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In this article, the stiffness mapping of compliant robotic systems is generalized to the special Euclidean group SE(3). A geometric framework is proposed to unify the existing stiffness models. We analyze the symmetry and exactness relationship between joint and Cartesian stiffness matrices in this framework. To verify the theoretical results, motions of different types of manipulators, including serial and parallel ones, are tested in simulations. Based on the conservative property of the stiffness matrix, an impedance control strategy to achieve variable stiffness is proposed. In addition, a feasible stiffness identification method is developed using the skew-symmetric structure of the stiffness matrix.

Particle-based dynamic occupancy maps were proposed in recent years to model the obstacles in dynamic environments. Current particle-based maps describe the occupancy status in discrete grid form and suffer from the grid size problem, wherein a large grid size is unfavorable for motion planning while a small grid size lowers efficiency and causes gaps and inconsistencies. To tackle this problem, this article generalizes the particle-based map into continuous space and builds an efficient 3-D egocentric local map. A dual-structure subspace division paradigm, composed of a voxel subspace division and a novel pyramid-like subspace division, is proposed to propagate particles and update the map efficiently with the consideration of occlusions. The occupancy status at an arbitrary point in the map space can then be estimated with the weights of the particles. To reduce the noise in modeling static and dynamic obstacles simultaneously, an initial velocity estimation approach and a mixture model are utilized. Experimental results show that our map can effectively and efficiently model both dynamic obstacles and static obstacles. Compared to the state-of-the-art grid-form particle-based map, our map enables continuous occupancy estimation and substantially improves the mapping performance at different resolutions.

High-fat diets (HFD) could cause obesity, trigger lipid accumulation, and induce oxidative stress and inflammation, leading to kidney damage. This study aimed to elucidate the protective effects of nuciferine on HFD-caused nephrotoxicity and explore the underlying mechanisms in Kunming mice and palmitic acid-exposed HK-2 cells. In obese mice, nuciferine notably alleviated HFD-induced chronic renal dysfunction and delayed renal fibrosis progression and podocyte apoptosis, as evidenced by the increased expressions of renal function factors BUN, CRE, and UA and the decreased expressions of key protein factors TGF-β1, p-Samd3, Wnt-1, and β-catenin. Nuciferine also effectively attenuated HFD-induced renal lipid accumulation via the AMPK-mediated regulation of FAS and HSL expressions and suppressed inflammation and oxidative stress via the AMPK-mediated Nrf-2/HO-1 and TLR4/MyD88/NF-κB pathways. In addition, consistent with the results of animal experiments, nuciferine remarkably reversed cell damage and attenuated lipid accumulation, inflammation, and oxidative stress in palmitic acid-exposed HK-2 cells through the AMPK-mediated signaling pathway. Therefore, nuciferine could be a new food-derived protective agent to offset obesity and correlative kidney damage.

A homogeneous pneumatic soft robot may generate complex output motions using a simple input pressure, resulting from its morphological shape that locally deforms the soft material to different degrees by simultaneously tailoring the structural characteristics and orienting the input pressure. To date, design of the morphological shape (inverse problem) has not been fully addressed. This article outlines a geometry–mechanics–optimization integrated approach to automatically shaping a pneumatic soft actuator or robot that achieves the desired deformation behavior. Instead of constraining the robot's geometry within any predefined regular shape, we employ B-splines to allow generation of freeform boundary surfaces, and use nonlinear mechanical modelling and shape derivative based optimization to navigate the high-dimensional design space. Our design framework can readily regulate the surface quality during the morphological evolution, by imposing the geometric constraints in terms of the principal curvatures and the minimal distance between surfaces as penalty functions. The effect of external forces including the gravity and the interaction force at the end-effector is also taken into account to generalize the method for design problems in which the load capability is also pursued. To improve the computational efficiency, suboptimization problems are constructed within a trust region in which the displacement-dependent objective function is approximated by its first-order Taylor polynomial based on the gradient information to avoid frequently performing time-consuming nonlinear finite element analysis. The suboptimization problems are then solved by the quasi-Newton method combined with the backtracking line search strategy. We showcase various applications to validate our design approach, including actuators for basic extension, bending, and twisting motions, and continuous robot arms that can perform desired in-plane and out-of-plane configurations. We also show that our method can address design of multiple chambers for achieving multiple target deformation behaviors, by co-optimizing the morphological shape and air pressures, which is validated by two examples.

Brain-computer interface (BCI) provides a novel technology for patients and healthy human subjects to control a robotic arm. Currently, BCI control of a robotic arm to complete the reaching and grasping tasks in an unstructured environment is still challenging because the current BCI technology does not meet the requirement of manipulating a multi-degree robotic arm accurately and robustly. BCI based on steady-state visual evoked potential (SSVEP) could output a high information transfer rate; however, the conventional SSVEP paradigm failed to control a robotic arm to move continuously and accurately because the users have to switch their gaze between the flickering stimuli and the target frequently. This study proposed a novel SSVEP paradigm in which the flickering stimuli were attached to the robotic arm's gripper and moved with it. First, an offline experiment was designed to investigate the effects of moving flickering stimuli on the SSVEP's responses and decoding accuracy. After that, contrast experiments were conducted, and twelve subjects were recruited to participate in a robotic arm control experiment using both the paradigm one (P1, with moving flickering stimuli) and the paradigm two (P2, conventional fixed flickering stimuli) using a block randomization design to balance their sequences. Double blinks were used to trigger the grasping action asynchronously whenever the subjects were confident that the position of the robotic arm's gripper was accurate enough. Experimental results showed that the paradigm P1 with moving flickering stimuli provided a much better control performance than the conventional paradigm P2 in completing a reaching and grasping task in an unstructured environment. Subjects' subjective feedback scored by a NASA-TLX mental workload scale also corroborated the BCI control performance. The results of this study suggest that the proposed control interface based on SSVEP BCI provides a better solution for robotic arm control to complete the accurate reaching and grasping tasks.

Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although prosthetic hand devices with myoelectric control can be dated back to more than 70 years ago, their applications with anthropomorphic robotic mechanisms and sensory feedback functions are still at a relatively preliminary and laboratory stage. Nevertheless, a recent series of proof-of-concept studies suggest that soft robotics technology may be promising and useful in alleviating the design complexity of the dexterous mechanism and integration difficulty of multifunctional artificial skins, in particular, in the context of personalized applications. Here, we review the evolution of neuroprosthetic hands with the emerging and cutting-edge soft robotics, covering the soft and anthropomorphic prosthetic hand design and relating bidirectional neural interactions with myoelectric control and sensory feedback. We further discuss future opportunities on revolutionized mechanisms, high-performance soft sensors, and compliant neural-interaction interfaces for the next generation of neuroprosthetic hands.

