ABSTRACT Green finance—including environmental, social, and governance investing and sustainable finance regulations—is widespread, but can it substitute for carbon pricing in fighting climate change? In a unified model, I show that (i) when carbon prices reflect the social cost of carbon, green finance should not be used; (ii) when carbon prices are too low, green finance can implement the social optimum if each firm's cost of capital can be set to its sustainable discount rate , which increases with the ratio of carbon emissions to firm value. I provide calibrations, analyze stranded assets, and present implementations through subsidies or preferential financing for green firms.
This study examines the pricing dynamics of Non-Fungible Tokens (NFTs) in the secondary market using advanced machine-learning techniques. We construct a large dataset of Ethereum-based NFT transactions initially comprising over 500,000 raw blockchain observations spanning multiple NFT segments, including art, collectibles, gaming, metaverse, and utility assets, over the period from November 2018 to March 2023. Following data preprocessing, synchronization across data sources, and the construction of history-dependent features, the analysis focuses on a final analytical sample of approximately 70,000 transactions. To address the challenges of non-fungibility, thin trading, and high price dispersion, we develop an interpretable predictive framework that integrates domain-informed manual feature engineering, automated Deep Feature Synthesis, and dimensionality reduction via Principal Component Analysis. Three non-linear models—Random Forest, XGBoost, and a Multilayer Perceptron—are trained and evaluated using both random and time-aware validation strategies. The results indicate that XGBoost consistently achieves the highest predictive accuracy, both overall and across individual NFT segments, while historical transaction prices emerge as the dominant predictor of future prices. Segment-level analysis reveals substantial heterogeneity in predictability, with art and collectible NFTs exhibiting more stable pricing patterns than gaming and metaverse assets. Overall, the findings highlight strong path dependence and reputation-driven valuation in NFT markets and demonstrate that carefully designed machine-learning models can deliver high predictive performance without sacrificing economic interpretability.
This paper addresses the technical and regulatory challenges of building secure data pipelines to support federated learning (FL), where models train collaboratively across multiple organizations without sharing raw data. The paper explores privacy-preserving data engineering techniques such as differential privacy, homomorphic encryption, and secure aggregation within ETL frameworks. It outlines an architecture for orchestrating decentralized dataflows that comply with GDPR, HIPAA, and other regulatory standards while enabling cross-institutional AI innovation. By integrating secure connectors, encrypted model updates, and audit logging, the proposed pipeline design ensures both data protection and analytic utility, providing a blueprint for responsible AI deployment in healthcare, finance, and government sectors.
The COVID-19 pandemic exposed critical gaps in regional health security mechanisms, prompting ASEAN to establish the ASEAN Centre for Public Health Emergencies and Emerging Diseases (ACPHEED), with functions distributed across Indonesia, Thailand, and Vietnam. This policy analysis examines strategic development approaches for ACPHEED through comprehensive benchmarking of the European Centre for Disease Prevention and Control (ECDC), Africa Centres for Disease Control and Prevention (Africa CDC), and Gulf CDC, supported by consultations in Indonesia (2024) and Sweden (2025) involving ASEAN member states and international partners. A comparative analysis reveals distinct organizational models: the ECDC operates within European Union (EU) institutional frameworks emphasizing functional specialization; the Africa CDC employs decentralized Regional Coordination Centers; and the Gulf CDC implements hybrid governance via Permanent Communication Networks. Each model offers valuable lessons for ACPHEED's development, particularly concerning governance structures that balance regional coordination with national sovereignty. ACPHEED faces unique challenges due to ASEAN's consensus-based, nonlegislative institutional nature and its tri-country operational structure. Critical success factors include phased surveillance emphasizing a defined scope and capacity building; inclusive governance mechanisms ensuring equitable member-state ownership; and operational frameworks applying subsidiarity principles to complement existing ASEAN mechanisms. Sustainable financing remains paramount given ASEAN's limited budgetary authority. Japan's strategic partnership should capitalize on its technical expertise in laboratory systems, digital surveillance, and disaster preparedness through comprehensive institutional support. ACPHEED's success depends on sustained political commitment, realistic financial arrangements, and effective integration into global health security architectures. This analysis provides a strategic roadmap for ACPHEED's preparatory phase so that it can serve as a regional health security leader while addressing ASEAN-specific institutional constraints.
