Xi'an University of Technology

Abstract The current boom of safe and renewable energy storage systems is driving the recent renaissance of Zn‐ion batteries. However, the notorious tip‐induced dendrite growth on the Zn anode restricts their further application. Herein, the first demonstration of constructing a flexible 3D carbon nanotube (CNT) framework as a Zn plating/stripping scaffold is constituted to achieve a dendrite‐free robust Zn anode. Compared with the pristine deposited Zn electrode, the as‐fabricated Zn/CNT anode affords lower Zn nucleation overpotential and more homogeneously distributed electric field, thus being more favorable for highly reversible Zn plating/stripping with satisfactory Coulombic efficiency rather than the formation of Zn dendrites or other byproducts. As a consequence, a highly flexible symmetric cell based on the Zn/CNT anode presents appreciably low voltage hysteresis (27 mV) and superior cycling stability (200 h) with dendrite‐free morphology at 2 mA cm −2 , accompanied by a high depth of discharge (DOD) of 28%. Such distinct performance overmatches most of recently reported Zn‐based anodes. Additionally, this efficient rechargeability of the Zn/CNT anode also enables a substantially stable Zn//MnO 2 battery with 88.7% capacity retention after 1000 cycles and remarkable mechanical flexibility.

Abstract Ti 3 C 2 T x , a typical representative among the emerging family of 2D layered transition metal carbides and/or nitrides referred to as MXenes, has exhibited multiple advantages including metallic conductivity, a plastic layer structure, small band gaps, and the hydrophilic nature of its functionalized surface. As a result, this 2D material is intensively investigated for application in the energy storage field. The composition, morphology and texture, surface chemistry, and structural configuration of Ti 3 C 2 T x directly influence its electrochemical performance, e.g., the use of a well‐designed 2D Ti 3 C 2 T x as a rechargeable battery anode has significantly enhanced battery performance by providing more chemically active interfaces, shortened ion‐diffusion lengths, and improved in‐plane carrier/charge‐transport kinetics. Some recent progresses of Ti 3 C 2 T x MXene are achieved in energy storage. This Review summarizes recent advances in the synthesis and electrochemical energy storage applications of Ti 3 C 2 T x MXene including supercapacitors, lithium‐ion batteries, sodium‐ion batteries, and lithium–sulfur batteries. The current opportunities and future challenges of Ti 3 C 2 T x MXene are addressed for energy‐storage devices. This Review seeks to provide a rational and in‐depth understanding of the relation between the electrochemical performance and the nanostructural/chemical composition of Ti 3 C 2 T x , which will promote the further development of 2D MXenes in energy‐storage applications.

Abstract T cells are crucial for immune functions to maintain health and prevent disease. T cell development occurs in a stepwise process in the thymus and mainly generates CD4 + and CD8 + T cell subsets. Upon antigen stimulation, naïve T cells differentiate into CD4 + helper and CD8 + cytotoxic effector and memory cells, mediating direct killing, diverse immune regulatory function, and long-term protection. In response to acute and chronic infections and tumors, T cells adopt distinct differentiation trajectories and develop into a range of heterogeneous populations with various phenotype, differentiation potential, and functionality under precise and elaborate regulations of transcriptional and epigenetic programs. Abnormal T-cell immunity can initiate and promote the pathogenesis of autoimmune diseases. In this review, we summarize the current understanding of T cell development, CD4 + and CD8 + T cell classification, and differentiation in physiological settings. We further elaborate the heterogeneity, differentiation, functionality, and regulation network of CD4 + and CD8 + T cells in infectious disease, chronic infection and tumor, and autoimmune disease, highlighting the exhausted CD8 + T cell differentiation trajectory, CD4 + T cell helper function, T cell contributions to immunotherapy and autoimmune pathogenesis. We also discuss the development and function of γδ T cells in tissue surveillance, infection, and tumor immunity. Finally, we summarized current T-cell-based immunotherapies in both cancer and autoimmune diseases, with an emphasis on their clinical applications. A better understanding of T cell immunity provides insight into developing novel prophylactic and therapeutic strategies in human diseases.

