We solve Bellman's lost-in-a-forest problem for the golden gnomon $G$, the isosceles triangle with equal sides $1$ and apex angle $108^\circ$: the shortest curve guaranteed to reach the boundary of $G$ from an unknown starting position and heading is a symmetric seven-piece path of segments, circular shoulders, and tangents, of exactly determined length $C=1.282676025459\ldots$. To our knowledge, this is the first proved exact optimum for an isosceles triangle whose base angle is below $45^\circ$. The curve's parameters come from one isolated quartic root, and $C$ is transcendental. Equivalently, $C^{-1}G$ is the smallest homothetic golden-gnomon cover of all unit arcs. The proof introduces a balanced support calibration: one weighted family of escape inequalities, built on the linear relation among the triangle's three normals, exactly saturated by the candidate, through eighteen exact support windows, and confronting every shorter competitor at once. Aggregation along the normal fan compresses the calibration to a finite zero-sum family of supported vectors; summation by parts then bounds its total by path length whenever the running suffix balance, the ledger, stays in the unit disk. A local two-gap surgery and cyclic bitonicity force a shortest hypothetical counterexample into exactly the temporal order the ledger tolerates. Lean 4 verifies the two finite algebraic certificate families and the reusable discrete ledger identities and bounds.
The Financial Technology (FinTech) ecosystem has become a disruptive one which changed the face of the financial services industry with digital technology, innovative business models and new regulatory framework. The development, distribution and use of financial products and services have been revolutionized by technologies like artificial intelligence, blockchain, cloud, big data analytics, Internet of Things and open banking. This review paper aims to integrate and consolidate the available literature to gain an overview of the development of FinTech from Finance 1.0 to Finance 4.0, and their technological innovations as the backbone of the modern financial systems. It also explores some of the key FinTech business models like digital payments, digital lending, WealthTech, InsurTech and embedded finance, and the essential role of relevant government policies, digital public infrastructure and governance for responsible FinTech innovation. The paper also identifies relevant challenges in the fields of cybersecurity, data privacy, ethics in artificial intelligence, regulatory complexity and digital inclusion that remain to significantly impact the sustainable development of the FinTech ecosystem. Last but not least, new research opportunities are identified in the field of generative artificial intelligence, decentralized finance, green FinTech, and digital financial governance to be pursued by academia in the future. The multidisciplinary perspective employed in this review gives a comprehensive picture of the current developments in FinTech and can help researchers, practitioners and policymakers to understand the opportunities and risks associated with digital financial transformation.
The global healthcare supply chain is experiencing increasing challenges with respect to maintaining the security of medications, adequate storage of medications, and identifying potential issues with medications that may pose a risk to patient safety. This chapter introduces a prototype called the 'Smarter, Safe Healthcare Supply Chain.' The system brings together fast telemetry (simulating 4G and 5G), edge computing, blockchain smart contracts, and explainable anomaly detection to help stop compromised medications from reaching patients. Included in the prototype's design are an IoT temperature and location data sensing simulator; an edge service that checks the signature of a device and executes "explainable" checks; and two smart contracts associated with device tracking and alerting. Tools like latency simulation, on-chain device tracking, device allowance (i.e., allowing only those devices that have been verified via smart contracts to access the network), and audit logs allow for the prototype to demonstrate how new technologies can enhance, accelerate, and streamline operations and build trust throughout the supply chain. Some of the key results of the prototype include faster-than-anticipated response times under 5G simulated conditions, successful verification of devices (both at the edge and enterprise-level) via smart contract(s), and accurate alerting developed based on a predefined set of rules. The framework upon which the prototype is built follows the principles of Zero Trust (e.g., NIST SP 800-207A, GSMA 5G IoT Guidelines, and use case-specific Healthcare Compliance Controls). Limitations exist within the prototype (such as being a single-node blockchain and the use of rule-based alerting versus leveraging full machine learning capabilities); however, it presents a viable operational model for practical application within a regulated supply chain (e.g., pharmaceuticals). Future work will include multi-party blockchain networks, evolving AI algorithms, and demonstrating full integration of the prototype into existing regulatory workflow(s).
