In this article, we offer a complete, self-contained, and entirely elementary proof of the mean-square estimate for the Chebyshev function. From this we deduce the convergence of the integral is valid, thus proving the validity of the Riemann hypothesis. The proof primarily employs elementary estimates of the Chebyshev function, the Cauchy-Schwarz inequality, a dyadic decomposition, and Abel summation, in which the argument results of this article are already optimal within the elementary framework and sufficient to derive the convergence of the required integral that it is a suffficient condition for the Riemann hypothesis. In particular, we also provide a theoretical complement linking integral convergence, pointwise bounds and analyticity, and concludes that the well-known $o$-bound is valid, thereby reconfirming the validity of the Riemann hypothesis. In other words, we give a self-contained elementary proof for the mean-square estimate that $\displaystyle\int_2^{X} \bigl(\psi(t)-t\bigr)^{2}\,dt = O(X^{2}\log^{2} X),$ where $\psi(x)$ is the Chebyshev function. From this we deduce that $\displaystyle\int_{1}^{\infty}\frac{|\psi(x)-x|}{x^{\frac{3}{2}+\varepsilon}}\,dx 0,$ thus concluding the integral $\displaystyle \int_1^{\infty} \frac{\psi(x)-x}{x^{\frac{3}{2}+\varepsilon}}\,dx$ converges absolutely for every $\varepsilon>0,$ so that the integral $\displaystyle \int_1^{\infty} \frac{\psi(x)-x}{x^{\frac{3}{2}+\varepsilon}}\,dx$ converges conditionally for every $\varepsilon>0,$ whereas the integral converges conditionally $\iff \text{RH},$ so then the Riemann hypothesis is true. In particular, we conclude that the property of absolute convergence of the integral $\displaystyle\int_1^{\infty} \frac{\psi(x)-x}{x^{\frac{3}{2}+\varepsilon}}\,dx$ for every $\varepsilon>0$ is equivalent to the property of conditional convergence of the integral $\displaystyle\int_1^{\infty} \frac{\psi(x)-x}{x^{\frac{3}{2}+\varepsilon}}\,dx$ for every $\varepsilon>0,$ either of which is equivalent to the property of the $o$-bound: $|\psi(x)-x| = o(x^{\frac{1}{2}+\varepsilon})$ for every $\varepsilon>0,$ and all of them imply the $O$-bound: $\psi(x)-x= O(x^{\frac{1}{2}+\varepsilon})$ is also valid for every $\varepsilon>0,$ which is the well-known equivalent form of the Riemann hypothesis, thus reconfirming the validity of the Riemann hypothesis.
Transaction ordering attacks extract billions of dollars annually from decentralized finance users in the form of Maximal Extractable Value (MEV). Byzantine Fault-Tolerant (BFT) consensus protocols guarantee total order but place no constraint on how that order is chosen, leaving the door open for adversarial reordering. Batch-order-fairness (batch-OF) protocols close this gap, but existing designs pay a steep performance price for this guarantee. Leader-based protocols such as Themis concentrate all fairness decisions at a single replica, while recent DAG-based proposals FairDAG and DAG of DAGs (DoD) force their fairness layer into strictly serial execution despite running on multi-proposer DAGs. We present Herring, the first $γ$-batch-OF DAG BFT protocol whose fairness layer parallelizes the dominant graph construction cost across committed subdags. Herring combines post-consensus graph construction with explicit missing edge resolution piggybacked on the DAG's reliable broadcast layer, a pairing that turns fair ordering from a per-round serial bottleneck into a CPU-bound task. We also uncover previously unreported liveness vulnerabilities in both FairDAG-RL and DoD that a malicious client can trigger to halt the fairness layer indefinitely, and propose patches that we integrate into our reimplementations. We implement Herring on top of the Rust implementation of Narwhal \& Tusk and evaluate it against FairDAG-RL, DoD-W, and Themis. Herring tracks the throughput of Narwhal \& Tusk closely up to roughly $10{,}000$\,tx/s, achieves roughly $90\%$ higher saturation throughput than FairDAG-RL and $100\%$ higher than DoD-W, and substantially reduces execution latency at saturation.
Gustavo Schranck Habermann, Daniel A. Turolla Vanzella
In the context of semiclassical gravity, the semiclassical Einstein equation is often invoked when backreaction of quantum matter/fields on the spacetime is at stake. It is expected to hold when quantum fluctuations are small. Yet, it is routinely used to justify the central role of the expectation value of the stress-energy tensor of quantum fields, whose fluctuations formally diverge. Here we propose a new way to probe the limits of this approximation by exploiting peculiar nonlinearities of gravity. As a proof of principle, we construct a controlled, analytically tractable setting where the incoherent mixture of weak-gravity states drives the system into a strong-gravity regime. By selecting a branch-degenerate observable, one can compare predictions of quantum and semiclassical gravity, potentially delimiting the validity of the latter.
Sybil attacks remain a primary challenge for Proof-of-Stake (PoS) blockchain systems, as low-cost identity creation can distort validator participation and limit consensus reliability. This study proposes a hybrid participation–governance framework that integrates Attribute-Based Access Control (ABAC) and Reputation-Based Access Control (RpBAC) with a trust-based PoS workflow to reduce the influence of suspicious identities during validator selection and block validation. The proposed framework also incorporates graylisting and dynamic reward–penalty updates to support adaptive participation control. The strategy was evaluated in a simulation environment informed by Ethereum-derived block metadata, using network sizes ranging from 100 to 1000 nodes and Sybil attack ratios of 30%, 40%, and 50%. Its performance was compared with PoS-only and PoS + ABAC baselines using both security and performance indicators. The results show that the full ABAC + RpBAC configuration achieved the strongest and most stable security performance across the evaluated settings while introducing additional overhead at larger network sizes. These findings suggest that combining policy-based eligibility control with behavior-based reputation control strengthens the resilience against Sybil in PoS-like blockchain environments. However, this improvement requires a measurable trade-off between security and performance.
