Gabriel Fernández-Blanco, Pedro García-Cereijo, David Lema-Núñez, Diego Ramil-López · 8 authors
In the last years, especially since the COVID-19 pandemic, precision medicine platforms emerged as useful tools for supporting new tests like the ones that detect the presence of antibodies and antigens with better sensitivity and specificity than traditional methods. In addition, the pandemic has also influenced the way people interact (decentralization), behave (digital world) and purchase health services (online). Moreover, there is a growing concern in the way health data are managed, especially in terms of privacy. To tackle such issues, this article presents a sustainable direct-to-consumer health-service open-source platform called HELENE that is supported by blockchain and by a novel decentralized oracle that protects patient data privacy. Specifically, HELENE enables health test providers to compete through auctions, allowing patients to bid for their services and to keep the control over their health test results. Moreover, data exchanges among the involved stakeholders can be performed in a trustworthy, transparent and standardized way to ease software integration and to avoid incompatibilities. After providing a thorough description of the platform, the proposed health platform is assessed in terms of smart contract performance. In addition, the response time of the developed oracle is evaluated and NIST SP 800-22 tests are executed to demonstrate the adequacy of the devised random number generator. Thus, this article shows the capabilities and novel propositions of HELENE for delivering health services providing an open-source platform for future researchers, who can enhance it and adapt it to their needs.
T. Q. D. Pham, K. D. Tran, Khanh T. P. Nguyen, X. V. Tran · 6 authors
As global industries transition towards Industry 5.0 predictive maintenance PM remains crucial for cost effective operations resilience and minimizing downtime in increasingly smart manufacturing environments In this chapter we explore how the integration of Federated Learning FL and blockchain BC technologies enhances the prediction of machinerys Remaining Useful Life RUL within decentralized and human centric industrial ecosystems Traditional centralized data approaches raise concerns over privacy security and scalability especially as Artificial intelligence AI driven smart manufacturing becomes more prevalent This chapter leverages FL to enable localized model training across multiple sites while utilizing BC to ensure trust transparency and data integrity across the network This BC integrated FL framework optimizes RUL predictions enhances data privacy and security establishes transparency and promotes collaboration in decentralized manufacturing It addresses key challenges such as maintaining privacy and security ensuring transparency and fairness and incentivizing participation in decentralized networks Experimental validation using the NASA CMAPSS dataset demonstrates the model effectiveness in real world scenarios and we extend our findings to the broader research community through open source code on GitHub inviting collaborative development to drive innovation in Industry 5.0
Joel Mark P. Rodriguez, Genesis S. Austria, Glen B. Millar
This study investigates how ABCD technologies can improve learning assessments in higher education. The objective is to research how students perceive things, plan their behavior, and how ABCD technologies affect individual learning, academic integrity, co-learning, and trust in the assessment. Through a quantitative research design, survey responses were gathered from university students, and statistical tests, such as correlation and regression, were used to establish relationships between Perceived Usefulness (PU), Perceived Ease of Use (PEU), and Behavioral Intention (BI) towards ABCD adoption. The results showed that there was no significant relationship between PU, PEU, and BI, which suggests that students' attitudes, institutional policies, faculty support, and infrastructure matter more in adoption than institutional policies, faculty support, and infrastructure. While students recognize ABCD's efficiency and security benefits, fairness, ease of use, and engagement issues limit their adoption of these technologies. The research adds to Technology Acceptance Model (TAM) and Constructivist Learning Theory (CLT) by emphasizing external drivers of technology adoption. The limitations are based on self-reported data and one institutional sample. It is suggested that universities invest in faculty development, infrastructure, and policy-making to facilitate effective and ethical use of ABCD technologies in higher education.
