Existing research has focused on trajectory similarity computation under centralized data storage. However, in the real world, trajectories are often collected and held by multiple distinct entities that form a data federation. Due to commercial and legal restrictions, direct data sharing among these entities may be prohibited, which renders existing centralized methods incapable of supporting similarity computation over trajectory data federation.

Sub-headline: NUDT researchers systematize DCN congestion control, introducing the DCEF framework to tackle traffic volatility

With the continuous advancement of the new energy sector, direct methanol fuel cells (DMFCs) have attracted significant research interest. However, the development of DMFCs is hindered by the reliance on platinum-based anode catalysts, which suffer from high cost, intermediate-induced poisoning, and rapid performance degradation.

Titanium dioxide (TiO₂) is an important photocatalytic material, yet its performance is limited by bottlenecks in conventional preparation methods, such as high interfacial resistance and low specific surface area. Recently, a method combining laser cladding with electrochemical dealloying, reported by Frontiers of Materials Science, was used to fabricate porous TiO₂/Cu₂O heterojunction photoanodes from a Cu–Ti precursor.

With the continuous advancement of lithiumion batteries (LIBs), increasing demands have been placed on achieving ultrafast charging capability. Graphite, the dominant commercial anode material, suffers from sluggish ion transport kinetics and interfacial instability, which pose significant challenges to the fast-charging performance of LIBs. Previous strategies, including surface coatings and conductive network construction, often address these challenges in isolation, leading to an inherent tradeoff between structural stability and electrical conductivity. Xu et al. recently reported scalable onestep pyrolysis of pitch that concurrently constructs a conformal amorphouscarbon shell and an integrated graphene network (Gr) on graphite.

A new artificial intelligence (AI) framework offers a more reliable way to restore partially hidden objects in satellite imagery.