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The problem of lithium dendrite growth has persistently hindered the advancement of lithium metal batteries. Lithium phosphorus oxynitride (LiPON), functioning as an amorphous solid electrolyte, is extensively employed as an artificial solid electrolyte interphase (SEI) owing to its remarkable stability and mechanical strength, which is beneficial for effectively mitigating dendrite growth. Nevertheless, the significant challenge arises from the volume changes in the Li metal anode during cycling, leading to the vulnerability of LiPON due to its high rigidity, which impedes the widespread use of LiPON. To address this problem, our study introduces a lithium-boron (Li-B) alloy as the anode, featuring a 3D structure, which can be synergistic with the artificial LiPON layer during cycling, leading to a better performance. The average Coulombic efficiency (CE) of a Li || Cu half-cell reaches 95% over 120 cycles. The symmetric cells exhibit sustained operation for 950 h with a low voltage polarization of less than 20 mV under a current density of 0.5 mA/cm2 and for 410 h under 1 mA/cm2. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud by temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCFs), and a key PCF is selected. The 3D skeleton is predicted through 3D pose estimation, and the motion of the skeleton is estimated by analyzing the joints and bones of the 3D skeleton. For the deformation of the non-rigid human PC, the 3D PC model is transformed into a mesh model, and the key PCF is rigged using the 3D skeleton. After deforming the key PCF into the target PCF utilizing the motion vector of the estimated skeleton, the residual PC between the motion compensation PCF and the target PCF is generated. If there is a key PCF, the motion vector of the target PCF, and a residual PC, the target PCF can be reconstructed. Just as compression is performed using pixel correlation between frames in a 2D video, this paper compresses 3D PCFs by estimating the non-rigid 3D motion of a 3D object in a 3D PC. The proposed algorithm can be regarded as an extension of the 2D motion estimation of a rigid local region in a 2D plane to the 3D motion estimation of a non-rigid object (human) in 3D space. Experimental results show that the proposed method can successfully compress 3D PC sequences. If it is used together with a PC compression technique such as MPEG PCC (point cloud compression) in the future, a system with high compression efficiency may be configured. [ABSTRACT FROM AUTHOR]

The problem of lithium dendrite growth has persistently hindered the advancement of lithium metal batteries. Lithium phosphorus oxynitride (LiPON), functioning as an amorphous solid electrolyte, is extensively employed as an artificial solid electrolyte interphase (SEI) owing to its remarkable stability and mechanical strength, which is beneficial for effectively mitigating dendrite growth. Nevertheless, the significant challenge arises from the volume changes in the Li metal anode during cycling, leading to the vulnerability of LiPON due to its high rigidity, which impedes the widespread use of LiPON. To address this problem, our study introduces a lithium-boron (Li-B) alloy as the anode, featuring a 3D structure, which can be synergistic with the artificial LiPON layer during cycling, leading to a better performance. The average Coulombic efficiency (CE) of a Li || Cu half-cell reaches 95% over 120 cycles. The symmetric cells exhibit sustained operation for 950 h with a low voltage polarization of less than 20 mV under a current density of 0.5 mA/cm2 and for 410 h under 1 mA/cm2.

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Existing 3D skeleton-based action recognition approaches reach impressive performance by encoding handcrafted action features to image format and decoding by CNNs. However, such methods are limited in two ways: a) the handcrafted action features are difficult to handle challenging actions, and b) they generally require complex CNN models to improve action recognition accuracy, which usually occur heavy computational burden. To overcome these limitations, we introduce a novel AFE-CNN , which devotes to enhance the features of 3D skeleton-based actions to adapt to challenging actions. We propose feature enhance modules from key joint, bone vector, key frame and temporal perspectives, thus the AFE-CNN is more robust to camera views and body sizes variation, and significantly improve the recognition accuracy on challenging actions. Moreover, our AFE-CNN adopts a light-weight CNN model to decode images with action feature enhanced, which ensures a much lower computational burden than the state-of-the-art methods. We evaluate the AFE-CNN on three benchmark skeleton-based action datasets: NTU RGB + D, NTU RGB + D 120, and UTKinect-Action3D, with extensive experimental results demonstrate our outstanding performance of AFE-CNN. [ABSTRACT FROM AUTHOR]