BACKGROUND: High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing. RESULTS: We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and lncRNA transcripts. 10-fold cross-validation tests on human RefSeq mRNAs and GENCODE lncRNAs indicated that our tool could achieve accuracy of up to 95.6%. We demonstrated the utility of PLEK on transcripts from other vertebrates using the model built from human datasets. PLEK attained >90% accuracy on most of these datasets. PLEK also performed well using a simulated dataset and two real de novo assembled transcriptome datasets (sequenced by PacBio and 454 platforms) with relatively high indel sequencing errors. In addition, PLEK is approximately eightfold faster than a newly developed alignment-free tool, named Coding-Non-Coding Index (CNCI), and 244 times faster than the most popular alignment-based tool, Coding Potential Calculator (CPC), in a single-threading running manner. CONCLUSIONS: PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes. PLEK is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data. Its open-source software can be freely downloaded from https://sourceforge.net/projects/plek/files/.

Graphene oxide (GO) was successfully prepared by a modified Hummer's method. The reduction effect and mechanism of the as-prepared GO reduced with hydrazine hydrate at different temperatures and time were characterized by x-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), elemental analysis (EA), x-ray diffractions (XRD), Raman spectroscopy and thermo-gravimetric analysis (TGA). The results showed that the reduction effect of GO mainly depended on treatment temperature instead of treatment time. Desirable reduction of GO can only be obtained at high treatment temperature. Reduced at 95 °C for 3 h, the C/O atomic ratio of GO increased from 3.1 to 15.1, which was impossible to obtain at low temperatures, such as 80, 60 or 15 °C, even for longer reduction time. XPS, 13C NMR and FTIR results show that most of the epoxide groups bonded to graphite during the oxidation were removed from GO and form the sp(2) structure after being reduced by hydrazine hydrate at high temperature (>60 °C), leading to the electric conductivity of GO increasing from 1.5 × 10(-6) to 5 S cm(-1), while the hydroxyls on the surface of GO were not removed by hydrazine hydrate even at high temperature. Additionally, the FTIR, XRD and Raman spectrum indicate that the GO reduced by hydrazine hydrate can not be entirely restored to the pristine graphite structures. XPS and FTIR data also suggest that carbonyl and carboxyl groups can be reduced by hydrazine hydrate and possibly form hydrazone, but not a C = C structure.

In traditional cloud storage systems, attribute-based encryption (ABE) is regarded as an important technology for solving the problem of data privacy and fine-grained access control. However, in all ABE schemes, the private key generator has the ability to decrypt all data stored in the cloud server, which may bring serious problems such as key abuse and privacy data leakage. Meanwhile, the traditional cloud storage model runs in a centralized storage manner, so single point of failure may leads to the collapse of system. With the development of blockchain technology, decentralized storage mode has entered the public view. The decentralized storage approach can solve the problem of single point of failure in traditional cloud storage systems and enjoy a number of advantages over centralized storage, such as low price and high throughput. In this paper, we study the data storage and sharing scheme for decentralized storage systems and propose a framework that combines the decentralized storage system interplanetary file system, the Ethereum blockchain, and ABE technology. In this framework, the data owner has the ability to distribute secret key for data users and encrypt shared data by specifying access policy, and the scheme achieves fine-grained access control over data. At the same time, based on smart contract on the Ethereum blockchain, the keyword search function on the cipher text of the decentralized storage systems is implemented, which solves the problem that the cloud server may not return all of the results searched or return wrong results in the traditional cloud storage systems. Finally, we simulated the scheme in the Linux system and the Ethereum official test network Rinkeby, and the experimental results show that our scheme is feasible.

A combination of high-pressure compression molding plus salt-leaching was first proposed to prepare porous graphene/polystyrene composites. The specific shielding effectiveness of the lightweight composite was as high as 64.4 dB cm3 g−1, the highest value ever reported for polymer based EMI shielding materials at such a low thickness (2.5 mm).

Abstract The construction of advanced Zn‐ion hybrid supercapacitors (ZHSCs) with high energy density is promising but still challenging, especially at high current densities. In this work, a high‐energy and ultrastable aqueous ZHSC is demonstrated by introducing N dopants into a hierarchically porous carbon cathode for the purpose of enhancing its chemical adsorption of Zn ions. Experimental results and theoretical simulations reveal that N doping not only significantly facilitates the chemical adsorption process of Zn ions, but also greatly increases its conductivity, surface wettability, and active sites. Consequently, the as‐fabricated aqueous ZHSC based on this N‐doped porous carbon cathode displays an exceptionally high energy density of 107.3 Wh kg −1 at a high current density of 4.2 A g −1 , a superb power density of 24.9 kW kg −1 , and an ultralong‐term lifespan (99.7% retention after 20 000 cycles), substantially superior to state‐of‐the‐art ZHSCs. Particularly, such a cathode also leads to a quasi‐solid‐state device with satisfactory energy storage performance, delivering a remarkable energy density of 91.8 Wh kg −1 . The boosted energy storage strategy by tuning the chemical adsorption capability is also applicable to other carbon materials.

