Learning-Based Biharmonic Augmentation for Point Cloud Classification

Point cloud datasets often suffer from inadequate sample sizes in comparison to image datasets, making data augmentation challenging. While traditional methods, like rigid transformations and scaling, have limited potential in increasing dataset diversity due to their constraints on altering individual sample shapes, we introduce the Biharmonic Augmentation (BA) method. BA is a novel and efficient data augmentation technique that diversifies point cloud data by imposing smooth non-rigid deformations on existing 3D structures. This approach calculates biharmonic coordinates for the deformation function and learns diverse deformation prototypes. Utilizing a CoefNet, our method predicts coefficients to amalgamate these prototypes, ensuring comprehensive deformation. Moreover, we present AdvTune, an advanced online augmentation system that integrates adversarial training. This system synergistically refines the CoefNet and the classification network, facilitating the automated creation of adaptive shape deformations contingent on the learner status. Comprehensive experimental analysis validates the superiority of Biharmonic Augmentation, showcasing notable performance improvements over prevailing point cloud augmentation techniques across varied network designs

LCReg: Long-Tailed Image Classification with Latent Categories based Recognition

In this work, we tackle the challenging problem of long-tailed image recognition. Previous long-tailed recognition approaches mainly focus on data augmentation or re-balancing strategies for the tail classes to give them more attention during model training. However, these methods are limited by the small number of training images for the tail classes, which results in poor feature representations. To address this issue, we propose the Latent Categories based long-tail Recognition (LCReg) method. Our hypothesis is that common latent features shared by head and tail classes can be used to improve feature representation. Specifically, we learn a set of class-agnostic latent features shared by both head and tail classes, and then use semantic data augmentation on the latent features to implicitly increase the diversity of the training sample. We conduct extensive experiments on five long-tailed image recognition datasets, and the results show that our proposed method significantly improves the baselines.Comment: accepted by Pattern Recognition. arXiv admin note: substantial text overlap with arXiv:2206.0101

Graph theoretical analysis of functional network for comprehension of sign language

This work was supported by grants from the National Natural Science Foundation of China (NSFC: 31571158, 31170969) and National Key Basic Research Program of China (2014CB846102), and a grant from the National Institutes of Health (R01 DC010997). We thank Yong He and Roel Willems for providing insightful comments to this study and Amie Fairs for proofreading the manuscript. No conflict of interest is declared.Peer reviewedPostprin

Intrinsic Cerebro-Cerebellar Functional Connectivity Reveals the Function of Cerebellum VI in Reading-Related Skills

Funding This work was supported by grants from the National Natural Science Foundation of China (NSFC: 31971036, 31971039, and 31571158).Peer reviewedPublisher PD

Modality- and task-specific brain regions involved in Chinese lexical processing

fMRI was used to examine lexical processing in native adult Chinese speakers. A 2 task (semantics and phonology) x 2 modality (visual and auditory) within-subject design was adopted. The semantic task involved a meaning association judgment and the phonological task involved a rhyming judgment to two sequentially presented words. The overall effect across tasks and modalities was used to identify seven ROIs, including the left fusiform gyrus (FG), the left superior temporal gyrus (STG), the left ventral inferior frontal gyrus (VIFG), the left middle temporal gyrus (MTG), the left dorsal inferior frontal gyrus (DIFG), the left inferior parietal lobule (IPL), and the left middle frontal gyrus (MFG). ROI analyses revealed two modality-specific areas, FG for visual and STG for auditory, and three task-specific areas, IPL and DIFG for phonology and VIFG for semantics. Greater DIFG activation was associated with conflicting tonal information between words for the auditory rhyming task, suggesting this region's role in strategic phonological processing, and greater VIFG activation was correlated with lower association between words for both the auditory and the visual meaning task, suggesting this region's role in retrieval and selection of semantic representations. The modality- and task-specific effects in Chinese revealed by this study are similar to those found in alphabetical languages. Unlike English, we found that MFG was both modality- and task-specific, suggesting that MFG may be responsible for the visuospatial analysis of Chinese characters and orthography-to-phonology integration at a syllabic level

IL-17A Synergizes with IFN-γ to Upregulate iNOS and NO Production and Inhibit Chlamydial Growth

IFN-γ-mediated inducible nitric oxide synthase (iNOS) expression is critical for controlling chlamydial infection through microbicidal nitric oxide (NO) production. Interleukin-17A (IL-17A), as a new proinflammatory cytokine, has been shown to play a protective role in host defense against Chlamydia muridarum (Cm) infection. To define the related mechanism, we investigated, in the present study, the effect of IL-17A on IFN-γ induced iNOS expression and NO production during Cm infection in vitro and in vivo. Our data showed that IL-17A significantly enhanced IFN-γ-induced iNOS expression and NO production and inhibited Cm growth in Cm-infected murine lung epithelial (TC-1) cells. The synergistic effect of IL-17A and IFN-γ on Chlamydia clearance from TC-1 cells correlated with iNOS induction. Since one of the main antimicrobial mechanisms of activated macrophages is the release of NO, we also examined the inhibitory effect of IL-17A and IFN-γ on Cm growth in peritoneal macrophages. IL-17A (10 ng/ml) synergizes with IFN-γ (200 U/ml) in macrophages to inhibit Cm growth. This effect was largely reversed by aminoguanidine (AG), an iNOS inhibitor. Finally, neutralization of IL-17A in Cm infected mice resulted in reduced iNOS expression in the lung and higher Cm growth. Taken together, the results indicate that IL-17A and IFN-γ play a synergistic role in inhibiting chlamydial lung infection, at least partially through enhancing iNOS expression and NO production in epithelial cells and macrophages