A Cross-Multi-Domain Trust Assessment Authority Delegation Method Based on Automotive Industry Chain

To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply relationships in the automotive market,improving data sharing and interactions across various platforms,and achieving more detailed integration of data and operations.We propose a trust evaluation permission delegation method based on the automotive industry chain.The proposed method combines smart contracts with trust evaluation mechanisms,dynamically calculating the trust value of users based on the historical behavior of the delegated entity,network environment,and other factors to avoid malicious node attacks during the permission delegation process.We also introduce strict control over the cross-domain permission granting and revocation mechanisms to manage the delegation path,prevent information leakage caused by malicious node interception,and effectively protect data integrity and privacy.Experimental analysis shows that this method meets the realtime requirements of collaborative interaction in the automotive industry chain and provides a feasible solution to permission delegation issues in the automotive industry chain,offering dynamic flexibility in authorization and scalability compared to most existing solutions.

An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this paper.XG-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for nodes.The XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping model.Among them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus results.In order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT communication.Finally,we evaluate the performance of XG-PBFT.The experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of nodes.The results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety problems.Our study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves conductivity.mPR-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain dispersion.Integrating this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 cycles.In situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen reactions.Ex situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability tests.The present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

WIN-WIN CHAINS

The philosophical concept of one bond connecting the world is an established scientific and economic phenomenon today.The global industrial and supply chains are symbols of that universal link of fraternity,cooperation and globalization.Despite a few major economies still trying to push forward a decoupling agenda and favoring a“small yard,high fence”strategy,globalization and cooperation remain a global trend.

Model-driven full system dynamics estimation of PMSM-driven chain shell magazine

Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.

Chain Elongation Using Native Soil Inocula:Exceptional n-Caproate Biosynthesis Performance and Microbial Mechanisms

This study demonstrates the feasibility and effectiveness of utilizing native soils as a resource for inocula to produce n-caproate through the chain elongation(CE)platform,offering new insights into anaerobic soil processes.The results reveal that all five of the tested soil types exhibit CE activity when supplied with high concentrations of ethanol and acetate,highlighting the suitability of soil as an ideal source for n-caproate production.Compared with anaerobic sludge and pit mud,the native soil CE system exhibited higher selectivity(60.53%),specificity(82.32%),carbon distribution(60.00%),electron transfer efficiency(165.00%),and conductivity(0.59 ms∙cm^(-1)).Kinetic analysis further confirmed the superiority of soil in terms of a shorter lag time and higher yield.A microbial community analysis indicated a positive correlation between the relative abundances of Pseudomonas,Azotobacter,and Clostridium and n-caproate production.Moreover,metagenomics analysis revealed a higher abundance of functional genes in key microbial species,providing direct insights into the pathways involved in n-caproate formation,including in situ CO_(2)utilization,ethanol oxidation,fatty acid biosynthesis(FAB),and reverse beta-oxidation(RBO).The numerous functions in FAB and RBO are primarily associated with Pseudomonas,Clostridium,Rhodococcus,Stenotrophomonas,and Geobacter,suggesting that these genera may play roles that are involved or associated with the CE process.Overall,this innovative inoculation strategy offers an efficient microbial source for n-caproate production,underscoring the importance of considering CE activity in anaerobic soil microbial ecology and holding potential for significant economic and environmental benefits through soil consortia exploration.

Underwater Image Transmission Method and Realization Based on Inductively Coupled Mooring Chain

