Dynamic Motion Research Articles

A microfluidic manipulation platform based on droplet mixing technology

A microfluidic manipulation platform, utilizing droplet mixing technology in conjunction with piezoelectric actuation, has been constructed. This integration facilitates the realization of efficient and controllable mixing within micro-mixing chips. It boasts rapid droplet generation capabilities and enables precise control over droplet movement and internal mixing dynamics by modulating the operational parameters of the piezo pump. The pump itself offers a broad spectrum of output flow rates and pressures, ensuring ample power for the micro-mixing chip’s dispersed phase input. The platform’s actuation method combines active pressure and acoustic actuation. The efficacy of the platform is substantiated through numerical simulations and experimental validation. Furthermore, an optimization strategy employing support vector regression coupled with a particle swarm algorithm has been introduced for the micro-mixing chip. This method accurately forecasts data trends with minimal error margins. Notably, the micro-mixing chip’s mixing efficiency significantly increases, particularly at lower Reynolds numbers. Experimental findings indicate that the platform’s droplet mixing efficiency exceeds 95 %, rendering it a potent lab-on-a-chip solution for applications in bio-medicine, fine chemistry, and other fields.

Pedaling Asymmetry Reflected by Bilateral EMG Complexity in Chronic Stroke.

This study examines pedaling asymmetry using the electromyogram (EMG) complexity of six bilateral lower limb muscles for chronic stroke survivors. Fifteen unilateral chronic stroke and twelve healthy participants joined passive and volitional recumbent pedaling tasks using a self-modified stationary bike with a constant speed of 25 revolutions per minute. The fuzzy approximate entropy (fApEn) was adopted in EMG complexity estimation. EMG complexity values of stroke participants during pedaling were smaller than those of healthy participants (p = 0.002). For chronic stroke participants, the complexity of paretic limbs was smaller than that of non-paretic limbs during the passive pedaling task (p = 0.005). Additionally, there was a significant correlation between clinical scores and the paretic EMG complexity during passive pedaling (p = 0.022, p = 0.028), indicating that the paretic EMG complexity during passive movement might serve as an indicator of stroke motor function status. This study suggests that EMG complexity is an appropriate quantitative tool for measuring neuromuscular characteristics in lower limb dynamic movement tasks for chronic stroke survivors.

“This Bra Protects me Better than the Military”: Bodies and Protests in the Myanmar Spring Revolution

This article explores the gendered dynamics of revolutionary movements through a focus on women’s bodies as tools of resistance and protest. In the Myanmar Spring Revolution, gendered relations of power articulate with military authority to engender both women’s activism and military responses. To maintain power, the Myanmar military have sought to regulate women’s behaviour – and quell the protest – through attention to women’s bodies, sexuality, and reproductive potential. In response, women activists have mobilised against both state control and the violation of women’s bodies in imaginative and transgressive ways, using their bodies as well as gendered artefacts to subvert patriarchal and military norms. This analysis shows how women’s bodies constitute both the material object of protest – in the virtual and physical spheres – and the subject of resistance, aiming to challenge gendered logics. It means that the gendered body must be taken seriously in studies on revolutions and protests. The integral yet historically overlooked role of women in Myanmar’s revolutionary movements necessitates a gender-conscious analytical lens to fully comprehend the transformative potential and the power dynamics of such upheavals.

The ‘Karman method’ and the boundaries of self‐help: Itinerary of an abortion technology

AbstractThis article explores the controversial itinerary of Harvey Karman and his development in the 1970s of a manual vacuum abortion method which promised a simpler alternative to traditional methods. It highlights Karman's role, often overlooked in abortion rights narratives, as he navigated the transition from illegal to legal abortion, engaging with feminist collectives, doctors and population controllers. Drawing on diverse sources, it examines Karman's efforts to promote his devices and his complex position within medical and feminist circles. The article argues that post‐1972 tension between Karman and feminist activists reveals the gendered alliance dynamics of the abortion movement before and just after Roe v. Wade (1973). It also shows how these tensions encouraged feminist groups to redefine their own practices and led to the delineation of the boundaries of self‐help.

