Abdulkadri Toyin Alabi, Abdulrasaq Mustapha, Lukman Adebayo-Oke Abdulrauf
Purpose This study aims to evaluate the interplay of climate finance, green technologies, and energy transition in shaping environmental sustainability within the MINT economies (Mexico, Indonesia, Nigeria, Turkey), using the load capacity factor (LCF) as a comprehensive ecological indicator. Design/methodology/approach The study adopts the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) approach, capturing periods from 2000 to 2021. The robustness of the findings is subsequently reinforced through the application of Common Correlated Effects Mean Group and Dynamic Common Correlated Effects Mean Group (DCCEMG) estimators. Findings The results reveal that climate finance significantly enhances the LCF, affirming its role in promoting environmental sustainability through targeted investments in renewables. Energy transition exerts a short-term negative impact on LCF, reflecting the “transitional paradox,” where reliance on energies temporarily exacerbates ecological strain. However, green technologies show no statistically significant effects, likely due to fragmented adoption in MINT economies. Lastly, the study explores the U-shaped trajectory proposed by the LCC (load capacity curve) hypothesis and finds that it is not statistically validated for MINT economies. Practical implications Climate finance should prioritize high-impact renewables over transitional fuels to accelerate long-term sustainability. Moreover, energy transition timelines must account for short-term ecological costs; for instance, MINT nations could pair gas flaring reduction with decentralized solar grids to mitigate transitional harm. Policymakers should consider implementing targeted financial instruments to channel investments into sectors with the highest environmental returns. Originality/value This study introduces pioneering contributions to climate finance and sustainability research by developing a first-of-its-kind climate finance index, which captures the pragmatic energy transition strategies of emerging economies by integrating both renewable and transitional fuel investments.
Non-custodial staking in Ethereum empowers users to participate in securing the network without transferring their funds to any entity other than the official deposit contract. This approach minimizes the need for trust in third parties, aligning with the core principles of decentralization. However, there is a lack of studies to understand the risk that a staker takes when choosing a non-custodial solution. Furthermore, non-custodial staking may be difficult for non-technical users. In this paper, we analyze the risk of non-custodial staking in Ethereum and we provide some tools to simplify some of the processes for non-technical users. We introduce a detailed threat model in which an attacker gains access to a validator’s private key, and evaluate both the direct financial losses due to slashing and the potential economic incentives for an attacker. Two attack scenarios are explored-targeting solo stakers and coordinated attacks on non-custodial services-quantifying their impact and feasibility. We also provide lightweight Python scripts that enable users to generate and validate voluntary exit messages without deploying a full Ethereum node. These tools are especially relevant for increasing the resilience of non-custodial staking, particularly in the event of service disruption. Our results suggest that while validator key exposure is a serious risk, rational non-custodial providers are economically disincentivized from behaving maliciously.
The verifiability of machine learning models and the privacy of training data have become critical concerns due to their widespread deployment in sensitive applications. Ensuring that a model performs as claimed, without revealing private data or algorithms, is a significant challenge. Zero-Knowledge Proof systems (ZKPs) have emerged as a promising cryptographic solution, enabling the verification of statements without disclosing underlying information. Their integration with blockchain technology further enhances trust and decentralization, offering robust solutions for secure and transparent AI systems. This paper explores the use of ZKPs in machine learning, focusing on privacy-preservation techniques, model verifiability, and confidential AI. It compares the differences and challenges of employing ZKPs in machine learning versus blockchains, highlighting their unique requirements and overlapping benefits. We review the basic concepts of ZKPs, advances such as zkSNARKs and zk-STARKs, and their applications in blockchainbased AI frameworks to ensure data integrity, immutability, and scalability. Furthermore, the paper delves into the practical implications of using ZKPs in AI, providing case studies and analyzing their scalability, performance, and limitations. We conclude by identifying key challenges and presenting future research directions to extend the applicability of ZKPs in AI, particularly in federated learning, model fairness, and decentralized AI pipelines.
