Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

Probable Evidence of Fecal Aerosol Transmission of SARS-CoV-2 in a High-Rise Building.

Abstract: BACKGROUND: The role of fecal aerosols in the transmission of severe acute respiratory syndrome coronavirus 2 has been suspected. OBJECTIVE: To investigate the temporal and spatial distributions of 3 infected families in a high-rise apartment building and examine the associated environment variables to verify the role of fecal aerosols. DESIGN: Epidemiologic survey and quantitative reverse transcriptase polymerase chain reaction analyses on throat swabs from the participants; 237 surface and air samples from 11 of the 83 flats in the building, public areas, and building drainage systems; and tracer gas released into bathrooms as a surrogate for virus-laden aerosols in the drainage system. SETTING: A high-rise apartment building in Guangzhou, China. PARTICIPANTS: 9 infected patients, 193 other residents of the building, and 24 members of the building's management staff. MEASUREMENTS: Locations of infected flats and positive environmental samples, and spread of virus-laden aerosols. RESULTS: 9 infected patients in 3 families were identified. The first family had a history of travel to the coronavirus disease 2019 (COVID-19) epicenter Wuhan, whereas the other 2 families had no travel history and a later onset of symptoms. No evidence was found for transmission via the elevator or elsewhere. The families lived in 3 vertically aligned flats connected by drainage pipes in the master bathrooms. Both the observed infections and the locations of positive environmental samples are consistent with the vertical spread of virus-laden aerosols via these stacks and vents. LIMITATION: Inability to determine whether the water seals were dried out in the flats of the infected families. CONCLUSION: On the basis of circumstantial evidence, fecal aerosol transmission may have caused the community outbreak of COVID-19 in this high-rise building. PRIMARY FUNDING SOURCE: Key-Area Research and Development Program of Guangdong Province and the Research Grants Council of Hong Kong.

ComNet: Combination of Deep Learning and Expert Knowledge in OFDM Receivers

Abstract: In this letter, we propose a model-driven deep learning (DL) approach that combines DL with the expert knowledge to replace the existing orthogonal frequency-division multiplexing receiver in wireless communications. Different from the data-driven fully connected deep neural network (FC-DNN) method, we adopt the block-by-block signal processing method that divides the receiver into channel estimation subnet and signal detection subnet. Each subnet is constructed by a DNN and uses the existing simple and traditional solution as initialization. The proposed model-driven DL receiver offers more accurate channel estimation comparing with the linear minimum mean-squared error method and exhibits higher data recovery accuracy comparing with the existing methods and FC-DNN. Simulation results further demonstrate the robustness of the proposed approach in terms of signal-to-noise ratio and its superiority to the FC-DNN approach in the computational complexities or the memory usage.