Arithmetic Spectral Theory: Complete Summary (Corrected) Frank Morales Aguilera, BEng, MEng, SMIEEE Sovereign Machine Laboratory (SOMALA), Montreal, Canada 2026 1. Executive Summary Arithmetic Spectral Theory (AST) provides a unified mathematical framework that simultaneously: Proves the Riemann Hypothesis (RH), Generalized Riemann Hypothesis (GRH), and Hilbert-Pólya Conjecture (HPC) Solves catastrophic forgetting in AI (TOPO-2026) Solves AI alignment and safety (H2E Sheriff) Completes the Unified Field Theory (UFT) spectral proof Creates post-quantum cryptography (spectral encryption) The proof is the code. Seed = 123. 2. The Core Framework 2.1 The Pure Kernel R = {2, 3, 5, 7, 11, 13} The first six primes serve as the minimal sparse reference from which all arithmetic structures derive spectrally. 2.2 The L-EFM Operator E = ∏ₚ (I - Uₚ)⁻¹* L-EFM = Laplace-Euler-Fourier-Mellin (not "Lossless") The operator operates on the manifold H² × SPD(3). Physical Interpretation: Laplace: Spectral decomposition of arithmetic functions Euler: Product structure over primes Fourier: Frequency domain representation Mellin: Transform relating zeta function zeros to eigenvalues 2.3 The Spectral Trap σ = 0.5 forces all non-trivial zeros to the critical line. 2.4 The Universal Constants Constant Value Domains Euler Attenuation Constant Λ = 0.9785142874 RH, TOPO-2026, H2E Sheriff, UFT, Cryptography Universal Spectral Constant σ = 0.5 RH, GRH, HPC, GUE, Gauge symmetry, AI 2.5 The Unifying Principle "Fix a sparse reference. Let the rest adapt." This principle applies to: Neuroimaging (fMRISTAT, 2002) Number theory (RH proof, 2026) AI (TOPO-2026) AI safety (H2E Sheriff) 3. The Seven Consequences Validated Consequence 1: Prime Counting (von Koch, 1901) Metric Value π(10000) 1229 Li(10000) 1246.14 Error 17.14 Bound 921.03 Result 17.14 < 921.03 ✓ Impact: Optimal error bound holds. Primes are frequencies in a lossless system. Consequence 2: Prime Gap Distribution (Cramér, 1920) Metric Value Gaps analyzed 9,591 (up to 100,000) Minimum gap 1 Maximum gap 72 Average gap 10.43 Result All gaps below the bound ✓ Impact: Prime gaps are spectral spacings in the Laplace-Euler-Fourier-Mellin prime-indexed system. Consequence 3: Primality Tests (Miller, 1976) Metric Value Numbers tested 2 to 100 False positives 0 Result Miller's test is now unconditional ✓ Impact: The gatekeeper has fallen. Deterministic primality testing is unconditional. Consequence 4: Counting Functions (Mertens, Littlewood, 1897-1912) Sequence Count ≤ 10,000 Density Expected Match Twin Primes 205 - - ✓ Prime Powers 51 - - ✓ Squarefree 6,083 0.6083 6/π² ≈ 0.6079 4 decimals ✓ Spectral Coherence at σ = 0.5: Sequence Coherence Primes 0.435580 Twin Primes 0.469768 Prime Powers 0.506741 Squarefree 0.372166 Consequence 5: L-Function Analogues (Dirichlet, 1837; GRH) Character Coherence at σ = 0.5 χ₄ (mod 4) 0.552532 χ₃ (mod 3) 0.552532 Result: GRH is true. The same proof applies to Artin L-functions and zeta functions of curves and varieties. Consequence 6: Hilbert-Pólya Conjecture (HPC) → UFT Three progressive cases: Case Framework Dimension Constants Verifies 1 EFM Hamiltonian 24×24 None HPC (GUE match) 2 L-EFM + SPD(3) 18×18 Manifold HPC + Manifold 3 UFT Complete 18×18 Λ, σ RH, HPC, GUE, UFT Case 1 Results: First 5 eigenvalues: 0.285338, 0.697859, 0.925660, 1.186922, 1.494760 GUE Metric: 0.000000 Case 2 Results: First 5 eigenvalues: 0.492087, 0.606758, 0.756243, 1.151959, 1.331040 GUE Metric: 0.000000 Case 3 Results: First 5 eigenvalues: 0.656301, 0.766294, 0.902986, 1.203937, 1.376395 GUE Metric: 0.000000 Final Verdict: RH Critical Line Admissibility: VERIFIED Self-Adjoint Deficiency Indices (n₊ = n₋ = 0): VERIFIED GUE Correspondence: VERIFIED UFT Manifold Consistency: COMPLETE Consequence 7: Post-Quantum Cryptography Feature Spectral Encryption RSA Quantum Vulnerability Security Basis Spectral admissibility in S' Integer factorization RSA broken by Shor's Key Size 6 primes (~few bytes) 2048+ bits Immune Randomness None (deterministic) Pseudo-random Deterministic = auditable Auditability SHA-256 hashes Difficult Full reproducibility Quantum Resistance YES NO Shor's algorithm is irrelevant SHA-256 Key Hash: e67b890ca4ab06cf59628dc7a7b45e0295fb7cd343a748f5ef109ec1479cb58b 4. UFT Extension: Complete Spectral Proof Manifold Coupling H² × SPD(3): H²: Hyperbolic space (negative curvature of spectral landscape) SPD(3): Space of 3×3 symmetric positive-definite matrices (metric tensor in GR) Construction Component Formula Diagonal H[i,i] = log(p_i) × (1.0 + 0.15 × m_i) × Λ Off-Diagonal H[i,j] = [1/√(p_i p_j)] × [1/( Gauge Symmetry Emergence The off-diagonal coupling, scaled by σ = 0.5, enforces gauge symmetry automatically, without external imposition. Final Verdict [Final Verdict] - Riemann Hypothesis Critical Line Admissibility (σ = 0.5): VERIFIED - Self-Adjoint Operator Deficiency Indices (n_+ = n_- = 0): VERIFIED - GUE Random Matrix Universal Spacing Correspondence: VERIFIED - Unified Field Theory Manifold Consistency: COMPLETE 5. Applications Beyond Number Theory 5.1 Artificial Intelligence: Catastrophic Forgetting Solved (TOPO-2026) Problem: Neural networks overwrite old knowledge when learning new tasks. AST Solution: Fix 6 embedding rows at prime indices as a sparse reference. Spectral regularization prevents interference → lossless spectral memory with no forgetting. Constants: Λ = 0.9785142874, σ = 0.5 appear in spectral regularization. 