Delia-Elena Bărbuță, Cristian Nicolae Buţincu, Adrian Alexandrescu
Encouraging green innovation has become increasingly important in order to address sustainability challenges, yet startups and early-stage initiatives in this domain face numerous barriers, including lack of structured guidance, limited access to mentorship and funding, and concerns around intellectual property protection. This paper presents a solution entitled SPARK-IT GREEN, a decentralized platform designed to support eco-friendly innovation through a secure and transparent ecosystem. Building upon the original SPARK-IT framework, the platform introduces several new features, including a Green Business Model Canvas, lifecycle-aware AI matchmaking, decentralized governance via a Decentralized Autonomous Organization (DAO), and advanced intellectual property protection through blockchain-integrated encrypted storage. As an incentive for users to join the proposed SPARK-IT system, they can earn reward and reputation tokens. Our novel solution empowers innovators to define sustainability goals, find verified expert support, and apply for DAOgoverned funding based on community-aligned green priorities. It uses smart contracts deployed on a permissioned blockchain, token-based incentives, and a semantic matchmaker enriched with green project metrics. A detailed use case scenario shows how the proposed system can be used by a biodegradable packaging startup. SPARK-IT GREEN sets the foundation for a scalable, transparent, and sustainability-focused innovation ecosystem.
Traditional food supply chains are plagued by issues related to transparency, traceability, and food safety, resulting in inefficiencies, delays, and risks of contamination. In Saudi Arabia, operations within many supply chains rely on centralized systems without any possibilities for tracking origins of the product, conditions monitored, or conformity with regulatory guidelines guaranteed. Farm-to-Fork is a blockchainbased food supply chain management platform that seeks to address these problems through the use of Ethereum smart contracts, IoT temperature monitoring, and a decentralized framework mainly in the Saudi Arabian ecosystem. Built incrementally using Agile methodology and tools like Solidity, Truffle, and Web3.js, the platform offers secure, automated, and transparent transactions. Data was collected through interviews and surveys with manufacturers, distributors, and retailers, indicating that $76.7 \%$ of the stakeholder’s experience visibility issues, $66.7 \%$ experience contamination detection issues, and $90 \%$ think blockchain would improve transparency and data security. Farm-to-Fork offers traceability automated temperature validation, and tamper-proof records, significantly improving efficiency, accountability, transparency, and food safety regulation enforcement, the platform offers verifiable, secure, and trustless supply chain processes, an improved standard of food traceability for Saudi Arabia.
This paper addresses the application of blockchain in Digital Twin (DT) systems, which often rely on centralized architectures, by proposing and evaluating a decentralized management system for vehicle DTs. The system uses Ethereumbased ERC-1155 NFTs to represent vehicles. Smart contracts handle NFT minting, ownership transfers, and a three-phase lifecycle. Off-chain data is stored on IPFS, with privacy secured by an algorithm based on ECDH. A decentralized application was developed to enable interaction with the blockchain and IPFS. Evaluation of the system included static analysis, automated testing, and gas cost analysis. The system is capable of managing a vehicle NFT from its inception until its decommissioning, with all actions recorded on the blockchain and IPFS. While scalable at the smart contract level, Ethereum’s network throughput can pose limitations for full-scale automotive industry adoption, suggesting suitability for smaller-scale applications or the necessity for improvements in both Layer 1 and Layer 2 solutions. This work demonstrates a feasible end-to-end Web3 solution for vehicle Digital Twins, bringing transparency and data integrity to the vehicular ecosystem.
Distributed-ledger technologies (DLTs) have upended the design logic of, data-sharing web architectures, especially within sectors that demand uncompromising transparency, indelible audit trails, and decentralised governance. Yet curating an optimal DLT stack remains an intricate optimisation puzzle involving nuanced trade-offs across cryptographic rigour, elastic scalability, experiential ergonomics, propagation latency, cross-ledger interoperability, and fiscal prudence. To navigate this complexity, we introduce a tiered decision-support framework that welds expert-elicited priorities to empirical performance signals within a rigorous multi-criteria outranking model. The scheme yields transparent, rank-ordered shortlists of candidate ledgers and is demonstrated across healthcare, fintech, and supply-chain provenance scenarios. Results confirm the model’s ability to surface context-specific “best fits” even when decision objectives clash, thereby equipping engineers, CIOs, and policy designers with a defensible roadmap for trustworthy, efficient, and governance-aligned blockchain adoption. Future iterations will embed fuzzy logic and live-telemetry feedback to sharpen responsiveness in rapidly evolving operating environments.
