Motion Trajectory Research Articles

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Perceived Trajectories of Cyclic Sound Movement

Binaural beats are a phenomenon that occurs during dichotic stimulation due to binaural integration. It takes the form of cyclic movement of the sound image in the listener’s acoustic space when the beat frequency range is below 3 Hz. Our subjects used the inserted earphones to listen to the stimuli that created a sense of sound movement due to changes in the interaural time difference (ITD). We used three types of dichotic stimuli which simulated smooth azimuthal cyclic movement and cyclic abrupt shifts. The ITD changes determined central or lateral positions of movement trajectories. The results confirm that both types of movement created the effect of binaural beats. The range of beats depended on the spatial position of the trajectory: in the frontal sector of acoustic space, the range of beats was greater than on the left or right. The perceived trajectories of smooth motion were shorter than the trajectories of abrupt shift. The influence of spatial position on the perceived trajectory length is interpreted from the standpoint of nonlinear features of lateralization. It is suggested that the effect of ITD pattern on the perceived trajectory length is mediated by temporal integration mechanisms of binaural hearing.

Relation-aware interaction spatio-temporal network for 3D human pose estimation

3D human pose estimation is a fundamental task in analyzing human behavior, which has many practical applications. However, existing methods suffer from high time complexity and weak capability to acquire the relations at the human joint level and the spatio-temporal level. To this end, the Relation-aware Interaction Spatio-temporal Network (RISNet) is presented to achieve a better speed-accuracy trade-off in a parallel interactive architecture. Firstly, the Spatial Kinematics Modeling Block (SKMB) is proposed to encode spatially positional correlations among human joints, thereby capturing cross-joint kinematic dependencies in each frame. Secondly, the Temporal Trajectory Modeling Block (TTMB) is employed to further process the temporal motion trajectory of individual joints at several various frame scales. Besides, the bi-directional interaction modules across branches are presented to enhance modeling abilities at the spatio-temporal level. Experiments on Human 3.6M, HumanEva-I and MPI-INF-3DHP benchmarks indicate that the RISNet gains significant improvement compared to several state-of-the-art techniques. In conclusion, the proposed approach elegantly extracts critical features of body joints in the spatio-temporal domain with fewer model parameters and lower time complexity.

Finger Multi-Joint Trajectory Measurement and Kinematics Analysis Based on Machine Vision

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.

Motion Prediction and Object Detection for Image-Based Visual Servoing Systems Using Deep Learning

This study primarily investigates advanced object detection and time series prediction methods in image-based visual servoing systems, aiming to capture targets better and predict the motion trajectory of robotic arms in advance, thereby enhancing the system’s performance and reliability. The research first implements object detection on the VOC2007 dataset using the Detection Transformer (DETR) and achieves ideal detection scores. The particle swarm optimization algorithm and 3-5-3 polynomial interpolation methods were utilized for trajectory planning, creating a unique dataset through simulation. This dataset contains randomly generated trajectories within the workspace, fully simulating actual working conditions. Significantly, the Bidirectional Long Short-Term Memory (BILSTM) model was improved by substituting its traditional Multilayer Perceptron (MLP) components with Kolmogorov–Arnold Networks (KANs). KANs, inspired by the K-A theorem, improve the network representation ability by placing learnable activation functions on fixed node activation functions. By implementing KANs, the model enhances parameter efficiency and interpretability, thus addressing the typical challenges of MLPs, such as the high parameter count and lack of transparency. The experiments achieved favorable predictive results, indicating that the KAN not only reduces the complexity of the model but also improves learning efficiency and prediction accuracy in dynamic visual servoing environments. Finally, Gazebo software was used in ROS to model and simulate the robotic arm, verify the effectiveness of the algorithm, and achieve visual servoing.