Fluoroscopy: Taking a closer look at joint motion in osteoarthritis

BackgroundKnowledge of joint biomechanics is crucial for understanding the pathophysiology of osteoarthritis (OA). Biomechanical changes, especially in early-stage OA, are subtle and therefore require highly accurate and precise ways of measuring joint loading (i.e., forces) and kinematics (i.e., motion). Most OA research investigating kinematics to date using conventional measurement methods, has been restricted either to measures of functional, weight-bearing activities with limited precision, or to highly precise measures of non-functional activities. X-ray fluoroscopy, however, is a medical imaging modality that can be used to precisely measure high-speed dynamic human movement in vivo under weight-bearing conditions. ObjectiveTo illustrate the potential of fluoroscopy to measure human movement and study joint biomechanics in OA by highlighting several exemplary applications in studies on knee OA. DesignWe searched PubMed to identify a selection of relevant studies with fluoroscopic evaluation of joint mechanics in individuals with, or at risk of developing, knee OA. ResultsFluoroscopy has been utilized in biomechanical studies in populations with early stages of knee OA or at risk of developing knee OA, as well as in studies evaluating conservative treatment strategies for knee OA. Due to its ability to capture highly accurate and precise kinematic measures, fluoroscopy holds great promise in providing new insights in the role of biomechanics in OA pathogenesis. ConclusionsThe use of fluoroscopy in larger cohorts and longitudinal (interventional) studies may lead to more robust and generalizable results and could clarify the mediation pathways of joint biomechanics in the onset and progression of OA.

Study on Aerodynamic Performance and Wake Characteristics of a Floating Offshore Wind Turbine in Wind–Wave Coupling Field

Floating offshore wind turbines (FOWTs) exhibit complex motion with multiple degrees of freedom due to the interaction of wind and waves. The aerodynamic performance and wake characteristics of these turbines are highly intricate and challenging to accurately capture. In this study, dynamic fluid body interaction (DFBI) and overset grid technology are employed to investigate the dynamic motion of a 5 MW FOWT. We use the volume of fluid (VOF) method and improved delayed detached eddy simulation (IDDES) model to investigate the aerodynamic performance and wake evolution mechanism for various wave periods and heights. According to the findings, the magnitude of the pitch motion increases with the period and height of the waves, leading to a decrease in both the power output and thrust; the maximum power was reduced by nearly 6.8% compared to a wind turbine without motion. The value of power and thrust reduction varies for different wave periods and heights, and is influenced by the relative speed and pitch angle, which play a crucial role. Wind–wave coupling has a significant impact on the evolution of both wake and vortex structures for FOWT. The wake shape downstream is also dynamically influenced by the waves. In the presence of wind and wave coupling, the interaction between the wind turbine and the wake is heightened, leading to the merger of two unstable vortex rings into a single, larger vortex ring. The research unveils a comprehensive picture of the offshore wind energy dynamics and wake field, which holds immense significance for the design of floating wind turbines and the optimization of wind farm layout.

Dynamics and wave analysis in longitudinal motion of elastic bars or fluids

We look at the bifurcation analysis, chaotic behavior, multistability, and sensitivity analysis of the van der Waals equation, which is used in science and engineering to study the dynamics of various structures. The variant van der Waals equation covers one-dimensional longitudinal isothermal motion in elastic bars or fluids, which is the main focus of this research. The Galilean transformation transfers the given model into a planar dynamical system. The power series methodology produces exact wave solutions. In addition, after accounting for the perturbation component, sensitivity analysis for various initial value problems is used to investigate quasi-periodic, chaotic, and time series behavior. Numerical simulation results show that influencing viscosity and the coefficient of interfacial capillarity influence the dynamical factors of the examined model. We are observing what happens with viscosity and the interface coefficients to the wave solution. In some cases, for different parameter values, we present plots of both one-dimensional and two-dimensional graphical representations of individual solutions.

