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The heightened autonomy and robust adaptability inherent in a multi-robot system have proven pivotal in disaster search and rescue, agricultural irrigation, and environmental monitoring. This study addresses the coordination of multiple robots for the surveillance of various key target positions within an area. This involves the allocation of target positions among robots and the concurrent planning of routes for each robot. To tackle these challenges, we formulate a unified optimization model addressing both target allocation and route planning. Subsequently, we introduce an adaptive memetic algorithm featuring dual-level local search strategies. This algorithm operates independently among and within robots to effectively solve the optimization problem associated with surveillance. The proposed method’s efficacy is substantiated through comparative numerical experiments and simulated experiments involving diverse scales of robot teams and different target positions.

Abstract The permanent magnet eddy‐current coupler (PMEC) is a kind of non‐contact, stepless speed regulation device and has been widely used in transmissions. However, the current PMECs are coaxial and cannot achieve transmission and speed regulation in intersecting axes. An intersecting‐axis permanent magnet (PM) eddy current coupler (IPMEC), which consists of a disk‐type PM rotor and a barrel‐type conductive sheet (CS) rotor arranged with intersecting axes, is proposed. It generates eddy currents through the speed difference between the two rotors and uses the non‐contact electromagnetic force between the eddy currents and permanent magnets to transmit torque. During operation, the speed can be adjusted by altering the coupling area or air gap. A theoretical model of the IPMEC based on the equivalent magnetic circuit method is presented and verified by finite element simulation using ANSYS. Then, the effects of the pole number of the PMs, the radius of the CS rotor and the PM rotor on the performance were analysed, and the design method of the IPMEC was proposed. This study can be used to expand the application range of PMECs.

Additive manufacturing (AM) technology facilitates the creation of complex structures, where the printing path significantly impacts thermal distribution, subsequently influencing stress distribution and structural deformation. The primary challenge in path planning is to determine a printing turn angle that ensures uniform thermal distribution, thereby minimizing structural deformation while maintaining printing efficiency. To address this issue, we propose a composite function, which comprehensively characterizes the effects of the printing turn angle and the length of the printing path on the printing results. Combining a specific cubic porous structure, we calculate the maximum (Pmax) and minimum (Pmin) values of the composite function P, and compare the structural deformation and stress of the Pmax and Pmin paths with those of the typical Pzigzag path. Finite element method (FEM) simulation and experimental validation show that the Pmax path achieves significantly lower structural deformation and residual stress compared to the Pzigzag path and Pmin path.

Abstract Magnetic soft robots have shown great potential for biomedical applications due to their high shape reconfigurability, motion agility, and multi-functionality in physiological environments. Magnetic soft robots with multi-layer structures can enhance the loading capacity and function complexity for targeted delivery. However, the interactions between soft entities have yet to be fully investigated, and thus the assembly of magnetic soft robots with on-demand motion modes from multiple film-like layers is still challenging. Herein, we model and tailor the magnetic interaction between soft film-like layers with distinct in-plane structures, and then realize multi-layer soft robots that are capable of performing agile motions and targeted adhesion. Each layer of the robot consists of a soft magnetic substrate and an adhesive film. The mechanical properties and adhesion performance of the adhesive films are systematically characterized. The robot is capable of performing two locomotion modes, i.e., translational motion and tumbling motion, and also the on-demand separation with one side layer adhered to tissues. Simulation results are presented, which have a good qualitative agreement with the experimental results. The feasibility of using the robot to perform multi-target adhesion in a stomach is validated in both ex-vivo and in-vivo experiments.

Path pattern is one of the most significant parameters in the additive manufacturing (AM) process because it influences the specimen's final shape and residual stress distribution. Generally, the optimal path pattern is a computationally expensive, high-dimensional, and black-box permutation optimization problem. In this paper, we propose a combinatorial radial basis function surrogate-assisted genetic algorithm (CRBF-GA) to effectively generate the optimal path pattern by integrating the combinatorial radial basis function surrogate model (CRBF) with the genetic algorithm (GA). To demonstrate the effectiveness of the proposed CRBF-GA, a Ti-6Al-4V thin rod, a component of lattice, is chosen as the research object. Through numerical simulation, experimental verification, and error comparison analysis, the RBF-GA pattern is demonstrated to be the best path pattern among the random forest-assisted evolutionary algorithm (RF-EA), GA, spiral, and zigzag patterns, and it excels in achieving a more precise rod shape compared to the other patterns examined.