Numerical study on the motion characteristics of free fall lifeboats entering calm water and rough sea

As ocean engineering operations extend into deeper seas, the working environment becomes increasingly complex, making free fall lifeboats (FFLBs) more vital for maritime disaster rescues. Unlike traditional davit-launched lifeboats, FFLBs are propelled into the water at a specific velocity and angle, engaging in a complex motion process of launch, impact, submersion, and resurfacing. Therefore, to assess the safety of FFLBs, this paper regarding the lifeboat as a rigid body aims to investigate the six-degree-of-freedom motion characteristics of lifeboat entering the water with different entry angles θ and wave environment, with a specific focus on analyzing the primary causes of capsizing. The numerical simulations of water entry with various θ, wave heights H, and relative entry positions are carried out by combining large eddy simulation and overset mesh technology. The free surface is captured by the volume of fluid method, and the attitude change, acceleration change, motion trajectory, and free surface evolution law of lifeboats are analyzed. The findings suggest that lifeboats can enter calm water safely at θ of 20°–50° and maintain a stable posture. Moreover, in extreme conditions where θ is either 0° or 90°, there is a high risk of entry failure due to excessive vertical acceleration and poor motion attitude, respectively. Furthermore, when facing waves, lifeboats experience reduced horizontal displacement when entering at peak and downward zero point compared to calm water conditions, which poses challenges for avoiding potential dangers.

Computational account for the naturalness perception of others' jumping motion based on a vertical projectile motion model.

The visual naturalness of a rendered character's motion is an important factor in computer graphics work, and the rendering of jumping motions is no exception to this. However, the computational mechanism that underlies the observer's judgement of the naturalness of a jumping motion has not yet been fully elucidated. We hypothesized that observers would perceive a jumping motion as more natural when the jump trajectory was consistent with the trajectory of a vertical projectile motion based on Earth's gravity. We asked human participants to evaluate the naturalness of point-light jumping motions whose height and duration were modulated. The results showed that the observers' naturalness rating varied with the modulation ratios of the jump height and duration. Interestingly, the ratings were high even when the height and duration differed from the actual jump. To explain this tendency, we constructed computational models that predicted the theoretical trajectory of a jump based on the projectile motion formula and calculated the errors between the theoretical and observed trajectories. The pattern of the errors correlated closely with the participants' ratings. Our results suggest that observers judge the naturalness of observed jumping motion based on the error between observed and predicted jump trajectories.

Islam Nusantara vs Progressive Islam: Dynamics and Transformation in the Modern Context of Indonesia

This journal explores the comparative dynamics and transformative processes of Islam Nusantara and Progressive Islam within the modern Indonesian context. Islam Nusantara, rooted in local traditions and cultural syncretism, emphasizes moderation, tolerance, and integration with indigenous practices. In contrast, Progressive Islam focuses on rationalism, reform, and socio-political activism, drawing from contemporary interpretations of Islamic teachings. This study examines the historical evolution, theological foundations, and socio-political implications of both movements, highlighting their respective responses to global challenges and local contexts. By analyzing primary sources, field studies, and interviews with key figures, this research elucidates the complexities and intersections between these two paradigms. The findings reveal how Islam Nusantara and Progressive Islam shape Indonesian Muslim identity, influence public discourse, and contribute to the broader narrative of Islamic thought in the 21st century. This study provides a nuanced understanding of the ongoing negotiation between tradition and modernity in Indonesian Islam, offering insights into the future trajectories of these influential movements.

Motion Trajectory Perception of an Earthworm-Like Robot Using an Inertial Measurement Unit and Autonomous ZUPT

Motion Trajectory Perception of an Earthworm-Like Robot Using an Inertial Measurement Unit and Autonomous ZUPT

Non-cooperative target recognition and relative motion estimation with inertial measurement unit assistance

This study investigated the problems of non-cooperative target recognition and relative motion estimation during spacecraft rendezvous maneuvers. A structure integrating an Inertial Measurement Unit (IMU) and a visual camera was presented. The angular velocity output of the IMU was used to calculate the motion trajectories of star points in multiple image frames, which can highlight the motion of non-cooperative targets with respect to the image background to improve the probability of target recognition. To solve the problem of target misidentification caused by new star points entering the field of view, a target-tracking link based on IMU prediction was introduced to track the position of the target in the image. Furthermore, a measurement model was constructed using the line-of-sight vector generated from target recognition, and the relative motion state was estimated using a Huber-based non-linear filter. Semi-physical and numerical simulations were performed to evaluate the effectiveness and efficiency of the proposed method.