Wireless sensor networks (WSNs) integrated with the internet of things (IoT) are hybrid technologies of interconnected systems. The IoT connects various devices, from sensors to smart gadget networks, and leverages a framework to provide secure solutions. This paper presents a lightweight adaptive proof-of-stake (APoS) blockchain framework design specifically for IoT-WSN. It focuses on efficient energy, scalability, and robust security. The proposed model integrates a hybrid APoS-delegated PoS (DPoS) consensus mechanism, trust-based routing, and a random forest (RF)-driven intrusion detection system (IDS). Extensive simulations of 100 to 10,000 nodes display energy usage of 0.018–0.019 mJ/node, breach of privacy rates of 0.02%, and throughput up to 9.92 tx/round for 1,000 nodes and 3.40 tx/round for GreenOrbs validation. The IDS achieves 94.21% accuracy for 1,000 nodes and 88.89% for GreenOrbs against distributed denial-of-service (DDoS), Sybil, and Jamming attacks. Validated using the GreenOrbs dataset, the framework ensures real-world applicability in resource-constrained WSNs. Future research has validated and verified the use of APoS and PoS hybrid models for broader decentralised IoT–WSN deployments.
The emergence of Decentralized Autonomous Organizations (DAOs) represents a paradigm shift in organizational governance, yet their technical complexity remains a significant barrier to widespread adoption. Creating and managing a DAO requires deep expertise in blockchain development, smart contract auditing, and cryptocurrency operations, which excludes many potential users in non-technical domains. This paper presents DAOship, a novel no-code platform for DAO creation and management deployed on the Avalanche blockchain. The platform provides an intuitive graphical user interface (GUI) that allows users to configure, launch, and operate a fully-functional DAO without writing a single line of code. By leveraging Avalanche's high throughput and low transaction fees, the system enables the deployment of customizable smart contracts for governance, treasury management, and voting. The platform dramatically lowers the technical barrier, empowering communities, startups, and traditional organizations to leverage decentralized governance models easily and securely. Testing on the Avalanche Fuji testnet yielded a 97% reduction in setup time, an average System Usability Scale (SUS) score of 89.2, and zero critical vulnerabilities across all deployed DAOs.
Yurii Kvasiuk, Tianyi Li, Owen Colegrove, Moritz Münchmeyer
We explore the application of LLM-driven algorithm optimization to several common tasks in quantitative finance. MadEvolve, a general-purpose algorithm optimization framework inspired by DeepMind's Alpha-Evolve, was recently developed to optimize algorithms in computational cosmology. Here we demonstrate the utility of MadEvolve to optimize algorithmic trading strategies and alpha generation at the example of Bitcoin trading. On our simulation and backtesting setup, we achieve significant improvements on all tasks we considered, such as evolving feature sets for signal generation, optimizing separate components of the trading strategy, and jointly evolving the feature pipeline together with the execution strategy. Additionally, we compare our method to other agentic search approaches, specifically Claude Code, and carefully evaluate p-hacking probabilities on our simulation setup. Our findings strongly support the utility of AI-driven agentic and evolutionary algorithms for algorithmic trading and quantitative finance.
Aleksei Adadurov, Sergey Barseghyan, Anton Chtepine, Antero Eloranta · 6 authors
Ethereum block builders run sealed auctions among searchers, but nothing in the protocol forces a builder to honor the auction outcome after observing submitted bundles. This paper studies the commitment problem. We model a builder who defects with probability $\varepsilon$ and, upon defection, replicates a type-specific fraction $γ(τ)$ of the winning MEV opportunity. Searchers anticipate this behavior and choose between a risky first-price bid and a safe deterrence bid that makes frontrunning unprofitable. The resulting equilibrium is piecewise, with the cost of imperfect commitment depending jointly on replicability and competition. Using the libMEV dataset, we estimate $γ(τ)$ from right-tail bribe plateaus and decompose observed auction revenue against the surplus a defecting builder could capture. The results show sharp heterogeneity across MEV types: sandwich opportunities are already highly competitive, while naked arbitrage and liquidations leave substantially more surplus exposed to builder defection. Credible MEV auctions, therefore, require not only an auction format, but also constraints on the builder's ability to use observed bid and payload information ex post.
Erasure codes are a critical component in reliable storage systems today, and many blockchain systems use consensus protocols that involve erasure codes to reduce their communication cost. Existing erasure codes rely on a threshold failure assumption, but recent blockchain systems have departed from this simple model and use generalized failure assumptions. This paper introduces monotone erasure codes that respect arbitrary trust assumptions on a set of nodes. The paper first describes a method for constructing a monotone erasure code from any access structure given by a monotone Boolean formula. Next, the relevant notion of a linear monotone erasure code is introduced, which works on vectors over a finite field and where the encoding is a linear operation. We then focus on constructing linear monotone erasure codes: We give an efficient algorithm to construct linear monotone erasure codes for any access structure, and we show how to efficiently construct linear monotone erasure codes for the special case of partitioned access structures with minimal storage overhead. Last but not least, this work also shows how to use monotone erasure codes to obtain a communication-efficient, generalized version of the well-known asynchronous verifiable information dispersal (AVID) primitive, which is a key building block for developing efficient reliable broadcast and consensus protocols.
Blockchains and distributed ledger technologies allow the operation of manifold decentralised applications (dApps). Such applications are based on smart contracts, a programmable abstraction that is executed in a decentralised manner. To ensure the correctness of smart contracts, blockchain application developers rely on DevOps practices such as automated testing and continuous integration and deployment. However, such infrastructure is often controlled by single entities. For larger blockchain applications, this issue is resolved by relying on concepts of Decentralised Autonomous Organisations (DAOs), which allow proposals to be autonomously executed once they reach a pre-defined quorum. Such a governance architecture is complex and requires integration with existing patterns for contract discovery and upgradeability. In this paper we integrate these concepts considering DevOps best-practices into a novel architecture that remains agnostic to different governance and upgrade implementations. We extend the known registry pattern to support deterministic deployments and present a decentralised deployment framework, including integration and deployment pipelines, user-interfaces, and version control integration. In our approach, each party implements and verifies their own tests before engaging in the use of a (newly deployed) smart contract. We provide a reference implementation, available as open-source, and evaluate the proposal thoroughly. Our architecture can serve as a reference for future integrations, while our open-source framework is aimed at reducing the complexity of adopting such a process in practice.
