Muhammad Ali Hassan Ahmad, Muhammad Hashim Ali, Muhammad Ali Amer, Muhammad Naiman Jalil · 6 authors
A blockchain is a decentralized, secure ledger system that enables transparent and immutable record-keeping, essential for trust and security in digital transactions. Smart contracts are self-executing agreements encoded on a blockchain, enabling different parties to fulfill the terms of the agreement automatically. These contracts trigger corresponding actions when conditions are met, ensuring decentralized and transparent transactions. Writing reliable smart contracts is challenging due to the lack of standardization. To find security vulnerabilities, tools based on various approaches, including symbolic execution, are used. However, these tools often report a large number of false positives, raising concerns about their reliability. The time and effort spent investigating false positives diverts resources from addressing actual vulnerabilities. Therefore, such tools must also be evaluated according to the rate of false positives they exhibit. More importantly, the algorithms and heuristics used by the tools must be enhanced to distinguish between true vulnerabilities and false alarms. In this paper, we first demonstrate the prevalence of false positives in vulnerability reports generated by Mythril, a symbolic execution-based analysis tool for Ethereum smart contracts. We analyze the root causes of these inaccuracies and devise a rule-based approach based on the gained insight to reduce false positives. We implement our rules for the most impactful vulnerabilities in Mythril and assess the effectiveness of our approach. Our results show a significant reduction in false positives without compromising the detection of true vulnerabilities, thus enhancing the tool's reliability.
Stablecoins have rapidly emerged as an important class of digital assets and a component of the digital financial ecosystem. Despite their growing importance, the statistical properties of stablecoin transaction activity remain largely unexplored. To the best of our knowledge, this is the first study to investigate scaling behavior in stablecoin transaction data, focusing on USDT and USDC. We analyze approximately 370 million USDT and USDC transactions recorded on the Ethereum blockchain across six periods spanning June 2024 to February 2026. Based on interactions between Externally Owned Accounts (EOAs) and Smart Contracts (SCs), we classify transactions into four categories: EOA-EOA, EOA-SC, SC-EOA, and SC-SC. Using maximum-likelihood estimation of power-law exponents, we find that transaction value distributions exhibit heavy-tailed scaling for both stablecoins across all periods and interaction categories. We identify two distinct scaling regimes: EOA-involved categories cluster around 1.45-1.60, whereas SC-SC transactions exhibit higher exponents of approximately 1.72-1.73. Sensitivity analysis confirms that this separation is robust across periods, stablecoins, and fitting sample sizes. Counterfactual analysis shows that changes in category weights alone cannot explain the observed variation in the overall exponent. Across different sample sizes, the counterfactual path accounts for only about 10%-35% of the total temporal range observed in the actual data. Overall, our results indicate two broadly differentiated scaling regimes in the tail of stablecoin transaction values. Power-law tail behavior is observed throughout stablecoin transaction activity, but the exponent depends on whether transactions are driven by EOAs or SCs. These findings provide a basis for further research on scaling behavior and transaction heterogeneity in blockchain-based financial systems.
Novan Ilham Ramadhan, Rizky Parlika, Ardhon Rakhmadi
Electronic voting (e-voting) systems continue to face challenges related to transparency, result validation, and duplicate voting prevention. Blockchain technology offers characteristics such as decentralization, transparency, and immutability that can support more auditable voting processes. This study presents a prototype implementation of a blockchain-based e-voting system using Ethereum smart contracts to support transparent vote recording, public auditability, and wallet-level double voting prevention. The system was implemented using Solidity-based smart contracts deployed on the Ethereum Sepolia Testnet and integrated with MetaMask for transaction authentication. Smart contracts manage election creation, candidate registration, voter registration, vote recording, duplicate vote prevention, and voting result finalization. An audit trail mechanism was implemented to allow voting activities and transaction records to be publicly verified through the Etherscan blockchain explorer. All predefined functional testing scenarios were executed successfully. The evaluation results indicate an average gas usage of 75,109 gas, an estimated transaction cost of 0.000113 ETH, and a transaction latency of approximately 4–5 seconds. The implemented wallet validation mechanism and hasVoted mapping effectively prevent duplicate voting attempts associated with the same wallet address. However, the proposed system represents a prototype-level evaluation conducted on the Ethereum Sepolia Testnet and does not provide voter identity verification, ballot anonymity, or real-world election readiness. The findings demonstrate the feasibility of Ethereum smart contracts for transparent auditability and wallet-level double voting prevention in blockchain-based voting environments.
