Showing papers by "Xi'an Jiaotong University published in 2019"

Bag of Tricks and a Strong Baseline for Deep Person Re-Identification

Abstract: This paper explores a simple and efficient baseline for person re-identification (ReID). Person re-identification (ReID) with deep neural networks has made progress and achieved high performance in recent years. However, many state-of-the-arts methods design complex network structure and concatenate multi-branch features. In the literature, some effective training tricks are briefly appeared in several papers or source codes. This paper will collect and evaluate these effective training tricks in person ReID. By combining these tricks together, the model achieves 94.5% rank-1 and 85.9% mAP on Market1501 with only using global features. Our codes and models are available at https://github.com/michuanhaohao/reid-strong-baseline.

Quantifying the triboelectric series.

Abstract: Triboelectrification is a well-known phenomenon that commonly occurs in nature and in our lives at any time and any place. Although each and every material exhibits triboelectrification, its quantification has not been standardized. A triboelectric series has been qualitatively ranked with regards to triboelectric polarization. Here, we introduce a universal standard method to quantify the triboelectric series for a wide range of polymers, establishing quantitative triboelectrification as a fundamental materials property. By measuring the tested materials with a liquid metal in an environment under well-defined conditions, the proposed method standardizes the experimental set up for uniformly quantifying the surface triboelectrification of general materials. The normalized triboelectric charge density is derived to reveal the intrinsic character of polymers for gaining or losing electrons. This quantitative triboelectric series may serve as a textbook standard for implementing the application of triboelectrification for energy harvesting and self-powered sensing.

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data

Abstract: The success of intelligent fault diagnosis of machines relies on the following two conditions: 1) labeled data with fault information are available; and 2) the training and testing data are drawn from the same probability distribution. However, for some machines, it is difficult to obtain massive labeled data. Moreover, even though labeled data can be obtained from some machines, the intelligent fault diagnosis method trained with such labeled data possibly fails in classifying unlabeled data acquired from the other machines due to data distribution discrepancy. These problems limit the successful applications of intelligent fault diagnosis of machines with unlabeled data. As a potential tool, transfer learning adapts a model trained in a source domain to its application in a target domain. Based on the transfer learning, we propose a new intelligent method named deep convolutional transfer learning network (DCTLN). A DCTLN consists of two modules: condition recognition and domain adaptation. The condition recognition module is constructed by a one-dimensional (1-D) convolutional neural network (CNN) to automatically learn features and recognize health conditions of machines. The domain adaptation module facilitates the 1-D CNN to learn domain-invariant features by maximizing domain recognition errors and minimizing the probability distribution distance. The effectiveness of the proposed method is verified using six transfer fault diagnosis experiments.

Adhesive Hemostatic Conducting Injectable Composite Hydrogels with Sustained Drug Release and Photothermal Antibacterial Activity to Promote Full-Thickness Skin Regeneration During Wound Healing

Abstract: Developing injectable nanocomposite conductive hydrogel dressings with multifunctions including adhesiveness, antibacterial, and radical scavenging ability and good mechanical property to enhance full-thickness skin wound regeneration is highly desirable in clinical application. Herein, a series of adhesive hemostatic antioxidant conductive photothermal antibacterial hydrogels based on hyaluronic acid-graft-dopamine and reduced graphene oxide (rGO) using a H2 O2 /HPR (horseradish peroxidase) system are prepared for wound dressing. These hydrogels exhibit high swelling, degradability, tunable rheological property, and similar or superior mechanical properties to human skin. The polydopamine endowed antioxidant activity, tissue adhesiveness and hemostatic ability, self-healing ability, conductivity, and NIR irradiation enhanced in vivo antibacterial behavior of the hydrogels are investigated. Moreover, drug release and zone of inhibition tests confirm sustained drug release capacity of the hydrogels. Furthermore, the hydrogel dressings significantly enhance vascularization by upregulating growth factor expression of CD31 and improve the granulation tissue thickness and collagen deposition, all of which promote wound closure and contribute to a better therapeutic effect than the commercial Tegaderm films group in a mouse full-thickness wounds model. In summary, these adhesive hemostatic antioxidative conductive hydrogels with sustained drug release property to promote complete skin regeneration are an excellent wound dressing for full-thickness skin repair.