Electrorheological (ER) technology is an advanced technology based on ER effects. The most common material in ER technology is an electrorheological fluid (ERF), which is a type of smart soft material. The viscosity of ERF is reversibly adjustable by an applied electric field. A new type of electroresponsive soft material, electrorheological elastomer (ERE), which is a derivative of ERFs, has attracted wide attention due to its advantages of not precipitating and easy packaging. ER materials are widely applied in mechanical engineering due to their reversibly tunable characteristics, fast response, and low energy consumption. In addition to basic ER material fabrication and application, ER technology is also used in energy material preparation, oil transportation, and energy storage. The application of ER technology in the energy field provides a good example of the potential applications of ER technology in other fields. This article systematically summarizes the research status and future development prospects of ER technology in materials, energy, and mechanical engineering from the mechanism to application, combined with the latest research results.

Wire-arc directed energy deposition has the potential to revolutionize the production process of large-size components with faster deposition speeds at a lower cost. As the cornerstone of modern materials, steels, especially high-performance steels with properties such as corrosion, wear, and heat resistance, have increasingly been applied in wire-arc directed energy deposition. This paper provides a review of recent advancements in wire-arc directed energy deposition of high-performance steels, covering the microstructure, properties, and defect formation mechanism. Aiming at the properties of high-performance steels deposited by wire-arc directed energy deposition, such as thermal history and cooling rate. The comprehensive review had been introduced for the perspective what the simulation, analysis, and their composition with results and pre/in-situ/post-process for improving the properties of wire-arc directed energy deposition processed high-performance steels are then summarized. Finally, a systematic framework for performance optimization of wire-arc directed energy deposition high-performance steels is proposed. This review contributes to a better scientific understanding of the wire-arc directed energy deposition of high-performance steels and puts forward guiding opinions for the future work on high-performance steels manufacturing.

The prediction of significant wave height (SWH) is crucial for managing wave energy. While many machine learning studies have focused on accurately predicting SWH values within hours in advance, the primary concern should be given to the level of the wave height for real-world applications. In this paper, a classification framework for the time-series of SWH based on Transformer encoder (TF) and empirical mode decomposition (EMD) is developed, which can provide a lead time of 6 to 48 h with the fixed thresholds of 2 m for high level waves and 1.5 m for low level waves. The performance of this approach is compared to that of three mainstream algorithms with and without EMD features. Results from the datasets collected from buoy measurements in the Atlantic Ocean indicate that the optimal mean accuracy at a lead time of 6 h was 99.1% and the average training time was 75 s, demonstrating the accuracy and efficiency of this proposed model. This study provides valuable tools and references for real-world SWH prediction applications.

Here we developed a novel strategy to predict and control the electrothermal property and deformation pattern of electrically stimuli-responsive structures by printing programmable conductive patterns inside liquid crystal elastomer (LCE). It was found that the printed conductive patterns had excellent electrothermal performance and can be heated up to 120°C within 12 s under the stimulus of an applied voltage. By controlling the width and spacing of the conductive lines, the electrothermal temperature of bilayer LCE structures can be regionally modulated, which subsequently determines the structural deformation for desired actuation. A finite element simulation method was established to accurately predict the effect of different conductive pattern design on the final deformation profiles, which showed a good consistence to the experimental results. The presented strategy exhibited unique capability in fabricating conductive pattern-embedded electrothermal structures for various programmable deformations like wing flapping, soft robot crawling and finger bending.

Jumping is an important locomotion function to extend navigation range, overcome obstacles, and adapt to unstructured environments. Here, authors demonstrate legless soft robot capable of rapid, continuous, and steered jumping based on a soft electrohydrostatic bending actuator.

Optical detection equipment (ODE) is subjected to vibrations that hamper the quality of imaging. In this paper, an active vibration isolation and compensation system (VICS) for the ODE is developed and systematically studied to improve the optical imaging quality. An active vibration isolator for cameras is designed, employing a dual-loop control strategy with position compensation and integral force feedback (IFF) control, and establishing the mapping relationship between vibration and image quality. A performance metric for evaluating images is also proposed. Finally, an experimental platform is constructed to verify its effectiveness. Based on the experimental results, it can be concluded that the proposed VICS effectively isolates vibrations, resulting in a reduction of 13.95 dB in the peak at the natural frequency and an 11.76 Hz widening of the isolation bandwidth compared with the system without it. At the same time, the experiments demonstrate that the image performance metric value increases by 46.03% near the natural frequency.