Abstract Understanding hydrological effects of ecological restoration (ER) is fundamental to develop effective measures guiding future ER and to adapt climate change in China's Loess Plateau (LP). Streamflow ( Q ) is an important indicator of hydrological processes that represents the combined effects of climatic and land surface conditions. Here 14 catchments located in the LP were chosen to explore the Q response to different driving factors during the period 1961–2009 by using elasticity and decomposition methods based on the Budyko framework. Our results show that (1) annual Q exhibited a decreasing trend in all catchments (−0.30 ∼ −1.71 mm yr −2 ), with an average reduction of −0.87 mm yr −2 . The runoff coefficients in flood season and nonflood season were both decreasing between two periods divided by the changing point in annual Q series; (2) the precipitation ( P ) and potential evapotranspiration ( E 0 ) elasticity of Q are 2.75 and −1.75, respectively, indicating that Q is more sensitive to changes in P than that in E 0 ; (3) the two methods consistently demonstrated that, on average, ER (62%) contributing to Q reduction was much larger than that of climate change (38%). In addition, parameter n that entails catchment characteristics in the Budyko framework showed positive correlation with the relative area of ER measures in all catchments (eight of them are statistically significant with p < 0.05). These findings highlight the importance of ER measures on modifying the hydrological partitioning in the region. However, ER actions over the sloping parts of the landscape weakened the impact of those in channels (i.e., check‐dams) on Q , especially after the implementation of the Grain‐for‐Green project in 1999.

Piezoelectric nanogenerators with large output, high sensitivity, and good flexibility have attracted extensive interest in wearable electronics and personal healthcare. In this paper, the authors propose a high‐performance flexible piezoelectric nanogenerator based on piezoelectrically enhanced nanocomposite micropillar array of polyvinylidene fluoride‐trifluoroethylene (P(VDF‐TrFE))/barium titanate (BaTiO 3 ) for energy harvesting and highly sensitive self‐powered sensing. By a reliable and scalable nanoimprinting process, the piezoelectrically enhanced vertically aligned P(VDF‐TrFE)/BaTiO 3 nanocomposite micropillar arrays are fabricated. The piezoelectric device exhibits enhanced voltage of 13.2 V and a current density of 0.33 µA cm −2 , which an enhancement by a factor of 7.3 relatives to the pristine P(VDF‐TrFE) bulk film. The mechanisms of high performance are mainly attributed to the enhanced piezoelectricity of the P(VDF‐TrFE)/BaTiO 3 nanocomposite materials and the improved mechanical flexibility of the micropillar array. Under mechanical impact, stable electricity is stably generated from the nanogenerator and used to drive various electronic devices to work continuously, implying its significance in the field of consumer electronic devices. Furthermore, it can be applied as self‐powered flexible sensor work in a noncontact mode for detecting air pressure and wearable sensors for detecting some human vital signs including different modes of breath and heartbeat pulse, which shows its potential applications in flexible electronics and medical sciences.

The steady-state excess mean square error (EMSE) of the adaptive filtering under the maximum correntropy criterion (MCC) has been studied. For Gaussian noise case, we establish a fixed-point equation to solve the exact value of the steady-state EMSE, while for non-Gaussian noise case, we derive an approximate analytical expression for the steady-state EMSE, based on a Taylor expansion approach. Simulation results agree with the theoretical calculations quite well.

The rapid development of intelligent transportation system (ITS) offers great opportunities to improve the overall performance of energy management strategies (EMSs) for connected hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs). This paper systematically surveys the state-of-the-art in EMSs for connected HEVs/PHEVs. To this end, the main difference between HEVs/PHEVs and internal combustion engine (ICE) vehicles is first elaborated to introduce the EMSs of connected HEVs/PHEVs. A classification framework of EMSs for connected HEVs/PHEVs is then presented, where various approaches are classified into three categories, i.e., in terms of single-vehicle, two-vehicle, and multi-vehicle scenarios. Eco-driving for connected vehicles using V2I (Vehicle to Infrastructure) communication is emphasized as well. In the sequel, a comprehensive literature survey is presented, and each method is elaborated in terms of its basic principles, advantages, and disadvantages. Finally, future research trends from different perspectives are suggested with a view to further development in EMSs for connected HEVs/PHEVs.

