A Lite Distributed Semantic Communication System for Internet of Things

The rapid development of deep learning (DL) and widespread applications of Internet-of-Things (IoT) have made the devices smarter than before, and enabled them to perform more intelligent tasks. However, it is challenging for any IoT device to train and run DL models independently due to its limited computing capability. In this paper, we consider an IoT network where the cloud/edge platform performs the DL based semantic communication (DeepSC) model training and updating while IoT devices perform data collection and transmission based on the trained model. To make it affordable for IoT devices, we propose a lite distributed semantic communication system based on DL, named L-DeepSC, for text transmission with low complexity, where the data transmission from the IoT devices to the cloud/edge works at the semantic level to improve transmission efficiency. Particularly, by pruning the model redundancy and lowering the weight resolution, the L-DeepSC becomes affordable for IoT devices and the bandwidth required for model weight transmission between IoT devices and the cloud/edge is reduced significantly. Through analyzing the effects of fading channels in forward-propagation and back-propagation during the training of L-DeepSC, we develop a channel state information (CSI) aided training processing to decrease the effects of fading channels on transmission. Meanwhile, we tailor the semantic constellation to make it implementable on capacity-limited IoT devices. Simulation demonstrates that the proposed L-DeepSC achieves competitive performance compared with traditional methods, especially in the low signal-to-noise (SNR) region. In particular, while it can reach as large as 40x compression ratio without performance degradation.Comment: Accpeted by JSA

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

Transcriptional Activation of OsDERF1 in OsERF3 and OsAP2-39 Negatively Modulates Ethylene Synthesis and Drought Tolerance in Rice

The phytohormone ethylene is a key signaling molecule that regulates a variety of developmental processes and stress responses in plants. Transcriptional modulation is a pivotal process controlling ethylene synthesis, which further triggers the expression of stress-related genes and plant adaptation to stresses; however, it is unclear how this process is transcriptionally modulated in rice. In the present research, we report the transcriptional regulation of a novel rice ethylene response factor (ERF) in ethylene synthesis and drought tolerance. Through analysis of transcriptional data, one of the drought-responsive ERF genes, OsDERF1, was identified for its activation in response to drought, ethylene and abscisic acid. Transgenic plants overexpressing OsDERF1 (OE) led to reduced tolerance to drought stress in rice at seedling stage, while knockdown of OsDERF1 (RI) expression conferred enhanced tolerance at seedling and tillering stages. This regulation was supported by negative modulation in osmotic adjustment response. To elucidate the molecular basis of drought tolerance, we identified the target genes of OsDERF1 using the Affymetrix GeneChip, including the activation of cluster stress-related negative regulators such as ERF repressors. Biochemical and molecular approaches showed that OsDERF1 at least directly interacted with the GCC box in the promoters of ERF repressors OsERF3 and OsAP2-39. Further investigations showed that OE seedlings had reduced expression (while RI lines showed enhanced expression) of ethylene synthesis genes, thereby resulting in changes in ethylene production. Moreover, overexpression of OsERF3/OsAP2-39 suppressed ethylene synthesis. In addition, application of ACC recovered the drought-sensitive phenotype in the lines overexpressing OsERF3, showing that ethylene production contributed to drought response in rice. Thus our data reveal that a novel ERF transcriptional cascade modulates drought response through controlling the ethylene synthesis, deepening our understanding of the regulation of ERF proteins in ethylene related drought response

A data-assimilative ocean forecasting system for the Prince William sound and an evaluation of its performance during sound Predictions 2009

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