The 3D structured Zn anode which is grown on the surface of carbon cloth/carbon nanofiber framework (CC-CNF) can reduce the nucleation overpotential of the electrode and suppress dendrites owing to the high conductivity and abundant nucleation sites of the 3D skeleton. [Display omitted] Zn-ion battery (ZIB) is a promising electrochemical energy storage device because of the high performance, safety, and economic benefits, etc. However, the formation of Zn dendrites at anodes is seriously depressed their cycling life, Coulombic efficiency, safety, and capacity. Inhibition of Zn dendrites is considered as an efficient solution to improving the performance of ZIB. Herein, we demonstrate a 3D structured Zn anode coated in carbon nanofiber framework with carbon cloth as substrate (Zn@CC-CNF), which has the abundant Zn nucleation sites and homogeneous electrical field distribution for uniform Zn deposition, low nucleation/deposition energy barrier, and the capacity of alleviating side reactions. Thus, the Zn@CC-CNF based symmetric cells is stability operated over 400 h, which is over 400% longer than that of bare Zn coated on carbon cloth (Zn@CC). The impressive performance of the Zn@CC-CNF anode also endows the assembled Zn-MnO 2 full cell with long-term cycling stability. Better yet, the intrinsic flexibility of the carbon substrate enables the fabrication of flexible Zn-MnO 2 cell with gratifying mechanical deformation tolerance, illustrating their great application potential in flexible energy storage. [ABSTRACT FROM AUTHOR]

[Display omitted] • A LiF-Li 3 N/LiN x O y -enriched SEI is prepared in situ using a strongly lithiophilic 3D carbon fiber/MXene/ZnS skeleton. • Highly lithophilic 3D skeletons and LiF-Li 3 N/LiN x O y -enriched SEI synergistically regulate lithium nucleation and deposition behaviour. • The mechanisms for Li nucleation and deposition are elucidated by electrochemical in situ characterization techniques. Metallic lithium (Li) is an excellent electrode material for high-energy-density batteries; however, the continuous growth of Li dendrites and the poor deposited volume consistency of Li severely influence the stability of Li anodes. Herein, a LiF-Li 3 N/LiN x O y -enriched SEI is prepared in situ using a strongly lithiophilic 3D carbon fiber/MXene/ZnS (CMZ) skeleton. Multiscale in situ and ex situ characterizations reveal the mechanisms for Li nucleation and growth on the CMZ skeleton, proving that Li grows tightly over CMZ fibers. This behaviour is attributed to the CMZ skeleton, which provides abundant atomic-level active sites for the uniform and dense nucleation of Li. Electrochemical tests confirm that SEI enriched with LiF-Li 3 N/LiN x O y can effectively improve Li deposition kinetics, ensure uniform mass transfer and rapid migration of lithium ions in the SEI, and guarantee uniform growth of Li. Consequently, a half cell with a Li-CMZ electrode delivers a high Coulombic efficiency (99.83 %), an ultralong cycling life (17,860 h), and an excellent rate performance (30 mA cm−2). Moreover, full cells consisting of a Li-CMZ anode and different cathodes exhibit superior cycling stabilities. For Li-CMZ ‖ LiFePO 4 pouch cell, 84 % capacity is maintained after 300 cycles at 1 C. [ABSTRACT FROM AUTHOR]

