The rapid expansion of institutional repositories (IRs) has heightened concerns about digital rights management (DRM), copyright protection, content authenticity, and long-term digital preservation, particularly in developing countries where institutional and technological capacities remain constrained. This study examines the feasibility of adopting blockchain technology as a DRM solution for Ghanaian institutional repositories and evaluates whether its application is transformative or largely aspirational. Guided by the TechnologyâOrganizationâEnvironment (TOE) framework and Diffusion of Innovations (DOI) theory, the study employed a sequential explanatory mixed-methods design that integrated quantitative survey data with qualitative interviews with ICT directors, repository managers, academic librarians, systems librarians, and faculty members from eight Ghanaian universities. The findings reveal low DRM maturity across institutional repositories. 40% of participating institutions lacked formal DRM mechanisms. Although awareness of blockchain technology was moderately high among respondents, substantial disparities existed across stakeholder groups, with ICT personnel demonstrating higher levels of understanding than faculty members and academic librarians. Institutional readiness for blockchain adoption remained generally poor, constrained by inadequate infrastructure, funding limitations, insufficient technical expertise, weak policy frameworks, and low organizational preparedness. Despite these limitations, stakeholders expressed strong support for blockchainâs potential to strengthen tamper-proof authorship verification, enhance content authenticity and integrity, improve transparency through immutable audit trails, and automate copyright management through smart contracts. The study further suggests that capacity building, phased implementation strategies, open-source platforms, interdisciplinary collaboration, and institutional policy alignment are critical pathways for integrating blockchain into institutional repositories. The study concludes that blockchain-enabled DRM in Ghanaian IRs is a promising, emerging innovation and that its successful implementation depends on sustained investment in digital infrastructure, institutional reforms, technical training, and supportive regulatory frameworks.
Sangeetha Nagamani, Annamalai Selvarajan, Raghini Mohan, John Peter Vincent Paul ¡ 6 authors
Secure and transparent water resource management is made possible by blockchain technology and its characteristics such as decentralisation, immutable records, and smart contracts. Tracking water consumption in real time is made possible by collaborating blockchain technology with Internet of Thingsâbased sensors, authenticating data integrity and transparency in fetching records. Blockchain ensures the tamper-proof sustainability of water quality data for pollution prevention. It helps to secure real-time monitoring data permanently, including pH, turbidity, and pollutant levels, which enables regulators to address quality issues. The automation of water rights and allocation transactions in the water trade sector can be processed by blockchain-based smart contracts, which reduce transaction costs and administrative burdens. Water billing, permit issuing, and right transfers, which are part of water trading practices, are guaranteed by digital agreements. As a result, a peer-to-peer water auction can operate with reduced latency and robust fraud prevention. Hence, blockchain applications in water resource management remarkably enhance security, transparency, and efficiency for tracking, controlling pollution, and providing fair water trading through smart contracts.
Jaume Martin Bosch, Marco Combetto, Luca Tangi, A. Paula Rodriguez MĂźller
Introduction Blockchain technology (BCT) has been widely discussed as a potentially valuable technology for advancing sustainable development in the public sector. Its core features, including transparency, immutability and decentralisation, may contribute to more accountable, efficient and inclusive public services. However, limited empirical evidence exists on how BCT-based public sector initiatives align with the United Nations Sustainable Development Goals (SDGs). Methods This study examines 306 public sector BCT-based use cases across the EU, compiled by the Public Sector Tech Watch observatory. We apply a GPT-4o-based AI text classification pipeline to assess the degree of alignment between project descriptions and the 17 SDGs. The pipeline combines refined SDG descriptors, structured prompting and documented model parameters. Its outputs are benchmarked against a human-coded subset to assess validity. Results The results show strong alignment with SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals), followed by more moderate alignment with SDG 8 (Decent Work and Economic Growth). By contrast, goals such as SDG 2, SDG 6 and SDG 14 remain weakly represented. These findings provide an empirical overview of how BCT applications in EU public administrations are framed in relation to the SDGs. Discussion By highlighting patterns of alignment between BCT adoption and the SDGs, this study offers evidence to inform policymakers, practitioners and future research on sustainability-oriented public sector innovation. It also demonstrates the value of AI-assisted classification for mapping large corpora of digital government initiatives, while recognising that the results capture stated or perceived alignment rather than verified sustainability impacts.
