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1,491 results · page 15 of 63
A. Galdeman, M. Zignani, C. Quadri, S. Gaito
No abstract is available for this record.
Sonja Kivinen
Tämän opinnäytetyön tavoitteena oli selvittää, miten kassanhallinta ja talousohjaus tulisi suunnitella web3-pohjaisessa startup -yrityksessä, jonka liiketoimintamalli on kehitysvaiheessa. Tutkimus kohdistui case-yritykseen, jonka toiminta yhdistää kotimaisen luonnonkalan välittämiseen perustuvan kalaliiketoiminnan sekä digitaalisen toimitusketjuratkaisun kehittämisen. Tutkimus toteutettiin laadullisena kehittämistyönä, jossa aineistona hyödynnettiin yrityksen edustajien haastatteluja sekä kassanhallinnan ja talousohjauksen teoreettista viitekehystä. Työssä analysoitiin yrityksen rahoitusrakennetta, operatiivisen kassavirran haasteita sekä taloushallinnon nykytilaa. Tulosten perusteella kassanhallinta kehitysvaiheessa olevassa startup -yrityksessä tulee rakentaa integroiduksi kokonaisuudeksi, joka yhdistää maksuperusteisen kassavirtaennusteen, burn rate- ja runway-seurannan, operatiiviset ja strategiset mittarit sekä vaiheittaisen järjestelmäintegraation. Kalaliiketoiminnan erityispiirteet, kuten ostojen ja myyntien ajoituserot sekä varaston kiertoon sitoutuva pääoma, korostavat käyttöpääoman hallinnan merkitystä. Web3- ja ERP-ratkaisut voivat parantaa kassavirran läpinäkyvyyttä ja reaaliaikaista seurantaa, mutta niiden tulee tukea selkeästi määriteltyä talousohjausmallia. Taloushallinnon osalta suositeltavaksi ratkaisuksi muodostui hybridimalli, jossa lakisääteiset toiminnot ulkoistetaan ja operatiivisesti kriittiset prosessit integroidaan yrityksen omaan järjestelmään. Opinnäytetyön tuloksena syntyi käytännönläheinen kassanhallinnan ja mittariston malli, joka tukee yrityksen siirtymää kehitysvaiheesta kohti taloudellisesti kestävää liiketoimintaa.
Tiago Ferreira Cavazin
O presente diagnóstico econômico investiga as falhas estruturais e as vulnerabilidades sistêmicas inerentes aos modelos de engenharia econômica da Web3, fundamentando-se no princípio da não neutralidade da moeda conhecido como Efeito Cantillon. A pesquisa articula como a distribuição assimétrica inicial de tokens, frequentemente favorecendo fundadores e investidores institucionais, estabelece uma assinatura econômica de fragilidade que compromete a descentralização e a sustentabilidade dos protocolos digitais. Através de uma abordagem interdisciplinar, o relatório integra o conceito de Doppler Econômico para explicar a defasagem informacional entre agentes privilegiados e o público geral, além de utilizar a metáfora do Mammoth Money para descrever dinâmicas de predação de capital. Para a verificação empírica, aplica-se a Lei de Benford como ferramenta de auditoria estatística e a Curva de Laffer para determinar os limites de incentivos de emissão. O estudo conclui que a resiliência dos ecossistemas Web3 depende de um redesenho fundamental dos mecanismos de alocação inicial e de uma transparência radical que mitigue as distorções perceptivas e econômicas que levam a colapsos catastróficos e eventos de Cisne Negro.<br>
Ms. Aditi Methi
The rapid evolution of cryptocurrency, blockchain technology, and Web3 ecosystems has significantly transformed global financial systems and digital economies. India has emerged as one of the largest cryptocurrency adoption markets due to increasing internet penetration, fintech innovation, digital payment infrastructure, and a young technology-oriented population. Simultaneously, the rise of decentralized finance (DeFi), tokenized assets, Central Bank Digital Currencies (CBDCs), and artificial intelligence integration with blockchain has redefined the scope of digital assets beyond speculative investment instruments. This research paper examines the emerging trends, regulatory developments, opportunities, and challenges associated with cryptocurrency and blockchain adoption in India in 2026. The paper also analyses government policies, taxation frameworks, investor behavior, cybersecurity risks, and institutional participation. The findings suggest that India possesses strong potential to become a global blockchain innovation hub if supported by balanced regulation, improved investor awareness, and sustainable technological development.
