As there are numerous challenges to the global industrial and supply chains,the China International Supply Chain Expo(hereinafter referred to as the“CISCE”)hosted by the China Council for the Promotion of Internatio...As there are numerous challenges to the global industrial and supply chains,the China International Supply Chain Expo(hereinafter referred to as the“CISCE”)hosted by the China Council for the Promotion of International Trade(CCPIT),has been playing a unique role as a“stabilizer”for international cooperation,an“accelerator”for economic development,and a“booster”for future transformation.展开更多
Global coffee giant Starbucks has been rooted in the Chinese market for 26 years,committed to bringing high-quality products and excellent experiences to consumers.As an“old friend”of the China International Supply ...Global coffee giant Starbucks has been rooted in the Chinese market for 26 years,committed to bringing high-quality products and excellent experiences to consumers.As an“old friend”of the China International Supply Chain Expo(herei naf ter refer red to as the“CISCE”),Starbucks has participated in this event for two consecutive years and will draw a blueprint for the sustainable development of the coffee industry from the perspective of building a green industrial and supply chain at the 3rd CISCE.展开更多
The China International Supply Chain Expo is an important window through which to observe the trends of China's supply chain transformation.GEOPOLITICAL unrest,climate change challenges,and advances in digital tec...The China International Supply Chain Expo is an important window through which to observe the trends of China's supply chain transformation.GEOPOLITICAL unrest,climate change challenges,and advances in digital technology have reshaped the global supply chain in recent years.展开更多
We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and ext...We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and extending this analysis to larger spin chains,we demonstrate that mixed-state entanglement is profoundly shaped by both disorder and temperature.Our results reveal a sharp distinction between many-body localized and ergodic phases,with entanglement vanishing above diferent fnite temperature thresholds.Furthermore,by analyzing non-adjacent spins,we uncover an approximate exponential decay of entanglement with separation.This work advances the understanding of the quantum-to-classical transition by linking the entanglement properties of small subsystems to the broader thermal environment,ofering an explanation for the absence of entanglement in macroscopic systems.These fndings provide critical insights into quantum many-body physics,bridging concepts from thermalization,localization,and quantum information theory.展开更多
As the first national exhibition with the theme of supply chain,China International Supply Chain Expo(hereinafter referred to as the CISCE)has already become a key spot to observe the establishment of the Chinese ente...As the first national exhibition with the theme of supply chain,China International Supply Chain Expo(hereinafter referred to as the CISCE)has already become a key spot to observe the establishment of the Chinese enterprise industry chain.During the evolution of three CISCE,the leading dairy enterprise,Yili Group(hereinafter referred to as Yili),takes the practice of the entire industry chain as a sample,clearly outlining the development trajectory of China's dairy industry from“following”to“leading”.Its explorations of indust r ial chain col laborat ion,green transformation,and global layout are prominent.Therefore,providing a good paradigm for the high-quality development of the real economy.展开更多
Blockchain technologies have been used to facilitate Web 3.0 and FinTech applications.However,conventional blockchain technologies suffer from long transaction delays and low transaction success rates in some Web 3.0 ...Blockchain technologies have been used to facilitate Web 3.0 and FinTech applications.However,conventional blockchain technologies suffer from long transaction delays and low transaction success rates in some Web 3.0 and FinTech applications such as Supply Chain Finance(SCF).Blockchain sharding has been proposed to improve blockchain performance.However,the existing sharding methods either use a static sharding strategy,which lacks the adaptability for the dynamic SCF environment,or are designed for public chains,which are not applicable to consortium blockchain-based SCF.To address these issues,we propose an adaptive consortium blockchain sharding framework named ACSarF,which is based on the deep reinforcement learning algorithm.The proposed framework can improve consortium blockchain sharding to effectively reduce transaction delay and adaptively adjust the sharding and blockout strategies to increase the transaction success rate in a dynamic SCF environment.Furthermore,we propose to use a consistent hash algorithm in the ACSarF framework to ensure transaction load balancing in the adaptive sharding system to further improve the performance of blockchain sharding in dynamic SCF scenarios.To evaluate the proposed framework,we conducted extensive experiments in a typical SCF scenario.The obtained experimental results show that the ACSarF framework achieves a more than 60%improvement in user experience compared to other state-of-the-art blockchain systems.展开更多