In most rotational Doppler effect (RDE) measurements, the optical axis and the rotating axis of the object are required to be aligned. However, the condition is very difficult to achieve in practical applications of rotation detection, which seriously affects the received signal. Moreover, it is necessary to focus the beam on the rotating axis of a rotating surface in applications ranging from manufacturing to physical experiments. For example, the manufacture of diffraction optical elements requires aligning the beam to the rotating axis of the spindle. Therefore, how to determine the azimuth of the rotating axis has become an urgent problem to be solved. Based on a new type of superposed vortex beam with multiple topological charges (TCs), we report a new scheme for determining the position of rotating axis by only single RDE measurement, which greatly improves the measurement efficiency. According to the mode decomposition and conservation of angular momentum and energy, we reveal the RDE mechanism of the new structured beam named spliced superposed optical vortex (SSOV) and explain why the SSOV with asymmetrical defect is sensitive to the rotating axis of the object. In addition, in order to prove the effectiveness of the method, a proof-of-concept experiment is conducted to detect the position of object’s rotating axis in eight azimuth ranges, i.e., [iπ/4, (i+ 1)π/4](i= 0, 1, 2, 3, 4, 5, 6, 7). The idea of breaking the symmetry of the optical vortex (OV) and adding additional parameters in this study may have great potential for applications in optical manipulation and communication. Finally, considering that the orbital angular momentum (OAM) mode purity and quality of the incomplete OV and the SSOV will decrease during the far-field propagation, a new method for pre-correction of SSOV is proposed in this research, which overcomes the effects caused by Gouy phase shift and diffraction to some extent. Combined with inertial navigation, these methods above can also be applied to remote sensing, manufacturing, and physics experiments.

Currently, for the continuous targeting problem with the underactuated quadrotor, a nonlinear optimal control method with high computational efficiency is still missing. To tackle this problem, a novel efficient egocentric regulation approach with high computational efficiency is proposed in this article. Specifically, it directly formulates the optimal control problem in an egocentric manner regarding the quadrotor's body coordinates. Meanwhile, the nonlinearities of the system are decoupled through a mapping of the feedback states and control inputs, between the inertial and body coordinates. In this way, it only requires solving a quadratic performance objective with linear constraints and then generates control inputs analytically. Simulations and mimic biological experiments are carried out to verify the effectiveness and computational efficiency. Results demonstrate that the proposed control approach presents the highest and most stable computational efficiency compared with generic optimizers on different platforms. Particularly, on a commonly utilized onboard computer, our method can compute the control action in approximately 0.3 ms, which is on the order of 350 times faster than that of generic optimizers, establishing a control frequency around 3000 Hz.

Motor unit spike trains (MUSTs) decomposed from surface electromyography (sEMG) have been an emerging solution for neural interfacing, especially for the control of upper limb prosthetics. Accurate and efficient decomposition techniques are essential and desirable. However, most decomposition methods are designed for motor units (MUs) with global maximum of single or large muscle, while in general forearm muscles are usually small and slender with low global energy. Thus, we propose a novel approach using local spatial information towards more accurate and efficient sEMG decomposition of forearm muscles. A fast spatial spike detection method is proposed to replace the time-consuming iteration process of blind source separation (BSS) methods. Here, spatial distribution characteristics of motor unit action potential are leveraged to pre-classify the candidate MUs, and further to create initial MU templates, aiming to avoid repeating convergence to high-energy MUs. The results of both simulated and experimental sEMG signals show that low-energy MUs from small muscles are more easily found compared with conventional BSS algorithm. Specifically, the proposed method can identify more 40% reliable MUs while only 30% consuming time are needed. The outcomes provide a novel solution for more efficient sEMG decomposition, potentially paving the way of MUST-based non-invasive neural interface.

Chatter detection is an important approach to reduce detrimental effects induced by machining chatter on part quality and machine tool components. High-accuracy beat frequency estimation is crucial to effectively detect chatter with the beat effect phenomenon. The beat frequency can be obtained from the modulated instantaneous amplitude (IA) of the chatter vibration component. However, the estimation accuracy is severely impacted by the spectral leakage induced by negative parts and harmonics, since the IA is generally a nonsinusoidal periodical waveform. In this article, a novel spectral interference rejection method is developed for accurate beat frequency estimation during machining processes. This algorithm operates within the frequency domain and utilizes a method of accurately aligning a theoretical spectrum of a signal with multiple harmonics to the collected spectrum of the sampled signal. Through computer simulations and simulated machining signals, the performance of our algorithm is evaluated comprehensively in comparison to other estimators. Performance comparisons between different algorithms are carried out under different levels of noise and harmonic interference. Our algorithm is 15–25 dB more accurate than other algorithms, when the harmonic interference is severe. When dealing with simulation machining signals, the mean square error (MSE) of our algorithm is 15 dB less than others in three cases. Moreover, our algorithm is evaluated through two machining tests, and the results demonstrate that the proposed algorithm provides more accurate beat frequency estimation.

Objective. Surface electromyography (EMG) decomposition techniques have been developed to decode motor neuron activities non-invasively in the past decades, showing superior performance in human-machine interfaces such as gesture recognition and proportional control. However, neural decoding across multiple motor tasks and in real-time remains challenging, which limits its wide application. In this work, we proposed a real-time hand gesture recognition method by decoding motor unit (MU) discharges across multiple motor tasks ($>$10) in a motion-wise way. Methods. The EMG signals were first divided into numerous segments related to motions. The convolution kernel compensation algorithm was applied for each segment individually. The local MU filters, which indicate the MU-EMG correlation for each motion, were calculated iteratively in each segment and reused for global EMG decomposition to trace the MU discharges across motor tasks in real-time. The motion-wise decomposition method was applied on the high-density EMG signals recorded during twelve hand gesture tasks from eleven non-disabled participants. The neural feature of discharge count was extracted for gesture recognition based on five common classifiers. Main results. On average, 164$\pm$34 MUs were identified for twelve motions from each subject, with a pulse-to-noise ratio of 32.1$\pm$5.6 dB. The average time cost of EMG decomposition in a sliding window of 50 ms was less than 5 ms. The average classification accuracy using a linear discriminant analysis classifier was 94.6$\pm$8.1%, which was significantly higher than that of a time-domain feature called root mean square. The superiority of the proposed method was also validated with a previously published EMG database comprising 65 gestures. Conclusion and Significance. These results indicate the feasibility and superiority of the proposed method for MU identification and hand gesture recognition across multiple motor tasks, extending the potential applications of neural decoding in human-machine interfaces.