Semiconductor polymeric graphitic carbon nitride photocatalysts: the “holy grail” for the photocatalytic hydrogen evolution reaction under visible light

Abstract: Semiconductor polymeric graphitic carbon nitride (g-C3N4) photocatalysts have attracted dramatically growing attention in the field of the visible-light-induced hydrogen evolution reaction (HER) because of their facile synthesis, easy functionalization, attractive electronic band structure, high physicochemical stability and photocatalytic activity. This review article presents a panorama of the latest advancements in the rational design and development of g-C3N4 and g-C3N4-based composite photocatalysts for HER application. Concretely, the review starts with the development history, synthetic strategy, electronic structure and physicochemical characteristics of g-C3N4 materials, followed by the rational design and engineering of various nanostructured g-C3N4 (e.g. thinner, highly crystalline, doped, and porous g-C3N4) photocatalysts for HER application. Then a series of highly efficient g-C3N4 (e.g., metal/g-C3N4, semiconductor/g-C3N4, metal organic framework/g-C3N4, carbon/g-C3N4, conducting polymer/g-C3N4, sensitizer/g-C3N4) composite photocatalysts are exemplified. Lastly, this review provides a comprehensive summary and outlook on the major challenges, opportunities, and inspiring perspectives for future research in this hot area on the basis of pioneering works. It is believed that the emerging g-C3N4-based photocatalysts will act as the “holy grail” for highly efficient photocatalytic HER under visible-light irradiation.

Engineering the electronic structure of single atom Ru sites via compressive strain boosts acidic water oxidation electrocatalysis

Abstract: Single-atom precious metal catalysts hold the promise of perfect atom utilization, yet control of their activity and stability remains challenging. Here we show that engineering the electronic structure of atomically dispersed Ru1 on metal supports via compressive strain boosts the kinetically sluggish electrocatalytic oxygen evolution reaction (OER), and mitigates the degradation of Ru-based electrocatalysts in an acidic electrolyte. We construct a series of alloy-supported Ru1 using different PtCu alloys through sequential acid etching and electrochemical leaching, and find a volcano relation between OER activity and the lattice constant of the PtCu alloys. Our best catalyst, Ru1–Pt3Cu, delivers 90 mV lower overpotential to reach a current density of 10 mA cm−2, and an order of magnitude longer lifetime over that of commercial RuO2. Density functional theory investigations reveal that the compressive strain of the Ptskin shell engineers the electronic structure of the Ru1, allowing optimized binding of oxygen species and better resistance to over-oxidation and dissolution. While Ru-based electrocatalysts are among the most active for acidic water oxidation, they suffer from severe deactivation. Now, Yuen Wu, Wei-Xue Li and co-workers report a core–shell Ru1–Pt3Cu catalyst with surface-dispersed Ru atoms for a highly active and stable oxygen evolution reaction in acid electrolyte.

PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files.

Abstract: Motivation Linkage disequilibrium (LD) decay is of great interest in population genetic studies. However, no tool is available now to do LD decay analysis from variant call format (VCF) files directly. In addition, generation of pair-wise LD measurements for whole genome SNPs usually resulting in large storage wasting files. Results We developed PopLDdecay, an open source software, for LD decay analysis from VCF files. It is fast and is able to handle large number of variants from sequencing data. It is also storage saving by avoiding exporting pair-wise results of LD measurements. Subgroup analyses are also supported. Availability and implementation PopLDdecay is freely available at https://github.com/BGI-shenzhen/PopLDdecay.

Multi-platform discovery of haplotype-resolved structural variation in human genomes

Abstract: The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes.

Abstract: Regional severe haze represents an enormous environmental problem in China, influencing air quality, human health, ecosystem, weather, and climate. These extremes are characterized by exceedingly high concentrations of fine particulate matter (smaller than 2.5 µm, or PM2.5) and occur with extensive temporal (on a daily, weekly, to monthly timescale) and spatial (over a million square kilometers) coverage. Although significant advances have been made in field measurements, model simulations, and laboratory experiments for fine PM over recent years, the causes for severe haze formation have not yet to be systematically/comprehensively evaluated. This review provides a synthetic synopsis of recent advances in understanding the fundamental mechanisms of severe haze formation in northern China, focusing on emission sources, chemical formation and transformation, and meteorological and climatic conditions. In particular, we highlight the synergetic effects from the interactions between anthropogenic emissions and atmospheric processes. Current challenges and future research directions to improve the understanding of severe haze pollution as well as plausible regulatory implications on a scientific basis are also discussed.

