Chitosan/Sodium Alginate Multilayer pH-Sensitive Films Based on Layer-by-Layer Self-Assembly for Intelligent Packaging

The abuse of plastic food packaging has brought about severe white pollution issues around the world.Developing green and sustainable biomass packaging is an effective way to solve this problem.Hence,a chitosan/sodium alginate-based multilayer film is fabricated via a layer-by-layer(LBL)self-assembly method.With the help of superior interaction between the layers,the multilayer film possesses excellent mechanical properties(with a tensile strength of 50 MPa).Besides,the film displays outstanding water retention property(blocking moisture of 97.56%)and ultraviolet blocking property.Anthocyanin is introduced into the film to detect the food quality since it is one natural plant polyphenol that is sensitive to the pH changes ranging from 1 to 13 in food when spoilage occurs.It is noted that the film is also bacteriostatic which is desired for food packaging.This study describes a simple technique for the development of advanced multifunctional and fully biodegradable food packaging film and it is a sustainable alternative to plastic packaging.

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.

Solid Additive-Assisted Layer-by-Layer Processing for 19%Efficiency Binary Organic Solar Cells

Morphology is of great significance to the performance of organic solar cells(OSCs),since appropriate morphology could not only promote the exciton dissociation,but also reduce the charge recombination.In this work,we have developed a solid additive-assisted layer-by-layer(SAA-LBL)processing to fabricate high-efficiency OSCs.By adding the solid additive of fatty acid(FA)into polymer donor PM6 solution,controllable pre-phase separation forms between PM6 and FA.This intermixed morphology facilitates the diffusion of acceptor Y6 into the donor PM6 during the LBL processing,due to the good miscibility and fast-solvation of the FA with chloroform solution dripping.Interestingly,this results in the desired morphology with refined phase-separated domain and vertical phase-separation structure to better balance the charge transport/collection and exciton dissociation.Consequently,the binary single junction OSCs based on PM6:Y6 blend reach champion power conversion efficiency(PCE)of 18.16%with SAA-LBL processing,which can be generally applicable to diverse systems,e.g.,the PM6:L8-BO-based devices and thick-film devices.The efficacy of SAA-LBL is confirmed in binary OSCs based on PM6:L8-BO,where record PCEs of 19.02%and 16.44%are realized for devices with 100 and 250 nm active layers,respectively.The work provides a simple but effective way to control the morphology for high-efficiency OSCs and demonstrates the SAA-LBL processing a promising methodology for boosting the industrial manufacturing of OSCs.

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.

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.

In vitro corrosion and antibacterial properties of layer-by-layer assembled GS/PSS coating on AZ31 magnesium alloys

To enhance the corrosion resistance of magnesium（Mg） alloy and to impart its surface with antibacterial functionality for inhibiting biofilm formation and biocorrosion, Mg（OH）2 films were fabricated on AZ31 magnesium alloy substrates by an in-situ hydrothermal method and well-defined multilayer coatings, consisting of gentamicin sulfate（GS） and poly（sodium 4-styrene sulfonate）（PSS）, were prepared via layer-by-layer（Lb L） assembly. The morphologies, chemical compositions and corrosion resistance of the obtained（PSS/GS）n/Mg sample were investigated using scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, electrochemical methods and immersion tests. Finally, the bactericidal activity of（PSS/GS）n/Mg samples against Staphylococcus aureus was assessed by the zone of inhibition methods and plate-counting method. The so-synthesized composite coating on the Mg alloy substrates exhibits good corrosion resistance and antibacterial performance, which make them attractive as coatings for medical implanted devices.

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.