Himanshu Udupi, Ashutosh Sahoo, Akshay S. P., Gurukiran S. · 6 authors
Modern society functions on trust. The onchain economy, however, is built on the founding principles of trustless peer-to-peer interactions in an adversarial environment without a centralised body of trust and needs a verifiable system to quantify credibility to minimise bad economic activity. We provide a robust framework titled zScore, a core primitive for reputation derived from a wallet's onchain behaviour using state-of-the-art AI neural network models combined with real-world credentials ported onchain through zkTLS. The initial results tested on retroactive data from lending protocols establish a strong correlation between a good zScore and healthy borrowing and repayment behaviour, making it a robust and decentralised alibi for creditworthiness; we highlight significant improvements from previous attempts by protocols like Cred showcasing its robustness. We also present a list of possible applications of our system in Section 5, thereby establishing its utility in rewarding actual value creation while filtering noise and suspicious activity and flagging malicious behaviour by bad actors.
Abstract Decentralized Autonomous Organizations (DAOs) are attracting interest from various disciplines, particularly business and economics, and computer science. However, much like the parable of the blind men and the elephant, where each observer sees only part of the phenomenon, DAO research has largely remained fragmented across disciplines, limiting a comprehensive understanding of the potential of DAOs. This paper investigates to which extent DAO scholarship has achieved meaningful interdisciplinary integration. We address this question through an analysis of knowledge flows between Business and Economics and Computer Science, using citation network analysis, topic modelling, and outlet analysis. We find that while DAOs generate vibrant interdisciplinary discourse, the interactions remain predominantly applied and case-driven, with limited theoretical integration. By mapping interdisciplinary exchanges, we highlight key gaps and opportunities for greater synthesis across fields. We argue that strengthening the alignment between organizational and technical insights is crucial for advancing DAO research and fostering a more cohesive interdisciplinary framework.
We analyze developer activity across 10 major Ethereum repositories (totaling 129884 commits, 40550 issues) spanning 10 years to examine how events such as technical upgrades, market events, and community decisions impact development. Through statistical, survival, and network analyses, we find that technical events prompt increased activity before the event, followed by reduced commit rates afterwards, whereas market events lead to more reactive development. Core infrastructure repositories like Go-Ethereum exhibit faster issue resolution compared to developer tools, and technical events enhance core team collaboration. Our findings show how different types of events shape development dynamics, offering insights for project managers and developers in maintaining development momentum through major transitions. This work contributes to understanding the resilience of development communities and their adaptation to ecosystem changes.
Cryptocurrency network analysis consists of applying the tools and methods of social network analysis to transactional data issued from cryptocurrencies. The main difference with most online social networks is that users do not exchange textual content but instead value -- in systems designed mainly as cryptocurrency, such as Bitcoin -- or digital items and services in more permissive systems based on smart contracts such as Ethereum.
Decentralized physical infrastructure networks (DePINs) are an emerging vertical within "Web3" replacing the traditional method that physical infrastructures are constructed. Yet, the boundaries between DePIN and traditional method of building crowd-sourced infrastructures such as citizen science initiatives or other Web3 verticals are not always so clear cut. In this work, we systematically analyze the differences between DePIN and other Web2 and Web3 verticals. For this, the study proposes a novel decision tree for classifying systems as DePIN. This tree is informed by prior studies and differentiates DePIN from related concepts using criteria such as the presence of a three-sided market, token-based incentives for supply, and the requirement for physical asset placement in those systems. The paper demonstrates the application of the decision tree to various blockchain systems, including Helium and Bitcoin, showcasing its practical utility in differentiating DePIN systems. This research offers significant contributions towards establishing a more objective and systematic approach to identifying and categorizing DePIN systems. It lays the groundwork for creating a comprehensive and unbiased database of DePIN systems, which will inform future research and development within this emerging sector.
More than 95% of the crop genetic erosion articles analyzed in [9] reported changes in diversity, with nearly 80% providing evidence of loss. The lack of diversity presents a severe risk to the security of global food systems. Without seed diversity, it is difficult for plants to adapt to pests, diseases, and changing climate conditions. Genebanks, such as the Svalbard Global Seed Vault, are valuable initiatives to preserve seed diversity in a single secure and safe place. However, according to our analysis of the data available in the Seed Portal, the redundancy for some species might be limited, posing a potential threat to their future availability. Interestingly, the conditions to properly store seeds in genebanks, are the ones available in the freezers of our homes. This paper lays out a vision for Distributed Seed Storage relying on a peer-to-peer infrastructure of domestic freezers to increase the overall availability of seeds. We present a Proof-of-Concept focused on monitoring the proper seed storing conditions and incentive user participation through a Blockchain lottery. The PoC proves the feasibility of the proposed approach and outlines the main technical issues that still need to be efficiently solved to realize a fully-fledged solution.
