Electronic Health Records (EHR) is the main core of modern healthcare, but interoperability across different blockchain platforms is a key challenge. This work proposes a cross-chain middleware architecture, which facilitates secure and real-time synchronization of EHR data between Hyperledger Fabric (private blockchain) and Ethereum Sepolia Testnet (public blockchain). The framework integrates AES-256 encryption and Inter Planetary File System (IPFS) as decentralized storage to enhance patient privacy. To facilitate interoperability across the blockchains the research introduces a smart middleware layer. This layer autonomously monitors the blockchain events, processes encrypted CIDs, enforces real time cross chain consistency and smart contract-based access control. The experimental evaluation shows that proposed framework achieves low synchronization times (< 195 ms), low gas and latency costs, small encryption overhead (< 4–5 KB), robust file storage and retrieval through IPFS. Such positive evaluations with scalable and real-time deployment, sets the foundation of patient centric interoperable healthcare ecosystems.
In service firms, where value creation increasingly depends on human interaction and intangible assets, the development of soft skills and inclusive mindsets has become a strategic priority.Yet, traditional training programs rarely generate lasting behavioral change or make unconscious biases visible.This paper explores how Web3-enabled neuro-immersive technologies can transform learning processes within service organizations, turning technology-assisted experiences into ethically managed and measurable forms of knowledge creation.Drawing on ten real-world cases developed between 2021 and 2025 across consulting, banking, healthcare, and education, the study adopts a qualitative, comparative approach to examine how immersive simulations affect individuals' awareness, emotional regulation, and decision-making.
Open access
Virtual Reality Applications and Impacts
Human Resource Development and Performance Evaluation
Digital Asset Treasury (DAT) companies, public firms that hold large crypto reserves as a core strategy, deliver levered exposure to digital assets but face acute downside risk when equity premia over net asset value multiples (mNAV) compress in bear markets. This paper develops a survival framework that couples conservative treasury policy with an operating line that monetizes holdings independent of mark-to-market gains. Using Strategy (formerly MicroStrategy) as a case, we propose a "BTC-to-sats" payments rail that allocates a small, risk-capped liquidity sleeve of the treasury to Lightning Network channels, generating price-agnostic fee revenue (acquiring bps, routing, hedge/FX spread) while keeping settlement exposure near zero beta to BTC. We formalize a no-forced-sale condition and show how disclosed KPIs allow investors to test whether operating cash flows can bridge an 18 to 24-month bear without liquidations. The feasibility of the rail is supported by Strategy's Lightning initiative and empirical Lightning performance. Our model generalizes across DAT types and provides implementable disclosures that can sustain an mNAV premium through cycles.
Jimmy Jimmy, Kenny Rimba, Vincent Vincent, Ronsen Purba · 5 authors
E-voting systems are prone to challenges such as lack of transparency, risks of data manipulation, and dependence on centralized authorities, which can undermine trust in electoral processes. This research develops a blockchain-based e-voting system on the Polygon network, leveraging smart contracts and Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARK) to enhance security, transparency, and voter anonymity. The study employs an application development approach, implementing a structured methodology with initialization, registration, voting, and tallying phases. Smart contracts automate voter verification, vote casting, and result tabulation, while ZK-SNARK ensures voters can cast ballots anonymously without revealing their identities. The system’s transparency and immutability are tested using PolygonScan, demonstrating effective prevention of manipulations like double voting through cryptographic credentials (nullifier, commitment, and nullifier hash) and Merkle Tree structures. Results indicate that the system provides a secure, verifiable, and decentralized framework for elections. This implementation offers a robust foundation for future e-voting systems, promoting trust and integrity in digital voting processes.
