Cryptocurrencies and Web3 applications based on blockchain technology have flourished in the blockchain research field. Unlike Bitcoin and Ethereum, due to its unique architectural designs in consensus mechanisms, resource management, and throughput, TRON has developed a more distinctive ecosystem and application scenarios centered around stablecoins. Although it is popular in areas like stablecoin payments and settlement, research on analyzing on-chain data from the TRON blockchain is remarkably scarce. To fill this gap, this paper proposes a comprehensive data extraction and exploration framework for the TRON blockchain. An innovative high-performance ETL system aims to efficiently extract raw on-chain data from TRON, including blocks, transactions, smart contracts, and receipts, establishing a research dataset. An in-depth analysis of the extracted dataset reveals insights into TRON's block generation, transaction trends, the dominance of exchanges, the resource delegation market, smart contract usage patterns, and the central role of the USDT stablecoin. The prominence of gambling applications and potential illicit activities related to USDT is emphasized. The paper discusses opportunities for future research leveraging this dataset, including analysis of delegate services, gambling scenarios, stablecoin activities, and illicit transaction detection. These contributions enhance blockchain data management capabilities and understanding of the rapidly evolving TRON ecosystem.
Aiming at the problems of single-point failure, privacy leakage, and high communication delay existing in the process of massive intelligent terminals accessing the new power system with traditional centralized identity authentication methods, this paper proposes an efficient identity authentication method for power terminals based on blockchain and non-interactive zero-knowledge proof. By improving Schnorr protocol, a dynamic random number driven non interactive authentication mechanism is designed to avoid the high delay of private key transmission and multi round communication. At the same time, in combination with the distributed ledger characteristics of the blockchain, the terminal public key and authentication records are decentralized stored, eliminating the dependence on a single CA. In this paper, we propose an aggregate signature method, which aggregates the zero knowledge proofs of multiple devices into a total signature, reducing the computation and communication overhead when authenticating a large number of terminal devices. This paper analyzes the performance of the proposed method using building simulation blockchain on the Hyperledger Fabric platform. Compared with other methods, this method performs well in the actual authentication phase, and reduces the time cost by more than 4.5%. Through batch certification test, compared with single terminal certification, the time cost is reduced by more than 80%. The security analysis results show that this method can resist replay attacks, phishing attacks, etc., and ensure the identity anonymity of terminal devices, the confidentiality of private keys, and the integrity of data transmission.
To address the absence of process-level verifiability in federated learning, a verifiable architecture, zero-knowledge proof-verified and blockchain-audited federated learning (zk-BcFed), is proposed by integrating zero-knowledge proofs with blockchain. For each local model update, a multi-constraint zero-knowledge proof is generated by the client, and verified cryptographic evidence is recorded on-chain, enabling formal verification of local training without disclosure of private data. Across benchmark datasets including SVHN, FashionMNIST, and CIFAR10, among others, enabling zero-knowledge proofs is observed to produce a negligible change in accuracy while substantially improving robustness under model poisoning attacks. Collectively, zk-BcFed safeguards the computational integrity and correctness of federated learning and provides a reliable verifiability mechanism with modest overhead.
The article examines the problem of balancing security and flexibility in decision-making mechanisms within decentralized autonomous organizations (DAOs), which operate without centralized control through the use of smart contracts. To this end, two main voting models employed in DAOs are analyzed: the conjunctive model, which requires unanimous approval of a proposal by all participant groups, and the disjunctive model, where approval from a single group is sufficient. Both models have significant advantages and drawbacks: the former ensures a high level of security and protection of all parties’ interests but considerably slows down the decision-making process, while the latter provides speed and scalability but introduces risks of centralized influence. In response to these challenges, a hybrid voting model is proposed, in which the type of logic is determined by the nature of the proposal. Specifically, critical changes, such as updates to governance rules or quorum parameters, must involve all groups, whereas routine operational matters can be decided through a simplified disjunctive procedure. The implemented smart contract architecture supports both mechanisms and enables DAOs to dynamically adjust quorum thresholds through separate governance proposals. To evaluate the effectiveness of the model, a simulation of 1,000 voting processes was conducted under four different scenarios of participant activity: balanced, one-sided, and low overall participation. The results showed a reduction in the probability of deadlock situations and an increase in the share of successful votes when hybrid logic was applied, particularly under conditions of low or asymmetric participation. In addition, special attention was given to gas cost optimization: the disjunctive approach allows vote counting to be stopped once a quorum is reached by one group, thus reducing overall computational expenses. Therefore, the proposed solution appears promising for both financial DAOs and decentralized infrastructures, particularly the Internet of Things, where speed, scalability, and secure coordination are especially important.
