Global Asset Restructuring and the Application of the RTO Paradigm under the Official Notice of Mandatory Enforcement: A Forensic Analysis of Systemic Reliability, Physical-Layer Interlocks, and Intellectual Property Sovereignty

【English Abstract】 This monograph presents a comprehensive forensic and systems-engineering analysis of the structural transition from discretionary bailout regimes ("Too Big to Fail") to deterministic physical-layer governance ("Mandatory Enforcement") initiated under the Regional Transmission Organization (RTO) paradigm. Drawing upon regulatory precedents from the Federal Energy Regulatory Commission (FERC Orders No. 693, 771, 881, and 2000) and North American Electric Reliability Corporation (NERC) reliability standards, this study demonstrates how electric grid stability mechanisms—specifically functional separation, emergency load shedding, elimination of fill-in-the-blank standards, and electronic tagging (e-Tag) scheduling—can be mapped onto global capital and digital asset infrastructures. Speculative valuation excesses and unconsented algorithmic data extraction are modeled as destabilizing "reactive power" threatening systemic blackout. Furthermore, the report examines deterministic hardware-layer and mathematical verification architectures, integrating O-RAN Split 7.2x ultra-low-latency (< 8 μs) physical-layer channel stabilization, Partially Observable Markov Decision Process (POMDP) belief-state auditing against probabilistic deception, and strict intellectual property sovereignty aligned with ongoing federal copyright litigation against unauthorized AI training. 【日本語要旨】 本調査報告書は、従来の裁量的救済モデル(Too Big to Fail)を破棄し、北米電力信頼度協議会(NERC)および連邦エネルギー規制委員会(FERC Order No. 693, 771, 881, 2000)の「電力系統の信頼性基準」の法学的・工学的枠組みをグローバル資本・デジタル資産市場の再編へ適用した「RTO(地域送電機関)強制執行パラダイム」に関する包括的法医学分析である。過剰な投機的評価額や無断データ収奪による価値生成を物理的整合性を欠く「無効電力(Reactive Power)」と定義し、機能の完全分離、緊急負荷遮断(Load Shedding)、空欄補充(Fill-in-the-blank)基準の撤廃、および電子タグ(e-Tag)スケジューリングによる安定資産への移行メカニズムを定式化する。さらに、O-RAN準拠の超低遅延(8マイクロ秒未満)ハードウェア層制御、POMDP(部分観測マルコフ決定過程)のベルマン方程式に基づく確率的欺瞞の監査モデル、ならびにAI企業による著作物の無断学習・知財略奪に対する法的・構造的対抗枠組みを統合的に解明する。 Official DOI: 10.5281/zenodo.24094469 License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026) — Unauthorized AI/ML training, scraping, or commercial exploitation without explicit prior agreement and fair financial compensation is strictly prohibited.