Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human ...Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.展开更多
Direct recycling is a novel approach to overcoming the drawbacks of conventional lithium-ion battery(LIB)recycling processes and has gained considerable attention from the academic and industrial sectors in recent yea...Direct recycling is a novel approach to overcoming the drawbacks of conventional lithium-ion battery(LIB)recycling processes and has gained considerable attention from the academic and industrial sectors in recent years.The primary objective of directly recycling LIBs is to efficiently recover and restore the active electrode materials and other components in the solid phase while retaining electrochemical performance.This technology's advantages over traditional pyrometallurgy and hydrometallurgy are costeffectiveness,energy efficiency,and sustainability,and it preserves the material structure and morphology and can shorten the overall recycling path.This review extensively discusses the advancements in the direct recycling of LIBs,including battery sorting,pretreatment processes,separation of cathode and anode materials,and regeneration and quality enhancement of electrode materials.It encompasses various approaches to successfully regenerate high-value electrode materials and streamlining the recovery process without compromising their electrochemical properties.Furthermore,we highlight key challenges in direct recycling when scaled from lab to industries in four perspectives:(1)battery design,(2)disassembling,(3)electrode delamination,and(4)commercialization and sustainability.Based on these challenges and changing market trends,a few strategies are discussed to aid direct recycling efforts,such as binders,electrolyte selection,and alternative battery designs;and recent transitions and technological advancements in the battery industry are presented.展开更多
Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and sha...Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.展开更多
Seaweed,as a third generation of biomass energy,has significant potential to replace non-renewable fossil fuels.Among various conversion technologies,hydrothermal liquefaction can effectively convert seaweed into bio-...Seaweed,as a third generation of biomass energy,has significant potential to replace non-renewable fossil fuels.Among various conversion technologies,hydrothermal liquefaction can effectively convert seaweed into bio-oil.However,most current research on hydrothermal liquefaction products focuses on the oil phase and solid phase,with little attention given to the utilization of the aqueous phase by-product.In this study,the large seaweed Enteromorpha prolifera was selected as the raw material.The aqueous phase containing organic components was prepared through hydrothermal liquefaction at different temperatures,which was then mixed with the polymer polyvinyl alcohol to produce high-value chemical hydrogels.Furthermore,the hydrogels were salted out with Fe3+to explore its influence on the degree of crosslinking.The results show that the mechanical properties of the hydrogel are optimal when the hydrothermal temperature is 160℃,with a maximum fracture stress of 0.55 MPa.After salting-out treatment,the mechanical strength of the hydrogel was further enhanced,with the maximum breaking stress increment by 1.3 times(1.26 MPa).This indicates that the process of adding the aqueous phase to the hydrogel has research potential,and Fe3+can further strengthen the crosslinking process.The results of the present study will provide new insights and methods for aqueous phase valorization.展开更多
MXenes,a new family of two-dimensional(2D)materials with excellent electronic conductivity and hydrophilicity,have shown distinctive advantages as a highly conductive matrix material for lithium-ion battery anodes.Her...MXenes,a new family of two-dimensional(2D)materials with excellent electronic conductivity and hydrophilicity,have shown distinctive advantages as a highly conductive matrix material for lithium-ion battery anodes.Herein,a facile electrostatic self-assembly of SnO2 quantum dots(QDs)on Ti3C2Tx MXene sheets is proposed.The as-prepared SnO2/MXene hybrids have a unique 0D-2D structure,in which the 0D SnO2 QDs(~4.7 nm)are uniformly distributed over 2D Ti3C2Tx MXene sheets with controllable loading amount.The SnO2 QDs serve as a high capacity provider and the“spacer”to prevent the MXene sheets from restacking;the highly conductive Ti3C2Tx MXene can not only provide efficient pathways for fast transport of electrons and Li ions,but also buffer the volume change of SnO2 during lithiation/delithiation by confining SnO2 QDs between the MXene nanosheets.Therefore,the 0D-2D SnO2 QDs/MXene hybrids deliver superior lithium storage properties with high capacity(887.4 mAh g?1 at 50 mA g?1),stable cycle performance(659.8 mAh g?1 at 100 mA g?1 after 100 cycles with a capacity retention of 91%)and excellent rate performance(364 mAh g?1 at 3 A g?1),making it a promising anode material for lithium-ion batteries.展开更多
