This paper presents a verified funder landscape and fit-score shortlist for sustaining QNFO, a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of approximately 1,000 method papers across seven program areas. Every funder fact was verified by live HTTP retrieval on 2026-08-13 across twenty-six pages spanning Web3 and IPFS ecosystem grantors, open-science philanthropy, and decentralized-science programs; anything not verified live is explicitly flagged. The analysis scores eleven funders on eligibility for an unaffiliated individual, topical fit with decentralized and epistemics-oriented research, and application friction, yielding a weighted ranking led by NLnet NGI Zero (calls open September 3, 2026; deadline November 3, 2026, 12:00 CEST) and Emergent Ventures, followed by the Foresight Institute, Filecoin Foundation, the Ethereum Ecosystem Support Program, Gitcoin, and the Effective Altruism funds. A sequencing calendar spans August 2026 through 2027, including the Sovereign Tech Agency Fellowship cycle. The paper documents application-readiness gaps (legal entity, residency, tax position, public identity), per-funder pitch skeletons, and framing cautions, including the risk of presenting corpus volume as rigor. It closes with an agent-executable action plan.
Through this independent concept, the study introduces a fresh new perspective to the world of modern forensic accounting via a theory called “The Decentralized Fraud Matrix” (DFM). This conceptual research was developed specifically as an analytical tool to dissect the modus operandi of financial crimes in the digital-cyber era—including Web3 environments, blockchain architecture, DeFi protocols, and autonomous DAO systems. The focus of the DFM theory completely breaks away from the basic assumptions of the conventional fraud triangle, which has long been overly preoccupied with measuring human emotions. Mechanically, the originality of this theory rests on the testing of three interlocking cyber indicators in the field. These three indicators include the level of opacity in an actor’s digital identity concealment; technological engineering designed to break the audit trail of fund flows; and the exploitation of loopholes in physical national sovereignty boundaries, as well as cyber “jurisdictional evasion” tactics aimed at neutralizing the enforcement power of on-ground regulations, thereby rendering perpetrators immune to formal legal prosecution
This informative document explores the evolving digital asset landscape, covering cryptocurrency, NFTs, blockchain technology, Web3, and emerging market trends. It provides readers with practical insights into digital ownership, market developments, and the importance of research when evaluating opportunities in the growing blockchain economy. Collective Shift
The subject of the article is the management of distributed international teams in Web3 companies operating at the intersection of digital assets, platform services and cross border entrepreneurship. The aim of the work is to develop an analytical model of the relationship between a distributed team, managerial maturity and market stability. The methodological basis consists of comparative analysis, source analysis, conceptual synthesis, typologization and analytical generalization. The analytical part highlights coordination, trust and organizational scalability mechanisms affecting the competitiveness of Web3 companies.
The inherent challenge of balancing scalability, security, and decentralization – commonly termed the blockchain trilemma – continues to hinder the adoption of distributed systems. This paper presents InternxtChain, a decentralized storage framework designed to address this trilemma through a novel integration of erasure-coded sharding, zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs), and a sharded Proof-of-Storage consensus mechanism. By leveraging aggregated BLS-381 signatures and distributed redundancy protocols, the framework achieves a throughput of 2,800 transactions per second with a latency of 420 milliseconds across 1,024 nodes, surpassing Filecoin by a factor of 3.5 and Ethereum’s capacity by 165 times. The system maintains 99.9% data integrity even under adversarial conditions involving 30% Byzantine nodes. Additionally, InternxtChain reduces storage costs to $0.002 per gigabyte, representing an 85% reduction compared to centralized alternatives like AWS S3. Empirical evaluations demonstrate linear scalability to 4,200 transactions per second with 2,048 nodes, alongside hardware affordability at $180 per node. These advancements not only outperform decentralized platforms in throughput by 2.8 times but also ensure GDPR-compliant data sovereignty, positioning InternxtChain as a pioneering solution for Web3 ecosystems seeking to harmonize enterprise-grade performance with decentralized trustlessness.