Cybercriminals pose a significant threat to blockchain trading security, causing $40.9 billion in losses in 2024. However, the lack of an effective real-world address dataset hinders the advancement of cybercrime detection research. The anti-cybercrime efforts of researchers from broader fields, such as statistics and artificial intelligence, are blocked by data scarcity. In this paper, we present Real-CATS, a Real-world dataset of Cryptocurrency Addresses with Transaction profileS, serving as a practical training ground for developing and assessing detection methods. Real-CATS comprises 103,203 criminal addresses from real-world reports and 106,196 benign addresses from exchange customers. It satifies the C3R characteristics (Comprehensiveness, Classifiability, Customizability, and Real-world Transferability), which are fundemental for practical detection of cryptocurrency cybercrime. The dataset provides three main functions: 1) effective evaluation of detection methods, 2) support for feature extensions, and 3) a new evaluation scenario for real-world deployment. Real-CATS also offers opportunities to expand cybercrime measurement studies. It is particularly beneficial for researchers without cryptocurrency-related knowledge to engage in this emerging research field. We hope that studies on cryptocurrency cybercrime detection will be promoted by an increasing number of cross-disciplinary researchers drawn to this versatile data platform. All datasets are available at https://github.com/sjdseu/Real-CATS
Raha Aghaei, Ali A. Kiaei, Mahnaz Boush, Javad Vahidi · 6 authors
The integration of large language models (LLMs) into supply chain management (SCM) is revolutionizing the industry by improving decision-making, predictive analytics, and operational efficiency. This white paper explores the transformative impact of LLMs on various SCM functions, including demand forecasting, inventory management, supplier relationship management, and logistics optimization. By leveraging advanced data analytics and real-time insights, LLMs enable organizations to optimize resources, reduce costs, and improve responsiveness to market changes. Key findings highlight the benefits of integrating LLMs with emerging technologies such as IoT, blockchain, and robotics, which together create smarter and more autonomous supply chains. Ethical considerations, including bias mitigation and data protection, are taken into account to ensure fair and transparent AI practices. In addition, the paper discusses the need to educate the workforce on how to manage new AI-driven processes and the long-term strategic benefits of adopting LLMs. Strategic recommendations for SCM professionals include investing in high-quality data management, promoting cross-functional collaboration, and aligning LLM initiatives with overall business goals. The findings highlight the potential of LLMs to drive innovation, sustainability, and competitive advantage in the ever-changing supply chain management landscape.
In the past few years, "metaverse" and "non-fungible tokens (NFT)" have become buzzwords, and the prices of related assets have exhibited large fluctuations. Are those characteristic of a speculative bubble? In this paper, we attempt to answer this question, and better understand the underlying economic dynamics. We look at Decentraland, a virtual world platform where land parcels are sold as NFT collections. We find that initially, land prices followed traditional real estate pricing models - in particular, value decreased with distance from the most desirable areas - suggesting Decentraland behaved much like a virtual city. However, these real estate pricing models stopped applying when both the metaverse and NFTs gained increased popular attention and enthusiasm in 2021, suggesting a new driving force for the underlying asset prices. At that time, following a substantial rise in NFT market values, short-term holders of multiple parcels began to take major selling positions in the Decentraland market, which hints that, rather than building a metaverse community, early Decentraland investors preferred to cash out when land valuations became inflated. Our analysis also shows that while the majority of buyers are new entrants to the market (many of whom joined during the bubble), liquidity (i.e., parcels) was mostly provided by early adopters selling, which caused stark differences in monetary gains. Early adopters made money - more than 10,000 USD on average per parcel sold - but users who joined later typically made no profit or even incurred losses in the order of 1,000 USD per parcel. Unlike established markets such as financial and real estate markets, newly emergent digital marketplaces are mostly self-regulated. As a result, the significant financial risks we identify indicate a strong need for establishing appropriate standards of business conduct and improving user awareness.
