Tri-Prism Origami Enabled Soft Modular Actuator for Reconfigurable Robots.

Soft actuators hold great potential for applications in surgical operations, robotic manipulation, and prosthetic devices. However, they are limited by their structures, materials, and actuation methods, resulting in disadvantages in output force and dynamic response. This article introduces a soft pneumatic actuator capable of bending based on triangular prism origami.

Novel Design on Knee Exoskeleton with Compliant Actuator for Post-Stroke Rehabilitation.

Knee joint disorders pose a significant and growing challenge to global healthcare systems. Recent advancements in robotics, sensing technologies, and artificial intelligence have driven the development of robot-assisted therapies, reducing the physical burden on therapists and improving rehabilitation outcomes. This study presents a novel knee exoskeleton designed for safe and adaptive rehabilitation, specifically targeting bed-bound stroke patients to enable early intervention.

Leech-Inspired Amphibious Soft Robot Driven by High-Voltage Triboelectricity.

Leech locomotion, characterized by alternating sucker attachment and body contraction provides high adaptability and stability on complex terrains. Herein, a leech-inspired triboelectric soft robot is proposed for the first time, capable of amphibious movement, climbing, and load-carrying crawling. A high-performance triboelectric bionic robot system is developed to drive and control electro-responsive soft robots.

Effectiveness of virtual laboratory in engineering education: A meta-analysis.

With the development of network and simulation technology, virtual laboratories have been widely popularized in engineering education. However, few studies have systematically analyzed and summarized the impact of virtual labs on the effectiveness of engineering education. This study aims to conduct a meta-analysis of published data on the impact of virtual laboratories on engineering students' performance.

Anomaly Detection and Remaining Useful Life Prediction for Turbofan Engines with a Key Point-Based Approach to Secure Health Management.

Aero-engines, particularly turbofan engines, are highly complex systems that play a critical role in the aviation industry. As core components of modern aircraft, they provide the thrust necessary for flight and are essential for safe and efficient operations. However, the complexity and interconnected nature of these engines also make them vulnerable to failures and, in the context of intelligent systems, potential cyber-attacks.

Multi-Channel Fusion Decision-Making Online Detection Network for Surface Defects in Automotive Pipelines Based on Transfer Learning VGG16 Network.

Although approaches for the online surface detection of automotive pipelines exist, low defect area rates, small-sample and long-tailed data, and the difficulty of detection due to the variable morphology of defects are three major problems faced when using such methods. In order to solve these problems, this study combines traditional visual detection methods and deep neural network technology to propose a transfer learning multi-channel fusion decision network without significantly increasing the number of network layers or the structural complexity. Each channel of the network is designed according to the characteristics of different types of defects.

Residual Stress Analysis at the Conductor-Insulator Interface During the Curing Process of Hair-Pin Motors.

The curing process of hair-pin motor stator insulation is critical, as residual stress increases the risk of partial discharge and shortens a motor's lifespan. However, studies on the stress-induced defects during insulation varnish curing remain limited. This research integrates three-dimensional numerical simulations and experimental analysis to develop a curing model based on unsaturated polyester imide resin, aiming to explore the mechanisms of residual stress formation and optimization strategies.

Facile Synthesis of Thermoresponsive Alternating Copolymers with Tunable Phase-Transition Temperatures.

A series of novel amphiphilic alternating CPEG copolymers were synthesized through an amine-epoxy click reaction comprising aliphatic amine and polyethylene glycol diglycidyl ether (PEGDE). These polymers were characterized in detail via nuclear magnetic resonance (NMR), gel permeation chromatography (GPC), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) to confirm the successful synthesis. Due to their amphiphilic structure, these polymers display thermoresponsiveness, with tunable cloud points (Tcps) that are adjustable from 20.

A Modified Multiaxial Fatigue Model and Its Application for the Fatigue Life Prediction of Aircraft Hydraulic Pipes.

The fatigue failure of a structure may occur under a multiaxial vibration environment; it is necessary to establish a better multiaxial fatigue life prediction model to predict the fatigue life of the structure. This study proposes a new model (MWYT) by introducing the maximum absolute shear stress into the WYT model. The feasibility of the MWYT model is verified by using the multiaxial fatigue experimental data of 304 stainless steel, Q235B steel, 7075-T651 aluminum alloy and S355J0 steel.