Abstract Coral reefs across the Coral Triangle are experiencing unprecedented thermal stress, and the window for effective local mitigation of bleaching events is often measured in days, not months. Yet the standard reef-monitoring pipeline — collecting benthic imagery via divers or remotely operated vehicles (ROVs) and manually annotating it for signs of bleaching — routinely takes weeks to complete, a delay we term the manual-annotation bottleneck. This paper presents CoralEye, a decentralized, edge-optimized computer vision framework that diagnoses coral health in real time and is designed to eventually run entirely offline on consumer-grade hardware. CoralEye uses an optimized MobileNetV2 architecture, quantized to INT8 for edge deployment, trained on a curated subset of the Benthic Habitat Data (BHD) dataset to classify reef imagery into a three-class triage system — Healthy, Bleached, and Dead. On a held-out test set of 636 images, the framework achieved an overall accuracy of 97% (weighted-average precision 0.98, recall 0.97, F1-score 0.97) while processing underwater imagery at an average latency of 177 milliseconds per frame (∼5.6 FPS), benchmarked in a Google Colab CPU-only cloud runtime as a proxy for offline, GPU-free edge hardware. Relative to established manual annotation workflows such as Coral Point Count (CPCe), this proxy benchmark suggests a reduction in per-image processing time of over 99%, though this comparison has not yet been validated on a physical field device. We argue that this combination of accuracy and CPU-only efficiency is a promising step toward a shift in marine conservation technology from post-mortem documentation toward real-time, actionable diagnostics — particularly for under-resourced reef managers in bandwidth-constrained coastal communities, pending further validation on physical field hardware.
This paper investigates the evolving link between cryptocurrency and equity markets in the context of the recent wave of corporate Bitcoin (BTC) treasury strategies. We assemble a dataset of 39 publicly listed firms holding BTC, from their first acquisition through April 2025. Using daily logarithmic returns, we first document significant positive co-movements via Pearson correlations and single factor model regressions, discovering an average BTC beta of 0.62, and isolating 12 companies, including Strategy (formerly MicroStrategy, MSTR), exhibiting a beta exceeding 1. We then classify firms into three groups reflecting their exposure to BTC, liquidity, and return co-movements. We use transfer entropy (TE) to capture the direction of information flow over time. Transfer entropy analysis consistently identifies BTC as the dominant information driver, with brief, announcement-driven feedback from stocks to BTC during major financial events. Our results highlight the critical need for dynamic hedging ratios that adapt to shifting information flows. These findings provide important insights for investors and managers regarding risk management and portfolio diversification in a period of growing integration of digital assets into corporate treasuries.
Abstract A secure platform for exchanging and storing agricultural data is provided via a blockchain-powered framework. By integrating edge computing, blockchain technology, and the Internet of Things (IoT) the production of crops can be boosted while using fewer natural resources. In the sector of agriculture, sensors and equipment gather various data about the landscape, which can subsequently be delivered to a server in a cloud environment. Due to its extreme fragility, these data must be securely stored and guarded from unwanted access. The core aim of this work is to propose a hybrid Reconditioned Random value-based Wombat Optimization with Adaptive Multi-scale Vision Transformer-based EfficientNet (RRWO-AMViT-ENet) model integrated with Ethereum smart contracts for secure pest detection and smart irrigation in IoT environments. The gathered agricultural images are initially stored and managed using the Ethereum blockchain. Then, node authentication is performed using the Smart Contract-based Adaptive Deep Support Vector Machine (SC-ADSVM). A Reconditioned Random value-based Wombat Optimization (RRWO) is utilized to optimize the variables of the developed SC-ADSVM. In order to perform pest detection and smart irrigation, the Adaptive Multi-scale Vision Transformer-based EfficientNet (AMViT-ENet) is used. The proposed model is implemented on the IP102-Dataset, where it obtained an accuracy of 96.39% in the pest detection operation. Thus, the proposed model provides effective results for pest detection and the smart irrigation process. From the attained results, it is concluded that the recommended strategy can provide intelligent service to the farmer.
Blockchain technology provides a decentralized and secure data-management system. However, PoW consensus remains vulnerable to the risk of 51% attacks, where a single miner or pool controls over half of the network and can manipulate blocks and execute double-spending. This paper proposes a defense mechanism called Consensus-Level Restriction (CLR) for Ethereum Classic. It limits the number of sequential blocks from a single miner to reduce the feasibility of 51% attacks. We evaluated the effectiveness of CLR by using BlockSim simulator. Results show that CLR reduces the success rate of 51% attacks while maintaining a decentralized structure. This work strengthens blockchain security without compromising PoW principles.
