Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protectiv...Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.展开更多
As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security ...As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.展开更多
Deep neural networks remain susceptible to adversarial examples,where the goal of an adversarial attack is to introduce small perturbations to the original examples in order to confuse the model without being easily d...Deep neural networks remain susceptible to adversarial examples,where the goal of an adversarial attack is to introduce small perturbations to the original examples in order to confuse the model without being easily detected.Although many adversarial attack methods produce adversarial examples that have achieved great results in the whitebox setting,they exhibit low transferability in the black-box setting.In order to improve the transferability along the baseline of the gradient-based attack technique,we present a novel Stochastic Gradient Accumulation Momentum Iterative Attack(SAMI-FGSM)in this study.In particular,during each iteration,the gradient information is calculated using a normal sampling approach that randomly samples around the sample points,with the highest probability of capturing adversarial features.Meanwhile,the accumulated information of the sampled gradient from the previous iteration is further considered to modify the current updated gradient,and the original gradient attack direction is changed to ensure that the updated gradient direction is more stable.Comprehensive experiments conducted on the ImageNet dataset show that our method outperforms existing state-of-the-art gradient-based attack techniques,achieving an average improvement of 10.2%in transferability.展开更多
Anomaly detection(AD)in time series data is widely applied across various industries for monitoring and security applications,emerging as a key research focus within the field of deep learning.While many methods based...Anomaly detection(AD)in time series data is widely applied across various industries for monitoring and security applications,emerging as a key research focus within the field of deep learning.While many methods based on different normality assumptions performwell in specific scenarios,they often neglected the overall normality issue.Some feature extraction methods incorporate pre-training processes but they may not be suitable for time series anomaly detection,leading to decreased performance.Additionally,real-world time series samples are rarely free from noise,making them susceptible to outliers,which further impacts detection accuracy.To address these challenges,we propose a novel anomaly detection method called Robust One-Class Classification Detection(ROC).This approach utilizes an autoencoder(AE)to learn features while constraining the context vectors fromthe AE within a sufficiently small hypersphere,akin to One-Class Classification(OC)methods.By simultaneously optimizing two hypothetical objective functions,ROC captures various aspects of normality.We categorize the input raw time series into clean and outlier sequences,reducing the impact of outliers on compressed feature representation.Experimental results on public datasets indicate that our approach outperforms existing baselinemethods and substantially improves model robustness.展开更多
Cobalt-free cathode materials are attractive for their high capacity and low cost,yet they still encounter issues with structural and surface instability.AlPO_(4),in particular,has garnered attention as an effective s...Cobalt-free cathode materials are attractive for their high capacity and low cost,yet they still encounter issues with structural and surface instability.AlPO_(4),in particular,has garnered attention as an effective stabilizer for bulk and surface.However,the impact of interfacial reactions and elemental interdiffusion between AlPO_(4) and LiNi_(0.95)Mn_(0.05)O_(2) upon sintering on the bulk and surface remains elusive.In this study,we demonstrate that during the heat treatment process,AlPO_(4) decomposes,resulting in Al doping into the bulk of the cathode through elemental interdiffusion.Simultaneously,PO_(4)^(3-)reacts with the surface Li of material to form a Li_3PO_(4) coating,inducing lithium deficiency,thereby increasing Li/Ni mixing.The suitable Li/Ni mixing,previously overlooked in AlPO_(4) modification,plays a pivotal role in stabilizing the bulk and surface,exceeding the synergy of Al doping and Li_3PO_(4) coating.The presence of Ni^(2+)ions in the lithium layers contributes to the stabilization of the delithiated structure via a structural pillar effect.Moreover,suitable Li/Ni mixing can stabilize the lattice oxygen and electrode-electrolyte interface by increasing oxygen removal energy and reducing the overlap between the Ni^(3+/4+)e_g and O^(2-)2p orbitals.These findings offer new perspectives for the design of stable cobalt-free cathode materials.展开更多
Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For...Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.展开更多
The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an eff...The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.展开更多
The separator is an essential component of sodium-ion batteries(SIBs)to determine their electrochemical performances.However,the separator with high mechanical strength,good electrolyte wettability and excellent elect...The separator is an essential component of sodium-ion batteries(SIBs)to determine their electrochemical performances.However,the separator with high mechanical strength,good electrolyte wettability and excellent electrochemical performance remains an open challenge.Herein,a new separator consisting of amphoteric nanofibers with abundant functional groups was fabricated through supramolecular assembly of natural polymers for SIB.The uniform nanoporous structure,remarkable mechanical properties and abundant functional groups(e.g.-COOH,-NH_(2)and-OH)endow the separator with lower dissolution activation energy and higher ion migration numbers.These metrics enable the separator to lower the barrier for desolvation of Na^(+),accelerate the migration of Na^(+),and generate more stable solid electrolyte interphase(SEI)and cathode electrolyte interphase(CEI).The battery assembled with the amphoteric nanofiber separator shows higher specific capacity and better stability than that assembled with glass fiber(GF)separator.展开更多
