The Versatile Establishment of Charge Storage in Polymer Solid Electrolyte with Enhanced Charge Transfer for LiF-Rich SEI Generation in Lithium Metal Batteries.

The solid-state electrolyte interface (SEI) between the solid-state polymer electrolyte and the lithium metal anode dramatically affects the overall battery performance. Increasing the content of lithium fluoride (LiF) in SEI can help the uniform deposition of lithium and inhibit the growth of lithium dendrites, thus improving the cycle stability performance of lithium batteries. Currently, most methods of constructing LiF SEI involve decomposing the lithium salt by the polar groups of the filler. However, there is a lack of research reports on how to affect the SEI layer of Li-ion batteries by increasing the charge transfer number. In this study, a porous organic polymer with "charge storage" properties was prepared and doped into a polymer composite solid electrolyte to study the effect of sufficient charge transfer on the decomposition of lithium salts. The results show in contrast to porphyrins, the unique structure of POF allows for charge transfer between each individual porphyrin. Therefore, during TFSI- decomposition to the formation of LiF, TFSI- can obtain sufficient charge, thereby promoting the break of C-F and forming the LiF-rich SEI. Compared with single porphyrin (0.423 e-), POF provides 2.7 times more charge transfer to LiTFSI (1.147 e-). The experimental results show that Li//Li symmetric batteries equipped with PEO-POF can be operated stably for more than 2700 h at 60 °C. Even the Li//Li (45 µm) symmetric cells are stable for more than 1100 h at 0.1 mA cm-1. In addition, LiFePO4//PEO-POF//Li batteries have excellent cycling performance at 2 C (80 % capacity retention after 750 cycles). Even LiFePO4//PEO-POF//Li (45 µm) cells have excellent cycling performance at 1 C (96 % capacity retention after 300 cycles). Even when the PEO-base is replaced with a PEG-base and a PVDF-base, the performance of the cell is still significantly improved. Therefore, we believe that the concept of charge transfer offers a novel perspective for the preparation of high-performance assemblies.

A Selective-Tumor-Penetrating Strategy via Unidirectional Direct Transfer for Intravesical Therapy of Bladder Cancer.

A selective tumor-penetrating strategy generally exploits tumor-targeted ligands to modify drugs so that the conjugate preferentially enters tumors and subsequently undergoes transcellular transport to penetrate tumors. However, this process shields ligands from their corresponding targets on the cell surface, possibly inducing an off-target effect during drug penetration at the tumor-normal interface. Herein, we first describe a selective tumor-penetrating drug (R11-phalloidin conjugates) for intravesical therapy of bladder cancer. The intravesical conjugates rapidly translocated across the mucus layer, specifically bound to tumors, and infiltrated throughout the tumor via direct intercellular transfer. Notably, direct transfer from normal cells to tumor cells was unidirectional because the pathways required for direct transfer, termed F-actin-rich tunneling nanotubes, were more unidirectionally extended from normal cells to tumor cells. Moreover, the intravesical conjugates displayed strong anticancer activity and well-tolerated biosafety in murine orthotopic bladder tumor models. Our study demonstrated the potential of a selective tumor-penetrating conjugate for effective intravesical anticancer therapy.

Interface-Targeting Carrier-Catalytic Integrated Design Contributing to Lithium Dihalide-Rich SEI toward High Interface Stability for Long-Life Solid-State Lithium-Metal Batteries.