Abstract A comparative study of model predictive control (MPC) schemes and robust $$H_{\infty }$$ H ∞ state feedback control (RSC) method for trajectory tracking is proposed in this paper. The main objective of this paper is to compare MPC and RSC controllers’ performance in tracking predefined trajectory under different scenarios. MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire, which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode. RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison. Then, three test cases are built in CarSim-Simulink joint platform. Specifically, the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions. Besides, the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability. Furthermore, an extreme curve test is built where the road adhesion changes suddenly, in order to test the performance of both controllers under extreme conditions. Finally, the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

By designing double emissive layers, orange light-emitting layer (EML) and red EML and a space layer of blending hole-transporting material (HTM) with electron-transporting material (ETM), we have achieved efficient and color-tunable organic light-emitting diodes (OLEDs). It is found that the red shift of EL spectrum was enhanced when the ratio of HTM to ETM was 5:1. And a maximum current efficiency of 41.17 cd/A was reached. It has been demonstrated that two ultra-thin emissive layers could improve the current efficiency of the OLEDs. The current efficiency of the OLEDs with a 1 nm o;6range EML and a 1 nm red EML was enhanced by 27.4 % as compared to the reference devices. This is a novel approach to realizing voltage-controlled electroluminescence (EL) over different colors and intensity in a single OLED. The color-tunable OLEDs show the potential to be utilized as rear light on motor vehicle. We have investigated the effect of the ratio of HTM to ETM on the efficiency and spectral shift of the OLEDs through the control of recommendation zone.

Acoustic liners are the most effective solution to attenuate the noise of ducts with flows but still suffer from narrow sound absorption bandwidth and heavy bulk. In this work, we present a new type of acoustic meta-liner structure, which is composed of perforated plates and coiled-up Fabry–Pérot (FP) channels with carefully designed equivalent length. By tuning the geometric parameters of the perforated plate and the optimal combination of the coiled-up FP channels, perfect impedance matching is achieved in a broadband range. The strong dissipation of sound energy could also be observed under different speeds of grazing flow and high incident sound intensity. It is analytically, numerically, and experimentally demonstrated that for the structure, over 90% sound absorption is achieved in the broadband range from 500 to 3000 Hz in the absence of flow and the condition of grazing flow with a speed of 30–98 m/s, coupled with a 90–130 dB incident sound pressure level. Moreover, the thickness of the proposed simply structured meta-liner is 44 mm, which is only 8/125th of the wavelength corresponding to 500 Hz. As a deep sub-wavelength liner, it exhibits potential application prospects in the field of fluid–solid coupled machinery such as aero-engine systems and ventilation duct systems.

Ultra-broadband sound absorption with periodic gradient impedance matching is of great concern in the research of acoustic materials. This study investigates the impedance matching of composite acoustic metamaterials comprising micro-perforated plates (MPPs) and subsequent Fabry–Pérot(FP) channels. Based on the impedance matching theory, ultra-broadband sound absorption has been realized through a design with 36 channels whose thickness is only 50 mm. Also, the average sound absorption coefficient of 88% and an absorption frequency bandwidth (490–4000 Hz) can be achieved by preserving the matching impedance. Furthermore, by changing the thickness of the perfect absorber being 100 mm, the average sound absorption coefficient can reach greater than 90% in the frequency range of 250–4500 Hz. The proposed structure is validated analytically and experimentally. This work can help with designing and improving the method of acoustic metasurfaces and especially have the potential in ultra-broadband sound absorber designs.