Rapeseed(Brassica napus)is an oil crop grown worldwide,making it a key plant species in molecular breeding research.However,the complexity of its polyploid genome increases sequencing costs and reduces sequencing accu...Rapeseed(Brassica napus)is an oil crop grown worldwide,making it a key plant species in molecular breeding research.However,the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy.Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest.In this study,588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T.The platform comprised 54,765,with 54,058 resequenced markers from the pan-genome,and 855 variant trait-associated markers for 12 agronomic traits.The capture quality of BnaPan50T was demonstrated well in 12 typical accessions.Compared with a conventional genotyping array,BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes,promising wide application.Target capture sequencing and wholegenome resequencing in 90 doubled-haploid lines yielded 60%specificity,78%uniformity within tenfold coverage range,and 93%genotyping accuracy for the platform.BnaPan50T was used to construct a genetic map for quantitative trait loci(QTL)mapping,identify 21 unique QTL,and predict several candidate genes for yield-related traits in multiple environments.A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources.This study provides genomics resources to support target capture sequencing,genetic analysis and genomic breeding of rapeseed.展开更多
Blockchain technology has become a research hotspot in recent years with the prominent characteristics as public,distributed and decentration.And blockchain-enabled internet of things(BIoT)has a tendency to make a rev...Blockchain technology has become a research hotspot in recent years with the prominent characteristics as public,distributed and decentration.And blockchain-enabled internet of things(BIoT)has a tendency to make a revolutionary change for the internet of things(IoT)which requires distributed trustless consensus.However,the scalability and security issues become particularly important with the dramatically increasing number of IoT devices.Especially,with the development of quantum computing,many extant cryptographic algorithms applied in blockchain or BIoT systems are vulnerable to the quantum attacks.In this paper,an anti-quantum proxy blind signature scheme based on the lattice cryptography has been proposed,which can provide user anonymity and untraceability in the distributed applications of BIoT.Then,the security proof of the proposed scheme can derive that it is secure in random oracle model,and the efficiency analysis can indicate it is efficient than other similar literatures.展开更多
Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the ...Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the development of these applications,such as the issue with linearly growing storage capacity of blockchain systems.On the other hand,there is a lack of storage resources for sensor devices in IoT,and numerous sensor devices will generate massive data at ultra-high speed,which makes the storage problem of the IoT enabled by blockchain more prominent.There are various solutions to reduce the storage burden by modifying the blockchain’s storage policy,but most of them do not consider the willingness of peers.In attempt to make the blockchain more compatible with the IoT,this paper proposes a storage optimization scheme that revisits the system data storage problem from amore practically oriented standpoint.Peers will only store transactional data that they are directly involved in.In addition,a transaction verification model is developed to enable peers to undertake transaction verification with the aid of cloud computing,and an incentive mechanism is premised on the storage optimization scheme to assure data integrity.The results of the simulation experiments demonstrate the proposed scheme’s advantage in terms of storage and throughput.展开更多
OBJECTIVE： Bao-Xie-Ning （BXN）, a traditional Chinese herbal medicine （CHM） formula composed of Fructus Evodiae, Flos Caryophylli and Cortex Cinnamomi, and used for the treatment of infant diarrheal illness, was s...OBJECTIVE： Bao-Xie-Ning （BXN）, a traditional Chinese herbal medicine （CHM） formula composed of Fructus Evodiae, Flos Caryophylli and Cortex Cinnamomi, and used for the treatment of infant diarrheal illness, was subject to systematic assessment for its putative multiple pharmacodynamic effects and pharmacological antidiarrheal mechanisms. METHODS： High-performance liquid chromatography-diode array detector-electrospray ionization- mass spectrometric/mass spectrometry was developed and validated for identification and quantification of the main constituents in different extracts of BXN. Male Kunming mice weighing 20 to 25 g were used for detecting the antidiarrheal activity of the extracts. Ethanolic extract （EE）, volatile oil extract （VOE）, and aqueous extract （AE） of BXN were respectively subjected to pharmacodynamic and pharmacological comparison in assessing antidiarrheal effects with senna-induced diarrhea, castor oil-induced diarrhea, acetic acid-induced writhing assay, and isolated duodenum test. RESULTS： The highest yields of three detected components of BXN, rutaecarpine, eugenol and cinnamaldehyde were observed in EE. EE showed the most remarkable antidiarrheal activity in dose-dependent and time-dependent manners in both senna- and castor oil-induced diarrhea models, and presented dose-dependent analgesic activity in acetic acid-induced algesthesia model. In addition, EE extract of BXN also exhibited strong antimobility action on the intestine and strongest depression on spontaneous contraction of isolated duodenum. CONCLUSION： Ethanol extraction is an efficient method to extract the active constituents of BXN. BXN extract demonstrated multiple pharmacological activities affecting the main mechanisms of diarrhea, which validated BXN＇s usage in the comprehensive clinical treatment of diarrhea.展开更多
