A Marker-Controlled Watershed Algorithm for the Intelligent Picking of Long Jujubes in Trees

Vision is the most important way for an unmanned picking or plant protection robot to navigate an external environment. To achieve intelligent picking or plant protection, it is essential to obtain target location information. A new marker-controlled watershed (MCW-D) algorithm is proposed for object segmentation. By analyzing the shortcomings of the watershed algorithm and the characteristics of objects, the proposed MCW-D method mainly solves three problems. First, it reduces the influence of shadow and other factors on image color information. Based on histogram specification, secondary mapping is used to reduce the effects of lighting. Second, marker images are selected. All points with markers need to be located in the target object. The hue feature of long jujubes and trees is used as the marker image. Third, a mask image is acquired, which requires a clear boundary between the target and the background. An adaptive angle rotation based on an energy-driven approach is designed to find large differences between the target and the background. In a natural environment, the proposed MCW-D method respectively achieves segmentation accuracies of 94.7% and 93.2% on a jujube dataset and a tree dataset, which exceed the accuracies of widely used machine learning methods. These results promote the development of the forest and fruit economies

Beyond canonical PROTAC: biological targeted protein degradation (bioTPD)

Abstract Targeted protein degradation (TPD) is an emerging therapeutic strategy with the potential to modulate disease-associated proteins that have previously been considered undruggable, by employing the host destruction machinery. The exploration and discovery of cellular degradation pathways, including but not limited to proteasomes and lysosome pathways as well as their degraders, is an area of active research. Since the concept of proteolysis-targeting chimeras (PROTACs) was introduced in 2001, the paradigm of TPD has been greatly expanded and moved from academia to industry for clinical translation, with small-molecule TPD being particularly represented. As an indispensable part of TPD, biological TPD (bioTPD) technologies including peptide-, fusion protein-, antibody-, nucleic acid-based bioTPD and others have also emerged and undergone significant advancement in recent years, demonstrating unique and promising activities beyond those of conventional small-molecule TPD. In this review, we provide an overview of recent advances in bioTPD technologies, summarize their compositional features and potential applications, and briefly discuss their drawbacks. Moreover, we present some strategies to improve the delivery efficacy of bioTPD, addressing their challenges in further clinical development