe the geometric configuration of the laminated shells via a single-layer particle. Then, the Galerkin weak form governing equations are established explicitly and discretized using RKPM and linear transformation in the thickness direction. Furthermore, a laminate stacking sequence that can eliminate the coupling terms of linear and angular acceleration is proposed for simplification. For considering the orthotropic materials, the stress–strain transformation between local and material coordinates is introduced. A stiffened laminated shell model is also presented for simulating complex composited structures. The accuracy and convergence of the proposed laminated shell model are verified through several static and dynamic benchmarks, demonstrating the ability of the presented model to solve the nonlinear response of composite structures. [ABSTRACT FROM AUTHOR]

In this study, we considered the collective members of Pismis's clusters located at identical distances r(pc) and distributed around a mean absolute magnitude (Mo) following a Gaussian distribution with dispersion. We computed the distances rc(pc) of these clusters by applying a distance equation designed to account for Malmquist bias. Our computed distances were in satisfactory agreement when compared to previous research findings. In the second part of our work, we delved extensively into the Pismis 3 cluster, which is rarely studied, aged, and among the most affluent. We conducted analyses on its dynamical tidal radius, crossing time, relaxation time, and angular velocity. A kinematic analysis of these open clusters was carried out, encompassing aspects such as their apex position using the AD chart method, velocity ellipsoid parameters (VEPs), and the longitude of the vertex revealing a minimal value, as anticipated when pointing exactly at the Galactic Center. Additionally, we explored their ages in relation to evolution, linking them to formation mechanisms, metallicity, and opacity. [ABSTRACT FROM AUTHOR]

Introduction: While meaningless gross motor imitation (GMI) is a common challenge for children diagnosed with autism spectrum disorder (ASD), this topic has not attracted much attention and few appropriate test paradigms have been developed. Methods: The current study proposed a wrist rotation imitation (WRI) task (a meaningless GMI assignment), and established a WRI ability evaluation system using low-cost wearable inertial sensors, which acquired the simultaneous data of acceleration and angular acceleration during the WRI task. Three metrics (i.e., total rotation time, rotation amplitude, and symmetry) were extracted from those data of acceleration and angular acceleration, and then were adopted to construct classifiers based on five machine learning (ML) algorithms, including k-nearest neighbors, linear discriminant analysis, naive Bayes, support vector machines, and random forests. To illustrate our technique, this study recruited 49 ASD children (aged 3.5-6.5 years) and 59 age-matched typically developing (TD) children. Results: Findings showed that compared with TD children, those with ASD may exhibit shorter total rotation time, lower rotation amplitude, and weaker symmetry. This implies that children with ASD might exhibit decreased WRI abilities. The classifier with the naive Bayes algorithm outperformed than other four algorithms, and achieved a maximal classification accuracy of 88% and a maximal AUC value of 0.91. Two metrics (i.e., rotation amplitude and symmetry) had high correlations with the gross and fine motor skills [evaluated by Gesell Developmental Schedules-Third Edition and Psychoeducational Profile-3 (PEP-3)]. While, the three metrics had no significant correlation with the visual-motor imitation abilities (evaluated by the subdomain of PEP-3) and the ASD symptom severity [evaluated by the Childhood Autism Rating Scale (CARS)] . Discussion: The strengths of this study are associated with the low-cost measurement system, correlation between the WRI metrics and clinical measures, decreased WRI abilities in ASD, and high classification accuracy. [ABSTRACT FROM AUTHOR]

The dynamic behavior of the tensegrity structure (helix) of a rotary airborne wind energy (RAWE) machine was investigated by combining experimental and numerical techniques. Taking advantage of the slenderness of the helix, a dynamic model for the evolution of its center line and the torsional deformation was developed by using Cosserat theory. The constitutive relations for the axial, bending, and torsional stiffness, which are a fundamental component of the model, were obtained experimentally by carrying out laboratory tests. Three scenarios of increasing complexity were then studied with the numerical tool. Firstly, a stationary solution of the model, i.e., with fixed ends and no rotation, was found numerically and used to verify the correct implementation of a numerical code based on finite elements. The stability analysis of this solution, which corresponds to the state of the structure just after deployment but before operation, showed that the natural periods of longitudinal, lateral, and torsional modes of the RAWE structure under consideration are around 0.03, 0.2, and 0.4 s, respectively. Secondly, the dynamics in nominal operation was investigated by keeping both end tips fixed and implementing a controller that adjusts the torque at the ground to reach a target angular velocity of 120 rpm. Key characteristic variables like the tension and the response times of the helix were obtained. Thirdly, the dynamics of the helix when the lower end is fixed and the upper end is driven in a circular motion of frequency f1 was studied experimentally and numerically. The tension of the helix in the experiment increased for f1 above a certain threshold, and the structure collapsed at f1 = 5 Hz. Simulation analysis revealed a resonance of the structure at a higher frequency (around 13 Hz). [ABSTRACT FROM AUTHOR]

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b0 (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b0 is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. [ABSTRACT FROM AUTHOR]