Research background and purpose Digital technologies offer tangible economic benefits but are also exposed to the risk of misuse. Crowdfunding is a special support form for business, cultural or social enterprises. Due to anonymity, fragmentation of capital and wide coverage, crowdfunding transactions are particularly vulnerable to the risk of criminal activities related to the concealment of the source of income or illegal changes of the financing objective. This article addresses the risks of money laundering and terrorism financing, particularly on the specifics of crowdfunding. Research has proposed a synthetic risk indicator for AML/CFT, which may measure the level of risk and vulnerability of crowdfunding to money laundering and terrorism financing. Design/methodology/approach The discussion in the article is presented against the background of a comprehensive and integrated review of literature, covering national and foreign sources. The theoretical part of the article utilizes: method of analysis and criticism of literature, analysis and synthesis, and method of analysis and logical construction. In the empirical part, to assess the level of risk and vulnerability of crowdfunding to AML/CFT risk compared to other areas, a research procedure based on the TOPSIS linear ordering method was used. The analysis covers the years 2019 and 2023. Findings The results of the studies show that crowdfunding is one of the most vulnerable areas at risk of money laundering and terrorism financing. The high position in the ranking in 2019 and 2023 resulted mainly from the dynamic development of the crowdfunding market in Poland, its increasing availability, a high degree of decentralization, the occurrence of cross-border transactions and the increasing diversity of platforms in their business model. Maintaining the benefits of crowdfunding requires the simultaneous implementation of effective remedies, increased campaign transparency and close cooperation with supervisory authorities and institutions combating financial crime. Value added and limitations The study makes an important contribution to the literature on the subject, providing information on the criminality of crowdfunding. The results of the study can be used by supervisory and regulatory authorities as a tool for shaping security in innovative segments of the financial system. The main limitation was the relatively small number of variables selected for the synthetic measure.
Amid the institutionalization wave of Decentralized Finance (DeFi), U.S. institutional Liquidity Providers (LPs) have emerged as the core incremental capital for leading Decentralized Exchanges (DEXs). However, the adaptation gap between Uniswap V4's concentrated liquidity mechanism and institutional risk preferences, as well as regulatory compliance requirements, has hindered their market entry. This study focuses on the integration of "technical characteristics - institutional constraints - precise pricing" and constructs a machine learning pricing model optimized across three dimensions: return, risk, and compliance. By integrating Uniswap V4 on-chain data, institutional risk preference data, and market data, a Stacking ensemble architecture combining LightGBM and CNN-LSTM is designed, incorporating 22 core features to achieve precise pricing. Empirical results show that the model's Mean Absolute Error (MAE) on the test set was reduced by 37% compared to the benchmark, and the Root Mean Square Error (RMSE) is reduced by 42%. The Sharpe ratio reaches 1.87 (an increase of 62% compared to the benchmark), with a volatility of 15.3% and a compliance adaptability score of 91. In the case study, a $150 million liquidity supply achieved a 19.7% annualized return and an 8.3% maximum drawdown, successfully passing SEC compliance review. This research fills the gap in institution-oriented pricing models for V4, improves the institutional extension of Automated Market Maker (AMM) pricing theory, and provides a risk-controllable and compliance-adaptable pricing tool for U.S. institutions participating in DeFi, promoting the transformation of the DeFi ecosystem towards standardization and institutionalization. By aligning the V4 Hook mechanism with U.S. regulatory frameworks, this research provides a scalable technical standard for institutional DeFi adoption, reinforcing the competitive advantage of the U.S. Web3 financial ecosystem.
Термин сферы децентрализованных финансов анализируется в рамках когнитивной парадигмы. Целью исследования является определение роли когнитивно-матричного анализа в контексте изучения терминов рассматриваемой области знания. Объектом исследования выступает термин “decentralized finance”. Предметом является применение когнитивно-матричного анализа как метода изучения терминолексики сферы децентрализованных финансов. Научная новизна исследования заключается в том, что впервые в отечественном терминоведении проводится изучение англоязычных терминов указанной сферы с когнитивной позиции. В частности, приводится пример использования когнитивно-матричного анализа для определения концептуальной структуры термина изучаемой области знания. В статье рассматривается несколько подходов к определению понятия «термин»: субстанциональный, функциональный и когнитивный. Проводится когнитивно-матричный анализ на материале термина “decentralized finance” и его определений, закрепленных в глоссариях децентрализованных платформ, приложений и новостных англоязычных интернет-ресурсов, таких как Binance Academy, Consensys, Ethereum Website, Ethereum Glossary и Tastycrypto. В результате анализа определено, что наибольшую компонентную представленность в структуре концепта DECENTRALIZED FINANCE демонстрируют «техническая и технологическая» и «социальная» области, в то время как «финансовая» и «правовая» репрезентированы менее широко, что обусловлено смещением акцента в определениях термина с базовых характеристик на инновационные и дифференцирующие. Когнитивно-матричный анализ позволяет выявлять периферийные области и концептуальные компоненты когнитивной структуры терминов сферы децентрализованных финансов, подчеркивая их междисциплинарный характер. The term “decentralized finance” is analyzed within the framework of the cognitive paradigm. The article examinesthe application of cognitive-matrix analysis as a method for studying the terminological vocabulary of the specified domain. The object of the research is the term “decentralized finance”, while the subject is the application of cognitive matrix analysis as a method for studying the terminological vocabulary of decentralized finance. The novelty of the research lies in the fact that, for the first time in Russian terminology studies, English-language terms of the specified field are examined from a cognitive perspective. An example is provided of how cognitive matrix analysis can be used to identify the conceptual structure of decentralized finance terms. The article considers several approaches to defining the concept of the term: the substantial, functional, and cognitive. A cognitive matrix analysis is conducted on the material of the term “decentralized finance”, as represented in the glossaries of decentralized platforms, applications, and English-language news resources such as Binance Academy, Consensys, Ethereum Website, Ethereum Glossary, and Tastycrypto. The analysis reveals that the “technical and technological” and “social” peripheral domains are most prominently represented in the structure of the concept DECENTRALIZED FINANCE, whereas the “financial” and “legal” domains are less explicitly present. This is due to the shift in focus from basic characteristics of the concept to innovative and differentiating features in the term’s definitions. Cognitive matrix analysis makes it possible to identify peripheral domains and conceptual components of the cognitive structure of DeFi terminological vocabulary, highlighting its interdisciplinary nature.