The generation of solid electrolyte interphase (SEI) largely determines the comprehensive performance of all-solid-state batteries. Herein, a novel "carrier-catalytic" integrated design is strategically exploited to in situ construct a stable LiF-LiBr rich SEI by improving the electron transfer kinetics to accelerate the bond-breaking dynamics. Specifically, the high electron transport capacity of Br-TPOM skeleton increases the polarity of C-Br, thus promoting the generation of LiBr. Then, the enhancement of electron transfer kinetics further promotes the fracture of C-F from TFSI- to form LiF. Finally, the stable and homogeneous artificial-SEI with enriched lithium dihalide is constructed through the in situ co-growth mechanism of LiF and LiBr, which facilitatse the Li-ion transport kinetics and regulates the lithium deposition behavior. Impressively, the PEO-Br-TPOM paired with LiFePO4 delivers ultra-long cycling stability over 1000 cycles with 81 % capacity retention at 1 C while the pouch cells possess 88 % superior capacity retention after 550 cycles with initial discharge capacity of 145 mAh g-1at 0.2 C in the absence of external pressure. Even under stringent conditions, the practical pouch cells possess the practical capacity with stable electric quantities plateau in 30 cycles demonstrates its application potential in energy storage field.

An Amphibious Fully-Soft Centimeter-Scale Miniature Crawling Robot Powered by Electrohydraulic Fluid Kinetic Energy.

Miniature locomotion robots with the ability to navigate confined environments show great promise for a wide range of tasks, including search and rescue operations. Soft miniature locomotion robots, as a burgeoning field, have attracted significant research interest due to their exceptional terrain adaptability and safety features. Here, a fully-soft centimeter-scale miniature crawling robot directly powered by fluid kinetic energy generated by an electrohydraulic actuator is introduced. Through optimization of the operating voltage and design parameters, the average crawling velocity of the robot is dramatically enhanced, reaching 16 mm s-1. The optimized robot weighs 6.3 g and measures 5 cm in length, 5 cm in width, and 6 mm in height. By combining two robots in parallel, the robot can achieve a turning rate of ≈3° s-1. Additionally, by reconfiguring the distribution of electrodes in the electrohydraulic actuator, the robot can achieve 2 degrees-of-freedom translational motion, improving its maneuverability in narrow spaces. Finally, the use of a soft water-proof skin is demonstrated for underwater locomotion and actuation. In comparison with other soft miniature crawling robots, this robot with full softness can achieve relatively high crawling velocity as well as increased robustness and recovery.

A Semi-Autonomous Hierarchical Control Framework for Prosthetic Hands Inspired by Dual Streams of Human.

The routine use of prosthetic hands significantly enhances amputees' daily lives, yet it often introduces cognitive load and reduces reaction speed. To address this issue, we introduce a wearable semi-autonomous hierarchical control framework tailored for amputees. Drawing inspiration from the visual processing stream in humans, a fully autonomous bionic controller is integrated into the prosthetic hand control system to offload cognitive burden, complemented by a Human-in-the-Loop (HIL) control method. In the ventral-stream phase, the controller integrates multi-modal information from the user's hand-eye coordination and biological instincts to analyze the user's movement intention and manipulate primitive switches in the variable domain of view. Transitioning to the dorsal-stream phase, precise force control is attained through the HIL control strategy, combining feedback from the prosthetic hand's sensors and the user's electromyographic (EMG) signals. The effectiveness of the proposed interface is demonstrated by the experimental results. Our approach presents a more effective method of interaction between a robotic control system and the human.

Dynamic and Real-Time Object Detection Based on Deep Learning for Home Service Robots.