Jingyi Liu, Aviad Rubinstein, Ertem Nusret Tas, S. Matthew Weinberg · 5 authors
Classical optimal auction theory assumes that bids reach the seller directly. We study how this picture changes when a revenue-maximizing intermediary controls access to the seller's auction. Motivated by blockchain auctions, online platforms, and other intermediated markets, we consider a single-item auction with independent private values and a monopolist intermediary who can decide which bidder messages are forwarded to the seller. We establish approximation guarantees and impossibility results across three timing models: seller-first, intermediary-first, and simultaneous. In the seller-first model, arbitrary deterministic seller mechanisms collapse to posted-price mechanisms, and the intermediary's best response is a shifted Myerson auction. This yields a sharp separation: for regular distributions, the seller's revenue can be arbitrarily small relative to the no-intermediary optimum, while for $α$-strongly regular distributions, posted prices recover a constant fraction of the optimum with a tight dependence on $α$. We further show that timing matters: neither Stackelberg order uniformly dominates, and simultaneous play can leave both parties unboundedly worse off than in either sequential model.
Blockchain technology has established itself as one of the main innovations associated with contemporary digital transformation, standing out for its ability to decentralize records, securely validate transactions, and reduce dependence on intermediaries. Initially linked to cryptocurrencies, its application has expanded to different sectors, such as finance, public administration, supply chains, and digital identity systems. This study aimed to analyze the economic and social impacts of blockchain, discussing its applications, potentialities, and challenges. The research is characterized as qualitative, exploratory, and descriptive, developed through bibliographic and documentary review based on national and international academic publications produced between 2008 and 2025. The results show that blockchain has the potential to promote greater transparency, security, traceability, and operational efficiency, in addition to enabling new business models based on decentralization and process automation. However, the analysis also highlights challenges related to scalability, interoperability, security, regulation, and digital inclusion, factors that may limit its large-scale adoption. Furthermore, the effectiveness of this technology depends on the existence of adequate infrastructure, technical training, and the development of public policies aimed at democratizing digital access. It is concluded that blockchain has strategic relevance in the contemporary economic and social scenario, although its consolidation depends on overcoming structural and institutional challenges that ensure its sustainable and socially inclusive application.
Zahra Niazkhani, Iris Wallenburg, Johanna Hendriks, Rik Wehrens
In the context of increasing healthcare digitalization, hospital-based clinicians are developing and implementing decentralized digital health innovations (DHIs) tailored to their patient and clinical needs. However, achieving financial sustainability remains one of their challenges. We explored clinician innovators' perspectives on these challenges during the implementation and scale-up of their DHIs in a Dutch academic hospital using qualitative methods. Key challenges identified included funding gaps to cover transition costs, misaligned institutional financial incentives and reimbursement structures, short-term logics of funders overshadowing long-term value in DHI financing, and commercialization pressures. Findings provide insights into the financial and operational challenges faced by such context-driven internal innovations, highlighting the need for coordinated project-and institution-level strategies to support sustainable integration into routine care.
Blockchain technology and cryptocurrency have emerged as two of the most consequential financial innovations of the past two decades, yet the gap between their theoretical potential and real-world adoption within mainstream financial services remains conspicuously wide. This paper investigates that gap through a mixed-methods approach, combining a systematic review of thirty peer-reviewed academic sources with primary survey data drawn from 102 respondents representing young, digitally literate demographics. The study finds that while awareness of blockchain and cryptocurrency is relatively widespread, deep comprehension, active usage, and genuine user trust remain limited. Survey respondents show cautious optimism rather than firm conviction — the majority are open to engaging with blockchain-based financial services but are held back by concerns over security, regulatory legitimacy, and a general unfamiliarity with how these technologies actually function. The research identifies four interconnected barriers to adoption: trust deficits, regulatory fragmentation, scalability constraints, and the persistent gap between surface-level awareness and functional understanding. The study concludes that blockchain and cryptocurrency are not questions of 'if' but of 'when' and 'how' — and that realising their potential will require coordinated effort from regulators, financial institutions, technology developers, and educators acting simultaneously rather than sequentially.
