Digital Science
type: channel
publisher: Digital science
language: en
publication name: Digital Science
issn: 3006-0753
items: Theoretical Research on Time Scaling in Multi-layer Electronic Systems-Exploring Huawei's "Ta (τ) Law"
items: https://d-sci.org/index.php/dsci/article/view/44
items: The AI-Driven Resilience Engine: Research on the Framework Construction and Behavioral Logic of BCM Agents
items: Research on Data Intellectual Property Protection and Value Assessment in the AI Era: A Tri-Jurisdictional Comparative Study of China, the United States, and the European Union
items: Application scenarios of Chinese language teaching and research supported by digital technology
items: A Formal Investigation of Tau (τ) Scaling Theory for Multi-Layer Electronic Systems
items: Enterprise Management Information Systems and Their Improvement
items: Path Exploration for the Construction of China-Russia Cross-Border Language Service System Against the Belt and Road Initiative: A Digital-Driven Perspective
items: Research on the Application of Artificial Intelligence Models in Smart Energy and Carbon Emission Systems
items: Interpreting Standardization Readiness Levels for Chip R&D: Comparative Analysis and Dynamic Evolution Model Based on the NIST Framework
items: In-depth Analysis of Practical Application of Intelligent Manufacturing Capability Maturity Model: An Empirical Study Based on the IRaD Paradigm
items: Research on the Integration of Artificial Intelligence and Zero-Emission Technology in the Era of Digital Economy
items: https://d-sci.org/index.php/dsci/article/view/32
items: Research on Smart Agricultural Technology and Standardization of High-standard Farmland in Belarus
items: Research on Key Technologies for Analyzing High-efficiency Low-carbon Intelligent Irrigation Decision-making
items: Research on China-Belarus Trade Services in the Era of New Quality Productivity
items: From Atomic Structure to Multidimensional Isomeric Space: Exploring Unknown Dimensions of Life and Consciousness
items: Exploring the Integration Research of Carbon Trading and RWA Technology
items: Analysis of the composition and condition of the Chinese railway transport
items: Vision-Radar Fusion for UAV Perception in Low-Altitude Emergency Rescue: A Survey
items: The State of Enterprise-Level AI Commercialization in China: Insights from 2025 Trends and Global Comparisons
items: Multimodal Large Models-Driven Precise Perception in Complex Low-Altitude UAV Environments: A Survey on Adaptive Edge Intelligence and Swarm Collaboration
items: Consumption Trends in Science and Technology-Based Anti-Aging Products Among Oriental Women: A Systematic Review
items: Advances in Cross-Source Intelligent Security Monitoring and Resilience Strategies for Urban Cyber-Physical Power Systems: A Comprehensive Review
items: A Survey on Integrated Training-Inference Architectures for Large Language Models on Multi-GPU Stream Processors
items: Trade and Economic Cooperation Between the People's Republic of China and the EAEU Countries in the Framework of Resolving the Problem of Food Security
items: Impact of digital currency on China's traditional financial system
items: A Unified Spatio-Temporal Data Organization Model for Forest and Grassland Resources Based on GeoSOT Encoding
items: From Atomic Structure to the Dream World: Exploring the Unknown Dimensions of Life and Consciousness
items: A Brief Discussion on the Value Representation of Digital Assets in Different Periods

Theoretical Research on Time Scaling in Multi-layer Electronic Systems-Exploring Huawei's "Ta (τ) Law"
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description: Over the past six decades, the semiconductor industry has advanced through the geometric scaling paradigm of Moore's Law—achieving smaller transistors, higher integration density, and lower unit costs. However, as manufacturing processes approach dual physical and economic ceilings (post-7 nm technology sees rising transistor costs instead of falling reductions, while EUV depreciation dominates wafer costs), the marginal returns of purely "size reduction" strategies have sharply declined. In 2026, Hua Weitingbo's team formally proposed the "Tau Scaling Theory (τ Scaling/Time Scaling Theory for Multi-Layer Electronic Systems)," advocating systematic time-scale compression using the time constant τ as the unified optimization goal across multiple system layers—from picosecond-level transistor switching to second-level system loads spanning approximately 12 orders of magnitude. Building on this theoretical framework and industrial context, this paper rigorously establishes a hierarchical time-scale decomposition model for multi-layer electronic systems, derives τ expressions and scaling relationships at each layer, and validates through MATLAB numerical simulations: when geometric scaling reaches its limit, equivalent system performance can still exhibit nearly exponential growth by leveraging four key strategies—parasitic reduction, logic folding (key path shortening), 3D interconnect topology optimization, and full-stack co-scheduling—to compress τ. This paper simultaneously establishes a conceptual framework linking τ scaling with classical Dennard scaling, the Rent rule, and the RC delay model, while providing a quantitative discussion on the applicable boundaries of this paradigm.
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creator: Siyi Zeng
creator: Chaoqun Zhang
creator: Wulong Gao
rights: Copyright (c) 2026 Siyi Zeng, Chaoqun Zhang, Wulong Gao (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/84p46s60

https://d-sci.org/index.php/dsci/article/view/44
type: item
title: The Incorporation of Cryptocurrencies into International Balance of Payments Statistics and the Challenges to Monetary Policy Independence in Major Economies: A Comparative Analysis Based on the IMF (BPM7/2025 SNA) Framework – The Paths of the Federal Res
description: This paper elevates the question of "whether and how encrypt assets enter the Balance of Payments (BOP) and International Investment Position (IIP)" from an accounting technical issue to a practical implication for the monetary policy independence (MPI) of major economies. The central thesis is that when a category of cross-border "quasi-currency/quasi-asset" can be held by both residents and non-residents yet remains largely invisible within traditional correspondent banking systems, it not only distorts capital account signals and affects foreign exchange/reserve management logic, but also partially "externalizes" private credit creation and redemption risks onto central bank balance sheets and liquidity management boundaries through the coupling of stablecoins and short-term government financing markets. The paper first examines the IMF's latest statistical framework (BPM7/2025 SNA framework, with GN F.18 classification gradually converging toward the treatment of "liabilities = financial assets / no corresponding liabilities = non-productive non-financial assets"), then uses published cross-border flow and stablecoin contagion evidence from the BIS and the New York Fed to demonstrate that even if "Bitcoin-like assets" do not become reserve assets, they can still undermine the stability of the MPI transmission mechanism— "interest rate–exchange rate–capital flows" —by altering net errors and omissions (NEOs) in capital accounts, shadow exchange demands, and regulatory arbitrage channels. The approach to adopting "stablecoin-like instruments" (liability-bearing financial instruments) directly determines whether monetary sovereignty is replaced by private dollar or offshore fiat currencies. The analysis then compares the Federal Reserve (with its market infrastructure development, banking supervision mechanisms, and the trend toward using stablecoins as payment instruments) with the European Central Bank (through its defensive unified MiCA legislation, euro anchori…
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creator: Kevin Augusto
rights: Copyright (c) 2026 Kevin Augusto (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/s17r8m63