Sina Khoshtarkib zenoozi
No abstract is available for this record.
Fang Lin, Jianjun He
Non-fungible tokens (NFTs) have become a key asset class in Web3 markets, where visual artwork, textual narratives, and on-chain transaction patterns jointly determine value, yet their pricing dynamics remain volatile, opaque, and difficult to explain. Existing NFT valuation methods typically either ignore the multimodal nature of NFTs or treat assets as independent samples, failing to exploit the rich relational structures induced by shared creators, collections, and ownership patterns, and offering limited interpretability for high-stakes financial decisions. To address these challenges, we propose NFT-Insight, a multimodal graph transformer framework that unifies visual, textual, and blockchain information on a heterogeneous NFT graph and explicitly links structural and content signals to valuation behavior. The framework identifies closely related NFTs via a joint similarity measure in the multimodal embedding space, propagates information through a relation-specific graph attention network and a global transformer encoder, and adopts a regularization strategy that encourages consistent valuations for highly similar assets while still allowing data-driven differentiation. In addition, NFT-Insight integrates attention-based and SHAP-based explanations into a unified analysis pipeline, enabling joint study of valuation behavior and feature attributions at the level of related NFT pairs. Experiments on three large-scale, real-world NFT datasets show that NFT-Insight consistently outperforms strong unimodal, multimodal, and graph-based baselines, reducing MAE and RMSE by up to about 20% in static valuation (withR2up to 0.904), achieving robust cross-market performance with averageR2≈ 0.84 andr≈ 0.93, and attainingR2= 0.911 in temporal forecasting. Interpretability analysis reveals that visual, textual, blockchain, and graph-relational features achieve a high alignment between SHAP importance and attention weights (average Spearman correlation above 0.8), and case studies highlight meaningful valuation patterns driven by rarity, speculative trading, and temporal market shocks. Overall, the proposed framework offers a multimodal graph–based perspective on explainable NFT valuation and market forecasting, and provides a general template for incorporating complex relational and content interactions into graph-based learning in decentralized digital economies.
Adaobi Ndukaji
No abstract is available for this record.
Zishan Mohammad, Nicolas Harkiolakis, Saman Sarbazvatan
No abstract is available for this record.
Shema Nkindi Giscard, Mukiibi Moses
No abstract is available for this record.
Jonathan C Kraft
The Internet has evolved from its early promise of global connection and freedom into a centralized system dominated by Big Tech and governments, resulting in widespread data exploitation, surveillance, censorship, and erosion of user privacy and ownership. This paper traces the historical development of Web2 infrastructure, its foundational flaws—particularly the linkage of digital identities to real-world persons and the unchecked power of intermediaries—and the societal pressures that have exposed these vulnerabilities through events such as the Great Firewall of China, the Snowden revelations, the Cambridge Analytica scandal, and large-scale hacks. In response, the paper positions Web3 , underpinned by blockchain technology, as a necessary paradigm shift toward a decentralized, user-centric Internet. Web3 severs the tie between digital and physical identities, enables true data ownership, peer-to-peer encryption, global accessibility without geo-restrictions, and algorithmic governance that reduces reliance on potentially abusive middlemen. It argues that Web3 can encode core democratic values, including freedom of expression as articulated in Article 19 of the Universal Declaration of Human Rights, while addressing resistance from governments (concerned with control and taxation), Big Tech (threatened by loss of data monopolies), and everyday users (wary of complexity and perceived risks). The paper examines ethical considerations, potential misuse by bad actors, and the dual nature of technological innovation. It proposes four critical criteria for evaluating successful Web3 implementations: 1) affordability and equitable access with long-term cost reduction; 2) robust protection of individuals through privacy and bias mitigation, coupled with "freedom of speech, not reach"; 3) absence of any central governing body with control over development; and 4) a community-representative judicial system for handling violations of shared terms of service. Ultimately, this work contends that Web3 represents an inevitable evolution capable of empowering billions of users—particularly those in repressive regimes—by fostering transparency, equity, and self-governance, provided implementations adhere to these ethical and practical standards. It calls for cautious optimism, due diligence, and open-source verification in the transition to a more liberated and democratic digital era.