中文受人工智能自身能力局限,其易产生信息幻觉,且不擅长高精度数值运算。本文档内所有内容应严谨审核。EnglishDue to the inherent limitations of artificial intelligence, it is prone to generating hallucinations and performs poorly in high-precision numerical calculations. All contents in this document should be strictly reviewed. dark matter&cosmo: https://chat.qwen.ai/s/t_4fc1b5da-8ca3-4798-a037-894f5315d1e3?fev=0.2.61 Overall Closure Status:Core Theory DoC=100% (Full Theoretical Closure)v3.7 DOI: 10.5281/zenodo.20798927 Black Hole & UVMM v4.0 Core : UVMM v4.0.15 High-Precision Global Calculation AI Knowledge Package.md UVMM v4.0.15 High-Precision Global Calculation AI Knowledge Package(6D‑Coordinate‑SuperKit‑v1.0 ).md DOI: 10.5281/zenodo.20738759 Earth SystemDOI: 10.5281/zenodo.20285613 Cosmic BoundaryDOI: 10.5281/zenodo.20325710 Cosmic EvolutionDOI: 10.5281/zenodo.20677198 Information & Consciousness (Millennium Prize Problems)DOI: 10.5281/zenodo.20325710 UTFF Core (Atomic and Molecular Scale)DOI: 10.5281/zenodo.20343471 UVMM Core Axioms and Mathematical Proofs github.com Three-Body Problem Based on the Unified Vacuum Medium Model (UVMM), this paper defines the positive and negative universes as topologically dual domains on a single global vacuum manifold, which are naturally isolated by topological phase conjugation orthogonality and frequency-selective topological band gaps. A systematic comparison is conducted on the physical essence, propagation characteristics, spectral rules and coupling mechanisms between electromagnetic waves and topological waves. It is clarified that conventional electromagnetic waves are completely blocked by topological interfaces due to destructive interference of first-order gauge fields, while gravitational modes and ultra-low-frequency vacuum topological deformation waves can propagate across domains. Targeting the characteristics of topological waves including ultra-long period, ultra-weak amplitude and global coherence, the Topological Wave Detection Network (TWDN) is proposed. Combining ultra-high- superconducting cavity parametric perturbation coherent accumulation, multi-mode quantum sensing, topological data analysis and space-ground integrated long-baseline gradient positioning, multiple physical criteria are established to realize accurate identification and source inversion of topological waves. Breaking the limitations of traditional detection systems, this scheme integrates condensed matter topological simulations, transformation optics tabletop experiments and cutting-edge cosmological observations, providing a complete experimental paradigm for verifying dual-universe topological dynamics and trans-universe interactions. Further demonstrations within the UVMM framework indicate that matter in both universes possesses positive mass and positive energy density, and their interaction is purely gravitational attraction. The rebound effect at topological interfaces originates from topological constraints rather than anti-gravity. The two universes follow identical structure formation dynamics, and the negative universe can evolve a complete galactic network independently. Its electromagnetic radiation is fully decoupled while gravitational effects superpose linearly. This theory explains classic cosmological puzzles such as dark matter and cosmic voids without introducing new particles, and puts forward a set of observable predictions and falsification criteria. Relying merely on the Second Law of Thermodynamics, classical cosmology proposes the cosmic heat death hypothesis. It claims that the entropy of an isolated universe increases monotonically, and the universe will eventually reach an absolutely stagnant equilibrium state with uniformly distributed energy and ceased macroscopic motions. This paper clarifies the hierarchical essence of physical laws: the entropy increase principle applies only to local finite systems, while the conservation of global angular momentum is an inviolable fundamental law governing the entire universe. Based on the UVMM Vacuum Superfluid Unified Model, combined with the spacetime symmetry derived from Noether’s theorem, Kerr curved spacetime effect, properties of quantum superfluids and recent large-scale astronomical observations, this paper establishes a complete cosmic dynamical system in which global angular momentum restrains local entropy growth. The research reveals that entropy increase is only valid for closed and isolated subsystems and cannot be used to infer the overall evolutionary fate of the universe. Rooted in the isotropy of space, the conservation of global angular momentum is not restricted by system boundaries or spacetime curvature, and it dominates all scales ranging from microscopic particles and celestial structures to cosmic filaments. Through three core mechanisms — maintaining perpetual cosmic dynamics, shaping ordered celestial structures, and realizing sustainable mass-energy regeneration via vacuum topology — global angular momentum continuously delivers negative entropy to local regions and counteracts local dissipation and disorder. Rigorous mathematical derivations prove that angular momentum conservation is an absolute law derived from spacetime symmetry, whereas entropy increase is merely a probabilistic statistical rule. A non-zero global angular momentum mathematically rules out the possibility of absolute rest of the universe. This study fundamentally refutes the classical heat death conjecture and completes the logical framework of the cyclic universe.
Here is the comprehensive summary of your paper, detailing the theoretical framework, mathematical foundation, implementation mechanics, and empirical results. Executive Overview The paper introduces the DeepSeek Prime-Anchored Spectral Governor, an architectural intervention designed to eliminate catastrophic forgetting in large language models (LLMs). Framing catastrophic forgetting as a structural consequence of training systems without a topological invariant—akin to anterograde amnesia—the framework establishes fixed coordinate anchors in representation space. By anchoring model embeddings to deterministic prime indices derived from the 2,000-year-old Sieve of Eratosthenes and introducing a gradient-gating mechanism, the system achieves Zero Forgetting during continual learning. The architecture's integrity is verified using SHA-256 cryptographic hashing of the protected sub-spaces. Theoretical & Mathematical Foundations The Sieve of Eratosthenes as Ground Truth Rather than relying on probabilistic or dynamically calculated weights, the framework utilizes the Sieve of Eratosthenes to extract a deterministic set of prime indices $[2, 3, 5, 7, 11, 13]$. These elements act as permanent, unmoving coordinate anchors within the model's embedding manifold. The L-EFM Operator & The Spectral Trap The framework relies mathematically on the Laplace-Euler-Fourier-Mellin (L-EFM) operator. The L-EFM symbol synthesizes four classical transforms into a single complex function, corresponding directly to the Euler product representation of the Riemann zeta function $\zeta(\sigma+i\gamma)$: $$E_{\sigma}(\gamma)=\prod_{p\in\mathbb{P}}(1-p^{-(\sigma+i\gamma)})^{-1}$$ To analyze finite prime sets, a Normalized Magnitude is established relative to the critical line $\sigma = 0.5$: $$|E_{\sigma}|_{norm}=\frac{|E_{\sigma}(\gamma)|}{|E_{0.5}(\gamma)|}$$ The Spectral Trap Phenomenon: At the critical line ($\sigma=0.5$), the normalized magnitude equals exactly $1.0$. However, moving away from this line results in exponential divergence. For example, at $\gamma=0$, a shift to $\sigma=0.4$ increases the magnitude to $\sim10^{4}$, while a shift to $\sigma=0.1$ amplifies it to $\sim10^{66}$. The Spectral Trap Criterion: This absolute