This manuscript presents a conceptual and ideological-social framework for a cryptocurrency token denoted as $Rupert (or $Rupert), positioned as an innovative fusion of decentralized finance (DeFi) mechanisms and political advocacy aligned with the policy agenda of British politician Rupert Lowe MP and his associated movement, Restore Britain.
Abstract This study examines the dynamic connectedness that the innovative natural disasters index displays with major cryptocurrencies, decentralized finance assets (DeFi) and non-fungible tokens (NFTs) during the Russia-Ukraine conflict under intense inflationary pressures. Data spanning from 14 December 2021 to 31 January 2025 and three specifications of the Quantile Vector Autoregressive (Q-VAR) methodology at lower, middle and upper quantiles are adopted. Results indicate that natural disaster uncertainty has a larger footprint on DeFi assets in bear markets but is more influential on the NFTs in bull markets. So it acts as a hedge against medium risk digital currencies when pessimism prevails and motivates for investing in riskier assets in elevated investor optimism. The Ripple, Synthetic and Gala assets are the most tightly linked with natural disasters’ sentiment. Higher levels of geopolitical and monetary uncertainties fuel the switch of investors’ decision-making criteria. This study provides valuable insights for the potential of modern cryptocurrencies to survive during crises when conventional currencies devaluate and offers a compass for monetary authorities and investors.
Open access
Market Dynamics and Volatility
Blockchain Technology Applications and Security
Environmental and Biological Research in Conflict Zones
this study rigorously scrutinizes the revolutionary impact of artificial intelligence (AI) on banking organizations within India. It definitively analyses the transformative effects of AI on the Indian financial industry by reviewing pertinent literature, compelling case studies, and empirical data. The paper first establishes the major ways. AI unequivocally alters the financial sector. It then details how Indian Banking institutions effectively deploy AI across critical areas such as customer service, algorithmic trading, risk management, fraud detection, credit scoring, and regulatory compliance. The integration of AI into India’s financial ecosystem is highlighted through examples from major banks, fintech companies, and regulatory agencies, showcasing the methods used and the outcomes achieved. Furthermore, this study explores the impacts and challenges associated with AI implementation in the Indian banking industry [14]. It delves into the cultural factors, current regulations, data availability, talent acquisition, and regulatory frameworks that shape the application of AI in Indian banks. The combination of Decentralized finance and AI offers a revolutionary partnership that might completely change the sector, increase its flexibility, and lay the foundation for long-term viability. In recent years, AI and Decentralized finance have become prominent advances in technology that have attracted a lot of interest and acceptance. In conclusion, this study comprehensively analyses AI's effects on India’s banking sector. This research paper is based on secondary data with the help of various journal and websites. Researcher paper benefits to many Policymakers, practitioners, and scholars will find invaluable insights contributing to the growing literature on technology-driven transformations. The recommendations provided will enable stakeholders to effectively harness AI’s capabilities while proactively addressing inherent risks and challenges, thereby enhancing the resilience, efficiency, and customer-centric focus of financial institutions in India and ensuring their competitiveness in an increasingly digital landscape. This research highlights the need to adopt a-worthy strategies for the prevention of active fraud, eventually contributes to the integrity of financial systems.