A smart contract is a special type of transaction designed for the execution of automated logic on blockchains. Alas, smart contracts transactions are one of the major hindrances to blockchain throughput. Hence, improving the execution time of smart contracts is a prime challenge for Blockchains at large. To that end, concurrent execution of smart contract is an appealing direction, which has been adopted by several contemporary Blockchains like Solana, Aptos, Sui, Sei, and Monad. Executing smart contracts in parallel requires applying deterministic concurrency controls based on ensuring consistent ordering of all conflicting transactions in all miners/validators. Existing implementations rely on the Block's total ordering to resolve this requirement. Recently, it has been suggested that relying on minimal coloring of the conflict graph corresponding to the Block's transactions can provide a better performance potential, yet without any evaluation. In this paper, we compare between approaches to smart contracts parallelization. Our study’ finds that in many situations, indeed the coloring-based ordering leads to significantly better performance than the Block order preserving approach. However, this gain has its limits, and it is not always guaranteed. In particular, the results are largely dependent on the conflict ratio in the conflict graph and the type of application.
Blockchain Technology Applications and Security
Graph Theory and Algorithms
Physical Unclonable Functions (PUFs) and Hardware Security
A systemic "evidentiary deficit" now characterizes automated global civicsystems, undermining regulatory oversight, institutional accountability, and public trust in high-stakes domains. The increasing opacity of high-speed, algorithmically-driven decisions in finance, public health, and environmental governance creates un-auditable risks. This report posits Ternary Logic (TL) as a neutral, non-ideological infrastructure framework designed to remediate this deficit. TL extends traditional binary logic by introducing a formal, third logical state: 0 (Epistemic Hold), distinct from 1 (Proceed) and -1 (Halt). This 0 state functions as a mandatory, auditable "computational hesitation" triggered by predefined uncertainty or risk thresholds. By instrumenting this pause, TL transforms deliberation and uncertainty from an operational failure into a cryptographically verifiable evidentiary asset. This report details the TL architecture through its Eight Pillars, which provide an integrated "accountability stack" mapping institutional policy to cryptographic proof. It describes the tri-cameral governance model—Technical Council, Stewardship Custodians, and Smart Contract Safeguard—architected for long-term resilience and prevention of institutional capture. Furthermore, it details the technical architecture, including a dual-lane, low-latency (<300ms) design, a hybrid-shield (public/private) ledger system, and a novel cryptographic stack (combining Ephemeral Key Rotation, Zero-Knowledge Proofs, and Cryptographic Erasure) that simultaneously satisfies regulatory demands for auditability, legal requirements for privacy (e.g., GDPR), and commercial protection of trade secrets. This framework provides a sovereign-grade blueprint for establishing provable accountability in systems governed by institutions such as the Bank for International Settlements (BIS), U.S. Securities and Exchange Commission (SEC), U.S. Food and Drug Administration (FDA), and World Health Organization (WHO).
Decentralized Finance (DeFi) has been identified as an emerging technology for a transformative force in financial intermediation, introducing a trustless, programmable, and inclusive financial ecosystem. This paper identifies, show, and explores the integration of DeFi into traditional finance, focusing on how DeFi platforms are redefining financial intermediation and incorporates not only the financial perspective but also an IT-systems perspective, detailing architectures, data structures, and integration frameworks that enable collaboration between DeFi platforms and traditional financial institutions. The research identifies the limitations of current financial systems, evaluates the technical and regulatory challenges of integration, and highlights how DeFi innovations can increase efficiency, transparency, and inclusivity. Key components of this integration, such as smart contracts, decentralized lending, and interoperable frameworks, are analyzed along with their potential to overcome limitations in traditional finance. The paper concludes with recommendations for a mutually beneficial model combining DeFi and traditional finance to create a robust, secure, and inclusive global financial ecosystem.
Blockchain, artificial intelligence (AI), and the Internet of Things (IoT) are becoming more connected, creating new opportunities for building smarter, more secure, and automated systems. One area where this combination can be really helpful is environmental monitoring. In this paper, we present a smart contract system that uses a trained machine learning model to predict air quality based on real-time data and runs on the IOTA blockchain. The goal is to make smart contracts more intelligent by enabling them to make predictions and send alerts without needing a centralized server. The model was trained off-chain and then integrated into a smart contract deployed on the IOTA Wasp chain. The system was evaluated using standard regression metrics like the R2score, MAE, and MSE. The results show that the model fits the data well and the whole system runs efficiently, making it suitable for real-time use in IoT environments.