Yazid Maafa, Alexandre Chalal, Jiahui Xiang, Osman Salem · 5 authors
Blockchains have revolutionized information systems, evolving continuously in both performance and application sophistication. This paper compares public blockchain performances by examining their technical foundations and practical applications across sectors. Through benchmark analysis of key criteria, we develop hypotheses explaining performance variations. Our goal is to provide insight into this maturing ecosystem whose impact now extends well beyond cryptocurrencies into numerous innovation domains.
This study employs a theoretical, system design–based methodology to propose the Palm GreenChain framework—a blockchain-based platform aimed at enhancing traceability, transparency, financial coverage, and accountability in green bond financing for sustainable palm oil production in Malaysia. The methodology integrates Ethereum-compatible smart contracts, ESG oracles, IPFS-based data storage, and DAO (Decentralized Autonomous Organization) governance to structure a digital green bond lifecycle. Rather than relying on empirical data collection, the framework is conceptualized through the development of a multi-layered blockchain architecture and validated via comparative analysis with analogous blockchain applications in agriculture. The proposed system is designed to enable real-time traceability of green bond disbursements, automate ESG compliance verification using satellite and IoT data, and strengthen accountability and access to climate finance for smallholder farmers. By embedding performance-based returns within smart contracts, the model aligns financial incentives with conservation goals. Leveraging Malaysia’s advanced land administration infrastructure and digital capabilities, the framework presents a scalable, open-source solution to reduce greenwashing, expand financial inclusion in underserved agricultural communities, and enhance transparency and investor confidence in sustainable agricultural finance. By directly linking green finance to verifiable sustainability outcomes, Palm GreenChain addresses key limitations in conventional green bond mechanisms. Its applicability across diverse agricultural sectors positions it as a replicable blueprint for broader sustainable development. The framework is openly available via its GitHub repository.
Marcel Pehlke, Sophia Fedder, Clemens Schmitt, Mike Witkowski · 5 authors
Managing cryptographic keys remains a major barrier to blockchain adoption, especially for non-technical users. This paper presents a smart cardbased solution for secure and user-friendly key management, offering physical isolation of private keys and PIN-protected access via NFC. In a comparative study with the Waves Keeper browser extension, 33 participants completed blockchain-related tasks and rated both solutions in different categories of the Technology Acceptance Model (TAM) such as Perceived Usefulness, Ease of Use, and Result Demonstrability. The smart card system showed clear advantages in usability and perceived security. In general, the results highlight the potential of hardware-based approaches to improve blockchain accessibility and acceptance, with implications for Web3 applications and future research on usability and security integration.
Jeffson C. Sousa, Bruno Evaristo, Antonio Mateus, Ismael Ávila · 6 authors
This paper presents a performance evaluation of smart contracts designed for managing decentralized digital identities on Ethereum-based blockchain networks. The analysis focuses on core identity lifecycle operations such as creation, update, credential schema definition, and revocation control, all implemented through Solidity smart contracts. Two execution contexts were considered: an environment using Hyperledger Besu operating in permissioned mode, and a reference to the traditional Hyperledger Indy model. The tests were conducted in a private network simulating different load levels and consensus configurations. The evaluated metrics include response time, throughput, resource usage, and scalability. The results provide insights to support the selection of efficient architectures for digital identity solutions based on Self-Sovereign Identity (SSI) and Ethereum, particularly in enterprise or regulated environments.
Mohammad Alja’afreh, Sarah Tarawneh, Hikmat Adhami, Ali Karime · 5 authors
The metaverse—a persistent, multiuser fusion of digitally augmented reality and computer-generated virtuality— is emerging as a programmable substrate for identity, assets, and interaction. Its heterogeneous stack (XR clients, engines/SDKs, Web3 rails, wallets, marketplaces) enlarges the attack surface. This paper contributes: (i) a structured threat taxonomy specialized for Web3/XR platforms; (ii) explicit system and adversary models; (iii) a risk quantification scheme combining behavioral and on-chain signals; and (iv) a data-driven defense architecture aligning decentralized identity, wallet/custody guardrails, analytics, AI-aided detection, and policy instrumentation. We further instantiate these controls in the Medical MeTAI context, where confidentiality, integrity, and provenance requirements are stringent.