RAP chunks produced in cold milling operation of asphalt pavement: Evaluation, mechanism, and engineering investigation in China

Cold milling is a widely used method for rehabilitating asphalt pavement, generating reclaimed asphalt pavement (RAP) chunks. Within this process, aggregates within the asphalt pavement will be crushed, forming RAP agglomerates and aggregate breakdown. However, the mechanism of these phenomena has remained unclear, and a unified evaluation method has yet to be established. In this study, RAP agglomeration and aggregate fragmentation were characterized, five distinct methods were systematically assessed, and the mechanism of RAP agglomeration and breakdown was analyzed by discrete element method (DEM) simulation based on setting different particle contact parameters, then followed by a mechanical analysis, and demonstrated in engineering. The results revealed that both agglomeration and aggregate breakdown occur within RAP particles of various sizes, with the five methods showing similar trends in quantifying these effects. Through DEM simulations and mechanical analyses, the aggregate breakdown predominantly occurs at the cutter's motion trajectory of the cutter and during crack propagation, while agglomeration was mainly related to the sliding surface's area. The milling speed and depth positively impact RAP agglomeration, while negatively affecting aggregate breakdown, and milling drum speed exerts minimal influence on these phenomena. RAP agglomeration varies considerably in different engineering projects, and cold milling parameters should be determined based on the material composition of the asphalt pavement and design requirements to control agglomeration and breakdown rates of RAP.

Research on the safety risks of microwave irradiation on motion balance perception in electric power environments

To the microwave irradiation safety hazards caused by the co-construction of towers in smart grids, this paper investigates the effects of microwave irradiation in the power environment on the biological motion balance perception function. Firstly, simulation of microwave signals in the electric power environment, i.e., low-frequency harmonics and high-frequency carriers, were realized by signal modulation and applied in four types of behavior testing scenarios. Then, determining rats as target organisms to replace workers and randomly dividing into groups in proportion: open field, rotating rod fatigue, beam walking and forced swimming. Configuring radar with various parameters to match the electric power irradiation scene and stimulate rats, monitoring the abnormal behavior by image processing module, including posture, motion trajectory, distance, and other features. The experimental result showed that exposed to microwaves induce rats motor ability decline, balance perception imbalance, together with paralysis within long-term exposure, and its locomotor activity, coordination, posture control and reaction time all exhibit varying degrees of weakening. These findings indicate that microwave irradiation in electric power environment may pose significant health and safety risks for worker.

Dynamic and static mutual fitting for action recognition

Action recognition is intended to classify a video into a certain category by aggregating and summarizing its temporal and spatial information. Existing methods have achieved remarkable performance on the standard datasets. However, how to accurately recognize the action under occluded scenarios remains the major challenge in practical applications and is barely explored. Although previous augmentation methods have made some efforts by introducing additional modalities to deal with occlusion cases, the continuous occlusion related to temporal in the video is rarely focused. To tackle this issue, this paper takes the sample augmentation and feature representation into consideration. Specifically, we design a Dynamic Temporal-aware Erasing (DTE) augmentation strategy to enrich the occlusion samples. The proposed DTE builds upon an explicit analysis conditioned with temporal dimension along with the actors’ trajectories, which ensures the capability of carrying the temporal relation to an arbitrary spatial augmentation setting. Specifically, DTE makes the added augmentation samples more temporally consistent with obtaining the motion trajectories of the actors, enhancing the robustness against occlusions. Besides, we revisit the necessity of diverse backgrounds and propose Dynamic and Static Mutual Fitting (DSMF) to optimize the action recognition model. DSMF incorporates background auxiliary mutual fitting actors to distinguish features, which learns a smooth representation with the global temporal consistency. Extensive experiments conducted on standard benchmarks have proved that the proposed DSMF achieves competitive performance over powerful competitors.