Open access
Innovations and Analysis in Business and Education
Aijie Shu, Wenbin Wu, Gbenga Ibikunle, Fengxiang He
Credit exposure in Decentralized Finance (DeFi) is often implicit and token-mediated, creating a dense web of inter-protocol dependencies. Thus, a shock to one token may result in significant and uncontrolled contagion effects. As the DeFi ecosystem becomes increasingly linked with traditional financial infrastructure through instruments, such as stablecoins, the risk posed by this dynamic demands more powerful quantification tools. We introduce DeXposure-FM, the first time-series, graph foundation model for measuring and forecasting inter-protocol credit exposure on DeFi networks, to the best of our knowledge. Employing a graph-tabular encoder, with pre-trained weight initialization, and multiple task-specific heads, DeXposure-FM is trained on the DeXposure dataset that has 43.7 million data entries, across 4,300+ protocols on 602 blockchains, covering 24,300+ unique tokens. The training is operationalized for credit-exposure forecasting, predicting the joint dynamics of (1) protocol-level flows, and (2) the topology and weights of credit-exposure links. The DeXposure-FM is empirically validated on two machine learning benchmarks; it consistently outperforms the state-of-the-art approaches, including a graph foundation model and temporal graph neural networks. DeXposure-FM further produces financial economics tools that support macroprudential monitoring and scenario-based DeFi stress testing, by enabling protocol-level systemic-importance scores, sector-level spillover and concentration measures via a forecast-then-measure pipeline. Empirical verification fully supports our financial economics tools. The model and code have been publicly available. Model: https://huggingface.co/EVIEHub/DeXposure-FM. Code: https://github.com/EVIEHub/DeXposure-FM.
Abstract. The development of technologies for creating combat drones from civilian drones, the expansion of the practice of using these drones in ongoing military conflicts of varying intensity, as well as the development of artificial intelligence (AI) systems and the possibility of various combinations of AI with combat drones, constitute an already occurring, not yet fully understood, global security challenge that is dangerous for any existing country. The paper also examines the problem of an individual customer outsourcing the commission of an act of revenge or a terrorist attack to individual perpetrators, groups of perpetrators, as well as to AI systems that act autonomously using telecommunications networks, such as the Internet, robotics, and that conduct financing using cryptocurrencies. The security threats discussed here, in the context of the emergence of UAVs and other combat-purpose drones in private hands – supplied both from active armies and manufactured independently – represent a dual combination of threats to the established world order and opportunities for society. And it is clear that the security threat is not some ephemeral threat to the security of some ordinary voter, whose life and fate do not, in reality, interest anyone from the ruling stratum at all. The real security threat is the threat to the life, health, capital, and power of the stratum that rules society, as well as the risk that the service personnel of this stratum – in the form of intelligence services, security and judicial bodies, as well as the legislative branch – will be afraid to carry out the orders given to them, both those involving blatant violations of the law and those involving its simulated enforcement, aimed at continuing the exploitation of society under the guise of observing the constitution and other laws, conducting “a dog-and-pony version of democracy.” The other side of the coin manifests itself as “frontier justice” – the ability for an ordinary person to defend their violated rights even when the violator has an overwhelming advantage in the form of administrative, judicial, and financial resources. It should be taken into account that modern technologies – not only the combination of outsourcing with the use of public computer networks (Public Data Networks, PDN) to commit a crime, or the possibility of direct remote control of a drone, but also the possibility of using a drone with built-in AI deliberately trained to strike a target – are merely the tip of the iceberg that the “Titanic” of the established security system will collide with. Further technological development, in particular decentralized AI using Web 3.0 / Web3, will make it possible to use AI as the executor of a deceased person’s will, while transferring to the AI the necessary financial resources in cryptocurrency (including programming the AI to further criminal acquisition of funds for its activities), combined with the ability to use fab labs or to have the AI itself hire contractors, creates for the targets of an attack aimed by such an AI a situation of the inevitability of retribution. At the same time, these capabilities can be extrapolated to any life situations – for example, those involving deprivation of liberty, such as in connection with the abduction of any person following the example of the abduction of N. Maduro, or situations such as bankruptcy resulting from the bad-faith actions of counterparties. At the same time, the risk of retribution in the process of defending violated rights affects both rank-and-file executors – such as police officers and judges – and the real masters of the country in the form of the public and non-public elite. The latter situation – the threat to the lives of the elite – already appears to be a real problem requiring a solution. After all, it would be extremely painful for the ruling strata of countries that have fought wars and then reconciled – the main beneficiaries of the past war – to answer to the victims for crimes committed both during the war and during mobilization, even if the terms of peace provide for full amnesty. An absolutely unfamiliar sense of danger will also emerge among the ruling strata governing states that ignite wars and create crises, since they now find themselves in a vulnerable position. This situation is further aggravated by the fact that information – both factual and conspiracy theories – is now widely accessible and can serve as grounds for attacks on representatives of well-known families, both by informed individuals and by mentally ill people. Would the issue of depriving Denmark of Greenland even be on the agenda now if, during the 2024 assassination attempts on D. Trump (AP News, 2025; Reuters, 2025), terrorists had used not firearms but a group of fiber-optic drones with centralized AI trained to recognize its target? The third side of the coin will be the need to minimize offenses in society and to