A coupling approach to demand prediction and repositioning in SAV systems

Reinforcement Learning (RL) is currently one of the most commonly used techniques for traffic signal control (TSC), which can adaptively adjust traffic signal phase and duration according to real-time traffic data. However, a fully centralized RL approach is beset with difficulties in a multi-network scenario because of exponential growth in state-action space with increasing intersections. Multi-agent reinforcement learning (MARL) can overcome the high-dimension problem by employing global control of each local RL agent, but it also brings new challenges, such as failures of convergence caused by the non-stationary Markov Decision Process (MDP). In this paper, we introduce an off-policy nash deep Q-Network (OPNDQN) algorithm, which mitigates the weakness of both fully centralized and MARL approaches. The OPNDQN algorithm solves the problem that traditional algorithms cannot be used in large state-action space traffic models by utilizing a fictitious game approach at each iteration to find the nash equilibrium among neighboring intersections, by which no intersection has incentive to unilaterally deviate. One of the main advantages of the OPNDQN is that it can mitigate the non-stationarity of multi agent Markov process because it considers the mutual influence among neighboring intersections by sharing their actions. On the other hand, for training a large traffic network, the convergence rate of the OPNDQN is higher than that of existing MARL approaches because it does not incorporate all state information of each agent. We conduct extensive experiments by using Simulation of Urban MObility simulator (SUMO), and show the dominant superiority of the OPNDQN over several existing MARL approaches in terms of average queue length, episode training reward and average waiting time.</p

A prefrontal-thalamic circuit encodes social information for social recognition

Abstract Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing

High combustion activity of CH \u3c inf\u3e 4 and catalluminescence properties of CO oxidation over porous Co \u3c inf\u3e 3 O \u3c inf\u3e 4 nanorods

The highly porous Co 3O 4 nanorods are prepared by a simple hydrothermal method, in which CO(NH 2) 2 is employed as precipitating agent, and K60 (PVP, polyvinylpyrrolidone) is used as surfactant to improve the stability of the nanoparticles. For comparison, the bulk Co 3O 4 is prepared by thermal decomposition of cobalt nitrate. The samples are characterized by field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (ED), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, N 2 adsorption, Thermogravimetric analysis (TG), H 2-temperature programmed reduction (TPR), CO-, CH 4-, and O 2-temperature programmed desorption (TPD). The catalluminescence (CTL) and catalytic properties of the samples are investigated extensively. The results show that the Co 3O 4 nanorods are composed of nanoparticles, and have a large number of pores with a narrow pore size distribution (1.5-7nm). Compared with the bulk Co 3O 4, the porous nanorods have a higher CTL intensity of CO oxidation, and a higher activity of CH 4 combustion especially at a higher gas hourly space velocity (GHSV), which has been ascribed to its porous structure and larger surface area. © 2011 Elsevier B.V

Compact meta-differentiator for achieving isotropically high-contrast ultrasonic imaging

Abstract Ultrasonic imaging is crucial in the fields of biomedical engineering for its deep penetration capabilities and non-ionizing nature. However, traditional techniques heavily rely on impedance differences within objects, resulting in poor contrast when imaging acoustically transparent targets. Here, we propose a compact spatial differentiator for underwater isotropic edge-enhanced imaging, which enhances the imaging contrast without the need for contrast agents or external physical fields. This design incorporates an amplitude meta-grating for linear transmission along the radial direction, combined with a phase meta-grating that utilizes focus and spiral phases with a first-order topological charge. Through theoretical analysis, numerical simulations, and experimental validation, we substantiate the effectiveness of our technique in distinguishing amplitude objects with isotropic edge enhancements. Importantly, this method also enables the accurate detection of both phase objects and artificial biological models. This breakthrough creates new opportunities for applications in medical diagnosis and nondestructive testing