Spatiotemporal characteristics of mesoscale eddies in the South China Sea and the influence mechanism of Eddy Kinetic Energy

This paper uses 28 years of satellite altimeter fusion data from 1993 to 2020 to identify and track the mesoscale eddies in the South China Sea based on the Sea Level Anomaly (SLA) closed contour method, with the goal of improving our overall understanding of mesoscale eddy activities in the South China Sea and further investigating the ocean dynamic processes in the region, so as to provide fundamental data for climate change studies. The study examined the spatiotemporal distribution, generation and demise, and movement trajectories of the eddies. Furthermore, key parameters including velocity, vortex radius, amplitude and Eddy Kinetic Energy (EKE) were analyzed, with a particular emphasis on the seasonal changes and mechanisms that influence EKE in two areas of the South China Sea with high energy values. The South China Sea has more cyclonic eddies than anticyclonic eddies, according to the study, and its eastern region is primarily home to high-frequency generating areas. However, the majority of the vortices will eventually dissipate in the western and central areas of the South China Sea. Furthermore, vortices usually flow farther to the west. With decreasing latitude, the eddy radius and EKE distribution gradually increase, whereas the amplitude is contrary. EKE is caused by the interaction of factors including wind field driving, seawater movement, and circulation. Seasonal changes in the EKE occur near the Luzon Strait, and the sea area east of the south in Vietnam exhibits clear characteristics.

Quaternion Regularization of Differential Equations of Perturbed Central Motion and Regular Models of Orbital (Trajectory) Motion: Review and Analysis of Models, Their Applications

Quaternion Regularization of Differential Equations of Perturbed Central Motion and Regular Models of Orbital (Trajectory) Motion: Review and Analysis of Models, Their Applications

Distributed control of spacecraft formation under [formula omitted] perturbation in the port-Hamiltonian framework

To control the relative position and relative velocity of spacecraft formation, a time-varying nonlinear relative motion model under J2 perturbation in an elliptical orbit is established in the port-Hamiltonian (PH) framework, and a distributed control law for spacecraft formation is developed using the consensus algorithm for parameter estimation and the passivity-based control (PBC) method based on the state-error interconnection and damping assignment (IDA) technique. First, the influence of J2 perturbation on the potential energy and orbit parameters in the model is considered when the relative motion model is built in the PH frame, and the expression of the relative motion acceleration under J2 perturbation is given. Second, to solve the problem that the state of the chief spacecraft cannot be directly obtained from the deputy spacecraft under distributed communication, a consensus-based parameter estimation method is introduced, the estimated parameter of the chief spacecraft is applied to the relative motion model in the PH frame, and a state error model with the estimated parameters derived from the consistency algorithm is established. Then, after the stability analysis is conducted on the desired PH system containing the estimated parameter values, the desired Hamiltonian energy function with the estimated parameters is designed according to the time-varying errors of the relative equilibrium states of the deputy spacecraft and the errors between deputy spacecraft, and the distributed control law of spacecraft formation is derived based on the state-error IDA-PBC method. Finally, the expected relative motion trajectory designed based on the TH equation is used to simulate a spacecraft formation under J2 perturbation, and the results indicate that the spacecraft can quickly converge to the expected formation under the influence of the control law.

Tongue and jaw movement assessed by 3D motion capture during gum chewing.

The tongue plays an important role in mastication, swallowing, and articulation, but it cannot be directly observed because of its location inside the oral cavity. This study aimed to clarify detailed 3D tongue movements during chewing using electromagnetic articulography (EMA). The participants were 10 healthy, young volunteers (average age 26.8 ± 2.1years; 5 males, 5 females). Tongue and jaw movement during gum chewing was measured and recorded using EMA. Four EMA sensors were attached to the anterior, posterior, left, and right surfaces of the tongue, and one sensor was also attached to the mandibular left incisor. The tongue motion during the chewing cycle was spatially and sequentially analyzed based on the motion trajectories of the tongue and mandible. The tongue moved downward and to the masticatory side in a manner similar to the movement of the jaw. The anterior tongue marker moved downward to a greater extent than the other tongue markers. However, the tongue moved forward as the jaw moved backward. The anterior marker reached the most anterior position during the jaw-opening phase and the posterior markers reached the most anterior position during the jaw-closing phase. Just before maximum jaw-opening, all markers on the tongue reached the bottom lowest position. During the jaw-closing phase, the tongue reached the dominant farthest position in the masticatory side. All the markers reached the most posterior position during the occlusal phase. These findings demonstrate the sequence of tongue motion patterns during gum chewing.