Tapasi Bhattacharjee, Amalendu Singha Mahapatra, Dipika Pramanik
Educational crowdfunding has emerged as a promising approach to provide educational resources to underprivileged communities. Conventional systems often suffer from a lack of transparency, weak accountability, inefficient allocation of funds, and inadequate traceability of resource use. To address these issues, the present study proposes an intelligent and efficient educational supply chain management system, “EduDonateBlock.” It uses a blockchain-based crowdfunding framework to ensure transparency, accountability, and efficiency. Decentralization, immutability, and verifiable transactions are supported in educational campaigns. The entire workflow is decomposed into modular smart contracts. These are the identity and access contract (IAC), campaign and donation contract (CDC), verification and allocation contract (VAC), and supply chain and tracking contract (SCTC). These contracts are designed to ensure traceability, accountability, and efficient resource allocation among donors, educational institutions, and administrators. The mathematical framework of EduDonateBlock determines the optimal level of blockchain transparency. This minimizes the Total Expected Cost (TEC) of smart-contract operations. Numerical analysis identifies an optimal transparency level of 87.16% on-chain integration. This finding underscores the economic trade-off between transaction costs and the benefits of automation, operational efficiency, and reduced fraud risk. The proposed framework achieves a campaign success probability of 89.45% and an institutional payoff of Rs. 11,335.99. Furthermore, executing smart contracts requires 0.0044 ETH, and the average latency remains at 6.25 s. The simulation results show that EduDonateBlock offers a more efficient, reliable, and transparent solution for decentralized educational crowdfunding and socially impactful digital supply chains.
The expansion of blockchain technology and the evolution of digital platforms have led to the emergence of new concepts in contractual relations, of which "smart contracts" are among the most significant. These contracts are designed as blockchain-based computer programs that execute the terms of the parties' agreement in the form of digital codes and enable the automatic performance of obligations without the need for traditional intermediaries. Such features have increased the speed, transparency, and efficiency of transactions. However, the introduction of this technology into the field of contract law has raised fundamental questions regarding the legal nature, validity, and enforcement of such contracts in various legal systems, particularly those based on classical traditions. The aim of this research is to elucidate the legal nature of smart contracts and analyze the challenges of their enforcement in the Iranian legal system. The research method is descriptive-analytical, and data have been collected through library studies and the examination of domestic and international legal sources. Additionally, with a comparative approach, some legislative experiences of other countries in this field have been examined. The findings indicate that, despite technical differences, smart contracts can be analyzed within the framework of general contract rules. The principle of party autonomy and Article 10 of the Civil Code provide the capacity to accept this type of contract, and the Electronic Commerce Law, by recognizing data messages and electronic signatures, has established a basis for the validity of digital transactions. However, challenges such as ascertaining the true intent of the parties, determining liability for technical errors, and the conflict between the immutability feature of blockchain and institutions such as rescission and mutual rescission persist. Accordingly, the formulation of supplementary regulations, the development of legal infrastructure, and the enhancement of specialized knowledge appear essential for the safe and effective utilization of this technology.
Abdul Adlim, Babun Suharto, Wildan Khisbullah Suhma, Kholida Ulfi Mubaroka
The rapid development of crypto assets has challenged the classical concept of mal (property) in Islamic jurisprudence because digital assets do not possess tangible physical characteristics traditionally associated with lawful ownership. This study aims to reconstruct the paradigm of mal within contemporary fiqh by examining the legal status of crypto assets through the framework of maqasid al-shari'ah, particularly hifz al-mal, while evaluating the role of smart contracts in reducing contractual uncertainty (gharar). This study employed a qualitative normative legal approach based on literature analysis of classical fiqh, usul al-fiqh, contemporary Islamic legal scholarship, institutional fatwas, and financial regulations. The findings demonstrate that the concept of mal has evolved from a material-based understanding toward a value-oriented paradigm that emphasizes recognized benefit, scarcity, and lawful ownership. Under these criteria, crypto assets may be recognized as mal when supported by legitimate ownership, transparent governance, and productive economic purposes. Smart contracts contribute to minimizing contractual and operational gharar through automated execution and transaction transparency, although they cannot eliminate risks arising from market volatility. This study proposes a reconstructed paradigm of mal that provides a more contextual analytical framework for assessing the legality of digital assets within contemporary Islamic law.