Newton-Simpson-based predictor-corrector methods for milling chatter stability prediction.

Milling chatter, a form of self-excited vibration, can cause significant damage in machining and manufacturing processes. By selecting appropriate milling parameters, milling chatter can be effectively mitigated without sacrificing milling efficiency. Within the framework of the semi-discretization scheme, this paper introduces the Newton-Simpson-based predictor-corrector methods to compute milling stability lobe diagrams.

Numerical Homogenization Calculation of Effective Stiffness of Fused Deposition Modeling Printing Carbon Fiber Reinforced Polylactic Acid Composites.

The varied material and the inherent complex microstructure make predicting the effective stiffness of fused deposition modeling (FDM) printed polylactic acid (PLA)/carbon fiber (CF) composite a troublesome problem. This article proposes a microstructure scanning electron microscope (SEM) mapping modeling and numerical mean procedure to calculate the effective stiffness of FDM printing PLA/CF laminates. The printed PLA/CF parts were modeled as a continuum of 3D uniform linear elasticity with orthotropic anisotropy, and their elastic behavior was characterized by orthotropic constitutive relations.

Weak fault feature extraction method of rolling bearing based on wavelet packet decomposition and optimized MCKD.

The early fault characteristics of rolling bearings are weak, especially in a strong noise environment, which are more difficult to extract; therefore, a method based on wavelet packet decomposition, multi-verse optimizer, and maximum correlated kurtosis deconvolution for weak fault feature extraction of rolling bearings is proposed. First, the original vibration signal is decomposed using wavelet packet decomposition, followed by proposing a signal reconstruction method combining the Pearson correlation coefficient and energy ratio to effectively remove noise from the original signal. Second, the parameters L and M of Maximum Correlated Kurtosis Deconvolution (MCKD) are optimized using the multi-verse optimizer algorithm to obtain optimal filter settings.

Considering the Bottom Edge Cutting Effect of the Carbon Fiber Reinforced Polymer Milling Force Prediction Model and Optimization of Machining Parameters.

The milling force plays a pivotal role in CFRP milling. Modeling of the milling force is helpful to explore the changing law, optimize the processing parameters, and then reduce the appearance of defects. However, most of the existing models ignore the effect of the bottom edge.

Fundamentals of Viscoelastic Particle Focusing in Suddenly Expanded Microfluidic Channels.

Particles focusing in suddenly expanded microfluidic channels with viscoelastic biofluids have attracted increased interests due to the potential biomedical applications. In this work, three types of suddenly expanded channels were designed and employed for experiments. These suddenly expanded channels contained a certain number of triangular expansion structures on the sides of the straight channel to investigate the effect of secondary flow on particle viscoelastic focusing and we investigated particle focusing behavior in those three channels with 0.

Bio-inspired piezoelectric stick-slip actuation: Synergistic bridge-type and leveraged amplification mechanism via rowing-motion mimicry.

This paper presents the development of a new bionic piezoelectric stick-slip actuator (PSSA). This actuator is designed to simulate the human rowing motion. By synergizing a lever amplification structure with a bridge amplification mechanism, the design not only mimics the rowing motion, where the lever amplification structure acts like an oar and the bridge amplification mechanism resembles the force exerted by a person operating the oar, but also suppresses the problem of backward displacement in traditional PSSAs.

Study on the mechanism of grain size and residual stress coupling distribution on the intergranular corrosion susceptibility of AZ31B magnesium alloy.

In this paper, homogenization heat treatment and laser shock peening (LSP) processes were successfully carried out regulate the microstructure (grain size, residual stress, and element distribution, ) of the AZ31B magnesium alloy substrate surface. Based on the regulated AZ31B magnesium alloy substrate surface, it further explored and analyzed the mechanism and influence pattern of the coupling distribution of grain size and residual stress on the intergranular corrosion susceptibility of the substrate surface. Scanning electron microscopy (SEM) was used to observe the surface morphology, scanning Kelvin probe force microscopy (SKPFM) to observe the surface potential, zero resistance ammeter (ZRA) and scanning vibrating electrode technique (SVET) to measure the galvanic current on the surface, and electrochemical tests were conducted to evaluate its surface corrosion behavior.