Counterfeit medicines, fragmented record management, limited end-to-end visibility, and dependence on centralized databases create security and traceability challenges in pharmaceutical supply chains. This article presents Pharma-Chain, a blockchain-enabled pharmaceutical supply chain management system developed to record medicine registration, stakeholder interactions, ownership transfer, and authenticity verification on an Ethereum blockchain. The system integrates a React.js frontend with Web3.js, MetaMask wallet authentication, Solidity smart contracts, Truffle deployment tools, and Ganache for local blockchain development and validation. Manufacturers register medicine batches with product and lifecycle information; distributors and retailers verify blockchain records before accepting and transferring ownership; and customers retrieve medicine details and transaction history before purchase. The implementation was tested module by module and as an integrated application in a local Ethereum environment. Testing confirmed successful authentication and role-based access, medicine registration, ownership transfer, transaction validation, blockchain record retrieval, and medicine verification. Each successful supply-chain operation generated a blockchain transaction record, providing an immutable ownership history and improving transparency and auditability. The project demonstrates a practical decentralized approach for secure pharmaceutical tracking while identifying QR-code verification, IoT monitoring, AI-assisted analytics, mobile access, and deployment on public or enterprise blockchain networks as future extensions.
Open access
2 source records
Blockchain Technology Applications and Security
Pharmaceutical Quality and Counterfeiting
Physical Unclonable Functions (PUFs) and Hardware Security
This bilingual engineering report presents a practical framework for designing reliable AI agent systems in production environments. It focuses on explicit tool and permission boundaries, memory governance, observability, evaluation, human approval, failure recovery, and auditability. The report connects these concerns with the operational requirements of FinTech real-time systems and Web3 transaction workflows. It introduces the Controlled Action Protocol (CAP-1), a report-defined design proposal that binds an action proposal, policy decision, human approval, and execution record through identifiers, payload hashes, evidence, policy versions, and expiration windows. CAP-1 is not presented as a validated industry standard or a claim of industry-first novelty. The report also includes reference architectures, implementation guidance, risk analysis, and production-readiness checklists derived from the author's engineering practice from 2024 to 2026.本双语工程报告提出了一套面向生产环境的 AI Agent 可靠性工程框架,重点讨论工具与权限边界、记忆治理、可观测性、评估、人工审批、故障恢复和审计能力,并结合 FinTech 实时系统与 Web3 交易工作流的工程要求。报告定义受控行动协议 CAP-1,将行动提案、策略判定、人工授权和执行记录通过标识符、载荷 Hash、证据、策略版本和有效期绑定为可核验链条。CAP-1 被定位为本报告的设计提案,不被表述为已验证的行业标准,也不主张具有“行业首创”地位。报告同时给出参考架构、实施建议、风险分析和生产就绪检查清单,内容来源于作者 2024—2026 年间的工程实践总结。This is an author-directed technical report. Generative AI tools assisted under the author's direction with drafting, translation, language editing, diagram production, and document formatting; Pengpeng Han (Corn Han / 韩朋朋) retains responsibility for the report's factual accuracy, technical claims, source review, and final approval. Repository publication and DOI registration provide persistent identification and citation infrastructure; they do not imply peer review, third-party endorsement, or independent validation of the claims.本报告为由作者指导并负责的技术报告。生成式 AI 工具在作者指导下用于辅助起草、翻译、语言编辑、图表制作和文档排版;韩朋朋(Corn Han)对报告的事实准确性、技术主张、来源审核和最终批准承担责任。存储库发布及 DOI 注册用于提供持久标识和标准引用,不代表同行评审、第三方背书或对报告主张的独立验证。
Decentralised Autonomous Organisations (DAOs) raise fundamental questions for private law. While scholarly and regulatory attention has primarily focused on the legal status and governance of DAOs, comparatively little consideration has been given to how disputes involving these organisations should be resolved. This article examines the suitability of dispute resolution mechanisms for DAO-related disputes. Analysing the principal categories of disputes that have emerged in practice, the article critically evaluates blockchain-based dispute resolution mechanisms alongside traditional arbitration, in light of due process, enforceability, party autonomy, and the unique features of decentralised governance. It argues that neither purely code-based dispute resolution nor conventional litigation provides a satisfactory response to the complexity of DAO disputes. It concludes that arbitration, appropriately adapted to the technological and organisational realities of DAOs, offers the most promising framework for balancing decentralisation, legal certainty, and procedural fairness within the evolving Web3 ecosystem.
