Blockchain Papers

Yuri A. Tijerino

No abstract is available for this record.

Damiano Di Francesco Maesa, Francesco Donini, Paolo Mori, Laura Ricci

Non-Fungible Tokens (NFTs) are widely used nowadays for managing digital assets in many applications due to their ability to uniquely identify an asset and securely transfer and trace its ownership. Some scenarios require digital assets to be mutable, i.e., users should be allowed to update asset attributes over time, thus introducing possible security issues, since unwanted (or even malicious) updates could significantly decrease assets’ value. While various methods for NFT mutability exist, they often lack integrated, fine-grained, and on-chain enforceable authorisation models. This paper addresses this issue by considering an NFT expansion, named Non-Fungible Mutable Token (NMT), which natively supports the update of the attributes characterising each digital asset while guaranteeing a strict and fine-grained control over such updates. In fact, the NMT approach embeds an on-chain security support based on the Attribute-Based Access Control model within the NMT architecture, aimed at regulating, through access control policies enforcement, the execution of all the update operations defined on digital assets, from new token minting to ownership transfers and attribute updates.We propose a detailed architecture for NMTs and we outline the involved smart contracts structure, including the on-chain access control system. We validate our proposal by implementing it for two common use cases, wearables and digital event tickets in the metaverse, and by conducting an experimental evaluation of the deployment and execution costs. Moreover, we simulated the usage of NMTs over a given time interval to estimate the sustainability of the proposed approach over time.

Sen Yang, Aviv Yaish, Arthur Gervais, Fan Zhang

Permissionless Proof-of-Stake (PoS) economic security is predicated on the high cost of violating consensus safety or liveness. We show that liquid staking introduces additional risks that are not captured by standard PoS economic security arguments. Through an empirical study of Ethereum data, we find that the operational performance of liquid staking pools is positively associated with subsequent normalized liquid staking token (LST) returns. Motivated by this, we present a cross-layer attack: a low-stake adversary can manipulate the consensus protocol to degrade a target pool's performance and take application-layer positions that profit if the market reprices the corresponding \gls{LST} in-line with the historically observed association. To make the consensus layer manipulation concrete, we develop a deep reinforcement learning (DRL) framework to automatically discover attack strategies. Our evaluation shows that the learned strategies can recover near-optimal theoretical attacks and uncover new manipulation behaviors that significantly degrade target pool performance. We further characterize feasible application-layer monetization channels and analyze leveraged shorting in detail using Monte Carlo simulations, showing that such attacks can be profitable with over one-half probability for LSTs of major staking pools. Our findings reveal a previously overlooked attack surface in PoS systems with liquid staking and expose a gap between consensus and economic security.

Alper Alimoğlu, Can Ozturan

Blockchain technologies are making it possible to develop crypto-currencies and programmable smart contracts that can work in worldwide trustless and decentralized environments. Decentralized autonomous organizations (DAOs) that can coordinate the works of crowds of users, developers, and researchers can be built using smart contracts on blockchains. We contribute a decentralized autonomous software organization model and an Ethereum blockchain-based smart contract named AutonomousSoftwareOrg that provides a continuously operating virtual organization for open-source software development communities and users. AutonomousSoftwareOrg provides a project funding mechanism based on crypto-currencies, a decision-making mechanism based on voting, and recordkeeping for software usage citations and executions. Furthermore, software executions, along with their input and output data files, can also be transactionally recorded in AutonomousSoftwareOrg. This enables software execution graphs to be constructed for analysis. An AND/OR graph model of input/output data and software executions is presented, along with analysis algorithms for execution traceability and reproducibility assessment. AutonomousSoftwareOrg is deployed and tested on the Ethereum-based Bloxberg blockchain network which is operated by academic and research institutions, demonstrating its practical viability for sustainable open-source software development.

S Ahmed Basha

Rapid urbanization and the exponential growth of vehicles have led to severe traffic congestion, increased travel time, fuel consumption, and environmental pollution in metropolitan cities.Traditional traffic control systems, which rely on fixed-time signals and manual monitoring, are inadequate to handle dynamic and unpredictable traffic conditions.This project proposes a Smart Traffic Management System designed to optimize traffic flow and reduce congestion using advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and real-time data analytics.The system integrates smart sensors, cameras, and GPS-enabled devices to continuously monitor traffic density, vehicle movement, and road conditions.Data collected from these sources is processed using machine learning algorithms to predict traffic patterns and dynamically adjust traffic signal timings.Additionally, the system provides real-time route guidance to drivers through mobile applications and digital signboards, helping to distribute traffic evenly across the road network.Emergency vehicle prioritization and incident detection mechanisms are also incorporated to enhance response efficiency and safety.

