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Bird's-eye-view (BEV) representations derived from multi-camera input have become a central interface for online high-definition (HD) map construction. However, most approaches rely solely on ego-centric supervision, requiring large-scale scene structure to be inferred from incomplete observations, occlusions, and diminishing information density at long range, where perspective effects and spatial sparsity hinder consistent structural reasoning. We introduce Cross-View Supervision (CVS), a representation learning paradigm that transfers geometric and topological priors from an ego-aligned overhead perspective into camera-based BEV encoders. Rather than adding auxiliary semantic losses, CVS aligns representations in a shared BEV feature space and distills globally consistent structural knowledge from a perspective-privileged teacher into the ego-centric backbone. This supervision enhances structural coherence without modifying the inference architecture or requiring overhead input at test time. Experiments on nuScenes using ego-aligned aerial imagery from the AID4AD cross-view extension demonstrate consistent improvements over StreamMapNet while maintaining identical camera-only inference. CVS yields +3.9\\,mAP in the standard \\(6030\\,m\\) region and +9.9\\,mAP in the extended \\(10050\\,m\\) setting, corresponding to a 44\\% relative gain at long range. These results highlight perspective-privileged structural supervision as a promising training principle for improving BEV representation learning in HD map construction.

This work investigates the integration of spatially aligned aerial imagery into perception tasks for automated vehicles (AVs). As a central contribution, we present AID4AD, a publicly available dataset that augments the nuScenes dataset with high-resolution aerial imagery precisely aligned to its local coordinate system. The alignment is performed using SLAM-based point cloud maps provided by nuScenes, establishing a direct link between aerial data and nuScenes local coordinate system. To ensure spatial fidelity, we propose an alignment workflow that corrects for localization and projection distortions. A manual quality control process further refines the dataset by identifying a set of high-quality alignments, which we publish as ground truth to support future research on automated registration. We demonstrate the practical value of AID4AD in two representative tasks: in online map construction, aerial imagery serves as a complementary input that improves the mapping process; in motion prediction, it functions as a structured environmental representation that replaces high-definition maps. Experiments show that aerial imagery leads to a 15-23% improvement in map construction accuracy and a 2% gain in trajectory prediction performance. These results highlight the potential of aerial imagery as a scalable and adaptable source of environmental context in automated vehicle systems, particularly in scenarios where high-definition maps are unavailable, outdated, or costly to maintain. AID4AD, along with evaluation code and pretrained models, is publicly released to foster further research in this direction: https://github.com/DriverlessMobility/AID4AD.

Flatworms can very rapidly attach to and detach from many substrates. In the presented work, we analysed the adhesive system of the marine proseriate flatworm Minona ileanae . We used light-, scanning- and transmission electron microscopy to analyse the morphology of the adhesive organs, which are located at the ventral side of the tail-plate. We performed transcriptome sequencing and differential RNA-seq for the identification of tail-specific transcripts. Using in situ hybridization expression screening, we identified nine transcripts that were expressed in the cells of the adhesive organs. Knock-down of five of these transcripts by RNA interference led to a reduction of the animal's attachment capacity. Adhesive proteins in footprints were confirmed using mass spectrometry and antibody staining. Additionally, lectin labelling of footprints revealed the presence of several sugar moieties. Furthermore, we determined a genome size of about 560 Mb for M. ileanae . We demonstrated the potential of Oxford Nanopore sequencing of genomic DNA as a cost-effective tool for identifying the number of repeats within an adhesive protein and for combining transcripts that were fragments of larger genes. A better understanding of the molecules involved in flatworm bioadhesion can pave the way towards developing innovative glues with reversible adhesive properties. This article is part of the theme issue ‘Transdisciplinary approaches to the study of adhesion and adhesives in biological systems’.

Flatworms can very rapidly attach to and detach from many substrates. In the presented work, we analysed the adhesive system of the marine proseriate flat-worm Minona ileanae. We used light-, scanning- and transmission electron microscopy to analyse the morphology of the adhesive organs, which are located at the ventral side of the tail-plate. We performed transcriptome sequencing and differential RNA-seq for the identification of tail-specific transcripts. Using in situ hybridization expression screening, we identified nine transcripts that were expressed in the cells of the adhesive organs. Knock-down of five of these transcripts by RNA interference led to a reduction of the animal's attachment capacity. Adhesive proteins in footprints were confirmed using mass spectrometry and antibody staining. Additionally, lectin labelling of footprints revealed the presence of several sugar moieties. Furthermore, we determined a genome size of about 560 Mb for M. ileanae. We demonstrated the potential of Oxford Nanopore sequencing of genomic DNA as a cost-effective tool for identifying the number of repeats within an adhesive protein and for combining transcripts that were fragments of larger genes. A better understanding of the molecules involved in flatworm bioadhesion can pave the way towards developing innovative glues with reversible adhesive properties. This article is part of the theme issue 'Transdisciplinary approaches to the study of adhesion and adhesives in biological systems'.