Background:This study aimed to review treatments and evaluate the aesthetic outcomes,complications,and reoperation rates regarding surgical correction for a postoperative contracted nose.Methods:PubMed,MEDLINE,and Emb...Background:This study aimed to review treatments and evaluate the aesthetic outcomes,complications,and reoperation rates regarding surgical correction for a postoperative contracted nose.Methods:PubMed,MEDLINE,and Embase databases were searched for studies detailing aesthetic outcomes and complications of surgical correction of a contracted nose.Surgical procedures,adjuvant treatment,outcomes,and complications were synthesized and analyzed.Results:Nine articles encompassing 376 patients were included in the systematic review,and six articles(198 participants)were included in the meta-analysis.The most frequently used graft material was the autologous rib cartilage(61.1%).Surgical procedures were heterogeneous in these studies.The nasolabial angle reduced by 9.52°(95%confidence interval(CI):(-11.95,-7.09),P<0.0001),and the nasal length increased significantly(standardized mean difference(SMD)=2.25,95%CI:(1.26,2.23),P<0.00001).However,the evidence was insufficient to determine a significant change in the columellar-labial angle(SMD=-0.95,95%CI:(-2.19,0.29),P=0.13)and columellar-lobular angle(SMD=2.39,95%CI:(-1.20,5.97),P=0.19).Aesthetic dissatisfaction(12.5%)and infection(4.5%)were the most commonly reported complications.Reoperation was performed in 5.3%of patients.Conclusion:Surgical correction can increase the nasal length,reduce the nasolabial angle,and have a low reoperation rate.No significant improvement in the columellar-labial or columellar-lobular angle was observed.展开更多
Background:Scar contractions caused by trauma or burns can cause secondary physical dysfunction and disfigurement.Many minimally invasive methods for scar contraction have shown limited applicability and efficacy.This...Background:Scar contractions caused by trauma or burns can cause secondary physical dysfunction and disfigurement.Many minimally invasive methods for scar contraction have shown limited applicability and efficacy.This study investigated the feasibility and efficacy of intralesional collagenase injections for scar contraction treatment.Methods:Patients with contracted scars who had limited joint movement and physical disfiguration for>1 year were enrolled in this single-blind,randomized clinical trial from July 2017 to February 2018 at Shanghai Ninth People’s Hospital.Collagenase was injected into the firm-contracted scar(15 U/cm^(2))three times at 4-week intervals in the multiple treatment group and once in the single treatment group,and a placebo injection was performed in the control group.Scar length and skin texture were documented at the 4-and 12-week follow-ups.The safety of the collagenase treatment was also evaluated.Results:The contracted scar was significantly elongated after both single and multiple collagenase treatments.The results showed that,compared to a one-time treatment,repeated injections were more effective at 12 weeks,with an average improvement of 26.83(15.79%).At 12 weeks,78.9% of the patients in the multiple group and 52.9%in the single group achieved significant improvement at 12 weeks.No severe adverse events were observed.Conclusion:Intralesional collagenase injection showed promising results in improving scar contraction and provides an alternative treatment for patients.展开更多
The purpose of this case series is to report the indications for dermis-fat grafting and the outcome of treatment in orbital soft tissue contraction among patients in a tertiary center. It is a retrospective, consecut...The purpose of this case series is to report the indications for dermis-fat grafting and the outcome of treatment in orbital soft tissue contraction among patients in a tertiary center. It is a retrospective, consecutive, interventional case series where all patients with orbital soft tissue contraction who had dermis-fat grafting were studied. All nine patients in our series underwent secondary dermis-fat grafting for orbital soft tissue reconstruction. The major cause for contracted socket was surgical eye removal following trauma. Eight of nine patients had no orbital implants inserted at the time of primary eye removal and eight patients have had failed orbital reconstructive procedures. Satisfactory cosmetic results were reported in all patients post-operatively. Dermis-fat grafting for contracted socket reconstruction was found to give satisfactory cosmetic results in our studied population.展开更多
A contracted nose deformity is a challenging and distinct complication of rhinoplasty,particularly prevalent among Asian patients due to implant-related complications and infection-induced scar formation.Clinical pres...A contracted nose deformity is a challenging and distinct complication of rhinoplasty,particularly prevalent among Asian patients due to implant-related complications and infection-induced scar formation.Clinical presentations range from mild nasal tip upturning to severe distortion of nasal structures.This review outlines comprehensive surgical strategies for managing the contracted Asian nose,including wide release of the skin-soft tissue envelope,structural framework reconstruction with autologous rib cartilage,nasal tip elongation,and skin redraping techniques.Special considerations such as platelet-rich plasma,nanofat injection,and hyperbaric oxygen therapy are also discussed.Successful outcomes require meticulous planning,surgical expertise,and realistic patient expectations.展开更多