The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver ...The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver operational improvements, the heightened interconnectivity introduces significant cybersecurity challenges, particularly within military logistics, where mission-critical operations and life-safety concerns are paramount. This paper examines these unique cybersecurity requirements, focusing on advanced persistent threats, supply chain poisoning, and data breaches that could compromise sensitive operations. The study proposes a hybrid cybersecurity framework tailored to military logistics, integrating resilience, redundancy, and cross-jurisdictional security measures. Real-world applicability is validated through simulations, offering strategies for securing supply chains while balancing security, efficiency, and flexibility.展开更多
Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researchin...Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.展开更多
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 rel...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.展开更多
China-Africa Economic and Trade Expo in Changsha showcases new momentum in industrial cooperation Machinery and related services took centre stage at the fourth China-Africa Economic and Trade Expo(CAETE),held in Chan...China-Africa Economic and Trade Expo in Changsha showcases new momentum in industrial cooperation Machinery and related services took centre stage at the fourth China-Africa Economic and Trade Expo(CAETE),held in Changsha,Hunan Province,this June,amid a push to deepen industrial chain cooperation across key sectors like infrastructure,energy and agriculture.Inside the expo venue,industry leaders,officials and entrepre-neurs engaged in intense discussions,and signed a series of agreements and memoranda which are set to spur a new momentum in China-Africa industrial collaboration.展开更多
“We gained a lot through participating last China International Supply Chain Expo(hereinafter referred to as the CISCE),which has provided strong support for IBIH’s development strategy of‘accelerating globalizatio...“We gained a lot through participating last China International Supply Chain Expo(hereinafter referred to as the CISCE),which has provided strong support for IBIH’s development strategy of‘accelerating globalization’.”Sun Ruping,Sales Director of IBlH Advanced Material(Henan)(hereinafter referred to as IBIH),said in an interview with China’s Foreign Trade.展开更多
Microbial chain elongation(CE),utilizing anaerobic fermentation for the synthesis of high-value medium chain fatty acids(MCFAs),merges as a promising strategy in resource sustainability.Recently,it has pivoted that th...Microbial chain elongation(CE),utilizing anaerobic fermentation for the synthesis of high-value medium chain fatty acids(MCFAs),merges as a promising strategy in resource sustainability.Recently,it has pivoted that the use of different types of additives or accelerantstowards enhancing the products yield and fermentation quality has got much attention,with carbon-based materials emerging as vital facilitators.Based on bibliometrics insights,this paper firstly commences with a comprehensive review of the past two decades’progress in applying carbon-based materials within anaerobic fermentation contexts.Subsequently,the recent advancements made by different research groups in order to enhance the performance of CE systemperformance are reviewed,with particular focus on the application,impact,and underlying mechanisms of carbon-based materials in expediting MCFAs biosynthesis via CE.Finally,the future research direction is prospected,aiming to inform innovative material design and sophisticated technological applications,as well as provide a reference for improving the efficiency of anaerobic fermentation of MCFAs using carbon-based material,thereby contributing to the broader discourse on enhancing sustainability and efficiency in bio-based processes.展开更多
