Bidirectional Motion Research Articles

BRMPNet: bidirectional recurrent motion planning networks for generic robotic platforms in smart manufacturing

BRMPNet: bidirectional recurrent motion planning networks for generic robotic platforms in smart manufacturing

Design and performance evaluation of a stick–slip actuator with Z-shaped beam and two-stage amplification system

Abstract In the domain of piezoelectric driving, actuators that utilize the stick–slip effect at high speeds and low frequency have garnered significant interest. This study presents an innovative linear piezoelectric actuator that integrates a two-stage amplification system with a Z-shaped beam mechanism. The designed actuator has good driving speed at low frequency while overcoming the disadvantage of such actuators requiring two flexible mechanisms to achieve reverse motion and poor reverse performance. The structure and scale of the actuator are explained and designed through theory and simulation. The experimental results demonstrate the prototype’s capability for bidirectional motion. Subjected to a 400 Hz and 140 V excitation, the maximum speed of the actuator is 12.88 mm s−1. The maximum load capacity is tested to be of 0.35 N. This research introduces a new approach for the design of high-speed bidirectional motion stick–slip piezoelectric actuators.

Dynamic Music Video: Categorizing the Convergence of Video Games and Music Videos

The present article examines how the aesthetics of a specific format can be applied to another, thus creating a new autonomous product. This is the case of a distinctive point in video games wherein the playthrough is imbued with music video aesthetics, and the player interacts with the music, camera movements and landscape, becoming the protagonist and architect of what I propose to define as a “Dynamic Music Video”—following Collins’ definition of “dynamic music” (2008, 139). This study analyzes the musical transmedia narratives created from Death Stranding and other contemporary games, both regarding the gameplay experience and the User-Generated Content, focusing on their bidirectional motion: one that converts the players’ experience into a music video inserted into a video game, and one that converts the video game into an autonomous music video.

The Cervical and Meningeal Lymphatic Network as a Pathway for Retrograde Nanoparticle Transport to the Brain.

The meningeal lymphatic vessels have been described as a pathway that transports cerebrospinal fluid and interstitial fluid in a unidirectional manner towards the deep cervical lymph nodes. However, these vessels exhibit anatomical and molecular characteristics typical of initial lymphatic vessels, with the absence of surrounding smooth muscle and few or absent valves. Given its structure, this network could theoretically allow for bidirectional motion. Nevertheless, it has not been assessed as a potential route for nanoparticles to travel from peripheral tissues to the brain. We employed superparamagnetic iron oxide nanoparticles (SPIONs), exosomes loaded with SPIONs, gold nanorods, and Chinese ink nanoparticles. SPIONs were prepared via chemical coprecipitation, while exosomes were isolated from the B16F10 melanoma cell line through the Exo-Spin column protocol and loaded with SPIONs through electroporation. Gold nanorods were functionalized with polyethylene glycol. We utilized C57BL/6 mice for post-mortem and in vivo procedures. To evaluate the retrograde directional flow, we injected each nanoparticle solution in the deep cervical lymph node. The head and neck were fixed for magnetic resonance imaging and histological analysis. Here we show that extracellular vesicles derived from the B16F10 melanoma cell line, along with superparamagnetic iron oxide nanoparticles, gold nanorods, and Chinese ink nanoparticles can reach the meningeal lymphatic vessels and the brain of C57BL/6 mice after administration within the deep cervical lymph nodes post-mortem and in vivo, exclusively through lymphatic structures. The functional anatomy of dural lymphatics has been found to be conserved between mice and humans, suggesting that our findings may have significant implications for advancing targeted drug delivery systems using nanoparticles. Understanding the retrograde transport of nanoparticles through the meningeal lymphatic network could lead to novel therapeutic approaches in nanomedicine, offering new insights into fluid dynamics in both physiological and neuropathological contexts. Further research into this pathway may unlock new strategies for treating neurological diseases or enhancing drug delivery to the brain.

