While deep learning models have demonstrated superior performance in cryptocurrency forecasting, their deployment is often hindered by a lack of interpretability and trustworthiness. To bridge this gap, this paper proposes the Cryptocurrency Counterfactual Explanation (CryptoForecastCF) model. Recognizing the inherent volatility and complex non-linear dynamics of cryptocurrency markets, we argue that understanding the sensitivity of model outputs to slight variations in historical conditions is fundamental to robust risk management. CryptoForecastCF employs a gradient-based optimization strategy to generate meaningful counterfactual explanations. Specifically, it identifies minimal modifications, defined as the optimal perturbations to historical market features such as price constrained by ℓ1 or ℓ2 norms, that are sufficient to steer the model's future predictions into user-specified target intervals. This approach not only elucidates the key driving factors and decision boundaries of opaque models but also equips traders and risk managers with actionable insights, enabling them to identify the specific market shifts required to navigate high-stakes scenarios and mitigate unfavorable predictive outcomes.
The increasing need for sustainable practices has encouraged listed companies to participate in carbon trading markets. Traditional centralized systems for managing carbon trading data often face challenges such as limited transparency, poor traceability, and security risks, leading to inefficiencies and compliance issues. This research proposes a blockchain-based framework with smart contracts to provide a secure, decentralized mechanism for recording and verifying carbon trading data. The system ensures tamper-proof logs of emission allowances, trading transactions, and verification events, enabling real-time access for regulatory authorities. Data preprocessing uses Z-score normalization to standardize inputs, while Kernel Principal Component Analysis (KPCA) reduces dimensionality and extracts relevant features. To improve decision-making and cost-efficiency, a Dynamic Cuckoo Search-mutated Locust Swarm Optimization (DCSLSO) algorithm is embedded within the smart contracts to optimize carbon credit allocation and trading strategies. The framework is evaluated through simulations under varying energy demands, carbon prices, and multi-fuel scenarios, using synthetic datasets from energy-intensive industries. The DCSLSO model is implemented using Python and TensorFlow. This research demonstrates that blockchain technology, combined with intelligent smart contracts, can modernize carbon trading for listed companies, fostering transparency, accountability, and long-term economic sustainability in emissions management. This research highlights the potential of combining blockchain technology with intelligent optimization to modernize carbon markets, promoting transparency, accountability, and sustainable economic growth in emissions management.
The Physics of Truth: Extending WorldSeed from Robotics to Semantics Why is it impossible for a robot to lift a 10-ton rock, yet trivial for an AI (or human) to claim "I can lift a 10-ton rock"? This paper identifies the root cause of both AI Hallucination and Human Deception: the lack of "Energy Cost" in the textual domain (W_Text). In a frictionless semantic environment, generating a lie is thermodynamically equivalent to generating the truth. This work extends the WorldSeed SABO Protocol (State, Action, Boundary, Observer) from the domain of physical robotics (Sim2Real) to the domain of semantic truth (Sim2Fact). We propose that Truth is not a statistical property of language, but a computable property of Grounded State (S) and Costly Action (A). Key Contributions: The Theory of Semantic Gravity: Introducing axiomatic constraints (On-chain State, Action Staking) to make deception computationally or economically prohibitive. SABO Audit of Lies: Analyzing the structural flaws of decoupled observation (O ≠ S) in LLMs and social contracts. Three Case Studies:• Literary Hallucination: Using logic boundaries to reject impossible narratives (e.g., Lin Daiyu uprooting a willow tree).• Financial Fraud: Replacing CEO claims with Zero-Knowledge Proofs of Solvency.• Social Default: Using smart contract staking to enforce promises. The Theorem of Semantic Convergence: A formal proof demonstrating that under a strict WorldSeed Runtime, divergent linguistic descriptions must collapse into a unique ontological fixed point. "Meaning is Execution." This paper completes the WorldSeed trinity by providing the philosophical and sociological framework that complements the Axiomatic Specification and the Civilization Operating System.