This study examines the current state of digital asset auditing and proposes a clearer future vision through a systematic review of relevant literature and prior studies. It highlights the fundamental differences between digital and traditional assets, explains the classification of digital assets and their close association with blockchain technology, and analyzes the existing accounting and auditing frameworks considering international standards and provides a brief overview of the status of Egyptian legislation. The study also discusses the evolving role of auditors and the main stages of the audit process in the digital environment. The findings indicate that rapid digital transformation requires the development of advanced auditing standards and methodologies, and that the adoption of data analytics, smart contracts, and continuous auditing, together with enhancing auditors’ technical and professional competencies, contributes to improving audit quality, transparency, and risk management related to digital assets.
Open access
Security, Politics, and Digital Transformation
Financial Reporting and XBRL
Innovations and Analysis in Business and Education
Online voting platforms that rely on classical cryptography and centralized trust anchors face escalating challenges as the demand for secure and transparent digital elections grows. Such systems remain exposed to quantum-era threats, insider manipulation, and delayed audit mechanisms, which together can undermine public confidence and electoral legitimacy. To counter these risks, a quantum-resistant, multi-layer blockchain architecture has been developed to enable remote voting with continuous verifiability and resilience. This architecture resolves key weaknesses through five integrated layers. Quantum-Resistant Distributed Ledger Initialization (QR-DLI) embeds lattice-based cryptography, specifically Kyber and Dilithium variants, directly within the genesis block, ensuring the ledger is tamper-proof from inception and immune to quantum brute-force attacks. The Self-Adaptive Smart Contract Governance Engine (SASCG) introduces dynamic, participation-aware rule adjustments, allowing principled governance without manual overrides and ensuring that voting periods and eligibility rules adapt securely in real time. Homomorphic Vote Encryption with Multi-Authority Shard Key Distribution (HVE-MASKD) guarantees ballot confidentiality and authenticity by combining fully homomorphic encryption with distributed key shares, eliminating single points of trust. The Zero-Knowledge Proof–Based Real-Time Audit Layer (ZKP-RTAL) continuously validates ballot integrity while concealing vote content, creating a public and immutable audit trail. Finally, the Federated Performance & Threat Intelligence Optimizer (FPTIO) aggregates live telemetry and historical attack data to proactively tune consensus parameters and predict potential intrusions without interrupting the election process. Collectively, these layers achieve sub-second cryptographic operations, transaction throughput exceeding 1,500 TPS, over 99 % fraud detection accuracy, and strong scalability. The model provides a future-ready, auditable replacement for current e Voting infrastructures, strengthening digital democracy through post-quantum security, adaptive governance, and intelligent, continuous optimizations.
MARBIYAT TAHIR GIDADO, BASHIRU ABDULGANIYU, MOHAMMED NASIR MUSA, Umaru Umaru
The increasing digitalization of smart grids has significantly improved the efficiency, reliability, and sustainability of modern power systems. However, the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and cloud computing, has introduced new cybersecurity vulnerabilities that threaten critical energy infrastructure. This study presents a blockchain-enabled privacy-preserving Artificial intelligence framework designed to enhance cybersecurity in smart grid environments, with a particular focus on Northeast Nigeria as a case study. The framework integrates blockchain technology, federated learning, differential privacy, edge computing, and artificial intelligence (AI)-driven intrusion detection into a unified architecture to provide secure, intelligent, and privacy-aware protection for smart grid systems. The proposed framework was developed using the design science research methodology and evaluated through simulation and comparative performance analysis. The framework achieved excellent detection performance with an accuracy of 96.8%, precision of 95.9%, recall of 96.4%, and F1-score of 96.1%, significantly outperforming conventional centralized AI and blockchain-only approaches. The integration of federated learning and differential privacy effectively protected consumer information with a privacy leakage rate of only 2.7% while maintaining high model utility of 94.8%. The blockchain performance evaluation showed a transaction latency of 184.6 Ms, a throughput of 421.3 transactions per second, and efficient smart contract execution. The suitability of the framework for practical deployment with moderate resource requirements by computational assessment. The findings demonstrate that combining blockchain, privacy-preserving learning, and AI provides a comprehensive, scalable, and resilient cybersecurity solution for SGIs. This study contributes to the growing body of knowledge on smart grid cybersecurity and offers practical insights for utility providers, researchers, and policymakers seeking to strengthen the security and resilience of emerging smart grid systems, particularly in developing regions with infrastructural challenges.