It is of great significance to recognize hand gestures via measuring biological signals from forearm muscles for portable human–machine interaction (HMI). Decreasing the number of sensor nodes is imperative for practical HMI applications. However, it would be an enormous challenge to maintain gesture recognition performance for traditional myoelectric interface with sparse-site sensing. To overcome this drawback, we present a novel HMI predicting more than ten hand and wrist motions relying on only two hybrid mini-grid surface electromyography (sEMG), mechanomyography (MMG), and near-infrared spectroscopy (NIRS) sensor nodes. Beyond the time domain (TD) features of sEMG, additional information containing movement intention is measured from motor unit (MU) action potential trains (MUAPts) according to the decomposition of four-channel arrayed sEMG. Furthermore, low-frequency myofiber vibration and haemodynamics are extracted from MMG and NIRS, respectively. Experiments are performed on 13 healthy subjects to recognize 12 hand and wrist gestures. The results indicate that combining motor unit discharge feature yields consistently higher ( ${p} < 0.01$ ) classification accuracy (CA) (91.6%) than traditional TD features of sEMG (87.8%) using linear discrimination analysis (LDA) classifier. Additionally, both MMG and NIRS features are demonstrated effective supplementary to distinguish muscular activation patterns, producing significantly enhanced (4.2%–11.2%, ${p} < 0.05$ ) recognition performance with the fused information. The outcomes of this study are promising for the HMI applications such as controlling prosthetic hand and wearable device.

The intrinsic compliance of soft materials endows soft robots with great advantages to achieve large deformation and adaptive interactions in grasping tasks. However, current soft grippers usually focus on the in-plane large deformation and load capacity but ignore the effect of out-of-plane external loads, which may lead to instability in practical scenarios. This problem calls for stiffness design along multiple directions to withstand not only in-plane interacting forces with objects, but also unexpected out-of-plane loads. In this paper, we design a new type of soft finger by embedding an endoskeleton inside the widely-used Pneu-Nets actuator, and the endoskeleton layout is optimized to achieve a remarkable bending deflection and limited lateral deflection under combined external in-plane and out-of-plane loads. Based on the multi-objective topology optimization approach, the key structural features of the optimized endoskeleton are extracted and parameterized. The multi-material soft fingers are fabricated by the silicone compound mold method. Static and dynamic experiment results validate that the soft gripper with endoskeleton embedded exhibits remarkably improved out-of-plane stiffness, without sacrificing the in-plane bending flexibility, and leads to more stable grasping.

Parallel robots with rigid transmission mechanisms have been widely developed to improve the speed, precision, and load capability. However, it is still challenging in promoting soft parallel robots due to the difficulty in accurate kinematic modeling of soft continuum links. In this article, we present a general framework on the design, kinematic modeling, model-based characterization, and control for a class of soft parallel robots. The designed soft parallel robot consists of three fiber-reinforced soft pneumatic actuators, a base stage, and an output stage. With the introduction of the mathematical toolkit of the absolute nodal coordinate formulation, we develop a continuum-based model to describe and parameterize both the global complex configuration and the local large deformation of the soft parallel robot. In this sense, the mappings among the defined kinematic spaces of the robot can be characterized through force analysis. Based on the developed model, we next analyze the robot’s workspace and stiffness with different design parameters, which are also verified by a set of experiments. Finally, we establish a model-based trajectory tracking controller for the soft parallel robot. The experimental results demonstrate that with the feedforward controller, the end effector of the soft parallel robot can well follow the desired trajectories under different output velocities, where the average positioning error is about 2.6–3.9% of the maximum length of the workspace.

In the cooperative transportation task with a mobile manipulator (MM), the mobile robot and the manipulator must move simultaneously to adapt to the human motion. In addition, the motion of the MM is underconstrained due to redundancy, which makes MM real-time motion planning challenging. In this article, a capability map-based framework was proposed to enable real-time motion planning of the MM. In the motion planner, the dexterity of the MM, the formation of the human–robot system, and obstacle avoidance of the mobile robot are considered to get safe and human-like robot motion. Moreover, to make optimization faster and avoid local minimum, capability map, which represents the manipulability distribution of the MM in its workspace, is queried to determine the seed of the optimization algorithm. The proposed motion planner is self-contained and can be extended to the transportation task with multiple MMs. The effectiveness of this proposed framework is validated both in simulations and real-world experiments.

Robotic picking and placing systems can increase the flexibility of packing objects in a box and are attractive in many fields. However, owing to inevitable uncertainties in both the picking and placing stages, the objects cannot be placed at desired positions accurately and hence cannot be packed densely. This paper presents an additional pushing action that maximizes the packing density; i.e., after being released from the robot end, the object is moved by robotic pushing actions to arrange the packing densely. The robotic pushing strategy is determined through a deep reinforcement learning algorithm. The idea is to compress the objects toward a corner to improve the volume utilization rate by minimizing the result of a heuristic score. The learning process is implemented in simulation and the trained network is transferred to a robot system directly. Simulations and experiments are presented for the packing of regular and irregular objects to verify the proposed method.

It is vital to recognize the intention of finger motions for human-machine interaction (HMI). The latest research focuses on fine myoelectric control through the decoding of neural motor unit action potential trains (MUAPt) from high-density surface electromyographic (sEMG) signals. However, the existing EMG decoding algorithms rarely obtain the spatial matching relationship between decoded motion units (MU) and designated muscles, and the control interface can only recognize the trained hand gestures. In this study, a semi-supervised HMI based on MU-muscle matching (MMM) is proposed to recognize individual finger motions and even the untrained combined multi-finger actions Through automatic channel selection from high-density sEMG signals, the optimal spatial positions to monitor the MU activation of finger muscles are determined. Finger tapping experiment is carried out on ten subjects, and the experimental results show that the proposed sEMG decomposition algorithm based on MMM can accurately identify single finger motions with an accuracy of 93.1%±1.4%, which is comparable to that of state-of-the-art pattern recognition methods. Furthermore, the MMM allows unsupervised recognizing the untrained combined multi-finger motions with an accuracy of 73%±3.8%. The outcomes of this study benefit the practical applications of HMI, such as controlling prosthetic hand and virtual keyboard.