Jun-Won Lee
No abstract is available for this record.
LIU Ronglong, LI Ziwei, WAN Yue, WU Jiajing, JIANG Zigui
As the paradigm of ″decentralized next-generation Internet,″ Web3, relying on blockchain technology, has become an emerging field with great potential in the digital intelligence service ecosystem. However, Web3 phishing websites pose a serious threat to ecological health. Phishers carefully design domain names as the primary bait, inducing users to visit and engage in high-risk operations to steal digital assets. Currently, the antiphishing works of Web3 primarily focus on phishing account detection, phishing transaction detection, and phishing gang mining, whereas the existing phishing website domain name detection primarily targets traditional phishing websites, which have limitations such as insufficient adaptability and a lack of systematic analysis. To this end, a detection method called WPWHunter is proposed for Web3 phishing website domain names, which conducts multidimensional analysis on the detected real Web3 phishing websites and explores the potential application of Large Language Model (LLM) in web page analysis. The WPWHunter algorithm detects three features in Web3 phishing website domain names: inducing words, visual deception, and item name imitation. The experimental results show that WPWHunter can effectively detect suspicious Web3 phishing domains with a G-means index of 0.769 on a test set, which is 0.048 higher than that of the best-performing baseline method. Additionally, as a supplementary exploratory experiment, three universal LLM are used to analyze the content of Web3 phishing websites that WPWHunter failed to detect and the logic used by LLM to determine Web3 phishing websites is summarized.
Balasani Avinash, Balla Sahithi, Shaik Nousheen Sultana, Anugandula Kushal
The rapid progress in quantum computing poses a severe risk to contemporary blockchain systems, as their reliance on vulnerable primitives like ECDSA and RSA allows quantum algorithms (e.g., Shor's) to break discrete logarithm and factorization problems, potentially enabling attackers to forge signatures, steal assets, impersonate users, and compromise ledger immutability—undermining the core trust model of decentralized finance and Web3 applications.To preempt this crisis, we propose a next-generation quantum-resistant multicchain blockchain architecture fused with an intelligent AI-powered Web3 threat firewall. The framework natively adopts NIST-approved post-quantum cryptography, integrating lattice-based ML-DSA (Dilithium) and hash-based SLH-DSA (SPHINCS+) schemes throughout the protocol stack: from secure key-pair generation in wallets, through transaction signing, to rigorous multi-node verification during consensus. This design ensures end-to-end protection against foreseeable quantum threats across diverse chains without requiring disruptive hard forks or retrofits.Comprehensive testnet experiments quantify the trade-offs: post-quantum signatures incur larger payload sizes (typically 2–4× compared to ECDSA) and modestly increased signing/verification times, yet the overall transaction processing capacity remains practical for everyday use, with throughput and latency suitable for high-volume decentralized applications. Storage and bandwidth overheads stay manageable through optimized encoding and pruning techniques.Augmenting cryptographic hardening, the AI threat firewall leverages machine learning models to perform real-time anomaly detection across multichain interactions, identifying subtle signature irregularities, suspicious patterns, and novel attack vectors—including those exploiting transitional quantum vulnerabilities—thereby providing adaptive, proactive defense beyond static primitives.These findings confirm that fully quantum-secure blockchain systems are deployable today with acceptable performance penalties, paving the way for resilient, future-proof Web3 infrastructure capable of withstanding the quantum era while preserving usability, scalability, and economic viability for global adoption.
