Showing papers by "Harbin Institute of Technology published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Towards complete and error-free genome assemblies of all vertebrate species

Abstract: High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.

Image Matching from Handcrafted to Deep Features: A Survey

Abstract: As a fundamental and critical task in various visual applications, image matching can identify then correspond the same or similar structure/content from two or more images. Over the past decades, growing amount and diversity of methods have been proposed for image matching, particularly with the development of deep learning techniques over the recent years. However, it may leave several open questions about which method would be a suitable choice for specific applications with respect to different scenarios and task requirements and how to design better image matching methods with superior performance in accuracy, robustness and efficiency. This encourages us to conduct a comprehensive and systematic review and analysis for those classical and latest techniques. Following the feature-based image matching pipeline, we first introduce feature detection, description, and matching techniques from handcrafted methods to trainable ones and provide an analysis of the development of these methods in theory and practice. Secondly, we briefly introduce several typical image matching-based applications for a comprehensive understanding of the significance of image matching. In addition, we also provide a comprehensive and objective comparison of these classical and latest techniques through extensive experiments on representative datasets. Finally, we conclude with the current status of image matching technologies and deliver insightful discussions and prospects for future works. This survey can serve as a reference for (but not limited to) researchers and engineers in image matching and related fields.

Comprehensive defect suppression in perovskite nanocrystals for high-efficiency light-emitting diodes

Abstract: Electroluminescence efficiencies of metal halide perovskite nanocrystals (PNCs) are limited by a lack of material strategies that can both suppress the formation of defects and enhance the charge carrier confinement. Here we report a one-dopant alloying strategy that generates smaller, monodisperse colloidal particles (confining electrons and holes, and boosting radiative recombination) with fewer surface defects (reducing non-radiative recombination). Doping of guanidinium into formamidinium lead bromide PNCs yields limited bulk solubility while creating an entropy-stabilized phase in the PNCs and leading to smaller PNCs with more carrier confinement. The extra guanidinium segregates to the surface and stabilizes the undercoordinated sites. Furthermore, a surface-stabilizing 1,3,5-tris(bromomethyl)-2,4,6-triethylbenzene was applied as a bromide vacancy healing agent. The result is highly efficient PNC-based light-emitting diodes that have current efficiency of 108 cd A−1 (external quantum efficiency of 23.4%), which rises to 205 cd A−1 (external quantum efficiency of 45.5%) with a hemispherical lens. Guanidinium doping is shown to enhance the operation of perovskite nanocrystal light-emitting diodes.

A Review of Shape Memory Polymers and Composites: Mechanisms, Materials, and Applications

Abstract: Over the past decades, interest in shape memory polymers (SMPs) has persisted, and immense efforts have been dedicated to developing SMPs and their multifunctional composites. As a class of stimuli-responsive polymers, SMPs can return to their initial shape from a programmed temporary shape under external stimuli, such as light, heat, magnetism, and electricity. The introduction of functional materials and nanostructures results in shape memory polymer composites (SMPCs) with large recoverable deformation, enhanced mechanical properties, and controllable remote actuation. Because of these unique features, SMPCs have a broad application prospect in many fields covering aerospace engineering, biomedical devices, flexible electronics, soft robotics, shape memory arrays, and 4D printing. Herein, a comprehensive analysis of the shape recovery mechanisms, multifunctionality, applications, and recent advances in SMPs and SMPCs is presented. Specifically, the combination of functional, reversible, multiple, and controllable shape recovery processes is discussed. Further, established products from such materials are highlighted. Finally, potential directions for the future advancement of SMPs are proposed.

2D Transition Metal Dichalcogenides: Design, Modulation, and Challenges in Electrocatalysis.