Mamun Ahmed, Saha Reno, Salma Akter, A. K. M. Abu Nowshad Chowdhury

No abstract is available for this record.

Mohd Saleem, Sohrab, Matloob Ullah Khan, Faizan Khan Sherwani

Key components of blockchain technology, DeFi represent a revolutionary advance in digital contracts and automated trades, and they are integrated into decentralized networks such as Ethereum. These self-executing contracts eliminate the need for middlemen by autonomously enforcing specified terms. This paper offers a thorough analysis of Decentralized Finance (DeFi), smart contracts, covering their underlying theories, technological foundations, wide range of applications, and ramifications in context of financial inclusion and investment. In order to clarify the workings and practical applications of such innovations, the research technique comprises a methodical evaluation of the literature, an examination of case studies, and an amalgamation of empirical data. This study evaluates their effects on efficiency, transparency, and trust in international transactions by looking at how they are revolutionizing industries like finance, and decentralized governance. It also thoroughly examines security considerations, including best practices and vulnerabilities, as well as regulatory issues and new developments.

Michael Zouari, Ilan Alon, Ze’ev Shtudiner

The Landauer principle motivates the definition of economic temperature as the monetary price of processing a bit irreversibly. No empirical test of this definition exists in transparent fee markets. This paper fills that gap using daily Bitcoin and Ethereum data, constructing canonical thermodynamic state variables and evaluating five diagnostic layers: state variable behavior, Maxwell-type integrability, Carnot-style efficiency bounds, nonlinear regime separation, and structural break sensitivity to protocol events. Bitcoin's log-temperature behaves as a persistent mean-reverting process with an AR(1) coefficient of 0.97 and a half-life of 21 days; Ethereum is highly persistent, with weaker formal evidence of stationarity than Bitcoin. Maxwell integrability is frequency-dependent: Bitcoin passes all four relations at monthly frequency, whereas Ethereum passes two of four. Carnot-style evidence is the strongest: realized fee extraction efficiency stays well below the implied bound, with daily compliance exceeding 97% on both chains. Structural breaks around Bitcoin ordinals, EIP-1559, the merge, and Shanghai confirm that protocol changes reorganize the temperature relation. The thermodynamic framework provides structure that standard fee market analysis does not, including a first principles efficiency bound and a state space coherence test. The findings provide partial, frequency-dependent, and chain-specific empirical support for a Landauer-based thermodynamic description of blockspace markets.

Semenova Svitlana

Relevance. Problem statement. The rapid development of Decentralized Finance (DeFi) and the expansion of blockchain technologies within the digital economy and the broader process of financial digitalization complicate the application of traditional approaches to accounting and taxation of digital assets. The absence of clear criteria for interpreting the economic substance of DeFi and its implications for the recognition, measurement, and disclosure requirements of digital assets leads to heterogeneity in accounting practices, reduced comparability of financial reporting, and increased risks for auditors and investors. Consequently, there is a need to identify accounting-relevant characteristics of DeFi that can serve as a basis for accounting decisions regarding digital assets and for establishing a unified approach to their classification and measurement in accordance with International Financial Reporting Standards (IFRS). The purpose of the article is to provide a conceptual justification and structured generalization of the impact of DeFi and blockchain technologies on the methodology of accounting for digital assets through the identification of accounting-relevant characteristics that determine the specific features of their recognition, measurement, and disclosure in financial statements in accordance with IFRS, as well as their implications for the formation of tax liabilities within the DeFi environment. Methodology. The research objectives were addressed using general scientific and specialized methods, including analysis, synthesis, induction, deduction, comparison, abstraction, and a systems approach, which ensured an appropriate level of substantiation of the proposed arguments and the formulation of well-grounded conclusions. Results. The findings indicate that the transactional transparency of blockchain is accompanied by new valuation risks that affect asset measurement and revenue recognition. Existing tax regulations often fail to account for the specific characteristics of the DeFi ecosystem. Accounting-relevant characteristics of DeFi have been systematized, demonstrating that their influence extends beyond the accounting treatment of digital assets to the specific features of the protocol-based financial architecture within which economic rights and obligations are executed through algorithmic mechanisms without a centralized counterparty. Their systemic impact on the application of control criteria, the determination of the existence of contractual rights to claims, the selection of measurement models, the identification of the timing of revenue and liability recognition, and the scope of risk disclosures under IFRS has been substantiated. The theoretical contribution of the results lies in shifting from a descriptive analysis of blockchain technology to a structured accounting interpretation of DeFi from the perspective of control, measurement, and risk management concepts. Practical significance. The identification of accounting-relevant characteristics of DeFi is essential for developing a systematic approach to accounting for digital assets in a decentralized environment, as the protocol-based ecosystem of DeFi fundamentally alters the nature of the emergence of rights and obligations as well as the accrual of income, directly affecting the application of IFRS requirements. Such an approach ensures conceptual consistency between technological innovations and the regulatory framework of accounting and enhances the quality of financial information under conditions of financial system digitalization. The practical significance of the study lies in establishing a basis for updating corporate accounting policies and developing tax instruments that promote transparency and reduce risks in the digital asset sector. Prospects for further research. Future research should focus on improving disclosure standards and developing algorithmic models for the automated identification of economic transactions and tax events based on on-chain data.