The Metaverse utilizes emerging technologies such as Extended Reality (XR), Artificial Intelligence (AI), blockchain, and digital twins to provide an immersive and interactive virtual experience. As the Metaverse continues to evolve, it brings a range of security and privacy threats, such as identity management, data governance, and user interactions. This survey aims to provide a comprehensive review of the enabling technologies for the Metaverse. It also aims to provide a thorough analysis of key vulnerabilities and threats that may compromise its sustainability and user safety. We perform a systematic literature review (SLR) to identify key vulnerabilities and their countermeasures in Metaverse platforms. Metaverse offers a much larger attack surface compared to conventional digital platforms. Immersive, decentralized, and permanent characteristics of the Metaverse generate new vulnerabilities. Although there are many countermeasures to these vulnerabilities, most of them are theoretical or have not been tested in real-world environments. Our review highlights current advancements, identifies research gaps, and outlines future directions to ensure a secure, resilient, and ethically governed Metaverse.
Elections are not the only but arguably one of the most important pillars for the proper functioning of liberal democracies. Recent evidence across the globe shows that it is not straightforward to conduct them in a free and fair manner. One constant concern is the role of money in politics, more specifically, election campaign financing. Frequent scandals are proof of the difficulties encountered with current approaches to tackle the issue. Suggestions on how to overcome the problem exist but seem difficult to implement. With the help of blockchain technology we might be able to make a step forward. A separate crypto currency specifically designed to pay for costs of political campaigning and advertising could be introduced. Admittedly, at this stage, there are many open questions. However, under the assumption that blockchain technology is here to stay, it is an idea that deserves further exploration.
Juwon Kim, Hyunwook Lee, Hyotaek Jeon, Seungmin Jin · 5 authors
Directional forecasting in financial markets requires both accuracy and interpretability. Before the advent of deep learning, interpretable approaches based on human-defined patterns were prevalent, but their structural vagueness and scale ambiguity hindered generalization. In contrast, deep learning models can effectively capture complex dynamics, yet often offer limited transparency. To bridge this gap, we propose a two-stage framework that integrates unsupervised pattern extracion with interpretable forecasting. (i) SIMPC segments and clusters multivariate time series, extracting recurrent patterns that are invariant to amplitude scaling and temporal distortion, even under varying window sizes. (ii) JISC-Net is a shapelet-based classifier that uses the initial part of extracted patterns as input and forecasts subsequent partial sequences for short-term directional movement. Experiments on Bitcoin and three S&P 500 equities demonstrate that our method ranks first or second in 11 out of 12 metric--dataset combinations, consistently outperforming baselines. Unlike conventional deep learning models that output buy-or-sell signals without interpretable justification, our approach enables transparent decision-making by revealing the underlying pattern structures that drive predictive outcomes.
This paper introduces a Blockchain-Integrated Explainable AI Framework (BXHF) for healthcare systems to tackle two essential challenges confronting health information networks: safe data exchange and comprehensible AI-driven clinical decision-making. Our architecture incorporates blockchain, ensuring patient records are immutable, auditable, and tamper-proof, alongside Explainable AI (XAI) methodologies that yield transparent and clinically relevant model predictions. By incorporating security assurances and interpretability requirements into a unified optimization pipeline, BXHF ensures both data-level trust (by verified and encrypted record sharing) and decision-level trust (with auditable and clinically aligned explanations). Its hybrid edge-cloud architecture allows for federated computation across different institutions, enabling collaborative analytics while protecting patient privacy. We demonstrate the framework's applicability through use cases such as cross-border clinical research networks, uncommon illness detection and high-risk intervention decision support. By ensuring transparency, auditability, and regulatory compliance, BXHF improves the credibility, uptake, and effectiveness of AI in healthcare, laying the groundwork for safer and more reliable clinical decision-making.