Control Flow Graphs(CFGs)are essential for understanding the execution and data flow within software,serving as foundational structures in program analysis.Traditional CFG construction methods,such as bytecode analysi...Control Flow Graphs(CFGs)are essential for understanding the execution and data flow within software,serving as foundational structures in program analysis.Traditional CFG construction methods,such as bytecode analysis and Abstract Syntax Trees(ASTs),often face challenges due to the complex syntax of programming languages like Java and Python.This paper introduces a novel approach that leverages Large Language Models(LLMs)to generate CFGs through a methodical Chain of Thought(CoT)process.By employing CoT,the proposed approach systematically interprets code semantics directly from natural language,enhancing the adaptability across various programming languages and simplifying the CFG construction process.By implementing a modular AI chain strategy that adheres to the single responsibility principle,our approach breaks down CFG generation into distinct,manageable steps handled by separate AI and non-AI units,which can significantly improve the precision and coverage of CFG nodes and edges.The experiments with 245 Java and 281 Python code snippets from Stack Overflow demonstrate that our method achieves efficient performance on different programming languages and exhibits strong robustness.展开更多
Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have probl...Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.展开更多
Microbial consortia that catalyze chain elongation processes have been enriched using different selection strategies,for which the electron donor is an essential one.Propanol is an extraordinarily promising electron d...Microbial consortia that catalyze chain elongation processes have been enriched using different selection strategies,for which the electron donor is an essential one.Propanol is an extraordinarily promising electron donor because it can be generated from renewable resources,including lignocellulosic biomass and protein wastes.Here,propanol was proven in detail to be an efficient electron donor,enhancing the production of odd medium-chain carboxylates during chain elongation.By exploring various electron acceptors,reactor conditions,and electron donor/electron acceptor mol ratios,our study highlights that acetate is the most suitable electron acceptor for the production of both odd-and even-chain carboxylates.The optimal conditions for propanol-based chain elongation were 30℃ and pH 6,achieving 82.8%selectivity for odd-chain carboxylates.Another critical insight from our work is that a propanol/acetate mol ratio of 1:1 can minimize the inhibitory effect of propanol and maximize the yield of medium-chain carboxylates,with the highest concentration of n-heptanoate reaching 124.5 mmol C/L.This was further illustrated by 16S rRNA amplicon sequencing,which elucidated that the community composition and keystone species in a propanol-based reactor closely resembled that of the ethanol one.The dominant phylum of the propanol-based reactor,Firmicutes showed a significant positive correlation with the concentrations of n-caproate and n-valerate.Additionally,the co-occurrence of Clostridium sensu stricto 12 and Oscillibacter,known as typical chain elongators,was identified within the propanol-based reactor.These findings enhance our understanding of propanolbased chain elongation,offer guiding principles for reactor microbiota assembly,and support efficient odd medium-chain carboxylate production.展开更多
With the increasing importance of supply chain transparency,blockchain-based data has emerged as a valuable and verifiable source for analyzing procurement transaction risks.This study extends the mathematical model a...With the increasing importance of supply chain transparency,blockchain-based data has emerged as a valuable and verifiable source for analyzing procurement transaction risks.This study extends the mathematical model and proof of‘the Overall Performance Characteristics of the Supply Chain’to encompass multiple variables within blockchain data.Utilizing graph theory,the model is further developed into a single-layer neural network,which serves as the foundation for constructing two multi-layer deep learning neural network models,Feedforward Neural Network(abbreviated as FNN)and Deep Clustering Network(abbreviated as DCN).Furthermore,this study retrieves corporate data from the Chunghwa Yellow Pages online resource and Taiwan Economic Journal database(abbreviated as TEJ).These data are then virtualized using‘the Metaverse Algorithm’,and the selected virtualized blockchain variables are utilized to train a neural network model for classification.The results demonstrate that a single-layer neural network model,leveraging blockchain data and employing the Proof of Relation algorithm(abbreviated as PoR)as the activation function,effectively identifies anomalous enterprises,which constitute 7.2%of the total sample,aligning with expectations.In contrast,the multi-layer neural network models,DCN and FNN,classify an excessively large proportion of enterprises as anomalous(ranging from one-fourth to one-third),which deviates from expectations.This indicates that deep learning may still be inadequate in effectively capturing or identifying malicious corporate behaviors associated with distortions in procurement transaction data.In other words,procurement transaction blockchain data possesses intrinsic value that cannot be replaced by artificial intelligence(abbreviated as AI).展开更多