Evaluating the motion of a charged solid body having a globular cavity

The dynamical motion of a charged symmetrical solid body (SB) about its main symmetric axis is addressed in this work. The body is supposed to have a chamber with a globular shape, in which it contains a mobile mass and filled with a viscous liquid. This mass is assumed to be coupled via a double elastic band at a point that is situated along the dynamical symmetry axis and produces viscous friction. The body’s motion is influenced by a gyrostatic moment (GM), whose first two components on the body’s main axes are chosen to be zero. Additionally, the body is subject to the effects of an electromagnetic field, owing to a located point charge on the body’s dynamic symmetry axis. On the indicated motion, the combined impact of the viscous liquid and the mobile mass is investigated. The achieved outcomes show that, in the presence of internal dissipation, the system's motion tends towards a constant rotation around its axis at the point of highest inertia as time approaches infinity. To demonstrate how the body’s parameters affect the motion, the obtained outcomes are graphed. The method of fourth-order Runge-Kutta (4RKM) is employed to generate the governing system's numerical results, which are then displayed in additional diagrams. This work's relevance is concentrated on its considerable potential for usage in the submarine and gyroscope industries. The novelty of this work lies in the intricate interplay of rotational dynamics due to the GM, viscous liquid and electromagnetic effects to achieve new results, besides the gained numerical outcomes. Therefore, these results are considered novel and have significant theoretical and practical relevance. Moreover, it can be used to study the motion of celestial bodies, such as planets or moons, which might have internal cavities filled with fluids or other materials. The charged nature could be relevant for bodies with significant magnetic fields.

Robot control based on motor primitives: A comparison of two approaches

Motor primitives are fundamental building blocks of a controller which enable dynamic robot behavior with minimal high-level intervention. By treating motor primitives as basic “modules,” different modules can be sequenced or superimposed to generate a rich repertoire of motor behavior. In robotics, two distinct approaches have been proposed: Dynamic Movement Primitives (DMPs) and Elementary Dynamic Actions (EDAs). While both approaches instantiate similar ideas, significant differences also exist. This paper attempts to clarify the distinction and provide a unifying view by delineating the similarities and differences between DMPs and EDAs. We provide nine robot control examples, including sequencing or superimposing movements, managing kinematic redundancy and singularity, control of both position and orientation of the robot’s end-effector, obstacle avoidance, and managing physical interaction. We show that the two approaches clearly diverge in their implementation. We also provide a real-robot demonstration to show how DMPs and EDAs can be combined to get the best of both approaches. With this detailed comparison, we enable researchers to make informed decisions to select the most suitable approach for specific robot tasks and applications.

Stability Analysis of Controlled DC Motor

Controlled dc motors are nonlinear systems, thatshow a nonlinear action in their operation including, sub-harmonics and chaos when they work outside their designspecifications. This nonlinearity forces the motor changingits normal operation to a random-like behaviour; In thispaper, the nonlinear dynamics of DC motors areinvestigated. It is shown that the concept of the Poincarémap approach and the monodromy matrix method can besuccessfully applied to determine the stability of DC motors

Research on a smart bra design strategy and platform for breast health risk monitoring

To reduce the risk of breast disease in women, we proposed a new smart bra design scheme. We implanted high-precision temperature sensors into the bra for real-time data monitoring, and used multipoint comparison technology to obtain early warnings of breast lesions based on abnormal temperature data. The proposed monitoring system can perform functions such as real-time data feedback, periodic report recording, remote consultation, health management, and electronic medical record generation. Compared with previous approaches, the functionality of this smart bra is not affected by dynamic body movements or environmental temperature, and its monitoring range for breast diseases is wider. This study promotes the monitoring and prevention of breast diseases in women, leading to a shift from disease treatment to disease prevention.

Robot Learning Method for Human-like Arm Skills Based on the Hybrid Primitive Framework.

This paper addresses the issue of how to endow robots with motion skills, flexibility, and adaptability similar to human arms. It innovatively proposes a hybrid-primitive-frame-based robot skill learning algorithm and utilizes the policy improvement with a path integral algorithm to optimize the parameters of the hybrid primitive framework, enabling robots to possess skills similar to human arms. Firstly, the end of the robot is dynamically modeled using an admittance control model to give the robot flexibility. Secondly, the dynamic movement primitives are employed to model the robot's motion trajectory. Additionally, novel stiffness primitives and damping primitives are introduced to model the stiffness and damping parameters in the impedance model. The combination of the dynamic movement primitives, stiffness primitives, and damping primitives is called the hybrid primitive framework. Simulated experiments are designed to validate the effectiveness of the hybrid-primitive-frame-based robot skill learning algorithm, including point-to-point motion under external force disturbance and trajectory tracking under variable stiffness conditions.