introduce mechanisms of genuine democracy and accountability of the authorities for the results of their activities, when the overwhelming majority of the population is involved in decision-making – from ensuring the functioning of a city district to the election of sheriffs, judges, prosecutors, and all the way to voting on draft laws as well as federal elections (see the experience of Switzerland). This system will make it possible to reduce the number of legal violations by representatives of the ruling strata and to hold them accountable for both past and ongoing crimes without the need for extrajudicial reprisals by private individuals. Concluding the enumeration of the main aspects of changes in public life caused by the development of private combat robotics, let us also consider the fourth side of the same coin. All the technologies and capabilities discussed can be implemented by a wide range of individuals with disturbed psyches, for example religious fanatics, as well as by criminal elements, for whom new technologies present the broadest opportunities for blackmail, robberies, and extortion. And it is precisely against such individuals that it will be necessary to create a security system of a new quality – one that does not yet exist – a security system costing hundreds of billions of euros for each country deploying it, ensuring comprehensive protection of society from new types of threats. Of course, it may seem that the development of such a security system is possible without social modernization of relations in society and without the introduction of mechanisms of real democracy. It may seem that the implementation of a police state based on a digital concentration camp is more preferable. Perhaps – but this would require conducting an experiment, for example following the model of Pakistan or the DPRK, where the ruling military or party elite lives isolated from the main part of the population. In doing so, the ruling stratum would have to survive under new conditions of total war with its own population, from whom, for the sake of “security,” absolutely all remaining freedoms would be taken away, following the example of the DPRK. The application of AI that can operate in our world after the death of the person for whom the AI serves as executor proves that the empirical rule “you can’t take your money with you” is gradually losing its meaning: AI or artificial consciousness (AC) makes it possible to practically and almost inevitably implement the will of either the deceased or, say, a person who has been imprisoned or kidnapped, as well as someone who has found themselves in other situations that limit their ability to act. In this regard, the next customer ordering the next kidnapping of N. Maduro will think very hard about whether it is worth dying from retaliatory actions by AI, or from the actions of an actor who has decided that the triggering event for the AI’s predefined action cycle has occurred. At the same time, an actor in the form of decentralized AI cannot be intimidated, bought, or destroyed. In effect, new technologies put at the disposal of private individuals and organizations what previously only states had at their disposal, in particular an analogue of a system like “Perimeter” (RVSN RF index 15E601, known in journalism as “Dead Hand”) (Stilwell, 2022). Of course, the AI (or AC) systems discussed above – first and foremost decentralized AI, designed so that they cannot be influenced or have their operating order changed either by shutdown or by blackmail involving the risk of shutdown – may also inherently carry socially constructive tasks. Already now, AI systems can function as independent and autonomous executors, even though they still contain certain built-in technological limitations. Even this, however, already makes it possible to use such systems effectively both as operational AI assistants and as systems for auditing human decisions for compliance with specified goals and/or means (Gudkov, 2020; Cowger, 2023; Li, 2024; Bell, 2025; Brennan, 2025; Brown, 2025). Here and throughout, wherever AI is discussed, the possibility of using an IS is also implied – one that differs from AI by the presence of a software equivalent of will. The rate at which AI systems operating in the PDN evolve into IS systems also operating in the PDN is not considered here, nor is the time it takes for laboratory IS systems to enter the PDN. And, as practice shows, innovations are primarily directed toward the sphere of committing crimes – for example, the elimination of undesirable individuals – an activity engaged in both by independent criminals, such as roaming bandits, and by the intelligence services and ministries of defense of stationary bandits – states. In this regard, although the fully robotic technologies discussed above, which do not involve human intervention in their operation from the moment of launch, can also be used for constructive activities, their priority emergence in cri
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2 source records
Ethics and Social Impacts of AI
Legal, Health, Environmental and COVID-19 Challenges
Imoleayo Abraham Awodele, Molusiwa S. Ramabodu, Nathaniel Ayinde Olatunde, Iruka C. Anugwo
Africa is richly endowed with renewable energy resources, including solar, wind, and hydropower, yet the continent faces a significant energy access deficit, with over 600 million people lacking reliable electricity. Traditional fossil fuel-based energy models have proven inadequate for meeting the region's growing energy demands while posing environmental and economic challenges. This study explores the need to transcend these conventional energy paradigms by accelerating the adoption of sustainable, inclusive renewable energy systems tailored to Africa's unique context. Adopting a qualitative research approach, the study employed document analysis of policy reports, scholarly literature, and energy market trends to examine the continent's renewable energy transition. Thematic analysis identified key barriers such as limited access to financing, fragmented regulatory frameworks, and insufficient technical capacity. However, the findings also highlight transformative opportunities, including decentralized energy systems for off-grid rural communities, digital innovations, and international climate finance. The study recommends empowering community-driven energy models, adopting innovative financing mechanisms such as microcredit and crowdfunding and fostering cross-sectoral collaboration. These measures will not only expand energy access but also position Africa as a leader in global climate action, environmental sustainability, and inclusive energy innovation. Keywords: Renewable Energy Transition; Decentralized Energy Systems; Sustainable Development; Africa Energy Policy.