In this article, the problem of video inpainting combines multiview spatial information and interframe information between video sequences. A vision system is an important way for autonomous vehicles to obtain information about the external environment. Loss or distortion of visual images caused by camera damage or pollution seriously makes an impact on the vision system ability to correctly perceive and understand the external environment. In this article, we solve the problem of image restoration by combining the optical flow information between frames in the video with the spatial information from multiple perspectives. To solve the problems of noise in the single-frame images of video frames, we propose a complete two-stage video repair method. We combine the spatial information of images from different perspectives and the optical flow information of the video sequence to assist and constrain the repair of damaged images in the video. This method combines the interframe information of the front and rear image frames with the multiview image information in the video and performs video repair based on optical flow and a conditional generation adversarial network. This method regards video inpainting as a pixel propagation problem, uses the interframe information in the video for video inpainting, and introduces multiview information to assist the repair based on a conditional generative adversarial network. This method was trained and tested in Zurich using a data set recorded by a pair of cameras mounted on a mobile platform.

In this paper, an active control strategy is employed to actively tune the vibration and wave propagation properties in a piezoelectric metamaterial beam. The piezoelectric actuator and sensor are periodically arranged along the piezoelectric metamaterial beam. By using the extended Hamilton principle, the governing equations for the fully coupled piezoelectric metamaterial beam are obtained. The negative proportional feedback control strategy is introduced to achieve the periodical active stiffness for the piezoelectric metamaterial beam. The band structures and natural frequencies of the proposed periodic structure are derived by the transfer matrix method, and the spectral element method is applied as numerical validation. The influences of the feedback control gain ratio, length ratio, and the number of the unit cells on natural frequencies and bandgaps are discussed. Results indicate that the natural frequencies of the system are reduced with the increase in the feedback control gain ratio and length ratio. In addition, multiple bandgaps can be generated by using the negative proportional feedback control strategy. It is found that bandwidths can be obviously broadened by selecting the proper feedback control gain ratio and length ratio. The theoretical and numerical results show that the vibration and wave propagation properties of the proposed piezoelectric metamaterial beam can be controlled by using the negative proportional feedback control strategy.

Deep classification tracking aims at classifying the candidate samples into target or background by a classifier generally trained with a binary label. However, the binary label merely distinguishes samples of different classes, while inadvertently ignoring the distinction among the samples belonging to the same class, which weakens the classification and locating ability. To cope with this problem, this article proposes a soft labeling with quasi-Gaussian structure instead of the binary labeling, which distinguishes the samples belonging to different classes and the same class simultaneously. Like as the binary label, the signs of labels for target and background samples are set to be plus and minus respectively to distinguish samples of different classes. Further, to exploit the difference among samples in the same class, the label values of samples in the same class are designed as a monotonically decreasing quasi-Gaussian function about Intersection over Union. Therefore, the corresponding response function is a two-piecewise monotonically increasing quasi-Gaussian combination function about Intersection over Union. Due to such response function, deep classification tracking trained with this proposed soft labeling achieves better classification and location performance. To validate this, the proposed soft labeling is integrated into the pipeline of the deep classification tracker SiamFC. Experimental results on OTB-2015 and VOT benchmark show that our variant achieves significant improvement to the baseline tracker while maintaining real-time tracking speed and acquires comparable accuracy as recent state-of-the-art trackers.

A novel hybridization scheme is proposed with electromagnetic transduction to improve the power density of piezoelectric energy harvester (PEH) in this paper. Based on the basic cantilever piezoelectric energy harvester (BC-PEH) composed of a mass block, a piezoelectric patch, and a cantilever beam, we replaced the mass block by a magnet array and added a coil array to form the hybrid energy harvester. To enhance the output power of the electromagnetic energy harvester (EMEH), we utilized an alternating magnet array. Then, to compare the power density of the hybrid harvester and BC-PEH, the experiments of output power were conducted. According to the experimental results, the power densities of the hybrid harvester and BC-PEH are, respectively, 3.53 mW/cm3 and 5.14 μW/cm3 under the conditions of 18.6 Hz and 0.3 g. Therefore, the power density of the hybrid harvester is 686 times as high as that of the BC-PEH, which verified the power density improvement of PEH via a hybridization scheme with EMEH. Additionally, the hybrid harvester exhibits better performance for charging capacitors, such as charging a 2.2 mF capacitor to 8 V within 17 s. It is of great significance to further develop self-powered devices.

