The Monty-Hall (parameterized strategist-host) Theorem along with a constructive proof is presented, by solving the corresponding Monty-Hall Problem, wherein the host plays a parameterized strategy on the guest. It establishes the limits on the range of values for the probability of winning the prize. Eight extreme strategies (corresponding to the set of extreme values for the three perturbation parameters) have been well characterized. It is shown that there does not exist any strategy wherein a switched-choice will always (irrespective of the placement of the prize and irrespective of the initial-choice of the guest) lead to an enhancement in the chances of winning the prize. The classical Monty-Hall Problem is a special case with zero-value for each of the three perturbation parameters. This paper is an attempt to correct the errors (of long-standing historical significance) in the application of statistical methodology in solving the classical Monty-Hall Problem - one of them being the erroneous use of conditional probabilities for updating the knowledge to facilitate the decision-making by the guest, based on the information about a losing-choice, which itself is dependent on the initial-choice of the guest. Similar scenarios in data science, machine learning & artificial intelligence can have serious far-reaching consequences.
The digitalization of the architecture, engineering, and construction (AEC) industry has demonstrated the revolutionary potential of integrating blockchain technology with building information modelling (BIM). However, the selection of the most appropriate blockchain solution is a multiple-criteria decision-making (MCDM) problem, which is usually influenced by conflicting criteria and deep uncertainty. To overcome this, the present study proposes an extended Fermatean fuzzy weighted aggregated sum product assessment (Extended FF-WASPAS) model. Unlike existing Fermatean fuzzy WASPAS (FF-WASPAS) methods, which are based on a single expert and may be biased, the proposed model incorporates the evaluations of multiple decision makers (DMKs) through a consensus-driven mechanism to ensure unbiased and accurate results. A case study is conducted to evaluate five leading blockchain platforms, Hyperledger Fabric, Polkadot, Tezos, Ethereum, and Algorand, under eight BIM-related criteria. The result indicates that Ethereum is the best blockchain platform to digitalize BIM compared to the other platforms because it is scalable, interoperable, secure, and has a wide range of applications in the real world. Sensitivity analysis over a wide range of parameter values, as well as DMKs assigned with different weight sets, confirmed the stability of the ranking. Furthermore, a quantitative comparative analysis with FF multiple criteria group decision-making (FF-MCGDM) and FF-WASPAS approaches, as well as a qualitative analysis with existing models in various fuzzy environments, confirms the robustness and reliability. Overall, the study provides a strong, interpretable, and consensus-based decision-support framework with high practical value for AEC stakeholders who wish to deploy secure, transparent, and efficient blockchain-enabled BIM solutions.
Background The medical device sector, valued at $569 billion, faces persistent financing challenges. Around 78% of startups fail because of capital shortages, not due to lacking technical quality. Blockchain-based tokenization emerges as a way to broaden access, yet success relies on economic factors of platforms and clear regulations. Methods Transaction cost data from Bitcoin, Ethereum, and XRP Ledger covered 540 days from January 2024 to June 2025, providing 3,240 observations per network. Experts, numbering 12, participated in a modified Delphi method to form a framework tailored to healthcare. Project outcomes came from Monte Carlo simulations running 10,000 iterations, checked by a triple control-loop system, and compared against two real-world examples. Volumes of transactions drew from stochastic models involving monthly, quarterly, and annual elements, mixing fixed regulatory needs with variable market influences. Results Layer-1 (L1) fees differ by orders of magnitude; representative 2025 snapshots show BTC and ETH L1 far above XRPL and major ETH L2s. XRPL fees are typically a tiny fraction of a cent; the base cost is 10 drops (0.00001 XRP) and is dynamically adjusted by network load. Probabilities of success varied from 10.1% to 12.3% on Bitcoin, 31.4%–48.3% on Ethereum based on Layer-2 adoption, and 71.6%–73.2% on XRP Ledger. Investor involvement correlated negatively with logarithms of costs, showing Spearman <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mrow><mml:mi>ρ</mml:mi></mml:mrow></mml:math> of −0.91. Differences in success exceeded 60 percentage points across platforms. Examples illustrated how elevated expenses reduce engagement in VitaDAO on Ethereum, whereas low-cost systems like XRP Healthcare support ongoing involvement. Conclusion Choosing a blockchain platform critically influences viability in tokenizing medical devices. Layer-2 options reduce cost gaps but add complexities in bridging and use. Platforms offering stability, minimal fees, and regulatory alignment promote wider inclusion and reliable funding. Technical features, steady costs, and readiness for compliance together shape whether tokenization boosts innovation in healthcare or maintains barriers.