A new contracted CI scheme—adjustable contracted CI scheme—is presented and programed. The efficiency of this scheme is tested by some example calculations. The result shows that the application of the new scheme is...A new contracted CI scheme—adjustable contracted CI scheme—is presented and programed. The efficiency of this scheme is tested by some example calculations. The result shows that the application of the new scheme is flexible and the correlation energy loss is lower than that of the original externally contracted CI method. Keywords: configuration interaction, contracted CI method, correlation energy.展开更多
Based on the hole-particle correspondence an approximate so-called doubly contracted CI scheme is proposed. Examples calculated based on the doubly contracted CI (DCCI) scheme show that the number of configurations af...Based on the hole-particle correspondence an approximate so-called doubly contracted CI scheme is proposed. Examples calculated based on the doubly contracted CI (DCCI) scheme show that the number of configurations after contraction is reduced by three orders of magnitude, and the computation time is reduced by an order of magnitude. The examples also show that compared with experiments the DCCI and uncontracted CI have similar and reasonable accuracy to some spectroscopic parameters.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.展开更多
The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Tradit...The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Traditional intrusion detection systems have limitations in terms of centralized architecture,lack of transparency,and vulnerability to single points of failure.This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems.This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signaturebased intrusion detection system.The introduced signature facilitates accurate detection and systematic classification of attacks,enabling categorization according to their severity levels within the transportation infrastructure.Through comparative analysis,the research demonstrates that the blockchain-based IDS outperforms traditional approaches in terms of security,resilience,and data integrity.展开更多
We thank Power et al.1 for their interest in our review2 and for contributing to this important scientific discussion.We welcome their commentary and acknowledge the merit of continuing to scrutinize and refine interp...We thank Power et al.1 for their interest in our review2 and for contributing to this important scientific discussion.We welcome their commentary and acknowledge the merit of continuing to scrutinize and refine interpretations in this evolving field.Given that much research time and financial investment is being given to the study of the effects of eccentric training in both athletic and clinical contexts,it is incumbent on our field to demonstrate whether eccentric contractions are a key(or the key)stimulus for sarcomerogenesis(increases in serial sarcomere number(SSN)).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
Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequ...Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequently,the academic community has devoted increasing attention to these security risks.However,conventional approaches to vulnerability detection frequently exhibit limited accuracy.To address this limitation,the present study introduces a novel vulnerability detection framework called GNNSE that integrates symbolic execution with graph neural networks(GNNs).The proposedmethod first constructs semantic graphs to comprehensively capture the control flow and data flow dependencies within smart contracts.These graphs are subsequently processed using GNNs to efficiently identify contracts with a high likelihood of vulnerabilities.For these high-risk contracts,symbolic execution is employed to perform fine-grained,path-level analysis,thereby improving overall detection precision.Experimental results on a dataset comprising 10,079 contracts demonstrate that the proposed method achieves detection precisions of 93.58% for reentrancy vulnerabilities and 92.73% for timestamp-dependent vulnerabilities.展开更多
Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work pr...Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.展开更多
The creator economy is revolutionizing the way in which individuals can profit from their engagement with online platforms.In this paper,we initiate the formal study of online learning in a creator economy by modeling...The creator economy is revolutionizing the way in which individuals can profit from their engagement with online platforms.In this paper,we initiate the formal study of online learning in a creator economy by modeling it as a three-party game between users,a platform,and content creators.The platform interacts with creators through contracts under a principal-agent framework and with users via a recommender system.We study how the platform can jointly optimize contracts and recommendation policies in an online learning setting.We analyze return-based and feature-based contracts.Under smoothness assumptions,return-based contracts achieve regretΘ(T^(2/3)).For feature-based contracts,we introduce an intrinsic dimension d and prove a regret bound O(T^(d+1)/(d+2)),which is tight for linear families.展开更多
Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their...Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their effectiveness,most GNN-based vulnerability detectors operate as black boxes,making their decisions difficult to interpret and thus less suitable for critical security auditing.The information bottleneck(IB)principle provides a theoretical framework for isolating task-relevant graph components.However,existing IB-based implementations often encounter unstable optimization and limited understanding of code semantics.To address these issues,we introduce ContractGIB,an interpretable graph information bottleneck framework for function-level vulnerability analysis.ContractGIB introduces three main advances.First,ContractGIB introduces an Hilbert–Schmidt Independence Criterion(HSIC)based estimator that provides stable dependence measurement.Second,it incorporates a CodeBERT semantic module to improve node representations.Third,it initializes all nodes with pretrained CodeBERT embeddings,removing the need for hand-crafted features.For each contract function,ContractGIB identifies themost informative nodes forming an instance-specific explanatory subgraph that supports the model’s prediction.Comprehensive experiments on public smart contract datasets,including ESC andVSC,demonstrate thatContractGIB achieves superior performance compared to competitive GNN baselines,while offering clearer,instance-level interpretability.展开更多
Air Liquide China announced on July 28thit has just signed a long-term contract withNanjing CEC Panda LCD Technology Corporationfor its new 6-generation Flat PanelDisplay (FPD) fab in the new Nanjing CrystalValley,Jia...Air Liquide China announced on July 28thit has just signed a long-term contract withNanjing CEC Panda LCD Technology Corporationfor its new 6-generation Flat PanelDisplay (FPD) fab in the new Nanjing CrystalValley,Jiangsu province.This fab willbe one of the most advanced 6-generationFPD fabs in China,with a total展开更多
A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV s...A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.展开更多
With the urgent need to resolve complex behaviors in nonlinear evolution equations,this study makes a contribution by establishing the local existence of solutions for Cauchy problems associated with equations of mixe...With the urgent need to resolve complex behaviors in nonlinear evolution equations,this study makes a contribution by establishing the local existence of solutions for Cauchy problems associated with equations of mixed types.Our primary contribution is the establishment of solution existence,illuminating the dynamics of these complex equations.To tackle this challenging problem,we construct an approximate solution sequence and apply the contraction mapping principle to rigorously prove local solution existence.Our results significantly advance the understanding of nonlinear evolution equations of mixed types.Furthermore,they provide a versatile,powerful approach for tackling analogous challenges across physics,engineering,and applied mathematics,making this work a valuable reference for researchers in these fields.展开更多
基金supported by the Key Clinical Projects of Peking University Third Hospital(grant no.BYSYZD2019013)。
文摘Background:This study aimed to review treatments and evaluate the aesthetic outcomes,complications,and reoperation rates regarding surgical correction for a postoperative contracted nose.Methods:PubMed,MEDLINE,and Embase databases were searched for studies detailing aesthetic outcomes and complications of surgical correction of a contracted nose.Surgical procedures,adjuvant treatment,outcomes,and complications were synthesized and analyzed.Results:Nine articles encompassing 376 patients were included in the systematic review,and six articles(198 participants)were included in the meta-analysis.The most frequently used graft material was the autologous rib cartilage(61.1%).Surgical procedures were heterogeneous in these studies.The nasolabial angle reduced by 9.52°(95%confidence interval(CI):(-11.95,-7.09),P<0.0001),and the nasal length increased significantly(standardized mean difference(SMD)=2.25,95%CI:(1.26,2.23),P<0.00001).However,the evidence was insufficient to determine a significant change in the columellar-labial angle(SMD=-0.95,95%CI:(-2.19,0.29),P=0.13)and columellar-lobular angle(SMD=2.39,95%CI:(-1.20,5.97),P=0.19).Aesthetic dissatisfaction(12.5%)and infection(4.5%)were the most commonly reported complications.Reoperation was performed in 5.3%of patients.Conclusion:Surgical correction can increase the nasal length,reduce the nasolabial angle,and have a low reoperation rate.No significant improvement in the columellar-labial or columellar-lobular angle was observed.
基金supported by the National Natural Science Foundation of China(grant nos.81501678,81971848,and 82272287)Clinical Research Plan of Shanghai Hospital Development Center(grant nos.SHDC2020CR1019B and SHDC2020CR4029)+1 种基金Shanghai Municipal Key Clinical Specialty(grant no.shslczdzk00901)Innovative Research Team of High-Level Local University in Shanghai(grant no.SSMUZDCX20180700).