Purpose The study investigates the effect of investor fear on cryptocurrency crash risk, with emphasis on overall market sentiment and COVID-19-related fear. It also evaluates the relative performance of Google search-based measures compared to the economic policy uncertainty (EPU) index and the volatility indexes (VIX) as benchmark indicators of uncertainty. Design/methodology/approach This study employs a quantitative empirical approach to examine the impact of investor fear on cryptocurrency price crash risk. Investor sentiment is proxied using the FEARS index derived from Google search volumes and the coronavirus fear index. Crash risk is measured using negative conditional skewness of weekly returns and down-to-up volatility. The analysis is based on weekly data for the top 10 cryptocurrencies from August 2010 to October 2021. Regression models are used to examine the relationship between investor fear and crash risk and to compare the explanatory power of Google-based fear indicators with traditional uncertainty measures. Findings The results show that investor fear significantly increases the risk, while COVID-19-related fear further intensifies this effect, highlighting the vulnerability of crypto markets during periods of heightened uncertainty. Moreover, Google-based fear indicators outperform the EPU index and the VIX in explaining and predicting crash risk. Overall, the findings suggest that investor attention and sentiment are more powerful drivers of cryptocurrency crash risk than traditional volatility-based measures. Originality/value This study links investor fear, including COVID-19 sentiment, to cryptocurrency crash risk and finds that Google-based fear indicators outperform traditional measures like the EPU index and the VIX in predicting market downturns.
Currently, the most significant threat to the validity of academic credentials in the United States is the advanced forgery of transcripts along with diploma mills. This research study addresses the potential of blockchain technology as a decentralized means to protect academic credentials. By integrating recent academic research and technical frameworks, this study analyzes the shift from centralized databases to immutable, distributed ledgers. The integration of various perspectives, including advanced zero-knowledge proof architectures as well as legal frameworks for transnational data circulation, is a major innovation of this study. Using a systematic literature review and a case study approach, the research indicates that though blockchain's potential to enhance security and automate processes through smart contracts is indeed great, a number of legal, compliance, and technical barriers have to be removed for it to be a viable option. This study proposes that the combination of artificial intelligence (AI), along with blockchain technology, provides the most secure option for U.S. higher education institutions.
This chapter proposes an integrated BlockchainâIoTâAI framework for secure and intelligent quality traceability, particularly in agricultural and rice supply chains. It explains how IoT sensors can continuously collect physical and environmental information, AI models can analyze images and sensor data for quality assessment, and blockchain can securely record important quality events and processing information. The framework supports unique digital identities for rice batches, quality monitoring, defect detection, moisture estimation, quality scoring, and QR-based access to traceability information. The chapter examines applications in rice quality certification, smart rice mills, food safety, warehouses, export-quality monitoring, consumer verification, and government procurement. Challenges related to data quality, sensor reliability, interoperability, stakeholder participation, scalability, and regulatory coordination are also addressed.
The programmable economy lacks a universal computational layer capable of interpreting, translating, verifying, and simulating the mathematical and cryptographic operations that underpin digital assets. Existing tools are fragmented: wallet software provides only rudimentary transaction signing, portfolio trackers offer aggregated views without evidence, and specialized calculators address isolated problems. No general-purpose, cryptographically verifiable, language-native computational environment exists for digital value. KHOTOR is designed to fill this gap. It is a universal, deterministic runtime that interprets the anti-entropic linguistic protocol Kryptophon, transforms plain-language queries into executable computational expressions, and performs multi-domain financial mathematics across asset conversion, transaction analysis, decentralized finance, tokenomics simulation, cryptographic proof generation, and risk assessment. Every output carries an epistemic classification â verified, observed, inferred, simulated, or uncertain â and can be exported as a Gamma-Proof: a cryptographically signed, independently verifiable artifact. This paper presents the complete KHOTOR architecture: a ten-layer computational engine, a formal abstract machine for Kryptophon evaluation, a tiered adoption model that makes the programmable economy accessible to non-technical users while creating a new domain of expertise for professionals, and a product family spanning a public cloud API, a web platform, a handheld consumer device, and integration with dedicated hardware instruments. All components are designed around a single governing principle: every calculation shows its work, every output carries a truth label, and no inference is ever presented as fact.