Yaroslava Yakovenko, Zavodovska D., Reichling Peter
Over the past decade, cryptocurrencies have evolved from a niche technological innovation into a global financial phenomenon. Bitcoin, Ethereum, and other digital assets have attracted massive attention from investors, policymakers, and the general public. The central debate surrounding cryptocurrencies centres on whether they represent a financial bubble destined to burst or the foundation of a new, decentralized financial future.
Essais sur le crédit, la découverte des taux et les facteurs déterminants du prix des jetons en finance décentralisée Cette thèse explore les fondements économiques et comportementaux de la finance décentralisée (DeFi), un champ en pleine expansion où les fonctions de prêt, d'emprunt et de fixation des taux d'intérêt sont assurées par des contrats intelligents plutôt que par des institutions financières. À travers trois essais complémentaires, ce travail analyse la conception des protocoles de crédit décentralisés, la formation des taux d'intérêt dans des marchés automatisés et les déterminants fondamentaux et comportementaux de la valorisation des tokens DeFi.Le premier essai examine l'architecture du protocole Atlendis, qui permet des prêts non ou partiellement collatéralisés grâce à l'articulation entre souscription off-chain et exécution on-chain. Le deuxième propose un modèle théorique de découverte de taux basé sur une approche de jeu multi-unités, identifiant les conditions d'efficience et les frictions propres aux marchés décentralisés. Le troisième évalue empiriquement les facteurs économiques et comportementaux influençant les rendements des tokens, révélant le rôle central du sentiment des investisseurs et de la liquidité on-chain dans la dynamique des prix. En combinant ingénierie financière, modélisation théorique et analyse empirique, cette recherche met en lumière les mécanismes par lesquels la DeFi redéfinit l'intermédiation, la formation des prix et la gouvernance financière dans un environnement transparent et programmable.
India holds a crucial place in the worldwide leadership of sustainable development since it is the largest democracy in the world and has one of the nations with the greatest economic growth. With innovation, inclusivity, and sustainability at its core, Viksit Bharat @2047 symbolizes India's ambition to become a fully developed country by the century of its independence. Emerging technologies are increasing productivity, boosting global competitiveness, and spurring innovation in various industries. By providing tailored financial assistance & investment suggestions, artificial intelligence-powered chatbots & robo-advisors are democratizing the provision of financial planning services. Decentralized finance (DeFi) systems and other blockchain-based solutions are simplifying trade finance procedures, lowering operating costs, and facilitating safe and transparent cross-border transactions. This chapter examines how innovation and technology are essential to achieving this lofty goal. It provides a thorough examination of India's contemporary digital infrastructure, the country's ascent in international innovation rankings, & the use of cutting-edge technologies including biotechnology, renewable energy, artificial intelligence, and space research. The story highlights government programs such as Start-up India, Digital India, and the National AI & Green Hydrogen Missions. Furthermore, the story underscores the importance of inclusive growth, which encompasses youth empowerment, women-led innovation, and rural digitization. Alongside strategic advice, issues like cybersecurity concerns, low investment in research and growth, and the digital divide are also discussed. India is positioned to emerge as a worldwide leader in technology, not simply a consumer, by cultivating a strong innovation ecosystem and utilizing partnerships between university, industry, and the private sector. This chapter provides a comprehensive plan for a tech-powered, inclusive, and sustainable Viksit Bharat before 2047. Higher education is one of the areas that must use developing technology, especially artificial intelligence (AI), to achieve Viksit Bharat 2047 (the Developed India 2047). Outside of higher education, artificial intelligence influences technology and economic progress. Young minds will realize this transformative vision as soon as they actively interact with AI. AI literacy empowers students in higher education to investigate, produce, and innovate. Students may do research, find solutions to real-world issues, and alter the course of history as they learn AI.
Open access
Innovation and Socioeconomic Development
Innovations and Analysis in Business and Education
This study is intended to examine the effect of the Degree of Fiscal Decentralization, Regional Financial Dependence, PAD Effectiveness, and SiLPA Financing Level on Capital Expenditure Allocation in Provinces on the Island of Sumatra during the period 2019 to 2023 with the official website of the Supreme Audit Agency of the Republic of Indonesia which is the main source of secondary data collection in this study. and multiple regression methods with Eviews 13. Based on the results of partial analysis, the variables of the degree of fiscal decentralization and regional financial dependence have a significant positive effect on the allocation of expenditure in the Province on the Island of Sumatra. In contrast, the variable effectiveness of PAD and the level of SiLPA financing on the allocation of capital expenditure in the Province on the Island of Sumatra. Simultaneous test results indicate that the four variables affect the allocation of capital expenditure. This finding indicates that an increase in the effectiveness of PAD and the level of SiLPA financing does not always lead to an increase in the allocation of capital expenditure if the provincial government on the island of Sumatra cannot manage the APBD budget properly.