Bidirectional pilus processing in the Tad pilus system motor CpaF

The bacterial tight adherence pilus system (TadPS) assembles surface pili essential for adhesion and colonisation in many human pathogens. Pilus dynamics are powered by the ATPase CpaF (TadA), which drives extension and retraction cycles in Caulobacter crescentus through an unknown mechanism. Here we use cryogenic electron microscopy and cell-based light microscopy to characterise CpaF mechanism. We show that CpaF assembles into a hexamer with C2 symmetry in different nucleotide states. Nucleotide cycling occurs through an intra-subunit clamp-like mechanism that promotes sequential conformational changes between subunits. Moreover, a comparison of the active sites with different nucleotides bound suggests a mechanism for bidirectional motion. Conserved CpaF residues, predicted to interact with platform proteins CpaG (TadB) and CpaH (TadC), are mutated in vivo to establish their role in pilus processing. Our findings provide a model for how CpaF drives TadPS pilus dynamics and have broad implications for how other ancient type 4 filament family members power pilus assembly.

High-dimensional multi-objective optimization of coupled cross-laminated timber walls building using deep learning

This paper introduces a deep learning-based multi-objective optimization framework, applying for advancing the design of the Cross-Laminated Timber Coupled Wall system. While traditional optimization methods often struggle with the curse of dimensionality in high-dimensional problems, the approach proposed in this study employs an autoencoder to effectively reduce the dimensionality of the design space. Subsequently, a neural network establishes a mapping between input variables and latent spaces, with another neural network forming the crucial link between these latent variables and the output responses. The proposed framework is integrated into the design process of a 20-story Cross-Laminated Timber Coupled Wall system, where uncertainties inherent in connection elements are systematically addressed to optimize the structural parameters. The non-dominated sorting genetic algorithm-II is utilized to estimate optimal design variables by minimizing three conflicting objective functions, thereby generating a Pareto front. This optimized design is then bench-marked against three deterministic models with varying coupling beam shear strengths. A two-dimensional numerical model developed in OpenSees facilitates nonlinear time history analysis using 50 bi-directional ground motion records, representative of the seismicity of Vancouver, Canada. The results of this study not only highlight the efficacy of the deep learning-based framework in enhancing the structural integrity and resilience of high-rise timber structures in seismic regions but also significantly contribute to the evolution of computational approaches in structural engineering.

Influence of Repeated Earthquake events on Structural Response of Multi‐storeyed RC buildings

Over the past decade, reinforced concrete (RC) multi-storeyed buildings have become more prevalent in urban environments. In addition, it has been well established in literature, that collapse of several RC buildings and resulting causalities, thereof are mainly attributed to the repeated nature of occurrence of earthquakes, more often leading to collapse. However, most existing design codes consider only a scenario earthquake characterized by the response spectrum specified by local codes of practice. This consideration do not address the repetitive nature of earthquakes, leading to inadequate estimation of design earthquake force. Hence, the present investigation focusses on proposing a probabilistic model to logically address the number of earthquake sequences to be considered at a chosen location. In addition, to ascertain attainment of collapse state of code designed 3D RC buildings, under a pattern of earthquake sequences (with simultaneous bi-directional ground motion data), a simple and computationally less intensive NLTHA (Nonlinear Time History Analysis) approach has been considered. Moreover, this approach captures the effect of sequential earthquakes and provides a quick rational decision on the structural behaviour, necessary for further analysis. Hence, eliminating the need to resort always for complex IDA (Incremental Dynamic Analysis) approaches to illustrate the structural behaviour. Moreover, the structural behaviour of RC buildings are represented in terms of base shear experienced and their corresponding response parameters (Horizontal displacement, Inter-story drift ratio (IDR), etc.,). The outcome of the results clearly contemplates the accumulation of damages in terms of response parameters, emphasizing the need for consideration of repeated earthquake sequences in seismic analysis.

Bidirectional motion of a planar fabricated piezoelectric motor based on unimorph arms

A fabrication methodology for piezoelectric motors based on multiple unimorph arms at the mesoscale is proposed. The combination of laser micromachining and lamination steps allows for a stator with a diameter of 9 mm and a thickness of 0.267 mm to be batch manufactured. This design is investigated via a finite element analysis where it is shown that the contact condition between the stator unimorph arms and rotor is dependent on the input drive frequency. The fabricated stator is then characterized experimentally where it is shown that a shift in the sinusoidal drive frequency from 3220 Hz to 3900 Hz results in a change to the rotational direction of the rotor from the positive to the negative direction. The torque of the motor is evaluated numerically to demonstrate the performance of the mesoscale piezoelectric motor in both rotational directions.