Inductively coupled mooring chain transmission technology plays a crucial role in the long-distance online monitoring of marine hydrographic information.However,the impedance characteristics of the seawater medium pose a limitation on its capability to achieve high-speed real-time transmission of underwater images.In this paper,based on the principle of inductively coupled transmission for marine applications,the selected 1920×1080 pixel images are segmented,packaged,and then transmitted to the sending node using the user datagram protocol(UDP),and the modulation and demodulation of the transmitted images are realized using the orthogonal frequency division multiplexing(OFDM)algorithm of least squares(LS)estimation,and eight combinations with different mapping modes and coding rates are tested in the bandwidth of 200-800 k Hz and the quality of the transmitted images is evaluated using three criteria:mean squared error(MSE),peak signal to noise ratio(PSNR),and structural similarity index(SSIM).The results indicate that the image transmission quality is optimal when the mapping method is 16-quadrature amplitude modulation(16QAM),the coding rate is 1/2,and the center frequency is 800 k Hz.Under these conditions,the maximum transmission rate is 0.84 Mbit s^(-1),the SSIM criterion exceeds 0.91690 d B,and the learned perceptual image patch similarity(LPIPS)is less than 0.06000.This paper provides a solution for the underwater image transmission of inductively coupled mooring chains for marine applications.

Research on Alliance Decision of Dual-Channel Remanufacturing Supply Chain Considering Bidirectional Free-Riding and Cost-Sharing

This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.

Mathematical Modeling of Possibility Markov Chains by Possibility Theory

Statistical regression models are input-oriented estimation models that account for observation errors. On the other hand, an output-oriented possibility regression model that accounts for system fluctuations is proposed. Furthermore, the possibility Markov chain is proposed, which has a disidentifiable state (posterior) and a nondiscriminable state (prior). In this paper, we first take up the entity efficiency evaluation problem as a case study of the posterior non-discriminable production possibility region and mention Fuzzy DEA with fuzzy constraints. Next, the case study of the ex-ante non-discriminable event setting is discussed. Finally, we introduce the measure of the fuzzy number and the equality relation and attempt to model the possibility Markov chain mathematically. Furthermore, we show that under ergodic conditions, the direct sum state can be decomposed and reintegrated using fuzzy OR logic. We had already constructed the Possibility Markov process based on the indifferent state of this world. In this paper, we try to extend it to the indifferent event in another world. It should be noted that we can obtain the possibility transfer matrix by full use of possibility theory.

Trade credit contracting in a risk-averse supply chain under adverse selection and moral hazard

Trade credit,as an effective tool for integrating and coordinating material,information,and financial flows in supply chain management,is becoming increasingly widespread.We explore how a manufacturer can design optimal trade credit contracts when a risk-averse retailer hides its sales cost information(adverse selection)and selling effort level(moral hazard).We develop incentive models for a risk-averse supply chain when adverse selection and moral hazard coexist,which are then compared with the results under single information asymmetry(moral hazard).Moreover,we analyze the effects of private information and risk-aversion coefficient on contract parameters,selling effort level and the profit or utility of the supply chain.The study shows that when the degree of retailer’s risk aversion is within a certain range,reasonable trade credit contracts designed by the manufacturer can effectively induce the retailer to report its real sales cost and encourage it to exert appropriate effort.Furthermore,we find that the optimal trade credit period,optimal transfer payment,and retailer’s optimal sales effort level under dual information asymmetry are less than those under single information asymmetry.Numerical analysis are conducted to demonstrate the effects of the parameters on decisions and profits.

Supply Chain Management Analysis and Design for a Variety of Economic Scenarios, Including Data and System Administration

Due to the rapid progress of information technology, organizations anticipate significant changes in the planning, scheduling, and optimization aspects of operation and supply chain management (SCM) shortly. Two primary types of risk have an impact on supply chain management and design. The first group deals with the difficulties in matching supply and demand, whereas the second group deals with disruptions to regular business operations. The essay offers a theoretical framework that combines the cooperative efforts of risk assessment and mitigation, which are critical for effectively handling potential supply chain interruptions. This content provides insightful viewpoints on the strategic resources and operational structure needed to improve organizational success. We utilized the partial least squares (PLS) method to address the problem of multicollinearity and measurement mistakes in examining cause-and-effect constructs. The statistical method, Least Squares (PLS), used in structural equation modeling, is based on partial variance. The Partial Least Squares (PLS) strategy uses a two-stage estimate procedure to calculate weights, loadings, and route estimations. Initially, several simple and complex regressions were performed with the provided model. The procedure was repeated until a solution was found, resulting in a set of weights used to determine the latent variable scores. In the second step, non-iterative PLS regression yields loadings, path coefficients, mean scores, and location parameters. According to the structural study, implementing Sustainable Supply Chain Management (SSCM) can significantly improve a business’s operational and financial performance. The findings offer a comprehensive understanding of several elements of supply chain management (SSCM), including information systems, organizational configurations, supply chain network architecture (SCND), and supply chain strategy (SCS). The supply chain is essential for effectively moving goods over great distances and encouraging cooperation between parties. Therefore, these connections are established precisely, quickly, and cheaply via a knowledgeable and efficient supply chain. Two key components are necessary for a supply chain (SC) to be successful: efficient collaboration and the smooth integration of information-sharing platforms.

