Showing papers by "South China University of Technology published in 2019"

Deep High-Resolution Representation Learning for Visual Recognition

Abstract: High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that is formed by connecting high-to-low resolution convolutions \emph{in series} (e.g., ResNet, VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation. Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representations through the whole process. There are two key characteristics: (i) Connect the high-to-low resolution convolution streams \emph{in parallel}; (ii) Repeatedly exchange the information across resolutions. The benefit is that the resulting representation is semantically richer and spatially more precise. We show the superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, suggesting that the HRNet is a stronger backbone for computer vision problems. All the codes are available at~{\url{this https URL}}.

Engineering bunched Pt-Ni alloy nanocages for efficient oxygen reduction in practical fuel cells

Abstract: Development of efficient and robust electrocatalysts is critical for practical fuel cells. We report one-dimensional bunched platinum-nickel (Pt-Ni) alloy nanocages with a Pt-skin structure for the oxygen reduction reaction that display high mass activity (3.52 amperes per milligram platinum) and specific activity (5.16 milliamperes per square centimeter platinum), or nearly 17 and 14 times higher as compared with a commercial platinum on carbon (Pt/C) catalyst. The catalyst exhibits high stability with negligible activity decay after 50,000 cycles. Both the experimental results and theoretical calculations reveal the existence of fewer strongly bonded platinum-oxygen (Pt-O) sites induced by the strain and ligand effects. Moreover, the fuel cell assembled by this catalyst delivers a current density of 1.5 amperes per square centimeter at 0.6 volts and can operate steadily for at least 180 hours.

Achieving over 16% efficiency for single-junction organic solar cells

Abstract: To achieve high photovoltaic performance of bulk hetero-junction organic solar cells (OSCs), a range of critical factors including absorption profiles, energy level alignment, charge carrier mobility and miscibility of donor and acceptor materials should be carefully considered. For electron-donating materials, the deep highest occupied molecular orbital (HOMO) energy level that is beneficial for high open-circuit voltage is much appreciated. However, a new issue in charge transfer emerges when matching such a donor with an acceptor that has a shallower HOMO energy level. More to this point, the chemical strategies used to enhance the absorption coefficient of acceptors may lead to increased molecular crystallinity, and thus result in less controllable phase-separation of photoactive layer. Therefore, to realize balanced photovoltaic parameters, the donor-acceptor combinations should simultaneously address the absorption spectra, energy levels, and film morphologies. Here, we selected two non-fullerene acceptors, namely BTPT-4F and BTPTT-4F, to match with a wide-bandgap polymer donor P2F-EHp consisting of an imide-functionalized benzotriazole moiety, as these materials presented complementary absorption and well-matched energy levels. By delicately optimizing the blend film morphology, we demonstrated an unprecedented power conversion efficiency of over 16% for the device based on P2F-EHp:BTPTT-4F, suggesting the great promise of materials matching toward high-performance OSCs.

LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking

Abstract: In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame in these sequences is carefully and manually annotated with a bounding box, making LaSOT the largest, to the best of our knowledge, densely annotated tracking benchmark. The average video length of LaSOT is more than 2,500 frames, and each sequence comprises various challenges deriving from the wild where target objects may disappear and re-appear again in the view. By releasing LaSOT, we expect to provide the community with a large-scale dedicated benchmark with high quality for both the training of deep trackers and the veritable evaluation of tracking algorithms. Moreover, considering the close connections of visual appearance and natural language, we enrich LaSOT by providing additional language specification, aiming at encouraging the exploration of natural linguistic feature for tracking. A thorough experimental evaluation of 35 tracking algorithms on LaSOT is presented with detailed analysis, and the results demonstrate that there is still a big room for improvements.

The sixth visual object tracking VOT2018 challenge results

Abstract: The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).