In this paper,we propose an asymmetric controlled bidirectional transmission protocol.In the protocol,by using the thirteen-qubit entangled state as the quantum channel,Alice can realize the transmission of a two-qubi...In this paper,we propose an asymmetric controlled bidirectional transmission protocol.In the protocol,by using the thirteen-qubit entangled state as the quantum channel,Alice can realize the transmission of a two-qubit equatorial state for Bob and Bob can transmit a four-qubit equatorial state for Alice under the control of Charlie.Firstly,we give the construction of the quantum channel,which can be done by performing several H and CNOT operations.Secondly,through implementing the appropriate measurements and the corresponding recovery operations,the desired states can be transmitted simultaneously,securely and deterministically.Finally,we analyze the performance of the protocol,including the efficiency,the necessary operations and the classical communication costs.And then,we describe some comparisons with other protocols.Since our protocol does not require auxiliary particles and additional operations,the classic communication costs less while achieving the multi-particle bidirectional transmission,so the overall performance of the protocol is better.展开更多
The state-of-the-art universal steganalysis method,spatial rich model(SRM),and the steganalysis method using image quality metrics(IQM)are both based on image residuals,while they use 34671 and 10 features respectivel...The state-of-the-art universal steganalysis method,spatial rich model(SRM),and the steganalysis method using image quality metrics(IQM)are both based on image residuals,while they use 34671 and 10 features respectively.This paper proposes a novel steganalysis scheme that combines their advantages in two ways.First,filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods.In addition,a total variant(TV)filter is also used due to its good performance of preserving image edge properties during filtering.Second,due to each type of these filters having own advantages,the multiple filters are used simultaneously and the features extracted from their outputs are combined together.The whole steganalysis procedure is removing steganographic noise using those filters,then measuring the distances between images and their filtered version with the image quality metrics,and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine.The scheme can work in two modes,the single filter mode using 9 features,and the multi-filter mode using 639 features.We compared the performance of the proposed method,the SRM and the maxSRMd2.The maxSRMd2 is the improved version of the SRM.The simulated results show that the proposed method that worked in the multi-filter mode was about 10%more accurate than the SRM and maxSRMd2 when the data were globally normalized,and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.展开更多
With the development of cloud computing technology,more and more data owners upload their local data to the public cloud server for storage and calculation.While this can save customers’operating costs,it also poses ...With the development of cloud computing technology,more and more data owners upload their local data to the public cloud server for storage and calculation.While this can save customers’operating costs,it also poses privacy and security challenges.Such challenges can be solved using secure multi-party computation(SMPC),but this still exposes more security issues.In cloud computing using SMPC,clients need to process their data and submit the processed data to the cloud server,which then performs the calculation and returns the results to each client.Each client and server must be honest.If there is cooperation or dishonest behavior between clients,some clients may profit from it or even disclose the private data of other clients.This paper proposes the SMPC based on a Partially-Homomorphic Encryption(PHE)scheme in which an addition homomorphic encryption algorithm with a lower computational cost is used to ensure data comparability and Zero-Knowledge Proof(ZKP)is used to limit the client’s malicious behavior.In addition,the introduction of Oblivious Transfer(OT)technology also ensures that the semi-honest cloud server knows nothing about private data,so that the cloud server of this scheme can calculate the correct data in the case of malicious participant models and safely return the calculation results to each client.Finally,the security analysis shows that the scheme not only ensures the privacy of participants,but also ensures the fairness of the comparison protocol data.展开更多
Two-dimensional covalent organic framework(COF)has distinctive properties that offer potential opportunities for developing advanced electrode materials.In this work,a core-shell material composed of TAPB-DMTP-COF(TAP...Two-dimensional covalent organic framework(COF)has distinctive properties that offer potential opportunities for developing advanced electrode materials.In this work,a core-shell material composed of TAPB-DMTP-COF(TAPB,1,3,5-tris(4-aminophenyl)benzene;DMTP,2,5-dimethoxyterephaldehyde)core and conducting polymer shell,TAPB-DMTP-COF@PANI,was synthesized solvothermally using a polymerization method.The structural cha racteristics of the prepared composite were revealed by X-ray diffraction patterns(XRD),fourier transform infrared spectra(FTIR),X-ray photoelectron spectroscopy(XPS),transmission electron microscopy(TEM).The electrochemical analyses were verified by subsequent monitoring of trace levels of acetaminophen.This resultant composite not only facilitated acetaminophen to interact with absorption sites byπ-πstacking effect and hydrogen bonding but also overcame the poor conductivity of COF.Under the optimal conditions,a low limit of detection of 0.032μmol/L and wide linear range of 0.10-500μmol/L were obtained.The electrochemical platform was almost unaffected by other interfering substances,and successfully applied for the practical detection of acetaminophen in commercial tablet,human blood serum and urine.The enhanced performance makes this COF based core-shell composite a promising material in electrochemical senso r.展开更多
Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitab...Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitably brings the issues with respect to data privacy and operating performance.In this paper,we proposed a novel blockchain scheme called Cipherchain,which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed.Specifically in our scheme,transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search(mPECK),and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger.By introducing execution-consensus-update paradigm of transaction flow,Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext,but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work.In addition,Cipherchain is a promising scheme to realize the technology combination of“blockchain+cloud computing”and“permissioned blockchain+public blockchain”.展开更多
Targeted muscle reinnervation has been proposed for reconstruction of neuromuscular function in amputees.However,it is unknown whether performing delayed targeted muscle reinnervation after nerve injury will affect re...Targeted muscle reinnervation has been proposed for reconstruction of neuromuscular function in amputees.However,it is unknown whether performing delayed targeted muscle reinnervation after nerve injury will affect restoration of function.In this rat nerve injury study,the median and musculocutaneous nerves of the forelimb were transected.The proximal median nerve stump was sutured to the distal musculocutaneous nerve stump immediately and 2 and 4 weeks after surgery to reinnervate the biceps brachii.After targeted muscle reinnervation,intramuscular myoelectric signals from the biceps brachii were recorded.Signal amplitude gradually increased with time.Biceps brachii myoelectric signals and muscle fiber morphology and grooming behavior did not significantly differ among rats subjected to delayed target muscle innervation for different periods.Targeted muscle reinnervation delayed for 4 weeks can acquire the same nerve function restoration effect as that of immediate reinnervation.展开更多
Herein,Pd nanoparticles loaded Co_(3)O_(4)catalysts(Pd@Co_(3)O_(4))are constructed from zeolitic imidazolate framework-67(ZIF-67)for the ethanol oxidation reaction(EOR).It is demonstrated for the first time that the e...Herein,Pd nanoparticles loaded Co_(3)O_(4)catalysts(Pd@Co_(3)O_(4))are constructed from zeolitic imidazolate framework-67(ZIF-67)for the ethanol oxidation reaction(EOR).It is demonstrated for the first time that the electrochemical conversion of Co_(3)O_(4)support would result in the charge distribution alignment at the Pd/Co_(3)O_(4)interface and induce the formation of highly reactive Pd-O species(PdO^(*)),which can further catalyze the consequent reactions of the intermediates of the ethanol oxidation.The catalyst,Pd@Co_(3)O_(4)-450,obtained under the optimized conditions exhibits excellent EOR performance with a high mass activity of 590 mA mg-1,prominent operational stability,and extraordinary capability for the electro-oxidation of acetaldehyde intermediates.Importantly,the detailed mechanism investigation reveals that Pd@Co_(3)O_(4)-450 could be benefit to the C-C bond cleavage to promote the desirable C1 pathway for the ethanol oxidation reaction.The present strategy based on the metal-support interaction of the catalyst might provide valuable inspiration for the design of high-performing catalysts for the ethanol oxidation reaction.展开更多
Cisplatin is broad-spectrum chemotherapeutic agent that has been widely used for the treatment of a variety of malignant tumors including breast cancer.However,the cisplatin chemoresistance,which derives from the inac...Cisplatin is broad-spectrum chemotherapeutic agent that has been widely used for the treatment of a variety of malignant tumors including breast cancer.However,the cisplatin chemoresistance,which derives from the inactivation by glutathione(GSH)depletion,remains a scientific issue to solve.Here,we report a novel type of smart disulfide switchable nanoparticles complexing cisplatin(switch NPs-cisplatin)that is rationally designed,and engineered by synthesizing a hyaluronic acid disulfide bonded polyaspartic acid(HA-ss-Pasp)and complexing cisplatin.The results showed that the switch NPs-cisplatin had a nanoscale of particle size(150 nm),higher drug encapsulation efficiency(>90%),and suitable drug release profile.They demonstrated evident pH responsiveness and GSH responsiveness,and targeting effect in the resistant breast cancer cells.Furthermore,they were able to block the cisplatin depletion by GSH in the resistant cancer cells,thereby circumventing the chemoresistance.Consequently,switch NPs-cisplatin displayed a remarkable killing effect in the resistant breast cancer cells in vitro,and in the resistant breast cancer-bearing mice.In conclusion,switch NPs-cisplatin could be used as a smart formulation of cisplatin for overcoming the chemoresistance of breast cancer.The present study also offers a universal drug delivery carrier platform for highly efficient but low systemic toxic chemotherapy.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1300203)the National Natural Science Foundation of China(Grant No.42371329s).
文摘Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.
基金supported by the Key Project of Joint Fund of the National Natural Science Foundation of China“Research on Key Technologies and Demonstration Applications for Trusted and Secure Data Circulation and Trading”(U24A20241)the National Natural Science Foundation of China“Research on Trusted Theories and Key Technologies of Data Security Trading Based on Blockchain”(62202118)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province([2024]014)Scientific and Technological Research Projects from the Guizhou Education Department(Qian jiao ji[2023]003)the Hundred-Level Innovative Talent Project of the Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)the Major Project of Guizhou Province“Research and Application of Key Technologies for Trusted Large Models Oriented to Public Big Data”(Qiankehe Major Project[2024]003)the Guizhou Province Computational Power Network Security Protection Science and Technology Innovation Talent Team(Qiankehe Talent CXTD[2025]029).
文摘As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.
基金supported in part by the National Natural Science Foundation(62202118,U24A20241)in part by Major Scientific and Technological Special Project of Guizhou Province([2024]014,[2024]003)+1 种基金in part by Scientific and Technological Research Projects from Guizhou Education Department(Qian jiao ji[2023]003)in part by Guizhou Science and Technology Department Hundred Level Innovative Talents Project(GCC[2023]018).
