TLMM v4.6: Resilience-Aware Structural Dynamics, Real-Time Adaptive Risk Mapping, and Continual Digital Twin Co-Evolution

This repository contains the technical report, publication-ready figures, README documentation, and a simplified conceptual Python demonstration script for: “TLMM v4.6: Resilience-Aware Structural Dynamics, Real-Time Adaptive Risk Mapping, and Continual Digital Twin Co-Evolution” TLMM (Threshold-Limited Mode Modulation) v4.6 is an exploratory computational framework for modeling nonstationary structural dynamics, resilience-aware adaptive risk mapping, and continually updated digital twin architectures. The framework integrates: • Time-evolving potential landscapes V(E,t)• Fokker–Planck-inspired structural dynamics• Resilience metric validation• Leave-one-subject-out cross-validation (simulation)• Comparative baseline model evaluation• Real-time streaming inference demonstrations• Predictive versus reactive control comparison• Inter-subject variability and parameter reliability• Adaptive forgetting and continual co-evolution• Hierarchical resilience and cross-scale coupling Key conceptual contributions of v4.6 include:• Resilience-aware adaptive inference• Continual digital twin updating• Adaptive forgetting under nonstationary dynamics• Cross-scale resilience modeling• Streaming state estimation and control timing• Environment-aware adaptation Repository contents:• Full technical report PDF• Publication-ready figures (Fig.1–Fig.10)• README documentation• Simplified conceptual Python demo script Important scope notice:All quantitative results are simulation-derived unless explicitly stated otherwise.No real EEG recordings, clinical cohorts, patient datasets, or empirical biomedical data were used. This work is intended for:• exploratory computational modeling• methodological development• digital twin architecture research• resilience-aware systems modeling• hypothesis generation No diagnostic, therapeutic, clinical decision-making, medical-device, or regulatory claims are made. Exploratory computational framework for resilience-aware adaptive inference, continual digital twin co-evolution, and nonstationary structural dynamics. Author:Koji OkinoIndependent ResearcherMay 2026