У статті досліджено економічний потенціал блокчейн-технологій як інструменту протидії глобальним змінам клімату. Проаналізовано реальний екологічний вплив криптовалют, зокрема порівняно енергоспоживання мереж Bitcoin та Ethereum після переходу на Proof-of-Stake. Розглянуто механізми токенізації вуглецевих кредитів, роль децентралізованих фінансів (DeFi) та децентралізованих автономних організацій (DAO) у кліматичному фінансуванні. Висвітлено практичні кейси застосування блокчейну в секторі відновлюваної енергетики та ризики грінвошингу. Окремо проаналізовано внесок вітчизняних науковців у дослідження впливу блокчейну на екологічну стійкість та формування «зеленої» цифрової економіки в Україні. Визначено перспективи інтеграції штучного інтелекту та Web3-технологій у кліматичні ініціативи до 2030 року.
This paper is written to evaluate and describe the legality of ‘smart contracts and DAOs. While traditional contracts provide general foundational elements which only fulfills the legal relation criteria. Application of these principles to blockchain based smart contract is very equivocal although, the concept itself provides numerous pros like technological efficiency and self-execution etc. This paper highlights the need to bridge the gap between legal doctrine and code-based execution through the development of legal framework. Furthermore, it explores the critical position of DAOs, which operate without centralized governance. By analyzing emerging global approaches and regulatory opinions, this paper highlights the essential need of innovation and compliance in this concept.
ECDSA signatures form the bedrock of blockchain transaction authentication, yet their security critically depends on proper nonce generation. We uncover a critical vulnerability in the Polygon MEV ecosystem: systematic nonce reuse that enables complete private key recovery. Analyzing on-chain data reveals that searchers, driven by the need for sub-second response times in sealed-bid auctions, employ predictable nonce patterns. These patterns create linear relationships between signatures, allowing passive attackers to recover private keys using elementary algebra. We provide a compact linear-system formulation for such attacks, including the dangerous case of cross-wallet nonce collisions, and present concrete evidence of exploitable patterns on Polygon. Our findings demonstrate how protocol-induced latency pressures can lead to catastrophic cryptographic failures in production blockchain systems, where a single implementation error compromises multiple accounts simultaneously.
I replicate and extend the cross-sectional trend-factor methodology of Liebi, Stulz, and Tsyvinski (2024) on a contemporaneous out-of-sample period and a liquidity-restricted coin universe. Using 141 USDT spot pairs over 128 weekly observations from November 2023 to April 2026, an Elastic-Net cross-sectional regression aggregating 29 technical indicators generates a long-short portfolio with a mean weekly return of 3.82% (Newey-West t = 5.03) and an annualized Sharpe ratio of 4.54. The strategy delivers market-neutral alpha of 3.82% per week (t = 7.09) with a CAPM beta of 0.020. Three findings warrant emphasis. First, value-weighting destroys the alpha entirely, confirming concentration in smaller, dispersed names. Second, twelve of the top fifteen Elastic-Net coefficients are negative, indicating that the underlying pattern is short-term reversal rather than trend continuation. Third, returns are heavily regime-dependent, with Sharpe ratios near 1.0 in trending markets and above 7.0 in dispersive regimes. Cross-sectional dispersion-harvesting alpha persists in cryptocurrency markets, but its empirical realization is sharply sensitive to universe liquidity, weighting scheme, rebalance horizon, and market regime.