Ultrahigh–energy density lead-free dielectric films via polymorphic nanodomain design

Abstract: Dielectric capacitors with ultrahigh power densities are fundamental energy storage components in electrical and electronic systems. However, a long-standing challenge is improving their energy densities. We report dielectrics with ultrahigh energy densities designed with polymorphic nanodomains. Guided by phase-field simulations, we conceived and synthesized lead-free BiFeO3-BaTiO3-SrTiO3 solid-solution films to realize the coexistence of rhombohedral and tetragonal nanodomains embedded in a cubic matrix. We obtained minimized hysteresis while maintaining high polarization and achieved a high energy density of 112 joules per cubic centimeter with a high energy efficiency of ~80%. This approach should be generalizable for designing high-performance dielectrics and other functional materials that benefit from nanoscale domain structure manipulation.

Metal halide perovskite nanostructures for optoelectronic applications and the study of physical properties

Abstract: Nanostructures of inorganic semiconductors have revolutionized many areas of electronics, optoelectronics and photonics. The controlled synthesis of semiconductor nanostructures could lead to novel physical properties, improved optoelectronic device performance and new areas for exploration. Lead halide perovskites have recently excited the photovoltaic research community owing to their high solar-conversion efficiencies and ease of solution processing; they also hold great promise for optoelectronic applications, such as light-emitting diodes and lasers. In this Review, we summarize recent developments in the synthesis and characterization of metal halide perovskite nanostructures with controllable compositions, dimensionality, morphologies and orientations. We examine the advantageous optical properties, improved stability and potential optoelectronic applications of these 1D and 2D single-crystal perovskite nanostructures and compare them with those of bulk perovskites and nanostructures of conventional semiconductors. Studies in which perovskite nanostructures have been used to study the fundamental physical properties of perovskites are also highlighted. Finally, we discuss the challenges in realizing halide perovskite nanostructures for optoelectronic and photonic applications and offer our perspectives on future opportunities and research directions. Metal halide perovskite nanostructures are promising materials for optoelectronic applications. In this Review, we discuss the synthesis and properties of 1D and 2D single-crystal perovskite nanostructures, examine potential optoelectronic applications and highlight recent studies in which these nanostructures have been used to study the fundamental properties of perovskites.

Synergy of Dopants and Defects in Graphitic Carbon Nitride with Exceptionally Modulated Band Structures for Efficient Photocatalytic Oxygen Evolution.

Abstract: Electronic structure greatly determines the band structures and the charge carrier transport properties of semiconducting photocatalysts and consequently their photocatalytic activities. Here, by simply calcining the mixture of graphitic carbon nitride (g-C3 N4 ) and sodium borohydride in an inert atmosphere, boron dopants and nitrogen defects are simultaneously introduced into g-C3 N4 . The resultant boron-doped and nitrogen-deficient g-C3 N4 exhibits excellent activity for photocatalytic oxygen evolution, with highest oxygen evolution rate reaching 561.2 µmol h-1 g-1 , much higher than previously reported g-C3 N4 . It is well evidenced that with conduction and valence band positions substantially and continuously tuned by the simultaneous introduction of boron dopants and nitrogen defects into g-C3 N4 , the band structures are exceptionally modulated for both effective optical absorption in visible light and much increased driving force for water oxidation. Moreover, the engineered electronic structure creates abundant unsaturated sites and induces strong interlayer C-N interaction, leading to efficient electron excitation and accelerated charge transport. In the present work, a facile approach is successfully demonstrated to engineer the electronic structures and the band structures of g-C3 N4 with simultaneous introduction of dopants and defects for high-performance photocatalytic oxygen evolution, which can provide informative principles for the design of efficient photocatalysis systems for solar energy conversion.

Designing crystallization in phase-change materials for universal memory and neuro-inspired computing

Abstract: The global demand for data storage and processing has increased exponentially in recent decades. To respond to this demand, research efforts have been devoted to the development of non-volatile memory and neuro-inspired computing technologies. Chalcogenide phase-change materials (PCMs) are leading candidates for such applications, and they have become technologically mature with recently released competitive products. In this Review, we focus on the mechanisms of the crystallization dynamics of PCMs by discussing structural and kinetic experiments, as well as ab initio atomistic modelling and materials design. Based on the knowledge at the atomistic level, we depict routes to improve the parameters of phase-change devices for universal memory. Moreover, we discuss the role of crystallization in enabling neuro-inspired computing using PCMs. Finally, we present an outlook for future opportunities of PCMs, including all-photonic memories and processors, flexible displays with nanopixel resolution and nanoscale switches and controllers. Chalcogenide phase-change materials (PCMs) are leading candidates for non-volatile memory and neuro-inspired computing devices. This Review focuses on the crystallization mechanisms of PCMs as well as the design principles to achieve PCMs with high switching speeds and good data retention, which will aid the development of PCM-based universal memory and neuro-inspired devices.