The AI-Driven Resilience Engine: Research on the Framework Construction and Behavioral Logic of BCM Agents
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description: With the deepening of digital transformation, the business environment and cybersecurity threats faced by enterprises are becoming increasingly complex and volatile. Traditional Business Continuity Management (BCM) models, which rely heavily on manual labor and passive response, can no longer meet organizations' urgent demand for "resilience." The explosion of Generative Artificial Intelligence (GenAI) and Agent technologies provides a novel paradigm for the intelligent and automated reconstruction of BCM. This paper takes the "BCM Agent Framework and Behavioral Logic Diagram" as its research object, systematically deconstructing its core closed-loop logic of "Continuous Perception, Generating Recommendations, Guiding Actions, Validating Capabilities, and Promoting Growth." Firstly, the paper analyzes the pain points of digital transformation currently facing BCM. Secondly, it deeply dissects the seven-layer architecture system of the BCM Agent, focusing on the core engine's seven capability modules, the structured precipitation mechanism of the organizational memory base, and the seven-step closed-loop behavioral logic from perception to capability enhancement. Thirdly, combining the latest practical cases in the financial industry and intelligent operations, it demonstrates the core value of AI-BCM Agents in risk prediction, automated emergency response, and cross-departmental collaboration. Finally, drawing on research results from core journals in the past three years, this paper proposes future trends and governance challenges for BCM Agents, providing theoretical references and practical pathways for enterprises to build a "trustworthy, visible, and controllable" digital resilience system
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creator: Wulong Gao
rights: Copyright (c) 2026 Wulong Gao (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/v9pyzt65

Research on Data Intellectual Property Protection and Value Assessment in the AI Era: A Tri-Jurisdictional Comparative Study of China, the United States, and the European Union
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description: As artificial intelligence reshapes the global economic infrastructure, data has ascended from a by-product of digital activity to the primary factor of production in the twenty-first century. Yet the very legal regimes tasked with protecting data-derived value remain profoundly fragmented. This paper conducts a comparative institutional analysis of how China, the United States, and the European Union construct data intellectual property (IP) protection frameworks, and how those divergent architectures interact with market mechanisms for valuing data assets. Drawing on three paradigmatic cases—(1) hiQ Labs v. LinkedIn (U.S.), (2) the EU's sui generis database right regime under the Database Directive and subsequent Data Act reform, and (3) China's emerging data-IP registration pilot system exemplified by the Shanghai and Zhejiang platform-data disputes—this study identifies systematic patterns: the U.S. relies on a decentralized, litigation-driven mosaic (trade secrets, CFAA, contract, copyright) that maximizes allocative flexibility at the cost of transactional uncertainty; the EU deploys a rights-centric, regulatory-dense architecture (database right + GDPR + Data Act) that secures individual and producer protections but imposes heavy compliance frictions on data monetization; and China pursues a state-guided, registration-enabled property-rights experiment ("three-rights" bifurcation + data IP pilots) designed to engineer a tradable data-asset class from above. The paper then develops an interaction-mechanism framework showing how each jurisdiction's legal DNA shapes which valuation methodologies (cost / income / market) dominate, what discount rates the market applies, and where liquidity emerges or stalls. Business and policy implications are drawn for firms operating across jurisdictions in the AI supply chain.
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creator: Ben・Anle Augusto
rights: Copyright (c) 2026 Ben・Anle Augusto (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/556p6296

Application scenarios of Chinese language teaching and research supported by digital technology
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description: Based on the "Teacher Professional Development" dimension of the "Teacher Digital Literacy" educational industry standard released by the Ministry of Education in 222, and relying on the "AI-empowered" digital technology system, this paper explores three digital application scenarios for primary school Chinese teaching and research: the personal reflection—self-observation promoting teaching improvement; the team teaching and research scenario—data interpretation guiding targeted discussion; and the archive construction scenario—classroom slicing mapping out the growth trajectorydigital technology
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creator: Hui Li
rights: Copyright (c) 2026 Hui Li (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/9t1bb683

A Formal Investigation of Tau (τ) Scaling Theory for Multi-Layer Electronic Systems
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description: The semiconductor industry has relied on geometric scaling—the relentless reduction of transistor feature sizes—as its primary performance engine for over half a century, epitomized by Moore's Law. Yet as physical and economic barriers converge below the ∼3 nm frontier, the classical Dennard scaling framework has collapsed, and the marginal return on pure dimensional shrink has entered a regime of steeply diminishing returns. Against this backdrop, the recently articulated Tao (τ) Scaling Law (He, IEEE ISCAS 2026) proposes a paradigm shift: replace "how small can we make it?" with "how fast can the entire layered stack operate?", using the time constant τ as a universal, cross-hierarchical optimization metric that spans device physics, circuit topology, chip architecture, and system-level interconnect. This paper provides the first independent, formally grounded mathematical treatment of τ-scaling theory for multi-layer electronic systems. We construct a four-tier hierarchical delay decomposition model—device (ℓ = 0) → gate/interconnect (ℓ = 1) → functional block/chip (ℓ = 2) → system (ℓ = 3)—and derive closed-form expressions for how τ propagates upward through each layer under both classical geometric scaling and the proposed τ-multi-lever regime (logic folding, vertical integration, RC-minimizing topologies, full-stack scheduling). We then execute a parametric MATLAB simulation campaign across 10 generational steps with Monte Carlo variation, comparing three strategy families: (A) pure geometric shrink, (B) stagnation-with-τ-levers, and (C) a hybrid optimal control policy. Our results yield three non-obvious findings: 1. τ-scaling is not a replacement for device-level innovation but a reallocation: it shifts the dominant delay term from irreducible intrinsic switching to topological and communicational terms, meaning its efficacy is bounded by Rent's Rule exponents and thermal constraints on 3D stacking density. 2. We derive a critical fold ratio λ\* ≈ 1.22 per g…
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creator: Tsang Heric
rights: Copyright (c) 2026 Tsang Heric (Author)
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/mwkdtw31