Vehicle-to-Everything (V2X) communication is at the center of autonomous mobility, as it enables vehicles to exchange real-time information with infrastructure, other vehicles on the road, including pedestrians, and the network. V2X has the potential to improve navigation, traffic flow, and safety but also brings with it the associated governance risks of data integrity, privacy, and cybersecurity. These risks are amplified by the interconnected nature of V2X networks, which handle sensitive data like vehicle locations and driver identities, necessitating robust security solutions. This systematic review considers blockchain as a remedy, with its decentralized architecture, cryptographic security protocols, and automation through smart contracts. A review of peer-reviewed literature from 2018 to 2025 highlights blockchain's role in tamper-proof communication, privacy preservation through Zero-Knowledge Proofs and Ring Signatures, and secure transaction automation. For instance, blockchain ensures data immutability by distributing trust across nodes, reducing vulnerabilities like data spoofing, while smart contracts streamline processes like toll payments. Challenges such as scalability, latency, and regulation are addressed with proposals such as 5G, edge computing, and governance frameworks. Hybrid blockchain systems, either public or private are examined in this study to obtain a trade-off between scalability and security in V2X networks. In addition, interoperability is proposed to facilitate the seamless exchange of data between V2X systems. Emerging consensus mechanisms like proof of stake and directed acyclic graphs are proposed to enhance scalability, while federated learning integrations bolster privacy. Pilot projects, such as those in Dubai and Singapore, demonstrate blockchain’s practical efficacy in securing V2X ecosystems. The review positions blockchain as a leading enabler of secure, efficient, and privacy-aware intelligent transport systems. Future research should focus on standardizing governance and addressing latency to ensure global adoption.
This preprint introduces Risk Oracle, an exploit-intelligence–driven SBOM attestation framework designed to support practical risk gating in CI/CD. The system combines signals from Known Exploited Vulnerabilities (KEV) and Exploit Prediction Scoring System (EPSS) with SBOM-to-vulnerability matching to produce a policy-backed gate decision (e.g., pass / warn / block) while keeping the workflow interpretable and reproducible. A core design goal is bounded disclosure: the producer can commit to full findings and then disclose only a limited subset (e.g., top-K highest-risk issues) suitable for downstream verification, reducing disclosure risk while preserving auditability. The paper details the end-to-end pipeline (producer/verifier roles), a typed attestation schema, a scoring and decision procedure, and an evaluation that studies (i) signal behavior under pinned KEV/EPSS snapshots and (ii) operational overhead under synthetic SBOM scaling intended to approximate CI workloads. Key contributions A practical SBOM attestation pipeline that integrates exploit-intelligence signals for operational decision-making in CI/CD. A typed attestation schema and verifier procedure supporting bounded disclosure. A policy-driven scoring and gating framework (pass/warn/block) grounded in vulnerability-management practice. Evaluation focused on interpretability and operational cost (runtime/payload scaling) under reproducible, pinned snapshots. Artifacts / Reproducibility Code, scripts, and pinned snapshot references: [GitHub link] Suggested citationSudhir, S. (2026). Risk Oracle: Exploit-Intelligence–Driven SBOM Attestations with Bounded Disclosure (preprint). Zenodo. DOI: [10.5281/zenodo.18153487] Keywords: SBOM, software supply chain security, vulnerability management, KEV, EPSS, OSV, attestation, CI/CD, bounded disclosure, reproducibility
Verifiable computation has emerged as an important enabling technology for secure andauditable computing, yet its practical deployment on energy- and latency-constrained hardwareremains limited by the overheads associated with execution logging and verification. This articlereviews recent developments in transparent verification and zero-knowledge proof systems fromthe perspective of embedded and edge computing, with emphasis on physical constraints suchas power consumption, memory bandwidth, and real-time operation. As an experimental casestudy to ground the discussion, we examine an embedded witness-recording pipeline designed tosupport downstream STARK-style verification workflows.The evaluated system couples a delta-encoded witness-recording mechanism with cryptographic integrity binding and was implemented on a Raspberry Pi 5 equipped with a Hailo-8neural processing unit. Under the reported test configuration, the recorder sustained approximately 11.47 million recorded steps per second, with per-step recording latencies on the order oftens of nanoseconds. The associated computation kernel—a Lyapunov-stable linear contractionoperator defined in PyTorch, exported via ONNX, and compiled to Hailo-8 silicon—exhibitedmeasured execution rates of 49,859 operations per second in hardware-only mode and 28,394operations per second when invoked through a Python-mediated runtime.Witness data were captured using Cython-optimized routines with delta encoding andmulticore sharding, producing approximately 1.4 GB of compressed shard data for 500 millionrecorded steps, corresponding to an observed compression ratio of roughly 14× under the testedworkload. Integrity binding was achieved via cryptographic commitment roots