文摘Background:Scar contractions caused by trauma or burns can cause secondary physical dysfunction and disfigurement.Many minimally invasive methods for scar contraction have shown limited applicability and efficacy.This study investigated the feasibility and efficacy of intralesional collagenase injections for scar contraction treatment.Methods:Patients with contracted scars who had limited joint movement and physical disfiguration for>1 year were enrolled in this single-blind,randomized clinical trial from July 2017 to February 2018 at Shanghai Ninth People’s Hospital.Collagenase was injected into the firm-contracted scar(15 U/cm^(2))three times at 4-week intervals in the multiple treatment group and once in the single treatment group,and a placebo injection was performed in the control group.Scar length and skin texture were documented at the 4-and 12-week follow-ups.The safety of the collagenase treatment was also evaluated.Results:The contracted scar was significantly elongated after both single and multiple collagenase treatments.The results showed that,compared to a one-time treatment,repeated injections were more effective at 12 weeks,with an average improvement of 26.83(15.79%).At 12 weeks,78.9% of the patients in the multiple group and 52.9%in the single group achieved significant improvement at 12 weeks.No severe adverse events were observed.Conclusion:Intralesional collagenase injection showed promising results in improving scar contraction and provides an alternative treatment for patients.
文摘The purpose of this case series is to report the indications for dermis-fat grafting and the outcome of treatment in orbital soft tissue contraction among patients in a tertiary center. It is a retrospective, consecutive, interventional case series where all patients with orbital soft tissue contraction who had dermis-fat grafting were studied. All nine patients in our series underwent secondary dermis-fat grafting for orbital soft tissue reconstruction. The major cause for contracted socket was surgical eye removal following trauma. Eight of nine patients had no orbital implants inserted at the time of primary eye removal and eight patients have had failed orbital reconstructive procedures. Satisfactory cosmetic results were reported in all patients post-operatively. Dermis-fat grafting for contracted socket reconstruction was found to give satisfactory cosmetic results in our studied population.
文摘A contracted nose deformity is a challenging and distinct complication of rhinoplasty,particularly prevalent among Asian patients due to implant-related complications and infection-induced scar formation.Clinical presentations range from mild nasal tip upturning to severe distortion of nasal structures.This review outlines comprehensive surgical strategies for managing the contracted Asian nose,including wide release of the skin-soft tissue envelope,structural framework reconstruction with autologous rib cartilage,nasal tip elongation,and skin redraping techniques.Special considerations such as platelet-rich plasma,nanofat injection,and hyperbaric oxygen therapy are also discussed.Successful outcomes require meticulous planning,surgical expertise,and realistic patient expectations.
基金Project supported by the National Natural Science Foundation of China (Grant No. 29773035).
文摘A new contracted CI scheme—adjustable contracted CI scheme—is presented and programed. The efficiency of this scheme is tested by some example calculations. The result shows that the application of the new scheme is flexible and the correlation energy loss is lower than that of the original externally contracted CI method. Keywords: configuration interaction, contracted CI method, correlation energy.
基金This work was supported by the National Natural Science Foundation of China(Grant No.20073032).
文摘Based on the hole-particle correspondence an approximate so-called doubly contracted CI scheme is proposed. Examples calculated based on the doubly contracted CI (DCCI) scheme show that the number of configurations after contraction is reduced by three orders of magnitude, and the computation time is reduced by an order of magnitude. The examples also show that compared with experiments the DCCI and uncontracted CI have similar and reasonable accuracy to some spectroscopic parameters.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
基金supported by the National Research Foundation(NRF),Republic of Korea,under project BK21 FOUR(4299990213939).
文摘The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Traditional intrusion detection systems have limitations in terms of centralized architecture,lack of transparency,and vulnerability to single points of failure.This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems.This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signaturebased intrusion detection system.The introduced signature facilitates accurate detection and systematic classification of attacks,enabling categorization according to their severity levels within the transportation infrastructure.Through comparative analysis,the research demonstrates that the blockchain-based IDS outperforms traditional approaches in terms of security,resilience,and data integrity.