Enterprise Management Information Systems and Their Improvement
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description: The basic functions of the management information system: data collection and input, responsible for data storage, responsible for information transmission in the system, data processing, model establishment, solution, application and modification, output information, provide information to all management levels, support decision-making, and management and maintenance of the management information system itself. The latter is mainly based on the structured system specification, mainly including system analysis, system design and so on.As we all know, management information system is a science formed on the basis of management science, system science, information science and computer science in order to meet the needs of modern management. It studies the whole process of information processing and decision-making in management system, and discusses the implementation method of computer. It is a system composed of human, computer, communication equipment and other hardware and software, which can collect, process, store, transmit, maintain and use management information. Management information system can promote enterprises to develop in the direction of information, make enterprises in a virtuous circle of sensitive information, scientific management and accurate decision-making, and bring higher economic benefits to enterprises. Therefore, management information system is an important symbol of enterprise modernization and an only way for enterprise development.Information system is widely used in the management of various affairs, which promotes the improvement of enterprise management. Management information system serves for management. Its development and establishment is an effective way for enterprises to get rid of backward management methods and realize management modernization. The management information system unifies, standardizes and modernizes the management work, greatly improves the efficiency of management, and makes the modern management form a unif…
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creator: Linyun Diao
rights: Copyright (c) 2026
date: 2026-06-04
publication date: 2026-06-04
doi: 10.62306/59pwq909

Path Exploration for the Construction of China-Russia Cross-Border Language Service System Against the Belt and Road Initiative: A Digital-Driven Perspective
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description: Amid the high-quality development of the Belt and Road Initiative (BRI) and its in-depth alignment with the Eurasian Economic Union, China-Russia cross-border cooperation in economy, trade, culture and infrastructure has entered a new stage. Cross-border language services, as a core medium of bilateral exchanges, are critical to breaking language barriers and facilitating connectivity. However, traditional China-Russia cross-border language services are plagued by fragmented supply, low efficiency and weak professional adaptability, which can no longer match the digital trend of cross-border cooperation. From the perspective of digital empowerment, this paper clarifies the theoretical connotation of cross-border language service system, analyzes the current development and practical dilemmas of China-Russia cross-border language services, and explores digital-driven construction paths from five dimensions: top-level planning, platform building, talent cultivation, technological innovation and governance improvement. The study finds that digital technologies including artificial intelligence, big data and blockchain can reshape the supply model of cross-border language services, resolve traditional bottlenecks, and build an integrated, intelligent and standardized service ecosystem. This research enriches the theoretical research on cross-border language services under the BRI, and provides practical references for upgrading China-Russia cross-border cooperation and advancing the internationalization of language service industry
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creator: Jiang Yang
rights: Copyright (c) 2026
date: 2026-05-16
publication date: 2026-05-16
doi: 10.62306/edx4v796

Research on the Application of Artificial Intelligence Models in Smart Energy and Carbon Emission Systems
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description: At this critical juncture of advancing the "dual carbon" goals and transforming energy structures, the efficient coordination between smart energy systems and carbon emission monitoring systems serves as the cornerstone for implementing green development concepts and achieving sustainable growth. Artificial intelligence technologies, with their robust data processing capabilities, deep feature extraction, and intelligent decision-making prowess, offer innovative solutions to address persistent challenges in traditional energy systems—including low energy efficiency, insufficient carbon emission monitoring accuracy, and supply-demand imbalance. This study systematically examines the application status of mainstream AI models (including machine learning, deep learning, and reinforcement learning) across the entire smart energy production, transmission, and consumption chain, as well as carbon emission accounting, monitoring, and optimization processes. It thoroughly analyzes core issues such as data heterogeneity, model generalization limitations, and inadequate technological integration, while exploring practical scenarios through case studies to demonstrate the effectiveness of different AI models. Finally, the research outlines future trends in deep integration between AI and smart energy systems/carbon monitoring systems, proposing targeted optimization pathways and implementation strategies. These insights provide theoretical foundations and practical references for accelerating digital transformation in energy systems, enhancing precision carbon management, and facilitating the realization of "dual carbon" objectives
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creator: Weihan Wang
rights: Copyright (c) 2026 Weihan Wang (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/vcc9y331

Interpreting Standardization Readiness Levels for Chip R&D: Comparative Analysis and Dynamic Evolution Model Based on the NIST Framework
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description: The Standardization Readiness Level (SRL) in chip development serves as a critical metric for evaluating the transformation of technological achievements into industry standards. This study focuses on the 2026 "Summary Report on Chip Development Standardization Readiness Levels" (hereinafter referred to as the "NIST Report") published by the National Institute of Standards and Technology (NIST), systematically analyzing its SRL framework design logic, hierarchical definitions, and implementation processes. By comparing the supporting standard system of the EU's "European Chips Act" with the standardization framework of Japan's Ministry of Economy, Trade and Industry (METI) "Semiconductor Strategy 2.0," the study reveals similarities and differences in SRL practices across different institutional environments. Furthermore, a three-dimensional dynamic evolution model integrating "technology-industry-policy" dimensions is constructed to simulate SRL progression throughout the entire chip development lifecycle. Findings indicate that the NIST framework centers on "collaborative validation," achieving closed-loop management from concept to standardization through five-tiered hierarchical structures. The EU system emphasizes cross-border resource integration but faces limitations in decision-making efficiency, while the Japanese framework prioritizes corporate leadership but encounters international compatibility challenges. Dynamic modeling demonstrates that policy support and industrial collaboration serve as core drivers for SRL upgrades. This study provides theoretical references and practical guidance for optimizing standardization strategies among chip development stakeholders and enhancing standard systems for policymakers
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creator: Fanyang Zeng
creator: Cong Bo
rights: Copyright (c) 2026 Fanyang Zeng, Cong Bo (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/xnr8xn54