The paper highlights the critical need to ensure the reliability of smart contracts and also security of smart contracts, which are agreements execute on their own and have terms that are directly encoded in the code. Smart contracts have transformed a number of industries by offering automated and secure transaction solutions. However, this innovation brings its own set of challenges, including security vulnerabilities and execution errors leading to serious economic and functional consequences. This survey aims to comprehensively address these issues by examining recent research on smart contract security and correctness verification. To lower the risks associated with smart contracts, the framework incorporates efficient techniques and technologies.The survey categorizes and analyzes key vulnerabilities, evaluates existing verification techniques, and proposes best practices for secure smart contract development. Additionally, it identifies research gaps and future directions to enhance the security of smart contracts. By guiding researchers and practitioners toward building more secure and reliable smart contract systems, this effort not only fortifies the backbone of blockchain technology but also encourages the scalability and resilience of decentralized systems in the fast-paced digital age of today with its wide range of use cases
Marine carbon dioxide removal (mCDR) projects are increasingly recognized as a strategic pillar in climate change mitigation. However, their effectiveness and credibility critically depend on the ability to implement secure and verifiable Monitoring, Reporting, and Verification (MRV) procedures, particularly in remote, adversarial, and resource-constrained environments like underwater ecosystems. Despite growing interest in mCDR, current MRV frameworks remain inadequate for such challenging contexts, lacking essential mechanisms to ensure secure device identity, reliable data provenance, and verifiable auditability, as mandated by standards such as ISO 14064-2 and ISO 14064-3. This thesis addresses these limitations by first focusing on the fundamental security challenges that arise in underwater untrusted environments. To overcome these barriers, it introduces a set of modular, composable building blocks that integrate: i) decentralized identifiers (DIDs) for self-sovereign identity management, ii) physically unclonable functions (PUFs) to cryptographically bind secrets to hardwaredevices, iii) non-interactive zero-knowledge proofs (NIZKPs) to enable lightweight and privacy-preserving authentication, and iv) distributed ledger technologies (DLTs) to ensure immutable and verifiable data anchoring. These solutions are designed to be modular, interoperable, and composable, providing the necessary foundation to build secure, transparent, and standards-compliant MRV frameworks suitable for deployment in underwater and blue carbon ecosystems. Crucially, the proposed work does not merely adapt to MRV requirements but proactively resolves critical security gaps that existing MRV models overlook, thus enabling trustworthy data collection, secure identity management, and verifiable certification in these complex environments. The individual building blocks have been implemented and validated on constrained embedded platforms (e.g., ESP32-C3), demonstrating their feasibility under the constraints of underwater sensing. Formal security guarantees are established using symbolic analysis, while empirical evaluations quantify the computational and communication overhead of each component under realistic conditions. By starting from low-level cryptographic primitives and addressing core security challenges, this thesis delivers a foundational contribution to the development of secure, verifiable, and scalable MRV infrastructures for underwater and blue carbon applications. The proposed approach supports the creation of trustworthy, standards-aligned MRV frameworks, enabling verifiable environmental accountability even in hostile and resource-constrained deployment scenarios.