Open access
Quality and Safety in Healthcare
Neuroethics, Human Enhancement, Biomedical Innovations
Slow and disputed progress payments undermine contractor liquidity and project schedules due to manual verification, fragmented data, and limited transparency. This paper presents a prototype system that incrementally integrates digital twin (DT), building information modeling (BIM), and blockchain to automate milestone-based payments. The continuously updated DT is conceptualized as a dynamic oracle, capturing real-time site conditions and comparing them with structured BIM milestones. Verified achievements trigger Ethereum smart contracts referencing Merkle-proofed evidence stored off-chain in InterPlanetary File System (IPFS), with disbursements authorized via Gnosis Safe multi-signature wallets. A prototype on a police station project shortened verification to payment from several days to minutes and eliminated disputes across all milestones. A survey of industry professionals confirmed gains in efficiency, transparency, and trust. The proposed system provides a practical foundation for transparent, automated payments and offers pathways for future adoption such as stablecoin settlement and public sector integration. • Digital twins resolve blockchain oracle challenges in construction payments. • BIM-blockchain integration reduces payment verification from days to minutes. • Smart contracts with multi-signature governance secure transaction integrity. • Stakeholders confirm enhanced payment speed, transparency, and trust.
Sabri Barbaria, Abderrazak Jemai, Halil İbrahim Ceylan, Raul Ioan Muntean · 6 authors
Background: Healthcare data interoperability faces significant barriers, including regulatory compliance complexities, institutional trust deficits, and technical integration challenges. Current centralized architectures demonstrate inadequate mechanisms for balancing data accessibility requirements with patient privacy protection, as mandated by HIPAA and GDPR frameworks. Traditional compliance approaches rely on manual policy implementation and periodic auditing, which are insufficient for dynamic, multi-organizational healthcare data-sharing scenarios. Objective: This study develops and proposes a blockchain-based healthcare data management framework that leverages Hyperledger Fabric, IPFS, and the HL7 FHIR standard and incorporates automated regulatory compliance mechanisms via smart contract implementation to meet HIPAA and GDPR requirements. It assesses the theoretical system architecture, security characteristics, and scalability considerations. Methods: We developed a permissioned blockchain architecture that employs smart contracts for privacy policy enforcement and for patient consent management. The proposed system incorporates multiple certification authorities for patients, hospitals, and research facilities. Architectural evaluation uses theoretical modeling and system design analysis to assess a system’s security, compliance, and scalability. Results: The proposed framework demonstrated enhanced security through decentralized control mechanisms and cryptographic protection protocols. Smart contract-based compliance verification can automate routine regulatory tasks while maintaining human oversight in complex scenarios. The architecture supports multi-organizational collaboration with attribute-based access control and comprehensive audit-trail capabilities. Conclusions: Blockchain-based healthcare data-sharing systems provide enhanced security and decentralized control compared with traditional architectures. The proposed framework offers a promising solution for automating regulatory compliance. However, implementation considerations—including organizational readiness, technical complexity, and scalability requirements—must be addressed for practical deployment in healthcare settings.