Beacon Kit: Ecosystem epoch heartbeat @ the world game (s). Block-time arbitrage tokenized commodity index, adaptive procedural template @ system of federated DeFi cryptocurrency quantum - AI systems consensus
The rapid growth of cryptocurrencies and increasing instability in traditional financial systems have significantly transformed global investment behaviour in recent years. In developing countries experiencing economic crises and currency depreciation, investors increasingly seek alternative financial assets that can preserve value and generate higher returns. Sri Lanka has recently experienced severe economic instability characterised by inflation, foreign-exchange shortages, sovereign debt problems, and rapid depreciation of the Sri Lankan rupee. Under these conditions, interest in cryptocurrency investment has increased, particularly among younger and technologically aware investors. Therefore, this study examines whether fiat currency devaluation shifts investment from the stock market to the cryptocurrency market among university students in Sri Lanka. The study adopts a quantitative research approach and uses primary data collected through a structured questionnaire from 150 final-year undergraduate students at the University of Sri Jayewardenepura. Stratified random sampling was used to select respondents from the Faculty of Humanities and Social Sciences, the Faculty of Management Studies and Commerce, and the Faculty of Applied Sciences. Descriptive statistics, chi-square analysis, and binary logistic regression were employed to analyse the relationship between rupee depreciation and cryptocurrency investment behaviour. The findings reveal that depreciation of the Sri Lankan rupee significantly influences investment decisions among university students. Most respondents perceived cryptocurrency investment as more profitable than stock-market investment during periods of economic uncertainty. The chi-square analysis identified significant relationships between cryptocurrency investment behaviour and age, income, stock-market investment, and perceptions of rupee depreciation. Furthermore, the binary logistic regression results confirmed that rupee depreciation positively and significantly affects cryptocurrency investment, whereas stock-market investment had a negative relationship with cryptocurrency investment behaviour. The study concludes that economic instability, declining confidence in fiat currency, and increasing awareness of digital financial systems encourage university students in Sri Lanka to shift their investment preferences from the traditional stock market to cryptocurrency.
The article examines the concept of legal settlement finality as applied to two fundamentally different payment instruments â decentralized cryptocurrencies and central bank digital currencies (CBDCs). The author analyzes the absence of a statutory definition of settlement finality in Russian financial law, compares the approaches of Russia, China, India and the UAE, and studies judicial practice and doctrine. Based on a comparative legal analysis, an original definition of the legal finality of digital settlement is proposed, and liability regimes for payment process participants prior to transaction completion are differentiated in relation to cryptocurrency P2P transactions and CBDC operations.
This systematic review synthesises empirical research on individual-level cryptocurrency adoption, distinguishing adoption intention, actual adoption and use, and continuance intention and use. We searched Scopus and Web of Science for English-language empirical studies published between 2019 and 2025 and synthesised findings using a structured narrative approach. Eighty-five studies were included, with reported sample sizes summing to 56,054 participants. No formal study-level risk-of-bias assessment was conducted. The literature was dominated by cross-sectional quantitative studies and technology-adoption frameworks, particularly UTAUT, TAM, TPB, and DOI. Evidence was strongly concentrated on adoption intention (n = 75), whereas actual adoption and use (n = 16) and continuance intention and use (n = 8) were examined much less frequently. Across studies, adoption was associated with psychological, technological, social, economic, knowledge-related, institutional, and individual factors, with no single determinant consistently dominating across outcomes. The synthesis further distinguished direct predictors, mediating mechanisms, moderators, drivers, and barriers. The evidence base is limited by its reliance on self-reported, cross-sectional designs and uneven coverage of realised and continued engagement. Future research should more clearly specify adoption outcomes and use longitudinal, behavioural, and post-adoption designs.