Implementing upgradeable smart contracts (USCs) has become a trend in Decentralized applications. Due to blockchain immutability, ensuring the upgradeability of smart contracts requires specialized implementation strategies. A systematic study of developers’ concerns regarding USC development can provide insights to reduce development costs and increase software robustness. In this work, we propose the first empirical study on exploring developers’ concerns over USCs. We first extract 2,224 USC-related posts based on an iterative process combining keyword filtering and manual filtering of posts from theEthereum StackExchangecommunity. Following open card-sorting practice, we propose 13 common development concerns based on the extracted posts, as well as the causes of these concerns. Furthermore, we analyze the frequency of these concerns within developer discussions. We highlight the most significant concerns of developers, where the top 5 most frequently discussed concerns are notably absent in existing research, e.g., code bugs originating from interacting and testing USCs in specific development frameworks. Additionally, we examine the real-world impact of these concerns by analyzing on-chain smart contracts and security reports from two widely referred databases, i.e.,RektandSlowmist. Based on case studies of the USC-related security reports in the past two years, we found that the causes of most USC security incidents are related to the identified concerns. Besides, we proposed a semi-automatic tool based on static analysis to detect related bugs and found 26 bugs in real-world smart contracts, which have involved over 0.3 million transactions. Based on these findings, we provide suggestions on the less-solved-yet-prevalent concerns regarding usability and security of USC development, such as facilitating the testing on USCs under existing development frameworks.
This research note calls for an alternative approach to understanding ‘innovativeness,’ particularly in arenas like Decentralized Finance (DeFi) where participant perceptions clash with mainstream evaluations, often leading to their dismissal. When conventional metrics fail to capture the perceived value and groundbreaking nature asserted from within these communities, there is a pressing need to explore their distinct ‘cosmologies’ or internal logics. This paper argues for the importance of investigating these alternative meaning systems – how value and innovation are defined and experienced by participants – rather than solely relying on external measures. It posits that a deeper engagement with the ‘native point of view’ in such ‘rejected arenas’ can yield crucial insights, not only for understanding these specific phenomena but also for challenging and enriching our broader conceptions of innovation. This note serves as a call to researchers to undertake such explorations.
This paper examines the growing challenges of verifying and validating micro-credentials within increasingly fragmented educational ecosystems. As traditional educational pathways diversify into modular learning experiences, the need for reliable verification mechanisms becomes critical for workforce mobility and lifelong learning recognition. Through comparative and inductive analysis, this research identifies key vulnerabilities in current micro-credential systems and proposes a conceptual framework for a multi-layered validation infrastructure. The proposed approach integrates interoperable verification protocols, distributed ledger technologies, and reputation-based validation mechanisms to establish trust across educational institutions, employers, and learners. The framework addresses fundamental challenges including standardization gaps, informal learning validation, and credential falsification risks. While implementation barriers exist related to scalability and cross-cultural acceptance, the multi-faceted validation ecosystem outlined offers promising pathways toward a more flexible, secure recognition system for modular qualifications. The establishment of trusted microcredential ecosystems could significantly enhance labor market efficiency by enabling precise skill verification while democratizing access to recognized qualifications beyond traditional academic institutions.
Due to the high rate of fragmentation, India's healthcare system is faced with stagnant patient data that is isolated in silos involving thousands of clinics and healthcare centers. This disunity is linked to significant gaps in patient care, as individuals carry actual documents and medical professionals struggle to obtain a comprehensive clinical history when necessary. In this study, the authors analyze how blockchain can be used to resolve the healthcare interoperability crisis in India. Compared to the traditional centralized databases, blockchain establishes a distributed ledger, through which records between patients remain securely shared within approved healthcare networks. Immutable feature maintains data integrity and the decentralized system offers high security against cyber-attacks that are being perpetrated more commonly on healthcare institutions. There are three main benefits to the implementation of a blockchain identified in the study. One is increased security due to distributed storage of data that removes single-point failover which hackers usually target. Second, the enhanced interoperability will enable the easy flow of information among the public and private healthcare providers eliminating repetitive tests and delays in care. Third, greater transparency allows the patients more influence on their healthcare data, as well as improves the ability to track clinical trials and outcomes. Nevertheless, a number of problems make the adoption of blockchain in the Indian healthcare industry difficult. The cost of implementation is still extremely high in many institutions especially the smaller clinics and the rural health care providers. The current electronic health records systems have to be upgraded significantly to connect to the blockchain networks. The regulatory frameworks will have to change, such as the Personal Data Protection Bill in 2020 in India, and ensure that they support decentralized data management alongside standards of compliance. Based on the conducted research, it can be concluded that the implementation of blockchain requires the joint work of governmental institutions, healthcare facilities, and technology corporations. Though there exist some technical and financial obstacles, the capability of blockchain to build a single, safe ecosystem in the healthcare industry may bring incredible changes in patient outcomes of the wide variety of healthcare in India.