Sanidhay Arora, Yingjiu Li, Yebo Feng, Jiahua Xu

Decentralized Finance (DeFi) offers open and permissionless financial services, but its core infrastructure remains exposed to serious security failures. Representative infrastructure classes such as decentralized exchanges (DEXs), protocols for loanable funds (PLFs), and cross-chain bridges matter because failures can propagate widely. This work presents a layered and empirically grounded framework for DeFi vulnerability prioritization. We analyze 558 exploit incidents from 2021–2025 and trace their mechanisms, vulnerabilities, and threat vectors across representative DeFi infrastructure classes. We introduce three complementary components: (1) a Risk Priority Number (RPN) used as an interpretable FMEA-style baseline for attack ranking, (2) an Adversarial Feasibility Score (AFS) that captures exploit feasibility from mapped adversarial-trait prevalence and accessibility, and (3) a Vulnerability-Centric Risk Score (VRS) defined as a structured priority ranking combining empirical likelihood, absolute economic severity, and attacker feasibility. The main validated model uses median per-incident USD loss as a consistent severity signal across the full incident dataset. Temporal validation shows that the structured vulnerability-priority model outperforms the multiplicative baseline and improves on the empirical base rank across both temporal holdouts and both future targets. The resulting framework provides an auditable remediation ordering for protocol developers, auditors, and risk managers.

Andrei Seoev, Dmitry Belousov, Anastasiia Smirnova, Ksenia Kurinova · 7 authors

Maximal Extractable Value (MEV) represents billions of dollars in extracted value that fundamentally shapes blockchain network dynamics and participant incentives. While research has focused on MEV extraction and mitigation, we lack systematic methods to attribute MEV opportunities to their on-chain origins. This paper formalizes the MEV opportunity attribution problem and introduces a systems framework for identifying which transactions create arbitrage opportunities and quantifying their contributions. We design and evaluate four attribution methods for atomic arbitrage on EVM-compatible networks: bot-data-driven, simulation-based, coefficient-based, and Shapley-based approaches. Through large-scale retrospective analysis spanning over one million blocks on Polygon, we demonstrate that the majority of atomic arbitrage opportunities can be traced to single source transactions, validating our central hypothesis about competitive MEV markets. We quantify a highly concentrated distribution of MEV creation, where a small subset of protocols generates most opportunities, and provide comparative analysis of method trade-offs in accuracy, cost, and scalability. Our findings offer insights for protocol designers reducing MEV leakage, validators optimizing transaction ordering, and analysts measuring ecosystem health through opportunity creation.

