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.

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.

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.

Physical Transformations of Agri-Food Products during Their Convective Drying: Characterization of the Contraction and Isotropicity of Okra

The physical transformations in terms of contraction of okra dimensions during convective drying were examined. During drying, the lateral and longitudinal dimensions of okra decrease over time. The lateral dimensions go from their initial value to around 53%, 65% and 66% of this value after 530 min. The length of the two samples used goes from 8.65 and 9.02 cm to 6.79 and 7.52 cm after 14,300 min, i.e. a variation of 78.50% and 83.37%. All the two directions give variations almost linear depending on the water content. These linear contractions result in a volume contraction of the okra. It considerably decreases in volume during the drying process. The volume goes from 831.32 cm3 to 367.57 cm3 in min, a variation of 44.22%. The isotropic index reveals that okra does not behave the same in the lateral and longitudinal directions. It contracts its diameter more than its length.

Generalized Kannan-type contraction and fixed point theorems

In this paper,the generalized Kannan-type contraction in cone metric spaces over Banach algebras is introduced.The fixed point theorems satisfying generalized contractive conditions are obtained,without appealing to completeness of X or normality of the cone.The continuity of the mapping is relaxed.Furthermore,we prove that the completeness in cone metric spaces over Banach algebras is necessary if the generalized Kannan-type contraction has a fixed point in X.These results greatly generalize several well-known comparable results in the literature.

Enhancing the activity of FeNi bimetallic electrocatalysts on overall water splitting by Nd_(2)O_(3)-induced FeNi lattice contraction

The development of high-efficiency and cost-effective bifunctional electrocatalysts for overall water splitting remains a formidable challenge.Herein,FeNi-Nd_(2)O_(3) nanoparticles anchored on N-doped carbon nanotubes(FeNi-Nd_(2)O_(3)/NCN) are designed for highly effective overall water splitting via a facile two-step hydrothermal approach.The synthetic FeNi-Nd_(2)O_(3) hetero-trimers(Fe 2p-Ni 2p-Nd 3d orbital coupling)on NCN achieve excellent oxygen evolution reaction(OER) and hydrogen evolution reaction(HER) activities with overpotentials of 270 and 120 mV at 10 mA cm^(-2) in 1 M KOH solution.Moreover,a small voltage of 1.52 V at 10 mA cm^(-2) is achieved when FeNi-Nd_(2)O_(3)/NCN is assessed as bifunctional catalyst for overall water splitting,which is superior to the typically integrated Pt/C and RuO_(2) counterparts(1.54 V at 10 mA cm^(-2)).The related characterizations including X-ray absorption fine structure(XAFS)spectroscopy show that the remarkably improved activity is originated from Nd_(2)O_(3)-induced FeNi bimetallic lattice contraction.Furthermore,density functional theory(DFT) calculations indicate that the lattice contraction reduces binding energies of intermediates by downshifting the position of FeNi bimetallic d-band center relative to the Fermi level to optimize catalytic performance.Therefore,the Nd_(2)O_(3)-induced FeNi bimetallic lattice contraction may provide a new perspective for designing and synthesizing innovative catalytic systems.

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.

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.

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.

DIRECTED HYPERGRAPH THEORY AND DECOMPOSITION CONTRACTION METHOD

A new branch of hypergraph theory-directed hyperaph theory and a kind of new methods-dicomposition contraction(DCP, PDCP and GDC) methods are presented for solving hypernetwork problems.lts computing time is lower than that of ECP method in several order of magnitude.

Thick-skinned Contractional Salt Structures in the Kuqa Depression,the Northern Tarim Basin:Constraints from Physical Experiments

Thick-skinned contractional salt structures are widely developed in the western Kuqa depression, northern Tarim basin. To understand the mechanisms that govern the development of these structures, physical experiments are conducted and the results show that they are largely governed by the activities of basement faults and the forming of paleo-uplifts and basement slopes. The model materials in this study are dry sand, vaseline and plasticene （or hard foam）, simulating the suprasalt, salt, and subsalt layers respectively. The experiments show that, due to the activities of basement faults and the forming of the paleo-uplifts, salt bodies usually accumulate and thicken significantly on the middle top of the paleo-uplifts which are constrained by the pre-exiting boundary faults. The development of large-scale thrust faults and salt nappes is favored by the basement slops with larger dips. The experiments also conclude that differential structural deformation could occur between the subsalt and suprasalt layers because of the presence of salt layers. Their geometries and the locations of structural highs are different, despite of the great similarities in the uplifted areas. The pierced salt diapir is not observed in the experiments, which indicates that the contractional shortening does not effectively accelerate the development of the salt diapir.