Model of Electric Locomotive Simulator Cabin Excitations

Striving to increase the speed of rail vehicles and thus improve the comfort of traveling passengers at the same time, undertakes activities in the sphere of ensuring an appropriate level of safety of rail, passenger, and freight transport. One of the elements of activities in this area is the training of train drivers. Until recently, this training consisted of a theoretical and practical part on the vehicle, alongside an experienced train driver. Considering the increasing level of automation of railway traffic control systems and locomotive equipment, as well as training costs and requirements related to the introduction of TSI, it is becoming an increasingly common requirement to conduct practical training on railway vehicle traffic simulators, while the conditions in the simulator cabin and the trainee’s feelings should correspond to the actual driving conditions. A locomotive driving simulator is a system consisting of a cabin of a suitable type of locomotive or EMU, mapped in 1:1 scale, coupled with a motion excitation system and computer programs connected together forming the software of the cab visualization and dynamics system. The basic program simulating the dynamics and kinematics of the cabin’s motion is a program containing a motion dynamics model that generates signals forcing the movement of the exciters on which the cabin’s platform is mounted. The correct operation of the simulation model depends on the created mathematical model, which can be built in several ways. This article presents the issue of building a mathematical model describing the dynamics of the rail vehicle motion, which can then be used in the simulation model of the simulator cabin motion. Two ways of proceeding in the process of approaching the construction of a mathematical model of rail vehicle motion dynamics will be presented, with the possibility of later use in creating a simulation model of the motion of the locomotive simulator cabin. One of the possible routes was used in the past in the construction of the EP09 locomotive simulator.

Dynamic investigation of the electromechanical coupling system in a permanent magnet direct-drive locomotive under rotor eccentricity faults

In the traction system of a direct-drive locomotive, the gearbox design is eliminated, enabling the direct transmission of output torque from the traction motor to the wheelset. Due to this unique structure, rotor eccentricity, which is a common fault in traction motors, can have a direct impact on the dynamic performance of key components such as the motor, bogie, and wheelset in locomotives. In order to investigate the dynamic response of the direct drive locomotive under rotor eccentricity faults, a comprehensive electromechanical coupling model that considers the dynamic motion of the rotor is established in this paper. The coupling effect between the mechanical system and the electrical system, as well as the dynamic forces induced by rotor eccentricity, are taken into account in the model. The simulation results reveal that ripple torque has an obvious effect on rotor dynamics behaviour, while rotor air-gap eccentricity and mass eccentricity exhibit varying degrees of influence on the dynamic performance of the vehicle system. Furthermore, the influence laws of rotor eccentric distance on the vibration responses of critical locomotive components are revealed. These findings provide valuable theoretical guidance for the operational maintenance and fault diagnosis of traction motors in direct-drive locomotives.

Real-time quantification of in vivo cerebrospinal fluid velocity using the functional magnetic resonance imaging inflow effect.

In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory-gated approaches, such as 4D flow magnetic resonance imaging (MRI), cannot capture CSF movement in real time because of limited temporal resolution and, in addition, deteriorate in accuracy at low fluid velocities. Other techniques like real-time phase-contrast-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability, even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional MRI (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath-holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.

A novel multi-step superposition model for the dispersion analysis of multiaxial prestressed plate-like structures

Understanding the dispersion characteristics of multi-axial prestressed plate-like structures is crucial for the engineering application of guided wave non-destructive testing. However, existing analytical and semi-analytical models neglect both constitutive and geometric nonlinearities induced by the prestress and require tedious theoretical derivation and coding, which may not achieve accurate predictions. To address these issues, a convenient model based on the multi-step superposition analysis was proposed to investigate the effects of an arbitrary multiaxial prestress on the dispersion characteristics of plate-like structures. The core idea of this model involves introducing an initial configuration to describe the static pre-deformation between undeformed and final states; then, the dynamic wave motion was superimposed on the initial pre-deformation for the eigenfrequency analysis. Additionally, the strain energy density of the hyperelastic material was implanted and set as the relevant variable between the two steps by the inheritance of the solution. This model significantly improved the accuracy compared to the conventional method, as validated through biaxial acoustoelastic experiments. Subsequently, the acoustoelastic responses of the multiaxial prestressed 6061-T6 aluminum plate were investigated. The results reveal that the non-uniform in-plane prestress leads to the coupling of guided wave modes propagating along non-principal directions. Furthermore, the effects induced by multiaxial prestress in the frequency bands with low dispersion could be decomposed into the sum of the effects induced by three uniaxial prestresses with a very small deviation. This work provides new insights into the acoustoelastic behavior and a theoretical basis to optimize the guided wave mode and frequency.