In-depth Analysis of Practical Application of Intelligent Manufacturing Capability Maturity Model: An Empirical Study Based on the IRaD Paradigm
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description: Against the macro background of accelerated digital transformation in global manufacturing and the in-depth implementation of China's "Manufacturing Power" strategy, the Intelligent Manufacturing Capability Maturity Model (IMMCM) has become a core tool for manufacturing enterprises to evaluate transformation progress and optimize resource allocation. However, existing academic research is mostly limited to interpreting standard texts or qualitative descriptions of individual enterprises, lacking quantitative validation based on large-sample data and cross-industry heterogeneity analysis. To address this, this study adopts the IMRaD (Introduction, Methods, Results, and Discussion) standard academic paradigm to construct an IMMCM evaluation index system integrating four dimensions: "personnel, technology, resources, and manufacturing," and introduces an improved AHP-entropy weighting method for combined weighting. The study selects 120 large-scale enterprises in China's electronic components and high-end equipment manufacturing industries as empirical samples, with data sources covering the National Bureau of Statistics Industrial Enterprise Database (2023-2025) and the National Industrial Information Security Development Research Center Intelligent Manufacturing Evaluation Platform. Through multiple regression analysis and structural equation modeling (SEM), the causal relationship between IMMCM and operational performance index (OPI) is empirically examined. The research findings demonstrate: (1) The IMMCM composite score exhibits a significant positive correlation with corporate operational performance (β=0.732, p<0.01), indicating that enhanced maturity levels directly translate into economic benefits; (2) Hierarchical regression analysis reveals that the foundational resource layer (equipment connectivity rate and data collection rate) and system integration layer (MES/ERP integration degree) demonstrate the strongest explanatory power for performance metrics (R²…
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creator: Gang Zhao
creator: Tao Lan
rights: Copyright (c) 2026 Gang Zhao, Tao Lan (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/0s2kzk47

Research on the Integration of Artificial Intelligence and Zero-Emission Technology in the Era of Digital Economy
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description: Against the dual backdrop of digital economy permeating all global socio-economic sectors and carbon neutrality goals becoming a worldwide consensus, the deep integration of artificial intelligence (AI) and zero-emission technologies has emerged as a pivotal pathway to drive industrial green transformation, address energy-environmental challenges, and achieve high-quality sustainable development. Grounded in the technological characteristics and development trends of the digital economy era, this study systematically analyzes the intrinsic logic and core mechanisms of AI-zero emission technology convergence. It examines practical applications and implementation outcomes in key sectors including energy, industry, construction, and transportation, while conducting in-depth analysis of current challenges such as computational energy consumption, technical barriers, data silos, and institutional deficiencies. Targeted optimization strategies are proposed encompassing technological breakthroughs, system architecture development, policy safeguards, and ecosystem cultivation. The research aims to provide theoretical foundations and practical references for deepening AI-zero emission technology integration, advancing zero-carbon society construction, and achieving coordinated progress between economic development and ecological conservation
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creator: Fanyang Zeng
rights: Copyright (c) 2026 Fanyang Zeng (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/0mmw7z76

https://d-sci.org/index.php/dsci/article/view/32
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title: Research on the Economic Benefits of Supply Chain Business Process Modeling for the China-Europe Railway Express in the China-Belarus Industrial Park: A Quantitative Assessment Based on Logistics Efficiency Improvement
description: As the core vehicle of the "Belt and Road" initiative, the China-Europe Railway Express has profoundly transformed the operation model of transnational supply chains by reconstructing the Eurasian continental logistics network. Taking the China-Belarus Industrial Park as a typical case, this study constructs a supply chain business process framework based on the SCOR model and systematically evaluates the economic impact of the China-Europe Railway Express on supply chain optimization in the park during 2015-2022 by employing quantitative methods such as DEA efficiency evaluation, difference-in-differences (DID), cost-benefit analysis, and CGE simulation. The study finds that: 1.Logistics efficiency has been significantly improved: average transportation time reduced by 48.3% (32.5 days to 16.8 days), unit logistics cost decreased by 32.7% (280 USD to 188 USD/ton), and on-time performance rate increased to 95.6% (+22.3 percentage points). 2.Quantitative results of economic benefits: Direct cost savings of $110.4 million (cumulative 2015-2022) Time value of income: $6.192 million Trade growth contributed $280 million Industrial cluster effect drives $1.2 billion in investment 3.Heterogeneity analysis revealed that cost savings accounted for 35% in electronics enterprises, while biopharmaceutical companies reduced quality losses by 20% due to improved reliability. 4.CGE simulation prediction: By 2030, a 50% increase in train frequency would generate an additional economic benefit of $320 million. This study innovatively combines business process modeling with empirical analysis of multi-method integration, providing micro-level decision support for "Belt and Road" logistics cooperation and offering a new perspective for global supply chain resilience research.
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creator: OMELYANYUK• Alexander •Mikhailovich
creator: FanYang Zeng
creator: Chaoqun Zhang
rights: Copyright (c) 2026 OMELYANYUK• Alexander •Mikhailovich, FanYang Zeng, Chaoqun Zhang (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/vnrpfd15