In situ sprayed bioresponsive immunotherapeutic gel for post-surgical cancer treatment

Abstract: Cancer recurrence after surgical resection remains a significant cause of treatment failure. Here, we have developed an in situ formed immunotherapeutic bioresponsive gel that controls both local tumour recurrence after surgery and development of distant tumours. Briefly, calcium carbonate nanoparticles pre-loaded with the anti-CD47 antibody are encapsulated in the fibrin gel and scavenge H+ in the surgical wound, allowing polarization of tumour-associated macrophages to the M1-like phenotype. The released anti-CD47 antibody blocks the ‘don’t eat me’ signal in cancer cells, thereby increasing phagocytosis of cancer cells by macrophages. Macrophages can promote effective antigen presentation and initiate T cell mediated immune responses that control tumour growth. Our findings indicate that the immunotherapeutic fibrin gel ‘awakens’ the host innate and adaptive immune systems to inhibit both local tumour recurrence post surgery and potential metastatic spread. A gel with therapeutic nanoformulation that can be sprayed at the tumour resection site after surgery activates immune response in the tissue microenviroment, inhibiting tumour recurrence and potential metastasis.

Plant-inspired adhesive and tough hydrogel based on Ag-Lignin nanoparticles-triggered dynamic redox catechol chemistry

Abstract: Adhesive hydrogels have gained popularity in biomedical applications, however, traditional adhesive hydrogels often exhibit short-term adhesiveness, poor mechanical properties and lack of antibacterial ability. Here, a plant-inspired adhesive hydrogel has been developed based on Ag-Lignin nanoparticles (NPs)triggered dynamic redox catechol chemistry. Ag-Lignin NPs construct the dynamic catechol redox system, which creates long-lasting reductive-oxidative environment inner hydrogel networks. This redox system, generating catechol groups continuously, endows the hydrogel with long-term and repeatable adhesiveness. Furthermore, Ag-Lignin NPs generate free radicals and trigger self-gelation of the hydrogel under ambient environment. This hydrogel presents high toughness for the existence of covalent and non-covalent interaction in the hydrogel networks. The hydrogel also possesses good cell affinity and high antibacterial activity due to the catechol groups and bactericidal ability of Ag-Lignin NPs. This study proposes a strategy to design tough and adhesive hydrogels based on dynamic plant catechol chemistry.

Aggregation-induced emission: fundamental understanding and future developments

Abstract: Since the introduction of the concept of aggregation-induced emission (AIE) in 2001, many research groups have become involved in AIE research. Aggregation-induced emission luminogens (AIEgens) have emerged as a novel type of advanced material with excellent performance in various fields. Much effort has been devoted to determining the AIE mechanism(s) by theoreticians and experimentalists. Restriction of intramolecular motion has been recognized as the general working mechanism of AIE, but the mechanims of some AIE systems still remain unclear. In this focus article, the progress of the fundamental understanding of the AIE mechanism is reviewed and the future developments in AIE research are discussed. The goal is to provide a brief yet insightful introduction and interpretation of the subject to both new and experienced AIE researchers.

Graph Convolutional Networks for Temporal Action Localization

Abstract: Most state-of-the-art action localization systems process each action proposal individually, without explicitly exploiting their relations during learning. However, the relations between proposals actually play an important role in action localization, since a meaningful action always consists of multiple proposals in a video. In this paper, we propose to exploit the proposal-proposal relations using GraphConvolutional Networks (GCNs). First, we construct an action proposal graph, where each proposal is represented as a node and their relations between two proposals as an edge. Here, we use two types of relations, one for capturing the context information for each proposal and the other one for characterizing the correlations between distinct actions. Then we apply the GCNs over the graph to model the relations among different proposals and learn powerful representations for the action classification and localization. Experimental results show that our approach significantly outperforms the state-of-the-art on THUMOS14(49.1% versus 42.8%). Moreover, augmentation experiments on ActivityNet also verify the efficacy of modeling action proposal relationships.

Structural Design and Electronic Modulation of Transition-Metal-Carbide Electrocatalysts toward Efficient Hydrogen Evolution.

Abstract: As the key of hydrogen economy, electrocatalytic hydrogen evolution reactions (HERs) depend on the availability of cost-efficient electrocatalysts. Over the past years, there is a rapid rise in noble-metal-free electrocatalysts. Among them, transition metal carbides (TMCs) are highlighted due to their structural and electronic merits, e.g., high conductivity, metallic band states, tunable surface/bulk architectures, etc. Herein, representative efforts and progress made on TMCs are comprehensively reviewed, focusing on the noble-metal-like electronic configuration and the relevant structural/electronic modulation. Briefly, specific nanostructures and carbon-based hybrids are introduced to increase active-site abundance and to promote mass transportation, and heteroatom doping and heterointerface engineering are encouraged to optimize the chemical configurations of active sites toward intrinsically boosted HER kinetics. Finally, a perspective on the future development of TMC electrocatalysts is offered. The overall aim is to shed some light on the exploration of emerging materials in energy chemistry.