Motor attempt (MA)/motor imagery (MI)-based brain–computer interface (BCI) is a newly developing rehabilitation technology for motor impairment. This study aims to explore the relationship between electroencephalography sensorimotor rhythm and motor impairment to provide reference for a BCI design. Twenty-eight stroke survivors with varying levels of motor dysfunction and spasticity status in the subacute or chronic stage were enrolled in the study to perform MA and MI tasks. Event-related desynchronization (ERD)/event-related synchronization (ERS) during and immediately after motor tasks were calculated. The Fugl–Meyer assessment scale (FMA) and the modified Ashworth scale (MAS) were applied to characterize upper-limb motor dysfunction and spasticity. There was a positive correlation between FMA total scores and ERS in the contralesional hemisphere in the MI task (P < .05) and negative correlations between FMA total scores and ERD in both hemispheres in the MA task (P < .05). Negative correlations were found between MAS scores of wrist flexors and ERD in the ipsilesional hemisphere (P < .05) in the MA task. It suggests that motor dysfunction may be more correlated to ERS in the MI task and to ERD in the MA task while spasticity may be more correlated to ERD in the MA task.

Although significant advances in the design of soft robotic hands have been made to mimic the structure of the human hands, there are great challenges to control them for coordinated and human-like postures. Based on the principle of postural synergies in the human hand, we present a synergistic approach for coordinated control of a soft robotic hand to replicate the human-like grasp postures. To this end, we firstly develop a kinematic model to describe the control variables and the various postures of the soft robotic hand. Based on the postural synergies, we use the developed model and Principal Component Analysis (PCA) method to describe the various postures of the soft robotic hand in a low-dimensional space formed by the synergies of actuator motions. Therefore, the coordinates of these synergies can be used as low-dimensional control inputs for the soft robotic hand with a higher-dimensional postural space. Finally, we establish an experimental platform on a customized soft robotic hand with 6 pneumatical actuators to verify the effectiveness of the development. Experimental results demonstrate that with only a 2-dimensional control input, the soft robotic hand can reliably replicate 30 grasp postures in the Feix taxonomy of the human hand.

The inherent compliance of soft materials imbues robots, generally referred to as soft robots, with particular advantages in producing adaptive and safe interactions. However, the mainstream design paradigms of soft robots have been focused on pursuing large free motions only, usually at the expense of greatly decreased stiffness, leading to limited capability of withstanding external loads in interactive scenarios. There is a pressing need to incorporate the interaction specifications at the design stage to embody soft robots with not only proper deformability but equally importantly, considerable stiffness to perform complex tasks in practical applications. Here, inspired by the dexterity of human hands, we propose a computational design framework for soft grippers with a focus on improving their interaction performance in power grasping or precision grasping mode. The design paradigm rests on attaching a relatively stiffer skeleton layer to the parametric pneumatic networks based actuator which is widely used due to the geometric advantage, and the skeleton layout is designed for customized interaction conditions by a level set based topology optimization approach. As expected, the optimized skeleton layouts exhibit specified structural features highly relevant to the predefined concentrated loads for precision grip or distributed loads for power grip, which physically implies the compromise between deformability and stiffness. Since the interaction forces are difficult to measure in situ, we devise power and precision grasping scenarios and evaluate the critical actuation pressure of the object’s falling instead. The experiments qualitatively demonstrate the superiority of each specified design. This work represents an initial step toward the rational design for interaction in soft robots.

A novel hybrid material consisted of carbon covered Fe3O4nanoparticles and MoS2nanoflower (FCM) was designed and prepared by micelle-assisted hydrothermal methods. Multiple techniques, including X-Ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS) were employed to characterize it. The results show that FCM has a flower-like morphology with a 330 nm Fe3O4core as well as 70 nm highly crystalline MoS2shell. FCM is superparamagnetic with a saturation magnetization of 35 emu g−1. Then hydrocracking of Canadian bitumen residue (CBR) was applied to estimate its catalytic activity. The results show that FCM exhibits superior catalytic hydrocracking activity compared to bulk MoS2and commercial oil-dispersed Mo(CO)6by the same Mo loading. Further measurement by elemental analysis, XPS and XRD reveals that the MoS2nanoflower with abundant catalytic active sites and covered carbon layer with anti-coke ability donate to the superior upgrading performance. Besides, the catalysts can be easily recovered by the external magnetic field. This work provides a novel kind magnetic nanocatalyst which is potential for slurry-phase hydrocracking applications.

Regenerative, cell‐based therapy is a promising treatment option for diabetic kidney disease (DKD), which has no cure. To prepare for clinical translation, this systematic review and meta‐analysis summarized the effect of cell‐based interventions in DKD animal models and treatment‐related factors modifying outcomes. Electronic databases were searched for original investigations applying cell‐based therapy in diabetic animals with kidney endpoints (January 1998‐May 2019). Weighted or standardized mean differences were estimated for kidney outcomes and pooled using random‐effects models. Subgroup analyses tested treatment‐related factor effects for outcomes (creatinine, urea, urine protein, fibrosis, and inflammation). In 40 studies (992 diabetic rodents), therapy included mesenchymal stem/stromal cells (MSC; 61%), umbilical cord/amniotic fluid cells (UC/AF; 15%), non‐MSC (15%), and cell‐derived products (13%). Tissue sources included bone marrow (BM; 65%), UC/AF (15%), adipose (9%), and others (11%). Cell‐based therapy significantly improved kidney function while reducing injury markers (proteinuria, histology, fibrosis, inflammation, apoptosis, epithelial‐mesenchymal‐transition, oxidative stress). Preconditioning, xenotransplantation, and disease‐source approaches were effective. MSC and UC/AF cells had greater effect on kidney function while cell products improved fibrosis. BM and UC/AF tissue sources more effectively improved kidney function and proteinuria vs adipose or other tissues. Cell dose, frequency, and administration route also imparted different benefits. In conclusion, cell‐based interventions in diabetic animals improved kidney function and reduced injury with treatment‐related factors modifying these effects. These findings may aid in development of optimal repair strategies through selective use of cells/products, tissue sources, and dose administrations to allow for successful adaptation of this novel therapeutic in human DKD. Cell‐based therapies improve diabetic kidney repair: a systematic review and meta‐analysis.