Supply chain coordination with inventory risk allocation

Unlike the traditional decentralized channel,the drop-shipping channel entails a retailer relaying consumers’orders to the manufacturer,which proceeds to stock the orders and directly ship them to the consumers.This study explores supply chain coordination and product quality in drop-shipping and traditional channels.Specifically,we analyze the performance of both channels under wholesale price and revenue-sharing contracts.Our study yields several key findings.First,the revenue-sharing contract can coordinate both traditional and drop-shipping channels,effectively increasing supply chain performance.Second,given the channel structure,the retailer prefers the wholesale price contract,whereas the manufacturer prefers the revenue-sharing contract.Third,product quality is higher in the drop-shipping channel when demand uncertainty is high.Finally,the implementation of the revenue-sharing contract increases product quality in the traditional channel,whereas it keeps product quality unchanged in the drop-shipping channel.

High-temperature resistant polymer nanocomposites with exfoliated organic-modified montmorillonite nanosheets strongly adsorbed on polymer chains

It has been demonstrated that almost all polymer-clay nanocomposites show higher temperature stability than that of pure polymer, which is attributed to the active exfoliated clay nanosheet firmly adsorbed onto the polymer chains, due to polerization and nucleation effect, the clay nanosheets could protect the polymer chains from destroying. To prove such mechanism, the water-soluble polymer nanocomposites(AAA/SLS-MMT) were synthesized by the in-situ polymerization of 2-acrylamide-2-methyl-propane sulfonic acid, acrylamide, 4-acryloylmorpholine, and organically modified montmorillonite. The techniques of nuclear magnetic resonance, atomic force microscopy and scanning electron microscopy etc., clearly characterized the successful synthesized of sample's structure, the exfoliated MMT nanosheet adsorbed polymer chain's scale, and well-dispersed morphology, espectively. The adsorption model, X-ray photoelectron spectroscopy presented the existence of strong adsorption, while molecular simulation calculations first concluded that the strong adsorption energy was-13032.06 kcal/mol. Thermo-gravimetric-analysis proved the temperature of maximum thermal degradation of powder sample(AAA/1.0 wt% SLS-MMT) was over 298℃. After ageing at 180℃ for 4 h, the apparent viscosity of 5 g/L AAA/1.0 wt% SLS-MMT aqueous solution was 326.7 mPa,s, while that of pure polymer(AAA) was only 8.3 mPa,s. This optimized sample has the smallest FLAPIvalue at all test temperatures from 180 to 220℃ in both fresh and salt water based drilling fluid. All the evidences of high temperature resistance indicate that the strong adsorption can enhance the thickness of hydrated shell and adsorption of clay particles in drilling fluid at high temperature. Such mechanism supplied the better way to design high-temperature resistant fluid loss additives for deep and ultra-deep oil and gas formation engineering.

