Identification, sorting, and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes. In this work, based on an artificial intelligence (AI)-assisted object detection model for cell phenotype screening and a cross-interface contact method for single-cell exporting, we developed an automatic and index-based system called EasySort AUTO, where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed, "One-Cell-One-Tube" manner. The target cell is automatically identified based on an AI-assisted object detection model and then mobilized via an optical tweezer for sorting. Then, a crossinterface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube, which leads to coupling with subsequent single-cell culture or sequencing. The efficiency of the system for single-cell printing is >93%. The throughput of the system for single-cell printing is ~120 cells/h. Moreover, >80% of single cells of both yeast and Escherichia coli are culturable, suggesting the superior preservation of cell viability during sorting. Finally, AI-assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples, which was validated by downstream single-cell proliferation assays. The automation, index maintenance, and vitality preservation of EasySort AUTO suggest its excellent application potential for single-cell sorting.

As one of the largest energy consumers in the world, China’s total electricity consumption has increased by 416.33% during the sample years of 2001 to 2019. In 2019, the top five provinces in terms of power use were all located on the eastern coast. They have contributed 38.39% of the total consumption, causing a power shortage of 594.5 billion kWh in the provinces, while the power generation in the central and western regions have far exceeded their electricity consumption. In order to alleviate the problem of the mismatch between the power resource centers and the load centers in China, ultra-high voltage (UHV) projects, as one of the most important projects in recent years, have bridged the resource gap between the regions and have improved the allocation efficiency of the power resources. Although the cross-provincial transmission of electricity opens the pathway for the consumption of resources, the causal effects of the project on the regions along the line have not been accurately analyzed. Firstly, by constructing a quasi-natural experiment, this paper uses county-level panel data during the period of 2000 to 2019 to analyze the economic benefits that are generated by the inter-regional power transmission project. Secondly, the pathways of the economic effects of UHV are also verified. Finally, this paper also analyzes the heterogeneous effect of power-resource-rich provinces in the construction of the project. Through the pathways of local enterprise dynamics, employment level, and industrial structure, the findings prove that cross-regional power transmission has significantly enhanced the economic growth of the related regions and has played an especially positive role for the power exporting provinces. This paper provides empirical evidence for the effect of optimal resource allocation and the infrastructure development of developing countries and supplies a policy reference for developing countries’ resource allocation optimization strategies.