AbstractAs a key bridge between the real economy and financial capital, supply chain finance generates core data such as transaction documents, logistics information, and financing contracts, whose secure, trustworthy, and controllable management is crucial.Traditional centralized notarization schemes suffer from single points of failure, risks of data tampering, and high trust costs.Although blockchain offers tamper-evident notarization, limited on-chain storage and throughput constrain its direct use in large-scale data scenarios.To address this tension, this paper investigates a secure data notarization and access control algorithm grounded in an on-chain/off-chain hybrid storage architecture and smart contracts.We first construct a layered data management model: high-value, low-volume data hashes (digital fingerprints) and key access-control policies are anchored on-chain to ensure immutability, while complete large-volume raw data are encrypted and stored off-chain (e.g., in IPFS or distributed databases) to ensure scalability.To tackle potential challenges of on-/off-chain consistency and integrity verification under this hybrid architecture, we design an efficient verification mechanism based on cryptographic commitments, ensuring any tampering with off-chain data can be detected quickly and succinctly.Furthermore, to achieve fine-grained privacy protection and compliant use, we propose a smart-contract-based dynamic access control algorithm.By deploying access-control policies as executable code on-chain, the algorithm performs automated logical checks to deliver precise authorization and comprehensive audit logging, ensuring security and transparency throughout data sharing and circulation.Through theoretical security analysis and prototype experiments, the proposed scheme preserves data immutability and traceability while significantly improving the storage efficiency and processing performance of supply chain finance notarization systems, and it enables flexible and secure access control.The results indicate that the coordinated mechanism of on-chain/off-chain hybrid storage and smart contracts offers a feasible technical pathway for building efficient, trustworthy, and secure supply chain finance infrastructure.
This article explores the characteristics of data resources from the perspective of production factors, analyzes the demand for trustworthy circulation technology, designs a fusion architecture and related solutions, including multi-party data intersection calculation, distributed machine learning, etc. It also compares performance differences, conducts formal verification, points out the value and limitations of architecture innovation, and looks forward to future opportunities.
Electric vehicles (EVs) are increasingly central to sustainable mobility, yet their integration into smart city infrastructures remains limited by centralized data systems that restrict scalability, threaten user privacy, and heighten exposure to cyber risks. Most prior work has concentrated on technical performance, with little attention to governance requirements such as accountability, regulatory compliance, and citizen trust. To address this gap, this study develops a decentralized EV data management framework based on IOTA’s Tangle, a distributed ledger designed for secure, scalable, and fee-less interactions across vehicles, charging stations, and urban digital platforms. Using a comparative design, conventional blockchain systems are evaluated against IOTA through simulation results. Findings show that the IOTA-based model sustains faster validation, eliminates fees, and supports higher throughput, while also aligning with governance principles reflected in policies such as the GDPR. The study demonstrates how distributed ledgers can advance both technical feasibility and trust in EV ecosystems.
У період суспільних криз та нестабільності стратегічний фандрайзинг стає важливим практичним інструментом забезпечення фінансової стабільності та соціально-економічного розвитку. Метою роботи є аналіз стратегічних підходів до інноваційного потенціалу фандрайзингу, які можуть бути успішно використані для ефективного залучення фінансування. Методологія. У процесі дослідження було застосовано загальні наукові методи: аналіз і синтез, порівняння, структурно-логічний метод, систематизація, узагальнення та абстракція. Наукова новизна. У дослідженні розглянуто проблематику стратегічного фандрайзингу у контексті інструментарію фінансової підтримки в умовах обмеженого ресурсного забезпечення. Розглянуто різні підходи до фандрайзингу, в тому числі – цифрового, традиційного, інноваційного та партнерського. Проаналізовано особливості конкретних стратегій та інструментів, таких, як краудфандинг, онлайн-платформи, технології non-fungible tokens (NFT). Встановлено, що комплексний підхід до фандрайзингу, який асимілює сучасні та традиційні методи, дозволяє забезпечити максимальну ефективність у досягненні фінансової стабільності. Висновки. У дослідженні обґрунтовано, що краудфандинг, онлайн-платформи та NFT позиціонуються надійними інструментами фандрайзингу, зокрема, на етапі формування стратегії діяльності компанії. Запропоновано ключові підходи до врегулювання ринку краудфандингових інвестицій. Доведено, що розглянуті види альтернативного фінансування та підтримки вбачаються дієвим засобом трансформації підходів до фінансування інноваційних проєктів. Проведена у статті аналітика дозволяє ідентифікувати переваги моделей фандрайзингу, а також виділити дотичні ризики та виклики, що дозволить розробляти та впроваджувати ефективні стратегії їх нівелювання.