Abstract: Hydrogen has been deemed as an ideal substitute fuel to fossil energy because of its renewability and the highest energy density among all chemical fuels One of the most economical, ecofriendly, and high-performance ways of hydrogen production is electrochemical water splitting Recently, 2D transition metal dichalcogenides (also known as 2D TMDs) showed their utilization potentiality as cost-effective hydrogen evolution reaction (HER) catalysts in water electrolysis Herein, recent representative research efforts and systematic progress made in 2D TMDs are reviewed, and future opportunities and challenges are discussed Furthermore, general methods of synthesizing 2D TMDs materials are introduced in detail and the advantages and disadvantages for some specific methods are provided This explanation includes several important regulation strategies of creating more active sites, heteroatoms doping, phase engineering, construction of heterostructures, and synergistic modulation which are capable of optimizing the electrical conductivity, exposure to the catalytic active sites, and reaction energy barrier of the electrode material to boost the HER kinetics In the last section, the current obstacles and future chances for the development of 2D TMDs electrocatalysts are proposed to provide insight into and valuable guidelines for fabricating effective HER electrocatalysts

Exploring the impact of COVID-19 on tourism: transformational potential and implications for a sustainable recovery of the travel and leisure industry

Abstract: The study stipulates phases to observe the proposed mechanism in formulating the travel and leisure industry's recovery strategies. The present pandemic COVID-19 has resulted in global challenges, economic and healthcare crises, and posed spillover impacts on the global industries, including tourism and travel that the major contributor to the service industry worldwide. The tourism and leisure industry has faced the COVID-19 tourism impacts hardest-hit and lies among the most damaged global industries. The leisure and internal tourism indicated a steep decline amounting to 2.86 trillion US dollars, which quantified more than 50% revenue losses. In the first step, the study explores the consequences and settings of the COVID-19 pandemic and how innovation and change can contribute to the tourism industry's revival to the next normal. Thus, the study determines that tourism enterprises and scholars must consider and change the basic principles, main assumptions, and organizational situations related to research and practice framework through rebuilding and establishing the tourism sector. In the second step, the study discusses direct COVID-19 tourism impacts, attitudes, and practices in gaining the leisure industry's boom and recovery. In the third phase, the study proposes to observe the characteristics and COVID-19 tourism consequences on the travel and tourism research. The findings provide insights in regaining the tourism industry's operational activities and offer helpful suggestions to government officials, scholars, and tourism firms to reinvest in the tourism industry to set it back to a normal position.

A review on ammonia, ammonia-hydrogen and ammonia-methane fuels

Abstract: Combustion of fuels to generate energy is integral to various human activities, both domestic and industrial. However, the predominance of hydrocarbon fuel usage produces emissions containing pollutants that cause multiple environmental complications and risks to human health. Therefore, replacement of conventional fuels to achieve zero carbon emission is of utmost importance. In terms of carbon-free fuel, ammonia offers several advantages over hydrogen. However, its low burning velocity and high fuel NOx emissions inhibit large-scale usage. Hence, hydrogen and methane have been studied in this review as possible secondary fuels to aid ammonia combustion and address the aforementioned issues. This review starts from the suitability of ammonia fuel as energy vector in terms of physicochemical and combustion characteristics, moving through the kinetics and mechanisms of ammonia-based and ammonia-fuel combustion. The impacts and limitations of each system are also addressed, thus providing a comparison on each system. Particularly, this review assesses and discusses the advantages and mechanisms involved with secondary fuel addition to the ammonia combustion, presenting the role of key reaction differences and the change in key reaction mechanism under different conditions at the level of reaction mechanisms. Finally, this review covers future perspectives and challenges on the usage and development of ammonia-based fuels, emphasizing the maturity of ammonia-based and ammonia-fuel combustion kinetics. Herein, this work summarizes the principles of the combustion reactions of ammonia-based and ammonia-fuel systematically and serves as a theoretical reference of ammonia-fuel combustion kinetics for transitioning into future practical applications where ammonia is an important energy vector.

Stretchable Electronics Based on PDMS Substrates.

Abstract: Stretchable electronics, which can retain their functions under stretching, have attracted great interest in recent decades. Elastic substrates, which bear the applied strain and regulate the strain distribution in circuits, are indispensable components in stretchable electronics. Moreover, the self-healing property of the substrate is a premise to endow stretchable electronics with the same characteristics, so the device may recover from failure resulting from large and frequent deformations. Therefore, the properties of the elastic substrate are crucial to the overall performance of stretchable devices. Poly(dimethylsiloxane) (PDMS) is widely used as the substrate material for stretchable electronics, not only because of its advantages, which include stable chemical properties, good thermal stability, transparency, and biological compatibility, but also because of its capability of attaining designer functionalities via surface modification and bulk property tailoring. Herein, the strategies for fabricating stretchable electronics on PDMS substrates are summarized, and the influence of the physical and chemical properties of PDMS, including surface chemical status, physical modulus, geometric structures, and self-healing properties, on the performance of stretchable electronics is discussed. Finally, the challenges and future opportunities of stretchable electronics based on PDMS substrates are considered.

