Porous materials possessing high surface area, large pore volume, tunable pore structure, superior tailorability, and dimensional effect have been widely applied as components of lithium–oxygen ...(Li–O2) batteries. Herein, the theoretical foundation of the porous materials applied in Li–O2 batteries is provided, based on the present understanding of the battery mechanism and the challenges and advantageous qualities of porous materials. Furthermore, recent progress in porous materials applied as the cathode, anode, separator, and electrolyte in Li–O2 batteries is summarized, together with corresponding approaches to address the critical issues that remain at present. Particular emphasis is placed on the importance of the correlation between the function‐orientated design of porous materials and key challenges of Li–O2 batteries in accelerating oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) kinetics, improving the electrode stability, controlling lithium deposition, suppressing the shuttle effect of the dissolved redox mediators, and alleviating electrolyte decomposition. Finally, the rational design and innovative directions of porous materials are provided for their development and application in Li–O2 battery systems.
The application of nonaqueous Li–O2 batteries is limited by challenges from the cathode, anode, separator, and electrolyte. The perspectives of porous materials for Li–O2 batteries are outlined, the advances of porous materials for targeting critical battery challenges are highlighted, and rational design and future directions of porous‐materials‐based Li–O2 battery systems are suggested.
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2.
Global Contrast Based Salient Region Detection Cheng, Ming-Ming; Mitra, Niloy J.; Huang, Xiaolei ...
IEEE transactions on pattern analysis and machine intelligence,
2015-March-1, 2015-Mar, 2015-3-1, 20150301, Volume:
37, Issue:
3
Journal Article
Peer reviewed
Open access
Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer ...graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.
Double role: A traceless directing group also acts as an internal oxidant in a novel RhIII‐catalyzed protocol developed for the synthesis of ortho‐alkenylated tertiary anilines (see scheme). A ...five‐membered cyclometalated RhIII complex is proposed as a plausible intermediate and confirmed by X‐ray crystallographic analysis.
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Soft scales (Hemiptera: Coccidae), including important agricultural and forestry pests, are difficult to identify directly by morphological characters. Mitochondrial genomes (mitogenomes) have been ...widely used in species identification and phylogenetic research. However, only three complete mitogenomes, and very few mitochondrial genes of scale insects (Hemiptera: Coccoidea) can be searched in GenBank. Mitogenome comparisons between scale insects or between scale insects and other hemipteran species have not yet been reported.
In this study, detailed annotation of three new mitogenomes and comparative analysis of scale insects were completed, as well as comparative analysis of the gene composition, gene arrangement, codon usage and evolutionary forces between scale insects and 488 other hemipteran species for the first time. We found that high A + T content, gene rearrangement and truncated tRNAs are common phenomena in soft scales. The average A + T content and codon usage bias of scale insects are higher and stronger than those of other hemipteran insects, respectively. The atp8 gene of Hemiptera and nine other protein-coding genes of scale insects are under positive selection with higher evolutionary rates.
The study revealed the particularity of the scale insect mitogenomes, which will provide a good reference for future research on insect phylogenetic relationships, insect pest control, biogeography and identification.