The Internet of Things (IoT) has become a major issue that has gained significant attention in the research community. Advances in IoT technologies have resulted in the emergence of various security issues and raised concerns about potential privacy breaches of IoT data. Utilizing Blockchain (BC) is seen as a promising solution for addressing security issues in the IoT. This paper offers a clear overview of IoT security threats, including the related security characteristics and the challenges that come with integrating BC with IoT. A brief discussion of various consensus protocols and existing security techniques is presented. A comparative study of several Distributed Ledger Technology (DLT) platforms based on both qualitative and quantitative evaluation criteria is also presented. This paper explores the role of BC Technology in improving security in Intrusion Detection Systems (IDS) and other applications in the IoT environment. Additionally, the paper identifies open issues and highlights potential research opportunities that can benefit future studies.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion resources: Kowalski et al. (2026a), A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring. https://doi.org/10.5281/zenodo.19502460 Kowalski, M. M. and Claude (Anthropic). (2026). Taxonomy of AI Bullshit: hallucination and hedging subcategories. Zenodo. https://doi.org/10.5281/zenodo.20631337. Kowalski, M. M. & Claude (Anthropic). (2026). Hallucination Test Suite and Execution Records: test strings, activation blocks, trial data and AI transcripts. Zenodo. https://doi.org/10.5281/zenodo.21325014.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion paper: Kowalski et al. (2026a), "A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring." https://doi.org/10.5281/zenodo.19502460
Résumé Au Maroc, les très petites entreprises (TPE) représentent 96 % du tissu entrepreneurial et génèrent 23 % du PIB, mais 75 à 80 % d'entre elles demeurent exclues du crédit bancaire formel. Dans ce contexte d'exclusion financière structurelle, la Finance Décentralisée (DeFi) — fondée sur les technologies blockchain et les smart contracts — se présente comme une alternative potentielle. Toutefois, son adoption par les dirigeants de TPE reste conditionnée par un ensemble de déterminants encore peu explorés dans la littérature, en particulier la confiance dans ces technologies. Cet article vise à identifier les déterminants de l'intention d'adoption de la DeFi par les TPE marocaines à travers une revue de la littérature et la proposition d'un modèle conceptuel de recherche. En s'appuyant sur le modèle UTAUT (Venkatesh et al., 2003) comme cadre théorique de référence, complété par les théories de la confiance dans les systèmes technologiques (McKnight et al., 2002 ; Pavlou, 2003 ; Zhou, 2011), cet article propose un modèle étendu intégrant cinq déterminants directs de l'intention d'adoption : la facilité d'usage perçue, l'utilité perçue, l'influence sociale, les conditions facilitatrices, et la confiance dans la technologie DeFi — algorithmi que et institutionnelle. Le genre et l'âge du dirigeant sont intégrés comme variables modératrices. Sur le plan théorique, cet article contribue à enrichir la littérature sur l'adoption des FinTech en proposant une opérationnalisation de la confiance adaptée aux spécificités de la DeFi dans un contexte d'économie émergente. Sur le plan managérial, il fournit un cadre actionnable pour les décideurs publics, les régulateurs et les concepteurs de solutions DeFi ciblant les marchés non bancarisés. Mots-clés : Finance Décentralisée (DeFi) ; UTAUT ; Confiance ; Adoption technologique ; TPE Maroc ; Inclusion financière ; Blockchain ; FinTech ; Modèle conceptuel Abstract In Morocco, micro-enterprises (TPEs) account for 96% of the entrepreneurial fabric and generate 23% of GDP, yet 75 to 80% of them remain excluded from formal bank credit. Against this backdrop of structural financial exclusion, Decentralized Finance (DeFi) — built on blockchain technologies and smart contracts — emerges as a potential alternative. However, its adoption by TPE managers remains conditional on a set of determinants that are still underexplored in the literature, particularly trust in these technologies. This paper aims to identify the determinants of DeFi adoption intention among Moroccan micro-enterprises through a literature review and the proposal of a conceptual research model. Drawing on the UTAUT model (Venkatesh et al., 2003) as the theoretical framework, complemented by trust theories in technological systems (McKnight et al., 2002; Pavlou, 2003; Zhou, 2011), this article proposes an extended model integrating five direct determinants of adoption intention: perceived ease of use, perceived usefulness, social influence, facilitating conditions, and trust in DeFi technology — algorithmic and institutional. The manager's gender and age are included as moderating variables. Theoretically, this article contributes to the FinTech adoption literature by proposing an operationalization of trust adapted to the specificities of DeFi in an emerging economy context. Managerially, it provides an actionable framework for policymakers, regulators, and DeFi solution designers targeting unbanked markets. Keywords: Decentralized Finance (DeFi); UTAUT; Trust; Technology Adoption; Micro-Enterprises Morocco; Financial Inclusion; Blockchain; FinTech; Conceptual Model
Prof. Narde S. A., Yadav N.S., Ghodake D.T., Patil S.J., Salunkhe S. S.