Ovaj rad analizira transformativnu ulogu kriptovaluta u infrastrukturi savremenog organizovanog kriminala, argumentujuÄi da blockchain tehnologija nije samo novi alat za stare kriminalne prakse, veÄ da konstituiĹĄe kvalitativno novu kriminalnu ekonomsku arhitekturu koja mijenja temeljne odnose izmeÄu kriminalnih aktera, Ĺžrtava i institucija. Kroz sistematsku analizu tehniÄkih mehanizama od Bitcoin pseudoanonimnosti i privacy coins, do DeFi protokola i cross-chain hopping tehnika, rad mapira evoluciju kriptovalutnog pranja novca od primitivnih jednokratnih transakcija prema sofisticiranim, viĹĄeslojnim operacijama koje kombinuju tehnoloĹĄku sofisticiranost s institucionalnim ranjivostima globalnog regulatornog mozaika. Posebna analitiÄka paĹžnja posveÄena je sluÄajevima koji demonstriraju konvergenciju kriptokriminala s drĹžavnom strategijom, tj. ransomware koji funkcioniĹĄu kao paraziti na globalnoj digitalnoj ekonomiji, DeFi eksploatacijama koje u minutama dreniraju stotine miliona dolara, i sjevernokorejskim drĹžavno-sponzorisanim hakerskim operacijama koje finansiraju zabranjene oruĹžane programe pod sankcijama. Rad evaluira regulatorne odgovore poput MiCA, FATF Travel Rule i OFAC sankcije, te identifikuje sistemske praznine koje ostavljaju DeFi i peer-to-peer sistem izvan efektivne regulatorne kontrole. ZakljuÄak poziva na fundamentalnu promjenu paradigme regulatornog pristupa, i to od retrospektivne forenzike prema prospektivnoj arhitekturi transparentnosti koja mora biti ugraÄena u same protokole.
While much has been written about the volatility of digital assets, academic scholarship has largely overlooked how blockchain technologies have been adopted and reimagined by LGBTQ+ communities. This article addresses that gap through a digital ethnography of queer NFT communities active during the crypto craze of 2022, combining online participant observation with semi-structured interviews. Drawing on JosĂŠ Esteban MuĂąozâs concept of queer futurity, it examines how queer users imagined blockchain as a speculative platform for alternative economic and social possibilityâdespite the financial risks embedded in the technologyâs libertarian and capitalist structures. The article interrogates the utopian rhetoric of inclusion, decentralisation, and wealth redistribution that was deployed within these communities to justify their interest in and holdings of non-fungible tokens (NFTs) and cryptocurrency. Queer leaders leveraged the blockchain to foster inclusive digital communities and promote wealth circulation amongst LGBTQ+ individuals, while community members embraced the technology as a risky opportunity for queer economic mobility. The article positions blockchain as a contested site where competing futurities collideâoffering the illusion of liberation and the reproduction of existing inequalities. It argues that while queer users sought to make the blockchain âqueer from the start,â their efforts were ultimately constrained by the capitalist logics that underpin the technology.
Muhammad Farooq Shaikh, S. Hamza Hassan, Jawwad Shamsi, Alessia Maccaro ¡ 5 authors
Background and objective The integration of blockchain and digital twin (DT) technologies is increasingly recognised as a promising approach for improving healthcare data integrity, interoperability, privacy, and clinical decision support. While digital twins enable dynamic patient modelling and predictive healthcare applications, blockchain provides secure data governance through decentralised trust, auditability, and access control. However, existing research remains fragmented, with limited synthesis of the architectural integration, regulatory readiness, ethical governance, and interoperability of blockchain-enabled healthcare digital twin systems. This systematic scoping review addresses these gaps by providing a comprehensive architectural and compliance-oriented analysis of the current evidence. Methods A systematic scoping review was conducted following PRISMA 2020 guidelines using Scopus, PubMed, and Web of Science. From 148 identified records, 55 eligible studies published between 2020 and 2025 were included after duplicate removal and eligibility screening. Data were extracted on digital twin functionality, blockchain architecture, healthcare application domains, consensus mechanisms, privacy-preserving strategies, and regulatory and ethical alignment. Structured Python-based visual mapping and comparative analyses were performed to identify architectural, governance, and compliance patterns across the literature. Results The findings demonstrate that blockchain is predominantly employed to provide access control, audit logging, data integrity, consent management, and secure data provenance within healthcare digital twin ecosystems. Patient-level and EHR-centred digital twins represented the most mature application areas, whereas cross-domain and infrastructure-level frameworks dominated early architectural exploration. The review identifies recurring compliance-oriented architectural patterns while revealing substantial gaps in clinically validated deployments, interoperability with established healthcare standards, decentralised governance models, and formal implementation of GDPR- and HIPAA-compliant engineering practices. Comparative heatmap analyses further highlight the uneven maturity of ethical governance and regulatory integration across blockchain functionalities. Conclusion This review provides the first comprehensive compliance-oriented architectural synthesis of blockchain-enabled healthcare digital twin systems by integrating technical architecture, regulatory readiness, ethical governance, and privacy-preserving design patterns within a unified analytical framework. The proposed architectural mapping identifies critical research gaps in interoperability, governance engineering, consensus optimisation, and real-world clinical validation, providing a foundation for the development of trustworthy, GDPR/HIPAA-aligned, FHIR-compatible, and clinically interoperable healthcare digital twin ecosystems.
