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The long-term effects of administrative division adjustments on economic development in Dalian City, China, is presently unclear. Therefore, we employed a geographically and temporally weighted regression model to construct an index assessment system using the annual number of newly registered enterprises as the dependent variable. We empirically studied the effects of administrative division adjustments of townships in Dalian City from 2010 to 2020. The results showed that: (i) adjustments in townships administrative divisions negatively affected regional enterprise concentrations and economic development in general, whereas industrial and transportation factors demonstrated positive effects to variable degrees, and the effects of policy, location, and population factors were not significant. (ii) Over time, the effects of townships administrative division adjustments changed from positive to negative, and the negative effects displayed an increasing trend, revealing that (iii) the effect of administrative division adjustments in Dalian City was positive and negative over time. This further reveals the objective problem that administrative division adjustment in recent years was effective over the short term, but not over the long term. (iv) During the study period, administrative division adjustments positively affected regional enterprise concentrations and economic development solely during a short time frame and in a small geographical area. However, its negative effects increased extensively, which infers that maintaining a relatively stable administrative division is more beneficial for promoting economic development in Dalian City.

Quantitative analysis through image processing is a key step to gain information regarding the microstructure of materials. In this paper, we develop a deep learning-based method to address the task of image segmentation for microscopic images using an Al–La alloy. Our work makes three key contributions. (1) We train a deep convolutional neural network based on DeepLab to achieve image segmentation and have significant results. (2) We adopt a local processing method based on symmetric overlap-tile strategy which makes it possible to analyze the microscopic images with high resolution. Additionally, it achieves seamless segmentation. (3) We apply symmetric rectification to enhance the accuracy of results with 3D information. Experimental results showed that our method outperforms existing segmentation methods.