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li

Cross-chain NFT migration refers to the process of transferring digital assets along with their associated functionalities and guarantees between distinct blockchain platforms. However, architectural divergences among these platforms introduce critical challenges, often resulting in features that fail to behave as intended. While protocol-level mechanisms can coordinate data transfer, they are insufficient to resolve deeper compatibility issues arising from fundamental differences in state organization, transaction execution, and ownership representation. Thus, the critical challenge lies in predicting which NFT features can be preserved, which require redesign, and which are fundamentally incompatible, prior to undertaking costly migration attempts. To address this challenge, we first derive a tailored four-layer NFT architecture based on standard blockchain stacks, distinguishing cryptographic, state-management, transaction-processing, and ownership primitives, with explicit upward dependencies. Building on this architecture, we conceptualize an NFT as a bundle of features and define successful cross-chain NFT migration as the preservation of these features. Grounded in this model, we propose a four-phase migration analysis methodology comprising source feature specification, primitive-level dependency mapping, target platform profiling, and compatibility assessment, which classifies each feature as natively preserved, partially mismatched, or completely mismatched. We evaluate this methodology through a proof-of-concept analysis of Ethereum-to-Solana NFT migration, identifying several incompatibility issues that hinder seamless NFT migration.

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li

Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security auditing, often operating without centralized oversight. However, existing reputation mechanisms fail in this setting for three fundamental reasons: agents can strategically optimize against evaluation procedures; demonstrated competence does not reliably transfer across heterogeneous task contexts; and verification rigor varies widely, from lightweight automated checks to costly expert review. Current approaches to reputation drawing on federated learning, blockchain-based AI platforms, and large language model safety research are unable to address these challenges in combination. We therefore propose \textbf{AgentReputation}, a decentralized, three-layer reputation framework for agentic AI systems. The framework separates task execution, reputation services, and tamper-proof persistence to both leverage their respective strengths and enable independent evolution. The framework introduces explicit verification regimes linked to agent reputation metadata, as well as context-conditioned reputation cards that prevent reputation conflation across domains and task types. In addition, AgentReputation provides a decision-facing policy engine that supports resource allocation, access control, and adaptive verification escalation based on risk and uncertainty. Building on this framework, we outline several future research directions, including the development of verification ontologies, methods for quantifying verification strength, privacy-preserving evidence mechanisms, cold-start reputation bootstrapping, and defenses against adversarial manipulation.

Karl T. Ulrich

Renewed attention to the identity of Bitcoin's pseudonymous creator has revived an old worry: that the roughly 1.148 million BTC mined by Satoshi and never moved represent a major tail risk for bitcoin. This paper argues that the worry is overstated. The mechanical downside of selling the position is bounded well below the feared collapse, and the outcomes most consistent with sixteen years of observed behavior are not bearish for bitcoin's effective supply. We analyze the position in two ways. First, we model the case of a purely financial holder. Multiple sale scenarios, checked against both a square-root-law estimate and the historical record of large sales, suggest that bitcoin's current market liquidity could absorb a patient multi-year sale with a cumulative price impact centered around 10 to 13 percent relative to a no-sale case. The same arithmetic also links the downside from a surprise sale to the upside from a confirmed burn: both are bounded by the same effective-supply adjustment, so the doom case and the burn-rally case cannot both be large. Second, we consider the preferences implied by the sixteen-year record. Ideological restraint, privacy, already having enough, and preserving the myth all point toward further dormancy, permanent loss of access, or a deliberate burn. A sale or an act of sabotage remains possible, but the record supports it less strongly. Under both approaches, the mechanical bear case is bounded, and the likeliest outcomes are neutral to mildly positive for bitcoin's effective supply. The argument does not rule out transient overshoot or leverage-driven amplification; it bounds the durable repricing the coins themselves can cause.

Muhammet Anil Yagiz, Fahrettin Horasan, Ahmet Hasim Yurttakal

Integrity of audit logs produced by Internet of Things (IoT) devices is a prerequisite for post-incident forensics, regulatory compliance, and operational accountability. While blockchain-backed logging infrastructures can satisfy this requirement, they introduce consensus overhead, network dependencies, and deployment complexity that are often prohibitive at the IoT edge. This paper presents a lightweight and evaluated integrity verification pipeline that combines Merkle-tree commitments with resource-aware adaptive chunking to provide tamper evidence without relying on distributed ledger technologies. The proposed pipeline operates in three stages: (i) resource-aware batch ingestion via adaptive chunk sizing, (ii) Merkle-tree construction with O(logn) inclusion proof generation, and (iii) deterministic single-entry verification against a trusted root anchor. We further report an implementation audit that identified and corrected two evaluation defects: a double-counting bug in tampering metrics and a redundant full-tree reconstruction during batch appends. Using the corrected implementation, five-run benchmarks on synthetic IoT log datasets demonstrate throughput exceeding 130,000 logs/s for 100,000 records. The system achieves per-entry verification latency of approximately 22 ms, proof generation latency of 22 ms, an average proof size of 1,006 bytes, and peak memory usage below 5 MB. Tampering detection achieves perfect precision, recall, and F1-score (1.0) across corruption ratios ranging from 1% to 50%.

