Millimeter-wave joint radar and communication system based on photonic frequency-multiplying constant envelope LFM-OFDM.

The joint radar and communication (JRC) system providing both large-capacity transmission and high-resolution ranging will play a pivotal role in the next-generation wireless networks (e.g., 6G and beyond) and defense applications. Here, we propose and experimentally demonstrate a novel photonics-assisted millimeter-wave (mm-wave) JRC system with a multi-Gbit/s data rate for communication function and centimeter-level range resolution for radar function. The key is the design of the intermediate-frequency (IF) JRC signal through the angle modulation of the linear frequency modulation (LFM) radar carrier using orthogonal frequency division multiplexing (OFDM) communication signal, inspired by the idea of constant-envelope OFDM (CE-OFDM). This IF angle-modulated waveform facilitates the broadband photonic frequency (phase)-multiplying scheme to generate mm-wave JRC signal with multiplied instantaneous bandwidth and phase modulation index for high-resolution LFM radar and noise-robust CE-OFDM communication. It is with fixed low power-to-average power ratio to render robustness against the nonlinear distortions. In proof-of-concept experiments, a 60-GHz JRC signal with an instantaneous bandwidth over 10-GHz is synthesized through a CE-LFM-OFDM signal encoded with a 2-GBaud 16-QAM OFDM signal. Consequently, a 1.5-cm range resolution of two-dimension imaging and an 8-Gbit/s data rate are achieved for both radar and communication functions, respectively. Furthermore, the proposed JRC system is able to achieve higher radar range resolution and better anti-noise communication, when using higher-order photonic frequency multiplying.

Lactobacillus plantarum-derived extracellular vesicles protect against ischemic brain injury via the microRNA-101a-3p/c-Fos/TGF-ß axis.

Currently, the reported source of extracellular vesicles (EVs) for the treatment of ischemic stroke（IS）is limited to mammals. Moreover, these EVs are restricted to clinical translation by the high cost of cell culture. In this respect, Lactobacillus plantarum culture is advantaged by low cost and high yield. However, it is poorly understood whether Lactobacillus plantarum-derived EVs (LEVs) are applicable for the treatment of IS. Here, our results demonstrated that LEVs reduced apoptosis in ischemic neuron both in vivo and in vitro. As revealed by high-throughput sequencing, miR-101a-3p expression was significantly elevated by LEV treatment in OGD/R-induced neurons, as confirmed in the tMCAO mice treated with LEVs. Mechanistically, c-Fos was directly targeted by miR-101a-3p. In addition, c-Fos determined ischemia-induced neuron apoptosis in vivo and in vitro through the TGF-ß1 pathway, miR-101a-3p inhibition aggravated ischemia-induced neuron apoptosis in vitro and in vivo, and miR-101a-3p overexpression produced the opposite results. Hsa-miR-101-3p was downregulated in the plasma of patients with IS but upregulated in the patients with neurological recovery after rt-PA intravenous thrombolysis. In conclusion, Our results demonstrated for the first time that LEVs might inhibit neuron apoptosis via the miR-101a-3p/c-Fos/TGF-ß axis, and has-miR-101-3p is a potential marker of neurological recovery in IS patients.

An Optimal Multi-Channel Trilateration Localization Algorithm by Radio-Multipath Multi-Objective Evolution in RSS-Ranging-Based Wireless Sensor Networks.

The Global Positioning System (GPS) is unable to provide precise localization services indoors, which has led to wireless sensor network (WSN) localization technology becoming a hot research issue in the field of indoor location. At present, the ranging technology of wireless sensor networks based on received signal strength has been extensively used in indoor positioning. However, wireless signals have serious multipath effects in indoor environments. In order to reduce the adverse influence of multipath effects on distance estimation between nodes, a multi-channel ranging localization algorithm based on signal diversity is herein proposed. In real indoor environments, the parameters used for multi-channel localization algorithms are generally unknown or time-varying. In order to increase the positioning accuracy of the multi-channel location algorithm in a multipath environment, we propose an optimal multi-channel trilateration positioning algorithm (OMCT) by establishing a novel multi-objective evolutionary model. The presented algorithm utilizes a three-edge constraint to prevent the traditional multi-channel localization algorithm falling into local optima. The results of a large number of practical experiments and numerical simulations show that no matter how the channel number and multipath number change, the positioning error of our presented algorithm is always smaller compared with that of the state-of-the-art algorithm.