• Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter

    1 month ago - By Springer

    Abstract
    Individual thermal comfort models based on physiological parameters could improve the efficiency of the personal thermal comfort control system. However, the effect of thermal history has not been fully addressed in these models. In this study, climate chamber experiments were conducted in winter using 32 subjects who have different indoor and outdoor thermal histories. Two kinds of thermal conditions were investigated: the temperature dropping and severe cold conditions. A simplified method using historical air temperature to quantify the thermal history was proposed and used to...
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  • Assessment of Protein Model Structure Accuracy Estimation in CASP14: Old and New Challenges

    1 month ago - By Wiley

    Abstract
    In CASP, blind testing of model accuracy estimation methods has been conducted on models submitted by tertiary structure prediction servers. In CASP14, model accuracy estimation results were evaluated in terms of both global and local structure accuracy, as in the previous CASPs. Unlike the previous CASPs that did not show pronounced improvements in performance, the best single-model method showed an improved performance in CASP14, particularly in evaluating global structure accuracy when compared to both the best single-model methods in previous CASPs and the best multi-model...
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  • Protein oligomer modeling guided by predicted inter‐chain contacts in CASP14

    1 month ago - By Wiley

    Abstract
    For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted inter-chain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed...
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