A unified formulation of geometry-aware discrete dynamic movement primitives

Learning from demonstration (LfD) is considered as an efficient way to transfer skills from humans to robots. Traditionally, LfD has been used to transfer Cartesian and joint positions and forces from human demonstrations. The traditional approach works well for some robotic tasks, but for many tasks of interest, it is necessary to learn skills such as orientation, impedance, and/or manipulability that have specific geometric characteristics. An effective encoding of such skills can be only achieved if the underlying geometric structure of the skill manifold is considered and the constrains arising from this structure are fulfilled during both learning and execution. However, typical learned skill models such as dynamic movement primitives (DMPs) are limited to Euclidean data and fail in correctly embedding quantities with geometric constraints. In this paper, we propose a novel and mathematically principled framework that uses concepts from Riemannian geometry to allow DMPs to properly embed geometric constrains. The resulting DMP formulation can deal with data sampled from any Riemannian manifold including, but not limited to, unit quaternions and symmetric and positive definite matrices. The proposed approach has been extensively evaluated both on simulated data and real robot experiments. The performed evaluation demonstrates that beneficial properties of DMPs, such as convergence to a given goal and the possibility to change the goal during operation, apply also to the proposed formulation.

Spatial and temporal dynamics of thermal motion of a chain of liquid lead nanoinclusions attached to a fixed dislocation segment in an aluminum matrix

Thermal motion of a chain of liquid lead nanoinclusions attached to a dislocation segment fixed at its ends in the aluminum-based alloy was studied in situ using TEM in the temperature range from 442 °C to 497 °C. The projections of points of the trajectories of the inclusions onto the dislocation line were analyzed. The evidence for the collective interaction of all the inclusions and their spatially correlated collective thermal motion was obtained. Also, moderate temporal autocorrelation of thermal motion of the inclusions and a very weak temporal cross-correlation of thermal motion of the inclusions in all pairs was shown. The FFT phase spectra of the time dependencies of the inclusions positions on the dislocation segment give the evidence for the phase synchronization of thermal oscillations of the inclusions. It is shown that the thermal oscillations of the terminal inclusion attached to the dislocation node and elevation of temperature lead to decrease in the level of synchronization of thermal oscillations of the inclusions in the chain. It is indicated that the development of the process of desynchronization of thermal oscillations of the inclusions manifests itself by an increase in the density of phase steps in the initially linear unwrapped phase spectra accompanying by an increase in the interaction of the steps.

The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin-destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales-10-100 m and 100-3000 m-to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems.

Advanced Computer Vision Methods for Tracking Wild Birds from Drone Footage

Wildlife conservationists have historically depended on manual methods for the identification and tracking of avian species, to monitor population dynamics and discern potential threats. Nonetheless, many of these techniques present inherent challenges and time constraints. With the advancement in computer vision techniques, automated bird detection and recognition have become possible. This study aimed to further advance the task of detecting wild birds using computer vision methods with drone footage, as well as entirely automating the process of detection and tracking. However, detecting objects from drone footage presents a significant challenge, due to the elevated altitudes, as well as the dynamic movement of both the drone and the birds. In this study, we developed and introduce a state-of-the-art model titled ORACLE (optimized rigorous advanced cutting-edge model for leveraging protection to ecosystems). ORACLE aims to facilitate robust communication across multiple models, with the goal of data retrieval, rigorously using various computer vision techniques such as object detection and multi-object tracking (MOT). The results of ORACLE’s vision models were evaluated at 91.89% mAP at 50% IoU.