There are various kinds of carnivorous plants in nature, and most of them excrete acidic digestive fluids which contain digestive enzymes, especially acidic proteinases, to digest trapped insects and other prey for nutrition. Previous inhibitor studies indicated that the acid proteinase nepenthesin from Nepenthes belongs to the aspartic proteinase family. Recently, we purified two nepenthesins from the digestive fluid of N. distillatoria, investigated their molecular and enzymatic properties, and elucidated their primary structures by cDNA cloning of nepenthesins from N. gracilis.

This study focusses on computer vision to be applied to fractography. Automatic image segmentation by Hough transform and average brightness in region of interest was performed to find an origin of brittle fracture in martensitic steels. In addition, it is emphasized that morphology of microstructure or fracture surface should be quantified as much as possible to extract its features.

Finding the fracture initiation sites is critical for understanding the fracture mechanism and thus improving the products' quality, whereas some hard-to-detected features are easily missed in the human-effortbased characterizations with human eye and involve lots of labor force. In this study, computer-aided detection of fracture initiation sites is proposed to augment human expertise to efficiently find the fracture initiation sites, and thus to reduce the labor cost. With a deep-learning you only look once object detector, the fracture initiation sites of steel were successfully detected in this study. Furthermore, based on the trained detection model, an easy-to-use application for detecting initiation sites has been further developed, exhibiting great potential for high-efficiency detection of fracture initiation sites.