A novel electro-mechanical chewing system for food oral processing research: A comprehensive design approach

This paper presents a comprehensive design approach for an electro-mechanical system for food oral processing research. The bespoke design and prototype of the proposed device is a standalone and compact table top model and can be operated using a customized software interface. The design considered a bi-directional chewing motion to enable nearly similar mandible movement pattern as in human. Food texture profile can be estimated using a load cell with capacity up to 300 N. This design included a section of real shaped teeth assembly consisting of three teeth; and a controlled supply line for multi-point saliva injections. The device is fitted with easily replaceable sensors for in situ measurements of conductivity, pH, and temperature. Operating volume of the device can be kept in equivalence with the volume of human oral and nasal space. The device chamber can be hermetically sealed and temperature controlled. A duct system is fitted to connect the device with external analytical systems, such as electronic nose, for measuring gaseous substance release during experimentation. The system also enables easy retrieval of the processed sample so as to use the masticated samples and processed saliva for subsequent analysis by analytical instruments, such as electronic tongue, to identify released soluble compounds and taste profiles. Moreover, the design emphasized on easy cleaning and maintainability. Based on the proposed design, two working prototypes are developed. It is envisaged that the device will be a novel contribution to the progress in the field of food science, new product development, training to future professionals, and strengthening industry-academic collaborations in foreseeable future.

Lightweight Violence Detection Model Based on 2D CNN with Bi-Directional Motion Attention

With the widespread deployment of surveillance cameras, automatic violence detection has attracted extensive attention from industry and academia. Though researchers have made great progress in video-based violence detection, it is still a challenging task to realize accurate violence detection in real time, especially with limited computing resources. In this paper, we propose a lightweight 2D CNN-based violence detection scheme, which takes advantage of frame-grouping to reduce data redundancy greatly and, meanwhile, enable short-term temporal modeling. In particular, a lightweight 2D CNN, named improved EfficientNet-B0, is constructed by integrating our proposed bi-directional long-term motion attention (Bi-LTMA) module and a temporal shift module (TSM) into the original EfficientNet-B0. The Bi-LTMA takes both spatial and channel dimensions into consideration and captures motion features in both forward and backward directions. The TSM is adopted to realize temporal feature interaction. Moreover, an auxiliary classifier is designed and employed to improve the classification capability and generalization performance of the proposed model. Experiment results demonstrate that the computational cost of the proposed model is 1.21 GFLOPS. Moreover, the proposed scheme achieves accuracies of 100%, 98.5%, 91.67%, and 90.25% on the Movie Fight dataset, the Hockey Fight dataset, the Surveillance Camera dataset, and the RWF-2000 dataset, respectively.

Cross-modal interaction and multi-source visual fusion for video generation in fetal cardiac screening

To address the limitation of preserving data for dynamic visualization in fetal ultrasound screening, a novel framework is proposed to facilitate the generation of fetal four-chamber echocardiogram videos, incorporating multi-source visual fusion and understanding. The framework utilizes an effective spectrogram-ultrasound synchronizer to align the ultrasound images with time, ensuring the generated video matches the actual heartbeat rhythm. It further employs effective frame interpolation techniques to synthesize a video by incorporating a nonlinear bidirectional motion prediction. By integrating a Transformer model for the autoregressive generation of visual semantic sequence, the proposed framework demonstrates its capability to generate high-resolution frames. Experimental outcomes show the Clip-Similarity of 96.23% and DINOv2-Similarity of 99.77%. Furthermore, a multimodal dataset of fetal echocardiogram examinations has been constructed.

Sedimentation of a spherical squirmer in a square tube under gravity

In this study, we used a three-dimensional lattice Boltzmann method to simulate the settling motion of a spherical squirmer in a square tube under the effect of gravity. A spherical squirmer model with chirality was chosen to simulate the motion of a real microswimmer in a three-dimensional space and to systematically analyze its kinematic properties. According to the results of this study, we identified seven different motion modes: diagonal plane large-amplitude oscillation, central stable sedimentation, bidirectional spiral motion, rebound motion, unidirectional spiral motion, corner stable motion, and near-wall attraction oscillation. It was shown that the formation of different motion modes is caused by the effects of squirmer-type factor and chirality. squirmer-type factor determines the stable motion position of the squirmer in the channel. Chirality makes the head direction of the squirmer more susceptible to change, thus changing the motion trajectory of the squirmer. In addition, it was found that the self-propelling strength determines the speed of squirmer’s motion, which affects the motion frequency of squirmer’s periodic oscillations.

