STEM Image Analysis Based on Deep Learning: Identification of Vacancy Defects and Polymorphs of MoS2.

Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The conventional analysis of STEM images is an extensive hands-on process, which limits efficient handling of high-throughput data. Here, we apply a fully convolutional network (FCN) for identification of important structural features of two-dimensional crystals. ResUNet, a type of FCN, is utilized in identifying sulfur vacancies and polymorph types of MoS2 from atomic resolution STEM images. Efficient models are achieved based on training with simulated images in the presence of different levels of noise, aberrations, and carbon contamination. The accuracy of the FCN models toward extensive experimental STEM images is comparable to that of careful hands-on analysis. Our work provides a guideline on best practices to train a deep learning model for STEM image analysis and demonstrates FCN's application for efficient processing of a large volume of STEM data.

The case for moderate-risk buyers: An empirical investigation.

Despite recent increase in research on compulsive buying and excessive buying, the category of buyers whose buying patterns are approaching the clinical level but still somewhat below it has rarely been recognized in the literature. In this paper, we propose the case for the category of moderate-risk buyers. Following Ridgway et al.'s (2008) findings, moderate-risk buyers were operationalized as scoring 21-24 on Compulsive Buying Index. We hypothesized that moderate-risk buyers would hold significantly higher materialistic values than non-compulsive buyers, while exhibiting significantly less depressive symptoms and covert narcissism than full-fledged compulsive buyers. An online survey of individuals who frequently engaged in buying lapses was used (N=809). We found that moderate-risk buyers were significantly different from both compulsive buyers and non-compulsive buyers in the frequency of buying lapses, hiding purchases and frequency of experiencing negative feelings leading to buying lapses. Furthermore, consistent with our hypothesis, moderate-risk buyers held significantly lower covert narcissism and depression than full-fledged compulsive buyers, but their materialism was not significantly different from each other. Our findings support the case for moderate-risk buyers as a separate group from full-fledged compulsive buyers.