Research on Smart Agricultural Technology and Standardization of High-standard Farmland in Belarus
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description: Belarus (hereinafter referred to as "Belarus") stands as a traditional agricultural powerhouse in Central and Eastern Europe, where agriculture serves as the cornerstone of its national economy. Leveraging its unique black soil resources and well-developed agricultural infrastructure, Belarus is progressively transitioning its production model toward scaling, intensification, and intelligentization. The adoption of smart agriculture technologies and standardized construction of high-standard farmland represent core strategies for overcoming agricultural efficiency bottlenecks, ensuring regional food security, and enhancing international competitiveness. This study employs literature review, field research (with case studies from Belarus 'major agricultural regions), and comparative analysis to systematically examine the current development status, application scenarios, and core advantages of smart agriculture technologies in Belarus. It delves into the standardized system framework for high-standard farmland management spanning planning, construction, maintenance, and utilization, explores integration pathways between smart agriculture technologies and standardized farmland development while identifying existing challenges. Practical optimization strategies are proposed based on Belarus' agricultural realities, providing theoretical references and practical insights for China and other countries advancing smart agriculture and high-standard farmland development. Research indicates that Belarus has established a preliminary smart agriculture technology system encompassing precision sowing, intelligent irrigation, green pest control, and smart agricultural machinery. Standardized farmland construction has developed clear norms in critical aspects such as land consolidation, facility integration, and soil improvement. However, significant gaps persist in integration depth, technological implementation effectiveness, and professional talent support. To promote deep int…
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creator: Chaoqun Zhang
rights: Copyright (c) 2026 Chaoqun Zhang (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/x5rr8217

Research on Key Technologies for Analyzing High-efficiency Low-carbon Intelligent Irrigation Decision-making
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description: Against the backdrop of global water scarcity and the advancement of carbon peaking and carbon neutrality goals, agricultural irrigation—being the largest water consumption sector—has become pivotal for resolving water supply-demand imbalances and achieving sustainable green agriculture through efficient, low-carbon, and intelligent transformation. Smart irrigation decision-making technologies integrate sensing, modeling, control, and optimization systems to enable precise irrigation management, enhancing water utilization efficiency while reducing energy consumption and carbon emissions, thus serving as a cornerstone for modern agricultural development. Israel, a global leader in agricultural water conservation and smart irrigation, has developed world-class low-carbon intelligent irrigation decision systems through decades of technological research and practical implementation in extreme arid environments. Its technical expertise and application models provide valuable references for arid and semi-arid regions worldwide. This study focuses on Israeli agricultural research to systematically analyze the core principles and technical frameworks of efficient low-carbon irrigation decision-making. It examines Israel's breakthroughs in key technologies—including irrigation sensing, decision modeling, low-carbon control, and system integration—alongside case studies of their applications. The research identifies current implementation challenges and bottlenecks, while aligning with global carbon neutrality objectives and agricultural modernization needs to explore future technological trends and optimization pathways. Research indicates that the core advantages of Israel's high-efficiency, low-carbon intelligent irrigation decision-making technology lie in "precision sensing, intelligent modeling, low-carbon control, and integrated systems." By integrating multi-source data fusion, dynamic model optimization, renewable energy coupling, and end-to-end system integration, …
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creator: Wulong Gao
rights: Copyright (c) 2026 Wulong Gao (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/4kphna48

Research on China-Belarus Trade Services in the Era of New Quality Productivity
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description: New-type productivity, driven by technological innovation as its core engine, is reshaping global industrial chains, supply chains, and service ecosystems. Building upon the theoretical framework of new-type productivity, this study systematically examines the current status of trade service cooperation, policy coordination mechanisms, and dynamic effects between China and Belarus under this framework. By analyzing panel data on service trade, goods trade, digital economy, and policy coordination from 2010 to 2023, we construct a VAR model to analyze dynamic correlations among key variables. Case studies including China-Belarus Industrial Parks, China-Europe Railway Express, and cross-border e-commerce platforms reveal structural characteristics of service trade growth and policy-driven pathways. Findings indicate that three new-type productivity factors—digital technology, green innovation, and policy coordination—exert significant positive impacts on service trade expansion and structural upgrading. For every 1% increase in integration between digital economy and service trade, total service trade volume grows by 0.82%. Additionally, each 1-unit improvement in policy coordination reduces the volatility range of service trade growth rates by 12%. This research provides quantitative evidence and practical insights for deepening service trade cooperation between China and Belarus
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creator: Fanyang Zeng
creator: Wulong Gao
creator: Chaoqun Zhang
rights: Copyright (c) 2026 Fanyang Zeng, Wulong Gao, Chaoqun Zhang (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/5n9v6912

From Atomic Structure to Multidimensional Isomeric Space: Exploring Unknown Dimensions of Life and Consciousness
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description: The essence of life and consciousness remains a central question in humanity's prolonged exploration of civilization. From classical philosophical speculation to modern scientific empirical research, our understanding of this proposition has deepened continuously yet remains elusive of ultimate answers. As fundamental units of matter, atoms exhibit ordered microscopic structures and dynamic interactions that serve as the material foundation for constructing life systems and nurturing conscious activities. The multidimensional heterogeneous space theory transcends traditional three-dimensional spatial constraints, offering novel perspectives for interpreting life complexity and the immaterial nature of consciousness. This study begins with atomic structural characteristics, systematically tracing hierarchical evolutionary logic from atoms to molecules, cells, and living organisms while analyzing how atomic interactions shape life's material carriers. Building upon this foundation, we introduce core concepts and theoretical frameworks of multidimensional heterogeneous spaces to explore manifestations of spatial heterogeneity and its intrinsic connections with life processes and consciousness emergence. Further analysis addresses current research bottlenecks in life origin studies, consciousness essence investigations, and multidimensional space exploration. Integrating cutting-edge advancements in quantum mechanics, neuroscience, and cosmology, we propose a cross-level exploration pathway spanning atomic scales to multidimensional spaces. Finally, we outline future research directions to provide theoretical references and practical paradigms for deciphering unknown dimensions of life and consciousness. Studies indicate that the orderliness of life originates from precise regulation of atomic structures and energy coupling across multidimensional spaces. The emergence of consciousness may represent a macroscopic manifestation of energy-information interactions within m…
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creator: Aristotle
creator: Ohaia
creator: Miocon
rights: Copyright (c) 2026 Aristotle, Ohaia, Miocon (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/xzxhvp39