Abstract In recent years, the rapid growth of digital technologies in education has increased the importance of academic certificates for employment, higher studies, and professional validation. However, the issue of fake and forged certificates has become a serious challenge for institutions and organizations. Traditional certificate verification systems are manual, time-consuming, and often lack transparency and security. These systems are also vulnerable to data manipulation and unauthorized access due to centralized storage. To address these challenges, this paper proposes a blockchain-based academic certificate validation system. The system uses blockchain technology to securely store certificate data in the form of cryptographic hash values generated using the SHA-256 algorithm. Since blockchain is decentralized and immutable, once data is stored, it cannot be altered or deleted. The system allows administrators to upload student data and issue results, which are then stored on the blockchain. Each certificate is associated with a unique verification ID and can be validated using QR codes or direct input. The proposed system improves efficiency, enhances data security, and reduces the risk of fraud. The results demonstrate that the system is faster, more reliable, and more secure than traditional methods.
This replication package contains the data and scripts used in this empirical study, including the LLM-based semantic validation pipeline, the observed practice extraction process, and all figures from the research questions (RQ1–RQ5). ERC_Observed_Practicess.xlsx: workbook of observed practices ERC_Observed_Practices_Process_Review.xlsx: Phases to generate the workbook of observed practices Other supplementary materials: Essential data files (data/) results_semantic_validation.json: 11,559 issues classified by LLM (substantive, category, justification) sample_manual_review_updated.csv: ~400 manually reviewed entries for LLM quality validation eips_labels.csv / ercs_labels.csv: PR metadata from Ethereum repositories for status evolution analysis (RQ5) Scripts (scripts/) 01: scrapes the official ERC list from ethereum.org 02 : filters the dataset for ERC mentions via regex 03: classifies issues via Gemini (substantive + category) 03: removes duplicates from the validation JSON 03: merges LLM results with issue metadata 04: extracts observed practices per ERC via Gemini, cross-referenced with official specs 05: fetches GitHub labels and generates ERC status evolution figure (RQ5) 06: generates all quantitative figures (RQ1–RQ4)
While public blockchains provide transparent and auditable transaction histories, they inherently compromise user privacy. Existing privacy-enhancing protocols, such as those deployed on Ethereum, typically rely on succinct zero-knowledge proofs (zk-SNARKs) to obscure the transaction graph. However, implementing comparable cryptographic guarantees on high-throughput blockchains like Algorand is challenging due to strict per-call execution budgets and the state contention introduced by global Merkle accumulators. This paper presents Obscura, a decentralized, non-custodial privacy protocol tailored for constrained smart contract environments. Obscura achieves transaction anonymity using Linkable Spontaneous Anonymous Group (LSAG) signatures over the BN254 elliptic curve, verified entirely on-chain. To overcome limitations of the Algorand Virtual Machine (AVM), we introduce a novel state model that leverages Algorand's Box Storage for $O(1)$ commitment membership checks, eliminating the need for global Merkle accumulators, and a dynamic opcode-budget expansion mechanism via pooled inner application calls. Our implementation demonstrates that signer-ambiguous privacy is practical and efficient on Algorand without relying on trusted setups or succinct proofs. Obscura provides a robust privacy layer for transparent ledgers, bridging the gap between high-throughput blockchain architectures and the dual requirements of cryptographic privacy and selective auditability.
