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Real-World Deployment of a 5G-Connected Edge-Controlled Aerial Robot in Industrial Subterranean Mines
arXiv:2606.04818v1 Announce Type: new Abstract: This article presents the first real-world autonomous flight of a 5G-connected aerial robot controlled by an edge-offloaded controller, and aims to bridge the gap between controlled and factual setups. The robot operates within an active industrial subterranean mine, while the high-level controller is deployed in a nearby Kubernetes-based edge cluster. Communication between the robot and the edge is enabled via a 5G New Radio (NR) Standalone...
Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks
arXiv:2606.03462v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance on graph-structured data, but their effectiveness depends heavily on the quality of the observed graph. In real applications, graph topology is often imperfect: noisy edges may connect unrelated nodes, while missing edges may prevent useful information from being propagated. Existing robust graph learning methods mainly address this problem by removing suspicious edges or by learning a new...
Temporal Cliques Admit Linear Spanners
arXiv:2606.05156v1 Announce Type: new Abstract: A temporal graph is a graph in which every edge carries a non-empty set of time labels, and it is temporally connected if for every two vertices $u$ and $v$, there exists a $u$-$v$-path with non-decreasing time labels. A spanner is a subset of its edges preserving temporal connectivity. Unlike static graphs, temporally connected graphs need not admit sparse spanners; nonetheless, minimizing spanner size is a central and widely studied problem.
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
arXiv:2606.01560v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are vulnerable to adversarial attacks, which inherently invert connectivity patterns by introducing disassortative edges in assortative graphs and assortative edges in disassortative graphs. This structural inversion creates structure-feature mismatches that disrupt neighborhood aggregation across different graph types.
Quantum-Inspired Reinforcement Learning for Low-Latency Intrusion Detection in V2X and Internet-of-Vehicles Networks
Announce Type: new Abstract: Smart cities increasingly depend on dense edge, IoT, and vehicular networks to deliver critical urban services, including traffic control, connected mobility, infrastructure monitoring, and energy management. In this ecosystem, the Internet of Vehicles (IoV) is central to intelligent transportation, enabling continuous communication among vehicles, roadside infrastructure, and cloud-edge platforms. This connectivity, however, also enlarges the attack surface and...
Q-FE: A Quantum-Native 6G Far-Edge Architecture Securing Industrial IoT Digital Twins via CSIDH-PQC and Asynchronous Federated Learning
arXiv:2606.03611v1 Announce Type: new Abstract: Sixth-generation (6G) wireless networks will underpin ultra-dense Industrial IoT (IIoT) ecosystems in which resource-constrained Far-Edge devices -- autonomous mobile robots, industrial actuators, connected vehicles -- must simultaneously satisfy sub-millisecond latency, $10^{-7}$-class reliability, and decades-long cryptographic security. Current architectures delegate Digital Twin (DT) computation to centralised cloud or Mobile Edge Computing...
This startup wants to reduce payment friction on prediction markets
As prediction market volumes continue to march higher and platforms increasingly look to institutional players to engage, a startup is seeking to make it easier to move money around on event contract exchanges. EDGE Markets — which runs a banking platform designed for gambling and prediction market spending — is set to debut two products, the company shared exclusively with CNBC ahead of a Monday announcement. It will also reveal a $29.2 million Series A funding round, led by venture capital...
Overarming America: Game theory explores how fear and social pressure drive gun purchases
Overarming America: Game theory explores how fear and social pressure drive gun purchases Stephanie Baum Scientific Editor Robert Egan Associate Editor A Dartmouth College study is the first to map the interplay of personal choice and social networks that has led to the United States being one of the world's most heavily armed countries, with 120 firearms for every 100 people. The researchers describe in Science Advances how individual incentives to buy firearms can lead to a phenomenon they...
The Unreasonable Redundancy of Nature's Protein Folds
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On the Duke--Erd\H{o}s--R\"odl Problem at the One-Third Threshold
Announce Type: cross Abstract: Let $G$ be an $n$-vertex graph with $e(G)\ge n^2/ k$. We prove a self-contained internal short-cycle core theorem at the threshold $k\le n^{1/3}$: the graph $G$ contains a subgraph $H_6$ with $\Omega(n^2/ k^3)$ edges in which every two distinct edges lie together on a cycle of length at most $6$ contained in $H_6$, and a subgraph $H_8$ with $\Omega(n^2/k^2)$ edges in which every two distinct edges lie together on a cycle of length at most $8$ contained in...