We describe a protocol for creating, updating, and revoking digital diplomas that we anticipate would make use of the protocol for transferring digital assets elaborated by Goodell, Toliver, and Nakib. Digital diplomas would maintain their own state, and make use a distributed ledger as a mechanism for verifying their integrity. The use of a distributed ledger enables verification of the state of an asset without the need to contact the issuing institution, and we describe how the integrity of a diploma issued in this way can persist even in the absence of the issuing institution.
This paper critically reviews the integration of Artificial Intelligence (AI) and blockchain technologies in the context of Medical Internet of Things (MedIoT) applications, where they collectively promise to revolutionize healthcare delivery. By examining current research, we underscore AI's potential in advancing diagnostics and patient care, alongside blockchain's capacity to bolster data security and patient privacy. We focus particularly on the imperative to cultivate trust and ensure reliability within these systems. Our review highlights innovative solutions for managing healthcare data and challenges such as ensuring scalability, maintaining privacy, and promoting ethical practices within the MedIoT domain. We present a vision for integrating AI-driven insights with blockchain security in healthcare, offering a comprehensive review of current research and future directions. We conclude with a set of identified research gaps and propose that addressing these is crucial for achieving the dependable, secure, and patient -centric MedIoT applications of tomorrow.
Verisign reported a 125 percent increase in data breaches within the healthcare sector in the United States during 2022, with 18.2 million patient records being impacted. Growing healthcare data volumes and diversification mean that medical information is becoming more valuable. Many Health Centers use various technologies to ease the classification, storage, and exchange of big data. This use can also make the health data of the users at risk and vulnerable. AI and blockchain are among the leading technologies at hand. With AI, data-driven operations and big data efficiency have been improved with respect to traditional techniques. Due to its potential to bring about improvements in health services and lower medical costs, this AI technology is regularly used in healthcare. Blockchain helps protect transactions on sharing information and private privacy as long as the exchange of knowledge is that of the standard. The objective of this analysis is to investigate the research and unique contributions since 2008 regarding blockchain-integrated AI and healthcare systems. The work sheds light on applied AI-based healthcare schemes with machine, ballistic, and acrylic learning and disparate blockchain structures. The use of technology in order to ensure patient data security and manage medical information effectively in healthcare settings offers a highly successful position for both healthcare providers and patients. From 2018 to 2021, the best year was 2021 to grow, enhancing everything to examine the download of the device and the counting of Google Academies, for which the joining perspective was borrowed; local research experts were asked, identified articles in recent years, and read reviews of large research grants.
The convergence of humans and artificial intelligence systems introduces new dynamics into the cultural and intellectual landscape. Complementing emerging cultural evolution concepts such as machine culture, AI agents represent a significant techno-sociological development, particularly within the anthropological study of Web3 as a community focused on decentralization through blockchain. Despite their growing presence, the cultural significance of AI agents remains largely unexplored in academic literature. Toward this end, we conceived hybrid netnography, a novel interdisciplinary approach that examines the cultural and intellectual dynamics within digital ecosystems by analyzing the interactions and contributions of both human and AI agents as co-participants in shaping narratives, ideas, and cultural artifacts. We argue that, within the Web3 community on the social media platform X, these agents challenge traditional notions of participation and influence in public discourse, creating a hybrid marketplace of ideas, a conceptual space where human and AI generated ideas coexist and compete for attention. We examine the current state of AI agents in idea generation, propagation, and engagement, positioning their role as cultural agents through the lens of memetics and encouraging further inquiry into their cultural and societal impact. Additionally, we address the implications of this paradigm for privacy, intellectual property, and governance, highlighting the societal and legal challenges of integrating AI agents into the hybrid marketplace of ideas.