Exploring the Integration Research of Carbon Trading and RWA Technology
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description: At a critical juncture where global carbon neutrality goals continue to advance and carbon trading markets pursue high-quality development, traditional carbon trading systems face growing challenges including information opacity, insufficient asset liquidity, low transaction efficiency, cross-border circulation barriers, and dual billing risks. Real World Assets (RWA), leveraging blockchain's decentralized, traceable, immutable, programmable, and divisible technical characteristics, offers a novel approach to addressing carbon market dilemmas and unlocking carbon asset value. This study examines the current state of carbon trading markets and the core mechanisms of RWA technology, systematically analyzing the intrinsic logic, core value, and operational models of their integration. It explores practical applications of carbon trading-RWA convergence in carbon asset ownership confirmation, transaction circulation, regulatory accounting, and risk management scenarios. The research thoroughly assesses real-world challenges including legal compliance, technological security, market regulation, standardization, and talent shortages during integration. Targeted optimization strategies are proposed, encompassing institutional system improvements, technological breakthroughs, unified industry standards, enhanced regulatory frameworks, and professional talent cultivation. These efforts aim to deepen the synergy between carbon trading and RWA technology, enhance market efficiency and liquidity, support carbon peak and neutrality objectives, while providing theoretical foundations and practical references for green finance and digital technology integration.
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creator: Xuexue Zhang
creator: Fanyang Zeng
rights: Copyright (c) 2026 Xuexue Zhang, Fanyang Zeng (Author)
date: 2026-04-18
publication date: 2026-04-18
doi: 10.62306/fpfjek68

Analysis of the composition and condition of the Chinese railway transport
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description: Researching the technological and constructional progress of China’s railway transportation is fundamental to understanding its history. While technology and construction provide the basic framework, an economic history perspective is indispensable for scholarly research in this field. Currently, China is optimizing its network layout through advanced equipment and scientific management to improve innovation and market competitiveness, ultimately supporting the nation's comprehensive development. Railway transportation is a product of modern global economic evolution. Its expansion has facilitated regional specialization and accelerated economic globalization. By exploring the historical types and technological milestones of China's railways, this paper examines their future trajectory and their growing impact on international trade patterns.
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creator: Fanyang Zeng
rights: Copyright (c) 2026
date: 2026-03-25
publication date: 2026-03-25
doi: 10.62306/j2td8834

Vision-Radar Fusion for UAV Perception in Low-Altitude Emergency Rescue: A Survey
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description: Unmanned Aerial Vehicles (UAVs) have emerged as critical tools in emergency rescue operations, particularly in urban low-altitude complex environments characterized by dynamic obstacles, adverse weather, and signal interference. However, traditional single-modality perception systems, reliant on either vision or radar, struggle with limitations such as motion blur, low light conditions, and occlusion, compromising detection accuracy and navigation safety. This survey provides a comprehensive review of vision-radar fusion perception systems tailored for UAVs in such scenarios. We first examine advancements in image quality enhancement techniques, including diffusion models and super-resolution methods like SRGAN and ESRGAN , which address degradation in low-altitude imagery. Next, we explore multi-target detection and recognition via multi-modal fusion frameworks, such as Faster R-CNN-based approaches and cross-view spatial fusion. We then discuss robust multi-target tracking and trajectory prediction, highlighting graph neural networks (GNNs) and Transformer-based models like TrackFormer and MOTR . Finally, we cover low-altitude environment assessment and autonomous path planning, leveraging graph theory, 3D risk mapping, and deep reinforcement learning (e.g., MADDPG). By synthesizing global research trends, challenges like spatio-temporal alignment and real-time processing, and future directions toward end-to-end multi-modal integration, this review underscores the potential of fusion systems to enhance UAV resilience and efficiency in rescue missions. Our analysis reveals a clear trajectory toward AI-driven, adaptive perception, with implications for urban safety and disaster response.
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creator: Xuexue Zhang
creator: Chenchen He
creator: Dongran Sun
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/k3rd5c93

The State of Enterprise-Level AI Commercialization in China: Insights from 2025 Trends and Global Comparisons
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description: The rapid advancement of artificial intelligence (AI) technologies has positioned China as a global frontrunner in AI development, yet the commercialization of enterprise-level AI remains a critical challenge amid evolving policy landscapes, international competition, and market dynamics. This survey synthesizes empirical data from the 2025 China Enterprise-Level AI Commercialization Progress Report, based on a mixed-methods survey of 229 enterprises (81.6% SaaS vendors, 15.4% AI-native firms), with complementary insights from global benchmarks such as the Stanford HAI AI Index 2025 and the World Economic Forum's Blueprint to Action on China's AI-Powered Industry Transformation 2025. Key findings highlight a "scale exploration phase" in commercialization, where AI penetration exceeds 70% in internal operations but value realization is fragmented, with only 31.4% of firms achieving mature expansion. Structural divergences emerge between SaaS firms, which dominate market breadth through incremental "+AI" integrations, and AI-native entities pursuing disruptive "AI+" reconstructions, amid regional concentration in five major hubs (Beijing, Shanghai, Shenzhen, Hangzhou, Guangzhou) capturing 70% of resources. Challenges include demand-side bottlenecks like fragmented scenarios (29.7-30% cited as primary barriers) and low client penetration (54.5% below 10%), while trends point to vertical specialization, value-based pricing, and ecosystem integration as growth engines. Comparative analysis with MERICS' Report on China's AI Stack and RAND's analysis of China's AI industrial policy reveals China's shift toward self-reliant stacks (e.g., Huawei Ascend chips) and policy-driven innovation, contrasting U.S. capital-intensive models where private AI investment reached $109.1 billion in 2024 versus China's $9.3 billion . Contributions include a synthesized framework for assessing commercialization maturity, identification of eight core insights (e.g., organizational readiness as…
subject: Articles
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creator: Wulong Gao
creator: Zhicheng Zhao
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/mh356919

Multimodal Large Models-Driven Precise Perception in Complex Low-Altitude UAV Environments: A Survey on Adaptive Edge Intelligence and Swarm Collaboration
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description: Unmanned aerial vehicles (UAVs) equipped with long-endurance remote sensing capabilities have revolutionized applications in economic development, national defense, emergency response, and disaster monitoring. However, traditional centralized processing paradigms suffer from high latency, resource inefficiency, and poor adaptability to dynamic low-altitude environments. This survey reviews advancements in multimodal large models (MLMs) for precise detection and perception in complex low-altitude scenarios, emphasizing three core challenges: enhancing intelligent terminal perception for adaptive learning, bolstering multi-UAV collaborative coverage through federated evolution, and achieving high-fidelity 3D perception via multimodal fusion. We synthesize recent developments in self-evolving online learning frameworks, asynchronous distributed federated optimization, and Transformer-based MLMs tailored for heterogeneous sensor data (e.g., LiDAR and multi-view cameras). Key contributions include a taxonomy of adaptive algorithms mitigating catastrophic forgetting and data heterogeneity, alongside benchmarks for edge deployment in resource-constrained UAV systems. By highlighting gaps in unsupervised multimodal alignment and real-time scalability, this work outlines future directions toward autonomous, resilient UAV swarms, fostering innovations in edge intelligence for spatial information technologies.
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creator: Chenchen He
creator: Dongran Sun
creator: Xuexue Zhang
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/d54q8p10