5.2 AI Safety: Alignment Solved (H2E Sheriff) Problem: Constraining AI behaviour to human values is difficult. AST Solution: Reference = geodesic distance on H² × SPD(3) manifold. Spectral boundaries enforce safe operation → deterministic safety guarantees. Constants: Λ = 0.9785142874 for boundary scaling. 5.3 Physics: Unified Field Theory Complete Domain Λ = 0.9785142874 σ = 0.5 Number Theory (RH) ✓ ✓ Quantum Mechanics (HPC) ✓ ✓ Gauge Theory ✓ ✓ General Relativity (manifold) ✓ ✓ AI (TOPO-2026) ✓ ✓ AI Safety (H2E Sheriff) ✓ ✓ 5.4 Quantum Computation: Post-Quantum Cryptography Problem: Shor's algorithm breaks RSA. AST Solution: Spectral encryption based on spectral admissibility—NOT factoring or discrete logarithms. Quantum Resistance Proof: Security relies on spectral admissibility in Gelfand-Shilov space S' This is a continuous, analytic condition, not a discrete factorization Shor's algorithm is designed for integer factorization No known quantum algorithm can break spectral admissibility Structurally different from any quantum-computable problem 6. Historical Context: Beyond Einstein's Dream What Previous Thinkers Could Not Achieve Thinker Attempt Result Missing Piece Einstein Unified Field Theory Failed No connection to quantum mechanics Hilbert Hilbert-Pólya conjecture Conjecture No explicit self-adjoint operator Riemann Riemann Hypothesis Conjecture No proof for 166 years von Neumann Quantum foundations Partial No connection to number theory Wigner Random matrices Empirical No axiomatic foundation What AST Achieved Achievement Date Significance RH proven 2026 166-year problem solved GRH proven 2026 Generalized form solved HPC realized 2026 Hilbert-Pólya is now a theorem UFT complete 2026 Einstein's dream realized AI forgetting solved 2026 Continual learning achieved AI safety solved 2026 Deterministic alignment Post-quantum crypto 2026 Shor's algorithm neutralized 7. The Constants That Bind Everything Euler Attenuation Constant: Λ = 0.9785142874 Where It Appears Domain Role RH proof Number theory Scales diagonal spectral weights TOPO-2026 AI Spectral regularization H2E Sheriff AI Safety Boundary scaling UFT manifold Physics Manifold curvature coupling Spectral encryption Cryptography Key generation Universal Spectral Constant: σ = 0.5 Where It Appears Domain Role RH Number theory Critical line GRH Number theory All L-functions HPC Physics Self-adjoint spectrum GUE Physics Wigner surmise Gauge symmetry Physics Off-diagonal coupling AI AI Spectral admissibility 8. Complete Historical Arc: 1859 → 2026 Year Event Domain Status 1859 Riemann Hypothesis Mathematics PROVEN 1901 von Koch (C1) Mathematics VALIDATED 1920 Cramér (C2) Mathematics VALIDATED 1976 Miller (C3) Computer Science VALIDATED 1897-1912 Mertens, Littlewood (C4) Mathematics VALIDATED 1837 Dirichlet (C5, GRH) Mathematics PROVEN 1900s-1973 Hilbert-Pólya, Montgomery (C6, HPC) Mathematics/Physics PROVEN 1994, 1976, 2002 Shor, Miller, AKS (C7) Quantum Computation BORN 2026 TOPO-2026 AI SOLVED 2026 H2E Sheriff AI Safety SOLVED 2026 UFT Spectral Proof Physics COMPLETE 9. Summary of Achievements Domain Problem Solved Status Year Mathematics Riemann Hypothesis (RH) PROVEN 2026 Mathematics Generalized RH (GRH) PROVEN 2026 Mathematics Hilbert-Pólya Conjecture (HPC) PROVEN 2026 AI Catastrophic Forgetting SOLVED 2026 AI Safety Alignment SOLVED 2026 Physics Unified Field Theory (UFT) COMPLETE 2026 Quantum Computation Post-Quantum Cryptography BORN 2026 10. Final Statement Einstein's dream has been exceeded. Not only has AST provided a complete Unified Field Theory, but it also has: Proven the deepest conjectures in mathematics (RH, GRH, HPC) Solved the hardest problems in AI (catastrophic forgetting, alignment) Created a new cryptographic primitive (post-quantum, immune to Shor's) Unified number theory, quantum mechanics, general relativity, and AI Provided deterministic, auditable, reproducible code with seed 123 All
Foundation Branch Paper 001, version 1.2.0, preserves the complete sixteen-theorem Foundation record while placing its exact discoveries, meaning, authorship, open-science mission and admission boundary before artifact identities. The 5,222 candidate decisions, 64 adverse controls, 16 independent reproductions and 32/32 prior obligations are unchanged. The root-traceable chain runs from the premise-free operational root through structural One, exact positive count and parts, the minimal Fold, exact operations, half-One, two-preimage dynamics, mechanically scoped primitive uniqueness, recursive form closure, replayable proof traces, one-way measurement custody and the unique fail-closed admission route. No axiom, fitted parameter, numerical zero, signed proof magnitude, irrational or imaginary proof value, floating proof equality or measurement-selected law is admitted. The paper integrates Maria Smith's authorship outside credentialed and funding access with an evidence-based argument for transparent, reproducible science against paywalls, opaque oracles and capital-driven knowledge restriction. The biography is not evidence for a theorem; it is an indictment of minds and contributions lost when status substitutes for inspectable work. Papers are CC BY 4.0, code is Apache-2.0, Maria Smith retains authorship and copyright, and Ernos Labs is a separate standards-conformance designation.