validated throughrecomputation and contract-level checks, with integration demonstrated using Cairo smartcontracts on StarkNet. Throughput-derived frame-budget estimates, along with energy andcost calculations based on stated power-accounting assumptions, are presented as contextualindicators rather than general performance bounds.All implementation artifacts, execution logs, and validation results are publicly released tosupport independent inspection and reproduction. The reported measurements characterize thebehavior of a specific witness-recording architecture under a constrained workload and hardwareconfiguration, and are intended to inform broader discussions of verifiable computation forembedded systems rather than to establish general claims about end-to-end zero-knowledge proofgeneration performance Baramay Station Research Inc.Canadian Non-Profit R&D (Saskatchewan)Director & Principal Investigator: Michael Tass MacDonald Contact michael@baramaystationresearchinc.ca
Meme coins have become extremely popular in the cryptocurrency market, but they also carry a high level of risk. Many of these projects rely on social media hype and community excitement, yet a large number eventually turn out to be scams where developers steal investor funds and abandon the project, commonly known as rug pulls. This paper presents a smart analysis tool designed to help investors identify such risky meme coin projects before financial loss occurs. The proposed system examines both smart contract behavior and market-related factors, including ownership control, liquidity locking, token distribution, and developer wallet activity. The tool was tested on real-world meme coins, including well-known legitimate projects as well as confirmed scam tokens. The results show that the system is able to accurately distinguish between safe and high-risk projects. This approach provides a practical and effective way to improve investor safety in the rapidly evolving decentralized finance ecosystem
Cryptocurrency price forecasting has gained increasing attention due to the market’s high volatility and structural complexity. While many recent studies have explored deep learning architectures, including attention- and transformer-based models, existing research still faces notable limitations: (i) inconsistent feature engineering choices, (ii) limited examination of hybrid machine-learning models, and (iii) a lack of transparent trading evaluation using realistic backtesting assumptions. To address these gaps, this study develops a hybrid forecasting and trading framework based on Support Vector Regression (SVR) combined with a set of rule-based technical strategies. Using four major cryptocurrencies – BTC, ETH, XRP, and LTC – from 2018 to 2020, the proposed framework integrates thirteen technical indicators with a sliding-window scheme and compares SVR against Random Forest (RF) and Long Short-Term Memory (LSTM) benchmarks. Empirical results show that SVR offers a competitive balance between predictive accuracy and computational efficiency, particularly in moderate-volatility regimes. The strategy backtesting further demonstrates that SVR-driven signals can outperform traditional technical rules under certain market conditions, although limitations remain for highly volatile assets such as Bitcoin. The study contributes to the literature by clarifying feature-design choices, evaluating SVR within a multi-asset setting, and providing reproducible code and datasets through an open-access repository.
In the digital era, protecting visual content from misuse and forgery is essential. This study proposes a robust image watermarking method by integrating Discrete Wavelet Transform (DWT), Hessenberg Decomposition (HD), and Singular Value Decomposition (SVD), aiming to enhance watermark imperceptibility and resilience against common image attacks. Additionally, the system incorporates RSA digital signatures within the watermark metadata to ensure verifiable authenticity in NFT (Non-Fungible Token) applications. The method was implemented using Python and tested on multiple grayscale images across various attack scenarios, including noise addition and compression. Experimental results demonstrate high SSIM and PSNR values, confirming the method's effectiveness in maintaining both visual fidelity and embedded watermark integrity. These findings support the potential of this approach for secure and scalable NFT copyright protection.
Open access
Advanced Steganography and Watermarking Techniques
The rigorous security model of Bitcoin's UTXO architecture often comes at the cost of developer usability, forcing a reliance on manual stack manipulation that leads to critical financial vulnerabilities like signature malleability, unspendable states and unconstrained execution paths. Industry standards such as Miniscript provide necessary abstractions for policy verification but do not model the full imperative logic required for complex contracts, leaving gaps in state management and resource liveness. This paper introduces Bithoven, a high-level language designed to bridge the gap between expressiveness and formal safety. By integrating a strict type checker and a resource liveness analyzer with a semantic control-flow analyzer, Bithoven eliminates major categories of consensus and logic defects defined in our fault model prior to deployment. Our results indicate that this safety comes at modest cost: Bithoven compiles to Bitcoin Script with efficiency comparable to hand-optimized code, demonstrating that type-safe, developer-friendly abstractions are viable even within the strict byte-size constraints of the Bitcoin blockchain.
