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Exploring the 'black box' of thermal adaptation using information entropy

机译：利用信息熵探索热适应的“黑匣子”

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摘要

Thermal adaptation has been well interpreted well by behavioral, physiological, and psychological factors, but the mechanism and interaction between the three factors remain in a "black box". This paper aims to apply the general system theory and information entropy to investigate the quantitative relationships of the three thermal adaptation processes. Based on the database from the field survey and laboratory experiments conducted in the hot summer and cold winter climate zone (HSCW) of China, three typical adaptive indices: clothing insulation (Clo), thermal sensation votes (TSV), and sensory nerve conduction velocity (SCV) were selected to calculate Clo entropy, TSV entropy, SCV entropy, and total entropy. The regression models were developed between these entropies and the indoor air temperature to quantify the weights of the three adaptive categories. The models were used to compare the differences between China and Pakistan as well as between adaptive approaches and climate chamber experiments. The comfort and acceptable temperature ranges for the HSCW zone were obtained using the entropy models. Our findings propose a new perspective using entropy to quantify the behaviorally, physiologically, and psychologically adaptive approaches, which contribute to a better understanding of opening the "black box" of thermal adaptation.
机译：行为，生理和心理因素已经很好地解释了热适应，但是这三个因素之间的机制和相互作用仍然存在于“黑匣子”中。本文旨在运用一般系统理论和信息熵研究三种热适应过程的定量关系。根据在中国炎热的夏季和寒冷的冬季气候区（HSCW）进行的实地调查和实验室实验获得的数据库，得出三个典型的适应性指标：衣物隔热（Clo），热感投票（TSV）和感觉神经传导速度选择（SCV）来计算Clo熵，TSV熵，SCV熵和总熵。在这些熵和室内空气温度之间建立了回归模型，以量化三个自适应类别的权重。这些模型用于比较中巴之间以及适应性方法和气候室试验之间的差异。使用熵模型获得了HSCW区的舒适度和可接受的温度范围。我们的发现提出了一个新的观点，即使用熵来量化行为，生理和心理适应方法，从而有助于更好地理解打开热适应的“黑匣子”。

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