Decentralized autonomous organizations (DAOs), while gaining the ability toautonomously amend governance rules through proposal-voting mechanisms, simultaneously expose a fundamental design problem: when the object of modificationextends to the decision-making procedures themselves, the governance system risksfalling into value drift, procedural disintegration, or malicious capture during recursive revisions. This paper starts from the traditions of constitutional politicaleconomy and mechanism design to propose a hierarchical meta-constraint framework grounded on a gradient of engineering costs. The framework organizes governance rules into three tiers of decreasing rigidity: system consistency constraints,procedural virtues, and value homeostasis. Its highest tier relies not on prohibitionsderived from logical laws, but on the global state re-verification costs triggered byamendment behaviors to serve as a credible commitment device. The paper furtherpresents a technical path for compiling meta-constraints into descriptive assertionsverifiable by satisfiability modulo theory (SMT) solvers, delimits the decidabilityboundary of formal verification, and designs a dual-track adjudication mechanismthat structurally separates deterministic machine execution from deliberative socialconsensus. On this basis, the paper discusses the controlled evolution procedures ofmeta-constraints, the progressive decentralization of amendment procedures, andthe engineering limitations of the framework. The entire framework does not designate the correct option for any specific DAO decision; rather, it ensures thatwhatever direction the community chooses, the selection process itself will not losemeaning due to the self-destruction of its own rules.
This paper presents Polyquity, a Web2.5 platform enabling decentralized Initial Public Offering (IPO) fundraising through a hybrid data architecture. The platform leverages the Avalanche C-Chain for high-speed settlement, while utilizing a custom WebSocket indexer and PostgreSQL database to bridge the gap between blockchain security and institutional-grade user interfaces. By implementing a strict Role-Based Access Control (RBAC) model alongside modular architecture for auction mechanisms, fund escrow, and secondary market functions, Polyquity demonstrates how decentralized capital formation can achieve web2-equivalent performance while preserving core web3 security. The system utilizes the blockchain as the ultimate source of truth for state and funds, while the relational database serves as the source of speed for client-side rendering. Polyquity achieves sub-2-second transaction finality with 50% lower costs than Ethereum, supporting 10,000+ concurrent participants. This work establishes practical mechanisms for bridging traditional finance and decentralized ecosystems through a highly scalable, hybrid full-stack design.
Blockchain-based financial systems process billions in transactions but remain vulnerable to sophisticated fraud schemes. Current detection approaches analyze completed transactions, preventing neither fund loss nor protocol exploitation. We address this through an oracle-mediated prevention system integrating machine learning inference with smart contract execution. Training ensemble models on 12,847 Ethereum transactions with engineered features capturing gas anomalies and temporal patterns, we achieve 94.2\% fraud classification accuracy. Testnet deployment demonstrates 1.09-second response latency with 6.8\% computational overhead, contrasting favorably against prior on-chain implementations requiring 34\% overhead. Our working prototype validates practical viability for production environments where security requirements justify marginal transaction costs.
This paper explores contemporary blockchain applications in the supply chain and logistics sector, focusing on how distributed ledger technology enhances transparency, traceability, security, and operational efficiency across complex global supply networks. The study reviews key blockchain concepts, including consensus mechanisms, smart contracts, and tokenization, and examines their role in improving coordination among stakeholders. Real-world case studies from organizations such as Walmart, Nestlé, Pfizer, Moderna, and Maersk demonstrate practical implementations of blockchain for product traceability, anti-counterfeiting, and shipment tracking. The paper also analyzes major challenges facing blockchain adoption, including scalability limitations, regulatory uncertainty, interoperability issues, and data reliability concerns. Furthermore, it highlights emerging trends such as integration with artificial intelligence, Internet of Things technologies, digital twins, sustainability tracking, and cross-chain platforms. The findings suggest that blockchain plays a critical role in supporting digital transformation initiatives aligned with Industry 4.0 and enables the development of more resilient, transparent, and trustworthy supply chain ecosystems.