UAV-Assisted Emergency Networks in Disasters

Abstract: Reliable and flexible emergency communication is a key challenge for search and rescue in the event of disasters, especially for the case when base stations are no longer functioning. Unmanned aerial vehicle (UAV)-assisted networking is emerging as a promising method to establish emergency networks. In this article, a unified framework for a UAV-assisted emergency network is established in disasters. First, the trajectory and scheduling of UAVs are jointly optimized to provide wireless service to ground devices with surviving BSs. Then the transceiver design of UAV and establishment of multihop ground device-to-device communication are studied to extend the wireless coverage of UAV. In addition, multihop UAV relaying is added to realize information exchange between the disaster areas and outside through optimizing the hovering positions of UAVs. Simulation results are presented to show the effectiveness of these three schemes. Finally, open research issues and challenges are discussed.

Ammonia Synthesis Under Ambient Conditions: Selective Electroreduction of Dinitrogen to Ammonia on Black Phosphorus Nanosheets.

Abstract: Constructing efficient catalysts for the N2 reduction reaction (NRR) is a major challenge for artificial nitrogen fixation under ambient conditions. Herein, inspired by the principle of "like dissolves like", it is demonstrated that a member of the nitrogen family, well-exfoliated few-layer black phosphorus nanosheets (FL-BP NSs), can be used as an efficient nonmetallic catalyst for electrochemical nitrogen reduction. The catalyst can achieve a high ammonia yield of 31.37 μg h-1 mg-1 cat. under ambient conditions. Density functional theory calculations reveal that the active orbital and electrons of zigzag and diff-zigzag type edges of FL-BP NSs enable selective electrocatalysis of N2 to NH3 via an alternating hydrogenation pathway. This work proves the feasibility of using a nonmetallic simple substance as a nitrogen-fixing catalyst and thus opening a new avenue towards the development of more efficient metal-free catalysts.

An Isolated Zinc–Cobalt Atomic Pair for Highly Active and Durable Oxygen Reduction

Abstract: A competitive complexation strategy has been developed to construct a novel electrocatalyst with Zn-Co atomic pairs coordinated on N doped carbon support (Zn/CoN-C). Such architecture offers enhanced binding ability of O2 , significantly elongates the O-O length (from 1.23 A to 1.42 A), and thus facilitates the cleavage of O-O bond, showing a theoretical overpotential of 0.335 V during ORR process. As a result, the Zn/CoN-C catalyst exhibits outstanding ORR performance in both alkaline and acid conditions with a half-wave potential of 0.861 and 0.796 V respectively. The in situ XANES analysis suggests Co as the active center during the ORR. The assembled zinc-air battery with Zn/CoN-C as cathode catalyst presents a maximum power density of 230 mW cm-2 along with excellent operation durability. The excellent catalytic activity in acid is also verified by H2 /O2 fuel cell tests (peak power density of 705 mW cm-2 ).

Nature-inspired salt resistant bimodal porous solar evaporator for efficient and stable water desalination

