RELAX: Reinforcement Learning Enabled 2D-LiDAR Autonomous System for Parsimonious UAVs

Unmanned Aerial Vehicles (UAVs) have become increasingly prominence in recent years, finding applications in surveillance, package delivery, among many others. Despite considerable efforts in developing algorithms that enable UAVs to navigate through complex unknown environments autonomously, they often require expensive hardware and sensors, such as RGB-D cameras and 3D-LiDAR, leading to a persistent trade-off between performance and cost. To this end, we propose RELAX, a novel end-to-end autonomous framework that is exceptionally cost-efficient, requiring only a single 2D-LiDAR to enable UAVs operating in unknown environments. Specifically, RELAX comprises three components: a pre-processing map constructor; an offline mission planner; and a reinforcement learning (RL)-based online re-planner. Experiments demonstrate that RELAX offers more robust dynamic navigation compared to existing algorithms, while only costing a fraction of the others. The code will be made public upon acceptance

Transportation inequalities: From Poisson to Gibbs measures

We establish an optimal transportation inequality for the Poisson measure on the configuration space. Furthermore, under the Dobrushin uniqueness condition, we obtain a sharp transportation inequality for the Gibbs measure on $\mathbb{N}^{\Lambda}$ or the continuum Gibbs measure on the configuration space.Comment: Published in at http://dx.doi.org/10.3150/00-BEJ268 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Short O-O separation in layered oxide Na0.67CoO2 enables an ultrafast oxygen evolution reaction.

The layered oxide Na0.67CoO2 with Na+ occupying trigonal prismatic sites between CoO2 layers exhibits a remarkably high room temperature oxygen evolution reaction (OER) activity in alkaline solution. The high activity is attributed to an unusually short O-O separation that favors formation of peroxide ions by O--O- interactions followed by O2 evolution in preference to the conventional route through surface O-OH- species. The dependence of the onset potential on the pH of the alkaline solution was found to be consistent with the loss of H+ ions from the surface oxygen to provide surface O- that may either be attacked by solution OH- or react with another O-; a short O-O separation favors the latter route. The role of a strong hybridization of the O-2p and low-spin CoIII/CoIV π-bonding d states is also important; the OER on other CoIII/CoIV oxides is compared with that on Na0.67CoO2 as well as that on IrO2

MixFormerV2: Efficient Fully Transformer Tracking

Transformer-based trackers have achieved strong accuracy on the standard benchmarks. However, their efficiency remains an obstacle to practical deployment on both GPU and CPU platforms. In this paper, to overcome this issue, we propose a fully transformer tracking framework, coined as \emph{MixFormerV2}, without any dense convolutional operation and complex score prediction module. Our key design is to introduce four special prediction tokens and concatenate them with the tokens from target template and search areas. Then, we apply the unified transformer backbone on these mixed token sequence. These prediction tokens are able to capture the complex correlation between target template and search area via mixed attentions. Based on them, we can easily predict the tracking box and estimate its confidence score through simple MLP heads. To further improve the efficiency of MixFormerV2, we present a new distillation-based model reduction paradigm, including dense-to-sparse distillation and deep-to-shallow distillation. The former one aims to transfer knowledge from the dense-head based MixViT to our fully transformer tracker, while the latter one is used to prune some layers of the backbone. We instantiate two types of MixForemrV2, where the MixFormerV2-B achieves an AUC of 70.6\% on LaSOT and an AUC of 57.4\% on TNL2k with a high GPU speed of 165 FPS, and the MixFormerV2-S surpasses FEAR-L by 2.7\% AUC on LaSOT with a real-time CPU speed.Comment: NIPS202

Facile Preparation of Bimetallic MOF-derived Supported Tungstophosphoric Acid Composites for Biodiesel Production

In this work, the novel TPA@C-NiZr-MOF catalyst is synthesized by the impregnation of tungstophosphoric acid (TPA) on the NiZr-based metal-organic framework (NiZr-MOF) followed by calcination up to 300 °C. The as-prepared catalyst materials were structurally, morphologically, and texturally characterized by XRD, FTIR, temperature programmed desorption of NH3 ( TPD-NH3 ), N2 physisorption, SEM, TEM, and XPS. The prepared catalyst can be used as an efficient heterogeneous catalyst for biodiesel production from oleic acid (OA) with methanol. The results indicated that, in comparison to TPA@NiZr-MOF, the TPA@C-NiZr-MOF catalyst calcined at 300 °C exhibits excellent catalytic performance probably owing to the synergistic effect between TPA and metal oxide skeletons, high acidity, as well as larger surface area and pore size. Additionally, the TPA@C-NiZr-MOF catalyst can be reused in up to six cycles with an acceptable conversion. This study showed that the bimetallic MOF-derived composite materials can be used as an alternative potential heterogeneous catalyst toward biorefinery applications