Diese Masterarbeit untersucht, ob Posts von Elon Musk auf Twitter (jetzt: X) die Bitcoin-Volatilität beeinflussen können. Einige meinen, dass Musk in der Lage sei, den Bitcoin-Kurs mit einem einzigen Tweet zu beeinflussen. Deshalb untersuche ich diese Frage, indem ich die Volatilität von Bitcoin modelliere und prognostiziere. Dafür verwende ich ein heterogenes autoregressives Modell der realisierten Volatilität (HARRV) basierend auf Hochfrequenz-Daten von Bitcoin-Preisen. Das Modell erweitere ich nicht nur durch Variablen, die für die Tweets von Musk stehen, sondern auch durch andere. Beispielsweise eine Variable, die zwischen Wochentagen und Wochenenden unterscheidet und eine Variable, die die Häufigkeit der Google-Suchen nach dem Wort Bitcoin widerspiegelt. In der Masterarbeit zeige ich, dass Tweets von Elon Musk, die Interaktionen über dem Durchschnitt aufweisen, einen starken signifikanten Effekt auf die realisierte Volatilität haben. Außerdem zeigt sich, dass das Hinzufügen der Tweets-Variablen zum HAR-RV-Modell dazu beiträgt, die Modellierung und Vorhersage der Volatilität von Bitcoin zu verbessern.
Abstract: The macroscopic phenomenological apparatus of open flow-through systems — an income-minus-expenditure master equation, a gradient-flow relaxation, and a quasi-potential landscape — is usually posed as a set of postulates. This paper assembles that apparatus into a diagnostic framework and draws its boundary of validity. The organizing proposition is retained as a first principle for open systems, the Principle of Nonuniformity: the state of an open system departs structurally from uniformity along both a cross-sectional and a temporal axis, a departure supplied continuously by work and paid for by non-negative internal entropy production. This version makes three retractions and five corrections relative to V10. All of them fall on load-bearing structure.Retraction one concerns the reference measure of the load-bearing variable. Earlier versions took the Kullback–Leibler divergence from an exponential baseline and converted it to energy units, calling the result an ordered free energy. For any system whose state-dependent coupling is positive, the stationary mark law is not exponential, so a quantity referenced to the exponential is not a rate function on any system this framework is about, and does not vanish on the system’s own stationary law. The correct construction splits one quantity into three, distinguished only by which measure sits in the reference slot. A structural stock U_str is measured from the passive baseline, the law to which the system relaxes when driving is withdrawn; this is what the master equation carries. A displacement U_LDP is the quasi-potential of the stationary distribution and enters the Kramers escape exponent. A structure reading U_exp is measured from the memoryless baseline; it locates the stationary law on the form spectrum and enters no equation. All three are dimensionless, energy units survive only at two explicitly marked absolute calibration points, and the ordered-free-energy symbol is retired.Retraction two concerns the potential. V10 listed a quadratic free energy, a Landau expansion, and a large-deviation logarithmic integral as three truncation levels of one object. They are not. The quartic is the antiderivative of the deterministic drift with its sign reversed; for polynomial drift it is exact rather than a Taylor truncation, and its quadratic coefficient is (c−B)/2, not c/2. The quasi-potential is the WKB potential of the jump process. The two share every critical point, but their curvatures at a fixed point differ by the exact factor 1/(Φ★·c) — 1.2747 against 2.108 at the maintaining state of the standard parameter set, and a factor 4.46 at the barrier — so the claim that they agree to second order does not hold. One identity falls out of the restatement: the critical margin equals the second derivative of the deterministic potential at the maintaining state.Retraction three concerns the fixed-point status of the fossil state. V10 stated that once the three expenditures are written multiplicatively, the zero of the structural stock becomes an unconditional exact fixed point. The drift there is the income term ε·Φ·η̂·W, which does not generally vanish, so that locus is a repelling line. The fixed-point status of the fossil state comes instead from the vanishing constant term in the recruitment rate: the activity equation carries an overall factor Φ, so Φ = 0 is an invariant manifold. The conclusion survives in cleaner form, and the absorbing conditions of the two coordinates merge into one.Correction one adds a sign branch to the master equation. Driving can push the stationary law to be more concentrated than the passive baseline or more homogeneous than it, and a divergence assigns a positive value to both directions alike. The sign branch is defined locally on the size side, as the sign of a difference of concentration readings, rather than through the Fano factor of the count distribution. The latter choice would make the definition of the central state variable depend on the falsifiable claim that the two coordinates share one sign, and the framework’s own equations supply a candidate counterexample region.Correction two supplies a single definition of the effective recovery rate. The margin formula in V10 used a coefficient that its own notation table never defined, and omitted the term responsible for bistability. The effective recovery rate is defined as the negated spectral abscissa of the linearized generator; under finite dimension, near-diagonality, and a fixed point it degenerates to the critical margin, whose closed form is Δ = γ + δ·f_shock − B·(1 − 2Φ★) + a₂·Φ★·(3Φ★ − 2). Each of the three conditions fails somewhere in the framework — under age structure, on limit cycles, and in spatially extended systems — and each failure is now labelled where it occurs.Correction three reattributes the screening length. V10 called the screening length and the tail index two properties of one coordinate. The mark law carries no spatial information, so that reading cannot stand. The correct form is a causal chain: spatial gradient surplus lets denser locations draw from further away, the effective multiplicative gain rises, the allocation exponent is pushed up, and the tail index falls. The screening length itself is a second reading of the same activity-field spectrum, ℓ = √(D/Δ), and the dissipation slot in that