A new epoxy-based polymerizing/compositing synchronic process was carried out in 3D structure of a melamine sponge. The cured polymer formed a porous and wave-shaped coating on the surface of skeleton in a uniform way. The obtained composite sponge was used as a microflow support for the immobilization of phospholipase A 1 (PLA 1 , from Thermomyces lanuginosus/Fusarium oxysporum) by co-adsorption/cross-linking with polyethylenimine (PEI). The loading amount and the specific activity of immobilized PLA 1 under the optimal immobilization conditions were 45.7 mg/g support and 9.1 U/mg protein. The PLA 1 -immobilized microflow supports were placed in a columnar reactor, in which transesterification was operated in continuous circulation way. The reaction produced DHA/EPA-incorporated phosphatidylcholine, the hydrolysis side reaction could be inhibited by removal of free water in the reaction medium. Under optimized conditions the incorporation percentage of DHA/EPA and PC yield of 54.3% and 82.4% within 18 h at 55 ℃, respectively. After 10 cycles, the immobilized PLA 1 retained 71.2% of the original activity. The use of microflow support has an advantage on easier scaling up the reactor size towards much larger productivity and higher efficiency. • The novel microflow support showed advantages on easier scaling up, mass transfer and multiphase dispersion. • The immobilized PLA 1 catalyzed transesterification on microflow supports in a pump-driving columnar reactor. • Inhibition of hydrolysis optimized the reaction to produce DHA/EPA-rich phosphatidylcholine in high efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud by temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCFs), and a key PCF is selected. The 3D skeleton is predicted through 3D pose estimation, and the motion of the skeleton is estimated by analyzing the joints and bones of the 3D skeleton. For the deformation of the non-rigid human PC, the 3D PC model is transformed into a mesh model, and the key PCF is rigged using the 3D skeleton. After deforming the key PCF into the target PCF utilizing the motion vector of the estimated skeleton, the residual PC between the motion compensation PCF and the target PCF is generated. If there is a key PCF, the motion vector of the target PCF, and a residual PC, the target PCF can be reconstructed. Just as compression is performed using pixel correlation between frames in a 2D video, this paper compresses 3D PCFs by estimating the non-rigid 3D motion of a 3D object in a 3D PC. The proposed algorithm can be regarded as an extension of the 2D motion estimation of a rigid local region in a 2D plane to the 3D motion estimation of a non-rigid object (human) in 3D space. Experimental results show that the proposed method can successfully compress 3D PC sequences. If it is used together with a PC compression technique such as MPEG PCC (point cloud compression) in the future, a system with high compression efficiency may be configured.

Pose prediction is to predict future poses given a window of previous poses. In this paper, we propose a new problem that predicts poses using 3D positions of skeletal sequences.Different from the traditional pose prediction based on mocap frames, this problem is convenient to use in real applications due to its simple sensors to capture data. We also present a new framework, pseudo-image sequence evolution-based 3D pose prediction, to address this new problem. Specifically, a skeletal representation is proposed by transforming a 3D skeletal sequence into an image sequence, which can model different correlations among different joints. With this image-based skeletal representation, we model the pose prediction as the evolution of an image sequence. Moreover, a novel inference network is proposed to predict multiple future poses in a non-recursive manner using decoders with independent parameters. In contrast to the recursive sequence-to-sequence model, we can improve the computational efficiency and avoid error accumulations significantly. Extensive experiments are carried out on two benchmark datasets (e.g., G3D and FNTU). The proposed method achieves state-of-the-art performance on both datasets, which demonstrates the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

In the field of body affect recognition, the majority of literature is based on experiments performed on datasets where trained actors simulate emotional reactions. These acted and unnatural expressions differ from the more challenging genuine emotions, thus leading to less valuable results. In this article, a solution for basic non-acted emotion recognition based on 3D skeleton and Deep Neural Networks (DNNs) is provided. The proposed work introduces three majors contributions. First, temporal local movements performed by subjects are examined frame-by-frame, unlike the current state-of-the-art in non-acted body affect recognition where only static or global body features are considered. Second, an original set of global and time-dependent features for body movement description is provided. Third, this is one of the first works to use deep learning methods in the current non-acted body affect recognition literature. Due to the novelty of the topic, only the UCLIC dataset is currently considered the benchmark for comparative tests. On the latter, the proposed method outperforms all the competitors. [ABSTRACT FROM AUTHOR]