This study maps the development, collaboration patterns, citation structure, and thematic evolution of research on blockchain technology in the waqf sector. A bibliometric analysis of 417 Scopus-indexed publications published from 2006 to 12 July 2024 was performed using Bibliometrix in RStudio and VOSviewer. The analysis covered publication trends, influential sources and contributors, country productivity, citation impact, collaboration networks, and keyword co-occurrence. The results show increasing scholarly attention to the intersection of blockchain, Islamic finance, fintech, and waqf management. Malaysia and Indonesia emerged as the most productive and most cited countries, while an international co-authorship rate of 29.74% indicated moderate cross-border collaboration. Keyword analysis revealed that the field is anchored in Islamic finance, fintech, blockchain, and waqf, with growing attention to cash waqf, crowdfunding, financial inclusion, digital transformation, smart contracts, cybersecurity, and technology adoption. However, these patterns demonstrate scholarly attention and thematic associations rather than empirical proof of blockchain’s operational benefits in waqf institutions. This study identifies priority gaps in empirical implementation, Shariah governance, stakeholder adoption, technical feasibility, and socioeconomic impact evaluation of blockchain-enabled waqf systems.
Blockchain interoperability remains a major challenge because heterogeneous blockchain networks cannot securely and efficiently exchange cross-chain data and transactions. Existing interoperability solutions often rely on central relays or trusted intermediaries, creating security vulnerabilities, limited fault tolerance, and a single point of failure. To address these limitations, this paper proposes VeriMesh, a decentralised mesh-based interoperability framework that combines trust-adaptive routing, multi-path relay verification, and Zero-Knowledge Proof (ZKP)-based validation for secure cross-chain communication. VeriMesh models relay nodes as a trust-weighted graph in which routing decisions dynamically adapt based on node behaviour and delivery reliability. Multi-path routing improves resilience against adversarial relay nodes, while transport-layer ZKP verification enables privacy-preserving validation without exposing sensitive information. The framework was implemented using Python relay nodes, Solidity smart contracts, and an Ethereum (Ganache) environment. Experimental evaluation using structured event-driven workloads demonstrated stable latency below 34 ms and delivery success rates above 85% up to 40% malicious node presence. Comparative evaluation against single-path and random multi-path relay baselines showed improved fault tolerance and routing reliability. The results demonstrate favourable scalability and robustness within the evaluated network range ( N = 10–30), while larger-scale evaluation remains future work. All experiments were conducted in a controlled local Ganache blockchain environment rather than on a public Ethereum testnet or mainnet, so the reported latency, gas, and delivery figures characterise protocol-layer behaviour under controlled conditions and should not yet be interpreted as representative of performance under public-network conditions such as real gas markets, block propagation delays, or network congestion.
The increasing demand for trustworthy and privacy-preserving credit reporting systems has exposed the limitations of both centralized and existing blockchain-based solutions, including scalability bottlenecks, weak privacy protection, and insufficient incentive mechanisms. To address these challenges, we propose LightCred, a novel consortium blockchain-based personal credit management framework that integrates lightweight nodes, Merkle proofs, multi-role smart contracts, and privacy-preserving cryptographic techniques. LightCred features a five-layer architecture that efficiently collects, verifies, stores, and serves credit data while ensuring data integrity, confidentiality, and regulatory compliance. Specifically, it (i) employs a low-cost and traceable data reduction mechanism through lightweight nodes and Merkle proofs to minimize storage and improve verifiability; (ii) introduces a multi-role smart contract model that enforces dynamic access control and fair incentive distribution based on participant reputations; and (iii) integrates zero-knowledge proofs and homomorphic encryption to support privacy-preserving credit scoring and querying. Experimental results demonstrate that LightCred achieves superior performance compared to five baseline methods, delivering up to 5% higher throughput, 3–5% lower privacy leakage, and 10–15% reduced storage costs, while maintaining competitive latency and auditability. These findings validate LightCred as a robust, scalable, and privacy-aware credit management solution, offering a viable alternative for modern credit reporting systems.