When is honest Bitcoin mining rational? This question is central to the incentive design of proof-of-work blockchains. Sapirshtein et al. computationally derived near-tight lower and upper bounds on the incentive-compatibility threshold using a Markov Decision Process. Kiayias et al.'s Blockchain Mining Games instead derived theoretical lower and upper bounds. However, this theoretical approach has two limitations: its model restricts miners to a narrow action space and assumes idealized tie behavior, and its lower and upper bounds are far from tight. We resolve both limitations. We develop a more realistic model with a broader miner action space and asymmetric tie-breaking parameters $γ^-$ and $γ^+$. We then propose an algorithm that computes lower and upper bounds on the incentive-compatibility threshold with a maximum error of $9.98006\times10^{-4}$.
We study the impact that two miners equipped with quantum computers purpose-built for quantum Bitcoin mining will have on the 51% attack threshold of the Bitcoin network, given that the miners are playing a competitive game against each other to be the first to mine a block. We extend an existing game-theoretic framework for Bitcoin mining and compute the resultant payoff matrices. From these payoff matrices, we determine optimal quantum mining strategies for two non-colluding and aggressive quantum miners with multiple opportunities at finding a valid block in an otherwise classical Bitcoin network. We show that these optimal quantum mining strategies have a negligible effect on the 51% attack threshold. The novelty of our work is the inclusion of the Aggressive Quantum Mining Strategy and the realistic approach of allowing the quantum miners to restart their search if their measurements do not yield a valid block when determining the optimal quantum mining strategies. Our result is important for evaluating quantum-mining threats on cryptocurrencies based on Proof-of-Work, e.g. Bitcoin
Language-model efficiency is often discussed through concepts that are related but not equivalent: token count, embedding dimensionality, parameter count, key-value cache size, and retrieved-context length. This article presents a structured critical review, supported by document-level traceability, of matrix and vector methods used to reduce storage and inference costs in language models and retrieval-augmented generation (RAG) systems. The analysis shows that matrix factorization, adaptive embeddings, and Matryoshka representations compress parameters or vectors but do not automatically decrease the number of input tokens. Direct token reduction requires sequence-level interventions, including appropriate tokenization, selection, prompt compression, gist tokens, and retrieved-context control. KV-cache compression reduces memory and latency without necessarily changing the tokens submitted to the model. We propose a mathematical framework that separates V (vocabulary size), d (embedding dimension), n (sequence length), k (number of retrieved documents or passages), and nKV (cache positions retained).
The widespread problem of cyberbullying in today’s digital environment is made worse by the quick spread of IoT devices and the difficulties in organizing and protecting digital evidence. Traditional forensic methods are often inadequate due to their inability to provide a tamper-proof chain-of-custody and their limited scalability under high data loads. To overcome these constraints, our work makes use of innovative technologies such as a permissioned blockchain (Hyperledger Fabric), powerful encryption methods (AES-256 and RSA), and decentralized off-chain storage (IPFS). We propose an integrated, blockchain-driven forensic evidence collection framework that ensures secure, real-time evidence acquisition from diverse IoT devices, automated validation via smart contracts, and efficient, Role-Based Access Control for evidence retrieval. A hybrid consensus mechanism, combining elements of PBFT and Proof-of-Stake, enhances the system’s security and scalability while reducing processing latency and energy consumption. Experimental results demonstrate that our approach achieves high throughput and low latency, making it a strong and reliable solution for forensic investigations in cyberbullying cases. Within our experimental scope, the framework strengthens the integrity and authenticity of digital evidence and addresses key regulatory considerations, though real-world validation remains future work.
The governance of new technology projects in remote and developing economies is frequently undermined by severe information asymmetry and fragmented telecommunications infrastructure. While theoretical public policy advocates for the deployment of distributed ledger technologies to enhance institutional design and regulatory transparency, evaluating the economic impact of these systems relies heavily on static, retrospective datasets. This paper proposes a cloud-native architectural framework utilizing Amazon Web Services to construct a real-time, serverless pipeline for telecommunications governance and blockchain integration. By deploying asynchronous Python middleware integrated with simulated smart contracts, the proposed system programmatically ingests high-frequency network telemetry and cross-border telecommunications data. The system translates these inputs into a dynamic Institutional Transparency Index, instantly identifying regulatory bottlenecks and pricing friction across public-private partnerships. Preliminary architectural evaluations demonstrate that decoupling the governance tracking from legacy, centralized state databases significantly reduces information asymmetry, providing policy researchers with a deterministic, highly scalable tool for modeling the economics of distributed ledgers in developing contexts.
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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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.
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.