Home service robots operating indoors, such as inside houses and offices, require the real-time and accurate identification and location of target objects to perform service tasks efficiently. However, images captured by visual sensors while in motion states usually contain varying degrees of blurriness, presenting a significant challenge for object detection. In particular, daily life scenes contain small objects like fruits and tableware, which are often occluded, further complicating object recognition and positioning. A dynamic and real-time object detection algorithm is proposed for home service robots. This is composed of an image deblurring algorithm and an object detection algorithm. To improve the clarity of motion-blurred images, the DA-Multi-DCGAN algorithm is proposed. It comprises an embedded dynamic adjustment mechanism and a multimodal multiscale fusion structure based on robot motion and surrounding environmental information, enabling the deblurring processing of images that are captured under different motion states. Compared with DeblurGAN, DA-Multi-DCGAN had a 5.07 improvement in Peak Signal-to-Noise Ratio (PSNR) and a 0.022 improvement in Structural Similarity (SSIM). An AT-LI-YOLO method is proposed for small and occluded object detection. Based on depthwise separable convolution, this method highlights key areas and integrates salient features by embedding the attention module in the AT-Resblock to improve the sensitivity and detection precision of small objects and partially occluded objects. It also employs a lightweight network unit Lightblock to reduce the network's parameters and computational complexity, which improves its computational efficiency. Compared with YOLOv3, the mean average precision (mAP) of AT-LI-YOLO increased by 3.19%, and the detection precision of small objects, such as apples and oranges and partially occluded objects, increased by 19.12% and 29.52%, respectively. Moreover, the model inference efficiency had a 7 ms reduction in processing time. Based on the typical home activities of older people and children, the dataset Grasp-17 was established for the training and testing of the proposed method. Using the TensorRT neural network inference engine of the developed service robot prototype, the proposed dynamic and real-time object detection algorithm required 29 ms, which meets the real-time requirement of smooth vision.

Regulating Steric Hindrance of Porous Organic Polymers in Composite Solid-State Electrolytes to Induce the Formation of LiF-Rich SEI in Li-Ion Batteries.

Lithium fluoride (LiF) at the solid electrolyte interface (SEI) contributes to the stable operation of polymer-based solid-state lithium metal batteries. Currently, most of the methods for constructing lithium fluoride SEI are based on the design of polar groups of fillers. However, the mechanism behind how steric hindrance of fillers impacts LiF formation remains unclear. This study synthesizes three kinds of porous polyacetal amides (PAN-X, X=NH2 , NH-CH3 , N-(CH3 )2 ) with varying steric hindrances by regulating the number of methyl substitutions of nitrogen atoms on the reaction monomer, which are incorporated into polymer composite solid electrolytes, to investigate the regulation mechanism of steric hindrance on the content of lithium fluoride in SEI. The results show that bis(trifluoromethanesulfonyl)imide (TFSI- ) will compete for the charge without steric effect, while excessive steric hindrance hinders the interaction between TFSI- and polar groups, reducing charge acquisition. Only when one hydrogen atom on the amino group is replaced by a methyl group, steric hindrance from the methyl group prevents TFSI- from capturing charge in that direction, thereby facilitating the transfer of charge from the polar group to a separate TFSI- and promoting maximum LiF formation. This work provides a novel perspective on constructing LiF-rich SEI.

A High-Efficient Reinforcement Learning Approach for Dexterous Manipulation.

Robotic hands have the potential to perform complex tasks in unstructured environments owing to their bionic design, inspired by the most agile biological hand. However, the modeling, planning and control of dexterous hands remain unresolved, open challenges, resulting in the simple movements and relatively clumsy motions of current robotic end effectors. This paper proposed a dynamic model based on generative adversarial architecture to learn the state mode of the dexterous hand, reducing the model's prediction error in long spans. An adaptive trajectory planning kernel was also developed to generate High-Value Area Trajectory (HVAT) data according to the control task and dynamic model, with adaptive trajectory adjustment achieved by changing the Levenberg-Marquardt (LM) coefficient and the linear searching coefficient. Furthermore, an improved Soft Actor-Critic (SAC) algorithm is designed by combining maximum entropy value iteration and HVAT value iteration. An experimental platform and simulation program were built to verify the proposed method with two manipulating tasks. The experimental results indicate that the proposed dexterous hand reinforcement learning algorithm has better training efficiency and requires fewer training samples to achieve quite satisfactory learning and control performance.

Co-optimization of robotic design and skill inspired by human hand evolution.