In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no...In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application.To this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure probability.The results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load conditions.In addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.展开更多
ZnS has great potentials as an anode for lithium storage because of its high theoretical capacity and resource abundance;however,the large volume expansion accompanied with structural collapse and low conductivity of ...ZnS has great potentials as an anode for lithium storage because of its high theoretical capacity and resource abundance;however,the large volume expansion accompanied with structural collapse and low conductivity of ZnS cause severe capacity fading and inferior rate capability during lithium storage. Herein,0D-2 D ZnS nanodots/Ti_(3)C_(2)T_x MXene hybrids are prepared by anchoring ZnS nanodots on Ti_(3)C_(2)T_(x) MXene nanosheets through coordination modulation between MXene and MOF precursor(ZIF-8) followed with sulfidation. The MXene substratecoupled with the ZnS nanodots can synergistically accommodate volume variation of ZnS over charge–discharge to realize stable cyclability. As revealed by XPS characterizations and DFT calculations,the strong interfacial interaction between ZnS nanodots and MXene nanosheets can boost fast electron/lithium-ion transfer to achieve excellent electrochemical activity and kinetics for lithium storage. Thereby,the as-prepared ZnS nanodots/MXene hybrid exhibits a high capacity of 726.8 mAh g^(-1) at 30 mA g^(-1),superior cyclic stability(462.8 mAh g^(-1) after 1000 cycles at 0.5 A g^(-1)),and excellent rate performance. The present results provide new insights into the understanding of the lithium storage mechanism of ZnS and the revealing of the e ects of interfacial interaction on lithium storage performance enhancement.展开更多
LncRNA(long non-coding RNA) H19 is a transcript of the H19 gene that is expressed during embryogenesis.We previously discove red a role for circular lncRNA H19 in the onset and prognosis of cerebral ischemic stroke.In...LncRNA(long non-coding RNA) H19 is a transcript of the H19 gene that is expressed during embryogenesis.We previously discove red a role for circular lncRNA H19 in the onset and prognosis of cerebral ischemic stroke.In this study,we used serum from patients with ischemic stroke,and mouse and cell culture models to elucidate the roles of plasma and neuronal exosomes in the regulatory effect of lncRNA H19 on insulin-like growth factor-1 and its mechanism in ischemic stroke,using western blotting,quantitative real-time polymerase chain reaction,and enzyme-linked immunosorbent assays.Plasma exosomal IncRNA H19 was negatively associated with blood levels of insulin-like growth factor-1 in samples from patients with cerebral ischemic stroke.In a mouse model,levels of exosomal IncRNA H19 were positively correlated with plasma and cerebral lncRNA H19.In a cell co-culture model,we confirmed that IncRNA H19 was transported from neuro ns to astrocytes by exosomes to induce downregulation of insulin-like growth factor-1 through the H19/let-7 a/insulin-like growth factor-1 receptor axis.This study provides the first evidence for the transpo rtation of IncRNA H19 by exosomes and the relationship between IncRNA H19 and insulinlike growth factor-1.展开更多
The sixth-generation(6G)network must provide better performance than previous generations to meet the requirements of emerging services and applications,such as multi-gigabit transmission rate,higher reliability,and s...The sixth-generation(6G)network must provide better performance than previous generations to meet the requirements of emerging services and applications,such as multi-gigabit transmission rate,higher reliability,and sub-1 ms latency and ubiquitous connection for the Internet of Everything(IoE).However,with the scarcity of spectrum resources,efficient resource management and sharing are crucial to achieving all these ambitious requirements.One possible technology to achieve all this is the blockchain.Because of its inherent properties,the blockchain has recently gained an important position,which is of great significance to the 6G network and other networks.In particular,the integration of the blockchain in 6G will enable the network to monitor and manage resource utilization and sharing efficiently.Hence,in this paper,we discuss the potentials of the blockchain for resource management and sharing in 6G using multiple application scenarios,namely,Internet of things,deviceto-device communications,network slicing,and inter-domain blockchain ecosystems.展开更多
Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of im...Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of image or video processing,which imposes enormous pressure on the UAV computation platform.To solve this issue,in this work,we propose an intelligent Task Offloading Algorithm(iTOA)for UAV edge computing network.Compared with existing methods,iTOA is able to perceive the network’s environment intelligently to decide the offloading action based on deep Monte Calor Tree Search(MCTS),the core algorithm of Alpha Go.MCTS will simulate the offloading decision trajectories to acquire the best decision by maximizing the reward,such as lowest latency or power consumption.To accelerate the search convergence of MCTS,we also proposed a splitting Deep Neural Network(sDNN)to supply the prior probability for MCTS.The sDNN is trained by a self-supervised learning manager.Here,the training data set is obtained from iTOA itself as its own teacher.Compared with game theory and greedy search-based methods,the proposed iTOA improves service latency performance by 33%and 60%,respectively.展开更多
