The Connotations of the Constitutional Clause on Human Rights Protection From the Perspective of Foreign-related Rule of Law

The inclusion of the human rights clause in the Chi-nese Constitution is the core normative manifestation of the constitu-tionalization of human rights,and points to the relationship between international law and the Constitution in the sense of positive law.The inclusion of the human rights clauses in the Chinese Constitution itself is an inherent part of the development of China’s socialist constitution,and socialism has already contributed valuable concepts and practices of human rights protection to the modern world in its early stage.The constitutionalization of human rights protection does not necessarily lead to the superiority of international law over the constitutional order of a country,but rather to the convergence of international law and domestic law through the constitutional order.The relevant rules of international law will be effective only when they are transformed into domestic law through the Constitution and the human rights clause in the Constitution.Correspondingly,the domestic legal order is brought into line with the international legal order through the Con-stitution and its human rights clause.Behind the system of fundamen-tal rights in the constitutional order is the value foundation of the en-tire legal system.The advancement of foreign-related rule of law has brought new opportunities for China’s judicial practice to further pro-mote the protection of human rights.In the future,we should further integrate the human rights values embedded in socialism into China’s constitutional practice,enhance human rights protection around the country,and take a more active part in global human rights gover-nance.

Construction and Application of An Interdisciplinary Team Teaching Model for Foreign-Related Nursing English in Higher Vocational Colleges from the Perspective of Ecolinguistics

Under the background of globalization,there are severe challenges in the cultivation of the professional skills of nursing staff,especially the English skills of foreign-related nursing,which has become an important part of the training of nursing talents.At present,most English teaching of foreign-related nursing in higher vocational colleges follows the traditional grammar teaching model.However,as most of the teaching staff for medical English are English teachers who have limited nursing professional knowledge,the industry characteristics of medical English are not fully demonstrated in the teaching process,and the lack of practicality inevitably reduces the quality of medical English teaching.Therefore,the traditional nursing English teaching model in higher vocational colleges can no longer meet the actual teaching needs.There is an urgent need to implement an interdisciplinary team teaching model that completely fits the industry environment of foreign-related nursing English and apply it flexibly to improve the quality of foreign-related nursing English teaching in higher vocational colleges,and lay a solid foundation for professional practice of nursing staff.Based on the perspective of ecolinguistics,this article explores the application strategies of the interdisciplinary team teaching model for foreign-related nursing English in higher vocational colleges,with the view to provide guidelines for the actual teaching of foreign-related nursing English.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach

This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.

Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

The fast-paced development of blockchain technology is evident.Yet,the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem.Conventional smart contract vulnerability detection primarily relies on static analysis tools,which are less efficient and accurate.Although deep learning methods have improved detection efficiency,they are unable to fully utilize the static relationships within contracts.Therefore,we have adopted the advantages of the above two methods,combining feature extraction mode of tools with deep learning techniques.Firstly,we have constructed corresponding feature extraction mode for different vulnerabilities,which are used to extract feature graphs from the source code of smart contracts.Then,the node features in feature graphs are fed into a graph convolutional neural network for training,and the edge features are processed using a method that combines attentionmechanismwith gated units.Ultimately,the revised node features and edge features are concatenated through amulti-head attentionmechanism.The result of the splicing is a global representation of the entire feature graph.Our method was tested on three types of data:Timestamp vulnerabilities,reentrancy vulnerabilities,and access control vulnerabilities,where the F1 score of our method reaches 84.63%,92.55%,and 61.36%.The results indicate that our method surpasses most others in detecting smart contract vulnerabilities.

A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

In recent years,the number of smart contracts deployed on blockchain has exploded.However,the issue of vulnerability has caused incalculable losses.Due to the irreversible and immutability of smart contracts,vulnerability detection has become particularly important.With the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts.This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts.Subsequently,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection.These tools are categorized based on their open-source status,the data format and the type of feature extraction they employ.Then we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and accuracy.Finally,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection tools.Meanwhile,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

Preserving Data Secrecy and Integrity for Cloud Storage Using Smart Contracts and Cryptographic Primitives

Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various benefits.However,the adoption of cloud storage poses significant risks to data secrecy and integrity.This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology,smart contracts,and cryptographic primitives.The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data.To preserve data secrecy,symmetric encryption systems are employed to encrypt user data before outsourcing it.An extensive performance analysis is conducted to illustrate the efficiency of the proposed mechanism.Additionally,a rigorous assessment is conducted to ensure that the developed smart contract is free from vulnerabilities and to measure its associated running costs.The security analysis of the proposed system confirms that our approach can securely maintain the confidentiality and integrity of cloud storage,even in the presence of malicious entities.The proposed mechanism contributes to enhancing data security in cloud computing environments and can be used as a foundation for developing more secure cloud storage systems.