Abstract: The shortage of clean water is one of the predominant causes of human mortality, especially in remote rural areas. Currently, solar steam generation is being adopted as an efficient, sustainable, and low-cost means for water desalination to produce clean water. However, preventing salt accumulation during operation while maintaining long-term stability and a rapid evaporation rate is a critical challenge that needs to be urgently addressed to further facilitate the practical applications of solar desalination, especially for desalinating high-salinity brine. Here, we demonstrate that a bimodal porous structure (e.g., balsa wood) can serve as an efficient and stable solar vapor generator for high-salinity brine desalination. Taking advantage of the inherent bimodal porous and interconnected microstructures of balsa wood, rapid capillary transport through the microchannels and efficient transport between the micro- and macrochannels through ray cells and pits in the bimodal evaporator can lead to quick replenishment of surface vaporized brine to ensure fast and continuous clean water vapor generation. The bimodal evaporator demonstrates a rapid evaporation rate of 6.4 kg m−2 h−1 under 6 suns irradiation and outstanding long-term stability for desalination of high salinity brine. The large vessel channels play a critical role in preventing salt from accumulating, as evidenced by controlled experiments with large vessels either blocked in the bimodal evaporator (balsa evaporator) or absent in a unimodal evaporator (e.g., cedar wood) whose porous structure occurs naturally without large vessels. Both approaches demonstrate severe salt accumulation during solar desalination due to a lack of sufficient brine replenishment from the bulk solution beneath. With its unique bimodal porous and interconnected microstructure configuration obtained by a facile and scalable fabrication method, our bimodal porous structured evaporator device represents an efficient, stable, low-cost, and environmentally friendly solar vapor generator for high-salinity brine desalination.

Molecular Motion in Aggregates: Manipulating TICT for Boosting Photothermal Theranostics

Abstract: Planar donor and acceptor (D–A) conjugated structures are generally believed to be the standard for architecting highly efficient photothermal theranostic agents, in order to restrict intramolecular motions in aggregates (nanoparticles). However, other channels of extra nonradiative decay may be blocked. Now this challenge is addressed by proposing an “abnormal” strategy based on molecular motion in aggregates. Molecular rotors and bulky alkyl chains are grafted to the central D–A core to lower intermolecular interaction. The enhanced molecular motion favors the formation of a dark twisted intramolecular charge transfer state, whose nonradiative decay enhances the photothermal properties. Result shows that small-molecule NIRb14 with long alkyl chains branched at the second carbon exhibits enhanced photothermal properties compared with NIRb6, with short branched chains, and much higher than NIR6, with short linear chains, and the commercial gold nanorods. Both in vitro and in vivo experiments demonstrate t...

Modulation of recombination zone position for quasi-two-dimensional blue perovskite light-emitting diodes with efficiency exceeding 5

Abstract: In recent years, substantial progress has been made in developing perovskite light-emitting diodes with near-infrared, red and green emissions and over 20% external quantum efficiency. However, the development of perovskite light-emitting diodes with blue emission remains a great challenge, which retards further development of full-color displays and white-light illumination based on perovskite emissive materials. Here, firstly, through composition and dimensional engineering, we prepare quasi-two-dimensional perovskite thin films with improved blue emission, taking advantages of reduced trap density and enhanced photoluminescence quantum yield. Secondly, we find a vertically non-uniform distribution of perovskite crystals in the PEDOT:PSS/perovskite hybrid film. Through modulating the position of the recombination zone, we activate the majority of quasi-two-dimensional perovskite crystals, and thus demonstrate the most efficient blue perovskite light-emitting diode to date with emission peak at 480 nm, record luminance of 3780 cd m−2 and record external quantum efficiency of 5.7%. Halide perovskite based light-emitting diodes attracted intensive research interest recently but the efficiency of blue diodes is much lower than the green and red ones. Here Li et al. push up the efficiency of blue diodes through composition engineering and vertical morphology control.

Edge Computing for Autonomous Driving: Opportunities and Challenges

Abstract: Safety is the most important requirement for autonomous vehicles; hence, the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety of autonomous vehicles. Specifically, autonomous driving systems are extremely complex; they tightly integrate many technologies, including sensing, localization, perception, decision making, as well as the smooth interactions with cloud platforms for high-definition (HD) map generation and data storage. These complexities impose numerous challenges for the design of autonomous driving edge computing systems. First, edge computing systems for autonomous driving need to process an enormous amount of data in real time, and often the incoming data from different sensors are highly heterogeneous. Since autonomous driving edge computing systems are mobile, they often have very strict energy consumption restrictions. Thus, it is imperative to deliver sufficient computing power with reasonable energy consumption, to guarantee the safety of autonomous vehicles, even at high speed. Second, in addition to the edge system design, vehicle-to-everything (V2X) provides redundancy for autonomous driving workloads and alleviates stringent performance and energy constraints on the edge side. With V2X, more research is required to define how vehicles cooperate with each other and the infrastructure. Last, safety cannot be guaranteed when security is compromised. Thus, protecting autonomous driving edge computing systems against attacks at different layers of the sensing and computing stack is of paramount concern. In this paper, we review state-of-the-art approaches in these areas as well as explore potential solutions to address these challenges.