Single-Junction Polymer Solar Cells with 16.35% Efficiency Enabled by a Platinum(II) Complexation Strategy

Abstract: A new strategy of platinum(II) complexation is developed to regulate the crystallinity and molecular packing of polynitrogen heterocyclic polymers, optimize the morphology of the active blends, and improve the efficiency of the resulting nonfullerene polymer solar cells (NF-PSCs). The newly designed s-tetrazine (s-TZ)-containing copolymer of PSFTZ (4,8-bis(5-((2-butyloctyl)thio)-4-fluorothiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene-alt-3,6-bis(4-octylthiophen-2-yl)-1,2,4,5-tetrazine) has a strong aggregation property, which results in serious phase separation and large domains when blending with Y6 ((2,2'-((2Z,2'Z)-((12,13-bis(2-ethylhexyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2″,3″:4',5']thieno[2',3':4,5]pyrrolo[3,2-g]thieno[2',3':4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile)), and produces a power-conversion efficiency (PCE) of 13.03%. By adding small amount of Pt(Ph)2 (DMSO)2 (Ph, phenyl and DMSO, dimethyl sulfoxide), platinum(II) complexation would occur between Pt(Ph)2 (DMSO)2 and PSFTZ. The bulky benzene ring on the platinum(II) complex increases the steric hindrance along the polymer main chain, inhibits the polymer aggregation strength, regulates the phase separation, optimizes the morphology, and thus improves the efficiency to 16.35% in the resulting devices. 16.35% is the highest efficiency for single-junction PSCs reported so far.

Design and fabrication of carbon dots for energy conversion and storage

Abstract: The emergence of carbon dots (CDs) has opened up an exciting new field in the science and technology of carbon nanomaterials and has attracted increasing interest in recent years. Due to their diverse physicochemical properties and favourable attributes, such as quantum confinement effects and abundant surface defects, CDs and their derived hybrids have shown exciting and indispensable prospects in the energy conversion and storage fields. Considering the latest developments, in this review, we comprehensively summarize the classification and structure of CDs. Three strategies for structural engineering of CDs are presented and analyzed, in terms of the tuning of size and crystallinity, and the methodologies for surface modification and heteroatom doping, with a focus on the relationship among the synthesis methods, structure and properties of the concerned CDs. More importantly, the recent advances in energy-oriented applications of CDs, including photo- and electro-catalysis, light-emitting diodes, photovoltaic cells, lithium/sodium ion batteries and supercapacitors, will be systematically highlighted. Finally, we discuss and outline the remaining major challenges and opportunities for CDs in the future.

Engineering Bioactive Self-Healing Antibacterial Exosomes Hydrogel for Promoting Chronic Diabetic Wound Healing and Complete Skin Regeneration.

Abstract: Rationale: Chronic nonhealing diabetic wound therapy and complete skin regeneration remains a critical clinical challenge. The controlled release of bioactive factors from a multifunctional hydrogel was a promising strategy to repair chronic wounds. Methods: Herein, for the first time, we developed an injectable, self-healing and antibacterial polypeptide-based FHE hydrogel (F127/OHA-EPL) with stimuli-responsive adipose-derived mesenchymal stem cells exosomes (AMSCs-exo) release for synergistically enhancing chronic wound healing and complete skin regeneration. The materials characterization, antibacterial activity, stimulated cellular behavior and in vivo full-thickness diabetic wound healing ability of the hydrogels were performed and analyzed. Results: The FHE hydrogel possessed multifunctional properties including fast self-healing process, shear-thinning injectable ability, efficient antibacterial activity, and long term pH-responsive bioactive exosomes release behavior. In vitro, the FHE@exosomes (FHE@exo) hydrogel significantly promoted the proliferation, migration and tube formation ability of human umbilical vein endothelial cells (HUVECs). In vivo, the FHE@exo hydrogel significantly enhanced the healing efficiency of diabetic full-thickness cutaneous wounds, characterized with enhanced wound closure rates, fast angiogenesis, re-epithelization and collagen deposition within the wound site. Moreover, the FHE@exo hydrogel displayed better healing outcomes than those of exosomes or FHE hydrogel alone, suggesting that the sustained release of exosomes and FHE hydrogel can synergistically facilitate diabetic wound healing. Skin appendages and less scar tissue also appeared in FHE@exo hydrogel treated wounds, indicating its potent ability to achieve complete skin regeneration. Conclusion: This work offers a new approach for repairing chronic wounds completely through a multifunctional hydrogel with controlled exosomes release.