文摘Deep neural networks remain susceptible to adversarial examples,where the goal of an adversarial attack is to introduce small perturbations to the original examples in order to confuse the model without being easily detected.Although many adversarial attack methods produce adversarial examples that have achieved great results in the whitebox setting,they exhibit low transferability in the black-box setting.In order to improve the transferability along the baseline of the gradient-based attack technique,we present a novel Stochastic Gradient Accumulation Momentum Iterative Attack(SAMI-FGSM)in this study.In particular,during each iteration,the gradient information is calculated using a normal sampling approach that randomly samples around the sample points,with the highest probability of capturing adversarial features.Meanwhile,the accumulated information of the sampled gradient from the previous iteration is further considered to modify the current updated gradient,and the original gradient attack direction is changed to ensure that the updated gradient direction is more stable.Comprehensive experiments conducted on the ImageNet dataset show that our method outperforms existing state-of-the-art gradient-based attack techniques,achieving an average improvement of 10.2%in transferability.
基金supported by the National Natural Science Foundation(62202118)Guizhou Province Major Project(Qiankehe Major Project[2024]014)+3 种基金Science and Scientific and Technological Research Projects from Guizhou Education Department(Qianiao ji[2023]003)Hundred-level Innovative Talent Project of Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)Guizhou Province Major Project(Qiankehe Major Project[2024]003)Foundation of Chongqing Key Laboratory of Public Big Data Security Technology(CQKL-QJ202300001).
文摘Anomaly detection(AD)in time series data is widely applied across various industries for monitoring and security applications,emerging as a key research focus within the field of deep learning.While many methods based on different normality assumptions performwell in specific scenarios,they often neglected the overall normality issue.Some feature extraction methods incorporate pre-training processes but they may not be suitable for time series anomaly detection,leading to decreased performance.Additionally,real-world time series samples are rarely free from noise,making them susceptible to outliers,which further impacts detection accuracy.To address these challenges,we propose a novel anomaly detection method called Robust One-Class Classification Detection(ROC).This approach utilizes an autoencoder(AE)to learn features while constraining the context vectors fromthe AE within a sufficiently small hypersphere,akin to One-Class Classification(OC)methods.By simultaneously optimizing two hypothetical objective functions,ROC captures various aspects of normality.We categorize the input raw time series into clean and outlier sequences,reducing the impact of outliers on compressed feature representation.Experimental results on public datasets indicate that our approach outperforms existing baselinemethods and substantially improves model robustness.
基金financial support from the Natural Science Foundation of Shandong Province (ZR2022QB140)the PhD Initiation Program of Liaocheng University (318052138)the Natural Science Foundation of Shandong Province (ZR2023MB002 and ZR2021MB114)。
文摘Cobalt-free cathode materials are attractive for their high capacity and low cost,yet they still encounter issues with structural and surface instability.AlPO_(4),in particular,has garnered attention as an effective stabilizer for bulk and surface.However,the impact of interfacial reactions and elemental interdiffusion between AlPO_(4) and LiNi_(0.95)Mn_(0.05)O_(2) upon sintering on the bulk and surface remains elusive.In this study,we demonstrate that during the heat treatment process,AlPO_(4) decomposes,resulting in Al doping into the bulk of the cathode through elemental interdiffusion.Simultaneously,PO_(4)^(3-)reacts with the surface Li of material to form a Li_3PO_(4) coating,inducing lithium deficiency,thereby increasing Li/Ni mixing.The suitable Li/Ni mixing,previously overlooked in AlPO_(4) modification,plays a pivotal role in stabilizing the bulk and surface,exceeding the synergy of Al doping and Li_3PO_(4) coating.The presence of Ni^(2+)ions in the lithium layers contributes to the stabilization of the delithiated structure via a structural pillar effect.Moreover,suitable Li/Ni mixing can stabilize the lattice oxygen and electrode-electrolyte interface by increasing oxygen removal energy and reducing the overlap between the Ni^(3+/4+)e_g and O^(2-)2p orbitals.These findings offer new perspectives for the design of stable cobalt-free cathode materials.
基金supported by the Natural Science Foundation under Grant No.61962009Major Scientific and Technological Special Project of Guizhou Province under Grant No.20183001Foundation of Guizhou Provincial Key Laboratory of Public Big Data under Grant No.2018BDKFJJ003,2018BDKFJJ005 and 2019BDKFJJ009.
文摘Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.
基金Foundation of National Natural Science Foundation of China(62202118)Scientific and Technological Research Projects from Guizhou Education Department([2023]003)+1 种基金Guizhou Provincial Department of Science and Technology Hundred Levels of Innovative Talents Project(GCC[2023]018)Top Technology Talent Project from Guizhou Education Department([2022]073).
文摘The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.
基金supported by the Outstanding Youth Team Project of Guangdong Natural Science Foundation(2023B1515040013)Guangdong Basic and Applied Basic Research Foundation(2023A1515012215,2023B1515040013,2023A1515012519)+1 种基金State Key Laboratory of Pulp&Paper Engineering(2023C07,2023PY03)Guangdong Col ege Students’Scientific and Technological Innovation(“Climbing Program”Special Fund,Pdjh2022a0026)
文摘The separator is an essential component of sodium-ion batteries(SIBs)to determine their electrochemical performances.However,the separator with high mechanical strength,good electrolyte wettability and excellent electrochemical performance remains an open challenge.Herein,a new separator consisting of amphoteric nanofibers with abundant functional groups was fabricated through supramolecular assembly of natural polymers for SIB.The uniform nanoporous structure,remarkable mechanical properties and abundant functional groups(e.g.-COOH,-NH_(2)and-OH)endow the separator with lower dissolution activation energy and higher ion migration numbers.These metrics enable the separator to lower the barrier for desolvation of Na^(+),accelerate the migration of Na^(+),and generate more stable solid electrolyte interphase(SEI)and cathode electrolyte interphase(CEI).The battery assembled with the amphoteric nanofiber separator shows higher specific capacity and better stability than that assembled with glass fiber(GF)separator.