Flexible control and trajectory planning of medical two-arm surgical robot.

This paper introduces the flexible control and trajectory planning medical two-arm surgical robots, and employs effective collision detection methods to ensure the safety and precision during tasks. Firstly, the DH method is employed to establish relative rotation matrices between coordinate systems, determining the relative relationships of each joint link. A neural network based on a multilayer perceptron is proposed to solve FKP problem in real time. Secondly, a universal interpolator based on Non-Uniform Rational B-Splines (NURBS) is developed, capable of handling any geometric shape to ensure smooth and flexible motion trajectories. Finally, we developed a generalized momentum observer to detect external collisions, eliminating the need for external sensors and thereby reducing mechanical complexity and cost. The experiments verify the effectiveness of the kinematics solution and trajectory planning, demonstrating that the improved momentum torque observer can significantly reduce system overshoot, enabling the two-arm surgical robot to perform precise and safe surgical tasks under algorithmic guidance.

Exploring Electrochemical Direct Writing Machining of Patterned Microstructures on Zr702 with Polyacrylamide Polymer Electrolyte.

Zirconium alloys possess excellent wear resistance, which ensures the durability and longevity of the components, making them widely used in medical and other fields. To enhance the functionality of these materials, it is often necessary to fabricate functional microstructures on their surfaces. Electrochemical machining (ECM) techniques demonstrate excellent machining performance for these metals, particularly in the processing of microstructures on complex curved surfaces. However, ECM often faces challenges due to the fluid nature of the electrolyte, resulting in low machining accuracy and localization. This paper proposes a novel method for fabricating complex patterned microstructures using a maskless electrochemical direct writing technique with a polyacrylamide (PAM) polymer electrolyte. By leveraging the non-Newtonian properties of PAM, this method effectively confines the electrolyte to specific areas, thus addressing the issue of poor localization in traditional ECM and reducing stray corrosion. To elucidate the electrochemical removal mechanism of Zr702 in the presence of PAM, polarization curves, viscosity characteristics, and current efficiency parameters were analyzed. Additionally, an experimental study was conducted using a custom-designed nozzle structure. The results showed that the PAM electrolyte could effectively reduce the EF, positively impacting machining accuracy and localization. By controlling the nozzle's motion trajectory, complex microstructures were successfully fabricated through direct writing, demonstrating promising application prospects.

Dopaminergic manipulations affect the modulation and meta-modulation of movement speed: Evidence from two pharmacological interventions

A body of research implicates dopamine in the average speed of simple movements. However, naturalistic movements span a range of different shaped trajectories and rarely proceed at a single constant speed. Instead, speed is reduced when drawing “corners” compared to “straights” (i.e., speed modulation), and the extent of this slowing down is dependent upon the global shape of the movement trajectory (i.e., speed meta-modulation) – for example whether the shape is an ellipse or a rounded square. At present, it is not known how (or whether) dopaminergic function controls continuous changes in speed during movement execution. The current paper reports effects on these kinematic features of movement following two forms of dopamine manipulation: Study One highlights movement differences in individuals with PD both ON and OFF their dopaminergic medication (N = 32); Study Two highlights movement differences in individuals from the general population on haloperidol (a dopamine receptor blocker, or “antagonist”) and placebo (N = 43). Evidence is presented implicating dopamine in speed, speed modulation and speed meta-modulation, whereby low dopamine conditions are associated with reductions in these variables. These findings move beyond vigour models implicating dopamine in average movement speed, and towards a conceptualisation that involves the modulation of speed as a function of contextual information.