Di Fabrizio Fantini, Maurizio Crotto
No abstract is available for this record.
Gokul Alex
No abstract is available for this record.
Igor Calzada
Abstract This article critically examines how Web3 decentralization policy trends impact global digital governance, questioning whether they genuinely distribute power or merely shift influence to a new, tech-savvy elite. Based on fieldwork in Silicon Valley since August 2022 and engagement with scholars and practitioners up to December 2025, the article provides a conceptual analysis with emerging empirical insights around the nascent global Web3 movement. While Web3 advocates challenge centralized data monopolies and traditional state structures, this analysis critiques the assumption that Web3 democratizes power, highlighting both its potential for inclusion and risks of exclusion, insofar as it may reinforce hierarchies rooted in technical expertise and digital access. While acknowledging the broader landscape of Web3 governance (including hybrid and federated models) and scoping the Global North and Global South contexts considering global adoption cases, the article particularly focuses on three post-Westphalian paradigms: (i) Network States, (ii) Network Sovereignties, and (iii) Algorithmic Nations. While Network States advocate for crypto-libertarian governance, Network Sovereignties and Algorithmic Nations emphasize cooperative governance aimed at empowering minority communities, such as indigenous groups, stateless nations, and e-diasporas, through decentralized, data-driven systems. By engaging with both the limitations and some promises, prospects, and pitfalls of Web3, this article questions whether Web3 can create a more inclusive global order or if influence is increasingly concentrated among a new elite. This article contributes to debates on sovereignty, governance, and citizenship by advocating hybrid policy frameworks that balance global and local dynamics, emphasizing solidarity, digital justice, and international cooperation for equitable Web3 governance.
Daniil Kniazkin
Tato práce se zabývá integrací protokolu zkLogin do aplikace Web3, aby se uživatel mohl přihlásit pomocí účtu OpenID Connect místo správy seed phrase. Práce vysvětluje princip zkLogin, porovnává jej s jinými přístupy k autentizaci ve Web3 a implementuje prototyp pro Sui a Ethereum. Větev pro Sui používá nativní podporu zkLogin, zatímco větev pro Ethereum používá Groth16 důkaz, chytrý účet, registr JWK a ERC-4337. Jednoduchý lending scénář ověřuje opakované změny on-chain stavu po přihlášení. Výsledky ukazují, že zkLogin může zjednodušit onboarding a omezit přímé zveřejnění vazby mezi účtem Web2 a on-chain adresou, ale prototyp stále závisí na poskytovateli identity, salt service, proving infrastruktuře a správě veřejných klíčů.
Abbas Yazdinejad, Hadis Karimipour
Memory-enabled large language model (LLM) agents, particularly those deployed in long-horizon, tool-using settings such as Web3-style autonomous workflows, introduce security risks that extend beyond single-prompt injection. By persisting and reusing information across interaction steps and sessions, these agents enable memory poisoning attacks in which adversarial inputs modify persistent agent state and influence future decisions after benign intermediate interactions. Recent work on context manipulation and “fake memories” demonstrates that adversarial content can be injected into an agent’s prompt-visible inputs or persistent memory; however, existing evaluations largely analyze such attacks at isolated interaction steps or static context snapshots, obscuring their temporal dynamics. In this paper, we present the first large-scale, trajectory-level measurement framework for analyzing temporal memory poisoning in memory-enabled LLM agents. We construct a schema-constrained dataset of 2,614 multi-step attack trajectories spanning four attack families,chain poisoning, policy rewriting, backdoor triggering, andslow drift, executed over shared persistent memory. We define temporal risk metrics over multi-step interaction trajectories that capture delayed activation, non-monotonic escalation, and the earliest point at which attacks become distinguishable from benign behavior. Our empirical results show that a substantial fraction of attacks remain indistinguishable from benign behavior until late-stage activation, despite exhibiting low or medium risk at all earlier steps. Slow-drift and backdoor-trigger attacks, in particular, systematically evade step-local evaluation until terminal interactions, while chain poisoning and policy rewriting exhibit non-monotonic risk trajectories. These findings demonstrate that memory poisoning risk is inherently temporal and cannot be reliably assessed using prompt-level or step-isolated evaluation, motivating trajectory-aware benchmarks for agent security.