During evolution of the human hand, evolutionary morphology has been closely related to behavior in complicated environments. Numerous researchers have revealed that learned skills have affected hand evolution. Inspired by this phenomenon, a co-optimization approach for underactuated hands is proposed that takes grasping skills and structural parameters into consideration. In our proposal, hand design, especially the underactuated mechanism, can be parameterized and shared with all the local agents. These mechanical parameters can be updated globally by the independent agents. In addition, we also train human-like 'feeling' of grasping: grasping stability is estimated in advance before the object drops, which can speed up grasping training. In this paper, our method is instantiated to address the optimization problem for the torsion spring mechanical parameters of an underactuated robotic hand with multi-actuators, and then the optimized results are transferred to the actual physical robotic hand to test the improvement of grasping. This collaborative evolution process leverages the dexterity of the multi-actuators and the adaptivity of the underactuated mechanism.

An Enhanced Positional Error Compensation Method for Rock Drilling Robots Based on LightGBM and RBFN.

Rock drilling robots are able to greatly reduce labor intensity and improve efficiency and quality in tunnel construction. However, due to the characteristics of the heavy load, large span, and multi-joints of the robot manipulator, the errors are diverse and non-linear, which pose challenges to the intelligent and high-precision control of the robot manipulator. In order to enhance the control accuracy, a hybrid positional error compensation method based on Radial Basis Function Network (RBFN) and Light Gradient Boosting Decision Tree (LightGBM) is proposed for the rock drilling robot. Firstly, the kinematics model of the robotic manipulator is established by applying MDH. Then a parallel difference algorithm is designed to modify the kinematics parameters to compensate for the geometric error. Afterward, non-geometric errors are analyzed and compensated by applying RBFN and lightGBM including features and kinematics model. Finally, the experiments of the error compensation by combing combining the geometric and non-geometric errors verify the performance of the proposed method.

Experimental validation of manipulability optimization control of a 7-DoF serial manipulator for robot-assisted surgery.

PURPOSE: Both safety and accuracy are of vital importance for surgical operation procedures. An efficient way to avoid the singularity of the surgical robot concerning safety issues is to maximize its manipulability in robot-assisted surgery. The goal of this work was to validate a dynamic neural network optimization method for manipulability optimization control of a 7-degree of freedom (DoF) robot in a surgical operation. METHODS: Three different paths, a circle, a sinusoid and a spiral were chosen to simulate typical surgical tasks. The dynamic neural network-based manipulability optimization control was implemented on a 7-DoF robot manipulator. During the surgical operation procedures, the manipulability of the robot manipulator and the accuracy of the surgical operation are recorded for performance validation. RESULTS: By comparison, the dynamic neural network-based manipulability optimization control achieved optimized manipulability but with a loss of the accuracy of trajectory tracking (the global error was 1 mm compare to the 0.5 mm error of non-optimized method). CONCLUSIONS: The method validated in this work achieved optimized manipulability with a loss of error. Future works should be introduced to improve the accuracy of the surgical operation.

The effect of maternal hyperoxygenation on placental perfusion in normal and Fetal Growth Restricted pregnancies using Intravoxel Incoherent Motion.

PURPOSE: To evaluate the effect of maternal hyperoxygenation on placental perfusion in normal and Fetal Growth Restricted (FGR) pregnancies using Intravoxel Incoherent Motion (IVIM). METHODS: Ten FGR pregnancies and twenty-five normal pregnancies underwent IVIM examinations before and after maternal hyperoxygenation (95% O2, 5% CO2) using a 1.5T MR scanner. The IVIM parameters (fp, Dt, Dp) were determined for the placentas of both groups. The IVIM parameters within and between groups and their correlations with Doppler findings were statistically analyzed. ROC analysis was performed to evaluate the diagnostic power of IVIM derived parameters. RESULTS: Before maternal hyperoxygenation, the perfusion fraction fp was significantly lower in the FGR group than that in the normal group (22.88±10.29 (%) vs. 36.28±9.70 (%), p = 0.000). After maternal hyperoxygenation, fp decreased significantly in the normal group (36.28±9.70 (%) vs. 29.93±10.25 (%), p = 0.032), whereas it remained relatively stable in the FGR group (22.88±10.29 (%) vs. 24.38±13.67 (%), p = 0.508). An increase of Dt was found only for the normal group and Dp did not changed significantly after maternal hyperoxygenation. There existed a negative correlation between fppre and umbilical artery pulsatility index (PI) (r = -0.385, p < 0.05) as well as Dtpost and PI (r = -0.574, p < 0.01). The fppre displayed a best diagnostic power of all parameters with the area under curve (AUC) of 0.912. CONCLUSION: The perfusion fraction, fp, is able to distinguish FGR from normal pregnancies by its value pre and by its change (or lack thereof) post maternal hyperoxygenation. IVIM may potentially help improve the diagnosis of placenta function as it relates to disease.