基金supported by the National Natural Science Foundation of China(31871653 to K.L.,31830067 to J.L.)the Talent Project of Chongqing Natural Science Foundation(cstc2021ycjhbgzxm0033 to K.L.)Germplasm Creation Special Program of Southwest University.
文摘Rapeseed(Brassica napus)is an oil crop grown worldwide,making it a key plant species in molecular breeding research.However,the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy.Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest.In this study,588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T.The platform comprised 54,765,with 54,058 resequenced markers from the pan-genome,and 855 variant trait-associated markers for 12 agronomic traits.The capture quality of BnaPan50T was demonstrated well in 12 typical accessions.Compared with a conventional genotyping array,BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes,promising wide application.Target capture sequencing and wholegenome resequencing in 90 doubled-haploid lines yielded 60%specificity,78%uniformity within tenfold coverage range,and 93%genotyping accuracy for the platform.BnaPan50T was used to construct a genetic map for quantitative trait loci(QTL)mapping,identify 21 unique QTL,and predict several candidate genes for yield-related traits in multiple environments.A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources.This study provides genomics resources to support target capture sequencing,genetic analysis and genomic breeding of rapeseed.
文摘Blockchain technology has become a research hotspot in recent years with the prominent characteristics as public,distributed and decentration.And blockchain-enabled internet of things(BIoT)has a tendency to make a revolutionary change for the internet of things(IoT)which requires distributed trustless consensus.However,the scalability and security issues become particularly important with the dramatically increasing number of IoT devices.Especially,with the development of quantum computing,many extant cryptographic algorithms applied in blockchain or BIoT systems are vulnerable to the quantum attacks.In this paper,an anti-quantum proxy blind signature scheme based on the lattice cryptography has been proposed,which can provide user anonymity and untraceability in the distributed applications of BIoT.Then,the security proof of the proposed scheme can derive that it is secure in random oracle model,and the efficiency analysis can indicate it is efficient than other similar literatures.
基金We would also thank the support from the National Natural Science Foundation of China(Nos.62172182,62202118,61962009)the Top Technology Talent Project from Guizhou Education Department(Qian jiao ji[2022]073)The Opening Foundation of Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province(Grant No.ZNKZN2021-07).
文摘Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the development of these applications,such as the issue with linearly growing storage capacity of blockchain systems.On the other hand,there is a lack of storage resources for sensor devices in IoT,and numerous sensor devices will generate massive data at ultra-high speed,which makes the storage problem of the IoT enabled by blockchain more prominent.There are various solutions to reduce the storage burden by modifying the blockchain’s storage policy,but most of them do not consider the willingness of peers.In attempt to make the blockchain more compatible with the IoT,this paper proposes a storage optimization scheme that revisits the system data storage problem from amore practically oriented standpoint.Peers will only store transactional data that they are directly involved in.In addition,a transaction verification model is developed to enable peers to undertake transaction verification with the aid of cloud computing,and an incentive mechanism is premised on the storage optimization scheme to assure data integrity.The results of the simulation experiments demonstrate the proposed scheme’s advantage in terms of storage and throughput.
基金supported and funded by the State Administration of Traditional Chinese Medicine of China (No.2003LHR20)
文摘OBJECTIVE： Bao-Xie-Ning （BXN）, a traditional Chinese herbal medicine （CHM） formula composed of Fructus Evodiae, Flos Caryophylli and Cortex Cinnamomi, and used for the treatment of infant diarrheal illness, was subject to systematic assessment for its putative multiple pharmacodynamic effects and pharmacological antidiarrheal mechanisms. METHODS： High-performance liquid chromatography-diode array detector-electrospray ionization- mass spectrometric/mass spectrometry was developed and validated for identification and quantification of the main constituents in different extracts of BXN. Male Kunming mice weighing 20 to 25 g were used for detecting the antidiarrheal activity of the extracts. Ethanolic extract （EE）, volatile oil extract （VOE）, and aqueous extract （AE） of BXN were respectively subjected to pharmacodynamic and pharmacological comparison in assessing antidiarrheal effects with senna-induced diarrhea, castor oil-induced diarrhea, acetic acid-induced writhing assay, and isolated duodenum test. RESULTS： The highest yields of three detected components of BXN, rutaecarpine, eugenol and cinnamaldehyde were observed in EE. EE showed the most remarkable antidiarrheal activity in dose-dependent and time-dependent manners in both senna- and castor oil-induced diarrhea models, and presented dose-dependent analgesic activity in acetic acid-induced algesthesia model. In addition, EE extract of BXN also exhibited strong antimobility action on the intestine and strongest depression on spontaneous contraction of isolated duodenum. CONCLUSION： Ethanol extraction is an efficient method to extract the active constituents of BXN. BXN extract demonstrated multiple pharmacological activities affecting the main mechanisms of diarrhea, which validated BXN＇s usage in the comprehensive clinical treatment of diarrhea.