With the improvement of the performance of optical equipment carried by on-orbit spacecraft, the requirements of vibration isolation are increasing. Passive isolation platforms are widely used, but the ability to suppress the low-frequency deterministic vibration disturbance is limited, especially near the system’s natural frequency. Therefore, an active vibration control strategy is proposed to improve passive isolation performance. In this paper, a Youla parameterized adaptive active vibration control system is introduced to improve the isolation performance of a piezo-actuated active–passive isolation structure. A linear quadratic Gaussian (LQG) central controller is first designed to shape the band-limited local loop of the closed-loop system. Then, the central controller is augmented into a Youla parameterized adaptive regulator with the recursive least square adaptive algorithm, and the Youla parameters (Q parameters) can be adjusted online to the desired value to suppress the unknown and time-varying multifrequency deterministic vibration disturbance. In the experiment, the residual vibration with respect to the combination of multiple frequencies is effectively suppressed by more than 20 dB on average, and a quick response time of less than 0.3 s is achieved when the deterministic residual vibration changes suddenly over time. The experimental results illustrate that the proposed adaptive active vibration control system can effectively suppress the low-frequency deterministic residual vibration.

The high performance and efficiency of multiple unmanned surface vehicles (multi-USV) promote the further civilian and military applications of coordinated USV. As the basis of multiple USVs’ cooperative work, considerable attention has been spent on developing the decentralized formation control of the USV swarm. Formation control of multiple USV belongs to the geometric problems of a multi-robot system. The main challenge is the way to generate and maintain the formation of a multi-robot system. The rapid development of reinforcement learning provides us with a new solution to deal with these problems. In this paper, we introduce a decentralized structure of the multi-USV system and employ reinforcement learning to deal with the formation control of a multi-USV system in a leader–follower topology. Therefore, we propose an asynchronous decentralized formation control scheme based on reinforcement learning for multiple USVs. First, a simplified USV model is established. Simultaneously, the formation shape model is built to provide formation parameters and to describe the physical relationship between USVs. Second, the advantage deep deterministic policy gradient algorithm (ADDPG) is proposed. Third, formation generation policies and formation maintenance policies based on the ADDPG are proposed to form and maintain the given geometry structure of the team of USVs during movement. Moreover, three new reward functions are designed and utilized to promote policy learning. Finally, various experiments are conducted to validate the performance of the proposed formation control scheme. Simulation results and contrast experiments demonstrate the efficiency and stability of the formation control scheme.

To ensure the mission implementation of Autonomous Underwater Vehicles (AUVs), faults occurring on actuators should be detected and located promptly; therefore, reliable control strategies and inputs can be effectively provided. In this paper, faults occurring on the propulsion and attitude control systems of a torpedo-shaped AUV are analyzed and located while fault features may induce confusions for conventional fault localization (FL). Selective features of defined fault parameters are assorted as necessary conditions against different faulty actuators and synthesized in a fault tree subsequently to state the sufficiency towards possible abnormal parts. By matching fault features with those of estimated fault parameters, suspected faulty sections are located. Thereafter, active FL strategies that analyze the related fault parameters after executing purposive actuator control are proposed to provide precise fault location. Moreover, the generality of the proposed methods is analyzed to support extensive implementations. Simulations based on finite element analysis against a torpedo-shaped AUV with actuator faults are carried out to illustrate the effectiveness of the proposed methods.

As a new type of marine unmanned intelligent equipment, autonomous underwater vehicle (AUV) has been widely used in the field of ocean observation, maritime rescue, mine countermeasures, intelligence reconnaissance, etc. Especially in the underwater search mission, the technical advantages of AUV are particularly obvious. However, limited operational capability and sophisticated mission environments are also difficulties faced by AUV. To make better use of AUV in the search mission, we establish the DMACSS (distributed multi-AUVs collaborative search system) and propose the ACSLA (autonomous collaborative search learning algorithm) integrated into the DMACSS. Compared with the previous system, DMACSS adopts a distributed control structure to improve the system robustness and combines an information fusion mechanism and a time stamp mechanism, making each AUV in the system able to exchange and fuse information during the mission. ACSLA is an adaptive learning algorithm trained by the RL (Reinforcement learning) method with a tailored design of state information, reward function, and training framework, which can give the system optimal search path in real-time according to the environment. We test DMACSS and ACSLA in the simulation test. The test results demonstrate that the DMACSS runs stably, the search accuracy and efficiency of ACSLA outperform other search methods, thus better realizing the cooperation between AUVs, making the DMACSS find the target more accurately and faster.