There has been a major cause of concern, especially concerning the integrity of political financing, since the idea of existing electoral bonds lacks transparency, traceability, and accountability. Although these systems are meant to help formalize political contributions, they usually help to allow anonymous contributions and disclosure at will, violating both the trust of a population and democratic responsibilities. The paper entails the design, development, and flow of ElectraChain, a decentralized system and blockchain-based electoral bond management platform. With the help of smart contracts and privacy-preserving cryptographic schemes like Zero-Knowledge Proofs (ZKPs), ElectraChain will preserve the tamper-proofness of bond transactions recording and preserve donor anonymity. The architecture proposed has secure KYC processes included, automated compliance procedures, and publicly available dashboards to go to the next level of transparency without any breach of privacy. Blockchain technology has been a device that allows the development of a viable prototype that supports the feasibility, security, and scalability of the system. The paper also assesses the technical parameters of the system and comments on the possibilities of the use of such a system nationally, which becomes a major step towards transparent, accountable, and technology-driven political financing in democracies.
Wireless Sensor Networks (WSNs) are widely used in various applications that require secure and efficient data aggregation. A novel secure data aggregation scheme is proposed in this study. This is a novel combination of Blockchain technology and Zero-Knowledge Proofs (ZKPs). This scheme is broken down into three parts. The first is Blockchain based Data Aggregation for storage of tamper proof and immutable data. Second, anonymity with ZKP to provide privacy preservation and secure identity verification. Finally, we combined Blockchain and ZKP operation to achieve energy efficiency and robust security. The proposed scheme guarantees data confidentiality, integrity, anonymity, and resilience to malicious attacks, and at the same time handles the energy optimization problem in WSNs. We implemented the proposed scheme in MATLAB to evaluate its performance with metrics like stability, jitter, latency, and throughput. Simulation results show that the proposed scheme achieved robust security in terms of data integrity and confidentiality by slightly compromising on the availability aspect.
Rural and underprivileged areas continue to grapple with the availability of affordable and dependable healthcare funding.Community based health insurance mechanisms are rife with inefficiencies including long delays in claim processing, fraudulent reporting, lack of transparency, and weak guardrails.This paper suggests a smart village-focused blockchain-based system on community health insurance.The platform is built on top of permissioned blockchain, smart contracts, and decentralized identity management to secure policy issuance, transparent premium collection, automated claims settlement, and community-based network governance.A prototype was implemented based on Hyperledger Fabric with off-chain storage of medical data and a mobile app for rural access.A simulation study was implemented to evaluate the performance of the proposed framework on a synthetic claim data, which have shown to significantly decrease the claim processing time, increase the rate of fraud detection, and raise the trust perception by all the involved users.Contribution -The proposed study aims to contribute towards designing and implementing (blockchain-enabled) healthcare financing models to pave the way for the promotion of sustainable healthcare for equitable benefits in rural smart village ecosystems.
