Progress in Application of CNTs in Lithium-Ion Batteries

The lithium-ion battery is widely used in the fields of portable devices and electric cars with its superior performance and promising energy storage applications. The unique one-dimensional structure formed by the graphene layer makes carbon nanotubes possess excellent mechanical, electrical, and electrochemical properties and becomes a hot material in the research of lithium-ion battery. In this paper, the applicable research progress of carbon nanotubes in lithium-ion battery is described, and its future development is put forward from its two aspects of being not only the anodic conductive reinforcing material and the cathodic energy storage material but also the electrically conductive framework material

Enhancing Balanced Graph Edge Partition with Effective Local Search

Graph partition is a key component to achieve workload balance and reduce job completion time in parallel graph processing systems. Among the various partition strategies, edge partition has demonstrated more promising performance in power-law graphs than vertex partition and thereby has been more widely adopted as the default partition strategy by existing graph systems. The graph edge partition problem, which is to split the edge set into multiple balanced parts to minimize the total number of copied vertices, has been widely studied from the view of optimization and algorithms. In this paper, we study local search algorithms for this problem to further improve the partition results from existing methods. More specifically, we propose two novel concepts, namely adjustable edges and blocks. Based on these, we develop a greedy heuristic as well as an improved search algorithm utilizing the property of the max-flow model. To evaluate the performance of our algorithms, we first provide adequate theoretical analysis in terms of the approximation quality. We significantly improve the previously known approximation ratio for this problem. Then we conduct extensive experiments on a large number of benchmark datasets and state-of-the-art edge partition strategies. The results show that our proposed local search framework can further improve the quality of graph partition by a wide margin.Comment: To appear in AAAI 202

Structural optimization and biological evaluation of 1,5-disubstituted pyrazole-3-carboxamines as potent inhibitors of human 5-lipoxygenase

AbstractHuman 5-lipoxygenase (5-LOX) is a well-validated drug target and its inhibitors are potential drugs for treating leukotriene-related disorders. Our previous work on structural optimization of the hit compound 2 from our in-house collection identified two lead compounds, 3a and 3b, exhibiting a potent inhibitory profile against 5-LOX with IC50 values less than 1µmol/L in cell-based assays. Here, we further optimized these compounds to prepare a class of novel pyrazole derivatives by opening the fused-ring system. Several new compounds exhibited more potent inhibitory activity than the lead compounds against 5-LOX. In particular, compound 4e not only suppressed lipopolysaccharide-induced inflammation in brain inflammatory cells and protected neurons from oxidative toxicity, but also significantly decreased infarct damage in a mouse model of cerebral ischemia. Molecular docking analysis further confirmed the consistency of our theoretical results and experimental data. In conclusion, the excellent in vitro and in vivo inhibitory activities of these compounds against 5-LOX suggested that these novel chemical structures have a promising therapeutic potential to treat leukotriene-related disorders

Robust Visual Compass Using Hybrid Features for Indoor Environments

Orientation estimation is a crucial part of robotics tasks such as motion control, autonomous navigation, and 3D mapping. In this paper, we propose a robust visual-based method to estimate robots’ drift-free orientation with RGB-D cameras. First, we detect and track hybrid features (i.e., plane, line, and point) from color and depth images, which provides reliable constraints even in uncharacteristic environments with low texture or no consistent lines. Then, we construct a cost function based on these features and, by minimizing this function, we obtain the accurate rotation matrix of each captured frame with respect to its reference keyframe. Furthermore, we present a vanishing direction-estimation method to extract the Manhattan World (MW) axes; by aligning the current MW axes with the global MW axes, we refine the aforementioned rotation matrix of each keyframe and achieve drift-free orientation. Experiments on public RGB-D datasets demonstrate the robustness and accuracy of the proposed algorithm for orientation estimation. In addition, we have applied our proposed visual compass to pose estimation, and the evaluation on public sequences shows improved accuracy