Identification of Underground Artificial Cavities Based on the Bayesian Convolutional Neural Network.

The development of underground artificial cavities plays an important role in the exploitation of urban spatial resources. As the rapidly growing number of underground artificial cavities with different depths and scales increases, the detection and identification of underground artificial cavities has become a key issue in underground engineering studies. Geophysical techniques have been widely used for the construction, management, and maintenance of underground artificial cavities. In this study, we present two identification methods for underground artificial cavities. Apparent resistivity imaging is the most popular technique for quickly identifying underground artificial cavities, using the forward simulation results of a three-dimensional earth model and comparing these with the preset positions of artificial cavities, as demonstrated in the experiment. To further improve the efficiency of underground artificial cavity identification, we developed a fast recognition approach for underground artificial cavities based on the Bayesian convolutional neural network (BCNN). Compared to a traditional convolutional neural network, the performance of the BCNN method was greatly improved in terms of the classification accuracy and efficiency of identifying underground artificial cavities with apparent resistivity image datasets.

The effects of dextran in residual impurity on trehalose crystallization and formula in food preservation.

The residual dextran impurities in the upstream process significantly impact the crystallization of starch-based functional sugar and the related food properties. This study intends to reveal the mechanism of dextran's influence on trehalose crystallization, and build a relationship among the dextran in syrup and the physicochemical and functional properties of trehalose. Instead of incorporating into the crystal lattice, dextran changes the assembly rate of trehalose molecules on crystal surface. The different sensitivity and adsorption capacity of the crystal surface to the chain length of dextran determines the growth rate of crystal surfaces, resulting in different crystal morphology. The bulk trehalose crystals, which were obtained from syrups with short chain dextran, have excellent powder properties, including best flowability (35◦), highest crystal strength (2.7 N), lowest caking rate (62.22 %), and the most uniform mixing with other sweeteners (sucrose/xylitol) in food formulations, achieving more stable starch preservation.

[On the academic value of Wutingzisujiebashiyinanjing (Wutingzi's Vernacular Explanation of Nanjing).].

Nanjing, one of the four ancient classics of TCM, was followed by later students of TCM, XIONG Zong-li, a famous doctor and publisher in the Ming Dynasty, compiled Wutingzisujiebashiyinanjing (Wutingzi's Vernacular Explanation of Nanjing) which combined visual and legible graphic interpretation with vernacular language to explain, or quoted the classics, combined with his own opinions. This book popularly and vividly displayed the substance of Nanjing to the descendants and made a great contribution to the popularization and propagation of TCM classics. It is a valuable reference book both to students and researchers of Nanjing.