As global energy systems pivot toward net-zero, Carbon Capture, Utilization and Storage (CCUS) has emerged as a foundational tool to mitigate industrial emissions (Abu Zahra et al. 2007; Boot-Handford et al. 2014; IEA 2020). However, the effectiveness, financeability and scalability of CCUS projects are severely hindered by traditional Monitoring, Reporting and Verification (MRV) workflows (IEAGHG 2017; U.S. DOE 2018–2023; Verra 2023). These legacy processes are typified by siloed data collection, infrequent audits, manual record reconciliation and a lack of trust between stakeholders. This results in substantial verification delays, compliance risks and a sluggish, opaque carbon market where the link between physical decarbonization and financial value is weak (ISO 2018; Dutta et al. 2021; Hartmann et al. 2023). Although real-time IoT sensing, AI-powered analytics and blockchain-based recordkeeping have each been explored independently (Garcia Freites and Jones 2021; Wang et al. 2019; Hartmann et al. 2023), no prior framework has fused these into a seamless, robust and self-governing digital pipeline for CCUS MRV and carbon-credit management at industrial scale (Hütten et al. 2022). This paper introduces a novel architecture that: Deploys dense, high-fidelity IoT sensor networks and edge-compute nodes across the full CCUS value chain (Abu Zahra et al. 2007; IEAGHG 2017; Dutta et al. 2021);Leverages advanced, multi-tiered AI/ML for operational intelligence, predictive reliability and financial optimization (Breiman 2001; Hochreiter and Schmidhuber 1997; Chen et al. 2019; Bender et al. 2021);Employs a hybrid off-chain/on-chain data model for performance, privacy and regulatory-grade auditability (Garcia Freites and Jones 2021; Boneh and Shoup 2020; NIST 2024);Harnesses Layer-2 blockchain with decentralized oracles and smart contracts to automate MRV validation, progressive credit minting, escrow and transparent marketplace integration (Buterin et al. 2014; zkSync 2024; Bai et al. 2021; KlimaDAO 2024).
Amidst a global surge in urban development foregrounding smart, sustainable, and now pandemic-proof design, new forms of longstanding hazard and health discourse are being deployed to justify dispossession, particularly in self-built districts. Looking at a case in Tirana, Albania, we examine how this discourse is being contemporized and paired with diverse digital media as it overlaps within a single project – the Tirana Riverside Project. As expressions of authoritative knowledge, architectural visualizations, social media posts, state-backed news broadcasts, and international design blogs work to validate this underlying ideology driving demolition. Such imagery and discourse, we contend, thus need to be read as artifacts of power that entrench government authority while substantiating mass dispossession. We argue that these processes are not only about the real estate profits demolition-based urban renewal generates but also – in Albania’s flawed democratic context – their ability to support the ruling elite. Using content analysis, we identify four hazard and health imaginaries overlapping within the project: 1) pandemic-proof design; 2) design for seismic emergencies; 3) zero-emission sustainable design; and 4) smart city technologies. We show how these imaginaries join longer traditions of normative discourse around hazard and health in urban renewal yet scrutinize their distinct contemporized and localized expressions.
In decentralized governance, quadratic voting (QV)—where the cost of acquiring voting power is convex—optimally aggregates voter preferences, outperforming simpler linear voting (LV) mechanisms when voters have complete information. But what if they do not? We show that uncertainty not only breaks QV optimality but can also cause it to underperform LV. Intuitively, this is because cost convexity can disincentivize better-informed voters from adequately conveying their private information. The optimal mechanism varies with the distribution of stakes and information among voters, implying that QV’s known advantages in preference aggregation do not readily extend to common-value information aggregation settings. This paper was accepted by Will Cong for the Special Issue on the Digital Finance. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2024.08469 .