Renewable energy in Africa has gained increasing attention as a strategic pathway to achieving sustainable development, energy security, and economic transformation. A structured search of peer-reviewed studies was conducted using Web of Science, Scopus, and ProQuest. Fifteen empirical studies met the strict PRISMA inclusion criteria for detailed systematic synthesis, while additional high-quality review articles, book chapters, and policy reports were incorporated to strengthen contextual interpretation of renewable energy deployment trends across Africa. This systematic review synthesizes empirical evidence on renewable energy deployment across the continent, focusing on trends, challenges, and opportunities. Africa is endowed with abundant solar, wind, hydropower, geothermal, and biomass resources, yet actual utilization remains uneven and limited, with solar and wind experiencing the most rapid growth in recent years. Hydropower continues to dominate installed capacity, while geothermal and emerging technologies remain largely underdeveloped. Persistent barriers to deployment include inadequate grid infrastructure, limited access to finance, policy and regulatory inconsistencies, institutional capacity constraints, and political instability, particularly in rural and decentralized systems. Despite these challenges, opportunities exist in the form of declining technology costs, growing private and international investment, expansion of decentralized energy systems, and regional cooperation initiatives. Strengthening policy implementation, improving governance coordination, investing in infrastructure and human capital, and promoting innovative financing mechanisms are critical to accelerating Africa’s renewable energy transition.
This white paper introduces the Coherence Ledger, a decentralized and time-weighted integrity scoring system designed to evaluate individuals and organizations based on long-term behavioral patterns rather than short-term claims.It critiques existing trust systems—including online reviews, credit scoring, and professional directories—as structurally vulnerable to manipulation, opacity, retaliation, and extraction incentives.The framework proposes a transparent scoring protocol combining behavioral events, exponential time decay, decentralized identity verification, and peer-based trust propagation to create measurable coherence scores.It integrates technologies such as decentralized identifiers (DIDs), Soulbound Tokens, and web-of-trust mechanisms to reduce gaming, increase accountability, and preserve auditability across digital systems.Positioned as post-extractive trust infrastructure, the work outlines how the Coherence Ledger could support hiring, finance, media verification, and institutional risk analysis by making extraction visible and rewarding sustained coherent behavior over time.
The rapid expansion of Artificial Intelligence Data Centers (AIDC) faces severe physical constraints, notably the linear O(n) scaling of power consumption, cooling requirements, and latency. In this paper, we propose the Lattice Swarm Protocol, a paradigm shift in distributed edge computing utilizing an O(1) constant memory architecture combined with the Virtual-to-Materialization (V2M) engine. We mathematically demonstrate that when interconnected via high-speed 400G/800G optical networks, multiple 1MW ultra-low-power edge nodes do not compute independently. Instead, they share Spatiotemporal Environmental Hashes across a 9192-D Lattice network. This mechanism exponentially reduces the computational load of the entire network as node count increases, creating a single 300MW-equivalent "Hyper-Organism" from merely 30 distributed 1MW nodes. We empirically validate this architecture through the implementation of zero-latency Stateless Custody protocols and interstellar acoustic materialization (Voyager 1), both audited by Google DeepMind Antigravity. This infrastructure establishes a new global standard for Autonomous Driving and Urban Air Mobility (UAM).Version 2 Update: Integrated Zero-Knowledge Proof (ZKP) mechanisms and Stateless Key Vaporization (0.024s), aligned with KIPO Patent No. 10-2026-0079266.
We introduce a new polynomial-time graph invariant combining three complementary components: (1) the enriched Bipartite Double Cover (BDC) vertex cover signature; (2) the Laplacian eigenvalue spectrum; and (3) the K_4 clique profile and Ollivier-Ricci curvature. We demonstrate that while spectral and standard BDC methods collapse on strongly regular graphs (SRGs) due to extreme symmetry, the geometric and dense-topological components of this hybrid invariant break the cospectrality. Specifically, the invariant successfully discriminates the classical cospectral pair Shrikhande vs. Rook(4,4) [SRG(16,6,2,2)] in polynomial time, where Shrikhande is K_4-free and Rook(4,4) contains exactly 8 cliques. Furthermore, empirical validation on low-power ARM Edge hardware demonstrates that the invariant scales efficiently, processing dense Paley graphs (up to N=97) in under 5 milliseconds. This confirms its sub-millisecond viability for real-time edge computing, zero-knowledge proofs (ZKPs) cryptanalysis, and cheminformatics.