Gabriela Mariutac, Claudiu Brândaș, Otniel Didraga, Mihai Plesa
The voluntary carbon market (VCM) has faced sustained legitimacy stress since 2023, when peer-reviewed work found that fewer than one in six issued credits represented a real emission reduction. In parallel, tokenisation through Web3 protocols, decentralised autonomous organisations (DAOs), and regenerative finance (ReFi) infrastructures introduced new participants interacting with incumbent registries without a shared coordination framework. Existing scholarship examines commons governance, complex system governance (CSG), and tokenised carbon markets largely in isolation; the gap addressed here is the absence of an integrated system-of-systems (SoS) governance treatment of the tokenised VCM. This study develops and empirically applies a polycentric SoS governance framework for the tokenised VCM, structured around four research questions and five foundational contributions. We treat the tokenised VCM as an SoS that is polycentric in configuration but not by design, and develop a system-of-systems engineering (SoSE) governance reading of it. We reformulate Ostrom’s eight design principles as SoS governance criteria for digital–physical hybrid commons, map each to CSG metasystem functions, and apply the framework to four cases: KlimaDAO, Toucan Protocol, Regen Network, and the post-2023 Verra reforms. Qualitative coding is complemented by on-chain and Base Carbon Tonne spot-price evidence from October 2021 to December 2025. Disclosure by an analytical intermediary acted on the SoS roughly seven weeks before formal regulatory action and was associated with about 90% of the observed bridging slowdown, interpreted descriptively rather than causally. We derive an eight-item reform agenda, six DAO–registry interface specifications, and a five-level governance maturity rubric.
Open access
Systems Engineering Methodologies and Applications
Web3 represents a paradigm shift of the internet from “platform centralization” to “protocol decentralization,” with its core value lying in rebuilding the trust foundation and value distribution logic of the digital world through blockchain technology. In 2026, the global Web3 infrastructure market is projected to reach $9.74 billion, the Web3 social platform market is expanding at a CAGR of 52.1%, and the decentralized physical infrastructure network (DePIN) market is estimated to reach $85 billion. However, the governance dilemma of Decentralized Autonomous Organizations (DAOs)——token voting leading to power concentration, frequent governance attacks, and low decision-making efficiency——is exposing the deep paradox of “code is law.” DeFi total value locked fell from $115 billion in January 2026 to $70 billion in June, a 39% decline; 121 security incidents caused $942 million in losses, reflecting the systemic fragility of decentralized finance. Meanwhile, global regulatory frameworks are accelerating——the EU MiCA is fully applicable, the U.S. GENIUS Act has taken effect, and Hong Kong‘s Stablecoin Ordinance has been implemented——marking Web3’s transition from “regulatory vacuum” to the “compliance era.” Based on the eight-dimensional framework of Prim-Lex Theory——Prim-Unity·Prim-Fire (Web3 network energy metabolic efficiency), Two Principles·Yin-Yang (dynamic balance between decentralization and effective governance), Three Realms·GC⁴A (cross-scale integration from technological infrastructure to application ecosystems to global governance), Four Phenomena·Four Colors (four-phase differentiated strategies for the Web3 lifecycle), Five Elements·Five Models (coupling of computational deficit/phase-transition early warning/spatial zoning/crypto balance sheet/systemic resilience), Six Dimensions·Six Directions (six-directional spatial layout of global Web3 infrastructure and the digital divide), Seven Luminaires·Seven Rhythms (synchronization between technological iteration cycles and governance response cycles), and Eight Trigrams·Eight Information (Web3 information network entropy and on-chain governance transparency)——this paper constructs, for the first time, an eight-dimensional quantitative assessment system for Web3 governance. It elaborates, dimension by dimension, the calculation principles, mathematical formulas, parameter meanings, and data sources. Using three empirical anchors——DAO governance attacks and reform experiments, DeFi protocol risk evolution, and the formation of global regulatory frameworks——this paper demonstrates the application pathway of the eight-dimensional framework in identifying “phase differences” and “critical windows” in Web3 governance, and proposes the “Web3 Governance Health Index” (Ψ_Web3), providing a quantifiable, programmable, and auditable mathematical language and governance tool for the transition of global Web3 from a “decentralized utopia” to an “eight-dimensional coherent state.”