This paper investigates the relationship between cryptocurrencies and other financial assets, with a particular focus on the dynamics of information flow between developed and emerging markets. To achieve this objective, the study applies a combined methodology of spillover index analysis and network topology based on graph theory. The analysis covers key cryptocurrencies (Bitcoin and Ethereum), stocks, and conventional currencies over the period November 2017 to September 2022, and distinguishes between short-term and long-run dynamics. The empirical findings show that in the short run, Bitcoin and Ethereum predominantly act as net shock transmitters, whereas in the long run, stocks and conventional currencies, together with Bitcoin and Ethereum, become the principal conveyors of spillover shocks. The network topology analysis corroborates these results by revealing the centrality of these assets in the spillover structure. By integrating spillover and network approaches across different markets and time horizons, this study contributes to the literature by providing a more nuanced understanding of how cryptocurrencies interact with traditional financial assets under varying market conditions.
Khoi Minh Nguyen, Lý Thị Trần, Binh-Hau Nguyen, Minh T. Nguyen · 7 authors
Blockchain functions as a “distributed ledger network,” ensuring immutability, transparency, and non-retroactivity of data, making it a key technology for sustainable development. This study explores how blockchain-enabled traceability systems influence consumer perceptions of environmental transparency, trust in technology, and purchase intentions for sustainable food in Vietnam. Using a digital survey of 450 participants and SmartPLS 4.0 with PLS-SEM analysis, findings reveal that both blockchain reviews and traceability systems significantly improve perceptions of transparency (β = 0.292; β = 0.364, p < 0.001) and technological trust (β = 0.268; β = 0.348, p < 0.001). The research bridges the gap between transparency perceptions and purchase behavior in sustainable development and foodservice strategy. It is one of the first studies to examine the combined impact of blockchain reviews and traceability. The article adds to existing literature by expanding understanding of blockchain’s effect, supporting businesses in aligning with the UN’s Sustainable Development Goals.
Since the advent of smart contracts, security vulnerabilities have remained a persistent challenge, compromsing both the reliability of contract execution and the overall stability of the virtual currency market. Consequently... | Find, read and cite all the research you need on Tech Science Press
Academic departments frequently exchange exam materials, assignment submissions, grade reports, attendance logs and durable student records. Conventional Learning Management Systems (LMS) centralize control and provide limited, non-portable audit trails which hinders cross-department collaboration and independent verification. This paper defines Electronic Student Records as encrypted, content-addressed documents anchored on Ethereum while data remain off chain and presents a practical model with a comparative analysis for department-level sharing. The model uses Sign-In with Ethereum (SIWE) for authentication, verifiable credentials for roles and consent, a minimal on-chain registry that records Keccak-256 digests, content identifiers, and timestamps with a policy reference and InterPlanetary File System (IPFS) storage with institutional pinning and multiple gateways. Access control adopts proxy re-encryption, enforced with time windows and periodic key rotation. Updates always re-encrypt and re-upload so each version receives a new Content Identifier (CID) and digest. A compact evaluation contrasts Ethereum Layer 1 with Zero-Knowledge (ZK) rollups for registry events, single versus multi-gateway IPFS with two or more replicas and Proxy Re-Encryption (PRE) versus Attribute-Based Encryption (ABE) as alternative keying strategies. The system reports metrics include chain cost, one-gateway (p50) and two-gateway (p95) read latency, availability under replication and revocation time under the re-upload policy. Findings indicate ZK rollups suit routine registry events, Layer1 suits high-value anchors, multi-gateway pinning improves tail latency and success rate and time-bounded PRE enables low-overhead revocation. The model offers a feasible path to privacy-preserving, auditable Electronic Student Records (ESRs) that integrate with existing LMS.