Durable poly(binaphthyl-co-p-terphenyl piperidinium)-based anion exchange membranes with dual side chains

Building well-developed ion-conductive highways is highly desirable for anion exchange membranes(AEMs).Grafting side chain is a highly effective approach for constructing a well-defined phaseseparated morphological structure and forming unblocked ion pathways in AEMs for fast ion transport.Fluorination of side chains can further enhance phase separation due to the superhydrophobic nature of fluorine groups.However,their electronic effect on the alkaline stability of side chains and membranes is rarely reported.Here,fluorine-containing and fluorine-free side chains are introduced into the polyaromatic backbone in proper configuration to investigate the impact of the fluorine terminal group on the stability of the side chains and membrane properties.The poly(binaphthyl-co-p-terphenyl piperidinium)AEM(QBNp TP)has the highest molecular weight and most dimensional stability due to its favorable backbone arrangement among ortho-and meta-terphenyl based AEMs.Importantly,by introducing both a fluorinated piperidinium side chain and a hexane chain into the p-terphenyl-based backbone,the prepared AEM(QBNp TP-QFC)presents an enhanced conductivity(150.6 m S cm^(-1))and a constrained swelling at 80℃.The electronic effect of fluorinated side chains is contemplated by experiments and simulations.The results demonstrate that the presence of strong electro-withdrawing fluorine groups weakens the electronic cloud of adjacent C atoms,increasing OH^(-)attack on the C atom and improving the stability of piperidinium cations.Hence QBNp TP-QFC possesses a robust alkaline stability at 80℃(95.3%conductivity retention after testing in 2 M Na OH for 2160 h).An excellent peak power density of 1.44 W cm^(-2)and a remarkable durability at 80℃(4.5%voltage loss after 100 h)can be observed.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Global Industrial and Supply Chain Restructuring:Background,Characteristics and Development Trends

The restructuring of global industrial and supply chains is a hot issue in today’s world,and as a result of the once-in-a-century changes and intensified geopolitical and economic competition,the demand for global industrial and supply chain security has risen sharply,with government departments and transnational corporations(TNCs)becoming the most critical stakeholders.Governments carefully calibrate industrial and trade policies from the perspective of national strategies to create industrial chains that support national competitive advantages,and multinational corporations respond to geopolitical risks by prioritizing industrial and supply chain security and sustainability over capital and efficiency.Against the backdrop of changes unseen in a century,decelerating globalization and global economic downturn,the characteristics and future trends of global industrial and supply chain restructuring are worth paying attention to.

Supply Chain Cooperation between China and ASEAN:A Top-Down Approach

The significant relocation of supply chains from China to ASEAN countries did not start with the pandemic.China has been steadily increasing its investment in ASEAN's low valueadded manufacturing sector due to the region's comparative advantage in labor costs.In recent years,changing geopolitics and the restructuring of regional economies in the Asia-Pacific region have accelerated this relocation.

Is the Global Supply Chain Well-Connected? The “One Report and Two Indices” Provide the Answer

On November 26th,the second China International Supply Chain Promotion Expo(CISCE)featured a thematic event-the China Council for the Promotion of International Trade(CCPIT)Think Tank Exchange Activity and the“One Report and Two Indices”launch conference,which was held in Beijing.At the conference,the 2024 edition of the Global Supply Chain Promotion Report(hereinafter referred to as the“Report”),the Global Supply Chain Promotion Index(hereinafter referred to as the“Promotion Index”),and the Global Supply Chain Connection Index(hereinafter referred to as the“Connection Index”),jointly developed by the CCPIT Academy and the Financial Program Center of the China Central Radio and Television Station,were released for the first time,Leveraging Chinese wisdom to foster cooperation in the global supply chain.Ren Hongbin,Chairman of the CCPIT,attended the launch and delivered a speech,and Zhao Ping,Dean of the CCPIT Academy unveiled the“One Report and Two Indices”.

International Supply Chain Cooperation and China’s Role

In recent years,the challenges facing the development of international supply chains have been increasing.Major country competition,COVID pandemic and geopolitical conflicts have impacted the development of international supply chains and continue to have negative effects.Against this background,the international community should cooperate to deal with the risks and challenges.

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

The diversity of data sources resulted in seeking effective manipulation and dissemination.The challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of computing.One of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task.This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO performance.On the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain performance.The proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant features.To confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve Bayes.Moreover,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different datasets.The proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.