Person re-identification (Re-ID) is a challenging and arduous task due to non-overlapping views, complex background, and uncontrollable occlusion in video surveillance. An existing method for capturing pedestrian local region information is to divide person regions into horizontal stripes, which may lead to invalid features and erroneous learning. To solve this problem, this paper proposes a 3D skeleton and a two-stream approach to person Re-ID. The first stream of the method uses the 3D skeleton for background filtering and region segmentation. The second stream uses Siamese net to extract the global descriptor. The features of the two streams are fused to preserve the integrity of the person. An optimized region matching method for metric learning is designed. Extensive comparing experiments were conducted with state-of-the-art Re-ID methods on the Market-1501, CUHK03, and DukeMTMC-reID datasets. Experimental results show that the proposed method outperforms the existing methods in recognition accuracy. [ABSTRACT FROM AUTHOR]

Although solid composite electrolytes show tremendous potential for the practical solid‐state lithium metal batteries, searching for a straightforward tactic to promote the ion conduction at electrolyte/electrode interface, especially settling lithium dendrites formation caused by the concentration gradient polarization, are still long‐standing problems. Here, the authors report a corrugated 3D nanowires‐bulk ceramic‐nanowires (NCN) skeleton reinforced composite electrolyte with regulated interfacial Li‐ion transport behavior. The special and integrated NCN skeleton endows the electrolyte with fast Li‐ion transfer and solves the Li+ concentration polarization at electrode/electrolyte interface, thereby eliminating the energy barrier originated from the redistribution of charge carriers and offering homogeneous interfacial Li‐ion flux on lithium anode. As a "double insurance", the bulk ceramic sheet in 3D framework enables the electrolyte to block the mobility of anions. The rational designed NCN composite electrolyte exhibits excellent ionic conductivity and the assembled all‐solid‐state battery possesses 90.2% capacity retention after 500 cycles. The proposed strategy affords a special insight in designing high‐performance solid composite electrolytes. [ABSTRACT FROM AUTHOR]

The practical application of the lithium anode in lithium metal batteries (LMBs) has been hindered by the uncontrollable growth of lithium dendrite and the high volumetric change during cycling. Herein, the in situ formed three-dimensional (3D) lithium–boron (Li–B) alloy is suggested as an excellent alternative to the Li metal, in which the 3D LiB skeleton can mitigate the growth of Li dendrites and volumetric change. In this study, the Li–B alloy anodes with different B contents were manufactured by high-temperature melting. It was found that the boron content had a significant effect on the electrochemical performance of the Li–B alloy. The Li–B alloy with the least B content (10 wt%, 10LiB) demonstrated the lowest overpotential of 0.0852 V after 300 h and the lowest interface resistance. However, the full cell with 15LiB as the anode displayed the best cycling performance of 115 mAh·g−1 after 100 cycles with a columbic efficiency greater than 97%. The obtained results suggest that the in situ formed three-dimensional Li–B alloy anode can be an excellent alternative to the Li anode via tuning B contents for next-generation high energy density LMBs. [ABSTRACT FROM AUTHOR]

Recent advances in terahertz (THz) absorbing materials and technology show futuristic potentials for practical applications in THz radars and telecommunications, stealth and shielding. However, the lack of versatile materials naturally working in this specific electromagnetic wave region with simultaneously featuring high absorption efficiencies, ultrabroad bandwidths, low‐costs, good stabilities, and flexibilities, is impeding the proliferation of real THz disruptive applications. Here a kind of flexible structure material, 3D nickel (Ni) skeleton, fabricated from an electroplating sintering method with irregular pore distribution makes possible the successful realization of a highly absorbing response for ultrabroadband THz waves due to the effective combination of both material and structural absorption mechanisms. 3D Ni skeletons with 90 ppi nonuniform pore‐size ranges enable >99% absorption capabilities in the frequency range of 0.5–2.0 THz independent on both the THz incidence angles and polarizations. Experimental validation of THz shielding implemented on both 100 GHz and 4.3 THz video imaging systems corroborates the highly efficient absorbing with frequency expansibility. Such capabilities are further verified on millimeter‐wave security checkers for 32–36 GHz. This prototypical demonstration lays the foundation for the next‐generation THz absorbing technology, accelerating advanced THz technologies toward practical applications. [ABSTRACT FROM AUTHOR]