The relevance of the study is determined by the need for in-depth study and systematization of innovative decision-making methods that Web3 technologies offer to the modern business environment. In the context of global digital transformation, traditional approaches to management and finance are proving insufficient to ensure the competitiveness and sustainable development of organizations. The purpose of this article is to analyze Web3 tools, in particular blockchain, asset tokenization, decentralized finance (DeFi), and decentralized autonomous organizations (DAOs), as a basis for forming new, more transparent, secure, and effective methods and models for management decision-making. The paper applies a comprehensive methodology that includes a systematic analysis of the functional capabilities of Web3 technologies and a structural-logical approach to classifying their impact on corporate governance and financial management. The use of case studies has made it possible to illustrate the practical aspects of integrating these tools into the activities of large companies. The results confirm that Web3 is not only a technological trend but also a new paradigm that provides managers with qualitatively different tools. It has been established that blockchain creates a foundation for trust and data security; tokenization and DeFi radically increase the flexibility and liquidity of financial management; and DAOs transform corporate governance into a collective and inclusive process. In addition, the integration of AI agents into routine operations allows managers to effectively refocus their attention on strategic planning. The practical value of the article lies in providing organizations with clear recommendations for implementing Web3 technologies: from the need to start with pilot projects to test systems and processes to the mandatory investment in the development of internal competencies. The materials in the article can serve as a basis for developing innovative strategies that will help business organizations minimize technical and regulatory risks and secure leadership in today's digital market.
The relevance of the study is determined by the need for in-depth study and systematization of innovative decision-making methods that Web3 technologies offer to the modern business environment. In the context of global digital transformation, traditional approaches to management and finance are proving insufficient to ensure the competitiveness and sustainable development of organizations. The purpose of this article is to analyze Web3 tools, in particular blockchain, asset tokenization, decentralized finance (DeFi), and decentralized autonomous organizations (DAOs), as a basis for forming new, more transparent, secure, and effective methods and models for management decision-making. The paper applies a comprehensive methodology that includes a systematic analysis of the functional capabilities of Web3 technologies and a structural-logical approach to classifying their impact on corporate governance and financial management. The use of case studies has made it possible to illustrate the practical aspects of integrating these tools into the activities of large companies. The results confirm that Web3 is not only a technological trend but also a new paradigm that provides managers with qualitatively different tools. It has been established that blockchain creates a foundation for trust and data security; tokenization and DeFi radically increase the flexibility and liquidity of financial management; and DAOs transform corporate governance into a collective and inclusive process. In addition, the integration of AI agents into routine operations allows managers to effectively refocus their attention on strategic planning. The practical value of the article lies in providing organizations with clear recommendations for implementing Web3 technologies: from the need to start with pilot projects to test systems and processes to the mandatory investment in the development of internal competencies. The materials in the article can serve as a basis for developing innovative strategies that will help business organizations minimize technical and regulatory risks and secure leadership in today's digital market.
G will enable sophisticated composite services that can be realized, bought, and sold across multi-stakeholder marketplaces. With the advent of intent-based networking, requests for these composite services will be through high-level intents, together with requisite service-level agreements (SLAs), and with significant latitude on the specifics of how the composite services are realized. At the same time, the 6 G ecosystem will be very large, with new stakeholder entrants dynamically joining and leaving. Hence, buyers and sellers will be concerned about the trustworthiness of the sellers and the realized composite services as well as the trustworthiness of buyers and their behaviors. Current approaches to trust in networking are typically based on measures such as reputation, in a manner that will not scale to such large and dynamic ecosystems and does not encourage new entrants to join. We propose an architecture for intent-based 6G multi-stakeholder marketplaces inspired by decentralized finance (DeFi); namely, intent-based cryptocurrency swaps on blockchains/cross-chains. In such DeFi paradigms, trust is implicitly modeled via techno-economic risk management, rather than explicitly computed measures such as reputation. We propose how to leverage such DeFi paradigms to enable trustworthy intent-based multi-stakeholder 6G services marketplaces with SLAs, in a manner that encourages new entrants. Our approach is based on techno-economic risk vs. market-driven rewards as a proxy for trust, realized through intent-based blockchain/crosschain architectures with SLA assurance. Our work provides an enabler for establishing trusted multi-stakeholder interactions with UNEXT, an intelligent networking platform being created by Nokia Bell Labs.