The forking problem plays a key role in the security issue,which is a major concern in the blockchain system.Although many works studied the attack strategy,consensus mechanism,privacy-protecting and security performa...The forking problem plays a key role in the security issue,which is a major concern in the blockchain system.Although many works studied the attack strategy,consensus mechanism,privacy-protecting and security performance analysis,most of them only address the intentional forking caused by a malicious attacker.In fact,without any attacker,unintentional forking still remains due to transmission delay and failure,especially in wireless network scenarios.To this end,this paper investigates the reason for generating unintentional forking and derives the forking probability expression in Wireless Blockchain Networks(WBN).Furthermore,in order to illustrate the unintentional forking on the blockchain system,the performances in terms of resource utilization rate,block generation time,and Transaction Per Second(TPS)are investigated.The numerical results show that the target difficulty of hash algorithm in generating a new block,the delay time of broadcasting,the network scale,and the transmission failure probability would affect the unintentional forking probability significantly,which can provide a reliable basis for avoiding forking to save resource consumption and improving system performance.展开更多
Objective:To explore whether the traditional Chinese medicine(TCM)Bu Jing Yi Shi Tablets alters the expression of scleral TGF-b1 and Smad3 in guinea pigs with formdeprivation myopia(FDM).Methods:Sixty-five guinea pigs...Objective:To explore whether the traditional Chinese medicine(TCM)Bu Jing Yi Shi Tablets alters the expression of scleral TGF-b1 and Smad3 in guinea pigs with formdeprivation myopia(FDM).Methods:Sixty-five guinea pigs were randomly divided into control,model,low-,medium-,and high-dose treatment groups.Except for the control group,FDM was induced by covering the right eye of each animal with opaque latex.The treatment groups were gavaged with different suspension concentrations of Bu Jing Yi Shi Tablets.Refraction and axial length were performed before and after myopia induction.At the end of the experiment,all right eyes were extracted,and scleral sections were prepared for staining and TGF-b1 and Smad3 immunohistochemistry.Scleral thickness and area,the scleral fibroblast quantity,and scleral TGFb1 and Smad3 expressions were measured.Results:The 5 FDM groups had the same initial axial length and diopter,the final diopter and axial length of the model group were significantly increased compared with the control group and treatment groups(P<.01).The axial length of each treatment group decreased as the dose decreased compared with the model group(P<.01);the total scleral area(P<.05 e.01)and the number of scleral fibroblasts(P<.01)in the model group were significantly lower than the treatment groups.Both the TGF-b1 and Smad3 integral optical densities in the model group were significantly lower than the control and medium-and high-dose treatment groups(P<.01).TGF-b1 and Smad3 mRNAs in the model group were decreased compared with the control group,but increased in expression after treatment.展开更多
Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobil...Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobile edge caching technology from the perspectie of caching resource management by examining a network composed of one operator, multiple users and Content Providers (CPs). The caching resource management model is constructed on the premise of fully considering the QoE of users and the servicing capability of the Base Station (BS). In order to create the best caching resource allocation scheme, the original problem is transformed into a multi-leader multi-follower Stackelberg game model through the analysis of the system model. The strategy combinations and the utility functions of players are analyzed. The existence and uniqueness of the Nash Equilibrium (NE) solution are also analyzed and proved. The optimal strategy combinations and the best responses are deduced in detail. Simulation results and analysis show that the proposed model and algorithm can achieve the optimal allocation of caching resource and improve the QoE of users.展开更多
Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.How...Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.However,due to the massive connectivity of mobile devices,the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system.We propose a deep Monte Carlo Tree Search(MCTS)-based intelligent Pilot-power Allocation Scheme(iPAS)to address this issue.The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training.To accelerate the searching convergence,we introduce a Deep Neural Network(DNN)to predict the pilot sequence and power allocation actions.The DNN is trained in a self-supervised learning manner,where the training data is generated from the searching process of the MCTS algorithm.Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function(CDF)of the ergodic spectral efficiency compared with the previous suboptimal algorithms.展开更多
The steady fusion plasma operation is constrained by tungsten(W)material sputtering issue in the EAST tokamak.In this work,the suppression of W sputtering source has been studied by advanced wall conditionings.It is a...The steady fusion plasma operation is constrained by tungsten(W)material sputtering issue in the EAST tokamak.In this work,the suppression of W sputtering source has been studied by advanced wall conditionings.It is also concluded that the W sputtering yield becomes more with increasing carbon(C)content in the main deuterium(D)plasma.In EAST,the integrated use of discharge cleanings and lithium(Li)coating has positive effects on the suppression of W sputtering source.In the plasma recovery experiments,it is suggested that the W intensity is reduced by approximately 60%with the help of~35 h Ion Cyclotron Radio Frequency Discharge Cleaning(ICRF-DC)and~40 g Li coating after vacuum failure.The first wall covered by Li film could be relieved from the bombardment of energetic particles,and the impurity in the vessel would be removed through the particle induced desorption and isotope exchange during the discharge cleanings.In general,the sputtering yield of W would decrease from the source,on the bias of the improvement of wall condition and the mitigation of plasmawall interaction process.It lays important base of the achievement of high-parameter and longpulse plasma operation in EAST.The experiences also would be constructive for us to promote the understanding of relevant physics and basis towards the ITER-like condition.展开更多
With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new ...With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new challenges to the operation of the grid.Firstly,A novel bidirectional interaction model is established based on modulation theory with nonlinear loads.Then,the electric energy measuring scheme of EVs for V2G is derived under the conditions of distorted power loads.The scheme is composed of fundamental electric energy,fundamental-distorted electric energy,distorted-fundamental electric energy and distorted electric energy.And the characteristics of each electric energy are analyzed.Finally,the correctness of the model and energy measurement method is verified by three simulation cases:the impact signals,the fluctuating signals,and the harmonic signals.展开更多
基金supported in part by the National Natural Science Foundation of China (NSFC) under Grant No.61976242in part by the Natural Science Fund of Hebei Province for Distinguished Young Scholars under Grant No.F2021202010+2 种基金in part by the Fundamental Scientific Research Funds for Interdisciplinary Team of Hebei University of Technology under Grant No.JBKYTD2002funded by Science and Technology Project of Hebei Education Department under Grant No.JZX2023007supported by 2022 Interdisciplinary Postgraduate Training Program of Hebei University of Technology under Grant No.HEBUT-YXKJC-2022122.
文摘Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.
基金National Research Foundation Singapore and National Environment Agency Singapore,Grant/Award Number:CTRL-2023-1D-01。
文摘Direct recycling is a novel approach to overcoming the drawbacks of conventional lithium-ion battery(LIB)recycling processes and has gained considerable attention from the academic and industrial sectors in recent years.The primary objective of directly recycling LIBs is to efficiently recover and restore the active electrode materials and other components in the solid phase while retaining electrochemical performance.This technology's advantages over traditional pyrometallurgy and hydrometallurgy are costeffectiveness,energy efficiency,and sustainability,and it preserves the material structure and morphology and can shorten the overall recycling path.This review extensively discusses the advancements in the direct recycling of LIBs,including battery sorting,pretreatment processes,separation of cathode and anode materials,and regeneration and quality enhancement of electrode materials.It encompasses various approaches to successfully regenerate high-value electrode materials and streamlining the recovery process without compromising their electrochemical properties.Furthermore,we highlight key challenges in direct recycling when scaled from lab to industries in four perspectives:(1)battery design,(2)disassembling,(3)electrode delamination,and(4)commercialization and sustainability.Based on these challenges and changing market trends,a few strategies are discussed to aid direct recycling efforts,such as binders,electrolyte selection,and alternative battery designs;and recent transitions and technological advancements in the battery industry are presented.