A Systematic Review and Performance Evaluation of Open-Source Tools for Smart Contract Vulnerability Detection

With the rise of blockchain technology,the security issues of smart contracts have become increasingly critical.Despite the availability of numerous smart contract vulnerability detection tools,many face challenges such as slow updates,usability issues,and limited installation methods.These challenges hinder the adoption and practicality of these tools.This paper examines smart contract vulnerability detection tools from 2016 to 2023,sourced from the Web of Science(WOS)and Google Scholar.By systematically collecting,screening,and synthesizing relevant research,38 open-source tools that provide installation methods were selected for further investigation.From a developer’s perspective,this paper offers a comprehensive survey of these 38 open-source tools,discussing their operating principles,installation methods,environmental dependencies,update frequencies,and installation challenges.Based on this,we propose an Ethereum smart contract vulnerability detection framework.This framework enables developers to easily utilize various detection tools and accurately analyze contract security issues.To validate the framework’s stability,over 1700 h of testing were conducted.Additionally,a comprehensive performance test was performed on the mainstream detection tools integrated within the framework,assessing their hardware requirements and vulnerability detection coverage.Experimental results indicate that the Slither tool demonstrates satisfactory performance in terms of system resource consumption and vulnerability detection coverage.This study represents the first performance evaluation of testing tools in this domain,providing significant reference value.

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency.Revolutionary advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer environment.ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users.However,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological variation.This may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS services.In this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between vehicles.Self-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed protocol.The results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0

The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.

Revisiting the Electron Radius in Light of Length Contraction

In previous work, the electron radius was identified as the “actual electron radius.” However, this is more accurately described as the electron radius at rest. This study reexamines the electron with an emphasis on the electron radius under motion, incorporating the effects of length contraction. The findings suggest that the radius is subject to Lorentz contraction, which has interesting implications for relativistic effects at the subatomic level.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

The Impact of Corporate Governance and Fair Value Accounting on Debt Contracts

This paper investigates the theoretical relationship between corporate governance,fair value accounting,and debt contracts.It primarily examines the individual impacts of corporate governance and fair value accounting on debt contracts,while also exploring the influence of corporate governance on fair value accounting.The study emphasizes the importance of considering the interests and legal status of creditors in the context of debt contracts.The findings indicate that strong corporate governance can reduce the likelihood of debt default and that the company’s restructuring costs in the event of a default determine whether improved corporate governance will increase or decrease debt costs.Additionally,the study reveals that the strength of corporate governance affects the value relevance of fair value accounting.However,the impact of fair value accounting on debt contracts is not inherently positive or negative;for instance,companies may use fair value adjustments with manipulative intent to enhance performance.Ultimately,the research highlights that discussions about corporate governance should not prioritize shareholder interests exclusively but also consider the legitimate position of creditors.

Scheduling on tractor and trailer transportation considering the influence of disrupted events based on the contract net and simulated annealing algorithm

To provide a much more resilient transport scheme for tractor and trailer transportation systems,this paper explores the generation method of tractor and trailer transport schemes considering the influence of disrupted events.Three states of tractors including towing loaded trailers,towing empty trailers,and idle driving are taken into account.Based on the disruption management theory,a scheduling model is constructed to minimize the total deviation cost including transportation time,transportation path,and number of used vehicles under the three states of tractors.A heuristics based on the contract net and simulated annealing algorithm is designed to solve the proposed model.Through comparative analysis of examples with different numbers of newly added transportation tasks and different types of road networks,the performance of the contract net algorithm in terms of deviations in idle driving paths,empty trailer paths,loaded trailer paths,time,number of used vehicles,and total deviation cost are analyzed.The results demonstrate the effectiveness of the model and algorithm,highlighting the superiority of the disruption management model and the contract net annealing algorithm.The study provides a reference for handling unexpected events in the tractor and trailer transportation industry.

Foreign-Related Tax Policy and Regime and Its Tendency of Development

China’s foreign--related tax system was established and developed in theprocess of deepening the reform and opening to the outside world begin-ning in 1979. Since the Third Plenary Session of the Eleventh CentralCommittee of the Chinese Communist Party, to meet the demands of thenew situation of opening to the outside world, several laws were promul-

CHINA'S FOREIGN-RELATED ARBITRATION

Before the founding of new China in1949,there was no any arbitrationlegislation or arbitration organs.On May 6,1954,the former central people’sgovernment passed the Decision on Settingup a Foreign Trade Arbitration Committeeunder the China Council for the Promotionof International Trade to provide the basicprinciples for China’s