Obesity is a growing health concern, mainly caused by poor dietary habits. Yet, accurately tracking the diet and food intake of individuals with obesity is challenging. Although 3D motion capture technology is becoming increasingly important in healthcare, its potential for detecting early signs of obesity has not been fully explored. In this research, we used a deep LSTM network trained with individual identity (identity-trained deep LSTM network) to analyze 3D time-series skeleton data from mouse models with diet-induced obesity. First, we analyzed the data from two different viewpoints: allocentric and egocentric. Second, we trained various deep recurrent networks (e.g., RNN, GRU, LSTM) to predict the identity. Lastly, we tested whether these models effectively encode obese-like motion representations by training a support vector classifier with the latent features from the last layer. Our experimental results indicate that the optimal performance is achieved when utilizing an identity-trained deep LSTM network in conjunction with an egocentric viewpoint. This approach suggests a new way to use deep learning to spot health risks in mouse models of obesity and should be useful for detecting early signs of obesity in humans.

K metal battery is a kind of high-energy-density storage device with economic advantages. However, due to the dendrite growth and difficult processing characteristics, it is difficult to prepare stable K metal anode with thin thickness and fixed area capacity, which severely limits its development. In this work, a multi-functional 3D skeleton (rGCA) is synthesized by simple vacuum filtration and thermal reduction, and K metal anodes with controllable thickness and area capacity (K content) can be fabricated by changing the raw material mass and graphene layer spacing of rGCA. Moreover, the graphene sheet layer of rGCA can relax stress and relieve volume expansion; carbon nanotubes can serve as the fast transport channel of electrons, reducing internal impedance and local current density; Ag nanoparticles can induce the uniform nucleation and deposition of K + . The K metal composite anodes (rGCA-K) based on the conductive skeleton can effectively suppress dendrites and exhibit excellent electrochemical performance in symmetric and full cells. The controllable fabrication process of stable K metal anode is expected to help K metal batteries move toward the stage of commercial production., (© 2023 Wiley-VCH GmbH.)

As we all known, the most promising alternative anode for the next-generation energy storage devices is the lithium metal anode. But the unpredictable dendrite growth and volume expansion during the cycles impedes its applications and commercialization. The Li-Cu-Zn three-phases alloy materials (including Li 2 Cu 3 Zn, Li-Zn and Li) have been synthesized to solve these problems. According to the density functional theory (DFT) analysis, all results indicate that the Li 2 Cu 3 Zn ternary alloy has the higher absorption energy of Li than bare Li, suggesting the superior lithiophilic. Meanwhile, the construction of Li 2 Cu 3 Zn alloy 3D skeleton is beneficial to uniform the Li+ flux and reducing the local current density. Furthermore, based on the analysis of in-situ X-ray diffraction, Li 2 Cu 3 Zn skeleton can keep stable during the cycles. The Li-Cu-Zn electrodes exhibit the stable cycling performance about more than 1200 h and pure lithium only for about 120 h (at 1 mA cm−2 and 1 mAh cm−2). And at 0.5 C, after 100 cycles, the NCM811 (LiNi 0.8 Co 0.1 Mn 0.1 O 2) ||Li-Cu-Zn cell delivers an excellent cycling stability for 92.3% capacity retention. In this work, uniform deintercalation of lithium ions through three-dimensional alloy framework structure provides a research basis for lithium-free anodes. • Introducing the 3D skeleton structure to homogenize the Li-ion flux. • The improvement of mechanical property and interfacial stability. • Forming uniformly nucleation sites to suppress the growth of lithium dendrites. • The synergies of 3D skeleton and strong Li+ affinity site. [ABSTRACT FROM AUTHOR]

