https://www.selleckchem.com/products/ldk378.html Finally, we highlight the theoretical models, such as error-based learning and Protection Motivation Theory, that oriented the game design, and can be reused to create SGs for other domains.Learning discriminative shape representation directly on point clouds is still challenging in 3D shape analysis and understanding. Recent studies usually involve three steps first splitting a point cloud into some local regions, then extracting the corresponding feature of each local region, and finally aggregating all individual local region features into a global feature as shape representation using simple max-pooling. However, such pooling-based feature aggregation methods do not adequately take the spatial relationships (e.g. the relative locations to other regions) between local regions into account, which greatly limits the ability to learn discriminative shape representation. To address this issue, we propose a novel deep learning network, named Point2SpatialCapsule, for aggregating features and spatial relationships of local regions on point clouds, which aims to learn more discriminative shape representation. Compared with the traditional max-pooling based feature aggregation networks, Point2SpatialpatialCapsule outperforms the state-of-the-art methods in the 3D shape classification, retrieval and segmentation tasks under the well-known ModelNet and ShapeNet datasets.Real-time 3-D intracardiac echocardiography (ICE) can enable faster imaging of surfaces orthogonal to the transducer, such as the pulmonary vein (PV) antra and cardiac valve annuli. However, the requirement for a 2-D grid of individually wired elements makes a traditional matrix array challenging to implement within an intravenous catheter. Helicoid array transducers are linear array transducers twisted about their long axis, allowing imaging of different elevation slices using sub-apertures. In this work, we examined the 3-D imaging characteristics of helico