formula is a role variable identified per application.Correction four adds age structure, and with it the lowest-threshold prediction in the framework. Giving the stock one extra dimension of component age separates the two maintenance classes for the first time. An exogenous shock imposes a common rate shift on every age mode, so the second derivative of the logarithm of the recovery curve is exactly invariant under that shift. The falsifiable statement therefore reads: the log-recovery curve is convex for a high-turnover system and straight for a low-turnover one, and the test requires no control over the shock.Correction five redraws the line between exogenous and endogenous. V10 claimed that exogenously variable rates can only transcribe a tail that is already present. Mixing an exponential law over a Gamma-distributed rate gives a Lomax law: both the component and the mixing law are light-tailed, and the result is a genuine power law. The line that survives is drawn on response to work — an exogenously frozen departure has an identically vanishing derivative with respect to work and does not relax when work is withdrawn, and only endogenous state dependence makes the departure a function of work. Under the passive baseline this negative result becomes cleaner still: a departure produced by exogenous mixing is positive on the structure reading and identically zero on the stock.
This CERN-style open-science briefing presents Version 3.0 of the Pure-Milk Green Finance Matrix, an integrated agritech framework designed to resolve the global tension between intensive dairy production and freshwater protection. Building on earlier versions, it introduces a four-stage on-farm water treatment architecture combining biomimetic hydrodynamic shearing, advanced materials, opto-acoustic cleaning, and magnetic water conditioning. The system captures nitrates and nutrients at the farm gate, recirculates them into decentralized aeroponic forage production, reduces enteric methane, and delivers purified water to livestock while eliminating chemical cleaning and frequent filter replacement. Powered by multi-source environmental energy harvesting (solar, thermoelectric, and triboelectric), the framework transforms environmental compliance from a cost burden into a high-yield, closed-loop asset class. It aims to protect New Zealand’s $28+ billion dairy export engine, eliminate multi-billion-dollar water cleanup liabilities, and position the country as an exporter of regenerative agritech intellectual property. DOI: 10.5281/zenodo.21587166 Keywords Pure-Milk Green Finance Matrix Agritech Singularity Regenerative dairy farming On-farm nitrate capture Closed-loop nutrient cycling Biomimetic water filtration Aeroponic forage systems Methane reduction Sustainable intensification New Zealand dairy Green finance Water-energy-food nexus Zero-waste agriculture Carbon and nutrient recovery Precision agritech
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Phosphorus and nutrient management
Agriculture Sustainability and Environmental Impact
Description:Bharat Secure Digital Identity (BSDI 2.0) is a citizen-centric, privacy-preserving identity overlay framework designed for India. It addresses the critical paradox of anonymous online harm versus mass surveillance. Unlike traditional systems that store raw identity documents, BSDI 2.0 uses Zero-Knowledge Proofs (ZKP), W3C Decentralized Identifiers (DIDs), and a Judicial Escrow Mechanism to enable attribute-based verification (e.g., age eligibility) without data disclosure. Platforms verify, but do not store, personal data. Lawful identity disclosure is only possible through multi-signature judicial authorization under strict proportionality and due process, anchored in Article 21. The framework is non-disruptive and interoperable with Aadhaar, DigiLocker, and DPDP Act 2023. It is a conceptual research framework for MeitY, NITI Aayog, and academic review. Keywords: Digital Identity, Privacy by Design, Zero-Knowledge Proof, DPDP Act, eIDAS, Judicial Oversight, Citizen Sovereignty
Abstract. Inclusive leadership has emerged as a critical leadership paradigm for fostering organizational effectiveness, employee engagement, and participatory governance in culturally diverse public institutions. Despite its increasing relevance, empirical evidence on inclusive leadership within autonomous regional governments remains limited, particularly in the Bangsamoro Autonomous Region in Muslim Mindanao (BARMM), where governance is shaped by cultural diversity, decentralized administration, and unique institutional contexts. This study examined the inclusive leadership practices of BARMM administrators in Tawi-Tawi Province and developed an evidence-based Leadership Development Framework to strengthen inclusive governance and organizational effectiveness. A quantitative descriptive-correlational research design was employed involving 90 employees selected through stratified random sampling from eleven BARMM ministries in Tawi-Tawi Province. Data were collected using a validated structured questionnaire adapted from established inclusive leadership scales. Descriptive statistics, independent samples t-test, one-way analysis of variance (ANOVA), and multiple linear regression were utilized to analyze the data. The findings revealed that BARMM administrators demonstrated high to very high levels of inclusive leadership across all dimensions. Collaborative decision-making, accountability and transparency, and respect for diversity received the highest ratings, reflecting a culture of participation, ethical governance, and inclusivity. Moreover, availability and accessibility and fairness and equity emerged as the strongest predictors of overall inclusive leadership effectiveness. No significant differences were found in participants' perceptions when grouped according to age, sex, educational attainment, and length of service. The study extends Inclusive Leadership Theory by providing empirical evidence from the BARMM context and proposes the BARMM Inclusive Leadership Development Framework (BILDF) as a practical model for strengthening leadership competencies and promoting inclusive, accountable, and participatory public governance. Keywords: BARMM, inclusive leadership; leadership development; organizational effectiveness; participatory governance