The explosive popularity of blockchain-based gaming has brought non-fungible tokens (NFTs) into the fray, as tradable collectibles that connote not only monetary worth but an experience as well. In contrast to traditional in-game items, gaming NFTs exist in two domains of use, on-chain marketplaces and off-chain ecosystems, providing new twists to their valuation. This paper analyzes the approach, issues, and possible developments of the NFT gaming collectibles valuation by consolidating the knowledge in economics, data science, and digital games research. We then present a taxonomy of value drivers, gameplay utility, rarity, provenance, community effects, and tokenomics, to develop a conceptual background. We then compare the relative advantages and (*) disadvantages of popular valuation methods, including hedonic pricing models, repeat-sales indices, machine learning, and liquidity-adjusted approaches. We also identify structural issues of this nascent market, including wash trading, fragmentation of liquidity, evolving product utility, mutability of metadata, and regulatory uncertainty. Critical synthesis helps us see how valuation practices are susceptible to abuse on both sides: how we can abuse the market, but also how we can design the technical aspects of markets to cheat. Lastly, we discuss research directions in the form of standardized benchmarks, dynamic valuation frameworks, interoperability-adjusted models, and integrity checks. The paper will contribute to both the academic and practice worlds as it will provide a reproducible course of action by scholars, game development companies, investors, and marketplaces interested in designing open and sustainable valuation methods for the gaming NFTs.
This study presents a comprehensive ten-year (2015–2024) evaluation of renewable energy development in Cameroon, emphasizing its intersection with Sustainable Development Goals (SDGs) and broader cross-sectoral development outcomes. Combining time-series analysis of national capacity data, policy content evaluation, and SDG-aligned simulation modeling, the paper assesses both technical and institutional trajectories of the energy transition. Key findings reveal a substantial increase in off-grid installations in underserved regions and a notable rise in grid-connected solar capacity—from 0 MW in 2015 to 63 MW by 2024—driven largely by post-2017 policy decentralization. Hydropower remains the dominant source, but the solar sector exhibited accelerated growth, contributing to enhanced rural electrification and public health infrastructure, with 27 % of rural health institutions now electrified. The renewable energy sector generated an estimated 3500 new jobs over the decade. An SDG alignment index applied across five targets indicates moderate but uneven progress, particularly for Goals 7 (affordable and clean energy), 3 (good health and well-being), and 13 (climate action). Scenario-based simulations underscore that policies promoting decentralized innovation and integrated energy planning significantly enhance rural energy access and socio-economic resilience. However, persistent financing barriers and institutional fragmentation constrain broader impact. The study offers a replicable analytical framework for data-driven, SDG-oriented assessment of energy transitions in Sub-Saharan Africa, contributing actionable insights for sustainable energy policy design in low-resource contexts. • Renewable energy in Cameroon grew steadily between 2015 and 2024. • Off-grid solar access expanded, boosting rural electrification progress. • Policy reforms accelerated decentralized energy access and regulation. • RE growth improved health, jobs, and equity across sectors. • A roadmap aligns RE planning with SDG targets for Cameroon.
René Dávila, Everardo Bárcenas, Rocío Aldeco-Pérez
Formal verification entails testing software to ensure it operates as specified. Smart contracts are self-executing contracts with the terms of the agreement directly written into lines of code. They run on blockchain platforms and automatically enforce and execute the terms of an agreement when meeting predefined conditions. However, Smart Contracts, as software models, often contain notable errors in their operation or specifications. This observation prompts us to conduct a focused study examining related works published across various sources. These publications detail specifications, verification tools, and relevant experiments. Subsequently, this survey proposes an alternative formal verification based on description logic.
