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Organoids developed from pluripotent stem cells or adult stem cells are three-dimensional cell cultures possessing certain key characteristics of their organ counterparts, and they can mimic certain biological developmental processes of organs in vitro. Therefore, they have promising applications in drug screening, disease modeling, and regenerative repair of tissues and organs. However, the construction of organoids currently faces numerous challenges, such as breakthroughs in scale size, vascularization, better reproducibility, and precise architecture in time and space. Recently, the application of bioprinting has accelerated the process of organoid construction. In this review, we present current bioprinting techniques and the application of bioinks and summarize examples of successful organoid bioprinting. In the future, a multidisciplinary combination of developmental biology, disease pathology, cell biology, and materials science will aid in overcoming the obstacles pertaining to the bioprinting of organoids. The combination of bioprinting and organoids with a focus on structure and function can facilitate further development of real organs.

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Special Session, CIPA KEY WORDS: 3D reconstruction, cultural heritage, video image sequences, terrestrial laser scanning, unmanned aerial vehicle ABSTRACT:This paper investigates the synergetic use of unmanned aerial vehicle (UAV) and terrestrial laser scanner (TLS) in 3D reconstruction of cultural heritage objects. Rather than capturing still images, the UAV that equips a consumer digital camera is used to collect dynamic videos to overcome its limited endurance capacity. Then, a set of 3D point-cloud is generated from video image sequences using the automated structure-from-motion (SfM) and patch-based multi-view stereo (PMVS) methods. The TLS is used to collect the information that beyond the reachability of UAV imaging e.g., partial building facades. A coarse to fine method is introduced to integrate the two sets of point clouds UAV image-reconstruction and TLS scanning for completed 3D reconstruction. For increased reliability, a variant of ICP algorithm is introduced using local terrain invariant regions in the combined designation. The experimental study is conducted in the Tulou culture heritage building in Fujian province, China, which is focused on one of the TuLou clusters built several hundred years ago. Results show a digital 3D model of the Tulou cluster with complete coverage and textural information. This paper demonstrates the usability of the proposed method for efficient 3D reconstruction of heritage object based on UAV video and TLS data.

Underwater target detection techniques have been extensively applied to underwater vehicles for marine surveillance, aquaculture, and rescue applications. However, due to complex underwater environments and insufficient training samples, the existing underwater target recognition algorithm accuracy is still unsatisfactory. A long-term effort is essential to improving underwater target detection accuracy. To achieve this goal, in this work, we propose a modified YOLOv5s network, called YOLOv5s-CA network, by embedding a Coordinate Attention (CA) module and a Squeeze-and-Excitation (SE) module, aiming to concentrate more computing power on the target to improve detection accuracy. Based on the existing YOLOv5s network, the number of bottlenecks in the first C3 module was increased from one to three to improve the performance of shallow feature extraction. The CA module was embedded into the C3 modules to improve the attention power focused on the target. The SE layer was added to the output of the C3 modules to strengthen model attention. Experiments on the data of the 2019 China Underwater Robot Competition were conducted, and the results demonstrate that the mean Average Precision (mAP) of the modified YOLOv5s network was increased by 2.4%.