The anonymity of cryptocurrency transactions poses substantial obstacles to protecting consumer rights, particularly by hindering tracking and dispute resolution, thereby making it challenging to safeguard consumers. This article examines India's legal framework for protecting consumers engaging in cryptocurrency transactions. It highlights the multifaceted challenges consumers face, including fraud, hacking, phishing, and market manipulation, primarily due to the anonymous nature of cryptocurrency transactions and the inherent lack of robust regulation. Comparing India's approach with that of the US, EU, and Japan, it identifies noticeable gaps in current regulations and subsequently proposes specific, actionable recommendations for improvement. The article emphasises the imperative need for consumer education and awareness, as well as for international cooperation among policymakers, industry stakeholders, and regulators to create a safer, more secure cryptocurrency environment. By analyzing consumer protection laws in depth and proposing amendments, it aims to balance transaction security effectively with investor protection, ultimately promoting a more reliable cryptocurrency ecosystem in India while also suggesting practical implementation strategies for regulators and fostering transparency in decentralized finance (DeFi) platforms to enhance overall market integrity. It further outlines specific policy frameworks that can be adopted to mitigate risks associated with anonymity, alongside actionable steps for enhancing dispute-resolution mechanisms and ensuring continual compliance with evolving global standards in digital asset regulation. KEYWORDS:- cryptocurrency transactions, consumer rights, legal framework, consumer education, transaction security
Ziyue Wang, Jiangshan Yu, Kaihua Qin, Dawn Song · 6 authors
Decentralized Finance (DeFi) has turned blockchains into financial infrastructure, allowing anyone to trade, lend, and build protocols without intermediaries, but this openness exposes pools of value controlled by code. Within five years, the DeFi ecosystem has lost over 15.75B USD to reported exploits. Many exploits arise from permissionless opportunities that any participant can trigger using only public state and standard interfaces, which we call Anyone-Can-Take (ACT) opportunities. Despite on-chain transparency, postmortem analysis remains slow and manual: investigations start from limited evidence, sometimes only a single transaction hash, and must reconstruct the exploit lifecycle by recovering related transactions, contract code, and state dependencies. We present TxRay, a Large Language Model (LLM) agentic postmortem system that uses tool calls to reconstruct live ACT attacks from limited evidence. Starting from one or more seed transactions, TxRay recovers the exploit lifecycle, derives an evidence-backed root cause, and generates a runnable, self-contained Proof of Concept (PoC) that deterministically reproduces the incident. TxRay self-checks postmortems by encoding incident-specific semantic oracles as executable assertions. To evaluate PoC correctness and quality, we develop PoCEvaluator, an independent agentic execution-and-review evaluator. On 114 incidents from DeFiHackLabs, TxRay produces an expert-aligned root cause and an executable PoC for 105 incidents, achieving 92.11% end-to-end reproduction. Under PoCEvaluator, 98.1% of TxRay PoCs avoid hard-coding attacker addresses, a +22.9pp lift over DeFiHackLabs. In a live deployment, TxRay delivers validated root causes in 40 minutes and PoCs in 59 minutes at median latency. TxRay's oracle-validated PoCs enable attack imitation, improving coverage by 15.6% and 65.5% over STING and APE.
The rapid advancement of blockchain network protocols has positioned decentralized finance (DeFi) as a key distributed application ecosystem in modern digital infrastructure. These distributed network systems are reshaping traditional financial paradigms by leveraging peer-to-peer protocols for accessible, transparent, and efficient services. However, the underlying network infrastructure faces significant security challenges, particularly concerning transaction manipulation within the framework of Maximal Extractable Value (MEV). MEV has emerged as a critical network security vulnerability due to its exploitation of transaction-ordering mechanisms in blockchain consensus protocols. Despite extensive research on MEV, critical gaps remain in understanding and securing distributed ledger networks against these vulnerabilities across various blockchain platforms. In this paper, we present a comprehensive survey of MEV within DeFi ecosystems through a multi-faceted approach. We provide a detailed taxonomy of MEV attack strategies targeting network protocol vulnerabilities. Furthermore, we offer a categorization of security countermeasures spanning consensus protocols, base-layer network design, and application-level defenses. Additionally, we present an empirical analysis of MEV dynamics across different blockchain networks, quantifying their impact on network performance, security, and fairness. This study contributes to enhancing the security of distributed network applications and advancing more robust and equitable network protocols for decentralized systems.