Global supply lines have been severely disrupted by the COVID-19 epidemic and the conflict between Russia and Ukraine, which has sharply increased the price of commodities and generated inflation. These incidents highlight how critical it is to improve supply chain resilience (SCRES) in order to fend off unforeseen setbacks. Controlling both internal and external interruptions, such as transportation problems brought on by natural catastrophes and wars, is the responsibility of SCRES. Enhancing resilience in supply chains requires accurate and timely information transfer. Promising answers to these problems can be found in the Metaverse and ChatGPT, two new digital technologies. The Metaverse may imitate real-world situations and offer dynamic, real-time 3D representations of supply chain data by integrating blockchain, IoT, network connection, and computer power.Large-scale natural language processing model ChatGPT improves communication and data translation accuracy and speed. To manage risk and facilitate decision making in Supply Chain management, firms should increase information transmission, Speed and quality. This study aim to show the importance of ChatGPT and Metaverse technologies to improve SCRES, with an emphasis on the most important criteria for SCRES, and maturity factor that can influence directly the SC development.
This study investigates how media influence and educational resources shape individual engagement with cryptocurrencies. As digital assets become increasingly mainstream, social media platforms, influencers, and financial analysts play a central role in driving public interest and investment behavior. Quantitative surveys and qualitative interviews reveal that persuasive narratives and success stories on social media often attract new investors, while accessible educational materials empower individuals to make informed decisions in a volatile market. The findings highlight that media exposure can spark initial adoption, but sustained and responsible participation depends on comprehensive education in cryptocurrency fundamentals, trading strategies, and blockchain technology
Mark C. Ballandies, Guangyao Li, Claudio J. Tessone
Abstract This paper investigates whether Bitcoin can be regarded as a decentralized autonomous organization (DAO), what insights it may offer for the broader DAO ecosystem, and how Bitcoin governance can be improved. First, a quantitative literature analysis reveals that Bitcoin is increasingly overlooked in DAO research, even though early works often classified it as a DAO. Next, the paper applies a DAO viability framework, centering on collective intelligence, digital democracy, and adaptation, to examine Bitcoin’s organizational and governance mechanisms. Findings suggest that Bitcoin instantiates key DAO principles by enabling open participation and employing decentralized decision-making through Bitcoin Improvement Proposals (BIPs), miner signaling, and user-activated soft forks. However, this governance carries potential risks, including reduced clarity on who truly “votes” due to the concentration of economic power among large stakeholders. The paper concludes by highlighting opportunities to refine Bitcoin’s deliberation process and reflecting on broader implications for DAO design, such as the absence of a legal entity. In doing so, it underscores Bitcoin’s continued relevance as an archetype for decentralized governance, offering important findings for future DAO implementations.
Stefano Balietti, Pietro Saggese, Stefan Kitzler, Bernhard Haslhofer
This chapter explores how Decentralized Autonomous Organizations (DAOs), a novel institutional form based on blockchain technology, challenge traditional centralized governance structures. DAOs govern projects ranging from finance to science and digital communities. They aim to redistribute decision- making power through programmable, transparent, and participatory mechanisms. This chapter outlines both the opportunities DAOs present, such as incentive alignment, rapid coordination, and censorship resistance, and the challenges they face, including token concentration, low participation, and the risk of de facto centralization. It further discusses the emerging intersection of DAOs and artificial intelligence, highlighting the potential for increased automation alongside the dangers of diminished human oversight and algorithmic opacity. Ultimately, we discuss under what circumstances DAOs can fulfill their democratic promise or risk replicating the very power asymmetries they seek to overcome.
The Bitcoin Network is a sophisticated accounting system that allows its underlying cryptocurrency to be trusted even in the absence of a reliable financial authority. Given its undeniable success, the technology, generally referred to as blockchain, has also been proposed as a means to improve legacy accounting systems. Accounting for real-world data, however, requires the intervention of a third party known as an Oracle, which, having not the same characteristics as a blockchain, could potentially reduce the expected integration benefit. Through a systematic review of the literature, this study aims to investigate whether the papers concerning blockchain integration in accounting consider and address the limitations posed by oracles. A broad overview of the limitations that emerged in the literature is provided and distinguished according to the specific accounting integration. Results support the view that although research on the subject counts numerous articles, actual studies considering oracle limitations are lacking. Interestingly, despite the scarce production of papers addressing oracles in various accounting sectors, reporting for ESG already shows interesting workarounds for oracle limitations, with permissioned chains envisioned as a valid support for the safe storage of sustainability data.