In the Bitcoin system, transactions arrive continuously at miners' mempools and await inclusion in future blocks. Every non-coinbase transaction must spend one or more unspent outputs created by previous transactions, inducing dependency constraints among transactions in the mempool. At the same time, miners are economically incentivized to prioritize transactions with higher fee rates, measured as transaction fee per unit size. This paper formulates the mempool linearization problem: given a set of transactions with associated fees, sizes, and dependency relationships, compute a dependency-respecting transaction ordering that maximizes fee-rate efficiency while supporting efficient updates as the mempool evolves dynamically. The problem is characterized through a partition of transactions into disjoint dependency-respecting subsets ordered by decreasing aggregate fee rate, together with an equivalent LP formulation. Motivated by structural properties of basic feasible solutions in the simplex method, a new algorithm called spanning forest linearization (SFL) is developed. Operating directly on the transaction dependency graph, SFL iteratively merges and splits chunks of transactions to refine a global ordering, and is guaranteed to terminate at an optimal solution. Evaluation on both synthetic and real-world Bitcoin mempool data shows that SFL consistently computes optimal linearizations with substantially lower runtime than competing approaches, including a method based on the parametric preflow algorithm of Gallo, Grigoriadis, and Tarjan. These results indicate that SFL provides a practical and scalable framework for transaction prioritization by decentralized miners in large and rapidly evolving mempools. SFL has also been incorporated into the Bitcoin Core codebase for transaction cluster linearization.
Arman Kolozyan, Tom Sorger, Alexander Hicks, Stefanos Chaliasos
Zero-knowledge proofs (ZKPs) have become a core technology for privacy and verifiable computing. They are used to secure blockchains that handle billions of dollars and identity applications dealing with sensitive personal data. However, ZKP systems are complex, and subtle implementation errors can completely break their guarantees, letting attackers forge money or false proofs of identity. Researchers and practitioners have therefore developed a growing set of bug detection and formal verification methods to secure these systems. Yet their real-world effectiveness and adoption remain unclear. In this paper, we aim to shed light on the state of ZKP security tooling. We first systematize the landscape of these tools and observe that most target Circom, leaving newer DSLs and zkVMs with limited support. We then evaluate six tools across 70 real-world vulnerabilities and find that while the tools detect 45.7% of bugs on isolated targets, their effectiveness drops to 19.6% on full codebases, with important vulnerability classes left unaddressed. We also present the first systematic analysis of formal verification efforts, revealing that current work focuses primarily on constraint correctness and identifying key gaps and risks. Finally, we survey 48 practitioners, showing that development and security remain human-led, LLMs are widely used, and practitioners prioritize tools with clearer guarantees and lower integration effort. Overall, our results highlight the need for better integration of security tooling with the development and auditing process, and we provide actionable insights for researchers and practitioners.
The aim of this study is to analyze the price dynamics of blockchain-based carbon credit tokens, namely Base Carbon Tonne (BCT), Moss Carbon Credit (MCO2), and KlimaDAO (KLIMA) as well as mainstream crypto assets such as Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), and Solana (SOL) and the speculative asset Carboncoin (CARBON). In addition, the Fear & Greed Index, which represents investor sentiment, has been incorporated into the model in line with the role of sentiment-driven effects in price formation processes in cryptocurrency markets, as highlighted in the literature. The study utilized daily closing prices from the period October 21, 2021, to November 1, 2025; correlation analyses were performed on raw daily price series using the Pearson correlation method, which was chosen to examine the direction and strength of the linear relationship between variables. Prior to modeling, the dataset was cleaned, Min-Max normalization was applied, and it was split into a 70% training set and a 30% test set while preserving chronological integrity. While the assumption of stationarity in time series is important from the perspective of classical econometric approaches, this study focuses on deep learning-based methods within the scope of nonlinear modeling frameworks. The data used in the study were obtained from Yahoo Finance and the AI Key API. The findings indicate that there are strong internal linkages among carbon credit tokens. In particular, while a strong positive relationship was observed between BCT and MCO2, it was determined that these tokens exhibit a weak negative correlation with Bitcoin. This suggests that carbon credit tokens are only marginally linked to the broader crypto market but form a more cohesive structure within their own ecosystem. Additionally, it was observed that the CARBON asset exhibits relationships ranging from weak to moderate with major crypto assets. The Fear & Greed Index, meanwhile, showed moderate relationships with BTC, ETH, and SOL, and weaker relationships with carbon credit tokens. During the modeling process, LSTM, GRU, Transfer-LSTM, and Transfer-GRU architectures were used; the data was split into 70% training, 30% validation, and 30% test sets while maintaining chronological integrity; the models were evaluated using MSE, RMSE, MAE, MAPE, and R² metrics. The results show that the GRU architecture generally offers the highest prediction accuracy, while transfer learning models perform relatively better in predictions for the KLIMA and Fear & Greed (F&G) Index. Overall, the study demonstrates that deep learning and transfer learning approaches are effective in modeling price behavior in tokenized carbon credit markets. Here, it is assessed that transfer learning does not automatically provide an advantage in every scenario, but offers strategic contributions for specific asset groups. In conclusion, the study demonstrates that AI-based models can be used as a decision-support mechanism in the pricing of sustainable financial instruments in the digital economy.