Myoelectric controlled interfaces driven by muscle activities have achieved good performance in ideal conditions and showed many potential medical-related and industrial applications. However, in practical applications, the performance could be drastically degraded due to the electrode (sensor) shift, which is inevitable in donning and doffing the system. In this study, we presented a novel channel selection method against electrode shift for robust pattern-recognition based myoelectric control. The proposed method was evaluated on twenty-four subjects, including twenty-two able-bodied subjects and two amputees, and compared with two traditional channel selection methods, i.e., uniform selection (UNI) and sequential feature selection (SFS). We demonstrated that the offline error rates of the proposed method were significantly lower than those of the other two methods (P<0.05), and its online performance in shift conditions was comparable to that in ideal conditions. These outcomes benefit the practical applications of robust myoelectric controlled interfaces.

Effective separation of cathode materials (CMs) from Al foils is critical for recycling spent lithium-ion batteries (LIBs). This study proposed a CaCl2-assisted microwave roasting technology for facile exfoliation of cathode materials and selective recovery of lithium. The specific action mechanism was studied by experiments and thermodynamic calculations. Under the action of microwave, CaCl2accelerated decomposition into chlorine-containing gas and rapidly diffused in cracks caused by thermal stress to ensure the separation of Al foil and active material layer. The decomposition product of CaCl2acts as an adsorbent to capture HF released by polyvinylidene difluoride (PVDF), inhibiting the fluorination reaction with electrode materials. The water vapor generated from the CaCl2and CMs promotes the diffusion of Li+out of the crystal lattice and then reacts with H2O and HCl to form water-soluble LiCl. Finally, 93.4 wt% CMs can be detached from Al foils, and 91.5% Li in the cathode powders could be extracted by subsequent water-leaching under optimal experimental conditions. These results show that this technology can provide both economic and environmental benefits, and have important guiding for the development of green and sustainable ways to efficiently recycle spent LIBs.

Purpose: To demonstrate the marginal corneal vascular remodelling using optical coherence tomography angiography (OCTA) after pterygium surgery. Methods: Twenty-two eyes of 19 patients (8 males, 11 females; age, 58.68 ± 0.34 years) with primary grade-T3 nasal pterygium were enroled in this study. The eyes underwent excision of the pterygium followed by a free limbal-conjunctival autograft. OCTA was performed in the nasal limbal area before surgery and at 10 days, 1 month, and 3 months after surgery. The scans were analyzed in terms of postoperative vascular remodelling of the autograft and marginal corneal vascular arcades (MCAs). Results: Preoperatively, the pterygium presented as abnormal centripetal vascular growth in OCTA scans. The conjunctival vessel density in the nasal quadrant was 29.26% ± 1.00%, 15.80% ± 0.83%, 19.80% ± 0.88%, and 20.26% ± 0.89% before and 10 days, 1 month, and 3 months, respectively, after surgery (F= 1.55, P&lt; 0.01). The vessel density of MCAs was 28.33% ± 0.88%, 42.09% ± 0.41%, and 42.46% ± 0.31% 10 days, 1 month, and 3 months, respectively, after surgery (F= 188.2, P&lt; 0.01). Conclusions: We describe a new application of OCTA for MCA vasculature imaging. Vascular remodelling of the graft and MCAs appeared at 1 month and continued for 3 months after surgery.

By 3D printing lattice structure with active materials, the structures can exhibit shape and functional changes under external stimulus. However, the programmable shape changes of the 3D printed lattice structures are limited due to the complex geometries, nonlinear behaviors of the active materials, and the diverse external stimuli. In this work, we propose a design framework combining experiments, theoretical modeling, and finite element simulations for the controllable shape changes of the 3D printed horseshoe under thermal stimulus. The theoretical model is based on a phase evolution model that combines the geometrical nonlinearity and the material nonlinearity. Results show that the shapes with positive or negative Poisson’s ratio and bending intermediate shapes can be programmed by tuning the geometrical parameters and the temperature distribution. This work provides a method to aid the design of 3D printed functional lattice structures and have potential applications in soft robotics, biomedicine, and energy absorbing fields.

Cellular senescence, a permanent arrest of cell proliferation, is characterized by a senescence-associated secretory phenotype (SASP), which reinforces senescence and exerts noxious effects on adjacent cells. Recent studies have suggested that transplanting small numbers of senescent cells suffices to provoke tissue inflammation. We hypothesized that senescent cells can directly augment renal injury. Primary scattered tubular-like cells (STCs) acquired from pig kidneys were irradiated by 10 Gy of cesium radiation, and 3 wk later cells were characterized for levels of senescence and SASP markers. Control or senescent STCs were then prelabeled and injected (5 × 105cells) into the aorta of C57BL/6J mice. Four weeks later, renal oxygenation was studied in vivo using 16.4-T magnetic resonance imaging and function by plasma creatinine level. Renal markers of SASP, fibrosis, and microvascular density were evaluated ex vivo. Per flow cytometry, irradiation induced senescence in 80–99% of STCs, which showed increased gene expression of senescence and SASP markers, senescence-associated β-galactosidase staining, and cytokine levels (especially IL-6) secreted in conditioned medium. Four weeks after injection, cells were detected engrafted in the mouse kidneys with no evidence for rejection. Plasma creatinine and renal tissue hypoxia increased in senescent compared with control cells. Senescent kidneys were more fibrotic, with fewer CD31+endothelial cells, and showed upregulation of IL-6 gene expression. Therefore, exogenously delivered senescent renal STCs directly injure healthy mouse kidneys. Additional studies are needed to determine the role of endogenous cellular senescence in the pathogenesis of kidney injury and evaluate the utility of senolytic therapy.

While cable-driven snake robots are promising in exploring confined spaces, their hyper-redundancy makes the collision-free motion planning difficult. In this paper, by combining the prediction lookup and interpolation algorithms, we present a new path following method for cable-driven snake robots to high-efficiently slither into complex terrains along a desired path. In our method, we first discretize the desired path into points, and develop the prediction lookup algorithm to efficiently find the points matched with joints of the robot. According to geometric relations between the prediction lookup results and link length of the robot, we develop the interpolation algorithm to reduce the tracking errors caused by the discretization. Finally, simulations and experiments of inspections in two confined spaces including the obstacle array and pipe tank system are performed on our custom-built 25 degree of freedoms (DOFs) cable-driven snake robot. The results demonstrate that the presented method can successfully navigate our snake robot into confined spaces with high computational efficiency and good accuracy, which well verifies effectiveness of our development.