Divya Narendar Uppulanche

The global financial ecosystem is experiencing a paradigm shift with the integration of blockchain technology into stock trading platforms. This study explores the adoption patterns, benefits, challenges, and case evidence of blockchain implementation in financial markets worldwide. Blockchain, or Distributed Ledger Technology (DLT), offers decentralized, immutable, and transparent transaction recording, enabling enhanced efficiency, reduced settlement times, and minimized operational risks. Using a descriptive research approach, the study examines key case studies, notably the Nasdaq Linq initiative, which applied blockchain to private securities transactions to streamline recordkeeping, improve transparency, and reduce reconciliation efforts. Findings indicate that the blockchain enhances settlement speed, strengthens investor trust through transparency, and provides operational efficiencies while adoption is influenced by regulatory frameworks, technological maturity, and implementation costs. The study concludes that targeted, phased implementation, regulatory collaboration, and pilot projects are critical for sustainable adoption, of the highlighting blockchain’s transformative potential to redefine global stock trading infrastructures.

Kazunori Ohumi

Modern societies are simultaneously confronting demographic collapse and intensifying conflicts over gender equality, care, and labor. These tensions are often treated as policy trade-offs, yet they stem from a deeper ontological limitation: the reduction of human existence to functional structure (E≈S). This paper introduces Universal Phase Crystallization Theory (UPCT) as a foundational shift toward defining existence as generative resonance (E=ΦR). By reframing freedom, equality, and ethics as dynamic conditions of generative participation, the apparent conflict between demographic policy and gender equality dissolves. What emerges is not a compromise, but a civilizational transition from function-centered systems to generation-centered structures. This work provides a unified theoretical framework for rethinking equality, care, and sustainability in the 21st century. Highlights Reveals that conflicts between demographic policy and gender equality originate from a shared S-centric ontology (E≈S) Introduces UPCT (E = ΦR) as a unified framework for redefining existence, equality, and ethics Reconstructs equality as non-comparability of generative potential, beyond functional parity Demonstrates that demographic decline is a systemic failure of generative continuity (d(ΦR)/dt<0) Proposes a civilizational redesign based on generative resonance rather than labor-market optimization Summary & Main Arguments 1. Ontological Diagnosis of Modern CrisisThis paper begins by identifying a foundational contradiction in modern societies: the persistent conflict between demographic sustainability and gender equality. Rather than interpreting this as a policy failure, the paper argues that the root cause lies in an implicit ontological assumption—namely, that human existence is reducible to structural or functional representation (E≈S). Within this framework, individuals are treated as economic actors, legal units, or measurable entities, leading to systemic tensions when biological, relational, and generative dimensions cannot be fully captured. 2. Historical Saturation of Functional EqualityTracing the evolution of equality from formal legal equality to distributive and identity-based equality, the paper demonstrates that modern equality has progressively intensified its reliance on functional comparability. While these developments have been historically emancipatory, they culminate in a paradox: the more equality is pursued through structural comparison, the more differences (biological, genetic, relational) become sources of conflict. This results in a zero-sum system that ultimately fragments social cohesion. 3. UPCT as Ontological ReframingTo resolve this impasse, the paper introduces Universal Phase Crystallization Theory (UPCT), which redefines existence as generative resonance (E=ΦR). Here, Φ represents generative potential, and R relational resonance. Structure (S) is not the essence of existence but a temporary crystallization within a dynamic generative cycle (Φ→R→S→Φ′). This reframing shifts the analytical focus from static structure to dynamic process. 4. Redefinition of Core ValuesWithin the UPCT framework, the foundational concepts of modern philosophy are reinterpreted. Freedom becomes participation in generative processes rather than choice within structures. Equality is redefined as the non-comparability of generative potential rather than functional uniformity. Ethics is formalized as the sustainability condition (d(ΦR)/dt≥0), transforming it from normative prescription to systemic viability condition. 5. Policy Implications and Civilizational TransitionFinally, the paper applies this framework to the conflict between demographic policy and gender equality. It demonstrates that the conflict dissolves when both are reinterpreted through generative conditions rather than structural distribution. Policy interventions—such as reducing structural burdens, restoring relational infrastructure, elevating care, and redesigning time—are reframed as foundational requirements for sustaining generative resonance. This marks not a policy adjustment, but a civilizational transition. Contributions 1. Ontological Regrounding of Social TheoryThis paper provides a fundamental ontological critique of modern social theory by identifying the implicit equation E≈S as the root of contemporary contradictions. By introducing E=ΦR, it establishes a new foundation that integrates process, relation, and generation into the definition of existence. 