基金Project supported by NSFC(Grant Nos.U1836205,61702040)the Major Scientific and Technological Special Project of Guizhou Province(Grant No.20183001)+2 种基金the Foundation of Guizhou Provincial Key Laboratory of Public Big Data(Grant No.2018BDKFJJ016)the Foundation of State Key Laboratory of Public Big Data(Grant No.2018BDKFJJ018)Beijing Natural Science Foundation(Grant No.4174089).
文摘In this paper,we propose an asymmetric controlled bidirectional transmission protocol.In the protocol,by using the thirteen-qubit entangled state as the quantum channel,Alice can realize the transmission of a two-qubit equatorial state for Bob and Bob can transmit a four-qubit equatorial state for Alice under the control of Charlie.Firstly,we give the construction of the quantum channel,which can be done by performing several H and CNOT operations.Secondly,through implementing the appropriate measurements and the corresponding recovery operations,the desired states can be transmitted simultaneously,securely and deterministically.Finally,we analyze the performance of the protocol,including the efficiency,the necessary operations and the classical communication costs.And then,we describe some comparisons with other protocols.Since our protocol does not require auxiliary particles and additional operations,the classic communication costs less while achieving the multi-particle bidirectional transmission,so the overall performance of the protocol is better.
基金This research was supported by National Natural Science Foundation of China(Grant Nos.41661144039,91337102,41401481)and Natural Science Foundation of Jiangsu Province of China(Grant No.BK20140997).
文摘The state-of-the-art universal steganalysis method,spatial rich model(SRM),and the steganalysis method using image quality metrics(IQM)are both based on image residuals,while they use 34671 and 10 features respectively.This paper proposes a novel steganalysis scheme that combines their advantages in two ways.First,filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods.In addition,a total variant(TV)filter is also used due to its good performance of preserving image edge properties during filtering.Second,due to each type of these filters having own advantages,the multiple filters are used simultaneously and the features extracted from their outputs are combined together.The whole steganalysis procedure is removing steganographic noise using those filters,then measuring the distances between images and their filtered version with the image quality metrics,and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine.The scheme can work in two modes,the single filter mode using 9 features,and the multi-filter mode using 639 features.We compared the performance of the proposed method,the SRM and the maxSRMd2.The maxSRMd2 is the improved version of the SRM.The simulated results show that the proposed method that worked in the multi-filter mode was about 10%more accurate than the SRM and maxSRMd2 when the data were globally normalized,and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.
基金supported by the National Natural Science Foundation of China under Grant No.(62202118.61962009)And in part by Natural Science Foundation of Shandong Province(ZR2021MF086)+1 种基金And in part by Top Technology Talent Project from Guizhou Education Department(Qian jiao ji[2022]073)And in part by Foundation of Guangxi Key Laboratory of Cryptography and Information Security(GCIS202118).
文摘With the development of cloud computing technology,more and more data owners upload their local data to the public cloud server for storage and calculation.While this can save customers’operating costs,it also poses privacy and security challenges.Such challenges can be solved using secure multi-party computation(SMPC),but this still exposes more security issues.In cloud computing using SMPC,clients need to process their data and submit the processed data to the cloud server,which then performs the calculation and returns the results to each client.Each client and server must be honest.If there is cooperation or dishonest behavior between clients,some clients may profit from it or even disclose the private data of other clients.This paper proposes the SMPC based on a Partially-Homomorphic Encryption(PHE)scheme in which an addition homomorphic encryption algorithm with a lower computational cost is used to ensure data comparability and Zero-Knowledge Proof(ZKP)is used to limit the client’s malicious behavior.In addition,the introduction of Oblivious Transfer(OT)technology also ensures that the semi-honest cloud server knows nothing about private data,so that the cloud server of this scheme can calculate the correct data in the case of malicious participant models and safely return the calculation results to each client.Finally,the security analysis shows that the scheme not only ensures the privacy of participants,but also ensures the fairness of the comparison protocol data.
基金supported by the National Natural Science Foundation of China(No.21205103)Jiangsu Provincial Natural Science Foundation(No.BK2012258)+2 种基金Young and Middle-aged Academic Leaders Foundation of Yangzhou UniversityTop-notch Academic Programs Project of Jiangsu Higher Education Institutions(TAPP)funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘Two-dimensional covalent organic framework(COF)has distinctive properties that offer potential opportunities for developing advanced electrode materials.In this work,a core-shell material composed of TAPB-DMTP-COF(TAPB,1,3,5-tris(4-aminophenyl)benzene;DMTP,2,5-dimethoxyterephaldehyde)core and conducting polymer shell,TAPB-DMTP-COF@PANI,was synthesized solvothermally using a polymerization method.The structural cha racteristics of the prepared composite were revealed by X-ray diffraction patterns(XRD),fourier transform infrared spectra(FTIR),X-ray photoelectron spectroscopy(XPS),transmission electron microscopy(TEM).The electrochemical analyses were verified by subsequent monitoring of trace levels of acetaminophen.This resultant composite not only facilitated acetaminophen to interact with absorption sites byπ-πstacking effect and hydrogen bonding but also overcame the poor conductivity of COF.Under the optimal conditions,a low limit of detection of 0.032μmol/L and wide linear range of 0.10-500μmol/L were obtained.The electrochemical platform was almost unaffected by other interfering substances,and successfully applied for the practical detection of acetaminophen in commercial tablet,human blood serum and urine.The enhanced performance makes this COF based core-shell composite a promising material in electrochemical senso r.
