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 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
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
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
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
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
Flowfield inverse design can obtain the desired flow and contour with high design efficiency,short design cycle,and small modification need.In this study,the Euler equations are formulated in the stream-function coord...Flowfield inverse design can obtain the desired flow and contour with high design efficiency,short design cycle,and small modification need.In this study,the Euler equations are formulated in the stream-function coordinates and combined with the given boundary conditions to derive a gridless space-marching method for the inverse design of subsonic,transonic,and supersonic flowfields.Designers can prescribe the flow parameters along the reference streamline to design flowfields and aerodynamic contours.The method is validated by the theoretical transonic solution,computational fluid dynamics,and experimental data,respectively.The method supports the fabrication of a Mach 2.0 single expansion tunnel.The calibration data agree well with the prescribed pressure distribution.The method is successfully applied to inverse design of contractions,nozzles,and asymmetric channels.Compared to classical analytic contractions,the contractions designed by the space-marching method provide a more accurate transonic flow.Compared to the classical Sivells’nozzle,the nozzle designed by the space-marching method provides a smaller workload,a more flexible velocity distribution,a 20%reduction in length,and an equally uniform flow.Additionally,the space-marching method is applied to design the asymmetric channels under various Mach numbers.These asymmetric channels perfectly eliminate Mach waves,achieving the shock-free flow turning and high flow uniformity.These results validate the feasibility of the space-marching method,making it a good candidate for the inverse design of subsonic,transonic,and supersonic internal flowfields and aerodynamic contours.展开更多
Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have probl...Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.展开更多
Changes in food production,often driven by distant demand,have a significant influence on sustainable man agement and use of land and water,and are in turn a driving factor of biodiversity change.While the connection ...Changes in food production,often driven by distant demand,have a significant influence on sustainable man agement and use of land and water,and are in turn a driving factor of biodiversity change.While the connection between land use and demand through value chains is increasingly understood,there is no comprehensive concep tualisation of this relationship.To address this gap,we propose a conceptual framework and use it as a basis for a systematic review to characterise value-chain connection and explore its influence on land-use and-cover change.Our search in June 2022 onWeb of Science and Scopus yielded 198 documents,describing studies completed after the year 2000 that provide information on both value-chain connection and land-use or-cover change.In total,we used 531 distinct cases to assess how frequently particular types of land-use or-cover change and value-chain connections co-occurred,and synthesized findings on their relations.Our findings confirm that 1)market inte gration is associated with intensification;2)land managers with environmental standards more frequently adopt environmentally friendly practices;3)physical and value-chain distances to consumers play a crucial role,with shorter distances associated with environmentally friendly practices and global chains linked to intensification and expansion.Incorporating these characteristics in existing theories of land-system change,would significantly advance understanding of land managers’decision-making,ultimately guiding more environmentally responsible production systems and contributing to global sustainability goals.展开更多
Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attack...Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.展开更多
Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual ri...Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual rights are straightforwardly enforced.Given the common belief that certain personality traits—such as trustworthiness,reliability,loyalty,thriftiness,and stinginess—are more often linked to conservatives(Republicans)than to liberals(Democrats),we investigate whether companies with conservative chief executive officers(CEOs)secure more advantageous loan terms compared to others.Our findings indicate that firms with conservative CEOs are able to negotiate bank loans with lower interest spreads and upfront fees.While we do not observe a direct impact of CEO overconfidence on loan pricing,we reveal that the combined influence of CEO conservatism and overconfidence contributes to our primary findings.Additionally,we discovered that conservative CEOs tend to receive more favorable non-price conditions(fewer covenants)and are less inclined to offer collateral.展开更多
Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart cont...Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart contracts for personal financial gain, which undermines the integrity of the Ethereum blockchain. This paper proposes a computer program called SADA (Static and Dynamic Analyzer), a novel approach to smart contract vulnerability detection using multiple Large Language Model (LLM) agents to analyze and flag suspicious Solidity code for Ethereum smart contracts. SADA not only improves upon existing vulnerability detection methods but also paves the way for more secure smart contract development practices in the rapidly evolving blockchain ecosystem.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.
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.
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.
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.