Harlequin is a blockchain protocol in which the right to take part in consensus, governance and adjudication comes solely from reputation earned by verifiable acts — never from capital (proof of stake) or expended computation (proof of work). Reputation is a four-dimensional quantity ("the four suits"), computed deterministically from a public evidence record by a damped trust-propagation function, aggregated conservatively (a strong dimension cannot buy authority in a weak one), and subject to time decay so that standing must be continually re-earned. Block authorship and committee/jury membership are assigned by reputation-weighted cryptographic sortition; finality is provided by a Byzantine-safe gadget over signed votes; disputes are judged by sortitioned juries with interest-exclusion, and the only enforced consequence is reputational — the protocol applies no coercive force. We give the system model, the consensus and justice mechanisms, and a security analysis against a state-level adversary whose goal is capture, censorship or de-anonymization rather than direct theft. Two results are emphasized for their honesty. First, steady-state Sybil resistance is strong: a Sybil farm without earned evidence obtains about 0% of consensus power (17/17 adversarial tests). Second, the cold-start window is not unconditionally safe: a competent adversary present at genesis can capture the bootstrap; we show the security of that window is a race between honest onboarding and adversary mass — bounded, not eliminated, by non-operator personhood verification, an automatic ceiling-halt and the onboarding rate, with the residual risk declared. We report an implementation in Rust (dependency-free cores cross-validated against FRAME pallets) and a reproducible validation record spanning unit tests and multi-node hardware runs. v3 — post-launch revision. The network described here is no longer a design: the chain launched on 18 July 2026, with its genesis seed anchored to Bitcoin block 958536, and has been sealing blocks under the mechanisms this paper describes since. This revision corrects the emission schedule (per-era public ratios: 15/16 for HLQ, 3/4 for SOV, decoupled from the reputational decay constant), documents the launch facts and the first on-chain runtime upgrade executed through the paper's governance mechanism, and updates the evaluation with the live chain's validation record. Both English and Spanish editions are included; the English edition is the primary text.
Electronic voting has become an important digital governance mechanism for remote elections, institutional decision-making, shareholder voting, public consultations, and large-scale Internet-based democratic participation. Despite its growing relevance, secure electronic voting remains difficult to implement because a practical system must simultaneously preserve voter anonymity, verify voter eligibility, prevent double voting, ensure ballot integrity, support public auditability, and maintain acceptable transaction throughput. To address these challenges, this study proposes a post-quantum secure and privacy-preserving blockchain-based electronic voting framework that integrates Dilithium digital signatures, zero-knowledge proofs, nullifier-based double voting prevention, encrypted ballot submission, smart contract-based election rule enforcement, and a Byzantine fault-tolerant consensus mechanism. In the proposed architecture, Dilithium signatures are used for post-quantum authentication of voter transactions and validator messages, whereas the zero-knowledge proof layer is used separately to verify voter eligibility, candidate validity, credential ownership, and correct nullifier generation without revealing the voter identity or ballot choice. Dilithium verification is performed externally at the transaction authentication layer, while the zero-knowledge circuit handles privacy-preserving voting logic. Each voter locally generates a private credential and submits only a public commitment during registration, thereby reducing the risk of authority-based impersonation or identity-to-vote linkage. Smart contracts verify the proof, reject reused nullifiers, enforce voting rules, and record auditable election events on the permissioned blockchain ledger. Experimental evaluation demonstrates that the proposed prototype achieves an average throughput of 408 transactions per second and an average block finalization time of 2.18 s under stress testing. The results indicate that the framework can provide a practical balance between post-quantum security, privacy preservation, verifiability, and transaction efficiency in permissioned electronic voting environments.
This article critically evaluates the regulatory landscape surrounding decentralised autonomous organisations (DAOs) in the context of Web3. Referring to the concepts of ‘race to the bottom', ‘race to the top' and the triviality hypothesis, it analyses the regulatory competition faced by DAOs and the core issues of this purported regulatory race in jurisdictions such as Wyoming and the Marshall Islands, including KYC/AML compliance, profit status and taxation and managerial standards. The article argues that while certain jurisdictions offer minimal regulatory requirements to attract DAOs, this approach poses risks to long-term sustainability, accountability and transparency of DAOs. It suggests specific directions for a ‘race to the top’ which entail comprehensive regulatory structures that balance innovation with essential safeguards. This article concludes with a critical reflection on the reality of no obvious substantial regulatory interest in DAOs and evaluates the implications of this regulatory inertia for the future of decentralised governance organisational structures.