The rapid growth of cybercrime, ransomware attacks, digital fraud, and large-scale cyber threats has significantly increased the need for secure and collaborative cyber forensic investigations. Traditional machine learning approaches often require organizations to share or centralize sensitive forensic datasets, creating challenges related to privacy, confidentiality, data ownership, and security. To address these limitations, this project proposes a PrivacyPreserving Distributed Training Architecture for Cyber Forensics using Blockchain and Homomorphic Encryption. The proposed framework integrates Federated Learning, Distributed Learning, CKKS-based Homomorphic Encryption, Blockchain Technology, and a Secure Model Exchange Space to enable multiple agencies to collaboratively train machine learning models without exposing their raw forensic data. Federated Learning allows organizations to train models locally and securely aggregate encrypted model updates, while Distributed Learning enables encrypted dataset partitions to be processed collaboratively by helper nodes without revealing the original data. CKKS Homomorphic Encryption protects sensitive information during computation, and blockchain technology provides decentralized trust through secure node authentication, transparent validation, immutable audit trails, and trusted model exchange among participating agencies. The framework is implemented using Python, Flask, Scikit-learn, TenSEAL, Ganache, Solidity, and Web3.py, providing a web-based platform for collaborative project management, encrypted training, blockchain monitoring, secure model sharing, performance evaluation, and cyber forensic prediction. Experimental results demonstrate that the proposed architecture successfully supports secure collaborative learning, encrypted computation, blockchain-based validation, and trusted model sharing while maintaining effective prediction performance. By integrating distributed learning, federated learning, homomorphic encryption, and blockchain into a unified framework, the proposed system provides a scalable, secure, and privacy-preserving solution for next-generation cyber forensic intelligence, enabling organizations to collaboratively strengthen cybersecurity without compromising the privacy, confidentiality, or ownership of sensitive forensic data
Facial recognition has become an essential technology in modern surveillance and law enforcement for the automatic identification of individuals from images and video streams. Conventional facial recognition techniques often experience reduced accuracy due to variations in illumination, facial pose, occlusion, low-quality images, and aging effects. To address these challenges, this paper proposes a Blockchain-Based Criminal Recognition and Evidence Management System that integrates advanced deep learning models with secure blockchain technology. The proposed system employs Multi-task Cascaded Convolutional Networks (MTCNN) for accurate face detection and facial alignment, followed by StyleGAN for age progression and age transformation to generate age-invariant facial representations while preserving the individual's identity. The transformed facial images are then processed by a Convolutional Neural Network (CNN)-based facial recognition model to extract discriminative facial features and accurately identify suspects by comparing them with a criminal database. Upon successful recognition, the system automatically generates real-time alerts for authorized personnel and securely stores recognition results, timestamps, confidence scores, and evidence metadata on a blockchain using Web3.py and Ganache, ensuring data integrity, transparency, traceability, and protection against unauthorized modification. By combining robust face detection, ageinvariant facial recognition, and tamper-proof evidence management, the proposed system provides an accurate, secure, and reliable solution for modern criminal identification and digital forensic investigations.
Das Forschungs- und Entwicklungsprojekt LCBIT (Low-Code Blockchain Integration Toolkit) wurde mit großem Erfolg durchgeführt. Das übergeordnete Ziel, hochkomplexe Blockchain-Technologien so zu abstrahieren, dass auch Nicht-Softwareentwickler in die Lage versetzt werden, dezentralisierte Anwendungen (dApps) eigenständig zu entwickeln und bereitzustellen, konnte im Berichtszeitraum vollständig erreicht werden. Im Mittelpunkt des Erfolgs stand die methodische und technologische Weiterentwicklung der bestehenden Low-Code/No-Code-Plattform (LCNC) der Heisenware GmbH zu einem umfassenden und intuitiven Werkzeugkasten für Web3-Anwendungen. Durch die exzellente und interdisziplinäre Zusammenarbeit im Konsortium - bestehend aus der Heisenware GmbH, der Hochschule Mittweida (Blockchain Competence Center Mittweida - BCCM), der TU Chemnitz (Professur Fabrikplanung und Intralogistik - FPIL) und dem assoziierten Partner in.hub GmbH - wurde ein modulares System geschaffen. Dieses vereint die Integration von Blockchain, IoT-Sensorik und klassischen Datenquellen nahtlos in einem Low-Code-Umfeld. Das Projekt hat bewiesen, dass sich durch die konsequente Abstraktion technischer Komplexität die Entwicklung dezentraler Anwendungen drastisch vereinfachen lässt. Insbesondere kleine und mittlere Unternehmen (KMU) erhalten dadurch einen niedrigschwelligen Zugang zu Web3-Technologien, ohne kostenintensive, eigene Blockchain-Expertise aufbauen zu müssen.