Purpose This study aims to fill a gap in cryptocurrency regulation research by establishing a dynamic framework that balances market stability and capital flight. It seeks to derive an optimal, adaptive regulatory strategy that reconciles stringent enforcement with its unintended consequences. Ultimately, the study provides insights to guide policymakers in designing interventions that sustain financial stability while supporting efficient market functioning in the evolving digital asset environment. Design/methodology/approach This study develops a differential game-theoretic model to capture the dynamic interplay between cryptocurrency regulators and market participants. Using stochastic differential equations to model market stability and capital flight, the framework derives Nash equilibrium conditions for optimal regulatory intensity and liquidity migration. The model is validated through Monte Carlo simulations that examine various market scenarios and sensitivity analyses for robustness across different parameter settings. Findings Results indicate that an aggressive initial regulatory stance rapidly enhances market stability, albeit at the cost of a temporary increase in capital flight. Over time, adaptive regulatory adjustments lead to a self-stabilizing equilibrium where volatility diminishes and liquidity migration is contained. The Nash equilibrium analysis confirms that a balanced enforcement strategy can effectively mitigate the adverse impacts of capital flight while maintaining overall market resilience, as supported by consistent outcomes from the simulation experiments. Research limitations/implications The model’s simplifying assumptions, including a homogeneous market and single regulator framework, limit its immediate real world applicability. It uses a continuous time approach and normally distributed shocks, which may not capture discrete regulatory events or extreme market disruptions. Additionally, the analysis is sensitive to parameter calibration. These limitations suggest further research is needed to incorporate multi-agent dynamics, market microstructure factors and alternative stochastic processes to improve empirical validation and practical relevance. Practical implications The study provides policymakers a dynamic framework for calibrating regulatory intensity to balance market stability with the risk of capital flight. It emphasizes that while strict initial enforcement can stabilize markets, subsequent moderation is key to sustaining resilience. The derived equilibrium conditions provide actionable insights for designing adaptive, real-time interventions that minimize liquidity outflows and improve overall market integrity, supporting a regulatory approach that promotes innovation while mitigating systemic risks. Originality/value This research pioneers the application of differential game theory to cryptocurrency regulation, integrating market stability and capital flight into a single dynamic model. By deriving Nash equilibrium conditions and validating the framework through numerical experiments, the paper advances current literature and provides a novel, theoretically rigorous tool. Its innovative perspective equips policymakers with a nuanced approach to designing responsive regulatory strategies in the fast-evolving digital asset space.
The article presents a comprehensive overview of zero-knowledge proof (ZKP) protocols as a fundamental concept of modern cryptography. The historical background of their emergence and the main properties ensuring reliability and confidentiality, i.e., completeness, soundness, and zero-knowledge — are considered. A classification of protocols into interactive and non-interactive ones is provided, with a special focus on modern solutions such as the zk-SNARK and the zk-STARK. The mathematical foundations of ZKPs are described in detail, including discrete logarithm proofs, the use of homomorphic encryption, polynomial commitments, hashing, and elliptic curves. Practical application areas are analyzed, including cryptocurrencies (Zcash, Ethereum), authentication systems, digital identity, and electronic voting. The advantages of using ZKPs are shown, such as enhanced privacy, reduced need for trusted intermediaries, and strengthened security. At the same time, key challenges are outlined, including scalability, implementation complexity, the problem of trusted setup, and potential vulnerability to quantum computing. It is concluded that zero-knowledge proof protocols are a powerful tool for ensuring confidentiality and reliability of digital systems, while further research is aimed at creating more efficient and quantum-resistant solutions.
Purpose: This study examines the potential of on-site water reuse (OSWR) systems as sustainable solutions to Nigeria’s growing urban water challenges, assessing technological, socio-cultural, economic, and regulatory dimensions to determine their role in improving resilience and equity. Methodology: A Systematic Literature Review (SLR) was conducted using Scopus, Web of Science, and Google Scholar databases, covering studies from 2015 to 2025. From over 400 initially identified publications, 100 were retained after applying the inclusion criteria. Thematic analysis was employed to evaluate the technological options, financial models, socio-cultural perceptions, and governance structures that influence OSWR adoption. Findings: Evidence suggests that low-cost technologies, such as biosand and ceramic filtration, ultraviolet disinfection, and modular greywater systems, are technically feasible and locally adaptable. Economic assessments highlight long-term cost savings; however, the upfront capital intensity requires innovative financing mechanisms. Socio-cultural barriers—including mistrust, hygiene concerns, and low awareness—remain significant, while regulatory frameworks are fragmented and lack explicit guidelines for decentralized reuse. Case studies in Lagos and Abuja confirm feasibility but reveal gaps in policy enforcement and sustained investment. Unique Contribution to Theory, Practice and Policy: OSWR systems are a viable pathway to strengthen urban water security, reduce reliance on centralized supply, and enhance resilience in Nigeria. Success requires governance reforms, participatory community engagement, targeted subsidies, and innovative financing (e.g., climate funds, PPPs). Embedding OSWR into national policy and urban planning frameworks is essential for long-term sustainability.