Dynamic bonding is a key factor for self-healing and stimuli-response polymeric materials. However, a detailed molecular-level understanding on effects from dynamic bond break and reform from interchain and intrachain cross-linking remains unclear. Here, we apply nonlinear rheological characterization on a polymer cross-linked with dynamic coordination cross-linking. Startup shear measurements and small amplitude oscillatory shear (SAOS) were used to confirm the existence of metal–ligand bond disassociation and reformation; Step extensional measurement was used to further characterize the dynamics of the interchain and intrachain cross-linkings’ disassociation and reformation. We found that dynamic bonds, which are shear rate sensitive, could be disassociated by continuous shear. When the shear or extension rate was much higher than the relaxation rate, both interchain and intrachain coordinated bondings may disassociate, and polymer chains became highly aligned; thus, more interchain reformation took place after extension cessation at higher strain since chain configurations have changed.

All-solid-state sodium ion batteries (ASIBs) based on sulfide electrolytes are considered a promising candidate for large-scale energy storage. However, the limited cycle life of ASIBs largely restricts their practical application. Cycling-stable ASIBs can be achieved only if the designed cathode can simultaneously address challenges including insufficient interfacial contact, electrochemical and chemical instability between the electrode and electrolyte, and strain/stress during operation , rather than just addressing one or part of these challenges. Chevrel phase Mo6S8has inherent high electronic conductivity and small volume change during sodiation/desodiation, and is chemically and electrochemically stable with the sulfide electrolyte, and therefore the only challenge of using Mo6S8as the cathode for ASIBs is the insufficient contact between Mo6S8and the solid electrolyte (SE). Herein, a thin layer of SE is coated on Mo6S8using a solution method to achieve an intimate contact between Mo6S8and the SE. Such a SE-coated Mo6S8cathode enabled an ASIB with a high cycling performance (500 cycles), even much better than that of the liquid-electrolyte batteries with the Mo6S8cathode. This work provides valuable insights for developing long-cycle life ASIBs.

Mesenchymal stem cells (MSC) have been experimentally used for kidney repair, but modest retention limits their efficacy. Cell‐surface coating allows modulating MSC homing and interaction with target cells. We coated mouse adipose tissue‐derived MSC with antibodies directed against kidney injury molecule‐1 (ab‐KIM1), which is upregulated in injured kidneys, and tested the hypothesis that this would enhance their therapeutic effects in ischemic kidney injury. Untreated MSC, ab‐KIM1‐coated MSC (KIM‐MSC), or vehicle, were injected systemically into the carotid artery of 2‐kidneys, 1‐clip mice 2 weeks after surgery. MSC retention in different organs was explored 24 hours, 48 hours, or 2 weeks after injection. Renal volume, perfusion, and oxygenation were studied 2 weeks after injection using magnetic resonance imaging in vivo, and renal inflammation, apoptosis, capillary density, and fibrosis ex vivo. The ab‐KIM1 coating had little effect on MSC viability or proliferation. The stenotic kidney showed upregulated KIM1 expression, selective homing, and greater retention of KIM‐MSC compared to untreated MSC and compared to other organs. KIM‐MSC‐injected mice improved renal perfusion and capillary density, and attenuated oxidative damage, apoptosis, and fibrosis compared to mice treated with vehicle or with native MSC. In conclusion, MSC coating with ab‐KIM1 increased their retention in the ischemic kidney and enhanced their therapeutic efficacy. This novel method may be useful to selectively target injured kidneys, and supports further development of strategies to enhance cell‐based treatment of ischemic kidney injury. StemCellsTranslationalMedicine2018;7:394–403 MSC were coated with KIM‐1 antibody by connecting with palmitic acid protein G, and were injected into the carotid artery of mice with renal artery stenosis. KIM‐MSC preferentially homed to the injured kidney, and were retained adjacent to sites of elevated KIM1 expression, in turn resulting in increased therapeutic efficacy, such as improved renal perfusion and capillary density, and attenuated oxidative damage, apoptosis, and fibrosis.

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Advanced myoelectric prosthetic hands are currently limited due to the lack of sufficient signal sources on amputation residual muscles and inadequate real-time control performance. This paper presents a novel human–machine interface for prosthetic manipulation that combines the advantages of surface electromyography (EMG) and near-infrared spectroscopy (NIRS) to overcome the limitations of myoelectric control. Experiments including 13 able-bodied and three amputee subjects were carried out to evaluate both offline classification accuracy (CA) and online performance of the forearm motion recognition system based on three types of sensors (EMG-only, NIRS-only, and hybrid EMG-NIRS). The experimental results showed that both the offline CA and real-time performance for controlling a virtual prosthetic hand were significantly (p $&lt;$ 0.05) improved by combining EMG and NIRS. These findings suggest that fusion of EMG and NIRS is feasible to improve the control of upper-limb prostheses, without increasing the number of sensor nodes or complexity of signal processing. The outcomes of this study have great potential to promote the development of dexterous prosthetic hands for transradial amputees.

All-inorganic solid-state sodium–sulfur batteries (ASSBs) are promising technology for stationary energy storage due to their high safety, high energy, and abundant resources of both sodium and sulfur. However, current ASSB shows poor cycling and rate performances mainly due to the huge electrode/electrolyte interfacial resistance arising from the insufficient triple-phase contact among sulfur active material, ionic conductive solid electrolyte, and electronic conductive carbon. Herein, we report an innovative approach to address the interfacial problem using a Na3PS4–Na2S–C (carbon) nanocomposite as the cathode for ASSBs. Highly ionic conductive Na3PS4contained in the nanocomposite can function as both solid electrolyte and active material (catholyte) after mixing with electronic conductive carbon, leading to an intrinsic superior electrode/electrolyte interfacial contact because only a two-phase contact is required for the charge transfer reaction. Introducing nanosized Na2S into the nanocomposite cathode can effectively improve the capacity. The homogeneous distribution of nanosized Na2S, Na3PS4, and carbon in the nanocomposite cathode could ensure a high mixed (ionic and electronic) conductivity and a sufficient interfacial contact. The Na3PS4-nanosized Na2S–carbon nanocomposite cathode delivered a high initial discharge capacity of 869.2 mAh g–1at 50 mA g–1with great cycling and rate capabilities at 60 °C, representing the best performance of ASSBs reported to date and therefore constituting a significant step toward high-performance ASSBs for practical applications.

