Spectral radius conditions for fractional [a,b][a,b]-covered graphs

A graph $G$ is called fractional $[a,b]$-covered if for every edge $e$ of $G$ there is a fractional $[a,b]$-factor with the indicator function $h$ such that $h(e)=1$. In this paper, we provide tight spectral radius conditions for graphs being fractional $[a,b]$-covered.Comment: 9 page

Does the Dirac Cone Exist in Silicene on Metal Substrates?

Absence of the Dirac cone due to a strong band hybridization is revealed to be a common feature for epitaxial silicene on metal substrates according to our first-principles calculations for silicene on Ir, Cu, Mg, Au, Pt, Al, and Ag substrates. The destroyed Dirac cone of silicene, however, can be effectively restored with linear or parabolic dispersion by intercalating alkali metal atoms between silicene and the metal substrates, offering an opportunity to study the intriguing properties of silicene without further transfer of silicene from the metal substrates

Mechanism of Exact Transition between Cationic and Anionic Redox Activities in Cathode Material Li2FeSiO4.

The discovery of anion redox activity is promising for boosting the capacity of lithium ion battery (LIB) cathodes. However, fundamental understanding of the mechanisms that trigger the anionic redox is still lacking. Here, using hybrid density functional study combined with experimental soft X-ray absorption spectroscopy (sXAS) measurements, we unambiguously proved that Li(2- x)FeSiO4 performs sequent cationic and anionic redox activity through delithiation. Specifically, Fe2+ is oxidized to Fe3+ during the first Li ion extraction per formula unit (f.u.), while the second Li ion extraction triggered the oxygen redox exclusively. Cationic and anionic redox result in electron and hole polaron states, respectively, explaining the poor conductivity of Li(2- x)FeSiO4 noted by previous experiments. In contrast, other cathode materials in this family exhibit diversity of the redox process. Li2MnSiO4 shows double cationic redox (Mn2+-Mn4+) during the whole delithiation, while Li2CoSiO4 shows simultaneous cationic and anionic redox. The present finding not only provides new insights into the oxygen redox activity in polyanionic compounds for rechargeable batteries but also sheds light on the future design of high-capacity rechargeable batteries

Five-Tiered Route Planner for Multi-AUV Accessing Fixed Nodes in Uncertain Ocean Environments

This article introduces a five-tiered route planner for accessing multiple nodes with multiple autonomous underwater vehicles (AUVs) that enables efficient task completion in stochastic ocean environments. First, the pre-planning tier solves the single-AUV routing problem to find the optimal giant route (GR), estimates the number of required AUVs based on GR segmentation, and allocates nodes for each AUV to access. Second, the route planning tier plans individual routes for each AUV. During navigation, the path planning tier provides each AUV with physical paths between any two points, while the actuation tier is responsible for path tracking and obstacle avoidance. Finally, in the stochastic ocean environment, deviations from the initial plan may occur, thus, an auction-based coordination tier drives online task coordination among AUVs in a distributed manner. Simulation experiments are conducted in multiple different scenarios to test the performance of the proposed planner, and the promising results show that the proposed method reduces AUV usage by 7.5% compared with the existing methods. When using the same number of AUVs, the fleet equipped with the proposed planner achieves a 6.2% improvement in average task completion rate

Motion-Scenario Decoupling for Rat-Aware Video Position Prediction: Strategy and Benchmark

Recently significant progress has been made in human action recognition and behavior prediction using deep learning techniques, leading to improved vision-based semantic understanding. However, there is still a lack of high-quality motion datasets for small bio-robotics, which presents more challenging scenarios for long-term movement prediction and behavior control based on third-person observation. In this study, we introduce RatPose, a bio-robot motion prediction dataset constructed by considering the influence factors of individuals and environments based on predefined annotation rules. To enhance the robustness of motion prediction against these factors, we propose a Dual-stream Motion-Scenario Decoupling (\textit{DMSD}) framework that effectively separates scenario-oriented and motion-oriented features and designs a scenario contrast loss and motion clustering loss for overall training. With such distinctive architecture, the dual-branch feature flow information is interacted and compensated in a decomposition-then-fusion manner. Moreover, we demonstrate significant performance improvements of the proposed \textit{DMSD} framework on different difficulty-level tasks. We also implement long-term discretized trajectory prediction tasks to verify the generalization ability of the proposed dataset.Comment: Rat, Video Position Predictio

Silicene Nanomesh

Similar to graphene, zero band gap limits the application of silicene in nanoelectronics despite of its high carrier mobility. By using first-principles calculations, we reveal that a band gap is opened in silicene nanomesh (SNM) when the width W of the wall between the neighboring holes is even. The size of the band gap increases with the reduced W and has a simple relation with the ratio of the removed Si atom and the total Si atom numbers of silicene. Quantum transport simulation reveals that the sub-10 nm single-gated SNM field effect transistors show excellent performance at zero temperature but such a performance is greatly degraded at room temperature