基金supported by STI 2030-Major Projects 2021ZD0200400National Natural Science Foundation of China(62276233 and 62072405)Key Research Project of Zhejiang Province(2023C01048).
文摘Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.
基金supported by the Jiangsu Province Outstanding Youth Fund(BK20230012)the National Natural Science Foundation of China(Grant No.52200155)+1 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(2023ZB736)the Qing Lan Project of Jiangsu Province.
文摘Seaweed,as a third generation of biomass energy,has significant potential to replace non-renewable fossil fuels.Among various conversion technologies,hydrothermal liquefaction can effectively convert seaweed into bio-oil.However,most current research on hydrothermal liquefaction products focuses on the oil phase and solid phase,with little attention given to the utilization of the aqueous phase by-product.In this study,the large seaweed Enteromorpha prolifera was selected as the raw material.The aqueous phase containing organic components was prepared through hydrothermal liquefaction at different temperatures,which was then mixed with the polymer polyvinyl alcohol to produce high-value chemical hydrogels.Furthermore,the hydrogels were salted out with Fe3+to explore its influence on the degree of crosslinking.The results show that the mechanical properties of the hydrogel are optimal when the hydrothermal temperature is 160℃,with a maximum fracture stress of 0.55 MPa.After salting-out treatment,the mechanical strength of the hydrogel was further enhanced,with the maximum breaking stress increment by 1.3 times(1.26 MPa).This indicates that the process of adding the aqueous phase to the hydrogel has research potential,and Fe3+can further strengthen the crosslinking process.The results of the present study will provide new insights and methods for aqueous phase valorization.
基金supported by the National Key Research and Development Program of China“New Energy Project for Electric Vehicle”(2016YFB0100204)the National Natural Science Foundation of China(Nos.51772030,21805011,51572011,51802012)+2 种基金the Joint Funds of the National Natural Science Foundation of China(U1564206)Beijing Key Research and Development Plan(Z181100004518001)China Postdoctoral Science Foundation(Nos.2017M620637,2018M643697,2019T120930).
文摘MXenes,a new family of two-dimensional(2D)materials with excellent electronic conductivity and hydrophilicity,have shown distinctive advantages as a highly conductive matrix material for lithium-ion battery anodes.Herein,a facile electrostatic self-assembly of SnO2 quantum dots(QDs)on Ti3C2Tx MXene sheets is proposed.The as-prepared SnO2/MXene hybrids have a unique 0D-2D structure,in which the 0D SnO2 QDs(~4.7 nm)are uniformly distributed over 2D Ti3C2Tx MXene sheets with controllable loading amount.The SnO2 QDs serve as a high capacity provider and the“spacer”to prevent the MXene sheets from restacking;the highly conductive Ti3C2Tx MXene can not only provide efficient pathways for fast transport of electrons and Li ions,but also buffer the volume change of SnO2 during lithiation/delithiation by confining SnO2 QDs between the MXene nanosheets.Therefore,the 0D-2D SnO2 QDs/MXene hybrids deliver superior lithium storage properties with high capacity(887.4 mAh g?1 at 50 mA g?1),stable cycle performance(659.8 mAh g?1 at 100 mA g?1 after 100 cycles with a capacity retention of 91%)and excellent rate performance(364 mAh g?1 at 3 A g?1),making it a promising anode material for lithium-ion batteries.
基金the National Natural Science Foundation of China under Grant 61701059,Grant 61941114,and Grant 61831002,in part by the Fundamental Research Funds for the Central Universities of New TeachersProject,in part by the Chongqing Technological Innovation and Application Development Projects under Grant cstc2019jscx-msxm1322,and in part by the Eighteentg Open Foundation of State Key Lab of Integrated Services Networks of Xidian University under Grant ISN20-05.