A Self‐Powered Dual Ratchet Angle Sensing System for Digital Twins and Smart Healthcare

AbstractIn the swiftly progressing landscape of wearable electronics and the Internet of Things (IoTs), there is a burgeoning demand for devices that are lightweight, cost‐effective, and self‐powered. In this study, a self‐powered bidirectional knee joint motion monitoring system is introduced, leveraging a dual ratchet sensing (DRS) system fabricated using 3D printing technology. This approach offers substantial economic and portability benefits. The DRS system is engineered to harness the negative work generated from knee joint movements to power commercial electronic devices, obviating the need for additional metabolic energy from the human body. By synergizing the DRS with virtual reality technology, it becomes feasible to monitor knee joint movements in real‐time with remarkable accuracy, presenting a novel avenue for the integration of digital twin technology. Through the amalgamation of convolutional neural network machine learning algorithms with Bayesian optimization techniques, the DRS system can discern up to 97% of knee joint movements, paving the way for innovative applications in smart rehabilitation and healthcare.

Multidimensional Seismic Response Analysis of Large-Scale Steel-Reinforced Concrete Frame-Bent Structures in CAP1400 Nuclear Power Plant

Irregularity in the plane layout of a building structure and the vertical discontinuity of lateral resistance components could lead to torsion and result in the brittle failure of a structure. According to the characteristics of the conventional island main building of nuclear power plants, this paper focuses on the conventional island main building of the CAP1400 nuclear power plant (NPP) in Shidaowan as the research object. A prototype structure model of the main building was developed using ABAQUS software. The seismic response of the structure under multidimensional ground motion was studied by inputting the X-direction and Y-direction translational and torsional components of ground motion in ABAQUS. The results demonstrate that the overall transverse displacement of the structure under bidirectional ground motion was significantly higher than that under unidirectional earthquakes, which was about 20%. Under a multidimensional frequent earthquake, the transverse displacement of the structure increased by about 13% on average compared with that under a bidirectional earthquake; the longitudinal increase was the largest, at about 28%. Finally, the lateral displacement of each layer of the steel-reinforced concrete (SRC) frame-bent main building structure with few walls proposed in this article decreased by an average of about 17% compared to the traditional SRC frame-bent main building structure. The longitudinal displacement was reduced by about 14% compared to the traditional SRC frame-bent main building structure.

Real-Time Tracking of Vesicles in Living Cells Reveals That Tau-Hyperphosphorylation Suppresses Unidirectional Transport by Motor Proteins.

Synaptic vesicle transport by motor proteins along microtubules is a crucially active process underlying neuronal communication. It is known that microtubules are destabilized by tau-hyperphosphorylation, which causes tau proteins to detach from microtubules and form neurofibril tangles. However, how tau-phosphorylation affects the transport dynamics of motor proteins on the microtubule remains unknown. Here, we discover that the long-distance unidirectional motion of vesicle-motor protein multiplexes (VMPMs) in living cells is suppressed under tau-hyperphosphorylation, with the consequent loss of fast vesicle-transport along the microtubule. The VMPMs in hyperphosphorylated cells exhibit seemingly bidirectional random motion, with dynamic properties far different from those of VMPM motion in normal cells. We establish a parsimonious physicochemical model of VMPM's active motion that provides a unified, quantitative explanation and predictions for our experimental results. Our analysis reveals that, under hyperphosphorylation conditions, motor protein multiplexes have both static and dynamic motility fluctuations. The loss of fast vesicle-transport along the microtubule can be a mechanism of neurodegenerative disorders associated with tau-hyperphosphorylation.

Cornerstone for MRI-compatible robots: A continuous pneumatic actuator with easy-to-connect prismatic/revolute and bidirectional encoder modules

The exceptional imaging capability of magnetic resonance imaging (MRI) enables the applications of robot-assisted surgery under MRI guidance. Essential to these robotic systems are the MRI-compatible robotic joint actuators. Among various actuation methods using MRI-compatible materials, pneumatic actuators are considered the most suitable for this application scenario due to their sterility, safety, and reliability. Yet, the current pneumatic actuators are either bulky, inefficient, or cannot achieve accurate bidirectional continuous motion. As a step forward, a novel high-performance continuous MRI-compatible pneumatic motor is proposed, along with quick-connect revolute/prismatic motion output modules and high accurate bidirectional encoder modules. The high performance of the pneumatic rotary and linear actuators are evaluated through experimental testing, where the rotary actuator can provide up to 2 Nm of output torque and over 28 W of output power, while the linear variant can deliver over 50 N of thrust, which surpass the SOTA competitors. Corresponding dynamic models are established and verified via experiments, with a maximum error of only 2.01%. Closed-loop control experiments demonstrate the high control precision and fast response frequency of the proposed pneumatic actuators, promoting the performance of joint actuators of various MRI-compatible surgical robots.