Exploration equipment for extreme environments like the Antarctic region constraints in power consumption, size, and weight. Furthermore, unmanned mobile exploration in environments with distributed IoET (Internet of Extreme Things) nodes requires long-range, delay-tolerant wireless communication. For these extreme environments, delay-tolerant communication systems can consider distributed ledgers as a way to record gains and losses to ensure coalition and reliability among nodes. However, Proof-of-Work (PoW), the most widely studied method for securing distributed ledger reliability, is simple to operate but highly energy-consumption. Proof-of-Stake (PoS) offers an energy-efficient alternative. This paper assumes a partially Δ-synchronized distributed system model for security analysis in PoS and analyzes the impact of network delays on the system. This analysis is an interpretation to identify methods for securing stability against balance attacks in public systems from the perspective of a partially Δ-synchronized model. The proposed technique is a game-theoretic approach that uses honest nodes to form a coalition to control delay. This study investigates the possibility of expanding the upper bound of the security region according to the attacker's occupation rate in a balanced attack by controlling the time delay required for nodes in a partially Δ-synchronized communication network to transmit messages to each other.
Decentralized Autonomous Organizations (DAOs) are emerging as key governance structures in Web3 ecosystems, enabling community-driven decision-making without centralized control. Yet, current DAO implementation frameworks often lack modularity, role adaptability, and low-code accessibility, limiting broader adoption-especially among non-technical users and emerging organizations. Targeting these issues, this paper proposes a modular, template-driven DAO system for public blockchains such as Ethereum, integrating reusable governance logic units, token-based role configuration, and low-code interfaces to support flexible and secure deployment. The system allows role-scoped configuration of governance parameters via templates and supports scenario-specific deployment using predefined smart contracts, avoiding the need for direct code modification in the demonstrated use case. A quadratic votingbased governance scenario was used to demonstrate how the proposed framework can enable DAO setup and participation without requiring direct contract modification for that specific use case. Internal validation, conducted with simulated stakeholder roles, confirmed improvements in usability, configuration safety, and governance clarity, while also identifying practical gaps in role-specific UI guidance and simulation tooling. Although the current implementation is limited to a single voting model and local deployment, the findings highlight the potential of templatebased DAO systems to enable more inclusive, adaptable, and transparent decentralized governance.
In this interview with Ana Maria Caballero, we explore how poetry intersects with technology and Web3, highlighting its potential to redefine creative expression, challenge power dynamics, and enhance the cultural relevance of poetry in the digital age.
This context informs the conversations with artists and creative practitioners in this book.Often, their work with and around Decentralised Autonomous Organisations (DAOs) emerges from these very concerns.Does that mean that DAOs are capable of solving the sociopolitical issues of precarity, cuts, and censorship?No. 'Free blockchain money' does not exist.DAOs do not 'magically' make more funding appear, least of all structurally so.And DAOs do not allow artists and cultural practitioners to leave behind their national contexts of austerity and repression and exchange them for some virtual utopia.However, this does not mean that engaging with DAOs is pointless in the face of these circumstances and limitations.In this publication, I ask practitioners to share their experiences, focussing specifically on the definition of new forms of agency in cultural decision-making, explorations of shared ownership in arts and culture amid widespread logics of private property and extractivism, and the making of prefigurative claims on futures envisioned from the bottom up.None of these practices will be able to replace the structures of state funding or cancel oppressive concentrations of power any time soon, but they do open up space to manoeuvre and create tactical interventions, to find each other and build solidarity, and to regain a sense of futurity together.In other words, to reimagine, reclaim, and restructure shared socio-technical futures.The six people that I interviewed represent key voices in the countercultural and artistic DAO space.Penny Rafferty is a cofounder of Black Swan -a DAO that pursued horizontal and decentralised approaches to art-making -and she pushes DAO discourse into new directions with critical and imaginative work.Erik Bordeleau is a co-founder of The Sphere -a DAO that explores new ecologies of funding to develop a regenerative commons for the performing arts -and contributes boundarypushing philosophical and media theoretical perspectives to DAO thought.Ruth Catlow developed CultureStake -a voting system for decentralised cultural decision-making that uses quadratic voting on the blockchain -and has been a central Repression of Palestinian Culture and soidarity: Independence as Resistance,' Reset! 8