This paper is the authoritative technical documentation of immo.quick Core version 2.1.0. It introduces and formally specifies the Deterministic Execution Proof Engine (DEPE) — the overarching orchestration layer that unifies five interlocking architectural components (Prior Admissibility Space, Exogenous Anchor Protocol, Sensor/Oracle Trust Bridge, Bi-Temporal Ledger, Machine Law Engine) into a single, unbroken, cryptographically provable execution corridor. Every transaction processed by DEPE produces an Execution Proof Artifact (EPA): a self-contained, externally verifiable, court-admissible proof object that the transaction was evaluated correctly under the rules applicable at the moment of execution. The EPA is not a log entry or a summary — it is a formal proof object that either verifies completely under the 6-step DEPE Verification Protocol, or does not verify at all. Version 2.1.0 introduces seven architectural advancements over v2.0.0: DEPE (Deterministic Execution Proof Engine): The integration layer producing a single signed EPA per transaction, cryptographically binding all five architectural layer outputs into an indivisible unit. EPA signature scheme: CRYSTALS-Dilithium-3 (NIST PQC standard). EPA generation latency: <100ms median. External verification latency: <50ms. JPO Pre-Fill Protocol: Reduces regulatory update latency for announced changes from 34ms to under 5ms by proactively compiling and staging rules upon legislative announcement, enabling millisecond-precision atomic swap at the effective date. Checker Rotation Governance (Six-Eye Principle): Formalizes a third independent checker drawn from a rotating governance pool for high-value and high-risk transactions. Rotation is deterministic (hash-based), requires no human discretion, and is itself bi-temporally logged and attested. Bypass requires simultaneous compromise of three institutionally separated hardware devices. BFT Quorum Specification: Formalizes Byzantine Fault Tolerance for the Bi-Temporal Ledger at f ≤ ⌊(n−1)/3⌋. Production configuration: n=7, f=2, quorum=5. Record commitment latency: 4ms median. Merkle replication lag: 12ms median. Deny Path Artifact (DPA): Every BLOCK decision generates a signed, immutable DPA specifying the exact gate condition, rule reference, and structural reason for rejection. Courts, regulators, and counterparties can independently verify not only that a transaction was blocked, but precisely why — with cryptographic proof. ZKP Circuit Library v2: Expanded to 47 pre-compiled, formally verified zero-knowledge proof circuits across banking/capital, AML/KYC, DORA/ICT, privacy/data, real estate, cross-border, and regulatory filing categories. All circuits use Groth16 and PLONK proving systems and are integrated directly into the Machine Law Engine compilation pipeline. Known Patterns Extension Protocol (KPEP): Enables ~70% acceleration for registered common transaction classes via formally verified proof templates, without any security reduction. Template match failure triggers automatic fallback to the full standard path. Additional v2.1.0 enhancements: ACASP Second-Order Anomaly Detection (ambiguity itself is a blocking condition); EAP dual-channel heartbeat with gap tolerance tightened from 50ms to 35ms; Offline Receipt Export for self-contained external verification without live system dependency. Central architectural guarantee (unchanged and strengthened): immo.quick Core is the only production architecture providing a complete, unbroken, cryptographically enforced provenance chain from the moment of physical real-world observation through the enforcement gate — with formally guaranteed zero false approval rate (Closed-World Assumption), formally guaranteed temporal accuracy (Bi-Temporal Ledger + BFT Quorum), and — as of v2.1.0 — a fully machine-verifiable Execution Proof Artifact for every transaction ever processed. This paper provides full formal specifications (TLA+/Z3 style), three detailed institutional case studies (DORA Art.11 ICT incident gate; cross-border real estate acquisition with §203 StGB / CLOUD Act conflict resolution; FATF Travel Rule enforcement with ZKP-selective disclosure), complete measured production performance data, and a complete attack surface analysis covering nine adversarial vectors including DEPE integration hash forgery and ACASP ambiguity injection. Supersedes: v2.0.0 (April 2026, DOI 10.5281/zenodo.19799660).