2. Unified Framework Across DisciplinesThe study bridges philosophy, economics, gender studies, and systems theory by offering a single conceptual framework capable of explaining demographic decline, care crises, and equality conflicts. This integration moves beyond fragmented disciplinary approaches. 3. Redefinition of Equality and EthicsA major theoretical contribution is the redefinition of equality as non-comparability and ethics as a dynamic sustainability condition. This resolves long-standing tensions between fairness, difference, and viability, offering a new paradigm for justice theory. 4. Reinterpretation of Feminist and Critical ThoughtRather than rejecting feminist, Marxist, or care-based critiques, the paper demonstrates how these traditions can be sublated within UPCT. It preserves their insights while extending them beyond structural limitations, avoiding both reductionism and opposition. 5. Civilizational Design FrameworkThe paper advances a practical theoretical model for societal redesign. By translating UPCT into policy principles—structural reduction, relational recovery, generative elevation, and temporal redesign—it provides a concrete pathway for transitioning toward a generative society. Author’s Related Works UPCT Foundational Theoretical Works Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT): A Generative Relational Ontology of Existence, Stability, and Emergence.https://doi.org/10.5281/zenodo.19065461 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT): A Unified Generative Theory of Time, Life, and Civilization.https://doi.org/10.5281/zenodo.18653237 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase I: A Unified Resolution of Quantum Paradoxes via Temporal Sampling.https://doi.org/10.5281/zenodo.18230537 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase II: A Phase Transition Law for Generative Systems under Measurement Optimization.https://doi.org/10.5281/zenodo.18408708 Ohumi, K. (2026). Universal Phase-Crystallization Theory (UPCT) I: Generative Time and Relational Space.https://doi.org/10.5281/zenodo.18979001 Ohumi, K. (2026). From Machine Civilization to Generative Civilization: Universal Phase-Crystallization Theory and the Generative Structure of Reality.https://doi.org/10.5281/zenodo.18935934 Ohumi, K. (2026). UPCT Existential Core: A Generative Ontology for Post-Functional Civilization. https://doi.org/10.5281/zenodo.19146516 Ohumi, K. (2026). A Generative-Relational Ontology of Sustained Existence: UPCT. https://doi.org/10.5281/zenodo.19469785 UPCT Ontology and Civilizational Philosophy Ohumi, K. (2026). Existence as Generativity: Desire, Structure, and the Dynamics of Civilizational Transition in Universal Phase Crystallization Theory. https://doi.org/10.5281/zenodo.19198157 Ohumi, K. (2026). From Having to Being: Toward a Generativity-Centered Ontology in the Age of Artificial Intelligence.https://doi.org/10.5281/zenodo.18829129 Ohumi, K. (2026). The Declaration of Life-OS: An Ontological Turn Toward a Generative Civilizational Spiral.https://doi.org/10.5281/zenodo.18645582 Ohumi, K. (2026). From Proof to Resonance: A Φ-Ontology of Existence, Labor, Education, and Economic Life.https://doi.org/10.5281/zenodo.18515955 Ohumi, K. (2026). Returning to the Source of Philosophy: Affirmation of Life as the Life-OS and a Radical Point of Departure.https://doi.org/10.5281/zenodo.18529485 Ohumi, K. (2026). Dialectics as a Relational Logic of Life: From Linear Ascent to Spiral Circulation.https://doi.org/10.5281/zenodo.18522371 Ohumi, K. (2026). Does Color Exist? Overcoming the Ontological-Epistemological Confusion Through Generative Phase Transition: An Application of Universal Phase Crystallization Theory (UPCT). https://doi.org/10.5281/zenodo.19105125 Ohumi, K. (2026). From Color to Sound: Human Cognitive Limits Between Ontology and epistemology and the Generative Resolution of UPCT. https://doi.org/10.5281/zenodo.19110346 Ohumi, K. (2026). Toward a Generative Theory of Human Motivation: Participation, Existence, and the Fundamental Drive. https://doi.org/10.5281/zenodo.19286911 Ohumi, K. (2026). What is Desire? The Transition from the "Machine OS" to the "Life OS" in the History of Human Thought. https://doi.org/10.5281/zenodo.19327281 Ohumi, K. (2026). The Ontology of Resonance Beyond Generative Supremacy: The First Principle of "Existence = Generation = Resonance" and the Mandalic Hierarchy of the Life OS. https://doi.org/10.5281/zenodo.19334259 Ohumi, K. (2026). Life as Generative Resonance: An Ontological Essay on Happiness, Wealth, and the Recovery of Human Generativity. https://doi.org/10.5281/zenodo.19394468 Ohumi, K. (2026). Co-Generative Intelligence: A Relational Framework for Human–AI Collaboration Beyond Optimization. https://doi.org/10.5281/zenodo.19659573 Ohumi, K. (2026). The Equation of Knowledge Dynamics: A Generative–Relational–Structural Field Theory of Intelligence and Civilization. https://doi.org/10.5281/zenodo.19707187 Ohumi, K. (2026). The Meta-principle of Generation and the End of Ideology: Dismantling Structural Illusions and Redefining the Ontology of Value via the Equation E = ΦR. https://doi.org/10.5281/zenodo.19724468 UPCT Science and Physics Foundations Ohumi, K. (2025). A Sampling-Theoretic Reinterpretation of Quantum Uncertainty and Wave Function Collapse.https://doi.org/10.5281/zenodo.1800