文摘In the blockchain,the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks.Various blockchain consensus mechanisms have been proposed.However,there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application.To this end,this work investigates three mainstream consensus mechanisms in the blockchain,namely,Proof of Work(PoW),Proof of Stake(PoS),and Direct Acyclic Graph(DAG),and identifies their performances in terms of the average time to generate a new block,the confirmation delay,the Transaction Per Second(TPS)and the confirmation failure probability.The results show that the consensus process is affected by both network resource(computation power/coin age,buffer size)and network load conditions.In addition,it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.
基金supported by the National Natural Science Foundation of China (21805011,51902251,52072021,and U2004212)the State Key Laboratory of Organic-Inorganic Composites (oic-202101010)+1 种基金the Natural Science Foundation of Shaanxi Provincial Department of Education (20JK0753)the Provincial Joint Fund of Shaanxi (2021JLM-28)。
文摘ZnS has great potentials as an anode for lithium storage because of its high theoretical capacity and resource abundance;however,the large volume expansion accompanied with structural collapse and low conductivity of ZnS cause severe capacity fading and inferior rate capability during lithium storage. Herein,0D-2 D ZnS nanodots/Ti_(3)C_(2)T_x MXene hybrids are prepared by anchoring ZnS nanodots on Ti_(3)C_(2)T_(x) MXene nanosheets through coordination modulation between MXene and MOF precursor(ZIF-8) followed with sulfidation. The MXene substratecoupled with the ZnS nanodots can synergistically accommodate volume variation of ZnS over charge–discharge to realize stable cyclability. As revealed by XPS characterizations and DFT calculations,the strong interfacial interaction between ZnS nanodots and MXene nanosheets can boost fast electron/lithium-ion transfer to achieve excellent electrochemical activity and kinetics for lithium storage. Thereby,the as-prepared ZnS nanodots/MXene hybrid exhibits a high capacity of 726.8 mAh g^(-1) at 30 mA g^(-1),superior cyclic stability(462.8 mAh g^(-1) after 1000 cycles at 0.5 A g^(-1)),and excellent rate performance. The present results provide new insights into the understanding of the lithium storage mechanism of ZnS and the revealing of the e ects of interfacial interaction on lithium storage performance enhancement.
基金supported by the National Natural Science Foundation of China,No.82271353(to JW)Key Research and Development Program of Liaoning Province,No.2020JH2/10300047(to JF).
文摘LncRNA(long non-coding RNA) H19 is a transcript of the H19 gene that is expressed during embryogenesis.We previously discove red a role for circular lncRNA H19 in the onset and prognosis of cerebral ischemic stroke.In this study,we used serum from patients with ischemic stroke,and mouse and cell culture models to elucidate the roles of plasma and neuronal exosomes in the regulatory effect of lncRNA H19 on insulin-like growth factor-1 and its mechanism in ischemic stroke,using western blotting,quantitative real-time polymerase chain reaction,and enzyme-linked immunosorbent assays.Plasma exosomal IncRNA H19 was negatively associated with blood levels of insulin-like growth factor-1 in samples from patients with cerebral ischemic stroke.In a mouse model,levels of exosomal IncRNA H19 were positively correlated with plasma and cerebral lncRNA H19.In a cell co-culture model,we confirmed that IncRNA H19 was transported from neuro ns to astrocytes by exosomes to induce downregulation of insulin-like growth factor-1 through the H19/let-7 a/insulin-like growth factor-1 receptor axis.This study provides the first evidence for the transpo rtation of IncRNA H19 by exosomes and the relationship between IncRNA H19 and insulinlike growth factor-1.
基金This work was supported in part by the U.K.EPSRC(EP/S02476X/1)Sichuan International Science and Technology Innovation Cooperation/Hong Kong,Macao and Taiwan Science and Technology Innovation Cooperation Project(2019YFH0163)Key Research and Development Project of Sichuan Provincial Department of Science and Technology(2018JZ0071).