Learn more about Theta Network and its impact on the development of decentralized infrastructure via blockchain-enabled media distribution, edge computing, AI integration, and Web3 innovation. With this in-depth overview, you will gain valuable information about its technology, features, practical applications, and future perspectives, emphasizing the need for thorough research before making an investment decision. If you are interested in blockchain, then this article is for you!
The rapid development of the Fourth Industrial Revolution (IR 4.0) and Web3 has catalyzed digital transformation in the education sector through the convergence of Artificial Intelligence (AI) and the metaverse. However, most existing initiatives remain isolated and passive, lacking adaptive learning capabilities. These initiatives also face cross-platform interoperability constraints, cybersickness, gaps in educator readiness, and ethical concerns regarding biometric data privacy. In view of this, this study was conducted with the objective of constructing an integrated conceptual framework, Edu-AIMeta, that links technological dimensions with learning theories, critically analyzing implementation challenges, and proposing sustainable cyber-governance strategies. To achieve these goals, this study employs a conceptual-integrated literature review design by critically analyzing and synthesizing theoretical perspectives from 22 articles published between 2022 and 2026 across the Scopus and Web of Science (WoS) databases. The research findings outline three primary dimensions of integration success: the AI cognitive engine, the spatial metaverse environment, and user adoption and competence, particularly among Generation Z students and educators. Moving forward, this paper recommends the development of an inclusive meta-governance framework through the implementation of open-source standards, the formulation of ethical guidelines for biometric data protection, and the provision of structured immersive pedagogical training programs to ensure an equitable, secure, and sustainable future educational ecosystem.
Ádám Bereczk, Zoltán Musinszki, Erika Szilágyiné Fülöp, Bettina Hódiné Hernádi
This study investigates the allocation of pre-sale capital by blockchain technology-based startup ventures, with a specific focus on the Play-to-Earn (P2E) segment within the Web3 ecosystem, and its impact on token price performance. Our aim is to determine the proportion of initial capital that P2E startups, according to their business plan (whitepaper), allocated to key areas such as team and advisor expenses, marketing activities, and product development. Subsequently, this research centers on the question of how the focal areas of pre-sale capital utilization (team, marketing, development) correlate with the subsequent price performance of the tokens issued by these startups. The timeliness and relevance of this topic are underscored by the dynamic evolution of blockchain technology and the P2E model, as well as the critical role of startups' capital allocation decisions. Understanding how the utilization of initial funding influences long-term value is also of paramount importance for investors. Based on the results, while excessive marketing expenditures may offer a project short-term benefits, this strategy can potentially have negative long-term consequences. A project's financial viability is contingent upon competent human resources and the insights of external experts; nevertheless, these elements alone are not definitively sufficient. The significance of product development was only evident when the effect was measured in Bitcoin terms; no correlation was found when measured in Dollars.
This record contains the presentation materials prepared for the Data for Policy July Fireside Chat, “Digital Infrastructures of Democracy,” delivered online on 20 July 2026 by Professor Igor Calzada and chaired by Professor Marta Poblet. The talk presents Calzada’s action-research programme on digital citizenship and the democratic governance of digital infrastructures. Building upon the Oxford Research Encyclopedia article Digital Infrastructures of Democracy, it conceptualises democracy as being increasingly mediated by three interconnected infrastructural layers: material infrastructure, data infrastructure and algorithmic infrastructure. These layers are not politically neutral; their ownership, design and governance shape participation, rights, public accountability and the distribution of power. The presentation connects this conceptual framework with research on AI economics, Web3 decentralisation, the Digital Metropolis, EcoTechnoPolitics, territorial digital inclusion, data cooperatives and anticipatory AI governance. Particular attention is devoted to evidence from the Basque Country and Gipuzkoa, including the emerging supercomputing and quantum ecosystem associated with IBM Quantum System Two. The Basque Country is examined not as a model to be replicated mechanically, but as a city-regional laboratory whose lessons can support context-sensitive institutional learning elsewhere. The central argument is that democratic resilience requires the alignment of technical design, institutional reform and civic agency. Advanced computational capacity becomes a democratic public capability only when institutions can govern technological dependencies, territorialise benefits, ensure accountability, respect ecological limits and preserve meaningful opportunities for public participation and contestation.