Lingfei Qian, Xueqing Peng, Yan Wang, Vincent Jim Zhang · 17 authors
Although Large Language Model (LLM)-based agents are increasingly used in financial trading, it remains unclear whether they can reason and adapt in live markets, as most studies test models instead of agents, cover limited periods and assets, and rely on unverified data. To address these gaps, we introduce Agent Market Arena (AMA), the first lifelong, real-time benchmark for evaluating LLM-based trading agents across multiple markets. AMA integrates verified trading data, expert-checked news, and diverse agent architectures within a unified trading framework, enabling fair and continuous comparison under real conditions. It implements four agents, including InvestorAgent as a single-agent baseline, TradeAgent and HedgeFundAgent with different risk styles, and DeepFundAgent with memory-based reasoning, and evaluates them across GPT-4o, GPT-4.1, Claude-3.5-haiku, Claude-sonnet-4, and Gemini-2.0-flash. Live experiments on both cryptocurrency and stock markets demonstrate that agent frameworks display markedly distinct behavioral patterns, spanning from aggressive risk-taking to conservative decision-making, whereas model backbones contribute less to outcome variation. AMA thus establishes a foundation for rigorous, reproducible, and continuously evolving evaluation of financial reasoning and trading intelligence in LLM-based agents.
Carlo Brunetta, Amit Chaudhary, Stefano Galatolo, Massimiliano Sala
Dynamically distributed inflation is a common mechanism used to guide a blockchain's staking rate towards a desired equilibrium between network security and token liquidity. However, the high sensitivity of the annual percentage yield to changes in the staking rate, coupled with the inherent feedback delays in staker responses, can induce undesirable oscillations around this equilibrium. This paper investigates this instability phenomenon. We analyze the dynamics of inflation-based reward systems and propose a novel distribution model designed to stabilize the staking rate. Our solution effectively dampens oscillations, stabilizing the yield within a target staking range.
The blockchain technology is sweeping the globe. Blockchain has emerged as a disruptive technology for the future generation of multiple industrial applications because to its decentralised, transparent, and secure nature. Cloud of Things, which is possible by the marriage of cloud computing with the Internet of Things, is one of them. Considering the need for security and efficiency as a problem, this paper proposes a safe and efficient smart home design that combines blockchain and cloud computing technologies to provide a comprehensive solution. The decentralised nature of blockchain technology allows it to provide processing services and create transaction copies of obtained sensible user data from smart homes. Blockchain, a distributed ledger technology that provides an immutable log of transactions recorded on a distributed network, has lately gained popularity as the underlying technology of cryptocurrencies and is revolutionising data storage and processing in computer network systems. Blockchain is seen as a possible option for future data-driven networks (DDNs) to provide safe data storage, sharing, and analytics, user privacy protection, strong, trustworthy network governance, and decentralised routing and resource management
The rapid growth of data-driven applications in healthcare, finance, IoT, and autonomous systems has created a pressing need for privacy-preserving and scalable machine learning methods. Traditional centralized learning, which aggregates data into a single repository, faces challenges related to data privacy, security, communication overhead, and regulatory compliance. Federated Learning (FL) offers a decentralized solution, enabling multiple clients to collaboratively train a global model without sharing raw data. Only model updates are exchanged, preserving privacy while leveraging distributed computational resources. This paper reviews FL architectures— including centralized, decentralized, horizontal, vertical, cross-device, and cross-silo—along with core components such as local clients, central servers, and communication protocols. Privacy- preserving techniques like differential privacy, secure aggregation, homomorphic encryption, and anonymization/pseudonymization are discussed to protect sensitive information. FL applications span healthcare, finance, IoT, smart devices, and autonomous systems, highlighting its transformative potential. Key challenges include data and system heterogeneity, efficient aggregation, personalization, robustness, and regulatory compliance. Future directions focus on enhanced privacy, communication efficiency, model personalization, and integration with edge and IoT environments. FL thus represents a promising paradigm for secure, collaborative, and distributed artificial intelligence.