With the rapid adoption of diffusion models for visual content generation, proving authorship and protecting copyright have become critical. This challenge is particularly important when model owners keep their models private and may be unwilling or unable to handle authorship issues, making third-party verification essential. A natural solution is to embed watermarks for later verification. However, existing methods require access to model weights and rely on computationally heavy procedures, rendering them impractical and non-scalable. To address these challenges, we propose NoisePrints, a lightweight watermarking scheme that utilizes the random seed used to initialize the diffusion process as a proof of authorship without modifying the generation process. Our key observation is that the initial noise derived from a seed is highly correlated with the generated visual content. By incorporating a hash function into the noise sampling process, we further ensure that recovering a valid seed from the content is infeasible. We also show that sampling an alternative seed that passes verification is infeasible, and demonstrate the robustness of our method under various manipulations. Finally, we show how to use cryptographic zero-knowledge proofs to prove ownership without revealing the seed. By keeping the seed secret, we increase the difficulty of watermark removal. In our experiments, we validate NoisePrints on multiple state-of-the-art diffusion models for images and videos, demonstrating efficient verification using only the seed and output, without requiring access to model weights.
The integration of blockchain technology into healthcare presents a paradigm shift for secure data management, enabling decentralized and tamper-proof storage and sharing of sensitive Electronic Health Records (EHRs). However, existing blockchain-based healthcare systems, while providing robust access control, commonly overlook the high latency in user-side re-computation of hashes for integrity verification of large multimedia data, impairing their practicality, especially in time-sensitive clinical scenarios. In this paper, we propose FAITH, an innovative scheme for \underline{F}ast \underline{A}uthenticated and \underline{I}nteroperable mul\underline{T}imedia \underline{H}ealthcare data storage and sharing over hybrid-storage blockchains. Rather than user-side hash re-computations, FAITH lets an off-chain storage provider generate verifiable proofs using recursive Zero-Knowledge Proofs (ZKPs), while the user only needs to perform lightweight verification. For flexible access authorization, we leverage Proxy Re-Encryption (PRE) and enable the provider to conduct ciphertext re-encryption, in which the re-encryption correctness can be verified via ZKPs against the malicious provider. All metadata and proofs are recorded on-chain for public verification. We provide a comprehensive analysis of FAITH's security regarding data privacy and integrity. We implemented a prototype of FAITH, and extensive experiments demonstrated its practicality for time-critical healthcare applications, dramatically reducing user-side verification latency by up to $98\%$, bringing it from $4$ s down to around $70$ ms for a $5$ GB encrypted file.
Non-fungible tokens (NFTs) have garnered attention because of their potential to disrupt traditional business models in various industries. This study provides insights into the drivers of individuals' intentions to purchase NFTs by investigating the relationship between perceived value (scarcity, uniqueness, verifiability, and royalty), as well as facilitating conditions, social influence, individual differences, and personality traits, and the intention to purchase NFTs. Decision-makers, creators, and investors can benefit from understanding these drivers. The proposed model integrates constructs from multiple adoption frameworks and related NFT literature to analyze the individual determinants of NFT purchase intentions. This study utilized a survey to collect data from participants and employed the partial least squares structural equation modeling (PLS/SEM) technique to validate the proposed model empirically. The findings indicate that perceived value, facilitating conditions, social influence, individual differences, and personality traits significantly shape individuals’ intentions to purchase NFTs. Perceived scarcity, verifiability, and royalty were found to be positively associated with perceived value, whereas perceived uniqueness did not demonstrate a statistically significant relationship. Furthermore, the study suggests that individual differences and personality traits do not moderate the relationship between perceived value and NFT purchase intention. However, individual differences and personality traits are directly associated with NFT purchase intention.
