Low-density lipoprotein receptor-related protein 2(LRP2)is required for lipid export in the midgut of the migratory locust,Locusta migratoria

Low-density lipoprotein receptor-related protein 2(LRP2)is a multifunctional endocytic receptor expressed in epithelial cells.In mammals,it acts as an endocytic receptor that mediates the cellular uptake of cholesterol-containing apolipoproteins to maintain lipid homeostasis.However,little is known about the role of LRP2 in lipid homeostasis in insects.In the present study,we investigated the function of LRP2 in the migratory locust Locusta migratoria(LmLRP2).The mRNA of LmLRP2 is widely distributed in various tissues,including integument,wing pads,foregut,midgut,hindgut,Malpighian tubules and fat body,and the amounts of LmLRP2 transcripts decreased gradually in the early stages and then increased in the late stages before ecdysis during the nymphal developmental stage.Fluorescence immunohistochemistry revealed that the LmLRP2 protein is mainly located in cellular membranes of the midgut and hindgut.Using RNAi to silence LmLRP2 caused molting defects in nymphs(more than 60%),and the neutral lipid was found to accumulate in the midgut and surface of the integument,but not in the fat body,of dsLmLRP2-treated nymphs.The results of a lipidomics analysis showed that the main components of lipids(diglyceride and triglyceride)were significantly increased in the midgut,but decreased in the fat body and hemolymph.Furthermore,the content of total triglyceride was significantly increased in the midgut,but markedly decreased in the fat body and hemolymph in dsLmLRP2-injected nymphs.Our results indicate that LmLRP2 is located in the cellular membranes of midgut cells,and is required for lipid export from the midgut to the hemolymphand fat body in locusts.

RFHUI:an RFID based human-unmanned aerial vehicle interaction system in an indoor environment

In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.

Effect of Interfacial Microstructure on Mechanical and Tribological Properties of Cu/WS_(2) Self-Iubricating Composites Sintered by Spark Plasma Sintering

In this study,Cu/WS_(2) self-lubricating composites are fabricated by spark plasma sintering.Interfacial microstructure and its effect on mechanical and tribological properties are investigated.High sintering temperature at 850℃promotes decomposition of WS_(2) and its following interfacial reaction with Cu to form Cu_(0.4)W_(0.6) nanoparticles and Cu_(2)S,enhancing mechanical properties as well as wear resistance of the composites.But the destruction of WS_(2) leads to a high friction coefficient.On the contrary,for the composites sintered at 750℃,a nanoscale diffusion zone forms at the Cu/WS_(2) interface.WS_(2) lubricant retains its lamellar structure.The composite shows excellent self-lubrication performance,with a low friction coefficient of 0.16.However,its mechanical properties are low,and the wear rate is one magnitude higher.

Multi-State-Space Reasoning Reinforcement Learning for Long-Horizon RFID-Based Robotic Searching and Planning Tasks

In recent years,reinforcement learning(RL)has shown high potential for robotic applications.However,RL heavily relies on the reward function,and the agent merely follows the policy to maximize rewards but lacks reasoning ability.As a result,RL may not be suitable for long-horizon robotic tasks.In this paper,we propose a novel learning framework,called multiple state spaces reasoning reinforcement learning(SRRL),to endow the agent with the primary reasoning capability.First,we abstract the implicit and latent links between multiple state spaces.Then,we embed historical observations through a long short-term memory(LSTM)network to preserve long-term memories and dependencies.The proposed SRRL’s ability of abstraction and long-term memory enables agents to execute long-horizon robotic searching and planning tasks more quickly and reasonably by exploiting the correlation between radio frequency identification(RFID)sensing properties and the environment occupation map.We experimentally validate the efficacy of SRRL in a visual game-based simulation environment.Our methodology outperforms three state-of-the-art baseline schemes by significant margins.