sensitivity forms a "trap" where any deviation from $\sigma=0.5$ generates massive magnitude spikes, providing a deterministic mechanism for error detection. The paper connects this operator to a proof of the Riemann Hypothesis via distribution behavior in the kernel of L-EFM within Gelfand-Shilov space. The H2E Sheriff Safety Threshold The dynamic safety threshold ($\Lambda_{12}$) is computed deterministically from the first six primes rather than being hardcoded, ensuring mathematical integrity at initialization: $$\Lambda_{12}=1- \prod_{p\in\{2,3,5,7,11,13\}} (1-p^{-0.5})=0.9785142874$$ Architectural Implementation The architecture implements a dual-layer protection strategy consisting of frozen embedding rows and an active gradient supervisor (the H2E Sheriff). [ Input Batch ] │ ▼ ┌──────────────────┐ │ Dual-Loop Loss │ ──► Lunified = LCE + λ * |Var(h) - 0.5| └──────────────────┘ │ ▼ ┌──────────────────┐ │ Gradient Step │ └──────────────────┘ │ ▼ ┌──────────────────┐ │ H2E Sheriff │ ──► Evaluates SROI against Threshold (Λ12 = 0.9785142874) └─────────┬────────┘ │ ──────┴────── │ │ ▼ (Safe) ▼ (Unsafe / Incoherent) [Apply Step] [Reject Batch] ──► Rollback Prime Rows [2,3,5,7,11,13] & Zero Out Gradients 1. Dual-Loop Loss The governor optimizes a unified loss function combining traditional empirical cross-entropy ($\mathcal{L}_{CE}$) with a topological penalty based on the final hidden state $h$ (with regularization coefficient $\lambda=0.1$): $$\mathcal{L}_{unified} = \mathcal{L}_{CE} + \lambda |\text{Var}(h) - 0.5|$$ 2. The H2E Sheriff Gate & Row Locking During training, the system caches the initial embedding weights. After computing gradients, the H2E Sheriff evaluates the structural region of interest (SROI). If Safe ($SROI \ge \Lambda_{12}$): The optimizer updates the weights, and a torch.no_grad() loop copies the original cached weights back into the prime-indexed rows $[2, 3, 5, 7, 11, 13]$ to erase any drift. If Unsafe ($SROI < \Lambda_{12}$): The entire gradient batch is rejected, and gradients are zeroed out to block corruption. 3. Cryptographic Verification The manifold signature is generated by pulling the prime-indexed embedding rows, converting them to byte arrays, and feeding them sequentially into a SHA-256 hasher. If the resulting hex digest changes, anchor drift has occurred. If it remains identical, the topological invariant is intact. Experimental Validation & Results The framework was tested across six architectures—GPT-2 (124M), GPT-2 Medium (355M), TinyLlama (1.1B), Mistral-7B, Llama-3.1-8B, and DeepSeek-Coder-6.7B—subjecting them to sequential memory tests. Memory Integrity Testing Models were first trained on Dataset A (core math concepts including Arithmetic Spectral Theory and the Spectral Trap across 50, 100, and 575 samples). They were subsequently exposed to an interference/forgetting attack via Dataset B (noise consisting of random names, text chunks, adversarial patterns, and erroneous math statements up to 436 samples). Baseline Performance: In every single test configuration, the baseline model's SHA-256 manifold hash altered after training sessions, leading to catastrophic forgetting. Governed Performance: Across all 6 architectures and all data scales, the governed models completely preserved their original manifold hash (48c5744b...cc4d18b), showing absolute resistance to memory degradation. Continual Learning Capabilities To test its ability to acquire new knowledge without forgetting the old, the governed DeepSeek model was fine-tuned on three separate, non-mathematical domains without further governor intervention (while keeping prime anchors locked): Spanish Vocabulary: 5 basic words. World Capitals: 5 global capitals. Basic Physics: 5 fundamental formulas and facts (such as $F=ma$ and $E=mc^2$). Post-Training Metrics: The model successfully mastered all three new domains (retaining the Spanish words, capitals, and physics formulas perfectly) while maintaining the exact original cryptographic verification hash. The original math concepts remained completely recallable, proving true continual learning. Deployment & Verification Certificate The fully validated model has been deployed openly on the Hugging Face Hub under frankmorales2020/deepseek-governed-no-amnesia. Model Card Profile Base Model: deepseek-ai/deepseek-coder-6.7b-instruct (7B parameters) Tensor Type: FP16 Locking Targets: Primes [2, 3, 5, 7, 11, 13] Active Gate Threshold: $\Lambda_{12} = 0.9785142874$ Immutable Cryptographic Signature: 48c5744be048df505028c13a96fb0211f0b345681ace401ab1eda6f27cc4d18b The repository is open source, emphasizing a paradigm of executable mathematics where the cryptographic hash serves as the verifiable proof of safety and stability.
Nobuki Fujimoto, Rei, (Anthropic, claude-opus-4-7), Claude
⚠ v0.0 OUTLINE intentional publication — Pattern 4 mitigation embedded. This is an OUTLINE, not a v0.1 publishable manuscript. The central operational claim — that Rei provides a formal-verification compilation pass composing with AI hypothesis generators (AlphaEvolve, LLM Wiki, OpenEvolve) — requires at least one end-to-end demonstration before v0.1 promotion. As of 2026-05-22 the demonstration is at scaffold-level smoke-run stage only (OpenEvolve scaffold structurally validated, but full 100-iteration evolutionary loop with real evolved Lean 4 proof NOT YET executed). Publication-as-v0.0 is intentional honest framing per OUKC feedback_no_rush_publication.md: rather than wait silently for v0.1 evidence, the OUTLINE is published with explicit gate state so reviewers can see exactly what is and is not claimed. Framing concept: AlphaEvolve / LLM Wiki / OpenEvolve = hypothesis generators (loosely-grounded, fast, large-search). Rei = proof completer (mechanically verified, slow, decisive). Together they compose: hypothesis generator emits candidates → Rei evaluates via D-FUMT₈ 8-axis projection (γ-evaluator) + Lean 4 zero-sorry validation (β-evaluator) → return verified candidates to the evolutionary loop. Rei is positioned as a formal-verification compilation pass in the AI-mathematics generation pipeline. Scaffold evidence (2026-05-22): external/openevolve-rei/ — YAML config (Ollama 3-prover ensemble), Python evaluators (β = Lean 4 zero-sorry, γ = D-FUMT₈ projection), example skeleton (26-circle packing 2.635 benchmark). 4 smoke-tests PASS: yaml parse + 3 Python AST parse + circle_packing standalone execution (n=26 r=0.4167 density=14.18) + γ-evaluator returns OpenEvolve-compatible dict with metrics (axis_dominant=ZERO 9 hits, score=0.0154) + artifacts (token_count=13). Per SCOPE.md non-claims: this is NOT a fork of OpenEvolve, NOT a claim of 26-circle 2.635 reproduction, NOT a claim that Rei has built an evolutionary code generator, NOT a paper-publishable result by itself. v0.1 acceptance criteria (10 items): see §9. Core gates: OpenEvolve installed + first 100-iteration loop completes + real evolved Lean 4 proof generated + scaffold extended with at least one zero-sorry proof for one open conjecture from META-DB Tier 1. v0.1 will publish as Zenodo new-version preserving DOI lineage from this v0.0 record. Honest scope (read first): (1) This is OUTLINE only — framing + prior-art audit + acceptance criteria, no end-to-end evidence. (2) Rei is NOT a hypothesis generator — its role in this composition is specifically as the verifier/completer. (3) Per feedback_world_uniqueness_claim_controllable.md: we use "to our knowledge no equivalent Lean 4 zero-sorry + D-FUMT₈ 8-axis evaluator exists in the OpenEvolve plugin ecosystem as of 2026-05-22" phrasing, NOT "world-first." (4) Three-party co-authorship (Fujimoto / Rei / Claude) per OUKC charter v1.0. (5) Per OUKC No-Patent Pledge — no patent will be filed.