Analyzing Ethereum Smart Contract Vulnerabilities at Scale Based on Inter-Contract Dependency

Smart contracts running on public blockchains are permissionless and decentralized,attracting both developers and malicious participants.Ethereum,the world’s largest decentralized application platform on which more than 40 million smart contracts are running,is frequently challenged by smart contract vulnerabilities.What’s worse,since the homogeneity of a wide range of smart contracts and the increase in inter-contract dependencies,a vulnerability in a certain smart contract could affect a large number of other contracts in Ethereum.However,little is known about how vulnerable contracts affect other on-chain contracts and which contracts can be affected.Thus,we first present the contract dependency graph(CDG)to perform a vulnerability analysis for Ethereum smart contracts,where CDG characterizes inter-contract dependencies formed by DELEGATECALL-type internal transaction in Ethereum.Then,three generic definitions of security violations against CDG are given for finding respective potential victim contracts affected by different types of vulnerable contracts.Further,we construct the CDG with 195,247 smart contracts active in the latest blocks of the Ethereum and verify the above security violations against CDG by detecting three representative known vulnerabilities.Compared to previous large-scale vulnerability analysis,our analysis scheme marks potential victim contracts that can be affected by different types of vulnerable contracts,and identify their possible risks based on the type of security violation actually occurring.The analysis results show that the proportion of potential victim contracts reaches 14.7%,far more than that of corresponding vulnerable contracts(less than 0.02%)in CDG.

The role of time preferences in contract breach:Evidence from Chinese poultry farmers participating in contract farming

Farmers’contract breach behavior is cited as one of the major stumbling blocks in the sustainable expansion of contract farming in many developing countries.This paper examines farmers’contract breach decisions from the perspective of time preferences.The empirical analysis is based on a household survey and economic field experiments of poultry households participating in contract farming conducted in Jiangsu Province,China.A discounted utility model and a maximum likelihood technique are applied to estimate farmers’time preferences and the effect of time preferences on contract breach in the production and sales phases are explored with a bivariate probit model.The results show that,on average,the poultry farmers in the sample are generally present biased and impatient regarding future utility.The regression results show that farmers with a higher preference for the present and a higher discount rate are more likely to breach contracts,and time preferences play a greater role in the production phase than in the sales phase.When considering heterogeneity,specific investments and transaction costs promote contract stability only for farmers with a low degree of impatience.Moreover,compared with large-scale farmers,small-scale farmers’contract breach decisions are more significantly affected by their time preferences.These results have implications for contract stability policies and other issues that are impacted by the linking of behavioral preferences to agricultural decisions.

Smart contract token-based privacy-preserving access control system for industrial Internet of Things

Due to mobile Internet technology's rapid popularization,the Industrial Internet of Things(IIoT)can be seen everywhere in our daily lives.While IIoT brings us much convenience,a series of security and scalability issues related to permission operations rise to the surface during device communications.Hence,at present,a reliable and dynamic access control management system for IIoT is in urgent need.Up till now,numerous access control architectures have been proposed for IIoT.However,owing to centralized models and heterogeneous devices,security and scalability requirements still cannot be met.In this paper,we offer a smart contract token-based solution for decentralized access control in IIoT systems.Specifically,there are three smart contracts in our system,including the Token Issue Contract(TIC),User Register Contract(URC),and Manage Contract(MC).These three contracts collaboratively supervise and manage various events in IIoT environments.We also utilize the lightweight and post-quantum encryption algorithm-Nth-degree Truncated Polynomial Ring Units(NTRU)to preserve user privacy during the registration process.Subsequently,to evaluate our proposed architecture's performance,we build a prototype platform that connects to the local blockchain.Finally,experiment results show that our scheme has achieved secure and dynamic access control for the IIoT system compared with related research.

Research on optimal intelligent routing algorithm for IoV with machine learning and smart contract

The huge increase in the communication network rate has made the application fields and scenarios for vehicular ad hoc networks more abundant and diversified and proposed more requirements for the efficiency and quality of data transmission.To improve the limited communication distance and poor communication quality of the Internet of Vehicles(IoV),an optimal intelligent routing algorithm is proposed in this paper.Combined multiweight decision algorithm with the greedy perimeter stateless routing protocol,designed and evaluated standardized function for link stability.Linear additive weighting is used to optimize link stability and distance to improve the packet delivery rate of the IoV.The blockchain system is used as the storage structure for relay data,and the smart contract incentive algorithm based on machine learning is used to encourage relay vehicles to provide more communication bandwidth for data packet transmission.The proposed scheme is simulated and analyzed under different scenarios and different parameters.The experimental results demonstrate that the proposed scheme can effectively reduce the packet loss rate and improve system performance.