This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convolutional Neural Network), FRCN (Fast Region-Convolutional Neural Network), and R-FCN (Region-Based-Fully Convolutional Network) in image feature extraction are analyzed after introducing the relevant region proposal network. Secondly, YOLO-v5 algorithm is established on the basis of YOLO algorithm. Besides, the multi-scale anchor mechanism of Faster R-CNN is utilized to improve the detection ability of YOLO-v5 algorithm for small targets in the image in the process of image detection, and realize the high adaptability of YOLO-v5 algorithm to different sizes of images. Finally, the proposed detection method YOLO-v5 algorithm + R-FCN is compared with other algorithms in NWPU VHR-10 data set and Vaihingen data set. The experimental results show that the YOLO-v5 + R-FCN detection method has the optimal detection ability among many algorithms, especially for small targets in remote sensing images such as tennis courts, vehicles, and storage tanks. Moreover, the YOLO-v5 + R-FCN detection method can achieve high recall rates for different types of small targets. Furthermore, due to the deeper network architecture, the YOL v5 + R-FCN detection method has a stronger ability to extract the characteristics of image targets in the detection of remote sensing images. Meanwhile, it can achieve more accurate feature recognition and detection performance for the densely arranged target images in remote sensing images. This research can provide reference for the application of remote sensing technology in China, and promote the application of satellites for target detection tasks in related fields.

The comprehensive intelligent development of the manufacturing industry puts forward new requirements for the quality inspection of industrial products. This paper summarizes the current research status of machine learning methods in surface defect detection, a key part in the quality inspection of industrial products. First, according to the use of surface features, the application of traditional machine vision surface defect detection methods in industrial product surface defect detection is summarized from three aspects: texture features, color features, and shape features. Secondly, the research status of industrial product surface defect detection based on deep learning technology in recent years is discussed from three aspects: supervised method, unsupervised method, and weak supervised method. Then, the common key problems and their solutions in industrial surface defect detection are systematically summarized; the key problems include real-time problem, small sample problem, small target problem, unbalanced sample problem. Lastly, the commonly used datasets of industrial surface defects in recent years are more comprehensively summarized, and the latest research methods on the MVTec AD dataset are compared, so as to provide some reference for the further research and development of industrial surface defect detection technology.

Abstract As a high‐capacity layered cathode material, Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 (NCM811) has been one of the most felicitous candidates for utilization in the next generation of high‐energy lithium ion batteries (LIBs). Notwithstanding its superiority, there are some issues concerning its cyclability, rate capability, and thermal stability that need to be settled prior to its further practical application. It is believed that upon cycling, chemical, mechanical, and electrochemical stability of the cathode–electrolyte interface plays a key role in resolving these issues. Therefore, all the extensive efforts directed so far toward the optimization of NCM811 electrochemical performance are by some means in connection with the cathode–electrolyte interface. Herein, unique structural and electrochemical characteristics of NCM811 together with in‐depth understanding of its underlying bulk/surface degradation mechanism through cycling are reviewed. More importantly, for the first time, all compatible approaches thus far adopted to perfect the performance of NCM811 are exclusively and scrupulously addressed. Lastly, the most reasonable resolutions to accomplish a robust cathode–electrolyte interface, and consequently impeccable NCM811, along with proposed future research directions are presented.

Existing static grid resource scheduling algorithms, which are limited to minimizing the makespan, cannot meet the needs of resource scheduling required by cloud computing. Current cloud infrastructure solutions provide operational support at the level of resource infrastructure only. When hardware resources form the virtual resource pool, virtual machines are deployed for use transparently. Considering the competing characteristics of multi-tenant environments in cloud computing, this paper proposes a cloud resource allocation model based on an imperfect information Stackelberg game (CSAM-IISG) using a hidden Markov model (HMM) in a cloud computing environment. CSAM-IISG was shown to increase the profit of both the resource supplier and the applicant. Firstly, we used the HMM to predict the service provider's current bid using the historical resources based on demand. Through predicting the bid dynamically, an imperfect information Stackelberg game (IISG) was established. The IISG motivates service providers to choose the optimal bidding strategy according to the overall utility, achieving maximum profits. Based on the unit prices of different types of resources, a resource allocation model is proposed to guarantee optimal gains for the infrastructure supplier. The proposed resource allocation model can support synchronous allocation for both multi-service providers and various resources. The simulation results demonstrated that the predicted price was close to the actual transaction price, which was lower than the actual value in the game model. The proposed model was shown to increase the profits of service providers and infrastructure suppliers simultaneously.