Perkembangan teknologi digital telah mentransformasi praktik akuntansi secara fundamental, memperluas perannya dari sekadar sistem pencatatan dan pelaporan menjadi instrumen strategis dalam pengambilan keputusan keuangan. Seiring dengan meningkatnya volume dan kompleksitas literatur mengenai akuntansi digital, diperlukan pemetaan sistematis untuk memahami struktur intelektual, tema penelitian utama, serta arah perkembangan bidang ini. Studi ini bertujuan untuk memetakan lanskap penelitian digital accounting dalam financial decision making menggunakan pendekatan bibliometrik. Data penelitian diperoleh dari publikasi terindeks Scopus dan dianalisis menggunakan teknik pemetaan bibliometrik melalui analisis kemunculan bersama kata kunci, jejaring penulis, institusi, dan negara. Hasil analisis menunjukkan bahwa decision making merupakan tema sentral yang menghubungkan berbagai klaster penelitian, dengan fondasi kuat pada sistem informasi akuntansi dan manajemen informasi. Selain itu, terdapat pergeseran signifikan menuju topik-topik mutakhir seperti artificial intelligence, machine learning, blockchain, automation, dan decentralized finance, yang menandai transformasi akuntansi digital menuju sistem prediktif dan real-time. Analisis kolaborasi juga mengungkap sifat global dan multidisipliner dari penelitian ini, meskipun beberapa tema seperti keberlanjutan dan teknologi emerging masih relatif kurang dieksplorasi. Temuan studi ini memberikan kontribusi konseptual dengan menyajikan gambaran komprehensif evolusi riset digital accounting serta memberikan implikasi praktis dan agenda riset masa depan bagi akademisi dan praktisi dalam mendukung pengambilan keputusan keuangan yang lebih efektif di era digital.
Financial technology (FinTech) has emerged as a transformative force in the global financial landscape, integrating advanced digital technologies like Artificial Intelligence and distributed ledger systems into traditional services. Since the early 21st century, it has fundamentally reshaped how payments, credit, investments, and risk management are handled. At the vanguard of this revolution are blockchain and cryptocurrencies, which provide decentralized and borderless alternatives to conventional banking. This research explores the evolution of these technologies, examining how smart contracts and automated systems drive efficiency and foster global financial inclusion. However, alongside these advancements, the study highlights the emergence of significant risks, particularly in the realms of cybersecurity, consumer protection, and the complex challenges of cross-border regulatory compliance. The paper further analyzes the strategic responses of traditional financial institutions and central banks, specifically focusing on the rise of Central Bank Digital Currencies (CBDCs) as a stable counter-narrative to private digital assets. Through various global case studies, the research illustrates the diverse regional adoption patterns influenced by local economic and cultural factors. Looking toward the future, the study predicts a trend of increased interoperability, where decentralized finance (DeFi) and programmable money integrate into mainstream economic structures. Ultimately, the paper argues that while the digital transformation of money offers immense potential for efficiency, its long-term success is contingent upon robust international governance frameworks and collaborative regulatory efforts to ensure trust and stability in the evolving global market.
Blockchain technology has emerged as a pivotal and transformative force, establishing transparent, secure, and decentralized frameworks for transaction management. Its core strengths include immutability, data decentralization, and consensus validation, alongside the automation provided by self-executing smart contracts. This review examines its foundational technologies, diverse applications, and associated challenges. Blockchain demonstrates profound potential across sectors like finance (e.g., Anti-Money Laundering and fraud reduction), education (credential verification), healthcare (secure record management), and the Metaverse (verifiable digital asset ownership via non-fungible tokens). However, adoption is significantly hindered by critical issues, including scalability bottlenecks, the energy inefficiency of protocols like Proof of Work, and security risks stemming from smart contract flaws, with case-based testing revealing up to 40% of public contracts have exploitable vulnerabilities. Recent advancements in high-throughput rollups and formal verification mitigate these risks. This coincides with a 2025 shift toward structured legal mandates, such as the EU’s MiCA, India’s VDA policy, and the U.S. GENIUS and CLARITY Acts. Therefore, future research must prioritize enhancing smart contract verification, developing energy-efficient consensus mechanisms, cross-chain interoperability, and fostering the continued alignment of supportive legal and regulatory frameworks.
The decentralized finance market exhibits extreme volatility and complex nonlinear dynamics that pose significant challenges for accurate price prediction and risk management. Traditional time series models, including Long Short-Term Memory networks and Transformer architectures, struggle with either computational inefficiency in capturing long-rangedependencies or inadequate context retention across extended sequences. This research investigates the application of Structured State Space Models, particularly the Mamba architecture with selective state spaces, for modeling temporal dependencies in DeFi markets. The proposed framework addresses the limitations of conventional approaches by leveraging SSMs' linear-time complexity while maintaining superior long-sequence modeling capabilities through context-aware selective mechanisms. Our methodology integrates SSM architectures with DeFispecific features including on-chain transaction volumes, liquidity metrics, and market microstructure indicators. Experimental validation across multiple cryptocurrency pairs demonstrates that SSM-based models achieve competitive performance compared to attentionbaseTransformers while offering substantial computational advantages. The results indicate that selective state space mechanisms enable effective capture of both short-term volatility patterns and long-horizon price trends in decentralized markets. This work contributes to the emerginintersection of advanced sequence modeling techniques and blockchain-based financial systems, providing insights for algorithmic trading strategies and risk assessment frameworks in the rapidly evolving DeFi ecosystem.