Dynamic Barrier Coverage in a Wireless Sensor Network for Smart Grids

The development of engineering technology such as inspection robots (IR) for transmission lines and wireless sensor networks (WSN) are widely used in the field of smart grid monitoring. However, how to integrate inspection robots into wireless sensor networks is still a great challenge to form an efficient dynamic monitoring network for transmission lines. To address this problem, a dynamic barrier coverage (DBC) method combining inspection robot and wireless sensor network (WSN) is proposed to realize a low-cost, energy-saving and dynamic smart grid-oriented sensing system based on mobile wireless sensor network. To establish an effective smart grid monitoring system, this research focuses on the design of an effective and safe dynamic network coverage and network nodes deployment method. Multiple simulation scenarios are implemented to explore the variation of network performance with different parameters. In addition, the dynamic barrier coverage method for the actual scene of smart grid monitoring considers the balance between network performance and financial costs

A Novel Method of Autonomous Inspection for Transmission Line based on Cable Inspection Robot LiDAR Data

With the growth of the national economy, there is increasing demand for electricity, which forces transmission line corridors to become structurally complicated and extend to complex environments (e.g., mountains, forests). It is a great challenge to inspect transmission line in these regions. To address these difficulties, a novel method of autonomous inspection for transmission line is proposed based on cable inspection robot (CIR) LiDAR data, which mainly includes two steps: preliminary inspection and autonomous inspection. In preliminary inspection, the position and orientation system (POS) data is used for original point cloud dividing, ground point filtering, and structured partition. A hierarchical classification strategy is established to identify the classes and positions of the abnormal points. In autonomous inspection, CIR can autonomously reach the specified points through inspection planning. These inspection targets are imaged with PTZ (pan, tilt, zoom) cameras by coordinate transformation. The feasibility and effectiveness of the proposed method are verified by test site experiments and actual line experiments, respectively. The proposed method greatly reduces manpower and improves inspection accuracy, providing a theoretical basis for intelligent inspection of transmission lines in the future

Identification of Darunavir Derivatives for Inhibition of SARS-CoV-2 3CLpro

The effective antiviral agents that treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are urgently needed around the world. The 3C-like protease (3CLpro) of SARS-CoV-2 plays a pivotal role in virus replication; it also has become an important therapeutic target for the infection of SARS-CoV-2. In this work, we have identified Darunavir derivatives that inhibit the 3CLpro through a high-throughput screening method based on a fluorescence resonance energy transfer (FRET) assay in vitro. We found that the compounds 29# and 50# containing polyphenol and caffeine derivatives as the P2 ligand, respectively, exhibited favorable anti-3CLpro potency with EC50 values of 6.3 μM and 3.5 μM and were shown to bind to SARS-CoV-2 3CLpro in vitro. Moreover, we analyzed the binding mode of the DRV in the 3CLpro through molecular docking. Importantly, 29# and 50# exhibited a similar activity against the protease in Omicron variants. The inhibitory effect of compounds 29# and 50# on the SARS-CoV-2 3CLpro warrants that they are worth being the template to design functionally improved inhibitors for the treatment of COVID-19

Teicoplanin derivatives block spike protein mediated viral entry as pan-SARS-CoV-2 inhibitors

The rapid emergence of highly transmissible SARS-CoV-2 variants poses serious threat to the efficacy of vaccines and neutralizing antibodies. Thus, there is an urgent need to develop new and effective inhibitors against SARS-CoV-2 and future outbreaks. Here, we have identified a series of glycopeptide antibiotics teicoplanin derivatives that bind to the SARS-CoV-2 spike (S) protein, interrupt its interaction with ACE2 receptor and selectively inhibit viral entry mediated by S protein. Computation modeling predicts that these compounds interact with the residues in the receptor binding domain. More importantly, these teicoplanin derivatives inhibit the entry of both pseudotyped SARS-CoV-2 Delta and Omicron variants. Our study demonstrates the feasibility of developing small molecule entry inhibitors by targeting the interaction of viral S protein and ACE2. Together, considering the proven safety and pharmacokinetics of teicoplanin as a glycopeptide antibiotic, the teicoplanin derivatives hold great promise of being repurposed as pan-SARS-CoV-2 inhibitors