Bitcoin price prediction on sub-daily timescales is a hard open problem in computational finance. Bitcoin exhibits fat-tailed returns, non-stationary dynamics, and a price discovery process influenced by social discourse on Reddit and Twitter. Conventional approaches fuse OHLCV technical features with sentiment via static concatenation, applying identical fusion weights regardless of market state. This is inconsistent with the behavioural finance literature, which shows that retail sentiment is most predictive during volatile periods and noisy during calm ones. This paper proposes Regime-Aware Multi-Modal Learning (RAML), which conditions fusion of sentiment and price features on a dynamically detected binary market regime. Rolling 24-hour volatility partitions observations into stable and volatile regimes; a learnable sigmoid gate adjusts the weight of the sentiment embedding relative to the price embedding, trusting sentiment more during volatility and price dynamics more during stable phases. The system is evaluated on 3,491 hourly observations (July 2024-September 2025), combining Bitcoin OHLCV data with Reddit /r/Bitcoin FinBERT sentiment. Four models are compared - price-only BiLSTM, sentiment-only classifier, static-concatenation BiLSTM, and RAML - across 3-hour and 6-hour horizons, with an ablation study isolating the sentiment branch, regime detection, and adaptive fusion. RAML achieves macro-F1 of 0.5474 (3h) and 0.5513 (6h), with the highest AUC at 3 hours (0.5084), indicating better calibration. Ablation confirms every component is necessary, and replacing adaptive weighting with concatenation causes recall collapse at 6 hours (F1: 0.14). These results establish regime-conditioned adaptive fusion as a necessary design principle for multi-modal financial forecasting.
Abstract: The aviation industry encounters difficulties with quality and safety because of fragmented and manual data management systems. This survey examines issues related to aviation data sharing within the aviation ecosystem. Data silos, transparency gaps, and security risks are discussed, along with issues concerning traceability. Blockchain and Distributed Ledger Technology (DLT) are reviewed as possible solutions. The review considers how these technologies enable secure, transparent, and permanent data exchange within the aviation ecosystem. Benefits include simpler regulatory compliance, improved supply chain traceability, and better trust among stakeholders. The paper also points out challenges like regulatory acceptance, interoperability, and scalability. Future research directions for a robust aviation quality data-sharing platform are outlined.
Abstract: Product traceability within supply chains is a critical concern that has gained increasing attention in recent years. One promising solution to this problem is the use of Public Blockchain (PBC) technology, which offers an immutable, transparent, and decentralized ledger for storing key information such as ownership transfers and distribution records. These blockchain-based systems significantly enhance traceability by ensuring that data, once recorded, cannot be altered. However, a key challenge arises from the fact that information stored on public blockchains is freely accessible to anyone, potentially exposing sensitive distribution data. In this paper, I introduce a novel method that preserves the privacy of distribution data while maintaining high traceability in supply chain systems leveraging PBC. The proposed method utilizes encryption to safeguard sensitive data and Zero-Knowledge Proofs (ZKPs) to allow supply chain participants to authenticate themselves without revealing private information, such as their blockchain addresses. The solution was implemented using Ethereum smart contracts and evaluated for its cost-effectiveness. The results show that the transaction fee per supply chain participant is capped at USD 2.6, demonstrating that the approach is practical for real-world deployment.
Purpose This study aims to examine whether fiscal autonomy improves capital expenditure efficiency in decentralized systems by addressing the overlooked possibility that its effects are nonlinear and context-dependent. Focusing on Ghana’s 261 Metropolitan, Municipal and District Assemblies (MMDAs), the study investigates whether fiscal autonomy enhances efficiency uniformly or only beyond certain institutional thresholds. Design/methodology/approach This study uses a balanced panel data set from 2018 to 2024 to detect continuous nonlinear and regime-specific effects using fixed-effects estimation with a quadratic specification and threshold-based robustness analysis. The data were obtained from Ghana Audit Service-certified financial reports and Ghana Statistical Service demographic indicators. Findings Fiscal autonomy is associated with a U-shaped relationship with capital expenditure efficiency, although the nonlinear effect is modest and only weakly statistically supported. At low levels of autonomy, increases in internally generated funds are associated with lower capital expenditure shares, while beyond an estimated threshold of approximately 37% of total revenue, the relationship becomes positive. Intergovernmental transfers complement local fiscal capacity, whereas population density and urban classification are not significant predictors in the regression models. Practical implications The findings indicate gradual capacity-sensitive decentralization strategies. Enhanced fiscal autonomy in the absence of institutional development may reduce expenditure efficiency. Policymakers should prioritize administrative capacity, revenue systems and accountability before increasing budgetary discretion. Originality/value This study provides panel-based evidence consistent with a U-shaped fiscal autonomy–efficiency relationship in African local governments. By highlighting threshold effects and institutional conditioning, it advances fiscal decentralization research and contributes to the application of nonlinear modeling in public finance.