Rana Alaa, Darío González-Ferreiro, Carlos Beis-Penedo, Manuel Fernández‐Veiga · 6 authors
Split learning is an approach to collaborative learning in which a deep neural network is divided into two parts: client-side and server-side at a cut layer. The client side executes its model using its raw input data and sends the intermediate activation to the server side. This configuration architecture is very useful for enabling collaborative training when data or resources are separated between devices. However, split learning lacks the ability to verify the correctness and honesty of the computations that are performed and exchanged between the parties. To this purpose, this paper proposes a verifiable split learning framework that integrates a zk-SNARK proof to ensure correctness and verifiability. The zk-SNARK proof and verification are generated for both sides in forward propagation and backward propagation on the server side, guaranteeing verifiability on both sides. The verifiable split learning architecture is compared to a blockchain-enabled system for the same deep learning network, one that records updates but without generating the zero-knowledge proof. From the comparison, it can be deduced that applying the zk-SNARK test achieves verifiability and correctness, while blockchains are lightweight but unverifiable.
This study is mainly indicated towards the emergence of non-fungible tokens (NFTs) as the new digital asset for investment. A comparative analysis is made between NFTs and the fungible tokens (cryptocurrency). It is observed that NFTs are highly volatile in nature, yet safer way to invest as it is secured by code, which cannot be easily hacked by scammers During the COVID-19 Pandemic, digital investments have become a trend among the crypto investors. It was a great alternative for the fungible investors. In today’s technological aided society, digital investments have become very common and is investors find it more convenient. Investment in the NFTs and FTs is more of a status symbol for the higher class of society. The future of NFTs is very diverse and endless. The scope of NFTs is very much diverse in the gaming sector and also in the real estate sector. The study stated that the major difference between both the assets is the uniqueness of each NFTs, whereas all the FTs are similar in nature. The digital asset is defined as something which holds value, has ownership and is discoverable on the digital platform. Lastly, the study discusses the various digital assets which include the stablecoins, utility tokens and security tokens.
M.Z. Haider, M.U. Ghouri, Tayyaba Noreen, M. Salman
Blockchain systems face persistent challenges of scalability, latency, and energy inefficiency. Existing consensus protocols such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) either consume excessive resources or risk centralization. This paper proposes \textit{Proof-of-Spiking-Neurons (PoSN)}, a neuromorphic consensus protocol inspired by spiking neural networks. PoSN encodes transactions as spike trains, elects leaders through competitive firing dynamics, and finalizes blocks via neural synchronization, enabling parallel and event-driven consensus with minimal energy overhead. A hybrid system architecture is implemented on neuromorphic platforms, supported by simulation frameworks such as Nengo and PyNN. Experimental results show significant gains in energy efficiency, throughput, and convergence compared to PoB and PoR. PoSN establishes a foundation for sustainable, adaptive blockchains suitable for IoT, edge, and large-scale distributed systems.
The contemporary Internet, a cornerstone of modern society, is characterized by a high degree of centralization. This centralization concentrates data and power within a few large corporations, raising significant concerns regarding data privacy, censorship, single points of failure, and monopolistic control. The "Decentralized Internet," often associated with the Web3 paradigm, proposes a fundamental shift toward a more open, trustless, and user-centric network. This paper presents a comprehensive survey of the decentralized Internet, beginning with an exploration of its core principles—trustlessness, censorship resistance, and user-controlled data. We then examine the key enabling technologies that underpin the decentralized Internet, including distributed ledger technologies (DLT), peer-to-peer (P2P) data protocols such as the InterPlanetary File System (IPFS), and smart contracts. Finally, we discuss the significant open challenges and research questions that must be addressed, including scalability, usability, governance, and regulatory uncertainty. This paper aims to provide a structured overview for researchers, developers, and policymakers interested in the future of Internet architecture. Index Terms—Decentralized Internet, Web3, Blockchain, Peer-to-Peer (P2P), IPFS, Distributed Ledger Technology (DLT), Smart Contracts, Decentralized Applications (dApps), Scalability, Governance.