Research on Strategies to Promote the Integration of Industrial Chain,Innovation Chain,and Supply Chain in the Beijing-Tianjin-Hebei Region

With the rapid development of international economic integration,industrial competition has gradually evolved from a competition of enterprise capabilities and resources to a game of comprehensive system collaboration capabilities among all participating parties.That is,the competition in the current international economy has evolved into an interactive and collaborative competition among the“three chains”of industry chain,capital chain,and innovation chain.Based on analyzing the current situation of the integration of the industrial chain,innovation chain,and supply chain,this article deeply analyzes the geographical advantages of the three chains in the Beijing-Tianjin-Hebei region.From the perspective of scientific and technological innovation and talent cooperation synergy,it proposes the integration strategy of the three chains in the Beijing-Tianjin-Hebei region.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

A Systematic Literature Review on Blockchain Consensus Mechanisms’ Security: Applications and Open Challenges

This study conducts a systematic literature review(SLR)of blockchain consensus mechanisms,an essential protocols that maintain the integrity,reliability,and decentralization of distributed ledger networks.The aim is to comprehensively investigate prominent mechanisms’security features and vulnerabilities,emphasizing their security considerations,applications,challenges,and future directions.The existing literature offers valuable insights into various consensus mechanisms’strengths,limitations,and security vulnerabilities and their real-world applications.However,there remains a gap in synthesizing and analyzing this knowledge systematically.Addressing this gap would facilitate a structured approach to understanding consensus mechanisms’security and vulnerabilities comprehensively.The study adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines and computer science standards and reviewed 3749 research papers from 2016 to 2024,excluding grey literature,resulting in 290 articles for descriptive analysis.The research highlights an increased focus on blockchain consensus security,energy efficiency,and hybrid mechanisms within 60%of research papers post-2019,identifying gaps in scalability,privacy,and interoperability for future exploration.By synthesizing the existing research and identifying the key trends,this SLR contributes to advancing the understanding of blockchain consensus mechanisms’security and guiding future research and structured innovation in blockchain systems and applications.

Applications and Challenges of Smart Technologies in Supply Chain Management

The advent of intelligent technologies in supply chain management(SCM)through the use of artificial intelligence(AI),the Internet of Things(IoT),blockchain,big data analytics,and others is a game changer.These improvements increase clarity,effectiveness,and flexibility,allowing companies to quickly deal with market changes and interruptions.Nevertheless,adopting such technologies comes with difficulties,such as information security,compatibility,exorbitant prices,and employee opposition.The applications of intelligent technologies for SCM are examined in this article,as well as the importance of their implementation and solutions that provide a competitive advantage for businesses.

Roller Screw and Threaded Chain Speed Reducer: An Experimental Evaluation

We are developing a speed reducer that can be considered a transformation of a worm gear reducer: the worm is replaced by an inverted roller screw, and the gear is replaced by a threaded chain drive. This configuration lessens wear, increases load capacity, and improves efficiency. The threaded chain consists of nut-shaped links. This paper presents the results of tests carried out on a prototype with a reduction ratio of 46.

Enhancing Enterprise Efficiency through Cross-Domain Supply Chain Linkage Management

In recent years,with the complexity and variability of international finance,debt,and geopolitical risks,the growth rate of domestic economic operations has slowed down.More enterprise groups are facing the transformation and upgrading from domestic leadership to internationalization,achieving revenue growth of nearly 10 billion yuan per year against the trend.The severe and complex internal and external environment has brought many challenges to the supply chain for enterprises.This article focuses on the goal of an“enterprise supply chain system focusing on value creation,strengthening system linkage,and improving overall chain efficiency,”aiming to find solutions to problems such as strong demand variability,frequent emergency needs,coexistence of project shortages and inventory surplus,long material turnover cycles,and high organizational complexity.By searching for key activities in the entire business chain of demand,design,production,service,and finance,implementing source planning,process control,system linkage,analysis and summary,and team collaboration,we have achieved more scientific demand forecasting,more accurate planning,more effective procurement cost reduction,more stable production performance supply,more convenient inventory sharing services,and more efficient integration of business and financial policies.

Suggestions on the Good Development of Pharmaceutical Cold Chain Logistics in China

Objective To study the characteristics and problems of the development of cold chain logistics in pharmaceutical industry,and to provide a reference for the development of China’s drug logistics.Methods Literature analysis was used to investigate the development of drug cold chain logistics,relevant laws and regulations,and policies in China.Then,the problems of industry development were summarized and some suggestions were put forward by referring to the mature concept of international drug cold chain logistics system.Results and Conclusion China’s cold chain logistics in pharmaceutical field is growing,but it is still in the development stage.By increasing government support,scientific research investment and professional training,the comprehensive strength of drug cold chain logistics can be improved to a certain extent,and the safety of drugs can be guaranteed for the people.

Research on the Application of Blockchain Technology in Cold Chain Logistics for Agricultural Products

With the continuous advancement of science and technology and the advent of the digital era,blockchain technology is increasingly demonstrating its great potential across various industries due to its unique features of decentralization,transparency,and immutability.In particular,in the cold chain logistics of agricultural products,the application of blockchain technology can not only enhance logistics efficiency but also ensure food safety and boost consumer trust[1].This paper first outlines the advantages of blockchain technology in cold chain logistics for agricultural products,and then clarifies the application pathways of blockchain technology in this field,providing a reference for relevant researchers.