基金supported by the National Key Research and Development Program of China(No.2019YFA0405300)the National Natural Science Foundation of China(No.12272405).
文摘Flowfield inverse design can obtain the desired flow and contour with high design efficiency,short design cycle,and small modification need.In this study,the Euler equations are formulated in the stream-function coordinates and combined with the given boundary conditions to derive a gridless space-marching method for the inverse design of subsonic,transonic,and supersonic flowfields.Designers can prescribe the flow parameters along the reference streamline to design flowfields and aerodynamic contours.The method is validated by the theoretical transonic solution,computational fluid dynamics,and experimental data,respectively.The method supports the fabrication of a Mach 2.0 single expansion tunnel.The calibration data agree well with the prescribed pressure distribution.The method is successfully applied to inverse design of contractions,nozzles,and asymmetric channels.Compared to classical analytic contractions,the contractions designed by the space-marching method provide a more accurate transonic flow.Compared to the classical Sivells’nozzle,the nozzle designed by the space-marching method provides a smaller workload,a more flexible velocity distribution,a 20%reduction in length,and an equally uniform flow.Additionally,the space-marching method is applied to design the asymmetric channels under various Mach numbers.These asymmetric channels perfectly eliminate Mach waves,achieving the shock-free flow turning and high flow uniformity.These results validate the feasibility of the space-marching method,making it a good candidate for the inverse design of subsonic,transonic,and supersonic internal flowfields and aerodynamic contours.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2025R97)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.
文摘Changes in food production,often driven by distant demand,have a significant influence on sustainable man agement and use of land and water,and are in turn a driving factor of biodiversity change.While the connection between land use and demand through value chains is increasingly understood,there is no comprehensive concep tualisation of this relationship.To address this gap,we propose a conceptual framework and use it as a basis for a systematic review to characterise value-chain connection and explore its influence on land-use and-cover change.Our search in June 2022 onWeb of Science and Scopus yielded 198 documents,describing studies completed after the year 2000 that provide information on both value-chain connection and land-use or-cover change.In total,we used 531 distinct cases to assess how frequently particular types of land-use or-cover change and value-chain connections co-occurred,and synthesized findings on their relations.Our findings confirm that 1)market inte gration is associated with intensification;2)land managers with environmental standards more frequently adopt environmentally friendly practices;3)physical and value-chain distances to consumers play a crucial role,with shorter distances associated with environmentally friendly practices and global chains linked to intensification and expansion.Incorporating these characteristics in existing theories of land-system change,would significantly advance understanding of land managers’decision-making,ultimately guiding more environmentally responsible production systems and contributing to global sustainability goals.
基金partially supported by the National Natural Science Foundation (62272248)the Open Project Fund of State Key Laboratory of Computer Architecture,Institute of Computing Technology,Chinese Academy of Sciences (CARCHA202108,CARCH201905)+1 种基金the Natural Science Foundation of Tianjin (20JCZDJC00610)Sponsored by Zhejiang Lab (2021KF0AB04)。
文摘Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.
文摘Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual rights are straightforwardly enforced.Given the common belief that certain personality traits—such as trustworthiness,reliability,loyalty,thriftiness,and stinginess—are more often linked to conservatives(Republicans)than to liberals(Democrats),we investigate whether companies with conservative chief executive officers(CEOs)secure more advantageous loan terms compared to others.Our findings indicate that firms with conservative CEOs are able to negotiate bank loans with lower interest spreads and upfront fees.While we do not observe a direct impact of CEO overconfidence on loan pricing,we reveal that the combined influence of CEO conservatism and overconfidence contributes to our primary findings.Additionally,we discovered that conservative CEOs tend to receive more favorable non-price conditions(fewer covenants)and are less inclined to offer collateral.
文摘Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart contracts for personal financial gain, which undermines the integrity of the Ethereum blockchain. This paper proposes a computer program called SADA (Static and Dynamic Analyzer), a novel approach to smart contract vulnerability detection using multiple Large Language Model (LLM) agents to analyze and flag suspicious Solidity code for Ethereum smart contracts. SADA not only improves upon existing vulnerability detection methods but also paves the way for more secure smart contract development practices in the rapidly evolving blockchain ecosystem.
