Robust Semantic Communications with Masked VQ-VAE Enabled Codebook

Although semantic communications have exhibited satisfactory performance for a large number of tasks, the impact of semantic noise and the robustness of the systems have not been well investigated. Semantic noise refers to the misleading between the intended semantic symbols and received ones, thus cause the failure of tasks. In this paper, we first propose a framework for the robust end-to-end semantic communication systems to combat the semantic noise. In particular, we analyze sample-dependent and sample-independent semantic noise. To combat the semantic noise, the adversarial training with weight perturbation is developed to incorporate the samples with semantic noise in the training dataset. Then, we propose to mask a portion of the input, where the semantic noise appears frequently, and design the masked vector quantized-variational autoencoder (VQ-VAE) with the noise-related masking strategy. We use a discrete codebook shared by the transmitter and the receiver for encoded feature representation. To further improve the system robustness, we develop a feature importance module (FIM) to suppress the noise-related and task-unrelated features. Thus, the transmitter simply needs to transmit the indices of these important task-related features in the codebook. Simulation results show that the proposed method can be applied in many downstream tasks and significantly improve the robustness against semantic noise with remarkable reduction on the transmission overhead.Comment: 16 pages, 11 figures. arXiv admin note: text overlap with arXiv:2202.0333

A Unified Multi-Task Semantic Communication System for Multimodal Data

Task-oriented semantic communication has achieved significant performance gains. However, the model has to be updated once the task is changed or multiple models need to be stored for serving different tasks. To address this issue, we develop a unified deep learning enabled semantic communication system (U-DeepSC), where a unified end-to-end framework can serve many different tasks with multiple modalities. As the difficulty varies from different tasks, different numbers of neural network layers are required for various tasks. We develop a multi-exit architecture in U-DeepSC to provide early-exit results for relatively simple tasks. To reduce the transmission overhead, we design a unified codebook for feature representation for serving multiple tasks, in which only the indices of these task-specific features in the codebook are transmitted. Moreover, we propose a dimension-wise dynamic scheme that can adjust the number of transmitted indices for different tasks as the number of required features varies from task to task. Furthermore, our dynamic scheme can adaptively adjust the numbers of transmitted features under different channel conditions to optimize the transmission efficiency. According to simulation results, the proposed U-DeepSC achieves comparable performance to the task-oriented semantic communication system designed for a specific task but with significant reduction in both transmission overhead and model size

Pseudogenization of Mc1r gene associated with transcriptional changes related to melanogensis explains leucistic phenotypes in Oreonectes cavefish (Cypriniformes, Nemacheilidae)

Organisms that have colonized underground caves encounter vastly different selective pressures than their relatives in above‐ground habitats. While disruption of certain pigmentation genes has been documented in various cave‐dwelling taxa, little is known about wider impacts across pigmentation and other gene pathways. We here study the timeframe and transcriptional landscape of a leucistic and blind cypriniform fish (Oreonectes daqikongensis, Nemacheilidae) that inhabits karst caves in Guizhou, China. Based on data from the mitochondrial ND4, ND5, and Cytb genes, we show that the divergence between O. daqikongensis and its most closely related pigmented species occurred ca. 6.82 million years ago (95% HPD, 5.12–9.01), providing ample time for widespread phenotypic change. Indeed, we found that the DNA sequence of Mc1r (melanocortin‐1 receptor), a key gene regulating the biosynthesis of melanin in most vertebrates, is pseudogenized in O. daqikongensis, caused by a 29 bp deletion in the protein‐coding region. Furthermore, 99,305 unigenes were annotated based on the transcriptome of skin tissue of Oreonectes fish. Among the differentially expressed unigenes, 7,326 (7.4% of the total unigenes) had decreased expression and 2,530 (2.5% of the total unigenes) had increased expression in O. daqikongensis skin. As predicted, the expression of Mc1r and 18 additional genes associated with melanin biosynthesis was significantly downregulated in the skin tissue of O. daqikongensis, but not in its congener. Our results, integrating with other studies on cavefishes, suggest that loss of pigmentation was caused by coding region loss‐of‐function mutations along with widespread transcriptional changes, resulting from extended evolutionary time as a cave‐dwelling form

TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback

Learning large-scale pre-trained models on broad-ranging data and then transfer to a wide range of target tasks has become the de facto paradigm in many machine learning (ML) communities. Such big models are not only strong performers in practice but also offer a promising way to break out of the task-specific modeling restrictions, thereby enabling task-agnostic and unified ML systems. However, such a popular paradigm is mainly unexplored by the recommender systems (RS) community. A critical issue is that standard recommendation models are primarily built on categorical identity features. That is, the users and the interacted items are represented by their unique IDs, which are generally not shareable across different systems or platforms. To pursue the transferable recommendations, we propose studying pre-trained RS models in a novel scenario where a user's interaction feedback involves a mixture-of-modality (MoM) items, e.g., text and images. We then present TransRec, a very simple modification made on the popular ID-based RS framework. TransRec learns directly from the raw features of the MoM items in an end-to-end training manner and thus enables effective transfer learning under various scenarios without relying on overlapped users or items. We empirically study the transferring ability of TransRec across four different real-world recommendation settings. Besides, we look at its effects by scaling source and target data size. Our results suggest that learning neural recommendation models from MoM feedback provides a promising way to realize universal RS