文摘We thank Power et al.1 for their interest in our review2 and for contributing to this important scientific discussion.We welcome their commentary and acknowledge the merit of continuing to scrutinize and refine interpretations in this evolving field.Given that much research time and financial investment is being given to the study of the effects of eccentric training in both athletic and clinical contexts,it is incumbent on our field to demonstrate whether eccentric contractions are a key(or the key)stimulus for sarcomerogenesis(increases in serial sarcomere number(SSN)).
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 by the National Key Research and Development Program of China(2020YFB1005704).
文摘Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequently,the academic community has devoted increasing attention to these security risks.However,conventional approaches to vulnerability detection frequently exhibit limited accuracy.To address this limitation,the present study introduces a novel vulnerability detection framework called GNNSE that integrates symbolic execution with graph neural networks(GNNs).The proposedmethod first constructs semantic graphs to comprehensively capture the control flow and data flow dependencies within smart contracts.These graphs are subsequently processed using GNNs to efficiently identify contracts with a high likelihood of vulnerabilities.For these high-risk contracts,symbolic execution is employed to perform fine-grained,path-level analysis,thereby improving overall detection precision.Experimental results on a dataset comprising 10,079 contracts demonstrate that the proposed method achieves detection precisions of 93.58% for reentrancy vulnerabilities and 92.73% for timestamp-dependent vulnerabilities.
文摘Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.
文摘The creator economy is revolutionizing the way in which individuals can profit from their engagement with online platforms.In this paper,we initiate the formal study of online learning in a creator economy by modeling it as a three-party game between users,a platform,and content creators.The platform interacts with creators through contracts under a principal-agent framework and with users via a recommender system.We study how the platform can jointly optimize contracts and recommendation policies in an online learning setting.We analyze return-based and feature-based contracts.Under smoothness assumptions,return-based contracts achieve regretΘ(T^(2/3)).For feature-based contracts,we introduce an intrinsic dimension d and prove a regret bound O(T^(d+1)/(d+2)),which is tight for linear families.
基金supported by the National Natural Science Foundation of China(Grant Nos.52208424,52208416,52078091,and 52108399)the Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0102).
文摘Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their effectiveness,most GNN-based vulnerability detectors operate as black boxes,making their decisions difficult to interpret and thus less suitable for critical security auditing.The information bottleneck(IB)principle provides a theoretical framework for isolating task-relevant graph components.However,existing IB-based implementations often encounter unstable optimization and limited understanding of code semantics.To address these issues,we introduce ContractGIB,an interpretable graph information bottleneck framework for function-level vulnerability analysis.ContractGIB introduces three main advances.First,ContractGIB introduces an Hilbert–Schmidt Independence Criterion(HSIC)based estimator that provides stable dependence measurement.Second,it incorporates a CodeBERT semantic module to improve node representations.Third,it initializes all nodes with pretrained CodeBERT embeddings,removing the need for hand-crafted features.For each contract function,ContractGIB identifies themost informative nodes forming an instance-specific explanatory subgraph that supports the model’s prediction.Comprehensive experiments on public smart contract datasets,including ESC andVSC,demonstrate thatContractGIB achieves superior performance compared to competitive GNN baselines,while offering clearer,instance-level interpretability.
文摘Air Liquide China announced on July 28thit has just signed a long-term contract withNanjing CEC Panda LCD Technology Corporationfor its new 6-generation Flat PanelDisplay (FPD) fab in the new Nanjing CrystalValley,Jiangsu province.This fab willbe one of the most advanced 6-generationFPD fabs in China,with a total
基金National Natural Science Foundation of China (12202293)Sichuan Science and Technology Program (2023NSFSC0393,2022NSFSC1952)。
文摘A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.
基金Supported by the National Natural Science Foundation of China(12201368,62376252)Key Project of Natural Science Foundation of Zhejiang Province(LZ22F030003)Zhejiang Province Leading Geese Plan(2024C02G1123882,2024C01SA100795).
文摘With the urgent need to resolve complex behaviors in nonlinear evolution equations,this study makes a contribution by establishing the local existence of solutions for Cauchy problems associated with equations of mixed types.Our primary contribution is the establishment of solution existence,illuminating the dynamics of these complex equations.To tackle this challenging problem,we construct an approximate solution sequence and apply the contraction mapping principle to rigorously prove local solution existence.Our results significantly advance the understanding of nonlinear evolution equations of mixed types.Furthermore,they provide a versatile,powerful approach for tackling analogous challenges across physics,engineering,and applied mathematics,making this work a valuable reference for researchers in these fields.