基金This work is supported by the NSFC(Grant Nos.61671087,61962009,61003287)the Fok Ying Tong Education Foundation(Grant No.131067)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province(Grant No.20183001)the Foundation of State Key Laboratory of Public Big Data(Grant No.2018BDKFJJ018)CCF-Tencent Open Fund WeBank Special Funding(CCF-WebankRAGR20180104)the High-quality and Cutting-edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China)the Fundamental Research Funds for the Central Universities,and the Fundamental Research Funds for the Central Universities No.2019XD-A02.
文摘Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitably brings the issues with respect to data privacy and operating performance.In this paper,we proposed a novel blockchain scheme called Cipherchain,which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed.Specifically in our scheme,transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search(mPECK),and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger.By introducing execution-consensus-update paradigm of transaction flow,Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext,but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work.In addition,Cipherchain is a promising scheme to realize the technology combination of“blockchain+cloud computing”and“permissioned blockchain+public blockchain”.
基金supported in part by the National Natural Science Foundation of China,Nos.U1913601,81927804the Key-Area Research and Development Program of Guangdong Province,No.2020B0909020004(GL)the National Natural Science Foundation of China,Nos.81960419,82260456(both to LY)。
文摘Targeted muscle reinnervation has been proposed for reconstruction of neuromuscular function in amputees.However,it is unknown whether performing delayed targeted muscle reinnervation after nerve injury will affect restoration of function.In this rat nerve injury study,the median and musculocutaneous nerves of the forelimb were transected.The proximal median nerve stump was sutured to the distal musculocutaneous nerve stump immediately and 2 and 4 weeks after surgery to reinnervate the biceps brachii.After targeted muscle reinnervation,intramuscular myoelectric signals from the biceps brachii were recorded.Signal amplitude gradually increased with time.Biceps brachii myoelectric signals and muscle fiber morphology and grooming behavior did not significantly differ among rats subjected to delayed target muscle innervation for different periods.Targeted muscle reinnervation delayed for 4 weeks can acquire the same nerve function restoration effect as that of immediate reinnervation.
基金supported by the National Natural Science Foundation of China(21336005)the Ministry of Science and Technology of China(2014EG111224)+1 种基金the National Key R&D Program of China(2021YFB4001200)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX22_3185)。
文摘Herein,Pd nanoparticles loaded Co_(3)O_(4)catalysts(Pd@Co_(3)O_(4))are constructed from zeolitic imidazolate framework-67(ZIF-67)for the ethanol oxidation reaction(EOR).It is demonstrated for the first time that the electrochemical conversion of Co_(3)O_(4)support would result in the charge distribution alignment at the Pd/Co_(3)O_(4)interface and induce the formation of highly reactive Pd-O species(PdO^(*)),which can further catalyze the consequent reactions of the intermediates of the ethanol oxidation.The catalyst,Pd@Co_(3)O_(4)-450,obtained under the optimized conditions exhibits excellent EOR performance with a high mass activity of 590 mA mg-1,prominent operational stability,and extraordinary capability for the electro-oxidation of acetaldehyde intermediates.Importantly,the detailed mechanism investigation reveals that Pd@Co_(3)O_(4)-450 could be benefit to the C-C bond cleavage to promote the desirable C1 pathway for the ethanol oxidation reaction.The present strategy based on the metal-support interaction of the catalyst might provide valuable inspiration for the design of high-performing catalysts for the ethanol oxidation reaction.
基金supported by the National Natural Science Foundation of China(Nos.81874303,82173752)。
文摘Cisplatin is broad-spectrum chemotherapeutic agent that has been widely used for the treatment of a variety of malignant tumors including breast cancer.However,the cisplatin chemoresistance,which derives from the inactivation by glutathione(GSH)depletion,remains a scientific issue to solve.Here,we report a novel type of smart disulfide switchable nanoparticles complexing cisplatin(switch NPs-cisplatin)that is rationally designed,and engineered by synthesizing a hyaluronic acid disulfide bonded polyaspartic acid(HA-ss-Pasp)and complexing cisplatin.The results showed that the switch NPs-cisplatin had a nanoscale of particle size(150 nm),higher drug encapsulation efficiency(>90%),and suitable drug release profile.They demonstrated evident pH responsiveness and GSH responsiveness,and targeting effect in the resistant breast cancer cells.Furthermore,they were able to block the cisplatin depletion by GSH in the resistant cancer cells,thereby circumventing the chemoresistance.Consequently,switch NPs-cisplatin displayed a remarkable killing effect in the resistant breast cancer cells in vitro,and in the resistant breast cancer-bearing mice.In conclusion,switch NPs-cisplatin could be used as a smart formulation of cisplatin for overcoming the chemoresistance of breast cancer.The present study also offers a universal drug delivery carrier platform for highly efficient but low systemic toxic chemotherapy.