Research on the High-Quality Development of Agricultural Supply Chain Financial Ecosystem Empowered by Science and Technology

A systematic perspective on agricultural supply chain finance can offer fresh insights into its development.The high-quality development of the agricultural supply chain finance ecosystem is crucial for the comprehensive revitalization of rural areas and the realization of agricultural power.Based on the current state of development of this ecosystem,this paper identifies several bottlenecks,such as insufficient policy and technical support in the macro-environment system,weak incentives for independent circulation within the industrial environment system,and inadequate motivation for stakeholders to participate in the micro-environment system.To address these issues,this paper proposes that the visualization,digitalization,and authenticity characteristics of the“blockchain+Internet of Things”technology architecture can effectively resolve these bottlenecks.Additionally,targeted strategies are suggested to promote the high-quality development of the agricultural supply chain finance ecosystem.

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.

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.

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.

Non-flammable long chain phosphate ester based electrolyte via competitive solventized structures for high-performance lithium metal batteries

Safety remains a persistent challenge for high-energy-density lithium metal batteries(LMBs).The development of safe and non-flammable electrolytes is especially important in harsh conditions such as high temperatures.Herein,a flame-retardant,low-cost and thermally stable long chain phosphate ester based(tributyl phosphate,TBP)electrolyte is reported,which can effectively enhance the cycling stability of highly loaded high-nickel LMBs with high safety through co-solvation strategy.The interfacial compatibility between TBP and electrode is effectively improved using a short-chain ether(glycol dimethyl ether,DME),and a specially competitive solvation structure is further constructed using lithium borate difluorooxalate(LiDFOB)to form the stable and inorganic-rich electrode interphases.Benefiting from the presence of the cathode electrolyte interphase(CEI)and solid electrolyte interphase(SEI)enriched with LiF and Li_(x)PO_(y)F_(z),the electrolyte demonstrates excellent cycling stability assembled using a 50μm lithium foil anode in combination with a high loading NMC811(15.4 mg cm^(-2))cathode,with 88%capacity retention after 120 cycles.Furthermore,the electrolyte exhibits excellent high-temperature characteristics when used in a 1-Ah pouch cell(N/P=0.26),and higher thermal runaway temperature(238℃)in the ARC(accelerating rate calorimeter)demonstrating high safety.This novel electrolyte adopts long-chain phosphate as the main solvent for the first time,and would provide a new idea for the development of extremely high safety and high-temperature electrolytes.

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.

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.

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.

Alkyl chain modulation of asymmetric hexacyclic fused acceptor synergistically with wide bandgap third component for high efficiency ternary organic solar cells

Herein,two asymmetric hexacyclic fused small molecule acceptors(SMAs),namely BP4F-HU and BP4F-UU,were synthesized.The elongated outside chains in the BP4F-UU molecule played a crucial role in optimizing the morphology of blend film,thereby improving charge mobility and reducing energy loss within the corresponding film.Notably,the PM6:BP4F-UU device exhibited a higher open-circuit voltage(V_(oc))of 0.878 V compared to the PM6:BP4F-HU device with a V_(oc)of 0.863 V.Further,a new wide bandgap SMA named BTP-TA was designed and synthesized as the third component to the PM6:BP4F-UU host binary devices,which showed an ideal complementary absorption spectrum in PM6:BP4F-UU system.In addition,BTP-TA can achieve efficient intermolecular energy transfer to BP4F-UU by fluorescence resonance energy transfer(FRET)pathway,due to the good overlap between the photoluminescence(PL)spectrum of BTP-TA and the absorption region of BP4F-UU.Consequently,ternary devices with 15wt%BTP-TA exhibits broader photon utilization,optimal blend morphology,and reduced charge recombination compared to the corresponding binary devices.Consequently,PM6:BP4F-UU:BTP-TA ternary device achieved an optimal power conversion efficiency(PCE)of 17.83%with simultaneously increased V_(oc)of 0.905 V,short-circuit current density(J_(sc))of 26.14 mA/cm^(2),and fill factor(FF)of 75.38%.

Earthquake disaster chain model based on complex networks for urban engineering systems

According to news reports on severe earthquakes since 2008,a total of 51 cases with magnitudes of 6.0 or above were analyzed,and 14 frequently occurring secondary disasters were identified.A disaster chain model was developed using principles from complex network theory.The vulnerability and risk level of each edge in this model were calculated,and high-risk edges and disaster chains were identified.The analysis reveals that the edge“floods→building collapses”has the highest vulnerability.Implementing measures to mitigate this edge is crucial for delaying the spread of secondary disasters.The highest risk is associated with the edge“building collapses→casualties,”and increased risks are also identified for chains such as“earthquake→building collapses→casualties,”“earthquake→landslides and debris flows→dammed lakes,”and“dammed lakes→floods→building collapses.”Following an earthquake,the prompt implementation of measures is crucial to effectively disrupt these chains and minimize the damage from secondary disasters.

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.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.