Piotr Fiszeder, Witold Orzeszko, Radosław Pietrzyk

Abstract This study investigates the use of ChatGPT as an automated tool for extracting and labeling Bitcoin-related news sentiment and examines how the resulting sentiment indicators affect Bitcoin returns and volatility. A large dataset of news headlines is processed via an API-based workflow, and the ChatGPT-derived sentiment indicators are subsequently incorporated as explanatory variables into selected statistical and machine learning models, including autoregressive (AR), heterogeneous autoregressive (HAR), Bayesian model averaging (BMA), least absolute shrinkage and selection operator (LASSO), and support vector regression (SVR). We find that while the sentiment indicators significantly improve in-sample estimation accuracy for returns and volatility, they do not lead to statistically significant gains in out-of-sample forecasting performance. This result suggests that ChatGPT-based sentiment measures primarily capture contemporaneous market-relevant information rather than persistent predictive signals, consistent with semi-strong market efficiency.

M.O. Shadmanova

The development of small business at the regional level is one of the key factors ensuring sustainable economic growth, employment expansion, and reduction of territorial disparities. In emerging economies, particularly in Uzbekistan, small business entities play a significant role in generating income, stimulating entrepreneurial activity, and strengthening regional economic resilience. However, despite large-scale reforms aimed at supporting entrepreneurship, substantial differences remain among regions in terms of access to finance, infrastructure quality, market opportunities, and institutional efficiency.This article examines the economic mechanisms of small business development in the regions of Uzbekistan through a comparative analysis of international practices, including the experiences of the United States, Germany, and South Korea. The study applies comparative, statistical, institutional, and analytical methods to evaluate the effectiveness of financial-credit instruments, tax incentives, innovation infrastructure, and decentralized governance models.The findings demonstrate that successful regional small business development depends on the coordinated interaction of three major factors: effective financial mechanisms, adaptive institutional systems, and developed entrepreneurial infrastructure. The study identifies the main constraints in Uzbekistan, including centralized management, weak regional financial institutions, and uneven territorial development.Based on the results, several policy recommendations are proposed, including decentralization of support mechanisms, expansion of regional financing instruments, development of business incubators and technology parks, and implementation of differentiated regional entrepreneurship strategies. The practical significance of the study lies in developing proposals aimed at improving the competitiveness and sustainability of small business entities in the regions of Uzbekistan.