This study provides a detailed analysis of the application of blockchain and Internet of Things(IoT)technologies in various aspects of commodity management,addressing issues such as information asymmetry,data security...This study provides a detailed analysis of the application of blockchain and Internet of Things(IoT)technologies in various aspects of commodity management,addressing issues such as information asymmetry,data security and privacy challenges,insufficient supply chain transparency,and difficulties in regulation.The study also explores the challenges and strategies associated with the implementation of these technologies.Through this analysis,the article aims to provide theoretical support and practical reference for improving the efficiency and quality of commodity management,thereby promoting the digital transformation of commodity management.展开更多
This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain financ...This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.展开更多
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.展开更多
Granular sludges can resist the toxicity inhibition of medium-chain fatty acids(MCFAs)and enhance the chain elongation(CE)process.However,the granulation process is time-consuming and requires a suitable facilitating ...Granular sludges can resist the toxicity inhibition of medium-chain fatty acids(MCFAs)and enhance the chain elongation(CE)process.However,the granulation process is time-consuming and requires a suitable facilitating granulation mean.This study proposed two continuous fed Expanded Granular Sludge Bed bioreactors,one with electric field(EF)and one without,to demonstrate the promotion of sludge granulation by EF and the enhancement of MCFAs production efficiency by the anaerobic granular sludge(An GS).Through more than 50 days of operation,the EF was demonstrated to be able to promote the granulation,and the formed An GS enhanced MCFAs yield by 36%.Besides,mechanism analysis indicated that the EF promoted microbial aggregation and extracellular polymeric substances(EPS)synthesis,which enabled An GS to form more easily.Besides,An GS formed with EF improved extracellular electron transfer capacity and microbial function activity,which also contributed to the production of more MCFAs.Overall,this study provides a method to facilitate An GS granulation and revealed the underlying mechanisms,and offers important support for the diverse applications of An GS in other bioresources recovery bioprocesses.展开更多
文摘As there are numerous challenges to the global industrial and supply chains,the China International Supply Chain Expo(hereinafter referred to as the“CISCE”)hosted by the China Council for the Promotion of International Trade(CCPIT),has been playing a unique role as a“stabilizer”for international cooperation,an“accelerator”for economic development,and a“booster”for future transformation.
文摘Global coffee giant Starbucks has been rooted in the Chinese market for 26 years,committed to bringing high-quality products and excellent experiences to consumers.As an“old friend”of the China International Supply Chain Expo(herei naf ter refer red to as the“CISCE”),Starbucks has participated in this event for two consecutive years and will draw a blueprint for the sustainable development of the coffee industry from the perspective of building a green industrial and supply chain at the 3rd CISCE.
文摘The China International Supply Chain Expo is an important window through which to observe the trends of China's supply chain transformation.GEOPOLITICAL unrest,climate change challenges,and advances in digital technology have reshaped the global supply chain in recent years.
基金supported by the National Natural Science Foundation of China(Grant Nos.92365202,12475011,and 11921005)the National Key R&D Program of China(Grant No.2024YFA1409002)Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)。
文摘We investigate the mixed-state entanglement between two spins embedded in the XXZ Heisenberg chain under thermal equilibrium.By deriving an analytical expression for the entanglement of two-spin thermal states and extending this analysis to larger spin chains,we demonstrate that mixed-state entanglement is profoundly shaped by both disorder and temperature.Our results reveal a sharp distinction between many-body localized and ergodic phases,with entanglement vanishing above diferent fnite temperature thresholds.Furthermore,by analyzing non-adjacent spins,we uncover an approximate exponential decay of entanglement with separation.This work advances the understanding of the quantum-to-classical transition by linking the entanglement properties of small subsystems to the broader thermal environment,ofering an explanation for the absence of entanglement in macroscopic systems.These fndings provide critical insights into quantum many-body physics,bridging concepts from thermalization,localization,and quantum information theory.
