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Cooperative perception that integrates sensing capabilities from both infrastructure and vehicle perception sensors can greatly benefit the transportation system with respect to safety and data acquisition. In this study, we conduct a preliminary evaluation of such a system by integrating a portable lidar-based infrastructure detection system (namely, Traffic Scanner [TScan]) with a Society of Automotive Engineers (SAE) Level 4 connected and automated vehicle (CAV). Vehicle-to-everything (V2X) communication devices are installed on both the TScan and the CAV to enable real-time message transmission of detection results in the form of SAE J2735 basic safety messages. We validate the concept using a case study, which aims at improving CAV situation awareness and protecting vulnerable road user (VRU) safety. Field testing results demonstrate the safety benefits of cooperative perception from infrastructure sensors in detecting occluded VRUs and helping CAVs to plan safer (i.e., higher post-encroachment time) and smoother (i.e., lower deceleration rates) trajectories. 

Stimuli-responsive RAPs with disulfide bonds enablein-situelectrode cleaningviaUV or electrochemical stimuli, effectively removing fouling and restoring electrode performance in electrochemical flow cells. 

Abstract Precise modulating the vertical structure of active layers to boost charge transfer is an effective way to achieve high power conversion efficiencies (PCEs) in organic solar cells (OSCs). Herein, efficient OSCs with a well‐controlled vertical structure are realized by a rapid film‐forming method combining low boiling point solvent and the sequential blade‐coating (SBC) technology. The results of grazing incident wide‐angle X‐ray scattering measurement show that the vertical component distribution is varied by changing the processing solvent. Novel characterization technique such as tilt resonant soft X‐ray scattering is used to test the vertical structure of the films, demonstrating the dichloromethane (DCM)‐processed film is truly planar heterojunction. The devices with chloroform (CF) processed upper layer show an increased mixed phase region compared to these devices with toluene (TL) or ‐DCM‐, which is beneficial for improving charge generation and achieving a superior PCE of 17.36%. Despite significant morphological varies, the DCM‐processed devices perform slightly lower PCE of 16.66%, which is the highest value in truly planar heterojunction devices, demonstrating higher morphological tolerance. This work proposes a solvent‐regulating method to optimize the vertical structure of active layers through SBC technology, and provides a practical guidance for the optimization of the active‐layer microstructure. 

Ear wearables (earables) are emerging platforms that are broadly adopted in various applications. There is an increasing demand for robust earables authentication because of the growing amount of sensitive information and the IoT devices that the earable could access. Traditional authentication methods become less feasible due to the limited input interface of earables. Nevertheless, the rich head-related sensing capabilities of earables can be exploited to capture human biometrics. In this paper, we propose EarSlide, an earable biometric authentication system utilizing the advanced sensing capacities of earables and the distinctive features of acoustic fingerprints when users slide their fingers on the face. It utilizes the inward-facing microphone of the earables and the face-ear channel of the ear canal to reliably capture the acoustic fingerprint. In particular, we study the theory of friction sound and categorize the characteristics of the acoustic fingerprints into three representative classes, pattern-class, ridge-groove-class, and coupling-class. Different from traditional fingerprint authentication only utilizes 2D patterns, we incorporate the 3D information in acoustic fingerprint and indirectly sense the fingerprint for authentication. We then design representative sliding gestures that carry rich information about the acoustic fingerprint while being easy to perform. It then extracts multi-class acoustic fingerprint features to reflect the inherent acoustic fingerprint characteristic for authentication. We also adopt an adaptable authentication model and a user behavior mitigation strategy to effectively authenticate legit users from adversaries. The key advantages of EarSlide are that it is resistant to spoofing attacks and its wide acceptability. Our evaluation of EarSlide in diverse real-world environments with intervals over one year shows that EarSlide achieves an average balanced accuracy rate of 98.37% with only one sliding gesture.