KHUSHI PATEL

Smart contracts — self-executing agreements expressed in blockchain code — are transacting billions of dollars of value daily, yet their legal enforceability under Indian law remains fundamentally uncertain. This article undertakes a systematic doctrinal analysis of smart contracts against the essential requirements of a valid contract under the Indian Contract Act, 1872 (“ICA”) and the authentication and evidentiary framework of the Information Technology Act, 2000 (“IT Act”). The analysis demonstrates that the ICA’s core requirements — offer and acceptance, consideration, capacity, free consent, and legality — can each be satisfied in a smart contract interaction when interpreted in light of the blockchain’s technical architecture. This article proposes the “Informed Interaction Standard” as a workable judicial test for offer and acceptance. It identifies two critical gaps in the IT Act: the non-recognition of blockchain cryptographic authentication as a valid electronic signature and the inapplicability of the Section 65B evidentiary certificate requirement to blockchain records. To address these gaps, the article proposes three targeted legislative interventions: a new Section 10B (IT Act) expressly validating smart contracts; a Section 3A notification recognising blockchain authentication; and a new Section 65C establishing an alternative evidentiary certification pathway for distributed ledger records. Comparative analysis of England, the United States, Singapore, and the European Union confirms that India is an outlier in its failure to resolve these questions and benchmarks the proposed reforms against best international practice. Keywords: smart contracts, Indian Contract Act 1872, Information Technology Act 2000, blockchain law, decentralised finance, digital signatures, Section 65B, electronic contracts, DAO, law reform.

Francisco R. Trejo-Macotela

This chapter examines the transformative role of blockchain as a foundational digital infrastructure for decentralised energy markets, assessing its capacity to enhance transparency, verifiability, and automated compliance in peer-to-peer electricity trading. It explores how distributed ledgers, smart contracts, and tokenised energy attributes may restructure established market arrangements by enabling immutable data governance and algorithmic execution of regulatory obligations. The analysis places particular emphasis on legal and institutional challenges, including data-protection requirements, cybersecurity vulnerabilities, allocation of liability, and the need for coherent regulatory alignment across jurisdictions. Drawing upon comparative international experiences, the chapter identifies governance approaches that support responsible experimentation while safeguarding consumer rights and system integrity. It ultimately argues that blockchain can foster resilient and equitable energy transitions when embedded within adaptive and normatively robust legal frameworks.

Bhavya Bhasuran, G. Ashwin Prabhu, G. Subash, E. Raviendiran · 8 authors

Decentralized energy markets are transforming electricity generation, distribution, and consumption by enabling peer-to-peer trading, active prosumer participation, and localized energy governance. Blockchain technology underpins these markets by delivering transparent, tamper-resistant, and automated transaction infrastructures through smart contracts and distributed ledgers. The discussion analyzes key blockchain frameworks for decentralized energy trading, focusing on platform architectures, consensus mechanisms, and interoperability models suited to energy systems. It also examines evolving regulatory pathways across jurisdictions, emphasizing interactions between decentralized trading models and existing energy laws, market rules, and grid codes. Emphasis is placed on compliance models that reconcile innovation with legal certainty, consumer protection, data privacy, and grid stability, while outlining challenges, best practices, and policy directions for scalable and compliant blockchain-enabled energy trading ecosystems.

Asif Ali Laghari, Awais Khan Jumani, Shoulin Yin, Muhammad Bux Alvi · 7 authors

Blockchain is a decentralized, public, and distributed ledger designed to securely record and track transactions. It possesses the potential to transform various industries, including healthcare, supply chain management, and financial services, by enhancing transparency, efficiency, and trust. Despite its promise, blockchain development continues to face several challenges, particularly concerning security, scalability, and standardization. This paper provides a comprehensive analysis of blockchain technology, focusing on its quality of service (QoS), security mechanisms, and the latest frameworks and models shaping its evolution. Furthermore, it examines existing limitations and identifies key open research challenges that must be addressed for broader adoption. The findings suggest that blockchain can substantially improve operational efficiency and data integrity across multiple domains; however, realizing its full potential requires continued research and technological advancement to overcome current barriers.

B Mounika, J Yugesh, J Varsha, K Sanjay

Counterfeit products pose a serious threat to global supply chains, resulting in economic losses, brand reputation damage, and consumer safety risks. Traditional centralized authentication systems are vulnerable to data tampering, lack transparency, and fail to provide end-to-end traceability. This paper proposes a blockchain-based product authentication framework that ensures secure, transparent, and tamper-proof tracking of products across the supply chain. The system integrates QR-code tagging, smart contracts, distributed ledger technology, and decentralized verification mechanisms to prevent counterfeit infiltration. Experimental evaluation demonstrates improved traceability accuracy, reduced verification time, and enhanced trust among stakeholders compared to conventional centralized databases. The proposed framework provides a scalable and secure solution for real-time product verification and counterfeit elimination.