文摘As the first national exhibition with the theme of supply chain,China International Supply Chain Expo(hereinafter referred to as the CISCE)has already become a key spot to observe the establishment of the Chinese enterprise industry chain.During the evolution of three CISCE,the leading dairy enterprise,Yili Group(hereinafter referred to as Yili),takes the practice of the entire industry chain as a sample,clearly outlining the development trajectory of China's dairy industry from“following”to“leading”.Its explorations of indust r ial chain col laborat ion,green transformation,and global layout are prominent.Therefore,providing a good paradigm for the high-quality development of the real economy.
基金supported by the National Key Research and Development Program of China (2022YFC3302300)National Natural Science Foundation of China under Grant (No.61873309,No.92046024,No.92146002)Shanghai Science and Technology Project under Grant (No.22510761000)。
文摘Blockchain technologies have been used to facilitate Web 3.0 and FinTech applications.However,conventional blockchain technologies suffer from long transaction delays and low transaction success rates in some Web 3.0 and FinTech applications such as Supply Chain Finance(SCF).Blockchain sharding has been proposed to improve blockchain performance.However,the existing sharding methods either use a static sharding strategy,which lacks the adaptability for the dynamic SCF environment,or are designed for public chains,which are not applicable to consortium blockchain-based SCF.To address these issues,we propose an adaptive consortium blockchain sharding framework named ACSarF,which is based on the deep reinforcement learning algorithm.The proposed framework can improve consortium blockchain sharding to effectively reduce transaction delay and adaptively adjust the sharding and blockout strategies to increase the transaction success rate in a dynamic SCF environment.Furthermore,we propose to use a consistent hash algorithm in the ACSarF framework to ensure transaction load balancing in the adaptive sharding system to further improve the performance of blockchain sharding in dynamic SCF scenarios.To evaluate the proposed framework,we conducted extensive experiments in a typical SCF scenario.The obtained experimental results show that the ACSarF framework achieves a more than 60%improvement in user experience compared to other state-of-the-art blockchain systems.
文摘The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver operational improvements, the heightened interconnectivity introduces significant cybersecurity challenges, particularly within military logistics, where mission-critical operations and life-safety concerns are paramount. This paper examines these unique cybersecurity requirements, focusing on advanced persistent threats, supply chain poisoning, and data breaches that could compromise sensitive operations. The study proposes a hybrid cybersecurity framework tailored to military logistics, integrating resilience, redundancy, and cross-jurisdictional security measures. Real-world applicability is validated through simulations, offering strategies for securing supply chains while balancing security, efficiency, and flexibility.
基金supported by the National Natural Science Foundation of China(Nos.U2244227,U2244226,42177172)the National Key R&D Program of China(No.2022YFC3004301)China Geological Survey Project(No.DD20230538)。
文摘Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.
基金funded by the Sichuan Science and Technology Program,Grant Nos.2024NSFSC0515,2024ZHCG0182 and MZGC20230013.
文摘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.
文摘China-Africa Economic and Trade Expo in Changsha showcases new momentum in industrial cooperation Machinery and related services took centre stage at the fourth China-Africa Economic and Trade Expo(CAETE),held in Changsha,Hunan Province,this June,amid a push to deepen industrial chain cooperation across key sectors like infrastructure,energy and agriculture.Inside the expo venue,industry leaders,officials and entrepre-neurs engaged in intense discussions,and signed a series of agreements and memoranda which are set to spur a new momentum in China-Africa industrial collaboration.
文摘“We gained a lot through participating last China International Supply Chain Expo(hereinafter referred to as the CISCE),which has provided strong support for IBIH’s development strategy of‘accelerating globalization’.”Sun Ruping,Sales Director of IBlH Advanced Material(Henan)(hereinafter referred to as IBIH),said in an interview with China’s Foreign Trade.
基金financially supported by the National Key R&D Program of China(No.2019YFC1906600)the National Natural Science Foundation of China(No.52000132).