We offer a new perspective on trust formation in smart contracts on blockchain that is based on deduction rather than induction. This shift in perspective allows us to explore the boundaries of trust in IT systems, analyze the conditions under which trust becomes dispensable, and unpack the sociotechnical complexity of supposedly “trust-free” systems. Through this approach, we introduce three key concepts: deductive certainty, a state in which an individual has full knowledge of the other party’s future behavior based on deduction; the possibility of deductive certainty that an IT system may provide; and deduction-related trust, a new type of trust rooted in the possibility of deductive certainty. We use these concepts to analyze smart contracts on a blockchain as a technology that offers the potential for deductive certainty by enabling complete deduction. Our analysis reveals the conditions under which smart contract-based applications, also known as dApps, can become “trust-free” and why, in practice, they often are not. Based on a sample of 536 dApps and a user survey, we provide evidence supporting our theoretical claims. Our findings suggest that the possibility of deductive certainty plays a significant role in forming initial trust in dApps. However, we also find that new users rely on both deduction-related trust and classical inductive trust, with the two sources of trust reinforcing each other.
The question at stake in Lagrangian controllability is whether one can move a patch of fluid particles to a target location by means of remote action in a given time interval. In the last two decades, positive results have been obtained both for the incompressible Euler and Navier-Stokes equations. However, for the latter, the case where the fluid is contained within domains bounded by solid boundaries with the no-slip condition has not been addressed, with respect to the difficulty caused by viscous boundary layers. In this paper, we investigate the Lagrangian controllability of viscous incompressible fluid in perforated domains for which the fraction of volume occupied by the holes is sufficiently small. Moreover, we quantitatively distinguish situations depending on the parameters for holes (diameter and distance) and for fluid (size of the initial data). Our approach relies on recent results on homogenization for evolutionary problems and on weak-strong stability estimates in measure of flows, alongside classical results on Runge-type approximations for elliptic equations and on Cauchy-Kowalevsky-type theorems for equations with analytic coefficients. Here, homogenization refers to the vanishing viscosity limit outside a porous medium, where (after scaling in time) the Navier-Stokes equations are homogenized to the Euler or Darcy equations. Indeed, in the proof, we act on the Navier-Stokes equations by strong and fast forcing to leverage inviscid approximations, which is a standard technique in the theory of controllability.
Open access
Advanced Mathematical Modeling in Engineering
Stability and Controllability of Differential Equations
Fan Liu, Yongan Zhang, Yanqiu Liu, Jia Li · 6 authors
The Body Condition Score (BCS) is a key indicator of dairy cattle’s health, production efficiency, and environmental impact. Manual BCS assessment is subjective and time-consuming, limiting its scalability in precision agriculture. This study utilizes computer vision to automatically assess cattle body condition by analyzing tail features, categorizing BCS into five levels (3.25, 3.50, 3.75, 4.0, 4.25). SE attention improves feature selection by adjusting channel importance, while spatial attention enhances spatial information processing by focusing on key image regions. EfficientNet-B0, enhanced by SE and spatial attention mechanisms, improves feature extraction and localization. To facilitate edge device deployment, model distillation reduces the size from 23.8 MB to 8.7 MB, improving inference speed and storage efficiency. After distillation, the model achieved 91.10% accuracy, 91.14% precision, 91.10% recall, and 91.10% F1 score. The accuracy increased to 97.57% for ±0.25 BCS error and 99.72% for ±0.5 error. This model saves space and meets real-time monitoring requirements, making it suitable for edge devices with limited resources. This research provides an efficient, scalable method for automated livestock health monitoring, supporting intelligent animal husbandry development.