This study aims to analyze the alignment of Indonesia’s regulations on electronic contracts with the UNCITRAL Model Law on Electronic Commerce in order to promote reforms to contract law that are more adaptable to digital developments. The digital transformation has made electronic contracts the primary means of conducting cross-border civil transactions. However, Indonesia’s regulations under the ITE Law are considered to be limited to business transactions and do not yet accommodate other civil relationships. The method used is normative legal research employing legislative, conceptual, and comparative approaches. This study analyzes the UNCITRAL Model Law on Electronic Commerce as an international legal instrument serving as a guideline for harmonization. In addition, this study also examines the ITE Law and its implementing regulations as sectoral regulations, as well as the Indonesian Civil Code as the general legal framework that should ideally serve as the overarching regulatory framework for electronic contracts. The novelty of this study lies in its analysis of the relationship between the principle of freedom of contract in the Indonesian Civil Code and UNCITRAL’s international standards, a topic rarely discussed in the national literature. The results of the study indicate that the UNCITRAL Model Law provides a flexible and universal framework consistent with the principle of freedom of contract; however, its application in Indonesia remains limited by the ITE Law’s focus solely on electronic transactions. The conclusion of this study is that harmonization of Indonesian contract law with international principles is necessary so that the regulation of electronic contracts can apply across sectors, not limited to business, and meet the dynamics of legal globalization.
Abstract - The rise of digital technology has led to an increase in cybercrime. This has made the management of digital forensic evidence more complicated. Traditional evidence management systems utilize manual methods and centralized databases. Methods like these are vulnerable to data tampering, unauthorized access, and human error. These issues threaten the integrity of the evidence and the chain of custody during the investigation process. In this paper, we introduce a system that utilizes blockchain technology, smart contracts, and a decentralized system for the tracking of forensic evidence. Security and transparency will be guaranteed. In our system, evidence records are stored as ERC-721 Non-Fungible Tokens. A private Ethereum blockchain was developed using Ganache and combined with wallet-based authentication and Role-Based Access Control to ensure that only authorized personnel have the ability to view and manage evidence. Smart contracts facilitate the registration, verification, transfer, and auditing of evidence, thus, considerably reducing the manual work and greatly increasing the trustworthiness of the system. We proposed a hybrid system of storage whereby evidence and its forensic files are stored off chain, and the evidence metadata and its forensic files are stored on chain. This paper presents the design and architecture of the system,implementation and evaluation are in progress.Our system will be a trusted, efficient, and effective system of evidence management.
Adam Zahir, Vincent Lefebvre, Mark Angoustures, Milan Groshev · 5 authors
Multi-agent systems (MAS) comprise autonomous software agents that collaborate to perform complex tasks in critical cyber-physical domains, including multi-robot coordination and the Industrial Internet of Things (IIoT). In such distributed environments, a compromised agent may execute modified software while appearing trustworthy, causing other agents to act on false information and corrupting the mission. Agents must therefore establish and maintain mutual trust throughout operation. Remote attestation (RA) is a well-established technique for this purpose, enabling a remote verifier to assess the integrity of a potentially compromised prover device. However, conventional RA approaches face significant limitations in MAS: integrity guarantees are restricted to boot or application-load time, designs rely on centralized trusted verifiers or security hardware, and attestation records lack transparency and auditability. To address these limitations, this paper presents D-MUTRA, a blockchain-based framework that introduces a mutual RA protocol in which agents measure their runtime integrity while verifying that of their peers, acting as both prover and verifier. The framework operates entirely in software and relies on two components: a Security-as-a-Service that instruments agents with lightweight measurement and verification capabilities, and a smart contract that coordinates the attestation protocol in a decentralized and transparent manner. We implement a proof-of-concept on a private Ethereum blockchain using Hyperledger Besu and evaluate it in a swarm robotics scenario built with Robot Operating System (ROS) and the Gazebo simulator. Results show that D-MUTRA enables agents to continuously attest one another, detects malicious software modifications, and scales to large deployments with negligible overhead on protected applications.