Research on the material removal mechanism of vibration-assisted nano-scratch on single-crystal GaN by molecular dynamics.

Context: Single-crystal gallium nitride (GaN) is a semiconductor material known for its hardness and brittleness. This research aims to reveal the differences in the micro-mechanisms of material removal during traditional grinding and ultrasonic vibration-assisted grinding and to provide guidance for the high-efficiency, high-quality planarization processing of single-crystal GaN. To achieve this purpose, molecular dynamics (MD) simulation methods were used to establish a model (30 nm × 40 nm × 15 nm) of single-crystal GaN being scratched by a single abrasive grain with and without ultrasonic vibration assistance.

Bufei Huoxue capsule alleviates silicosis by inhibiting the activation of nucleotide-like receptor containing pyrin domain 3 inflammasome and macrophages polarization based on network pharmacology.

Objective: To predict the targets of Bufei Huoxue capsule (, BFHX) using network pharmacology analysis and to explore its effects and functional targets in a silicotic rat model.

Methods: The drug and disease targets were correlated through network pharmacology analysis to explore the targets and signaling pathways of BFHX affecting silicosis. NR8383 cells were cultured to verify the core genes and pathways.

Aerodynamic Analysis of Rotor Spacing and Attitude Transition in Tilt-Powered Coaxial Rotor UAV.

Complex aerodynamic characteristics and optimal control during the attitude transition of tilt-powered coaxial twin-rotor unmanned aerial vehicles (UAVs) represent key challenges in flight control design. This study investigates aerodynamic mechanisms and control parameter optimization during the transition of UAVs from vertical to forward flight. By establishing a dynamic model and combining theoretical and numerical analyses, the optimal rotor spacing is determined to be h = 0.

Simultaneous Localization and Mapping Methods for Snake-like Robots Based on Gait Adjustment.

Snake robots require autonomous localization and mapping capabilities for field applications. However, the characteristics of their motion, such as large turning angles and fast rotation speeds, can lead to issues like drift or even failure in positioning and map building. In response to this situation, this paper starts from the gait motion characteristics of the snake robot itself, proposing an improved gait motion method and a tightly coupled method based on IMU and visual information to solve the problem of poor algorithm convergence caused by head-shaking in snake robot SLAM.

Construction of a CNN-SK weld penetration recognition model based on the Mel spectrum of a CMT arc sound signal.

Arc sound signals are considered appropriate for detecting penetration states in cold metal transfer (CMT) welding because of their noninvasive nature and immunity to interference from splatter and arc light. Nevertheless, the stability of arc sound signals is suboptimal, the conventional feature extraction methods are inefficient, and the significance of arc sound attributes for determining penetration statuses is often overlooked. In this study, a compact convolutional neural network (CNN) model is proposed for the adaptive extraction of features from arc sound signals.

Research of neural network-based model for nonlinear temperature drift compensation of MEMS accelerometers.

Downhole instrumentation requires more and more accuracy of MEMS inertial sensors. However, in measurement while drilling, temperature drift phenomenon of the sensor will have a cumulative impact on the drill pipe attitude solution. After experimental testing, the output response of the accelerometer had strong local linear and global nonlinear characteristics.

Assessment of rTMS treatment effects for methamphetamine addiction based on EEG functional connectivity.

Unlabelled: Methamphetamine (MA) addiction leads to impairment of neural communication functions in the brain, and functional connectivity (FC) may be a valid indicator. However, it is unclear how FC in the brain changes in methamphetamine use disorder (MUD) after treatment with repetitive transcranial magnetic stimulation (rTMS). Thirty-four patients with MUD participated in this study.

Motor imagery decoding using source optimized transfer learning based on multi-loss fusion CNN.

Transfer learning is increasingly used to decode multi-class motor imagery tasks. Previous transfer learning ignored the optimizability of the source model, weakened the adaptability to the target domain and limited the performance. This paper first proposes the multi-loss fusion convolutional neural network (MF-CNN) to make an optimizable source model.