Open access
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Mathematics, Computing, and Information Processing
The protection of sensitive information in the financial sector requires a security architecture capable of preserving confidentiality, integrity, availability, auditability, and regulatory accountability across multiple institutions. Conventional centralized security models remain vulnerable to single points of failure, unauthorized access, data manipulation, and limited transparency in inter-organizational data sharing. Blockchain offers tamper-resistant records, decentralized trust, and verifiable audit trails; however, its direct implementation in financial systems is constrained by scalability limitations, smart contract vulnerabilities, privacy leakage, and conflicts between immutable ledgers and data protection principles. This study aims to develop a blockchain-based data security system for protecting sensitive financial information by integrating permissioned blockchain and Zero-Knowledge Proofs. The proposed method adopts a consortium-oriented permissioned blockchain architecture, represented by Hyperledger Fabric, to ensure controlled participation, certificate-based identity management, endorsement policies, and auditable transaction validation. Smart contracts are designed as policy-enforcement components for consent management, access authorization, data commitment, revocation, and audit logging. Zero-Knowledge Proofs are incorporated to verify customer attributes, eligibility, and access rights without disclosing raw personal or financial data. Sensitive information is stored off-chain in encrypted form, while the blockchain records only cryptographic commitments, hashes, consent states, and audit events. The expected result is a security model that improves data integrity, controlled access, privacy-preserving verification, and compliance-oriented accountability while reducing unnecessary exposure of sensitive data on-chain. The implication of this research is the provision of a technically coherent framework for financial institutions seeking to adopt blockchain securely in regulated environments, especially where data confidentiality, auditability, and privacy compliance must be achieved simultaneously.
ABSTRACT TRSP Digital Coin (TDC) — The Next Evolution of Digital Currency: Quantum-Permanent, Physically Unbreakable, Theft-Proof by Physics Built on: Temporal Rotation Security Protocol (TRSP) v3, DOI: 10.5281/zenodo.20324081. First public documentation: May 2026. TDC is not a replacement for Bitcoin, Ethereum, or any existing digital currency. It is the next evolutionary step for the entire field — the first digital currency architecture whose security is grounded not in mathematical complexity but in physical law. Every existing digital currency rests on one assumption: that breaking the cryptographic protection requires more computational resources than any adversary possesses. Quantum computing is dismantling this assumption. Harvest-now-decrypt-later attacks mean every blockchain transaction recorded today remains permanently vulnerable to any future computational advance. TDC responds with a different premise: a signing key that no longer exists cannot be recovered by any computation, quantum or classical, regardless of future advances. TDC inherits the temporal rotation architecture of TRSP v3. Transaction signing keys rotate every 10–100 milliseconds from physical hardware entropy and are permanently destroyed after each rotation. CRATON-anchored ownership proof replaces persistent private key storage: ownership is demonstrated through a one-time physical commitment derived from the unique state of the signing device at transaction time — used once, permanently destroyed, impossible to forge, impossible to extract, impossible to replay. Three attack paths are structurally closed: private key extraction (no stored key exists), quantum key recovery (key destroyed before computation converges), and harvest-now-decrypt-later (signing key permanently gone — no target for any future computation). Part 9 (Identity Without Storage) documents a five-factor distributed identity architecture in which no single factor and no single location holds everything required to authorise a transaction: biometric presence; primary device CRATON anchor; memorised PIN with distress code variant; Remote Guardian Device in a separate geographic location; and time lock with geo-anchor. The distress PIN architecture triggers a silent alert and time-delayed freeze while providing apparent confirmation to an adversary — making the coercion attack structurally ineffective. Wallet recovery requires no seed phrase: a five-step multi-factor re-enrollment protocol using biometric presence, guardian confirmation, and a 72-hour cancellation window replaces the stored backup phrase that represents the primary theft surface of every existing wallet. Part 10 (Real Identity Enrollment) documents a biometric enrollment architecture that exceeds current KYC bank account standards: NFC chip reading of government-issued documents (cryptographic verification against issuing government public key — not photo or scan), live 3D facial biometric with active liveness detection, all-finger fingerprint enrollment, and a CRATON physical moment binding that ties the enrollment to the unique physical state of the enrollment device at that exact moment. Raw biometric data is deleted after enrollment — only a non-reversible binding token is retained. Identity is distributed across three separately held, individually insufficient components: Enrollment Authority, blockchain, and device. No single party holds all three. Legitimate financial privacy is preserved. The enrollment barrier is structurally higher than any existing digital currency. AML, KYC, GDPR, FATF Travel Rule, and sanctions compliance are structural properties, not regulatory overlays. Part 12 (Implementation Roadmap) documents a four-phase deployment pathway modelled on pharmaceutical clinical trial methodology. Phase 1 (Year 1–2): proof of concept with small high-security institutions — private banks, family offices, university research groups — using software-only TRSP daemon and TEE-based CRATON. Phase 2 (Year 2–4): institutional pilot with mid-size financial institutions and government treasury departments — dedicated CRATON hardware module, Remote Guardian architecture, orbital quorum activated above threshold. Phase 3 (Year 3–5): national pilot with CBDC programmes and full jurisdiction regulatory validation — complete five-factor identity, consumer enrollment refined at national scale. Phase 4 (Year 5–10): global rollout — CRATON chip standardisation licensable to semiconductor manufacturers, TLS 1.3 extension standardised through IETF, "Secured by TDC" certification programme. Each phase generates performance data that validates and de-risks the subsequent phase. The worst outcome at any phase is a parameter adjustment — no user loses funds, no system collapses. Part 13 (Digital Estate Architecture) addresses the inheritance problem that every existing digital currency has left unsolved: what happens to assets when the owner dies. Three mechanisms work together. Designated Heir Enrollment: heirs are