K. Satheshkumar, S. Ramalingam, A. Suresh Babu, S. Murugesan
ABSTRACT Vehicular ad hoc networks (VANETs) are essential components of intelligent transportation systems that facilitate realâtime communication between vehicles (V2V) and between vehicles and infrastructure (V2I). Despite their importance, VANETs face challenges, such as high node mobility, energy limitations, security risks, and everâchanging network topologies. Existing clustering and routing algorithms often struggle to manage the instability caused by mobility, energy disparities, and secure congestionâfree communication simultaneously. To address these challenges, this work introduced an integrated crossâlayer framework featuring three innovative algorithms: mobilityâaware black hole clustering (MâBHC), energyâaware piranha optimization algorithm (EPOA), and crossâlayer multiâattribute blockchain routing with congestion control (CLâMABRC). The MâBHC algorithm enhances the stability of clusters and counters blackâhole attacks by forming clusters dynamically based on realâtime vehicle mobility patterns. EPOA optimizes the selection of cluster heads (CHs) by reducing energy consumption through a bioâinspired resource allocation strategy modeled on piranha predation behavior. CLâMABRC addresses network congestion and security using blockchainâbased verification and crossâlayer routing decisions informed by multiâattribute metrics. Extensive simulations were conducted with a setting of 100 veh/km 2 . The proposed framework showed significant performance improvements over benchmark protocols, such as optimal securityâaware clusterâbased hybrid geographical and opportunistic routing (OSCâGOR), enhanced locationâaided ant colony routing (ELAACR), trustâbased multiâobjective honey badger algorithm (TMOHBA), and robust cryptographic scheme for reliable data communication (RCSRC). It achieved a throughput of 99.89 Kbps, endâtoâend delay of 3.9 ms, collision rate of 21.8%, energy consumption of 41.98%, and jitter of 0.05 ms. Together, the MâBHC, EPOA, and CLâMABRC algorithms create a robust, energyâefficient, and secure communication framework for VANETs, enhancing scalability, reliability, and realâtime performance in transportation systems.
The use of a wireless sensor network is increasingly supporting e-governance functions such as municipal utility monitoring, environmental monitoring, grievance-based field reporting, and smart public service delivery. Most wireless sensor network architectures rely on a gateway or database. However, this introduces vulnerabilities to data integrity, node accountability, and auditability. This study examines transparency through a blockchain-enabled WSN architecture for e-governance. The study applies a reproducible Python-based Monte Carlo simulation with a fixed random seed, five node densities, three architectural scenarios, and 450 observations. The scenarios that are compared in this work are a normal WSN, a centralized secure WSN, and a permissioned blockchain-enabled WSN with smart-contract-based identity registration, hash-linked data records, trust scoring, and tamper verification. Descriptive statistics, one-way ANOVA, Welch t-tests, Pearson correlation, and multiple linear regression analysis. The blockchain-assisted WSN, as evidenced by the simulation findings of our project, produced the highest mean data integrity score, tampering detection rate, trust score, malicious node detection rate, and packet delivery ratio. The architecture also improved the composite service efficiency index relative to the conventional baseline, even though it introduced higher latency, transaction confirmation time, and energy consumption. The research indicates that the permissioned blockchain can enhance public-sector WSN transparency with edge aggregation and lightweight cryptographic operations along with carefully tuned endorsement rules. The methods presented in this study allow for scrutiny of secure WSN designs tailored for e-governance.
