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.

Allocation of Public Service Facilities in Villages and Towns from the Perspective of Smart Contraction: A Case Study of Zixi County, Jiangxi Province

The limitation of traditional layout system and the continuous contraction of villages and towns have brought challenges to the layout of public service facilities.It is an imperative task against this background to integrate space resources and allocate public service facilities scientifically and reasonably.This paper took the system and method of rural public service facility allocation from the perspective of smart contraction as the theoretic support,and Zixi County in Jiangxi Province for example,built the four-level life circle of“county-fundamental-basic-routine”based on the influence factors of facility allocation,village and town contraction strength,rural comprehensive assessment results,residents’trip willingness and demands on public service facilities,finally proposed the suggestions for optimizing the allocation of village and town public service facilities.

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.

Construction of the“Micro-Ideological and Political”Model for Ideological and Political Teaching Reform in Bidding and Contract Management Courses

In the context of deepening educational reforms,the significance of ideological and political education has become increasingly prominent,emerging as a crucial aspect of enhancing students’comprehensive qualities.To ensure the orderly progress of ideological and political education in courses,it is essential to actively promote the integration of ideological and political elements within coursework.This integration aims to align professional course education with ideological and political education,fostering a collaborative educational model.Therefore,in the teaching of bidding and contract management courses,constructing a“micro-ideological and political”teaching model has emerged as a critical component.The implementation of this model facilitates the seamless integration of bidding and contract management coursework with ideological and political education,thereby elevating the teaching quality of these courses.Additionally,it leverages the synergistic role of coursework and ideology in educating students,ultimately enhancing the quality and level of talent cultivation.Hence,this paper proposes strategies for constructing a“microideological and political”model within the context of ideological and political teaching reforms in bidding and contract management courses,inviting discussion and exchange on this topic.

基于回声状态网络的智能合约漏洞检测方法

区块链平台上的智能合约是为链上各方提供安全可信赖服务的去中心化应用程序,而智能合约漏洞检测能确保智能合约的安全性。然而,现有的智能合约漏洞检测方法在样本数量不均衡和语义信息挖掘不全面时,会出现特征学习不足和漏洞检测准确率低的问题,而且,这些方法无法对新的合约漏洞进行检测。针对上述问题,提出一种基于回声状态网络(ESN)的智能合约漏洞检测方法。首先,根据合约图,对不同语义、语法边进行学习,并利用Skip-Gram模型训练得到特征向量;其次,结合ESN和迁移学习,实现对新合约漏洞的迁移扩展,以提高漏洞检测率;最后,在Etherscan平台搜集的智能合约数据集上进行实验。实验结果表明,所提方法的准确率、精确率、召回率和F1分数分别达到了94.30%、97.54%、91.68%和94.52%,与双向长短时记忆(BLSTM)网络、自注意力机制的双向长短时记忆(BLSTM-ATT)相比,所提方法的准确率分别提高了5.93和11.75个百分点,漏洞检测性能更优。消融实验也进一步验证了ESN对智能合约漏洞检测的有效性。

论替代交易规则——以《民法典合同编通则解释》第60条第2款为中心

《民法典合同编通则解释》第60条第2款确立的替代交易规则不仅具有比较法上的基础,而且其功能具有多样性,是可得利益损失的重要计算方式。替代交易规则主要适用于以种类物为标的物的合同,在以劳务或特定物给付为内容的合同中也有适用余地,但必须以发生根本违约为前提。替代交易规则原则上以解除合同为必要,但在特殊情形下也可以不解除合同而直接进行替代交易。替代交易尚须具有合理性,从而将不具有合理性的替代交易排除于可赔偿范围之外,以此保护违约方的利益。市场价格是判断替代交易合理性的依据,但并非唯一依据。除非出于减损规则的要求,替代交易并非一项义务,非违约方可以选择进行替代交易或者依据市场价格获得赔偿。通过替代交易规则可以解决继续性定期合同中可得利益损害计算的难题。实施替代交易后,非违约方原则上不得再请求违约方履行原给付,非违约方实施替代交易后应负有减损义务。

半密闭腔室工频建弧过程及建弧率影响因素分析

多腔室快速灭弧装置具有响应速度快、灭弧性能良好、能有效抑制雷电冲击闪络引起的线路跳闸等优点,作为一种新型配电网线路防雷措施备受关注。然而,半密闭腔室作为多腔室快速灭弧装置的基本单元,腔室内冲击放电电弧稳定转换为工频续流电弧的过程尚不明确,缺乏对半密闭腔室工频建弧率的深入研究。为分析半密闭腔室工频建弧过程及建弧率的影响因素,该文搭建半密闭腔室雷电冲击联合10 kV工频电压试验平台,测量了半密闭腔室冲击击穿后的电压、电流波形,探究了冲击放电电弧稳定转换为工频续流电弧的过程,对比分析普通间隙与半密闭腔室间隙的建弧率,并进一步探究半密闭腔室串联后的效果,发现多腔室灭弧结构可通过快速吹弧有效抑制冲击放电电弧向工频续流电弧的转变,将其工频建弧率限制在较低水平。同时,为了探究半密闭腔室建弧率的影响因素,该文通过改变腔室结构和电极半径分析其对工频建弧率的影响,结果表明,适当地增大腔室体积及气流量有助于防止高温气体在腔室内的堵塞,促进工频续流电弧的能量耗散,降低工频建弧率;一定程度地减小电极半径有助于增强冲击放电电弧的磁缩效应,抑制电弧弧柱直径的发展,降低工频建弧率。

碳限额交易机制下大数据服务商参与的供应链决策模型

碳限额交易机制下,以订购大数据服务的供应链集中式决策模型为基准,建立制造商和零售商分别订购大数据服务的分散式决策模型。求解模型并比较不同供应链成员企业订购大数据服务对供应链碳减排量、产品产量及利润的影响,最后对分散式决策下占优的情形设计收益共享契约实现供应链协调。研究表明:与零售商订购大数据服务相比,制造商订购大数据服务时,碳减排量、产品产量和企业利润均较高;碳减排量、产品产量、大数据服务商的努力程度、企业的单位支付水平以及供应链成员企业利润,均随消费者的低碳偏好程度或大数据服务对消费者影响程度的增加而提高,随订购大数据服务后与订购前企业成本的比的增加而降低;零售商分享任意比例收益给制造商,均可以降低碳排放量、增加产品产量,并提高其所在供应链成员企业的利润。

《民法典》视域下合伙合同解除规则的建构

合伙合同的解除,是合伙人脱离合伙关系的前提。合伙合同具有开放包容、组织化差异程度大、给付内容不确定、以信赖关系为基础的特征。合伙合同解除规则建构需要建立在确定性、效率和公平的核心逻辑基础上。实践中产生的合伙僵局,需要在《民法典》视域下,从合伙合同解除的核心价值逻辑出发,建构合伙合同法定解除、意定解除、酌定解除的规则体系加以应对,而酌定解除应以解除为原则,不解除为例外。

Research on telecommunication resale service supply chain coordination with revenue-sharing contract

The competition and cooperation between traditional telecom operators and resale operators in the supply chain are discussed, when the telecom industry developed telecommunication resale service. Supply chain contract is an effective way to coordinate the supply chain. This paper analyzes the revenue-sharing contract between telecom operators and resale operators. The study shows that by setting up a rational revenue-sharing ratio and wholesale price, a revenue-sharing contract can coordinate this supply chain, and telecom operators and resale operators can achieve a 'win-win' solution.