This study examines the role of impact investing and climate finance in generating measurable social value through renewable energy projects by applying the Social Return on Investment (SROI) framework. Growing global investment in renewable energy has emphasized financial performance and emission reduction outcomes, while systematic measurement of social impacts remains limited. The purpose of this research is to assess how SROI can be used to quantify the social and environmental value created by renewable energy investments and to demonstrate its relevance for impact-oriented decision-making. A mixed-methods approach was employed, combining secondary project data analysis, stakeholder engagement, outcome mapping, and monetization of social and environmental benefits to calculate SROI ratios. The findings reveal that renewable energy projects consistently produce social returns exceeding the initial investment, with SROI ratios varying according to project type, scale, stakeholder involvement, and socio-economic context. Community-based and decentralized projects tend to generate higher relative social returns, driven by employment creation, improved energy access, health improvements, and environmental benefits. The study concludes that integrating SROI into climate finance evaluation enhances transparency, accountability, and alignment between financial objectives and sustainable development goals.
This paper develops a deep reinforcement learning framework for cryptocurrency portfolio management in which transaction costs are derived from the Riemannian geometry of the underlying volatility model rather than assumed constant. A Proximal Policy Optimisation agent is trained on a reward function grounded in non-equilibrium thermodynamics: we use the free-energy Bellman equation, in which transaction costs are the geodesic slippage on the Fisher information manifold of a maximum-entropy Markov-switching GARCH model, and regime-transition costs are the Wasserstein-2 distance between the calm and turbulent return distributions. A thermodynamic Carnot bound on portfolio efficiency is established and empirically validated. Five hypotheses are tested across Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash over January 2017 to March 2026. The geometric-cost agent achieves statistically superior Sharpe ratios relative to flat-fee baselines on four of five assets; portfolio turnover is reduced by 56 to 83 percent relative to signal-following; the thermodynamic friction point at which the agent prefers no-trade is asset-specific and ordered by turbulent half-life; a joint topological and geometric circuit breaker reduces Maximum Drawdown by 28 to 38 percent; and ablation confirms that every component of the observation vector contributes a statistically significant performance gain. The framework requires liquid cryptocurrency markets with validated parametric volatility models; transferability to other asset classes requires upstream recalibration.
We present a production-ready framework for verifiable self-organization in networks of 768 coupled quantum oscillators (the “Crystal Brain”), integrating sixfine-tuned components: adaptive SPSA optimization with automatic plateau escape, multi-resolution Louvain community detection, non-deterministic proof seeds,normalized causal efficacy metrics, dynamic Merkle root hashing, and a semanticproof-tagging API. We map the Ising regime classification of Bhalla et al. (2026)onto a Kuramoto-type phase dynamics and demonstrate convergence to a coherentCAPTURE regime with 84.7% capture fraction. A companion octonionic atlas of 50nuclides (OctoSpec v0.4) reveals a moderate anti-correlation (r = −0.54, p < 0.001)between the Octonionic Anomaly Index and nuclear binding energy. All coherencemilestones are certified by zero-knowledge proofs generated at 80-bit security viathe ZEE200 backend and registered immutably on the ARKHE OCTRA chain.
The relationship between deterministic polynomial time (P) and polynomial space (PSPACE) is one of the foundational open problems in computational complexity theory. While proving P = PSPACE remains elusive and is widely believed to be false, the characterizations of PSPACE have yielded profound insights into modern computer science, specifically cryptography and zero-knowledge proofs. This paper surveys the landscape of PSPACE, examines the three fundamental barriers preventing resolution, and presents original systems-level experiments in C and Python that make the space-time tradeoff at the heart of the problem tangible and measurable.