In this paper, we propose a generator for piezoelectric energy harvesting from suspension structures. This device consists of a leaf spring and eight pairs of piezoelectric layers attached to inner and outer surfaces. We present a special type of leaf spring, which can magnify the force from the workload to allow the piezoelectric layers to achieve larger deformation. The generator is to solve the problem of vibration energy reutilization in a low-frequency vibration system. To verify the efficiency of the proposed configuration, a series of experiments are operated. The results indicate that the resonance frequency (25.2 Hz) obtained from the sweep experiment is close to the simulation result (26.1 Hz). Impedance-matching experiments show that the sum of the output power attains 1.7 mW, and the maximum single layer reaches 0.6 mW with an impedance matching of 610 KΩ, and the instantaneous peak-peak power density is 3.82 mW/cm3. The capacitor-charging performance of the generator is also excellent under the series condition. For a 4.7 μF capacitor, the voltage is charged to 25 V in 30 s and limited at 32 V in 80 s. These results demonstrate the exploitable potential of piezoelectric energy harvesting from suspension structures.

Unmanned surface vehicles (USVs) as unmanned intelligent devices can replace humans to perform missions more efficiently and safely in dangerous areas. However, due to the complex navigation environment and special mission requirements, USVs face many challenges in emergency response missions for marine oil spill accidents. To solve these challenges in the emergency response mission of the ‘Sanchi’ oil tanker collision and explosion accident, we designed and deployed an USV to perform the missions of real-time scanning and water sampling in the shipwreck waters. Compared with the previous USVs, our USV owned the following characteristics: Firstly, the improved navigation control algorithms (path following and collision avoidance) can provide high navigation accuracy while ensuring navigation safety; Secondly, an improved launch and recovery system (LARS) enabled the USV to be quickly deployed and recovered in the mission area; Thirdly, a new sampling system was specially designed for the USV. Our USV completed the missions successfully, not only providing a lot of information for rescuers but also offering a scientific basis for follow-up work.

Both Young’s modulus and specific membrane capacitance (SMC) are two important physical parameters for characterizing cell status. In this paper, we utilized a thin-neck-micropipette aspiration system to simultaneously quantify Young’s modulus and SMC value of six types of cell lines in different progression grades, which include four grades from the lowest metastatic potential G1 to the highest potential G4. We investigated how these two physical properties possess heterogeneities in bladder cancer cells with different grades and what roles they might play in grading bladder cancer. The characterization results of these cells of different cancer grades is linearly correlated with the cancer grades, showing that the Young’s modulus is negatively linearly correlated with bladder cancer grades, while SMC shows a positive linear correlation. Furthermore, the combination of these two physical properties on a scatter diagram clearly shows the cell groups with different cancer grades, which means that this combination could be a potential tumor grading marker to identify cancer cells with different metastatic potential.

Constructing vascular scaffolds is important in tissue engineering. However, scaffolds with characteristics such as multiple layers and a certain degree of spatial morphology still cannot be readily constructed by current vascular scaffolds fabrication techniques. This paper presents a three-layered bifurcated vascular scaffold with a curved structure. The technique combines 3D printed molds and casting hydrogel and fugitive ink to create vessel-mimicking constructs with customizable structural parameters. Compared with other fabrication methods, the technique can create more native-like 3D geometries. The diameter and wall thickness of the fabricated constructs can be independently controlled, providing a feasible approach for vascular scaffold construction. Enzymatically-crosslinked gelatin was used as the scaffold material. The morphology and mechanical properties were evaluated. Human umbilical cord derived endothelial cells (HUVECs) were seeded on the scaffolds and cultured for 72 h. Cell viability and morphology were assessed. The results showed that the proposed process had good application potentials, and will hopefully provide a feasible approach for constructing vascular scaffolds.

Constructing tissue engineered vascular grafts (TEVG) is of great significance for cardiovascular research. However, most of the fabrication techniques are unable to construct TEVG with a bifurcated and curved structure. This paper presents multilayered biodegradable TEVGs with a curved structure and multi-branches. The technique combined 3D printed molds and casting hydrogel and sacrificial material to create vessel-mimicking constructs with customizable structural parameters. Compared with other fabrication methods, the proposed technique can create more native-like 3D geometries. The diameter and wall thickness of the fabricated constructs can be independently controlled, providing a feasible approach for TEVG construction. Enzymatically-crosslinked gelatin was used as the material of the constructs. The mechanical properties and thermostability of the constructs were evaluated. Fluid-structure interaction simulations were conducted to examine the displacement of the construct’s wall when blood flows through it. Human umbilical vein endothelial cells (HUVECs) were seeded on the inner channel of the constructs and cultured for 72 h. The cell morphology was assessed. The results showed that the proposed technique had good application potentials, and will hopefully provide a novel technological approach for constructing integrated vasculature for tissue engineering.