The development of blockchain technology has given rise to the Decentralized Autonomous Organization (DAO), a new business organizational model that operates through smart contracts in a decentralized manner, without a conventional management structure. The existence of DAOs has not been accommodated in the Indonesian corporate legal system, creating a legal vacuum regarding legal subject status, accountability, legal standing, taxation, and dispute resolution. This study aims to analyze the characteristics of DAOs from a corporate law perspective and the urgency of convergence between corporate law and blockchain technology in its regulation in Indonesia. The study employs a normative juridical method with statutory, conceptual, and comparative approaches. The results indicate the need for regulations that recognize and regulate DAOs as digital business entities to achieve legal certainty, legal protection, and a sustainable digital investment climate.
B Santhosh Kumar, P. Penchala Prasad, M. Raghavendra Reddy
Abstract Alzheimerâs disease is a neurodegenerative disorder that affects millions of individuals worldwide, making early diagnosis through Magnetic Resonance Imaging a significant clinical necessity. Existing medical image analysis techniques often suffer from limitations associated with inadequate preprocessing, reduced sensitivity to subtle abnormalities in the hippocampus and cortex, poor generalization across heterogeneous MRI acquisition systems, and insufficient mechanisms for secure medical data management. To address these challenges, this research proposes an integrated framework combining the Internet of Medical Things (IoMT), Artificial Intelligence, and blockchain technology for secure and efficient Alzheimerâs disease monitoring. The proposed framework employs Feature Pooling VGG16 (FPVGG16) for discriminative feature extraction, while feature selection is optimized using the Wave Search Binary Waterwheel Plant Optimization algorithm. Subsequently, a feature-selective Coordinated Xception-based Convolutional Spatial Network (CXCSN) is utilized for accurate disease classification. Blockchain technology is incorporated to provide secure, tamper-resistant, and privacy-preserving management of patient information and MRI records. Experimental evaluations conducted on the Alzheimerâs Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets validate the effectiveness of the proposed framework, achieving accuracies of 99.31% and 99.21%, precisions of 99.28% and 99.25%, and recalls of 99.18% and 99.14 %, respectively. The results indicate that the proposed framework provides an effective solution for secure, reliable, and highly accurate Alzheimerâs disease diagnosis and monitoring.
Purpose This study aims to examine the feasibility of blockchain adoption during investment banksâ Know Your Customer (KYC) validation processes. It studies the role played by government in regulating the blockchain-based KYC process. Design/methodology/approach A framework based on the extended technology acceptance model (TAM) was conceptualised to formulate six hypotheses. Based on this, a structured questionnaire was developed and administered among the employees of investment banks through a multi-stage sampling technique. The final sample, comprising 605 responses, was analysed using a covariance-based structural equation modelling (Mediation Analysis) on JASP V.19. Findings The present research explains that the government, as a mediating variable, has a 45.7% direct impact and 54.3% indirect effect on investment banks in the adoption and actual usage of blockchain technology for KYC validation. The perceived ease of use, perceived usefulness and attitude to use technology are key factors that influence its adoption for front-office operations. Perceived ease of use is a dominant indicator within the model. Research limitations/implications This study contributes theoretically by extending the existing TAM model with its practical application in the KYC process during validation of customer documentation in the banking industry, adding practical relevance to the regulatory framework. Originality/value The research derives its originality from the mediating role of government regulation in implementing KYC through blockchain. It proposes a blueprint of a working model that can be internalised to optimise the processes, extending the existing theory and its application with practical relevance.