As the blockchain and decentralized finance (DeFi) ecosystems continue to expand and mature, rug pull scams involving meme coins are occurring with increasing frequency, posing a threat to the security of investors' assets and the healthy development of the industry. Rug Pull scams are characterized by extremely low deployment costs, covert execution, rapid fund transfers, and high detection difficulty. Traditional manual reviews or fixed rules struggle to meet real-time early warning requirements, and existing detection methods generally suffer from issues such as a single feature dimension, inadequate handling of class imbalance, and weak model generalization and interpretability. To address these shortcomings, this paper focuses on the detection of Ethereum-based rug pull scams. First, we clarify their definitions, types, and harm mechanisms, and construct a multi-dimensional feature system based on dimensions such as malicious smart contract design, on-chain transaction anomalies, liquidity manipulation, and social media disclosures. Next, using the "Second Uncle Coin"(token symbol: BOBU) case as an example, we reconstruct the attack process and derive quantitative detection metrics. Subsequently, a risk detection model based on a Multi-Layer Perceptron (MLP) is designed. We employ a combined strategy of SMOTE oversampling and Focal Loss to address the issue of sample imbalance, dynamically search for optimal thresholds to balance precision and recall, and incorporate gradient pruning and early stopping to enhance training stability. Experiments show that the model achieves an accuracy of 0.927, an F1 score of 0.787, and an AUC-ROC of 0.952 on the test set, outperforming traditional methods. Finally, a visualizable web-based detection system is developed using the Flask framework, enabling batch risk assessment, high-risk ranking display, and result export functions.
Autonomous AI agents, increasingly empowered by large language models, are becoming important components of human-machine systems for high-stakes decision support in digital twin ecosystems. However, existing multi-agent systems often lack robust verification for identity, capability, and policy compliance, especially in decentralized environments spanning multiple institutions. This paper proposes a neuro-symbolic decentralized governance framework for verifiable agents in collaborative digital twin environments. By representing agents through multi-layer semantic profiles, the framework bridges probabilistic neural reasoning with deterministic institutional governance, thereby supporting trustworthy human-AI collaboration and meaningful human oversight. Capabilities are grounded in formal domain ontologies to enable machine-interpretable, policy-aware, and context-sensitive participation. These credentials, issued by organizational authorities, are validated via blockchain-based smart contracts, ensuring auditable participation without exposing sensitive data. We demonstrate the framework using a decision-support prototype with clinic, digital twin, and wearable provider agents effectively prevents unauthorized interaction and enforces institutional policies with manageable overhead. Our findings suggest that neuro-symbolic decentralized governance provides a scalable and trustworthy pathway for safe human-machine collaboration across institutional boundaries.
Solidity has undergone 116 version iterations between August 2015 and February 2026, during which compiler updates have introduced behavioral changes, including issues later fixed in subsequent releases. Contracts compiled under specific versions may exhibit version-dependent execution behaviors, particularly in low-level code. These differences are often difficult for developers and users to recognize, creating opportunities for adversaries to exploit legacy compiler behaviors and deploy contracts with potentially deceptive outcomes. We define this issue as the Compiler Version Discrepancy (CVD) risk , where attackers leverage compiler-version-dependent behaviors to produce misleading or unfair outcomes while contracts appear functionally benign. We summarize five representative CVD risk patterns from real compiler inconsistencies. To mitigate this risk, we develop the CompileGuard detection tool. It combines Abstract Syntax Tree (AST) analysis, taint analysis, and symbolic execution with Control Flow Graph (CFG) analysis to identify version-sensitive code patterns. Evaluation on 227 smart contracts shows CompileGuard achieves an overall F1 score of 95.22%. A user study with 21 blockchain practitioners shows contracts exploiting CVD risks can mislead users, while detection reports enable all participants to correctly identify risk-inducing behaviors. These results highlight the practical exploitability of CVD risks and the effectiveness of automated detection in preventing such deception.