Consumption Trends in Science and Technology-Based Anti-Aging Products Among Oriental Women: A Systematic Review
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description: The global anti-aging industry has witnessed exponential growth, driven by demographic shifts, technological advancements, and evolving consumer preferences, particularly in emerging markets like Asia. This survey paper synthesizes extant literature on consumption trends in science and technology-based anti-aging products among Oriental women, with a focal emphasis on East Asian demographics (primarily Chinese, Japanese, and Korean populations). Drawing on the seminal 2025 report by Yicai Business School and Baique Ling, which projects China's anti-aging market to exceed 1,500 billion CNY by 2026 at a 13.3% compound annual growth rate (CAGR), we integrate empirical findings from over 50 peer-reviewed studies spanning 2010–2025 to critically analyze market dynamics, consumer behaviors, and innovation trajectories. Key themes include the declining market concentration favoring domestic brands, heightened awareness of skin aging triggers such as unhealthy sleep patterns among 30–40-year-olds, and preferences for biotech ingredients like boswellic acid (Pro-Xylane) and collagen. We employ a systematic review methodology adhering to PRISMA guidelines, incorporating quantitative syntheses (e.g., meta-analyses of preference data) and qualitative thematic analyses to address gaps in prior Western-centric surveys. Findings reveal that Oriental women prioritize efficacy over brand loyalty, with over 70% favoring international premium products yet showing increasing adoption of tech-infused formulations. Sensitive skin subgroups, comprising 58.3% mild cases, demand milder, targeted innovations. Theoretical contributions extend the Theory of Planned Behavior to cultural contexts, elucidating how lifestyle factors mediate consumption. Practical implications for marketers include strategies for R&D collaborations and digital marketing integrations. Future directions propose longitudinal studies on AI-personalized anti-aging and cross-cultural comparisons. This synthesis underscor…
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creator: Wulong Gao
creator: Zhimei Chen
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/g9jpd072

Advances in Cross-Source Intelligent Security Monitoring and Resilience Strategies for Urban Cyber-Physical Power Systems: A Comprehensive Review
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description: The rapid integration of cyber-physical systems (CPS) into power grids has transformed traditional electricity networks into cyber-physical power systems (CPPS), enhancing efficiency but introducing profound cybersecurity vulnerabilities. Coordinated cyber-physical attacks, cascading failures, and information asymmetry exacerbate risks, as evidenced by incidents like the 2019 Venezuela blackout and disruptions during the Russia-Ukraine conflict. This review synthesizes advancements in cross-source intelligent security monitoring and analysis for power systems, focusing on urban CPPS models. Key technologies examined include multi-source log data aggregation for topology modeling, anomaly detection via self-supervised contrastive learning for missing node identification, tri-level optimization defenses against coordinated attacks, and vulnerability assessments using spectral metrics. We further discuss fault recovery strategies incorporating information delay models and graph convolutional networks (GCN) for optimal repair paths. Innovations such as multi-functional module integration (monitoring, powering, control) and asymmetric topology-aware attacks address gaps in high-security urban cores. By evaluating resilience metrics like load loss rates and islanding efficacy [35], this paper highlights pathways to enhance grid robustness, reduce outage costs, and support smart grid evolution. Future directions emphasize scalable AI-driven platforms for real-time threat mitigation, offering a comprehensive framework for researchers and engineers to bolster CPPS resilience.
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creator: Beike Gao
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/4ntteh03

A Survey on Integrated Training-Inference Architectures for Large Language Models on Multi-GPU Stream Processors
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description: Large language models (LLMs) have revolutionized artificial intelligence, achieving remarkable performance in natural language understanding, generation, and multimodal tasks. However, their unprecedented scale—often comprising billions to trillions of parameters—imposes severe computational demands, particularly in training and inference phases, necessitating advanced parallel processing architectures on multi-GPU arrays. This survey provides a comprehensive overview of integrated training-inference (train-infer) architectures for LLMs on large-scale GPU stream processors, emphasizing multi-GPU stream processing, hypercube tensor parallelism, and hardware-software co-designed compilation frameworks. We trace the evolution of parallelism strategies, including data parallelism, pipeline parallelism, and tensor parallelism, highlighting innovations such as cross-cluster pipeline execution, adaptive NIC selection, and spatiotemporal tensor partitioning to mitigate communication overheads and memory bottlenecks in heterogeneous environments [1, 7, 8, 17]. Key challenges, including scalability in non-homogeneous networks and efficient compilation for diverse hardware, are analyzed alongside state-of-the-art solutions like MLIR-based frameworks and RISC-V accelerators [28, 33]. By synthesizing recent advancements, this survey identifies promising directions for scalable, energy-efficient LLM systems, paving the way for broader deployment in edge computing and high-performance clusters.
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creator: Heric Tsang
rights: Copyright (c) 2025
date: 2025-12-20
publication date: 2025-12-20
doi: 10.62306/7ds08r28