文摘Microbial chain elongation(CE),utilizing anaerobic fermentation for the synthesis of high-value medium chain fatty acids(MCFAs),merges as a promising strategy in resource sustainability.Recently,it has pivoted that the use of different types of additives or accelerantstowards enhancing the products yield and fermentation quality has got much attention,with carbon-based materials emerging as vital facilitators.Based on bibliometrics insights,this paper firstly commences with a comprehensive review of the past two decades’progress in applying carbon-based materials within anaerobic fermentation contexts.Subsequently,the recent advancements made by different research groups in order to enhance the performance of CE systemperformance are reviewed,with particular focus on the application,impact,and underlying mechanisms of carbon-based materials in expediting MCFAs biosynthesis via CE.Finally,the future research direction is prospected,aiming to inform innovative material design and sophisticated technological applications,as well as provide a reference for improving the efficiency of anaerobic fermentation of MCFAs using carbon-based material,thereby contributing to the broader discourse on enhancing sustainability and efficiency in bio-based processes.
基金Supported by the National Natural Science Foundation of China(62462036,62262031)Jiangxi Provincial Natural Science Foundation(20242BAB26017,20232BAB202010)+1 种基金Distinguished Youth Fund Project of the Natural Science Foundation of Jiangxi Province(20242BAB23011)the Jiangxi Province Graduate Innovation Found Project(YJS2023032)。
文摘Control Flow Graphs(CFGs)are essential for understanding the execution and data flow within software,serving as foundational structures in program analysis.Traditional CFG construction methods,such as bytecode analysis and Abstract Syntax Trees(ASTs),often face challenges due to the complex syntax of programming languages like Java and Python.This paper introduces a novel approach that leverages Large Language Models(LLMs)to generate CFGs through a methodical Chain of Thought(CoT)process.By employing CoT,the proposed approach systematically interprets code semantics directly from natural language,enhancing the adaptability across various programming languages and simplifying the CFG construction process.By implementing a modular AI chain strategy that adheres to the single responsibility principle,our approach breaks down CFG generation into distinct,manageable steps handled by separate AI and non-AI units,which can significantly improve the precision and coverage of CFG nodes and edges.The experiments with 245 Java and 281 Python code snippets from Stack Overflow demonstrate that our method achieves efficient performance on different programming languages and exhibits strong robustness.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2025R97)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.
基金supported by the National Key R&D Program of China(No.2022YFC2105301)the National Natural Science Foundation of China(No.52270096).
文摘Microbial consortia that catalyze chain elongation processes have been enriched using different selection strategies,for which the electron donor is an essential one.Propanol is an extraordinarily promising electron donor because it can be generated from renewable resources,including lignocellulosic biomass and protein wastes.Here,propanol was proven in detail to be an efficient electron donor,enhancing the production of odd medium-chain carboxylates during chain elongation.By exploring various electron acceptors,reactor conditions,and electron donor/electron acceptor mol ratios,our study highlights that acetate is the most suitable electron acceptor for the production of both odd-and even-chain carboxylates.The optimal conditions for propanol-based chain elongation were 30℃ and pH 6,achieving 82.8%selectivity for odd-chain carboxylates.Another critical insight from our work is that a propanol/acetate mol ratio of 1:1 can minimize the inhibitory effect of propanol and maximize the yield of medium-chain carboxylates,with the highest concentration of n-heptanoate reaching 124.5 mmol C/L.This was further illustrated by 16S rRNA amplicon sequencing,which elucidated that the community composition and keystone species in a propanol-based reactor closely resembled that of the ethanol one.The dominant phylum of the propanol-based reactor,Firmicutes showed a significant positive correlation with the concentrations of n-caproate and n-valerate.Additionally,the co-occurrence of Clostridium sensu stricto 12 and Oscillibacter,known as typical chain elongators,was identified within the propanol-based reactor.These findings enhance our understanding of propanolbased chain elongation,offer guiding principles for reactor microbiota assembly,and support efficient odd medium-chain carboxylate production.