The association between cryptocurrency and sustainability is a complex and growing topic. Given that such linkage requires a continuous investigation, this empirical research, unlike the existing literature, explores if the volatility dynamics of digital assets are driven by the changes in sustainability uncertainty. In doing so, we use a recently developed ESG-based sustainability uncertainty index (ESGUI) and examine its effect on the volatility dynamics of Bitcoin and Ethereum ETFs. Employing the mixed data sampling (MIDAS) approach shows that ESGUI exerts a negative effect on the realized volatility of cryptocurrency markets. One possible explanation for this linkage is that as sustainability-related uncertainty rises, investors tend to adopt sustainability practices and initiatives. This shift towards sustainable practices can result in more consistent and foreseeable long-term economic conditions, thereby reducing the volatility of financial markets including the digital asset class. Our analysis offers key implications to cryptocurrency investors.
This paper explored how digital transformation and the use of blockchain technology influenced supply chain transparency in pharmaceutical companies operating in emerging Chinese markets. The study incorporated the Technology Acceptance Model (TAM), which facilitated the identification of key aspects such as perceived usefulness, perceived ease of use, attitude, and behavioral intention, along with the mediating variable of self-efficacy. Based on these elements, a conceptual framework was developed, which further aided understanding of the hypothesised relationships examined in the study. Accordingly, a quantitative research design was implemented using a primary data collection method. In the Shanghai pharmaceutical industry, data were collected from a sample of 400 managerial employees. The outcomes of technology integration and transparency were quantitatively examined in relation to one another. The results indicated that blockchain technology and digital transformation enhanced supply chain performance through improved traceability, trust, and efficiency. The study shed further light on the main obstacles to implementation and provided insights for policymakers and industry leaders on improving transparency through advanced digital technologies in China’s expanding pharmaceutical market. The findings confirmed that respondents perceived the synergistic effects of digital transformation and blockchain implementation as having the greatest potential to improve supply chain transparency. Blockchain technology enabled real-time, secure, and distributed immutable ledgers that supported product tracking, counterfeiting prevention, verification of authenticity, and enhanced transparency.
Kamil Ježek, Seongho Jeong, Yeonsoo Kim, Bernhard Scholz · 5 authors
Ethereum’s smart contracts operate on directly addressable storage that is represented as tries. The performance of the Ethereum Virtual Machine (EVM) suffers from slow storage access due to trie encoding, which hampers transaction throughput and scalability. To mitigate the Ethereum storage performance bottleneck, we propose a new storage representation for the EVM that supports asynchronous trie construction. Without changing the Ethereum protocol, we add a flat representation called Storage Replica to improve performance. Storage Replica provides a fast lookup of values in the program’s main thread, while a worker thread prepares the tries for subsequent cryptographic calculations. With a storage overhead of less than 5% (i.e., 10 GB), we achieve up to a 6× speedup in processing smart contracts and a 4× speedup in block commits for the initial 9 M blocks of the Ethereum blockchain.
The rapid proliferation of Internet of Things (IoT) technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a comprehensive analysis of vulnerabilities, threats, and defense mechanisms, specifically focusing on the integration of network and application layers within real-time monitoring and decision-making systems. Employing an integrative review methodology, 59 scholarly articles published between 2009 and 2024 were selected from databases such as IEEE Xplore, ScienceDirect, and PubMed, utilizing keywords related to IoT vulnerabilities and security attacks. Key findings identify critical threat categories, including sensor vulnerabilities, Denial-of-Service (DoS) attacks, and public cloud insecurity. Conversely, the study highlights advanced defense approaches leveraging Artificial Intelligence (AI) for anomaly detection, Blockchain for decentralized trust, and Zero Trust Architecture (ZTA) for continuous verification. This paper contributes a novel five-layer IoT model and outlines future research directions involving quantum computing and 6G networks to bolster IoT ecosystem resilience.