1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses.

Abstract: Reference genomes are essential for metagenomic analyses and functional characterization of the human gut microbiota. We present the Culturable Genome Reference (CGR), a collection of 1,520 nonredundant, high-quality draft genomes generated from >6,000 bacteria cultivated from fecal samples of healthy humans. Of the 1,520 genomes, which were chosen to cover all major bacterial phyla and genera in the human gut, 264 are not represented in existing reference genome catalogs. We show that this increase in the number of reference bacterial genomes improves the rate of mapping metagenomic sequencing reads from 50% to >70%, enabling higher-resolution descriptions of the human gut microbiome. We use the CGR genomes to annotate functions of 338 bacterial species, showing the utility of this resource for functional studies. We also carry out a pan-genome analysis of 38 important human gut species, which reveals the diversity and specificity of functional enrichment between their core and dispensable genomes.

Emerging ultra-narrow-band cyan-emitting phosphor for white LEDs with enhanced color rendition.

Abstract: Phosphor-converted white LEDs rely on combining a blue-emitting InGaN chip with yellow and red-emitting luminescent materials. The discovery of cyan-emitting (470–500 nm) phosphors is a challenge to compensate for the spectral gap and produce full-spectrum white light. Na0.5K0.5Li3SiO4:Eu2+ (NKLSO:Eu2+) phosphor was developed with impressive properties, providing cyan emission at 486 nm with a narrow full width at half maximum (FWHM) of only 20.7 nm, and good thermal stability with an integrated emission loss of only 7% at 150 °C. The ultra-narrow-band cyan emission results from the high-symmetry cation sites, leading to almost ideal cubic coordination for UCr4C4-type compounds. NKLSO:Eu2+ phosphor allows the valley between the blue and yellow emission peaks in the white LED device to be filled, and the color-rendering index can be enhanced from 86 to 95.2, suggesting great applications in full-spectrum white LEDs. Luminescent crystals that efficiently emit light in the narrow cyan color wavelength range, from 470 to 500 nanometers, could be used to fill a gap or “valley” in light-emitting diodes (LEDs) intended to mimic the full spectrum of daylight. There is great interest in developing more efficient and cost-effective full daylight spectrum LED lighting sources. These can create more natural indoor lighting conditions that are also believed to be more beneficial for health. Researchers in China and Russia, led by Zhiguo Xia at the University of Science and Technology Beijing, developed a suitable inorganic crystalline compound showing narrow cyan emission, with the formula Na0.5K0.5Li3SiO4:Eu2+. The many possible applications include LEDs for daylight spectrum lamps used to treat the low mood and depression associated with Seasonal Affective Disorder (SAD).

Divalent europium-doped near-infrared-emitting phosphor for light-emitting diodes

Abstract: Near-infrared luminescent materials exhibit unique photophysical properties that make them crucial components in photonic, optoelectronic and biological applications. As broadband near infrared phosphors activated by transition metal elements are already widely reported, there is a challenge for next-generation materials discovery by introducing rare earth activators with 4f-5d transition. Here, we report an unprecedented phosphor K3LuSi2O7:Eu2+ that gives an emission band centered at 740 nm with a full-width at half maximum of 160 nm upon 460 nm blue light excitation. Combined structural and spectral characterizations reveal a selective site occupation of divalent europium in LuO6 and K2O6 polyhedrons with small coordination numbers, leading to the unexpected near infrared emission. The fabricated phosphor-converted light-emitting diodes have great potential as a non-visible light source. Our work provides the design principle of near infrared emission in divalent europium-doped inorganic solid-state materials and could inspire future studies to further explore near-infrared light-emitting diodes. Here the authors report a near-infrared K3LuSi2O7:Eu2+ phosphor for non-visible light source application. The selective site occupation of Eu2+ in LuO6 and K2O6 polyhedrons is found to be responsible for the light emission and these insights could serve as design principles for discovery and design of such phosphors.