Fluctuation theorems are a class of equalities each of which links a thermodynamic path functional such as heat and work to a state function such as entropy and free energy. Jinwoo and Tanaka [L. Jinwoo and H. Tanaka, Sci. Rep. 5, 7832 (2015)] have shown that each microstate of a fluctuating system can be regarded as an ensemble (or a 'macrostate') if we consider trajectories that reach each microstate. They have revealed that local forms of entropy and free energy are true thermodynamic potentials of each microstate, encoding heat, and work, respectively, within an ensemble of paths that reach each state. Here we show that information that is characterized by the local form of mutual information between two subsystems in a heat bath is also a true thermodynamic potential of each coupled state and encodes the entropy production of the subsystems and heat bath during a coupling process. To this end, we extend the fluctuation theorem of information exchange [T. Sagawa and M. Ueda, Phys. Rev. Lett. 109, 180602 (2012)] by showing that the fluctuation theorem holds even within an ensemble of paths that reach a coupled state during dynamic co-evolution of two subsystems.

The rapid growth of the aviation industry has progressively heightened the importance of airport maintenance management. There is an increasing need for a comprehensive system that considers the diverse requirements of various stakeholders. Existing research has primarily focused on the technological advancements of optimization models, with limited applicability in practice. In this study, we introduce the Condition Cases Optimization (CCO) to address these limitations while incorporating multi-facility and multi-year network optimization models. We developed condition index, Serviceability Level, integrated assessment indices and performance models for decision-making criteria. We categorize conditions into three classes and propose a practical decision-making strategy that can flexibly adapt to budget constraints. Sensitivity analysis highlights the impact of initial budget, maintenance methods, costs, and thresholds on decision outcomes. Through a case study we validate the effectiveness and practicality of the CCO method as an efficient decision-making tool.