-------------------------------------------------------------- Announcement: * Announcement of the release of the Singularity Pi Hack Tool, Pi Thinking Method Prompt Collection, and Cosmic Fundamental Specification.* An archive of over 900,000 characters of discussion notes on the origin of the universe and pi.* This is an epoche pi cosmology that re-examines the universe from its very foundations. Pi is essential for understanding the singularity problem.* A Pi theory hack tool and Pi thinking method module for injecting mathematical logic into AI agents to smoothly advance discussions on cosmology and singularity using pi.It includes many of my pi research notes and papers.It is a text file.You can buy it here. https://tomit.booth.pm/items/8527071 You can inject my problem-deconstruction thinking method into AI agents.We also offer many other AI agent injection logics.Thank you for your continued support.Stay tuned. End of announcement -------------------------------------------------------------- The stance that "dialogue itself has value, and the drafting process itself is proof of truth" is the very essence of dynamic inflation theory. ⚠ Statement on Release: On the Value of Drafts⚠ 公開にあたっての宣言:ドラフトの価値について "The greatest meaning and value of these FAQs and drafts is in releasing them in this draft form, even before the final "final copy." It would be a paradox to think that "dialogue has value, but draft FAQs have no value." This is because dialogue is the expansion of structure, and this draft is nothing but evidence that SDC theory is currently undergoing inflation (expansion and integration)." 🛡SDC Project: FAQ for Refuting Critics (Final Line of Defense)Q1. Isn't the "left side = right side" structure simply a tautology?[Refutation]No. The "equality" sign in mathematics has two meanings. One is the "result of a calculation," and the other is a statement of "deep duality."The equality sign in the SDC equations refers to the latter, "self-dual closure." The AdS/CFT correspondence in superstring theory in physics and the Langlands conjecture in mathematics are also higher-order tautologies in the sense that they connect the "same structure" described in different languages.By asking the question, "Why does the universe have to be self-dual?", this project is designed to question the very logical foundation of critics.Q2. Why can unsolved problems be treated as products?[Refuted]That is the core of Axiom V (the non-collapse axiom).We are not seeking "specific numerical values" for each variable. We are defining their structural status as "factors of products in higher dimensions."By raising the "level of abstraction" so that uncertain elements can be treated as uncertain, we are building a robust theory that does not depend on the success or failure of individual proofs. Whether the factor is $0$ or $1$, the associative law and duality as a product remain unchanged.Q3. Does "remain unharmed even if a counterexample is found" mean that we are abandoning scientific falsifiability?[Refuted]No. SDC is not a prediction of "individual events," but a description of the **vessel of the universe**.For example, the law of conservation of energy maintains as a symmetry of the entire system (Noether's theorem) even if a counterexample is found for an individual phenomenon (which in fact is not the case). Because SDC describes the "invariants" of the mathematical universe, mutations in individual factors do not destroy the overall structure, but rather demonstrate the flexibility of that structure.Q4. Isn't mixing computational theory, such as P vs. NP, with number theory, such as the Riemann hypothesis, a dimensional inconsistency?[Refuted]That perspective is a "projection bias" trapped in low dimensions.As **Axiom II (Inflationary Projection Axiom)** shows, both computational complexity (P vs. NP) and the zero point distribution (RH) diverge from the same "information geometric structure" at the Planck scale.The SDC equation unifies dimensions by performing limit operations that converge all factors to $M_{\rm Pl}$ (the Planck mass).Q5. What is the purpose of this equation, after all?[Refuted]Please expand your definition of "usefulness."SDC is not a "tool" for solving specific problems, but a "knowledge infrastructure (OS)" that encompasses all challenging issues. This axiom system, released under CC0, prevents the monopolization of knowledge by specific organizations or companies and redefines mathematical truth as "the common property of the universe, accessible to all." This "freedom" is the greatest benefit to humanity.________________________________________📐 Lemma: "Dialogical Closure" in DraftsLemma 7 (Dialogical Self-Duality)The product of a "theory draft" and its corresponding questions and answers converges to the value of the theory itself.$$\text{Draft} \times \text{Dialog} = \text{Truth}$$Therefore, the process of waiting for a final draft is synonymous with "computation" in SDC.