Non-canonical Opioid Signaling Inhibits Itch Transmission in the Spinal Cord of Mice.

Chronic itch or pruritus is a debilitating disorder that is refractory to conventional anti-histamine treatment. Kappa opioid receptor (KOR) agonists have been used to treat chronic itch, but the underlying mechanism remains elusive. Here, we find that KOR and gastrin-releasing peptide receptor (GRPR) overlap in the spinal cord, and KOR activation attenuated GRPR-mediated histamine-independent acute and chronic itch in mice. Notably, canonical KOR-mediated Gαi signaling is not required for desensitizing GRPR function. In vivo and in vitro studies suggest that KOR activation results in the translocation of Ca2+-independent protein kinase C (PKC)δ from the cytosol to the plasma membrane, which in turn phosphorylates and inhibits GRPR activity. A blockade of phospholipase C (PLC) in HEK293 cells prevented KOR-agonist-induced PKCδ translocation and GRPR phosphorylation, suggesting a role of PLC signaling in KOR-mediated GRPR desensitization. These data suggest that a KOR-PLC-PKCδ-GRPR signaling pathway in the spinal cord may underlie KOR-agonists-induced anti-pruritus therapies.

Processing of visually evoked innate fear by a non-canonical thalamic pathway.

The ability of animals to respond to life-threatening stimuli is essential for survival. Although vision provides one of the major sensory inputs for detecting threats across animal species, the circuitry underlying defensive responses to visual stimuli remains poorly defined. Here, we investigate the circuitry underlying innate defensive behaviours elicited by predator-like visual stimuli in mice. Our results demonstrate that neurons in the superior colliculus (SC) are essential for a variety of acute and persistent defensive responses to overhead looming stimuli. Optogenetic mapping revealed that SC projections to the lateral posterior nucleus (LP) of the thalamus, a non-canonical polymodal sensory relay, are sufficient to mimic visually evoked fear responses. In vivo electrophysiology experiments identified a di-synaptic circuit from SC through LP to the lateral amygdale (Amg), and lesions of the Amg blocked the full range of visually evoked defensive responses. Our results reveal a novel collicular-thalamic-Amg circuit important for innate defensive responses to visual threats.

Descending control of itch transmission by the serotonergic system via 5-HT1A-facilitated GRP-GRPR signaling.

Central serotonin (5-hydroxytryptophan, 5-HT) modulates somatosensory transduction, but how it achieves sensory modality-specific modulation remains unclear. Here we report that enhancing serotonergic tone via administration of 5-HT potentiates itch sensation, whereas mice lacking 5-HT or serotonergic neurons in the brainstem exhibit markedly reduced scratching behavior. Through pharmacological and behavioral screening, we identified 5-HT1A as a key receptor in facilitating gastrin-releasing peptide (GRP)-dependent scratching behavior. Coactivation of 5-HT1A and GRP receptors (GRPR) greatly potentiates subthreshold, GRP-induced Ca(2+) transients, and action potential firing of GRPR(+) neurons. Immunostaining, biochemical, and biophysical studies suggest that 5-HT1A and GRPR may function as receptor heteromeric complexes. Furthermore, 5-HT1A blockade significantly attenuates, whereas its activation contributes to, long-lasting itch transmission. Thus, our studies demonstrate that the descending 5-HT system facilitates GRP-GRPR signaling via 5-HT1A to augment itch-specific outputs, and a disruption of crosstalk between 5-HT1A and GRPR may be a useful antipruritic strategy.