The rapid advancement of artificial intelligence (AI) and blockchain technologies has fundamentally transformed the normative foundations, authority structures, and legitimacy of contemporary legal systems. While these technologies are commonly portrayed as instruments for enhancing efficiency and legal certainty, their increasing integration into legal decision-making raises profound philosophical questions concerning the nature of law, justice, and human agency. This article critically examines how AI and blockchain reshape legal normativity through the lens of legal philosophy. Employing a normative juridical methodology supported by conceptual and philosophical approaches, the study analyzes the implications of algorithmic decision-making and decentralized technological infrastructures for the evolution of legal authority. The findings demonstrate a paradigmatic shift from human-centered normative reasoning toward computational rationality grounded in algorithmic logic. AI replaces interpretative legal reasoning with probabilistic prediction, privileging statistical inference over moral deliberation. Simultaneously, blockchain institutionalizes automated legal enforcement through smart contracts, thereby minimizing interpretative discretion and limiting the contextual flexibility traditionally required to achieve substantive justice. These developments contribute to the emergence of what this article conceptualizes as post-human legal normativity, in which legal authority increasingly resides within technological systems rather than human reasoning and institutional judgment. The study argues that this transformation generates significant challenges to justice, transparency, accountability, and democratic legitimacy. The growing reliance on algorithmic authority risks reducing law to a technical mechanism detached from its ethical and normative foundations. Consequently, the philosophy of law must be reconstructed to reaffirm the centrality of human agency in legal governance and to ensure that emerging technologies function as instruments serving legal values rather than autonomous sources of legal authority.
Transformer-based detectors for Solidity smart contracts almost universally encode a contract within a single 512-token window, then attribute performance differences to the choice of pre-trained encoder. We show this attribution is misplaced. On DIVE-25 (22,330 deployed contracts, eight DASP categories, multi-label at 2.46 labels per contract) the median contract occupies 2,994 sub-word tokens and only 5.48% fit a single window. We segment each contract at top-level declaration boundaries, pack the segments greedily into at most 24 chunks of 510 tokens for an effective context of 12,240 tokens covering 98.25% of the corpus, and recombine the chunk representations with a bidirectional LSTM under additive attention. Holding preprocessing, chunk budget, pooling, aggregator, loss, schedule, seeds and split identical, the extended context is worth +0.1038 micro-F1 and +0.1722 macro-F1 over single-window truncation, roughly four times the benefit of the best available encoder. The loss under truncation is markedly uneven: Front Running falls by 0.294 and Time manipulation by 0.262, while Access Control, whose indicators sit near the top of a file, loses 0.010. Fifty-one structural measurements and a five-relation contract graph enter the classifier through per-class gates initialised at Ď(â4) â 0.018, so any contribution must be learned; both open, and the resulting gain is 1.9 times larger on categories below 900 test instances. Under family-aware leakage-controlled partitioning the complete system reaches 0.8435 micro-F1 and0.7775 macro-F1, with the fusion gain significant under a paired bootstrap (macro-F1 +0.0173, 95% CI [+0.0113, +0.0236]). We report every result additionally on a twin-free test subset from which the 39.58% of test contracts sharing a structural twin with training are removed. Finally, evaluated against human-verified exploitability judgements the detector scores 0.455 mean AUC, below a baseline built from contract size and compiler version alone (0.735), bounding what any detector trained on analyser consensus can be claimed to do.
This chapter examines the transformative role of blockchain technology, artificial intelligence (AI), and smart contracts in reshaping trade finance and customs modernisation across Africa, with particular emphasis on the African Continental Free Trade Area (AfCFTA) framework. It explores how distributed ledger technologies are enhancing transparency and reducing transaction costs in cross-border trade, while AI-driven credit scoring and risk assessment models are expanding financial inclusion for underserved enterprises. The chapter analyses the deployment of smart contracts for automating trade documentation and compliance processes, and evaluates the impact of these technologies on fraud reduction and supply chain traceability. Drawing on real-world cases from the Pan-African Payment and Settlement System (PAPSS), Flutterwave, Kifiya, and the AfCFTA Digital Trade Protocol, the chapter highlights both opportunities and governance challenges, including data privacy, regulatory fragmentation, scalability constraints, and the digital infrastructure divide that characterises much of the continent. Policy recommendations for harmonised regulatory frameworks and capacity building are advanced.
Law, logistics, and international trade
Legal, Health, Environmental and COVID-19 Challenges