No abstract

Lung‐on‐a‐chip models hold great promise for disease modeling and drug screening. Herein, inspired by the iridescence phenomenon of soap bubbles, a novel biomimetic 3D microphysiological lung‐on‐a‐chip system with breathing visualization is presented. The system, with an array of pulmonary alveoli at the physiological scale, is constructed and coated with structural color materials. Cyclic deformation is induced by regular airflow, resembling the expansion and contraction of the alveoli during rhythmic breathing. As the deformation is accompanied with corresponding synchronous shifts in the structural color, the constructed system offers self‐reporting of the cell mechanics and enables real‐time monitoring of the cultivation process. Using this system, the dynamic relationships between the color atlas and disease symptoms, showing the essential role of mechanical stretching in the phenotypes of idiopathic pulmonary fibrosis, are investigated. These features make this human lung system ideal in biological study, disease monitoring, and drug discovery.

Information extraction and three-dimensional (3D) reconstruction of buildings using the vehicle-borne laser scanning (VLS) system is significant for many applications. Extracting LiDAR points, from VLS, belonging to various types of building in large-scale complex urban environments still retains some problems. In this paper, a new technical framework for automatic and efficient building point extraction is proposed, including three main steps: (1) voxel group-based shape recognition; (2) category-oriented merging; and (3) building point identification by horizontal hollow ratio analysis. This article proposes a concept of "voxel group" based on the voxelization of VLS points: each voxel group is composed of several voxels that belong to one single real-world object. Then the shapes of point clouds in each voxel group are recognized and this shape information is utilized to merge voxel group. This article puts forward a characteristic nature of vehicle-borne LiDAR building points, called "horizontal hollow ratio", for efficient extraction. Experiments are analyzed from two aspects: (1) building-based evaluation for overall experimental area; and (2) point-based evaluation for individual building using the completeness and correctness. The experimental results indicate that the proposed framework is effective for the extraction of LiDAR points belonging to various types of buildings in large-scale complex urban environments.

Exploring the green transition of cultivated land use from the perspective of green utilization efficiency evaluation has become an important content of deepening the study of cultivated land use transition, which is of great significance to promote food security and ecological civilization construction. At present, there are few studies on the green utilization efficiency of cultivated land (GUECL), which covers the comprehensive benefits of economy, ecology and society, combined with the requirements of ecological civilization and green development. Taking 65 cities (regions and autonomous prefectures) of the Yellow River Basin as the basic evaluation unit, the GUECL of the Yellow River Basin is evaluated with a Super-SBM model. In general, the GUECL of the Yellow River Basin was not high at four time points of 2000, 2006, 2012 and 2018, which presents a trend of “rising first and then falling”. Analyzing its temporal and spatial evolution pattern, the GUECL in the upper, middle and lower reaches presented an order of the upper reaches area > the lower reaches area > the middle reaches area; and the spatial variation trend showed a decrease from west to east, and a U-shaped change in the south-north direction. Using spatial correlation analysis, except for the year 2000, the GUECL in the Yellow River Basin presents a general distribution characteristic of spatial agglomeration, which is positively correlated in 2006, 2012 and 2018. The change of spatio-temporal pattern is the result of internal and external factors. The former mainly displays in the main characteristics of farmers, family characteristics and farmers’ cognition, while the latter is reflected in natural, social and policy factors.