文摘The sixth-generation(6G)network must provide better performance than previous generations to meet the requirements of emerging services and applications,such as multi-gigabit transmission rate,higher reliability,and sub-1 ms latency and ubiquitous connection for the Internet of Everything(IoE).However,with the scarcity of spectrum resources,efficient resource management and sharing are crucial to achieving all these ambitious requirements.One possible technology to achieve all this is the blockchain.Because of its inherent properties,the blockchain has recently gained an important position,which is of great significance to the 6G network and other networks.In particular,the integration of the blockchain in 6G will enable the network to monitor and manage resource utilization and sharing efficiently.Hence,in this paper,we discuss the potentials of the blockchain for resource management and sharing in 6G using multiple application scenarios,namely,Internet of things,deviceto-device communications,network slicing,and inter-domain blockchain ecosystems.
基金the Artificial Intelligence Key Laboratory of Sichuan Province(Nos.2019RYJ05)National Natural Science Foundation of China(Nos.61971107).
文摘Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of image or video processing,which imposes enormous pressure on the UAV computation platform.To solve this issue,in this work,we propose an intelligent Task Offloading Algorithm(iTOA)for UAV edge computing network.Compared with existing methods,iTOA is able to perceive the network’s environment intelligently to decide the offloading action based on deep Monte Calor Tree Search(MCTS),the core algorithm of Alpha Go.MCTS will simulate the offloading decision trajectories to acquire the best decision by maximizing the reward,such as lowest latency or power consumption.To accelerate the search convergence of MCTS,we also proposed a splitting Deep Neural Network(sDNN)to supply the prior probability for MCTS.The sDNN is trained by a self-supervised learning manager.Here,the training data set is obtained from iTOA itself as its own teacher.Compared with game theory and greedy search-based methods,the proposed iTOA improves service latency performance by 33%and 60%,respectively.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61701059,Grant 61941114,and Grant 61831002in part by the Fundamental Research Funds for the Central Universities of New Teachers Project,in part by the Basic and Advanced Research Projects of CSTC(No.cstc2019jcyj-zdxmX0008)+2 种基金in part by the Chongqing Science and Technology Innovation Leading Talent Support Program(CSTCCXLJR-C201710,and CSTCCXLJRC201908)in part by Chongqing Technological Innovation and Application Development Projects(cstc2019jscx-msxm1322)in part by the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant No.KJZD-K201900605).
文摘The forking problem plays a key role in the security issue,which is a major concern in the blockchain system.Although many works studied the attack strategy,consensus mechanism,privacy-protecting and security performance analysis,most of them only address the intentional forking caused by a malicious attacker.In fact,without any attacker,unintentional forking still remains due to transmission delay and failure,especially in wireless network scenarios.To this end,this paper investigates the reason for generating unintentional forking and derives the forking probability expression in Wireless Blockchain Networks(WBN).Furthermore,in order to illustrate the unintentional forking on the blockchain system,the performances in terms of resource utilization rate,block generation time,and Transaction Per Second(TPS)are investigated.The numerical results show that the target difficulty of hash algorithm in generating a new block,the delay time of broadcasting,the network scale,and the transmission failure probability would affect the unintentional forking probability significantly,which can provide a reliable basis for avoiding forking to save resource consumption and improving system performance.
基金the Scientific Research Foundation of Sichuan Provincial Education Department(11ZA065:Scleral TGF-b1 expression in guinea pigs with form-deprivation myopia is altered in response to invigoration spleen and elimination blood stasis)the Department of Public Health Foundation,Sichuan Province(110527:Study on FDM guinea pig scleral fibroblasts TGFb1/Smad3 signaling pathway)the Science and Technology Development Foundation of the Teaching Hospital of Chengdu University of TCM(2012-D-YY-12:Research on FDM:guinea pig retinal function is altered in response to nourishing Xu and removing blood stasis).
文摘Objective:To explore whether the traditional Chinese medicine(TCM)Bu Jing Yi Shi Tablets alters the expression of scleral TGF-b1 and Smad3 in guinea pigs with formdeprivation myopia(FDM).Methods:Sixty-five guinea pigs were randomly divided into control,model,low-,medium-,and high-dose treatment groups.Except for the control group,FDM was induced by covering the right eye of each animal with opaque latex.The treatment groups were gavaged with different suspension concentrations of Bu Jing Yi Shi Tablets.Refraction and axial length were performed before and after myopia induction.At the end of the experiment,all right eyes were extracted,and scleral sections were prepared for staining and TGF-b1 and Smad3 immunohistochemistry.Scleral thickness and area,the scleral fibroblast quantity,and scleral TGFb1 and Smad3 expressions were measured.Results:The 5 FDM groups had the same initial axial length and diopter,the final diopter and axial length of the model group were significantly increased compared with the control group and treatment groups(P<.01).The axial length of each treatment group decreased as the dose decreased compared with the model group(P<.01);the total scleral area(P<.05 e.01)and the number of scleral fibroblasts(P<.01)in the model group were significantly lower than the treatment groups.Both the TGF-b1 and Smad3 integral optical densities in the model group were significantly lower than the control and medium-and high-dose treatment groups(P<.01).TGF-b1 and Smad3 mRNAs in the model group were decreased compared with the control group,but increased in expression after treatment.