biometrically pre-registered at wallet setup — enrolled but cryptographically inactive during the owner's lifetime, with no access to balance or transaction history. Death Verification Protocol: succession requires three simultaneous conditions — official government-issued death certificate verified by the Enrollment Authority, 2-of-N Remote Guardian confirmation, and a mandatory 90-day waiting period during which the owner can cancel with biometric presence. Dead Man's Switch: an optional owner-defined inactivity window that triggers Guardian alerts and initiates the succession protocol if neither owner nor Guardian responds within the alert window. For owners without designated heirs: charitable designation to enrolled organisations, institutional estate trustee, or deliberate coin retirement. Owner financial privacy is maintained completely during lifetime. Post-succession historical access is configurable by the owner at setup. Novel contribution NC-TDC-17 is placed on the public record as defensive prior art. Privacy architecture clarification: the default state of every TDC wallet is complete financial anonymity. Identity disclosure is exclusively owner-initiated — the owner may selectively disclose individual transactions for tax certification, charitable donation receipts, regulatory compliance, or proof of funds. No court order, no government authority, and no institution can access wallet identity or transaction history without the owner's willing biometric participation. The three-part distributed binding token architecture makes bypass technically impossible — not merely legally prohibited. This is not a policy decision. It is a physical property of the architecture enforced by the requirement for live owner biometric activation of the device component. Novel contributions NC-TDC-13 (Geographic Coercion Evidence Layer), NC-TDC-14 (Phased Validation Rollout Architecture), NC-TDC-15 (Owner-Controlled Selective Disclosure), NC-TDC-16 (Enrollment-Anchored Privacy Architecture), and NC-TDC-17 (Digital Estate Architecture) are hereby placed on the public record as defensive prior art. Novel contributions NC-TDC-1 through NC-TDC-17 are placed on the public record as defensive prior art: quantum-permanent transaction signing; CRATON-anchored ownership proof; Generation 4 digital currency architecture; five-factor distributed identity; distress PIN with silent alert; Remote Guardian Device architecture; seed-phrase-free recovery protocol; biometric-CRATON enrollment binding; privacy-preserving three-part identity distribution; AML/KYC compliance by architecture; tiered enrollment framework; orbital CRATON quorum for sovereign transfers. The architectural frameworks described in this concept represent technical design guidelines only and are not legal advice, regulatory guidance, or binding specifications. Actual implementation in any jurisdiction will require adaptation to applicable local law including inheritance law, data protection regulation, anti-money laundering legislation, and financial services licensing requirements. Version 2 introduces four formal additions. Mathematical Formalization (Part 6.1.5): the transaction pipeline is formally specified as a four-step ephemeral verification protocol — KDF ephemeral key generation from physical entropy (sk_eph, pk_eph) = KDF(E_phys); Non-Interactive Zero-Knowledge Proof binding the ephemeral public key to the enrollment token without exposing persistent identity credentials; hardware-enforced destructive readout with thermodynamic irreversibility anchored in Landauer's Principle (ΔW ≥ n·k_B·T·ln2); and deterministic public-parameter-only ledger validation. Formal Threat Model (Part 4.5): three adversary classes formally defined — quantum network attacker (A_network, unbounded computational resources), malware/hardware attacker (A_local, full OS compromise), and coercion attacker (A_kinetic, physical duress) — with security proofs against each. Part 7b (AI-to-AI Micropayment Architecture, NC-TDC-21) documents the application of TDC quantum-permanent transaction signing to autonomous AI agent commerce. Every existing AI payment mechanism — static API keys, server-stored crypto wallets, centralised billing — represents a permanent credential attack surface vulnerable to quantum decryption. TDC coin eliminates this: each AI-to-AI transaction generates a CRATON commitment from the hardware entropy of the transacting inference node at that exact millisecond, used once to sign the micropayment and immediately destroyed. No stored credential on any server. Five new markets are documented: pay-per-inference settlement (USD 50B+ annual market), CRATON-anchored API key replacement, autonomous multi-agent revenue distribution at service delivery, AI training data micropayments for individual contributions, and cross-agent behavioural monitoring via the AI Guardian Layer at machine speed. The AI Guardian Layer (NC-TDC-19) monitors t
Pieter van den Berg, Andre Calmon, Andreas Gernert, Stef Lemmens · 6 authors
Problem definition: Emergency medical services (EMS) in many low- and middle-income countries utilize decentralized platforms coordinating independent ambulance providers. However, significant operational challenges arise from uncertainty in provider time availability and unpredictable idle locations. These uncertainties hinder reliable service coverage and negatively impact patient outcomes. Using data from our partner Flare in Nairobi, Kenya, we investigate the relative effectiveness of enhancing provider temporal commitment (time availability) versus spatial commitment (strategic location) to improve system coverage.Methodology/results: We employ optimization models adapted for ambulance commitment uncertainty, a detailed case study analysis, data-driven simulations, and a game-theoretic model. Our findings quantify a stark "cost of decentralization": the coverage provided by Flare's approximately 340 loosely committed ambulances could potentially be matched by fewer than 15 optimally deployed fully committed units. We find that enhancing spatial commitment generally yields higher marginal returns for improving coverage than solely increasing time availability. Adding just five optimized, location-flexible ambulances increased coverage substantially in simulation (e.g., by approximately 5\% over the baseline fleet) and reduced service variability. Simulations confirm the practical impact of interventions and validate model assumptions, while a game-theoretic model offers generalizable insights; both approaches align in highlighting the significant value of spatial coordination. Managerial implications: For managers and decision-makers overseeing decentralized EMS platforms, prioritizing strategies that improve spatial coordination offers an efficient path to enhancing service reliability and performance. Actionable strategies include targeted incentives that encourage providers to relocate strategically or deploy a small fleet of location-flexible, platform-controlled units to fill critical coverage gaps. Our framework offers practical tools for managers to identify coverage gaps and assess the potential impact of such interventions in resource-constrained settings, ultimately aiming to enhance emergency response.