Octara Pribadi, Johanes Terang Kita Perangin Angin, Erick Erick
The development of information technology has driven the need for stronger security systems and guaranteed privacy on web-based platforms. Traditional verification methods such as passwords and two-factor authentication are increasingly seen as insufficient in facing the growing complexity of cyber threats. Zero-Knowledge Proof (ZKP) emerges as an alternative solution that enables identity verification without revealing sensitive information. This research aims to implement ZKP technology in web-based systems to enhance user security and privacy. The method involves the implementation of a simple XOR-based ZKP algorithm to prove identity without disclosing personal data, as well as a three-step verification mechanism between the verifier and the prover. Implementation results show that the system can prevent attacks such as man-in-the-middle and replay attacks, while maintaining data confidentiality during the authentication process. This study also identifies challenges in system efficiency and verification process integrity and offers technical solutions to support broader ZKP integration in digital platforms. Thus, the use of ZKP in web-based systems holds great potential to improve user trust and security in the digital era.
Following the stablecoin legislation (GENIUS Act) enacted under the second Trump administration in 2025, blockchain has become core digital economy infrastructure. However, privacy risks from decentralization and transparency constrain adoption in regulated industries, requiring solutions that harmonize blockchain architecture with regulatory compliance. Existing research relies on reactive auditing or post-execution rule checking, which wastes computational resources or provides only basic encryption or access controls without comprehensive privacy compliance. The proposed Artificial Intelligence-enhanced Regulatory Proof-of-Compliance (AIRPoC) framework addresses this gap through a two-phase consensus mechanism that integrates AI legal agents with semantic web technologies for autonomous regulatory compliance enforcement. Unlike existing research, AIRPoC implements a dual-layer architecture where AI-powered regulatory validation precedes consensus execution, ensuring that only compliant transactions proceed to blockchain finalization. The system employs AI legal agents that automatically construct and update regulatory databases via multi-oracle networks, using SPARQL-based inference engines for real-time General Data Protection Regulation (GDPR) compliance validation. A simulation-based experimental evaluation conducted across 24 tests with 116,200 transactions in a controlled environment demonstrates 88.9% compliance accuracy, with 9502 transactions per second (TPS) versus 11,192 TPS for basic Proof-of-Stake (PoS) (4.5% overhead). This research represents a paradigm shift to dynamic, transaction-based regulatory models that preserve blockchain efficiency.
This article explores the application of financial technologies in the auditing of decentralized finance (DeFi) and how these technologies can improve the audit process. The research aims to identify the main challenges faced in DeFi auditing and to offer recommendations for strengthening audit methodologies using financial technologies (FinTech). The article discusses decentralized finance and its innovative management principles based on blockchain technology, which fundamentally transforms traditional financial systems. The study identifies key risks associated with DeFi, such as vulnerabilities in smart contracts and the lack of regulatory frameworks. The theoretical foundation includes a detailed analysis of the differences between traditional and decentralized finance, highlighting DeFi’s advantages – lower operational costs, greater accessibility, and transparency – while addressing regulatory and security challenges. The research methodology is based on scientific literature analysis and the classification of FinTech tools according to established criteria to evaluate the effectiveness of audit methods and their potential for improvement. The main findings show that FinTech tools, such as artificial intelligence (e.g., decision tree models) and blockchain technology, enhance the reliability and speed of DeFi audits while highlighting the need for a more robust regulatory system. This article is relevant due to the rapid growth of the DeFi sector and its importance in the digital transformation of the financial industry. Moreover, this research aims to classify the most widely used financial technology tools according to their functions and analyze their impact on traditional and decentralized finance auditing processes, offering insights for improving audit methodologies.