The increasing demand for sustainability and compliance with global carbon regulations has posed significant challenges for small and medium-sized enterprises (SMEs). This paper proposes a blockchain-based decentralized carbon credit trading platform tailored for SMEs in Taiwan, aiming to simplify the complex carbon trading process and lower market entry barriers. Drawing upon the Diffusion of Innovations theory and transaction cost economics, we illustrate how blockchain technology can reduce informational asymmetry and intermediary costs in carbon markets. By integrating Ethereum-based smart contracts, the platform automates transactions, enhances transparency, and reduces administrative burdens - addressing key obstacles such as technical complexity and market risks. A controlled experimental design was conducted to compare the proposed system with a conventional centralized carbon trading platform. Statistical analysis confirms its effectiveness in minimizing time and expenses while ensuring compliance with the Carbon Border Adjustment Mechanism (CBAM) and the Clean Competition Act (CCA). User satisfaction was measured using the Kano model, with the results identifying essential features and prioritizing future enhancements. This study contributes a more comprehensive solution for SMEs seeking to achieve carbon neutrality, underscoring the transformative potential of blockchain technology in global carbon markets.
Q&A websites rely on user-generated responses, with incentives such as reputation scores or monetary rewards often offered. While some users may find it intrinsically rewarding to assist others, studies indicate that payment can improve the quality and speed of answers. However, traditional payment processors impose minimum thresholds that many Q&A inquiries fall below. The introduction of Bitcoin enabled direct digital value transfer, yet frequent micropayments remain challenging. Recent advancements like the Lightning Network now allow frictionless micropayments by reducing costs and minimising reliance on intermediaries. This development fosters an "Internet of Value," where transferring even small amounts of money is as simple as sharing data. This study investigates integrating Lightning Network-based micropayment strategies into Q&A platforms, aiming to create a knowledge market free of minimum payment barriers. A survey was conducted to address the gap below the $2 payment level identified in prior research. Responses confirmed that incentives for asking and answering weaken as payments decrease. Findings reveal even minimal payments, such as £0.01, significantly encourage higher quality and effort in responses. The study recommends micropayment incentives for service-oriented applications, particularly Q&A platforms. By leveraging the Lightning Network to remove barriers, a more open marketplace can emerge, improving engagement and outcomes. Further research is needed to confirm if users follow through on reported intentions when spending funds.
Blockchain technology has emerged as a transformative tool for data management in a variety of industries, including fintech, research and healthcare. We have developed a workable blockchain based system that utilizes non fungible tokens NFTs to tokenize and prove ownership of the academic institutions credentials. This makes it easier to create provenance and ownership documentation for academic data and meta credentials. This system enables the secure sharing of academic information while maintaining control, offering incentives for collaboration, and granting users full transparency and control over data access. While the initial adoption of these systems is crucial for ongoing service usage, the exploration of the user acceptance behavioural model remains limited in the existing literature. In this paper, we build upon the Technology Acceptance Model TAM, incorporating additional elements to scrutinize the impact of perceived ease of use, perceived usability, and attitude towards the system on the intention to use a blockchain based academic data and meta credentials sharing system. The research, grounded in user evaluations of a prototype, employs a TAM validated questionnaire. Results indicate that individual constructs notably affect the intention to use the system, and their collective impact is statistically significant. Specifically, perceived ease of use is the sole factor with an insignificant influence on the intention to use. The paper underscores the dominant influence of attitude towards the system on perceived usefulness. It concludes with a discussion on the implications of these findings within the context of blockchain based academic data and meta credentials sharing, incorporating NFTs for ownership definition.