The Effect of Zhongyong Thinking on Remote Association Thinking: An EEG Study

The Doctrine of the Mean (zhongyong) introduced by Confucianism is not only an aspect of faith, but also a way of thinking for Chinese individuals. Zhongyong includes two thinking forms: eclectic thinking (ET; i.e., “neither-A-nor-B”) and integrated thinking (IT; i.e., “both-A-and-B”). Given the inclination of Asian individuals toward situational cognition, this study used questions about situations familiar to Chinese undergraduates to activate either ET or IT. This was done to investigate the effects of the two divergent thinking forms of zhongyong on performance levels on the Remote Associates Test (RAT). Both behavioral and EEG results found that participants in the IT condition demonstrated higher RAT scores than those in the ET condition. The conclusion was that the RAT and priming tasks shared the same neural mechanism. This meant that the priming tasks of IT allowed participants to enter a state of creative preparation in advance, further affecting resolution of the RAT

Expression profiles of microRNAs in skeletal muscle of sheep by deep sequencing

Objective MicroRNAs are a class of endogenous small regulatory RNAs that regulate cell proliferation, differentiation and apoptosis. Recent studies on miRNAs are mainly focused on mice, human and pig. However, the studies on miRNAs in skeletal muscle of sheep are not comprehensive. Methods RNA-seq technology was used to perform genomic analysis of miRNAs in prenatal and postnatal skeletal muscle of sheep. Targeted genes were predicted using miRanda software and miRNA-mRNA interactions were verified by quantitative real-time polymerase chain reaction. To further investigate the function of miRNAs, candidate targeted genes were enriched for analysis using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. Results The results showed total of 1,086 known miRNAs and 40 new candidate miRNAs were detected in prenatal and postnatal skeletal muscle of sheep. In addition, 345 miRNAs (151 up-regulated, 94 down-regulated) were differentially expressed. Moreover, miRanda software was performed to predict targeted genes of miRNAs, resulting in a total of 2,833 predicted targets, especially miR-381 which targeted multiple muscle-related mRNAs. Furthermore, GO and KEGG pathway analysis confirmed that targeted genes of miRNAs were involved in development of skeletal muscles. Conclusion This study supplements the miRNA database of sheep, which provides valuable information for further study of the biological function of miRNAs in sheep skeletal muscle

Kinetics of Host Cell Recruitment During Dissemination of Diffuse Malignant Peritoneal Mesothelioma

Diffuse malignant mesothelioma is an aggressive tumor which displays a median survival of 11.2 months and a 5-year survival of less than 5% emphasizing the need for more effective treatments. This study uses an orthotopic model of malignant mesothelioma established in syngeneic, immunocompetent C57Bl/6 mice which produce malignant ascites and solid tumors that accurately replicate the histopathology of the human disease. Host stromal and immune cell accumulation within malignant ascites and solid tumors was determined using immunofluorescent labeling with confocal microscopy and fluorescence-activated cell sorting. An expression profile of cytokines and chemokines was produced using quantitative real-time PCR arrays. Tumor spheroids and solid tumors show progressive growth and infiltration with host stromal and immune cells including macrophages, endothelial cells, CD4+ and CD8+ lymphocytes, and a novel cell type, myeloid derived suppressor cells (MDSCs). The kinetics of host cell accumulation and inflammatory mediator expression within the tumor ascites divides tumor progression into two distinct phases. The first phase is characterized by progressive macrophage and T lymphocyte recruitment, with a cytokine profile consistent with regulatory T lymphocytes differentiation and suppression of T cell function. The second phase is characterized by decreased expression of macrophage chemotactic and T-cell regulating factors, an increase in MDSCs, and increased expression of several cytokines which stimulate differentiation of MDSCs. This cellular and expression profile suggests a mechanism by which host immune cells promote diffuse malignant mesothelioma progression

Highly Photoluminescent Carbon Dots Derived from Discarded Chewing Gum: toward Multiple Sensing of pH, Ferric Ion, and Adenosine Triphosphate

Highly Photoluminescent Carbon Dots Derived from Discarded Chewing Gum: toward Multiple Sensing of pH, Ferric Ion, and Adenosine Triphosphat

Hot-injection strategy for 1-min synthesis of carbon dots from oxygen-containing organic solvents: Toward fluorescence sensing of hemoglobin

Hot-injection strategy for 1-min synthesis of carbon dots from oxygen-containing organic solvents: Toward fluorescence sensing of hemoglobi