IBVC: Interpolation-driven B-frame video compression

Learned B-frame video compression aims to adopt bi-directional motion estimation and motion compensation (MEMC) coding for middle frame reconstruction. However, previous learned approaches often directly extend neural P-frame codecs to B-frame relying on bi-directional optical-flow estimation or video frame interpolation. They suffer from inaccurate quantized motions and inefficient motion compensation. To address these issues, we propose a simple yet effective structure called Interpolation-driven B-frame Video Compression (IBVC). Our approach only involves two major operations: video frame interpolation and artifact reduction compression. IBVC introduces a bit-rate free MEMC based on interpolation, which avoids optical-flow quantization and additional compression distortions. Later, to reduce duplicate bit-rate consumption and focus on unaligned artifacts, a residual guided masking encoder is deployed to adaptively select the meaningful contexts with interpolated multi-scale dependencies. In addition, a conditional spatio-temporal decoder is proposed to eliminate location errors and artifacts instead of using MEMC coding in other methods. The experimental results on B-frame coding demonstrate that IBVC has significant improvements compared to the relevant state-of-the-art methods. Meanwhile, our approach can save bit rates compared with the random access (RA) configuration of H.266 (VTM). The code will be available at https://github.com/ruhig6/IBVC.

Finding and analyzing of the energy and force parameters of the flange formation process by orbital stamping by rolling

The study was carried out based on the developed mathematical model of the discrete hydraulic actuator. The model is characterized by considering the nonlinear friction based on the LuGre model, the bidirectional motion of the asymmetric hydraulic cylinder, and the elastic properties of the fluid. A series of simulation experiments on the braking process of the hydraulic actuator in the discrete control mode were carried out. The quantitative relationship between the rod braking time, the maximum peak pressure in the hydraulic cylinder chambers, the value of the initial rod velocity and the inertial mass of the moving parts are determined. Based on the research results it is possible to predict the braking time of the rod and the maximum peak pressure in the hydraulic cylinder chambers under various operating conditions and inertial loads. These predictions can be used in the settings and design process of hydraulic actuators.

A pneumatic particle-blocking variable-stiffness bending actuator

This study introduces a variable-stiffness pneumatic bending actuator to enhance the stiffness of flexible robots. The bending actuator combines the working principles of a pneumatic drive, a wedge structure, and particle blockage. It enables one-dimensional, bidirectional bending motion and offers pose-maintenance capabilities. The approach to variable-stiffness is both driven and antagonistic. Stiffness in both bending and opposite directions is nonlinearly correlated with air pressure values. Specifically, at 0.5 MPa of air pressure, the stiffness in the bending direction increases to 6.1 times the initial stiffness. At 0.15 MPa, the stiffness in the opposite direction is 2.1 times the initial value. When air pressure is greater than 0.15 MPa, the stiffness incrementally increases due to the wedge impedance force. A driven variable-stiffness control is simple and suitable for applications with a constant load direction, while the antagonistic approach is more suitable for occasions where the load direction changes during movement.

Diverse Motion In-betweening from Sparse Keyframes with Dual Posture Stitching.

In-betweening is a technique for generating transitions given start and target character states. The majority of existing works require multiple (often ≥ 10) frames as input, which are not always available. In addition, they produce results that lack diversity, which may not fulfill artists' requirements. Addressing these gaps, our work deals with a focused yet challenging problem: generating diverse and high-quality transitions given exactly two frames (only the start and target frames). To cope with this challenging scenario, we propose a bi-directional motion generation and stitching scheme which generates forward and backward transitions from the start and target frames with two adversarial autoregressive networks, respectively, and stitches them midway between the start and target frames. In contrast to stitching at the start or target frames, where the ground truth cannot be altered, there is no strict midway ground truth. Thus, our method can capitalize on this flexibility and generate high-quality and diverse transitions simultaneously. Specifically, we employ conditional variational autoencoders (CVAEs) to implement our autoregressive networks and propose a novel stitching loss to stitch the bi-directional generated motions around the midway point.