The collapse potential, mineralogy, microstructure, and particle morphology of a loess from the Loess Plateau, China, were characterized by double oedometer testing, X-ray diffraction, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and image analysis to elucidate the origin of its collapse behavior. Results show that the loess is highly collapsible with a maximum collapse index of 6.7% at a vertical stress of ∼200 kPa. The deposit contains both nonclay (i.e., quartz, albite, muscovite, and calcite) and clay (i.e., two chlorites) minerals. Microstructural, chemical, and image analyses indicate that interparticle calcite and clay cementation and silt particle morphology render the intact soil a metastable structure. Wetting-induced collapse is attributed to both primary and secondary microstructure features. The former is the abundance of weakly cemented, unsaturated, porous pure clay and clay–silt mixture aggregates whose slaking upon wetting initiates the overall structural collapse, while the latter consists of high porosity, unstable particle contacts, and clay coating on silt particles that act synergistically to augment the collapse. A conceptual microstructural model of a four-tiered hierarchy (i.e., primary clay and silt particles, clay aggregates and clay-coated silt particles, clay–silt mixture aggregates, and cemented aggregate matrix) is proposed to represent its structural characteristics and to account for its high collapsibility.

The attractive dielectric poly(vinylidene fluoride) (PVDF) and its copolymers are well confirmed possessing the highest electroactive response including dielectric constant, piezoelectric and ferroelectric effects, which have increasingly wide range of applications such as in energy transfer, energy generation and storage, monitoring and control, and include the development of capacitors, sensors, actuators and so on . In this study, by clarifying the reliability of dielectric performances on their crystal phase structure of various PVDF polymers, the different physical and chemical fabricating ways to achieve different forms of PVDF samples such as linear polymers, ferroelectrics, and relaxor ferroelectrics were identified and quantified. In addition, many recent advances in the PVDF‐based polymer dielectrics and some developed applications of these polymers are presented, which gives a reference in academic and engineering area to select an appropriate PVDF series dielectric polymer.

Abstract Perovskite nanocrystals are attracting great interest due to their excellent photonic properties. Here, through a supramolecular self‐assembly approach, the perovskite nanocrystals (NCs) with a novel circularly polarized luminescence (CPL) are successfully endowed. It is found that the achiral perovskite NCs can coassemble with chiral gelator in nonpolar solvents, in which the gelator molecules modify the surface of the perovskite NCs. Through such cogelation, the molecular chirality can transfer to the NCs resulting in CPL signals with a dissymmetric factor ( g lum ) up to 10 −3 . Furthermore, depending on the molecular chirality of the gelator, the CPL sense can be selected and the mirror‐imaged CPL is obtained. Such gels can be further embedded into the polymer film to facilitate flexible CPL devices. It is envisaged that this approach will afford a new insight into the designing of the functional chiroptical materials.

The biggest challenge of potassium-ion batteries (KIBs) application is to develop high-performance electrode materials to accommodate the potassium ions large size. Herein, by rational design, we carbonize three-dimensional (3D) ordered macroporous ZIF-8 to fabricate 3D interconnected nitrogen-doped hierarchical porous carbon (N-HPC) that shows excellent rate performance (94 mAh g–1 at 10.0 A g–1), unprecedented cycle stability (157 mA g–1 after 12000 cycles at 2.0 A g–1), and superior reversible capacity (292 mAh g–1 at 0.1 A g–1). The 3D hierarchical porous structure diminishes the diffusion distance for both ions/electrons, while N-doping improves the reactivity and electronic conductivity via producing more defects. In addition, the bicontinuous structure possesses a large specific surface area, decreasing the current density, again improving the rate performance. In situ Raman spectra analysis confirms the potassiation and depotassiation in the N-HPC are highly reversible processes. The galvanostatic intermittent titration measurement and first-principles calculations reveal that the interconnected macropores are more beneficial to the diffusion of the K+. This 3D interpenetrating structure demonstrates a superiority for energy storage applications.