Mechanisms mediating CCK-8S-induced contraction of proximal colon in guinea pigs

AIM:To investigate the effects of sulfated cholecystokinin octapeptide (CCK-8S) on the contractile activity of guinea-pig proximal colon.METHODS:Proximal colonic smooth muscle (PCSM) strips were obtained from adult female guinea pigs and contractile response of PCSM strips was recorded using a polyphysiograph.PCSM cells were isolated by enzymatic digestion.Resting potential (RP),action potential (AP),large conductance potassium channel currents (IBKCa) and L-type calcium currents (ICa-L) were recorded by patch-clamp techniques.RESULTS:(1) CCK-8S (10-7 mol/L) enhanced the mean contractile amplitude of colonic circular muscle and longitudinal muscle (LM) strips by 56.53% ± 11.92%(P=0.038) and 65.93% ± 12.98% (P=0.019),respectively,as well as the mean frequency of LM by 31.69% ± 13.58% (P=0.023),which were significantly attenuated by pretreating strips with devazepide,nifedipine,iberiotoxin,thapsigargin (TG) and BAPTA-AM (BA) respectively;(2) CCK-8S (10-7 mol/L) increased the AP amplitude by 38.6% ± 3.2% (P=0.015),decreased AP duration by 36.9% ± 8.7% (P=0.026),and depolarized the RP from-61.3 ± 2.7 mV to-29.8 ± 5.9 mV (P=0.032);and (3) Compared with the normal control group,CCK-8S (10-7 mol/L) enhanced the peak current of IBKCa by 18.7% ± 2.1% (from 916 ± 183 pA to 1088 ± 226 pA;at +60 mV;P=0.029),which was inhibited by respective pretreatment with iberiotoxin and devazepide.Additionally,CCK-8S (10-7 mol/L) intensif ied the peak current of ICa-L by 40% (from 60 ± 8 pA to 84 ± 11 pA;at +10 mV;P=0.012),compared to the normal control group,which was apparently suppressed by respective pretreatment with nifedipine,devazepide,TG and BA.In the respective presence of heparin and staurosporine,CCK-8S did not signif icantly enhance IBKCa and ICa-L.CONCLUSION:The results suggest that CCK-8S promotes guinea-pig proximal colon contraction by CCK1 receptors,following activation of the inositol triphosphate-protein kinase C signal transduction pathway.

Rapid bilateral anterior capsule contraction following high myopic cataract surgeries:a case report

We describe a rapid anterior capsule contraction following phacoemulsifiction and intraocular lens(IOL) implantation in an old woman with high myopia. The patient with high myopia complicated with cataract received phacoemulcification and IOL implantation bilaterally .The best-corrected visual acuity (BCVA) improved from 0.1 to 0.4 in the right eye and 0.5 in the left eye 1 week after surgeries.5 weeks after surgery of the right eye and 4 weeks after surgery of the left eye, the patient complained blurred vision in the right eye. BCVA of the right eye was 0.06 and that of the left was 0.1. Slit-lamp examination revealed anterior capsule contraction in both eyes and a fully closed capsulorhexis opening in the right eye. The IOLs were centered but almost completely enclosed, with numerous linear fibrous folds radiating from the hick central fibrosis. We surgically excised the central part of the anterior capsule of the eyes with microscissors, resulting again in BCVA of 0.4 and 0.5 in the right and left eyes respectively. Anterior capsule contraction might appear much earlier than three months after phacoemulsification and IOL implantation surgery in case of high myopia complicated with cataract. Patients with high myopia receive cataract and IOL surgery should be monitored carefully for the rapid development of anterior capsule contraction.