A wind-driven land-yacht robot which will be applied in polar expedition is presented in this article. As the main power of robot is provided by wing sail, improving the efficiency of wing sail is the key for its motion. Wing sail is composed of airfoil, so airfoil theory is researched first, and then several airfoils and their aerodynamic performance are compared, and a high-efficiency airfoil is selected. After that, overturning torque and start wind speed of robot are analyzed to determine the size of the wing sail. At last, the wing sail is manufactured and checked, and it is tested by start wind speed experiments, running speed experiments, steering motion, and obstacle avoidance experiments. The minimum start wind speed is 6 m/s. When wind speed is 10.3 m/s and angle of attack is 90°, running velocity of robot is 1.285 m/s. A land-yacht robot can run steering motion well and avoid obstacle to the target. The result shows that wing sail satisfies the motion requirement of land-yacht robot.

In this paper, classified theoretical models, consisting of contact with and placement of microsphere and picking operations, are simplified and established to depict the interactive behaviors of external and internal forces in pushing manipulations, respectively. Sliding and/or rolling cases, resulting in the acceleration of micromanipulations, are discussed in detail. Effective contact detection is achieved by combining alterations of light-shadow and relative movement displacement between the tip-sphere. Picking operations are investigated by typical interactive positions and different end tilt angles. Placements are realized by adjusting the proper end tilt angles. These were separately conducted to explore the interactive operations of nonconductive glass microspheres in a scanning electron microscope. The experimental results demonstrate that the proposed contact detection method can efficiently protect the end-tip from damage, regardless of operator skills in initial positioning operations. E-beam irradiation onto different interactive positions with end tilt angles can be utilized to pick up microspheres without bending the end-tip. In addition, the results of releasing deviations away from the pre-setting point were utilized to verify the effectiveness of the placement tilt angles.

The disturbing effect of the stray magnetic fields of Fe-based amorphous ribbons on the giant magnetoimpedance (GMI) sensor has been investigated systematically in this paper. Two simple methods were used for examining the disturbing effect of the stray magnetic fields of ribbons on the GMI sensor. In order to study the influence of the stray magnetic fields on the GMI effect, the square-shaped amorphous ribbons were tested in front, at the back, on the left and on the top of a meander-line GMI sensor made up of soft ferromagnetic films, respectively. Experimental results show that the presence of ribbons in front or at the back of GMI sensor shifts the GMI curve to a lower external magnetic field. On the contrary, the presence of ribbons on the left or on the top of the GMI sensor shifts the GMI curve to a higher external magnetic field, which is related to the coupling effect of the external magnetic field and the stray magnetic fields. The influence of the area and angle of ribbons on GMI was also studied in this work. The GMI sensor exhibits high linearity for detection of the stray magnetic fields, which has made it feasible to construct a sensitive magnetometer for detecting the typical stray magnetic fields of general soft ferromagnetic materials.

Foggy days limit the functionality of outdoor surveillance systems. However, it is still a challenge for existing methods tomaintain the uniformity of defogging between image regionswith a similar depth of field and large differences in appearance. To address above problem, this article proposes a regional gradient constrained prior (RGCP) for defogging that uses the piecewise smoothing characteristic of the scene structure to achieve accurate estimation and reliable constraint of the transmission. RGCP first derives that when adjacent similar pixels in the fog image are aggregated and spatially divided into regions, clusters of region pixels in RGB space conform to a chi-square distribution. The offset of the confidence boundary of the clusters can be regarded as the initial transmission of each region. RGCP further uses a gradient distribution to distinguish different regional appearances and formulate an interregional constraint function to constrain the overestimation of the transmission in the flat region, thereby maintaining the consistency between the estimated transmission map and the depth map. The experimental results demonstrate that the proposed method can achieve natural defogging performance in terms of various foggy conditions. [ABSTRACT FROM AUTHOR]