Developing high-performance electrocatalysts for oxygen evolution reaction (OER) is of importance for improving the overall efficiency of water splitting. Herein, the CoFe/(CoxFe1–x)3Mo3C heterojunction is purposely designed as an OER catalyst, which displays a low overpotential of 293 mV for affording a current density of 10 mA cm–2and a small Tafel slope of 48 mV/dec. Various characterization results demonstrate that the significant work-function difference between CoFe and (CoxFe1–x)3Mo3C can induce interfacial charge redistribution, which results in the formation of Co and Fe sites with a high-spin state, thus stimulating the surface phase reconstruction of CoFe/(CoxFe1–x)3Mo3C to corresponding active oxyhydroxide. Meanwhile, the electrochemical leaching of Mo ions from the initial structure can contribute to the formation of defective sites, further benefiting OH–adsorption and surface oxidation. Moreover, the remaining CoFe can accelerate electron migration during the electrocatalytic process. This study presents new insights into constructing efficient OER electrocatalysts with an optimized spin-state configuration via interfacial engineering.

Though many efforts have been devoted to the adsorptive removal of hazardous materials of organophosphorus pesticides (OPs), it is still highly desirable to develop novel adsorbents with high adsorption capacities. In the current work, the removal of two representative OPs, glyphosate (GP) and glufosinate (GF), was investigated by the exceptionally stable Zr-based MOFs of UiO-67. The abundant Zr–OH groups, resulting from the missing-linker induced terminal hydroxyl groups and the inherent bridging ones in Zr–O clusters of UiO-67 particles, served as natural anchorages for efficient GP and GF capture in relation with their high affinity toward phosphoric groups in OPs. The correlation between the most significant parameters such as contact time, OPs concentration, adsorbent dose, pH, as well as ionic strength with the adsorption capacities was optimized, and the effects of these parameters on the removal efficiency of GP and GF from the polluted aqueous solution were investigated. The adsorption of GP on UiO-67 was faster than that of GF, and a pseudo-second-order rate equation effectively described the uptake kinetics. The Langmuir model exhibited a better fit to adsorption isotherm than the Freundlich model. Thanks to the strong affinity and adequate pore size, the adsorption capacities in UiO-67 approached as high as 3.18 mmol (537 mg) g–1for GP and 1.98 mmol (360 mg) g–1for GF, which were much higher than those of many other reported adsorbents. The excellent adsorption characteristics of the current adsorbents toward OPs were preserved in a wide pH window and high concentration of the background electrolytes. These prefigured the promising potentials of UiO-67 as novel adsorbent for the efficient removal of OPs from aqueous solution.

Magnetic nanocomposites provide manifold perspectives for sustainable development. However, the cumbersome operation process and energy consumption after treatment limit its application in the practical industry. Herein, we present a simple and universal strategy to synthesize Fe3O4@PDA@shell nanoparticles via in-situ homogeneous hydrolysis reaction growth different nanomaterials on the PDA modified Fe3O4nanospheres, which can avoid multistep repetitive washing, redispersing, and drying. As an example, we introduced the synthesis process of Fe3O4@PDA@MoS2catalyst used for heavy oil hydrocracking in detail. The synthesis processes were significantly simplified and the dispersity and stability of the nanosized MoS2were improved due to the copious functional groups and strong adhesion properties of polydopamine. The as-prepared Fe3O4@PDA@MoS2nanoparticle catalysts showed high activity and excellent stability. The viscosity of residue was decreased by 99.8% and the recovery of the catalyst reached 90% under harsh conditions (405 ℃ at 13 MPa H2). We also demonstrate the versatility of this strategy for other shell materials, such as WS2, VS2, Pd, and Rh components, which is promising for designing multifunctional core−shell−shell materials for various applications.

Myocardial microvascular permeability-surface area product (MPSP) and fractional vascular volume (FVV), indices of endothelial function and microvascular perfusion, can be noninvasively evaluated by electron beam computed tomography (EBCT), but it remains unknown whether comparable assessments can be obtained with 64-slice multidetector CT (CT-64).

Heightened concern about the dangers of bioterrorism requires that measures be developed to ensure the safety of the blood supply. Multiplex detection of such agents using a blood-screening DNA microarray is a sensitive and specific method to screen simultaneously for a number of suspected agents. We have developed and optimized a multiplex polymerase chain reaction microarray assay to screen blood for three potential bioterror bacterial pathogens and a human ribosomal RNA gene internal control. The analytical sensitivity of the assay was demonstrated to be 50 colony-forming units/ml for Bacillus anthracis, Francisella tularensis, and Yersinia pseudotuberculosis(surrogate for Yersinia pestis). The absence of any false-positives demonstrated high analytical specificity. Screening B. anthracis-infected mouse blood samples and uninfected controls demonstrated effectiveness and specificity in a preclinical application. This study represents proof of the concept of microarray technology to screen simultaneously for multiple bioterror pathogens in blood samples.

Advances in development of artificial muscles have enabled creation of soft robots with biological dexterity and self-adaption in unstructured environments; however, production of scalable artificial muscles with multiple-mode actuations remains elusive. Inspired by muscle-fiber arrays in muscular hydrostats, we present a class of versatile artificial muscles called MAIPAMs (muscle-fiber array inspired pneumatic artificial muscles), capable of multiple-mode actuations (such as parallel elongation-bending-spiraling actuations, 10 parallel bending actuations and cascaded elongation-bending-spiraling actuations). Our MAIPAMs consist of active 3D elastomer-balloon arrays reinforced by a passive elastomer membrane, achieved through a planar design and one-step rolling fabrication approach. We introduce prototypical designs for the MAIPAMs and demonstrate their muscle-mimic structures and versatility, as well as their scalable ability to integrate flexible but non-stretchable layers for contraction and twisting actuation modes and compliant electrodes for self-sensing. We further demonstrate that this class of artificial muscles shows potential for versatile robotic applications, such as carrying a camera for recording videos, gripping or manipulating objects, and climbing a pipe-line.We demonstrate the first drone-based entanglement distribution under multi-weather conditions, which exhibits the third possible experimental strategy for quantum communication, in addition to fiber and satellite.

