A Study on the Right to Use Rural Homestead: Taking Changchun City and the Surrounding Area as the Example

Based on the analysis and comparison of the data collected from a field survey on the status quo of the right to use rural homestead in Changchun City and the surrounding area, this paper not only reflects on the history and theory of the right to use rural homestead in China, but also proposes solutions and suggestions in accordance with the reality towards the development of rural areas in China

Deep Learning for 1-Bit Compressed Sensing-based Superimposed CSI Feedback

In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state information (CSI) feedback has shown many advantages, while still faces many challenges, such as low accuracy of the downlink CSI recovery and large processing delays. To overcome these drawbacks, this paper proposes a deep learning (DL) scheme to improve the 1-bit compressed sensing-based superimposed CSI feedback. On the user side, the downlink CSI is compressed with the 1-bit CS technique, superimposed on the uplink user data sequences (UL-US), and then sent back to the base station (BS). At the BS, based on the model-driven approach and assisted by the superimposition-interference cancellation technology, a multi-task detection network is first constructed for detecting both the UL-US and downlink CSI. In particular, this detection network is jointly trained to detect the UL-US and downlink CSI simultaneously, capturing a globally optimized network parameter. Then, with the recovered bits for the downlink CSI, a lightweight reconstruction scheme, which consists of an initial feature extraction of the downlink CSI with the simplified traditional method and a single hidden layer network, is utilized to reconstruct the downlink CSI with low processing delay. Compared with the 1-bit CS-based superimposed CSI feedback scheme, the proposed scheme improves the recovery accuracy of the UL-US and downlink CSI with lower processing delay and possesses robustness against parameter variations.Comment: 12 pages, 11 figure

Overexpression of Brg1 Alleviates Hepatic Ischemia/Reperfusion-Induced Acute Lung Injury through Antioxidative Stress Effects

Aim. To investigate whether overexpression of Brahma-related gene-1 (Brg1) can alleviate lung injury induced by hepatic ischemia/reperfusion (HIR) and its precise mechanism. Methods. Cytomegalovirus-transgenic Brg1-overexpressing (CMV-Brg1) mice and wild-type (WT) C57BL/6 mice underwent HIR. Lung histology, oxidative injury markers, and antioxidant enzyme concentrations in the lung were assessed. The protein expression levels of Brg1, nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NAD(P)H:quinone oxidoreductase 1 (NQO1) in the lung were analyzed by Western blotting. Results. In the WT group, histopathological analysis revealed that lung damage peaked at 6 h after HIR. Meanwhile, the lung reactive oxygen species (ROS) and 8-isoprostane levels were significantly increased. The protein expression of Brg1 in lung tissue decreased to a minimum at 6 h. Overexpression of Brg1 alleviated lung injury and decreased the amounts of oxidative products, including the levels of 8-isoprostane and ROS, as well as the percentage of positive cells for 4-hydroxynonenal (4-HNE) and 8-oxo-2′-deoxyguanosine (8-OHdG). Brg1 overexpression increased the expression and nuclear translocation of Nrf2 as well as activated the antioxidases. In addition, it decreased the expression of inflammatory factors. Conclusion. Overexpression of Brg1 alleviates oxidative lung injury induced by HIR, likely through the Nrf2 pathway