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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]

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]

Decarbonization has become an urgent affair to restrain global warming. CO2 hydrogenation coupled with H2 derived from water electrolysis is considered a promising route to mitigate the negative impact of carbon emission and also promote the application of hydrogen. It is of great significance to develop catalysts with excellent performance and large-scale implementation. In the past decades, metal–organic frameworks (MOFs) have been widely involved in the rational design of catalysts for CO2 hydrogenation due to their high surface areas, tunable porosities, well-ordered pore structures, and diversities in metals and functional groups. Confinement effects in MOFs or MOF-derived materials have been reported to promote the stability of CO2 hydrogenation catalysts, such as molecular complexes of immobilization effect, active sites in size effect, stabilization in the encapsulation effect, and electron transfer and interfacial catalysis in the synergistic effect. This review attempts to summarize the progress of MOF-based CO2 hydrogenation catalysts up to now, and demonstrate the synthetic strategies, unique features, and enhancement mechanisms compared with traditionally supported catalysts. Great emphasis will be placed on various confinement effects in CO2 hydrogenation. The challenges and opportunities in precise design, synthesis, and applications of MOF-confined catalysis for CO2 hydrogenation are also summarized. [ABSTRACT FROM AUTHOR]

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.)