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We present a novel, variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher-dimensional space of distance transforms. In this implicit ...embedding space, registration is formulated in a hierarchical manner: the mutual information criterion supports various transformation models and is optimized to perform global registration; then, a B-spline-based incremental free form deformations (IFFD) model is used to minimize a sum-of-squared-differences (SSD) measure and further recover a dense local nonrigid registration field. The key advantage of such framework is twofold: 1) it naturally deals with shapes of arbitrary dimension (2D, 3D, or higher) and arbitrary topology (multiple parts, closed/open) and 2) it preserves shape topology during local deformation and produces local registration fields that are smooth, continuous, and establish one-to-one correspondences. Its invariance to initial conditions is evaluated through empirical validation, and various hard 2D/3D geometric shape registration examples are used to show its robustness to noise, severe occlusion, and missing parts. We demonstrate the power of the proposed framework using two applications: one for statistical modeling of anatomical structures, another for 3D face scan registration and expression tracking. We also compare the performance of our algorithm with that of several other well-known shape registration algorithms
The first example of cobalt‐catalyzed oxidative C−H/C−H cross‐coupling between two heteroarenes is reported, which exhibits a broad substrate scope and a high tolerance level for sensitive functional ...groups. When the amount of Co(OAc)2⋅4 H2O is reduced from 6.0 to 0.5 mol %, an excellent yield is still obtained at an elevated temperature with a prolonged reaction time. The method can be extended to the reaction between an arene and a heteroarene. It is worth noting that the Ag2CO3 oxidant is renewable. Preliminary mechanistic studies by radical trapping experiments, hydrogen/deuterium exchange experiments, kinetic isotope effect, electron paramagnetic resonance (EPR), and high resolution mass spectrometry (HRMS) suggest that a single electron transfer (SET) pathway is operative, which is distinctly different from the dual C−H bond activation pathway that the well‐described oxidative C−H/C−H cross‐coupling reactions between two heteroarenes typically undergo.
A bidentate 8‐quinolinyl ligand assists the cobalt‐catalyzed title reaction between two (hetero)arenes exhibiting a broad substrate scope and a high tolerance level for sensitive functional groups. The preliminary mechanistic study suggests that a single electron transfer pathway is operative.
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Although promising results have been achieved in the areas of traffic-sign detection and classification, few works have provided simultaneous solutions to these two tasks for realistic real world ...images. We make two contributions to this problem. Firstly, we have created a large traffic-sign benchmark from 100000 Tencent Street View panoramas, going beyond previous benchmarks. It provides 100000 images containing 30000 traffic-sign instances. These images cover large variations in illuminance and weather conditions. Each traffic-sign in the benchmark is annotated with a class label, its bounding box and pixel mask. We call this benchmark Tsinghua-Tencent 100K. Secondly, we demonstrate how a robust end-to-end convolutional neural network (CNN) can simultaneously detect and classify trafficsigns. Most previous CNN image processing solutions target objects that occupy a large proportion of an image, and such networks do not work well for target objects occupying only a small fraction of an image like the traffic-signs here. Experimental results show the robustness of our network and its superiority to alternatives. The benchmark, source code and the CNN model introduced in this paper is publicly available1.
Most convolutional neural networks (CNNs) lack midlevel layers that model semantic parts of objects. This limits CNN-based methods from reaching their full potential in detecting and utilizing small ...semantic parts in recognition. Introducing such mid-level layers can facilitate the extraction of part-specific features which can be utilized for better recognition performance. This is particularly important in the domain of fine-grained recognition. In this paper, we propose a new CNN architecture that integrates semantic part detection and abstraction (SPDACNN) for fine-grained classification. The proposed network has two sub-networks: one for detection and one for recognition. The detection sub-network has a novel top-down proposal method to generate small semantic part candidates for detection. The classification sub-network introduces novel part layers that extract features from parts detected by the detection sub-network, and combine them for recognition. As a result, the proposed architecture provides an end-to-end network that performs detection, localization of multiple semantic parts, and whole object recognition within one framework that shares the computation of convolutional filters. Our method outperforms state-of-theart methods with a large margin for small parts detection (e.g. our precision of 93.40% vs the best previous precision of 74.00% for detecting the head on CUB-2011). It also compares favorably to the existing state-of-the-art on finegrained classification, e.g. it achieves 85.14% accuracy on CUB-2011.
A Ru-catalyzed intermolecular silylation of unreactive, aliphatic C(sp3)–H bonds has been described for the first time. This protocol features low catalyst loading, a relatively broad substrate ...spectrum, good functional group tolerance, and no sensitivity to air, which provides a convenient and practical pathway for the construction of C–Si bonds.
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