Микола Маленко
This article examines the limitations of existing hybrid rollup solutions and presents an adaptive L2 architecture model that leverages artificial intelligence mechanisms. It is shown that current approaches to combining optimistic and ZK verification are largely based on static rules or manual mode selection, which prevents them from effectively accounting for load dynamics, risk profiles, and domain-specific properties of applications. Based on an analysis of optimistic, ZK, and hybrid rollups, an adaptive hybrid rollup model with AI-based transaction routing is proposed. This model combines transaction classification, GNN-based decision making, LSTM-based network condition forecasting, a dual-path execution system, and a continuous learning module. The article describes a Predictive Routing Algorithm that performs proactive selection between ZK and optimistic paths, taking into account cost, latency, security, and risk profile, as well as a Dynamic Resources Allocation mechanism that dynamically redistributes resources between the paths. The proposed multi-criteria optimization framework demonstrates the ability to tune objective weights to the specifics of different classes of DeFi and Web3 protocols. It is shown that the implementation of such a model is promising for systems with high transactional intensity, as it enables a shift from manual configurations to automated, data-driven policies for resource and risk management in hybrid rollup architectures.
Qian'ang Mao, Jiaxin Wang, Liu Ya, Li Zhu · 6 authors
The decentralized architecture of Web3 technologies creates fundamental challenges for Anti-Money Laundering and Counter-Financing of Terrorism compliance. Traditional regulatory technology solutions designed for centralized financial systems prove inadequate for blockchain's transparent yet pseudonymous networks. This systematization examines how blockchain-native RegTech solutions leverage distributed ledger properties to enable novel compliance capabilities. We develop three taxonomies organizing the Web3 RegTech domain: a regulatory paradigm evolution framework across ten dimensions, a compliance protocol taxonomy encompassing five verification layers, and a RegTech lifecycle framework spanning preventive, real-time, and investigative phases. Through analysis of 41 operational commercial platforms and 28 academic prototypes selected from systematic literature review (2015-2025), we demonstrate that Web3 RegTech enables transaction graph analysis, real-time risk assessment, cross-chain analytics, and privacy-preserving verification approaches that are difficult to achieve or less commonly deployed in traditional centralized systems. Our analysis reveals critical gaps between academic innovation and industry deployment, alongside persistent challenges in cross-chain tracking, DeFi interaction analysis, privacy protocol monitoring, and scalability. We synthesize architectural best practices and identify research directions addressing these gaps while respecting Web3's core principles of decentralization, transparency, and user sovereignty.
Alsaadah Saif Mohammed ALabri, Shahd Ibrahim Ali AL Balushi
Blockchain is a distributed database used to store an unchangeable, permanent record of all transactions. It is operated by processors that are a member of a peer-to-peer (P2P) network and functions as a decentralized database. Demand for decentralized applications (DApps), which provide accountability, safety, and independence beyond conventional centralized systems, is rising as a result of the quick development of blockchain technology. However, combining frontend, back end, and blockchain components into a unified and effective framework might be difficult for DApp designers. In order to simplify the creation of decentralized applications, this study suggests a full-stack blockchain framework that connects various levels. The framework creates an end-to-end development environment designed for compatibility and scalability by utilizing contemporary technologies, such as Solidity, with Web3.js for smart contract integration, React.js for the front-end, and Node.js/Express.js for the backend. Using cryptographic methods and decentralized storage (like IPFS), a layered architecture is intended to provide modularity, effective data flow, and increased security. The suggested framework streamlines DApp development processes, lowers latency in blockchain interactions, and boosts developer efficiency, according to implementation data. By offering a thorough architectural blueprint and execution method for full-stack DApp creation, this study advances the area of blockchain engineering and opens the door for safe, effective, and user-focused decentralized ecosystems.
