Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental Comparisons

With the advancement of maritime unmanned aerial vehicles (UAVs) and deep learning technologies, the application of UAV-based object detection has become increasingly significant in the fields of maritime industry and ocean engineering. Endowed with intelligent sensing capabilities, the maritime UAVs enable effective and efficient maritime surveillance. To further promote the development of maritime UAV-based object detection, this paper provides a comprehensive review of challenges, relative methods, and UAV aerial datasets. Specifically, in this work, we first briefly summarize four challenges for object detection on maritime UAVs, i.e., object feature diversity, device limitation, maritime environment variability, and dataset scarcity. We then focus on computational methods to improve maritime UAV-based object detection performance in terms of scale-aware, small object detection, view-aware, rotated object detection, lightweight methods, and others. Next, we review the UAV aerial image/video datasets and propose a maritime UAV aerial dataset named MS2ship for ship detection. Furthermore, we conduct a series of experiments to present the performance evaluation and robustness analysis of object detection methods on maritime datasets. Eventually, we give the discussion and outlook on future works for maritime UAV-based object detection. The MS2ship dataset is available at \href{https://github.com/zcj234/MS2ship}{https://github.com/zcj234/MS2ship}.Comment: 32 pages, 18 figure

Design, Synthesis and Biological Activity Testing of Library of Sphk1 Inhibitors

Our team discovered a moderate SphK1 inhibitor, SAMS10 (IC50 = 9.8 μM), which was screened by computer-assisted screening. In this study, we developed a series of novel diaryl derivatives with improved antiproliferative activities by modifying the structure of the lead compound SAMS10. A total of 50 new compounds were synthesized. Among these compounds, the most potent compound, named CHJ04022Rb, has significant anticancer activity in melanoma A375 cell line (IC50 = 2.95 μM). Further underlying mechanism studies indicated that CHJ04022R exhibited inhibition effect against PI3K/NF-κB signaling pathways, inhibited the migration of A375 cells, promoted apoptosis and exerted antiproliferative effect by inducing G2/M phase arrest in A375 cells. Furthermore, acute toxicity experiment indicated CHJ04022R exhibited good safety in vivo. Additionally, it showed a dose-dependent inhibitory effect on the growth of xenograft tumor in nude mice. Therefore, CHJ04022R may be a potential candidate for the treatment of melanoma

The sequence and <i>de novo</i> assembly of the giant panda genome

Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes