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Millimeter-wave (mm-wave) technology, crucial for future networks and vehicle-to-everything (V2X) communication in intelligent transportation, offers high data rates and bandwidth but is vulnerable to adversarial attacks, like interference and eavesdropping. It is crucial to protect V2X mm-wave communication from cybersecurity attacks, as traditional security measures often fail to counter sophisticated threats and complex attacks. To tackle these difficulties, the current study introduces an attention-enhanced defensive distillation network (AEDDN) to improve robustness and accuracy in V2X mm-wave communication under adversarial attacks. The AEDDN model combines the transformer algorithm with defensive distillation, leveraging the transformer's attention mechanism to focus on critical channel features and adapt to complex conditions. This helps mitigate adversarial examples by filtering misleading data. Defensive distillation further strengthens the model by smoothing decision boundaries, making it less sensitive to small perturbations. To evaluate and validate the AEDDN model, this study uses a publicly available dataset called 6g-channel-estimation and a proprietary dataset named MMMC, comparing the simulation results with the convolutional neural network (CNN) model. The findings from the experiments indicate that the AEDDN, especially in the complex V2X mm-wave environment, demonstrates enhanced performance. [ABSTRACT FROM AUTHOR]

Within the context of smart transportation and new infrastructure, Vehicle-to-Everything (V2X) communication has entered a new stage, introducing the concept of holographic intersection. This concept requires roadside sensors to achieve collaborative perception, collaborative decision-making, and control. To meet the high-level requirements of V2X, it is essential to obtain precise, rapid, and accurate roadside information data. This study proposes an automated vehicle distance detection and warning scheme based on camera video streams. It utilizes edge computing units for intelligent processing and employs neural network models for object recognition. Distance estimation is performed based on the principle of similar triangles, providing safety recommendations. Experimental validation shows that this scheme can achieve centimeter-level distance detection accuracy, enhancing traffic safety. This approach has the potential to become a crucial tool in the field of traffic safety, providing intersection traffic target information for intelligent connected vehicles (ICVs) and autonomous vehicles, thereby enabling V2X driving at holographic intersections. [ABSTRACT FROM AUTHOR]

Laser lighting has shown enormous potential in various fields, such as automotive lighting, military reconnaissance and projection display, due to its advantages of high brightness, small size and long illumination distance. However, phosphor in glass (PIG) has the problem of balancing high color rendering index (CRI) and high luminous flux (LF). Therefore, a composite PIG containing yellow phosphor (YAG:Ce3+) and red phosphor (CASN:Eu2+) was prepared. The internal quantum efficiency (IQE) of the prepared YAG:Ce3+ PIG is as high as 90.50% (95.4% of the original phosphor) and the luminous intensity at 150 °C is 93.3% of that at room temperature. After encapsulating YAG: Ce3+ with a mass percentage of 10 wt.% PIG and LD, the maximum LF obtained is 3479.2 lm. The LF of 7 wt.% CaAlSiN red PIG under 7.8 W laser excitation is 413 lm. By optimizing the ratio in the composite PIG, the maximum CRI of the laser device is 82.2, the correlation color temperature (CCT) is 4281 K, the luminous efficiency (LE) is 171.2 lm⋅W-1 and the LF is 2036.6 lm with the combination of 10 wt.% YAG:Ce3+ and 7 wt.%CASN:Eu2+. Meanwhile, high CRI and high LF of PIG-based laser devices are realized. Therefore, PIG with homogenous structure combination is regarded as a potential phosphor conversion material. [ABSTRACT FROM AUTHOR]

High-Definition Maps (HD Maps) are lane-level 3-dimensional road network models that ensure the safe operation of autonomous vehicles and drive the continuous advancement of autonomous driving technology to higher levels. However, HD Maps currently face challenges regarding limited coverage and description of indoor environments (e.g. underground parking), as well as the lack of uniformity between indoor and outdoor map formats. Therefore, this paper proposes a Layered HD Map model for both indoor and outdoor environments. The map model consists of 6 layers, allowing effective representation of indoor and outdoor environments, as well as transitional areas. The paper also establishes an Unmanned Ground Vehicle (UGV) to collect and update map data using LiDAR (Light Detection and Ranging) SLAM (Simultaneous Localization and Mapping) and autonomous exploration technology, aiming to enhance the efficiency and automation of HD Map acquisition. In order to verify the validity of the proposed map model, this paper conducted a navigation experiment in a double decker parking lot containing entrances and exits. The results of the experiments demonstrate that the Layered HD Map generated through autonomous LiDAR SLAM can effectively describe the indoor and outdoor environments, and enable successful navigation of UGVs. [ABSTRACT FROM AUTHOR]

Oxidative desulfurization (ODS) in diesel has attracted great attention for meeting the increasingly stringent standards in last few decades but remains a huge challenge that oxidant is underutilization. We achieve the high sulphur removal and the lowest n(H2O2)/n(S) over a smart heterogeneous catalyst of Fe-containing Ti-nanotube (Fe-TiNTs) which was prepared and synthesized by one-step hydrothermal method. X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), N2 adsorption–desorption and so on were used to characterize the catalyst. For DBT, the sulphur removal rate was nearly 99%, the Fe-TiNTs showed excellent catalytic selectivity in ODS, and their activity does not decrease significantly in the presence of various diesel compounds. The characterizations and iodometric titration analyses show that the high activity is related to the mechanism of Ti-η1-hydroperoxide and radical oxidation. [ABSTRACT FROM AUTHOR]

Synthesis of gem -difluorinated cyclobutenes presents certain challenges for considering the compatibility of the fluorine atom introduction with four-membered ring retention. Herein, we develop a transition-metal-free synthetic strategy toward gem -difluorinated cyclobutenes from gem -difluorinated cyclopropyl N -tosylhydrazons via ring expansion reaction. The gem -difluoro substitution alters the properties of the cyclopropane, facilitating the thermal rearrangement of cyclopropyl carbenes into cyclobutenes. This reaction can be easily handled free from inert gas protection, thus offering an efficient route to synthesize gem -difluorinated cyclobutenes.

Concerns about energy and the environment are motivating a reexamination of catalytic processes, aiming to achieve more efficient and improved catalysis compatible with sustainability. Designing an active site for such heterogeneous catalytic processes remains a challenge leading to a next level breakthrough. Herein, we discuss a fundamental aspect of heterogeneous catalysis: the chemical potential of electrons in solid catalysts during thermal catalysis, which directly reflects the consequent catalytic reaction rate. The use of electrochemical tools during thermal catalysis allows for the quantitative determination of the ill-defined chemical potentials of solids in operando , whereby the potential-rate relationship can be established. Furthermore, the electrochemical means can also introduce the direct perturbation of catalyst potentials, in turn, perturbing the coverage of adsorbates functioning as poison, promoters, or reactants. We collect selected publications on these aspects, and provide a viewpoint bridging the fields of thermal- and electro-catalysis., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)