Allen Lin
Decentralized Autonomous Organizations (DAOs) face inherent institutional conflicts between their decentralized governance structures, tokenized incentive mechanisms, and rigid global regulatory frameworks—with the U.S. regulatory landscape (SEC, OFAC, FinCEN) emerging as the most stringent and impactful. In 2024, 7 U.S.-based DAOs were subject to SEC investigations (aggregate penalties of $12.8 million), 18% incurred FinCEN sanctions for OFAC-sanctioned address interactions, and 68% of Base chain DAOs were denied institutional capital due to inadequate compliance documentation. Grounded in institutional economics (regulatory adaptation theory), RegTech principles, and blockchain traceability, this study proposes a “three-dimensional compliance adaptation framework” for DAO governance—integrating a regulatory rule engine (quantitative alignment with U.S. rules), automated on-chain audit report generation (transparency assurance), and dynamic governance optimization (securities risk mitigation). Drawing on the development of the “DAO Shield Pro” system and empirical testing across 7 representative U.S. Base chain DAOs (3 AI-focused, 2 meme-based, 2 investment-focused) over a 6-month period (March–August 2025), the framework achieves: (1) a 67.9% reduction in average compliance risk scores (from 3.8 to 0.98), (2) a 45.6-percentage-point increase in U.S. institutional investor participation (from 7.8% to 53.4%), (3) a 100% SEC regulatory inquiry acceptance rate, and (4) a 64.2% reduction in monthly compliance labor costs (from $19,200 to $6,870). This research fills critical gaps in DAO compliance scholarship by providing a theoretically rigorous, technically actionable, and empirically validated solution tailored to U.S. regulatory requirements (SEC Howey Test, OFAC sanctions screening, PCAOB auditing standards). It advances the field by quantifying ambiguous regulatory rules into executable on-chain logic and delivers a replicable paradigm for global DAO regulatory adaptation—strengthening U.S. competitiveness in the Web3 ecosystem and unlocking an estimated $42–$58 billion in latent institutional investment.
Rob J. Lewis, Jonas Lembrechts, P. D. Walker, Chunli Li · 5 authors
Background and Rationale Despite decades of progress in ecological monitoring, primary biodiversity and environmental data remain unevenly mobilised and poorly interoperable (Hampton et al. 2015, Poisot et al. 2019). Datasets, often gathered with public funds, frequently remain inaccessible or insufficiently described, limiting their reuse in global syntheses (Culina et al. 2018). Ecologists’ concerns about trust, transparency, and control of shared data persist, particularly where data production is resource-intensive or socially embedded. These concerns echo the foundational properties of distributed ledgers, where ownership and governance are distributed across peer networks rather than centralized repositories (Lewis et al. 2023). Forests exemplify both the potential and the challenge of such decentralised infrastructures. As globally significant carbon and biodiversity reservoirs, forests are also deeply fragmented across ownership and jurisdictional boundaries. In Europe alone, over half of forested land is privately owned, yet these actors often lack mechanisms to derive tangible value from stewardship. At the same time, digital twins (macroecological models) that integrate in situ and remotely sensed data, are becoming central to forest policy and monitoring frameworks (e.g., Food and Agriculture Organization of the United Nations (FAO), Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Global Biodiversity Framework (GBF)). ForestWeb3 (FW3) hypothesizes that a decentralised, Findable Accessible, Interoperable, Reusable (FAIR; Wilkinson et al. 2016, Nosek et al. 2022)-aligned data network can unlock the latent value of underused biodiversity data while building trust and incentives for participation.. Objectives Mobilisation and harmonisation of forest biodiversity and environmental data (Objective 1): to spearhead a shift from data curation to data stewardship through a decentralised data infrastructure built on open-source blockchain frameworks. Incentivisation and uptake (Objective 2): to design transnational pathways through which private forest owners