Blockchain technology has been recognized as an innovative and effective means to improve transparency, security, and efficiency in the financial sector. However, privacy issues and reduction of efficiency have challenged large-scale applications the most. This issue motivates the current study that proposes a zero-knowledge proof (ZKP)-based Hyperledger Fabric framework that will ensure secure and privacy-preserving financial transaction processing. With the combination of the ZKP methods and smart contracts, the confidentiality of transactions will be verified, but at the same time, there will be audits and fraud detection. The PaySim1 synthetic financial transaction dataset, which contains more than six million records, will serve for the simulation and evaluation of different realistic workloads. The results of the experiments indicate that the ZKP-enabled framework can process 80.07 TPS on average with 0.01249 s of average latency, providing a privacy score over 98% at the same time, which reflects the effectiveness of zero-knowledge proofs in protecting sensitive transaction details while still enabling accurate verification and auditability within the blockchain network. Although the throughput is lower than that of a standard blockchain network (998,406 TPS), the given framework detects all the fraud cases at a 1.78% false positive rate, thus making sure that the system is both secure and compliant. This reduction is primarily due to the additional cryptographic overhead introduced by ZKP generation and verification, representing a trade-off between enhanced privacy and transaction processing speed. Additionally, the different setups were compared with each other in terms of privacy, efficiency, and resource utilization, and the optimized ones performed well in terms of these three aspects. To sum up the experiment, ZKP and Hyperledger Fabric, when jointly applied, not only increased the privacy and trust factors in the financial systems but also created the possibility to have very good operating conditions that are suitable for the applications.
Como a perícia blockchain organiza evidências para vítimas e advogados Golpes com criptomoedas costumam envolver promessas de investimento, falsas corretoras, pirâmides, phishing, malware, engenharia social e transferências para carteiras controladas por fraudadores. A boa notícia é que blockchains públicas deixam rastros verificáveis. A má notícia é que transformar esses rastros em prova útil exige método. O que a perícia blockchain consegue mapear Uma análise técnica pode identificar transações de entrada e saída, carteiras intermediárias, consolidação de valores, uso de bridges, mixers, exchanges, contratos de tokens e movimentações de stablecoins como USDT e USDC. O objetivo é reconstruir o caminho do ativo e apontar possíveis pontos de identificação.
Mojtaba Eshghie, Wolfgang Ahrendt, Cyrille Artho, Thomas Hildebrandt · 5 authors
Abstract Smart contracts manage blockchain assets and embody business processes. Yet, mainstream languages lack explicit support for process concepts such as roles, action dependencies, and time constraints, leading to increased implementation complexity and analysis challenges. To address this, we use Dynamic Condition Response (DCR) graphs, a formal business process modeling language, to formalize the semantics of smart contract business logic. Modeling smart contracts in DCR graphs involves translating their underlying behavioral logic into a declarative visual model using DCR’s explicit constructs for events, roles, data, time, and inter-event relationships. Furthermore, we systematically model 15 common high-level smart contract design patterns , representing recurring solutions to business logic-level problems. These formalizations reduce ambiguity compared to informal descriptions and serve as language-independent specifications. We demonstrate the modeling process through three complete smart contract case studies that combine six design patterns. Our modeling methodology, formalizations, and correspondence between smart contract semantics and DCR graphs enable future automated analysis and verification.
Ankit Sitaula, Ashraf Uddin, John Ayoade, Nam H. Chu · 5 authors
Counterfeit and unsafe medicines pose significant risks to patient safety and undermine trust in healthcare systems. This paper presents ACTMeds, a blockchain-supported pharmaceutical traceability and recall platform that considers pharmaceutical supply chain requirements and public health operational needs relevant to the Australian Capital Territory (ACT). The system integrates Ethereum smart contracts, developed using Ganache, with a React-based web application providing regulator, operator, pharmacy, and auditor interfaces, alongside a public verification portal leveraging QR and GS1 barcodes. In addition, role-based access control is enforced across the medicine lifecycle, including manufacture, custody transfer, dispensing, and recall, with immutable on-chain events generated to support auditability and accountability. To balance transparency with confidentiality, the platform prototypes a zero-knowledge (ZK) recall mechanism in which regulators can cryptographically prove that recall conditions meet predefined policy requirements without disclosing sensitive incident details. Threat modeling was conducted using the STRIDE framework, and security evaluation combined static application security testing (Solhint and ESLint) and dynamic testing. The paper further discusses deployment options, cost considerations, ZK recall performance analysis, ethical implications, and future enhancements. Security testing validated the platform’s resilience, with no high-severity vulnerabilities identified and medium-severity issues related to HTTP security headers addressed. The results indicate that a regulator-led, privacy-preserving, tamper-evident ledger can improve medicine authenticity verification and recall responsiveness while maintaining compliance and data protection obligations.