Studies on the metal-support interaction have been a key step for deeply understanding the catalytic behavior of hydrodesulfurization (HDS) reactions. In particular, modification of the surface hydroxyl groups on alumina can determine its surface metal species and their dispersion degrees and thus influence the reactivity of catalysts. Herein, magnetic MoS2nanoparticles supported on thiol groups grafted alumina (Fe3O4@Al2O3-SH@MoS2) were synthesized, leading to excellent catalytic hydrodesulfurization performance in a slurry-phase reactor of 40% desulfurization efficiency and high stability of 105 h in the long-term evaluation. Density functional theory calculations and multiple catalyst characterizations demonstrated that the grafting of thiol groups not only significantly weakened the metal-support interaction by bridging the support and active phase but also inhibited the coke formation, improved the cycle performance of the catalyst. This work proves to be an effective method to adjust the metal-support interaction, leading to enhanced catalytic performance. Besides, the magnetic properties of the catalyst enable it to be separated from the reaction media quickly, which is promising to be used in slurry reactors that process heavy crude oil.

CheY, the response regulator of bacterial chemotaxis, plays a pivotal role in signal transduction in bacterial chemotaxis and interacts with at least three proteins: CheA, FliM, and CheZ. CheA receives signals from chemoreceptors and then transfers the signal to CheY by a phosphotransfer reaction. Phosphorylated CheY binds to FliM, one of the switch proteins, resulting in a change in flagellar rotation from counterclockwise to clockwise. Phosphorylated CheY is dephosphorylated by its intrinsic autophosphatase activity and by CheZ. The CheA- and FliM-binding surfaces of CheY have been well studied, but characterization of the CheZ-binding surface of CheY is incomplete. We have analyzed the effect of CheZ on the dephosphorylation rates of 14 mutants of CheY. Nine mutant CheY proteins showed more resistance to CheZ phosphatase activity than did wild-type CheY. These nine mutant CheY proteins could be divided into two groups: one with altered CheZ binding and the other with normal CheZ binding. The mutations causing reduced CheZ binding altered residues on the same surface of CheY, a region consisting of the β5-α5loop, the α1-helix, and part of the α5-helix. Mutations rendering CheY resistant to CheZ, isolated by Sanna et al.(Sanna, M. G., Swanson, R. V., Bourret, R. B., and Simon, M. I. (1995) Mol. Microbiol.15, 1069–1079), were also found to affect this surface. The mutations in the CheY protein that affect CheZ activity but not CheZ binding are located in the β4-α4loop, which appears to be involved in the catalytic activity of CheZ. Finally, our results indicate that the CheY surfaces that bind CheA, FliM, and CheZ overlap, but are not completely identical.

Exploring high-efficiency, robust and cost-effective catalysts for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) is greatly desirable. Herein, a series of transition-metal doped MoS2(M-MoS2, M = Mn, Fe, Co, Ni, Cu, Zn) with expanded interlayer spacing are fabricated by one-step solvothermal strategy. Notably, nickel doped molybdenum disulfide (Ni-MoS2) is found to exhibit prominent catalytic activity with an apparent rate constant (K) of 1.09 min-1and excellent stability over six continuous runs of recycling experiments. The results demonstrate that the expanded interlayer spacing (0.94 nm) can increase the active sites of reactant absorption, and Ni dopants can lower the energy level (d‐band center) to facilitate the desorption of H. Thus, the catalytic activity of Ni-MoS2is enhanced by synergistically structural and energy level modulation. This study offers an effective strategy to design transition metal sulfides with higher catalytic reactivity for the environment-related catalysis processes.

Exploiting precious-metal-free and high-activity oxygen evolution reaction (OER) electrocatalysts has been in great demands toward many energy storage and conversion processes, for example, carbon dioxide reduction, metal–air batteries, and water splitting. In this study, the simple solid-state method is employed for coupling Ni (electron donors) with lower-Fermi-level MoO2or WOx(electron acceptors) into donor–acceptor ensembles with well-designed interfaces as robust electrocatalysts for OER. The resulting Ni/MoO2and Ni/WOxelectrocatalysts exhibit smaller overpotentials of 287 and 333 mV at 10 mA cm–2as well as smaller Tafel slopes of 51 and 65 mV/dec, respectively, with respect to the single Ni, MoO2, WOx, and even the benchmark RuO2in 1 M KOH. Specially, on account of a higher Fermi level of Ni in comparison with MoO2and WOx, their strong electronic interaction results in directional interfacial electron transfer and increases the hole density over Ni, dramatically enriching the population of high-valence Ni3+active sites and decreasing the Fermi level of Ni. The existence of Ni3+can strengthen the chemisorption of OH–, and the downshift of the Ni Fermi level can significantly expedite migration of electrons toward the surface of catalysts during OER, thus synergistically boosting the OER catalytic performance. Furthermore, the inner Ni/MoO2and Ni/WOxheterostructures and the electrochemically induced surface layers of oxides/hydroxides collectively boost the OER kinetics. This study highlights the importance of designing highly efficient OER electrocatalysts with high-valence active species (Ni3+) and better matched energy levels induced by the work function difference through interfacial engineering.

This article presents a test bed for comprehensive study of a cable-driven hyper-redundant robot in terms of mechanical design, kinematics analysis, and experimental verification. To design the hyper-redundant robot, the multiple section structure is used. Each section consists of two rotational joints, a link mechanism, and three cables. In this sense, two degrees of freedom are achieved. For kinematics analysis between the actuator space and joint space, each section of the development is treated as three spherical–prismatic–spherical chains and a universal joint chain (3-SPS-U), which results in a four-chain parallel mechanism model. In order to obtain the forward kinematics from the joint space to task space directly and easily, the coordinate frames are established by the geometrical rules rather than the traditional Denavit–Hartenburg (D-H) rules. To solve the problem of inverse kinematics analysis, we utilize the product of exponentials approach. Finally, a prototype of 24-degrees of freedom hyper-redundant robot with 12 sections and 36 cables is fabricated and an experiment platform is built for real-time control of the robot. Different experiments in terms of trajectories tracking test, positioning accuracy test, and payload test are conducted for the validation of both mechanical design and model development. Experiment results demonstrate that the presented hyper-redundant robot has fine position accuracy, flexibility with mean position error less than 2%, and good load capacity.