文摘With the increasing importance of supply chain transparency,blockchain-based data has emerged as a valuable and verifiable source for analyzing procurement transaction risks.This study extends the mathematical model and proof of‘the Overall Performance Characteristics of the Supply Chain’to encompass multiple variables within blockchain data.Utilizing graph theory,the model is further developed into a single-layer neural network,which serves as the foundation for constructing two multi-layer deep learning neural network models,Feedforward Neural Network(abbreviated as FNN)and Deep Clustering Network(abbreviated as DCN).Furthermore,this study retrieves corporate data from the Chunghwa Yellow Pages online resource and Taiwan Economic Journal database(abbreviated as TEJ).These data are then virtualized using‘the Metaverse Algorithm’,and the selected virtualized blockchain variables are utilized to train a neural network model for classification.The results demonstrate that a single-layer neural network model,leveraging blockchain data and employing the Proof of Relation algorithm(abbreviated as PoR)as the activation function,effectively identifies anomalous enterprises,which constitute 7.2%of the total sample,aligning with expectations.In contrast,the multi-layer neural network models,DCN and FNN,classify an excessively large proportion of enterprises as anomalous(ranging from one-fourth to one-third),which deviates from expectations.This indicates that deep learning may still be inadequate in effectively capturing or identifying malicious corporate behaviors associated with distortions in procurement transaction data.In other words,procurement transaction blockchain data possesses intrinsic value that cannot be replaced by artificial intelligence(abbreviated as AI).
文摘This study provides a detailed analysis of the application of blockchain and Internet of Things(IoT)technologies in various aspects of commodity management,addressing issues such as information asymmetry,data security and privacy challenges,insufficient supply chain transparency,and difficulties in regulation.The study also explores the challenges and strategies associated with the implementation of these technologies.Through this analysis,the article aims to provide theoretical support and practical reference for improving the efficiency and quality of commodity management,thereby promoting the digital transformation of commodity management.
基金an initial outcome of the Research on the Trust Mechanism of Agricultural Supply Chain Financing in the Context of “Blockchain+Supply Chain” Integrated Governance (Project No:20AGL021)a key project under the National Social Science Fund of China (NSSFC)+3 种基金the Research on the Trust Mechanism of Online Bank Lending System Based on Online Social Capital of Long-tail Rural Households (Project No:19BGL155)a project under the NSSFCthe Research on the Cost Formation Mechanism of Data Factor Transactions and the Design of Transaction Mechanism (Project No:23CJY068)a youth project under the NSSFC
文摘This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
基金supported by the Natural Science Foundation of Heilongjiang Province(No.LH2023E051)Open Project of State Key Laboratory of Urban Water Resource and Environment(No.HC202241)Young Scientist Studio of Harbin Institute of Technology。
文摘Granular sludges can resist the toxicity inhibition of medium-chain fatty acids(MCFAs)and enhance the chain elongation(CE)process.However,the granulation process is time-consuming and requires a suitable facilitating granulation mean.This study proposed two continuous fed Expanded Granular Sludge Bed bioreactors,one with electric field(EF)and one without,to demonstrate the promotion of sludge granulation by EF and the enhancement of MCFAs production efficiency by the anaerobic granular sludge(An GS).Through more than 50 days of operation,the EF was demonstrated to be able to promote the granulation,and the formed An GS enhanced MCFAs yield by 36%.Besides,mechanism analysis indicated that the EF promoted microbial aggregation and extracellular polymeric substances(EPS)synthesis,which enabled An GS to form more easily.Besides,An GS formed with EF improved extracellular electron transfer capacity and microbial function activity,which also contributed to the production of more MCFAs.Overall,this study provides a method to facilitate An GS granulation and revealed the underlying mechanisms,and offers important support for the diverse applications of An GS in other bioresources recovery bioprocesses.