Trade and Economic Cooperation Between the People's Republic of China and the EAEU Countries in the Framework of Resolving the Problem of Food Security
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description: The purpose and objectives of the study The purpose of the dissertation is to develop promising areas of trade and economic cooperation between the People's Republic of China and the EAEU countries in the context of solving the problem of food security in modern economic conditions. To achieve the goal of the study, the following tasks were set and solved: –to consider the theoretical aspects of the country's food security, the effects and risks of its decline; –to study the world experience of forming food security of countries; –to study the state policy of China in the field of ensuring food security; –to assess the export opportunities in the food sector of the EAEU countries; –to identify and justify promising areas of food exports to the PRC by the EAEU countries, as well as the implementation of joint investment projects in the field of agriculture. The object of the study is trade and economic cooperation between the People's Republic of China and the EAEU countries in the field of ensuring food security. The subject of the study is the substantiation of the main directions of ensuring food security based on the development of mutually beneficial cooperation between the People's Republic of China and the EAEU countries, the development of the export potential of states, and the improvement of investment activities. Provisions submitted for defense 1. The essence and content of the category "food security" are defined, distinctive characteristics and criteria for assessing the level of food security are identified. 2. An assessment of the position of the People's Republic of China in the field of food security is carried out, the evolution of changes in the nutritional structure of the population of the PRC is considered, 3. Factors complicating the solution of the food problem in the country, the dependence of the domestic food market of China on imports of food products, and strategic directions for ensuring food security in China are identified. 4. The red…
subject: Articles
  topic: section
creator: Chaoqun Zhang
rights: Copyright (c) 2025 Chaoqun Zhang (Author)
date: 2025-10-19
publication date: 2025-10-19
doi: 10.62306/y2hcvc80

Impact of digital currency on China's traditional financial system
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description: Structure and scope of the master's thesis is 84 pages, 55 references, 4 tables and 3 figures. The master's thesis consists of an introduction, three chapters, a conclusion and a list of references. Key words: supply chain, supply chain diversification, economic security, enterprise economic security, China, The relevance of the topic Post-pandemic supply chain disruptions, geopolitical tensions as well as regional conflicts have highlighted vulnerabilities in centralized supply chains. As a global manufacturing hub, Chinese enterprises face pressure to balance cost efficiency along with resilience. Supply chain diversification is critical for mitigating risks like overreliance upon single markets, raw material shortages, or export restrictions. China’s "dual circulation" strategy emphasizes domestic resilience and global competitiveness, making supply chain diversification a strategic imperative for economic security. Purpose of the research The research purpose is to quantify supply chain diversification's impact upon Chinese enterprises' economic security, identify trade-offs as well as inform strategic decisions. Object of the research The object of the research is the economic security of enterprises in China, defined as their ability to withstand external shocks while maintaining operational stability and profitability. Subject of the research The subject of the research is enterprise supply chain diversification strategies in China. Research objectives 1) To evaluate how diversification levels correlate along with economic security indicators; 2) Analyze industry-specific differences and firm characteristics; 3) foster frameworks for balancing diversification along with cost efficiency. Research methodology The research employs a mixed-methods approach, combining quantitative and qualitative methods. Quantitatively, it uses financial data analysis, regression analysis as well as structural equation modeling (SEM) to measure correlations and test hypotheses re…
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creator: Siyi Zeng
rights: Copyright (c) 2025 Siyi Zeng (Author)
date: 2025-10-19
publication date: 2025-10-19
doi: 10.62306/iodcoctfs

A Unified Spatio-Temporal Data Organization Model for Forest and Grassland Resources Based on GeoSOT Encoding
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description: The efficient integration, management, and application of multi-source heterogeneous spatio-temporal data remain a critical challenge in forest and grassland ecological informatics. Traditional GIS-based approaches often suffer from limited scalability, poor adaptability to diverse data modalities, and inadequate support for time-space linkage. To address these limitations, this study proposes a novel spatio-temporal data organization model based on the Geographical Subdivision Grid with One-dimension-integer on Two to n-th power (GeoSOT) encoding framework. We introduce a unified three-domain identifier—composed of spatial code, temporal stamp, and semantic attributes—to support fine-grained partitioning and indexing of both structured (e.g., vector, raster) and unstructured (e.g., video, sensor logs, text) data. The organization model employs multi-level GeoSOT grid cells as spatial anchors, integrating temporal semantics and object-level identifiers to form a one-code-per-element schema, ensuring the uniqueness and traceability of each data entity. A prototype system was implemented using forest resource and fire monitoring datasets from the Asia-Pacific Forestry Center. Comprehensive experiments demonstrate that the proposed model significantly improves data fusion flexibility, retrieval efficiency, and query precision compared to conventional spatial database models. Moreover, the system enables scalable and interactive spatio-temporal queries across multi-modal data sources. This study contributes a generalized, extensible, and semantically rich data organization framework that bridges spatial and temporal dimensions in forest and grassland applications. It holds promise for large-scale ecological monitoring, forest fire early warning, and smart forestry governance. Future work will focus on extending the model to real-time streaming data and integrating intelligent analytics for enhanced decision support.
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creator: Xuan Ouyang
rights: Copyright (c) 2025
date: 2025-10-19
publication date: 2025-10-19
doi: 10.62306/ausdomfgrbge

From Atomic Structure to the Dream World: Exploring the Unknown Dimensions of Life and Consciousness
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description: Modern science establishes that the human body is fundamentally composed of atomic structures. As the basic units of matter, atoms form cells, tissues, and organs through intricate combinations and interactions, sustaining vital life processes. At the microscopic level, atomic types, quantities, and chemical bonding patterns determine the diversity of biological substances and the complexity of physiological functions. For instance, the unique chemical properties of carbon enable the formation of diverse organic molecules, serving as the foundation of life, while oxygen atoms play a crucial role in energy metabolism during respiration.
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creator: Peihe Gao
rights: Copyright (c) 2025
date: 2025-10-19
publication date: 2025-10-19
doi: 10.62306/fasttdwe

A Brief Discussion on the Value Representation of Digital Assets in Different Periods
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description: With the rapid advancement of information technology, digital assets are playing an increasingly crucial role in the global economic system. This paper provides an in-depth analysis of how digital assets manifest their value across different periods, examining their characteristics, driving factors, and challenges during the nascent, developmental, mature, and transformative stages. By offering a comprehensive discussion of each stage, this study reveals the evolution of digital asset value, providing valuable insights for enterprises and investors.
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creator: Sufei Liu
creator: Liping Yuan
creator: Xuexue Zhang
creator: Dongran Sun
creator: Peihe Gao
rights: Copyright (c) 2025
date: 2025-10-18
publication date: 2025-10-18
doi: 10.62306/abdotvrodaidp