and local communities can be economically rewarded for verifiable ecological data via nature-backed digital assets and ReFi mechanisms. Together, these objectives align technical innovation (Objective 1) with behavioural and economic motivation (Objective 2), establishing the groundwork for distributed biodiversity observatories capable of sustaining long-term ecological data flows. Methodological Approach WP 1 develops a blockchain-based data ledger with smart contracts that autonomously manage data registration, access control, and reuse. Metadata and identifiers are immutably recorded on-chain, while primary datasets remain decentralised on contributor-managed nodes. This architecture enables contributors to retain data sovereignty while ensuring transparency and traceability in reuse transactions. WP 2 extends the infrastructure to real-time environmental sensing through the integration of modular Internet ofThings (IoiT)-based microclimate sensors. These devices stream environmental data at high temporal resolution directly into the distributed ledger, forming a Decentralized Physical Infrastructure Network (DePIN) for ecological data. WP 3 links these data streams to the creation of digital twins of forest ecosystems, combining in situ biodiversity observations with satellite and climate datasets to model ecosystem integrity. These models underpin the valuation of nature-backed digital assets, a form of tokenised evidence for ecological performance, providing the data foundation for voluntary biodiversity and carbon markets. Finally, WP4 investigates forest owners’ perceptions, motivations, and barriers to adopting regenerative finance (ReFi)-based conservation mechanisms. Through interviews and a pan-European survey, it explores how varying sociocultural and institutional contexts shape engagement with emerging biodiversity credit schemes, drawing parallels to established Payment for Ecosystem Services frameworks (Kaiser et al. 2021). Significance and Legacy FW3 exemplifies the convergence of data decentralisation, digital sensing, and regenerative economics, a triad capable of transforming how ecological knowledge is produced, verified, and valued. By embedding data provenance and attribution within the infrastructure itself, we addresses long-standing issues of trust and recognition in ecological data sharing. Its incentive mechanisms offer pathways to decouple conservation finance from traditional public funding, potentially scaling stewardship and democratizing data mobilisation across millions of hectares of privately owned forest land. The project’s legacy lies in demonstrating that data infrastructures can be both scientific and economic commons, capable of sustaining biodiversity monitoring through distributed participation. Beyond its immediate technical deliverables, ForestWeb3 contributes to a broader vision of dynamic, self-sustaining ecological data ecosystems that power both global biodiversity frameworks and locally grounded conservation action.
Seda Canoruç, Abdülkadir Kaya
This study aims to analyze the volatility spillovers between Bitcoin and Ethereum, the two main actors in the cryptocurrency market, and altcoins across sectoral and financial groups. Using data from January 1, 2021, to March 6, 2023, the study applied the VAR-based method developed by Diebold and Yılmaz (2012) and measured both directional and total volatility spillovers. The findings show that Bitcoin's volatility largely stems from internal dynamics and spreads to other cryptocurrencies to a limited extent. In contrast, Ethereum is more affected by external shocks and exhibits a stronger volatility spillover across the market. Among altcoin categories, Gaming, Analytics, and DeFi groups were found to be the most influential in volatility transmission, while thematic tokens such as NFT, Web3, and Metaverse were more sensitive to external volatility. In contrast, stablecoins and tokens in the identity and healthcare sectors were found to have relatively low volatility and a more stable structure. These results offer important insights for investors and regulators regarding risk management strategies and portfolio diversification. The study provides a valuable framework for understanding the systematic volatility dynamics within the cryptocurrency ecosystem