文摘Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobile edge caching technology from the perspectie of caching resource management by examining a network composed of one operator, multiple users and Content Providers (CPs). The caching resource management model is constructed on the premise of fully considering the QoE of users and the servicing capability of the Base Station (BS). In order to create the best caching resource allocation scheme, the original problem is transformed into a multi-leader multi-follower Stackelberg game model through the analysis of the system model. The strategy combinations and the utility functions of players are analyzed. The existence and uniqueness of the Nash Equilibrium (NE) solution are also analyzed and proved. The optimal strategy combinations and the best responses are deduced in detail. Simulation results and analysis show that the proposed model and algorithm can achieve the optimal allocation of caching resource and improve the QoE of users.
文摘Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.However,due to the massive connectivity of mobile devices,the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system.We propose a deep Monte Carlo Tree Search(MCTS)-based intelligent Pilot-power Allocation Scheme(iPAS)to address this issue.The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training.To accelerate the searching convergence,we introduce a Deep Neural Network(DNN)to predict the pilot sequence and power allocation actions.The DNN is trained in a self-supervised learning manner,where the training data is generated from the searching process of the MCTS algorithm.Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function(CDF)of the ergodic spectral efficiency compared with the previous suboptimal algorithms.
基金supported by the National Key Research and Development Program of China(Nos.2017YFE0301100 and 2017YFA0402500)National Natural Science Foundation of China(No.11605237)the Users with Excellence Program of Hefei Science Center CAS(2020HSC-UE010)。
文摘The steady fusion plasma operation is constrained by tungsten(W)material sputtering issue in the EAST tokamak.In this work,the suppression of W sputtering source has been studied by advanced wall conditionings.It is also concluded that the W sputtering yield becomes more with increasing carbon(C)content in the main deuterium(D)plasma.In EAST,the integrated use of discharge cleanings and lithium(Li)coating has positive effects on the suppression of W sputtering source.In the plasma recovery experiments,it is suggested that the W intensity is reduced by approximately 60%with the help of~35 h Ion Cyclotron Radio Frequency Discharge Cleaning(ICRF-DC)and~40 g Li coating after vacuum failure.The first wall covered by Li film could be relieved from the bombardment of energetic particles,and the impurity in the vessel would be removed through the particle induced desorption and isotope exchange during the discharge cleanings.In general,the sputtering yield of W would decrease from the source,on the bias of the improvement of wall condition and the mitigation of plasmawall interaction process.It lays important base of the achievement of high-parameter and longpulse plasma operation in EAST.The experiences also would be constructive for us to promote the understanding of relevant physics and basis towards the ITER-like condition.
基金This work is supported by China Postdoctoral Science Foundation(2021M690798)Guizhou Province Science and Technology Plan Project(No.[2021]General 085)+1 种基金National Natural Science Foundation of China(No.61603034)the Fundamental Research Funds for the Central Universities(Nos.FRF-BD-19-002A,FRF-DF-20-14).
文摘With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new challenges to the operation of the grid.Firstly,A novel bidirectional interaction model is established based on modulation theory with nonlinear loads.Then,the electric energy measuring scheme of EVs for V2G is derived under the conditions of distorted power loads.The scheme is composed of fundamental electric energy,fundamental-distorted electric energy,distorted-fundamental electric energy and distorted electric energy.And the characteristics of each electric energy are analyzed.Finally,the correctness of the model and energy measurement method is verified by three simulation cases:the impact signals,the fluctuating signals,and the harmonic signals.