Stimuli-responsive bio-based polymeric systems and their applications

Abstract: Stimuli-responsive bio-based polymeric systems are gaining considerable attention as intelligent versatile tools that show great potential in various fields. In this review, an overview is given of recent developments of stimuli-responsive bio-based polymeric systems. The characteristics of bio-based polymers in different applications are discussed and the superiority of these advanced stimuli-responsive bio-based polymeric systems is highlighted. Furthermore, several emerging applications of these systems including intelligent drug delivery, responsive food packaging and smart water treatment are discussed and the section of intelligent drug delivery is emphasized in detail. Finally, the respective prospects and limitations inherent to these systems are addressed.

Giant piezoelectricity of Sm-doped Pb(Mg1/3Nb2/3)O3-PbTiO3 single crystals.

Abstract: High-performance piezoelectrics benefit transducers and sensors in a variety of electromechanical applications. The materials with the highest piezoelectric charge coefficients (d33) are relaxor-PbTiO3 crystals, which were discovered two decades ago. We successfully grew Sm-doped Pb(Mg1/3Nb2/3)O3-PbTiO3 (Sm-PMN-PT) single crystals with even higher d33 values ranging from 3400 to 4100 picocoulombs per newton, with variation below 20% over the as-grown crystal boule, exhibiting good property uniformity. We characterized the Sm-PMN-PT on the atomic scale with scanning transmission electron microscopy and made first-principles calculations to determine that the giant piezoelectric properties arise from the enhanced local structural heterogeneity introduced by Sm3+ dopants. Rare-earth doping is thus identified as a general strategy for introducing local structural heterogeneity in order to enhance the piezoelectricity of relaxor ferroelectric crystals.

Metal-Organic Framework-Based Stimuli-Responsive Systems for Drug Delivery

Abstract: With the rapid development of nanotechnology, stimuli-responsive nanomaterials have provided an alternative for designing controllable drug delivery systems due to their spatiotemporally controllable properties. As a new type of porous material, metal-organic frameworks (MOFs) have been widely used in biomedical applications, especially drug delivery systems, owing to their tunable pore size, high surface area and pore volume, and easy surface modification. Here, recent progress in MOF-based stimuli-responsive systems is presented, including pH-, magnetic-, ion-, temperature-, pressure-, light-, humidity-, redox-, and multiple stimuli-responsive systems for the delivery of anticancer drugs. The remaining challenges and suggestions for future directions for the rational design of MOF-based nanomedicines are also discussed.

Progressive Image Deraining Networks: A Better and Simpler Baseline

Abstract: Along with the deraining performance improvement of deep networks, their structures and learning become more and more complicated and diverse, making it difficult to analyze the contribution of various network modules when developing new deraining networks. To handle this issue, this paper provides a better and simpler baseline deraining network by considering network architecture, input and output, and loss functions. Specifically, by repeatedly unfolding a shallow ResNet, progressive ResNet (PRN) is proposed to take advantage of recursive computation. A recurrent layer is further introduced to exploit the dependencies of deep features across stages, forming our progressive recurrent network (PReNet). Furthermore, intra-stage recursive computation of ResNet can be adopted in PRN and PReNet to notably reduce network parameters with unsubstantial degradation in deraining performance. For network input and output, we take both stage-wise result and original rainy image as input to each ResNet and finally output the prediction of residual image. As for loss functions, single MSE or negative SSIM losses are sufficient to train PRN and PReNet. Experiments show that PRN and PReNet perform favorably on both synthetic and real rainy images. Considering its simplicity, efficiency and effectiveness, our models are expected to serve as a suitable baseline in future deraining research. The source codes are available at https://github.com/csdwren/PReNet.