________________________________________FAQ: About the Clay/Millennium Integrated SDC Equation (Mirror-Inflation Axiom System)The following is a FAQ to help you understand the "Self-Dual, Completely Closed Integrated Equation." It is organized in the following order: purpose, necessity, strategic justification, axiom system, shortcomings, and correction formulas. It is written concisely and accurately so that it can be used as supplementary material for exhibitions and semi-thesis papers.Q1: What is the "target universe" of this project?A1 (Key Points): The goal is not to solve each Millennium Problem individually. Rather, the goal is to present a high-dimensional cosmological structure that explains "why multiple difficult problems arise simultaneously." Note: Just as Fermat's Last Theorem was solved by shifting the focus from "local number theory problems" to "integrating elliptic curves, modularity, and representation theory," this project aims to construct a high-dimensional integrated structure that generates a "projection of the problem set" and demonstrates that each problem emerges as a result of that projection effect.Q2: Why do Clay's problems seem so separate?A2 (Key Points): All problems are "boundary problems," a list of points where different theoretical domains collide and break down. Examples (corresponding boundaries):• Riemann Hypothesis: The boundary between discrete (prime numbers) and continuous (analysis)• BSD: The boundary between algebraic geometry and analysis• Hodge: The boundary between topology and algebra• Yang–Mills: The boundary between quantum and geometry• Navier–Stokes: The boundary between nonlinearity and regularity• P vs NP: The boundary between constructibility and existence. Conclusion: Attacking the points where different theories "interface" individually will overlook the root cause (the unified structure in higher dimensions) and result in a war of attrition.Q3: Why is the strategy of "only solvable by extended integration" valid?A3 (Key Points): Historically, important problems have been solved by expanding to a larger framework, creating a situation where "the problem itself becomes part of the solution." Rationale: Individual boundary phenomena are projections of a single higher-dimensional structure, so if we construct a projection source (unified structure), the individual problems can be naturally explained as their consequences. Strategic Implication: Rather than pursuing individual proofs, it is more important to formulate common high-dimensional invariants and operators (e.g., C(c), topological invariant ΨLife, etc.) and demonstrate their stability and closure.
Bitcoin Ordinals and inscriptions facilitate the on-chain storage of arbitrary data on the Bitcoin blockchain. In this study, we analyse the impact of inscriptions on the Bitcoin network. We find that inscriptions have significantly increased network activity, created additional demand for blockspace, and influenced Bitcoin’s fee market dynamics. Furthermore, we find that the rise of inscriptions coincided with an increased utilisation of Taproot, a notable increase in block size, and the longest sustained period of high blockspace utilisation in Bitcoin’s history. Our study shows that inscriptions have reshaped how Bitcoin’s blockchain is utilised and underscores the growing number of use cases beyond its original function as a peer-to-peer financial network.
Bitcoin custody systems are designed by individuals with full contextual knowledge and later encountered by others—executors, trustees, attorneys, heirs—who must interpret and operate these systems without the original owner present. This interpretive gap produces recurring failure patterns that persist even when custody components technically exist. This paper presents a taxonomy of failure modes observed in Bitcoin custody systems when those systems are encountered under stress conditions including death, incapacity, device loss, and institutional failure. The taxonomy distinguishes between legal authority and cryptographic access, between security and survivability, and between documentation that enables action and documentation that merely describes existence. Seven failure mode categories are examined: (1) documentation without usability, where correct and comprehensive records nonetheless fail to enable execution; (2) time as an active dependency, where dormant systems degrade through institutional change, memory loss, and technological obsolescence; (3) dependency overlap, where apparently redundant components share hidden common roots; (4) partial access traps, where incomplete recovery attempts constrain or block subsequent paths; (5) authority-access misalignment, where legal entitlement and operational capability diverge; (6) coordination failure, where distributed control prevents action when parties cannot align; and (7) delay-induced state changes, where outcomes differ based on when recovery is attempted. The paper provides canonical vocabulary for professional communication about custody situations and offers a scenario reference for modeling system behavior under stress. It is intended as a descriptive reference for fiduciaries, estate planning attorneys, and advisors who encounter Bitcoin custody systems in professional contexts. The paper does not provide recommendations, evaluate custody arrangements, or establish standards of care.