K metal holds great promise as the ultimate anode candidate for K-ion batteries because of its high theoretical capacity and low operating potential. However, due to its high viscosity and poor mechanical processability, it remains challenging to manufacture potassium anodes with precise parameters by a simple and executable method. In this work, a high-performance potassium-carbon nanotubes (K@CNTs) composite film electrode with a three-dimensional (3D) skeleton and superior processability is prepared by simply incorporating CNTs into molten potassium. The in situ potassiation reaction between CNTs and molten K formed potassium carbide (KC 8 ) so as to obtain a solid-liquid mixture, which can reduce the surface tension of molten potassium and promote the preparation of the K@CNTs film electrode. The composite electrode can be molded into a variety of shapes and thicknesses in accurate dimensions. The porous, well-conducting CNTs act as a 3D skeleton uniformly distributed in the K metal, providing adequate surface and space to accommodate and attract K metal, thereby inhibiting the growth of the potassium dendrites and the volume expansion upon cycling. As a result, the K@CNTs composite anode exhibits excellent cyclability and rate capability in both symmetric and full cells. The superior processability and excellent electrochemical performance make this composite an ideal anode candidate for commercial applications in potassium metal batteries.

Increased concentration polarization and cell resistance due to aggregation of "dead Li" is one of the main factors that cause capacity decay during cycling of practical lithium metal batteries. Effective strategies that are able to accommodate dynamic volume expansion of "dead Li" is required to solve the above problem. Herein, a compressible 3D skeleton (polyaniline modified melamine foam) is introduced to modify lithium metal anode to self-adapt the volume expansion. Meanwhile, moderate conductivity of this 3D skeleton can induce the "bottom-up" deposition manner of Li and provide electron pathways to exploit the inactive Li in "dead Li". More importantly, the COMSOL simulations show that the 3D skeleton can effectively dissipate electrons accumulated on the tips of dendritic Li when unwanted Li dendrites contact the 3D skeleton to achieve low local current density. As a result, a Li/Cu cells using this 3D skeleton on the Cu side show long-term stability within 100 cycles under 3.8 mAh/cm2, and Li symmetrical cells using 3D skeleton modified Li foils achieve stable cycling for 2750 h under 5.0 mAh/cm2. The feasible fabrication process enables us to fabricate 0.6 Ah 3D skeleton modified Li/NCM811 pouch cells, which deliver capacity retention of 85% after 80 cycles under practical test protocols. A 3D skeleton with self-adaptive ability and moderate conductivity to accommodate expanded "dead Li" layer is applied on lithium metal anode to improve lifetime of Li metal batteries. An as-fabricated 2.6 Ah pouch cell which strictly follows requirements of practical Li metal cells can reach the energy density of 350 Wh/kg. [Display omitted] • Self-adaptive PANI&MF hosts effectively suppress volume expansion of Li anode during cycling. • COMSOL simulation indicates that PANI&MF can dissipate electrons on tips of Li dendrites to inhibit dendritic growth. • Lithium metal pouch cells with energy density of 350 Wh/kg is fabricated using PANI&MF-Li composite anode. [ABSTRACT FROM AUTHOR]

Uneven deposition and serious volume change restrict the commercial application of Li metal anode. Sn based alloy is pursued as the advanced anode via an alloying/dealloying mechanism while considering its resource abundance, low price, and high specific capacity. Herein, a three-dimensional (3D) Li 22 Sn 5 alloy skeleton is integrated with Li metal phase via phase-segregation process by a facial melting method, in which Li-rich dual-phase Li-Sn alloy named SnLi90 is produced. The free Li phase accounts for a huge proportion of the electrode weight and acts as the active material offering ultra-high specific capacity of 3087 mAh g−1. Alternatively, the unique interconnected rod-like Li 22 Sn 5 network serves as electrochemical "inert" framework due to its much higher redox potential. The favorable Li affinity of the Li 22 Sn 5 skeleton contributes to conformal Li deposition. Consequently, the SnLi90 anode can cycle stably for 1500 h in ester electrolyte at 1 mA cm−2 and 1 mAh cm−2, almost three times longer than that of the bare Li anode. The SnLi90 anode contains two phases, i.e., Li metal and Li 22 Sn 5 alloy. Li enables high specific capacity. Li 22 Sn 5 skeleton maintains structural integrity, electrochemical "inertness" and induces conformal deposition of Li. [Display omitted] [ABSTRACT FROM AUTHOR]