Inge Grondman, Valerie A. C. M. Koeken, Tristan Couwenbergh, Athanasios Karageorgos · 13 authors
Abstract Background Sepsis is a highly heterogeneous syndrome characterized by variable immune dysregulation states, including hyperinflammation and immunosuppression. Previous immunotherapy attempts in sepsis have largely failed, likely due to a “one-size-fits-all” approach that ignores each patient’s immune status. The recent ImmunoSep randomized clinical trial demonstrated that precision immunotherapy guided by the presence of either macrophage activation–like syndrome (MALS) or immune paralysis can improve early organ dysfunction in sepsis patients. However, the molecular mechanisms underlying these immune endotypes remain unclear. Objectives To identify the immunological signatures that distinguish MALS and immune paralysis. Methods We used single-cell RNA sequencing to profile circulating leukocytes of 6 healthy controls and 16 sepsis patients classified as MALS, immune paralysis or unclassified (when criteria for neither of these two immune endotypes were applicable). Classification was based on surrogate biomarkers ferritin and HLA-DR expression on monocytes. Thereafter, the transcriptional programs of these groups were compared. Results Pronounced differences were detected mainly in the transcriptional signature of monocytes from these patients, with a clear distinction between MALS and immune paralysis. Unsupervised clustering analysis revealed the existence of MALS-specific monocyte clusters, as well as one sepsis-specific monocyte cluster that was linked to greater comorbidity burden and may reflect increased clinical vulnerability in sepsis. These findings were validated in two independent cohorts, in which urosepsis was characterized by heterogeneous MALS and immune paralysis monocyte signatures. Moreover, MALS-specific monocyte clusters showed overlapping transcriptional signatures with severe COVID-19. Conclusions Our findings shed light on the heterogeneous immune landscape underlying sepsis and provide opportunities for patient stratification for future therapeutic development.
The increasing adoption of blockchain technology has transformed digital transaction systems by providing secure, decentralized, and transparent data management. The vehicle procurement process, however, still relies heavily on conventional procedures involving multiple intermediaries, manual documentation, and lengthy verification mechanisms that often increase operational costs and expose transactions to fraudulent activities. This paper presents a blockchain-enabled smart vehicle procurement framework that modernizes the complete purchasing lifecycle while preserving transaction integrity and user trust. The proposed system utilizes blockchain technology as an immutable distributed ledger for securely storing vehicle records, ownership history, buyer credentials, and transaction information. Smart contracts are employed to automate critical activities including buyer verification, ownership transfer, payment authorization, and regulatory validation without requiring manual intervention. The decentralized architecture minimizes dependency on third-party agencies while improving transparency, reducing processing delays, and enhancing security against data manipulation. Since every transaction is permanently recorded on the blockchain, both buyers and sellers can independently verify the authenticity of vehicle records before completing a purchase. The proposed framework maintains the same operational workflow and implementation strategy as the reference system while offering improved documentation quality and technical presentation. Experimental observations demonstrate that blockchain-assisted procurement significantly improves transaction efficiency, strengthens security, simplifies ownership transfer, and establishes a reliable digital marketplace for modern automotive commerce. The framework represents a scalable solution capable of supporting future intelligent transportation systems and smart mobility applications.
Version control systems (VCS), including central VCS (CVCS) and distributed VCS (DVCS), are widely adopted to manage changes to software code and various types of documents. Unlike CVCS, where entities obtain data from a central server, each entity in DVCS stores the entire repository and shares it independently. In VCS, existing access control schemes require the participation of a central server and cannot be deployed in a completely distributed scenario. Additionally, these schemes often fail to enforce fine-grained access control for write permissions, which is crucial for collaborative work in a distributed environment. In this paper, we propose a distributed version control system access control scheme (named DVAC), which enforces cryptographic access control on distributed user nodes based on attribute-based encryption (ABE) and attribute-based signature (ABS). DVAC is designed to enforce a cryptographic access control protocol for DVCS, which enables file granularity read and write separation access control without the support of a central server. To ensure the integrity of the core version control functions in DVCS while protecting data security, DVAC incorporates a version control adaptation protocol. Additionally, DVAC leverages Ethereum smart contracts to maintain access control policies, ensuring distributed storage and trusted management of access policies. The architecture of DVAC is designed to seamlessly integrate with existing mature DVCS, such as Git, with minimal modifications. We have implemented a prototype of DVAC and integrated it with Git. A comprehensive performance evaluation was conducted to assess the overhead introduced by DVAC, and it was demonstrated that the overhead is modest.