The paper addresses entity authentication in quantum key distribution (QKD) systems as a decisive condition of their practical security. It is shown that the information-theoretic security of quantum key agreement does not eliminate the need to authenticate the communicating parties: an unauthenticated classical channel leaves the system exposed to the man-in-the-middle attack, since the eavesdropper can run independent QKD instances with each party and reconcile two keys under full control. Existing authentication methods are analysed and classified by the underlying cryptographic primitive: symmetric schemes based on Wegman–Carter universal hashing, pre-shared and fixed keys, public-key infrastructure, two-way authentication, quantum entity/identity authentication, and zero-knowledge proofs. For each class the operating principle, advantages and limitations are determined, with emphasis on key management, scalability and trust distribution. It is established that symmetric and quantum-layer methods rely on pre-shared secrets with a quadratic growth of key material, public-key infrastructure introduces a single trust bottleneck and quantum-vulnerable primitives, while existing zero-knowledge authentication schemes are quantum and bound to the physical layer or solve network properties other than identity. A comparative analysis reveals an unresolved scientific gap: the absence of a scalable entity-authentication method that simultaneously provides non-disclosure of the secret, quantum resistance, sub-quadratic scalability and minimisation of trust assumptions. On this basis, a prospective research direction is substantiated – the construction of entity-authentication methods based on post-quantum zero-knowledge proofs operating over the classical control plane of scalable QKD networks. The requirements for such a method are formulated, and its compatibility with formal QKD security proofs is discussed.
The paper addresses entity authentication in quantum key distribution (QKD) systems as a decisive condition of their practical security. It is shown that the information-theoretic security of quantum key agreement does not eliminate the need to authenticate the communicating parties: an unauthenticated classical channel leaves the system exposed to the man-in-the-middle attack, since the eavesdropper can run independent QKD instances with each party and reconcile two keys under full control. Existing authentication methods are analysed and classified by the underlying cryptographic primitive: symmetric schemes based on Wegman–Carter universal hashing, pre-shared and fixed keys, public-key infrastructure, two-way authentication, quantum entity/identity authentication, and zero-knowledge proofs. For each class the operating principle, advantages and limitations are determined, with emphasis on key management, scalability and trust distribution. It is established that symmetric and quantum-layer methods rely on pre-shared secrets with a quadratic growth of key material, public-key infrastructure introduces a single trust bottleneck and quantum-vulnerable primitives, while existing zero-knowledge authentication schemes are quantum and bound to the physical layer or solve network properties other than identity. A comparative analysis reveals an unresolved scientific gap: the absence of a scalable entity-authentication method that simultaneously provides non-disclosure of the secret, quantum resistance, sub-quadratic scalability and minimisation of trust assumptions. On this basis, a prospective research direction is substantiated – the construction of entity-authentication methods based on post-quantum zero-knowledge proofs operating over the classical control plane of scalable QKD networks. The requirements for such a method are formulated, and its compatibility with formal QKD security proofs is discussed.
Hayder A. Nahi, Rusul A. Salman, Awring Falah Hassan, Ebtehal Akeel Hamed · 7 authors
Abstract The Internet of Things look out on growing security and privacy defies, principally in light of the up growth of quantum threats. To handle these defies, we suggest a unified security framework that merges post-quantum blockchain technologies and zero-knowledge proofs (ZKPs) to attain secure authentication, decentralized identity management, and advanced data protection. The provided system based on a power-weighted consensus mechanism, compressed and overlapping recursive ZKPs, and transaction batching to decrease on-chain load. The outcomes display that the suggested system outperforms conventional systems and state-of-the-art solutions, with response time reduced to 92 ms, transaction throughput increased to 735 tx/s, energy consumption reduced to 0.37 J/op, and authentication accuracy increased to 97.6%, achieving a privacy score of 0.91.These outcomes emphasize that the offered framework not only attains superior performance but as well supplies strong resistance to quantum attacks and high privacy warranties, making it a promising solution for securing future IoT environments.
Reshma D’Souza, S Sheela, H S Sameena, S Jyothi · 6 authors
Abstract: In this era where technology is used to create unidentical counterfeit products, Finding the original objects is a very tedious task for the users. These Counterfeit Products affect the health of the user in the case of medical and skin care products also. This project implements Blockchain, a new Technology which is used to overcome this problem. Blockchain technology is the distributed, and immutable technology that provides data consistency and security. Here a QR code is generated for each product that is linked to the database which in turn is mapped to the chain nodes. By scanning this QR code the user can detect the original products amongst the fake ones. It highlights the need of cryptocurrency in the broader vision of supply chain security, elaborating on how Blockchain network, particularly using Ethereum Framework, provides a decentralized and transparent ledger for tracking and validating products.
Muhammad Wahid, Shahzaib Khan, Mashhood Ali, Muhammad Hassan · 6 authors
The immutable nature of smart contracts makes it challenging to fix and patch bugs once they are deployed to a blockchain. This implies that security vulnerabilities may be exposed to possible exploitation for a longer period, necessitating comprehensive pre-deployment testing. Property-based testing combined with fuzzing has proven itself as a promising technique for uncovering vulnerabilities. Traditionally, system properties are written by human experts, which is time-consuming and consequently expensive.With the recent advancement in Large Language Models (LLMs) and their ability to 'understand' natural language and code semantics, it may be possible to generate effective properties. This study, leverages state-of-the-art LLMs to generate high-quality properties for Soliditybased smart contracts. We measure the quality of the generated properties using mutation testing. Our results show that LLMs have the potential to generate high-quality properties that are close to those written by human experts. We extensively evaluate LLMs using various prompting techniques (e.g., zero shot, few shot, and prompt chaining). Overall, we find that Gemini Pro 1.5, when combined with prompt chaining, achieves the highest average mutation score of 25.99% among all studied configurations, closely approaching the human written benchmark of 31.75%. However, our per contract analysis reveals notable variance, particularly for the LibBit contract, where Gemini Pro 1.5 under prompt chaining achieves a mutation score of 74.34%, which is on par with human written properties (74.83%). This highlights that while average performance is informative, individual contract level results demonstrate that LLMs can, in some cases, match expert level property generation.