Open collaboration business models (OCBMs) and software have existed since the 1950s but have been plagued by work ethic and financial bottleneck due to inadequate monetization schemes. OCBMs provide a range of advantages, primarily in accelerating problem solving & innovation, reducing costs, and enhancing security and transparency. Companies could establish sustainable revenue streams while benefitting from broad tech or platform adoption. However, fair revshare and credit attribution have been persistent problems with OCBMs. Businesses such as Diaspora, Soul Force, Sun Microsystems' Open Solaris, and others have experienced unsustainable OCBM initiatives, especially in the open-source software area. Web3 ethos-based business models and blockchain technologies provide an opportunity to correct and enforce many of the monetization strains associated with open collaboration. By decentralizing operational and governance control, free markets nested within companies that run themselves can be realized. The basic philosophy for a meritocratic monetization system with fair credibility-revshare automation is discussed.
Betas from spot regressions are central to asset pricing and risk management, as measures of systematic risk. This paper develops a new estimation and inference framework for spot regressions by leveraging high-frequency candlesticks, extending conventional (open-to-close) returns with intra-period high/low prices. Specifically, I construct candlestick-based estimators of regression parameters, including spot beta, by minimizing a quadratic risk under a fixed-k asymptotic framework. I then develop a feasible hypothesis testing procedure for spot betas with correct asymptotic size. Simulation results show that the proposed estimator reduces estimation risk relative to return-based estimators, especially in small samples, and the test achieves notably higher power. I apply the framework to assess the market neutrality of Bitcoin using 1-minute data on IBIT and SPY, finding deviations from neutrality, particularly in high-volatility periods.
Supply chain operations that include blockchain technology have the potential to improve cybersecurity and data integrity. The complexity and interconnectedness of global supply chains make it imperative to guarantee the security and validity of data for all parties involved. Because blockchain technology is decentralized, transparent, and unchangeable, it offers a perfect solution to common supply chain weaknesses, including fraud, data tampering, and illegal access. The use of blockchain technology to protect important data at each link in the supply chain—from manufacturing and procurement to distribution and delivery—is examined in this article. By leveraging smart contracts, cryptographic security, and distributed ledger systems, blockchain can ensure the traceability of goods, validate transactions, and protect sensitive information from cyber threats. The paper also highlights how blockchain has the potential to completely transform supply chain management security while addressing issues like scalability, integration with current systems, and regulatory considerations. In the end, this study highlights how blockchain technology may improve data integrity, lower cyber threats, and foster trust among supply chain actors.
The U.S. withdrawal from the Paris Agreement represented a pivotal setback in global climate governance, disrupting established funding streams, undermining emission reduction targets, and eroding multilateral trust. This systematic review synthesizes empirical and policy analyses to evaluate the political, economic, and scientific consequences of U.S. disengagement, with particular attention to disparities between developed and least developed countries (LDCs). Findings reveal three critical trends: (1) a substantial decline in reliable climate finance, disproportionately affecting LDCs; (2) weakened accountability mechanisms for major emitters; and (3) increased fragmentation in diplomatic negotiations. This paper argues that COP30 in Brazil (2025) must prioritize decentralized leadership models and robust, equitable climate finance mechanisms to restore momentum. Future research should explore quantifiable metrics for translating global stocktake outcomes into actionable national policies for high-emission economies and assess the efficacy of non-state actors in addressing identified governance gaps.
This paper examines the concepts of federalism, fiscal federalism, and fiscal decentralization, with a focus on the Indian context. It outlines the constitutional and institutional foundations of India’s federal structure, tracing the historical evolution of fiscal decentralization from the colonial period to the post-independence era including pre- reform era. The study analyses revenue-sharing mechanisms, taxation policies, and grants-in-aid, alongside the roles of key institutions such as the Finance Commission, GST Council, and NITI Aayog. Findings highlight persistent vertical and horizontal imbalances, the positive impact of GST on state fiscal autonomy, and the continuing need for equitable and efficient fiscal arrangements. The paper concludes with policy recommendations aimed at strengthening cooperative federalism, enhancing state-level fiscal flexibility, and improving transparency in intergovernmental transfers.