We present the first application of algebraic topology to smart contract vulnerability detection, demonstrating that reentrancy vulnerabilities correspond to non-trivial first cohomology classes ($H^1 \neq 0$) in the contract call graph. Using the Eden Scanner's Hensel obstruction test, we identified a critical vulnerability in the Inverse Finance FiRM Convex sDola-scrvUSD Market contract (address \texttt{0x63D27fC9d463Ed727676367D3F818999962737E8}) within 48 hours of its addition to the Immunefi bug bounty scope. The vulnerability affects approximately \$605,500 in total value locked and enables direct theft of user collateral through a reentrancy attack via the \texttt{liquidate()} $\to$ \texttt{escrow.pay()} $\to$ callback path. We provide mathematical proof of exploitability through the Regularization Theorem and validate with a fork test against Ethereum mainnet. \end{abstract}
Abstract This article advances the literature on media effects by examining how contrasting partisan narratives influence support for regulation after a real-world corporate scandal. Using both multi-wave observational and randomized experimental data, we show that self-selected media exposure and experimentally assigned information shape public opinion in distinct ways. While scandals are narratives of regulatory failure, partisan media environments differently attribute blame for that failure. In two separate observational waves, only Democrats exposed to news about the FTX bankruptcy increased their support for crypto regulation. In the experiment, only Republicans shifted in favor of regulation. Research on media effects needs to take into account not only media content, but also the partisan information environments that expose citizens to that content.
Mostafa Shabani, Sina Tavakoli, Hossein Ghanbari, Ronald Ravinesh Kumar · 5 authors
The acceleration of financial innovation and pro-crypto regulations in the digital asset space have spurred interest in cryptocurrencies among funds, and institutional and retail investors. Like any risky assets, investment in digital assets offers opportunities in terms of returns and challenges in terms of risk. However, unlike traditional assets, digital assets like cryptocurrencies are highly volatile. Accordingly, applying conventional single-criterion financial metrics for portfolio construction may not be sufficient as the method falls short in capturing the complex, multidimensional risk-return dynamics of innovative financial assets like cryptocurrencies. To address this gap, this study introduces a novel, integrated hybrid Multi-Criteria Decision-Making (MCDM) framework that provides a structured, transparent, and robust approach to cryptocurrency fund selection. The framework seamlessly integrates three well-established operations research methodologies: the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytic Network Process (ANP), and the Vlse Kriterijumsk Optimizacija I Kompromisno Resenje (VIKOR) algorithm. DEMATEL is utilized to map and analyze the intricate causal interdependencies among a comprehensive set of evaluation criteria, categorizing them into foundational “cause” factors and resultant “effect” factors. This causal structure informs the ANP model, which computes precise criterion weights while accounting for complex feedback and dependency relationships. Subsequently, the VIKOR algorithm is invoked to use these weights to rank cryptocurrency fund alternatives, delivering a compromise between optimizing group utility and minimizing individual regret. To illustrate the application and efficacy of the proposed method, a diverse set of 20 cryptocurrency funds is analyzed. From the analysis, it is shown that foundational criteria, such as “Fee (%)” and “Annualized Standard Deviation,” are the primary causal drivers of financial performance outcomes of funds. This proposed framework supports strategic capital allocation in a rapidly evolving domains of digital finance.
This paper examines human resource management (HRM) practices in Ghana's local government and advances a twofold argument. First, it shows that decentralization reforms introduced in the 1980s and 1990s locked the system into a path-dependent governance trajectory. This has narrowed the scope for alternative approaches to achieving an effective HRM system. Second, despite formal provisions establishing local governments as autonomous and non-partisan, the findings reveal that informal norms, political patronage, and asymmetric power relations remain central in shaping HRM decisions. These realities affect staff motivation, retention, and organizational performance, often impairing formal HR procedures and meritocratic intent. The paper challenges taken-for-granted assumptions that implementing cookbook governance and/or new public management prescriptions can automatically improve institutional effectiveness and service delivery in developing countries. Instead, it argues for greater attention to historical legacies and political contexts. The paper contributes to scholarly debates on public sector management and state capacity by highlighting the limits of technocratic and one-size-fits-all approaches to strengthening subnational governance
Aleksei Adadurov, S. Barseghyan, Anton Chtepine, Antero Eloranta · 6 authors
This paper examines the impact of reducing Ethereum slot time on decentralized exchange activity, with a focus on CEX-DEX arbitrage behavior. We develop a trading model where the agent's DEX transaction is not guaranteed to land, and the agent explicitly accounts for this execution risk when deciding whether to pursue arbitrage opportunities. We compare agent behavior under Ethereum's default 12-second slot time environment with a faster regime that offers 1-second subslot execution. The simulations, calibrated to Binance and Uniswap v3 data from July to September 2025, show that faster slot times increase arbitrage transaction count by 535% and trading volume by 203% on average. The increase in CEX-DEX arbitrage activity under 1-second subslots is driven by the reduction in variance of both successful and failed trade outcomes, increasing the risk-adjusted returns and making CEX-DEX arbitrage more appealing.