Pre-Training with Whole Word Masking for Chinese BERT

Abstract: Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks, and its consecutive variants have been proposed to further improve the performance of the pre-trained language models. In this paper, we aim to first introduce the whole word masking (wwm) strategy for Chinese BERT, along with a series of Chinese pre-trained language models. Then we also propose a simple but effective model called MacBERT, which improves upon RoBERTa in several ways. Especially, we propose a new masking strategy called MLM as correction (Mac). To demonstrate the effectiveness of these models, we create a series of Chinese pre-trained language models as our baselines, including BERT, RoBERTa, ELECTRA, RBT, etc. We carried out extensive experiments on ten Chinese NLP tasks to evaluate the created Chinese pre-trained language models as well as the proposed MacBERT. Experimental results show that MacBERT could achieve state-of-the-art performances on many NLP tasks, and we also ablate details with several findings that may help future research. We open-source our pre-trained language models for further facilitating our research community.

A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes

Abstract: Over the past twenty years, numerous research outcomes have been published, related to the design and implementation of soft sensors. In modern industrial processes, various types of soft sensors are used, which play essential roles in process monitoring, control and optimization. Emerging new theories, advanced techniques and the information infrastructure have enabled the elevation of the performance of soft sensing. However, novel opportunities are accompanied by novel challenges. This work is motivated by these observations and aims to present a comprehensive review of the developments since the start of the millennium. While a few books and review articles are published on the related topics, more focus on the most up-to-the-date advancement is put in this work, from the perspective of systems and control.

Recent Advances in Plasmonic Nanostructures for Enhanced Photocatalysis and Electrocatalysis.

Abstract: Plasmonic nanomaterials coupled with catalytically active surfaces can provide unique opportunities for various catalysis applications, where surface plasmons produced upon proper light excitation can be adopted to drive and/or facilitate various chemical reactions. A brief introduction to the localized surface plasmon resonance and recent design and fabrication of highly efficient plasmonic nanostructures, including plasmonic metal nanostructures and metal/semiconductor heterostructures is given. Taking advantage of these plasmonic nanostructures, the following highlights summarize recent advances in plasmon-driven photochemical reactions (coupling reactions, O2 dissociation and oxidation reactions, H2 dissociation and hydrogenation reactions, N2 fixation and NH3 decomposition, and CO2 reduction) and plasmon-enhanced electrocatalytic reactions (hydrogen evolution reaction, oxygen reduction reaction, oxygen evolution reaction, alcohol oxidation reaction, and CO2 reduction). Theoretical and experimental approaches for understanding the underlying mechanism of surface plasmon are discussed. A proper discussion and perspective of the remaining challenges and future opportunities for plasmonic nanomaterials and plasmon-related chemistry in the field of energy conversion and storage is given in conclusion.

Fuzzy Adaptive Finite-Time Fault-Tolerant Control for Strict-Feedback Nonlinear Systems

Abstract: This article devotes to investigating the issue of fuzzy adaptive control for a class of strict-feedback nonlinear systems with nonaffine nonlinear faults. The computational complexity is reduced by adopting the dynamic surface control technique. Under the framework of finite-time stability, a novel fault-tolerant control strategy is designed so that the closed-loop system is semiglobally practically finite-time stable, and the tracking error converges to a small residual set in a finite time. Finally, simulation studies for an electromechanical system are shown to verify the feasibility of the presented approach.

Bimetallic synergetic regulating effect on electronic structure in cobalt/vanadium co-doped carbon nitride for boosting photocatalytic performance

Abstract: The photocatalytic activity of bimetallic co-doped g-C3N4 can be boosted dramatically, whereas the enhanced mechanisms essentially have been rarely revealed. Here, the prepared Co/V co-doped g-C3N4 significantly enhances the photocatalytic activity. The degradation rate constant and TOC removal efficiency of TC−HCl in 120 min over the Co/V-g-C3N4-2 sample run up to 4.00 and 2.45 times as much as that of g-C3N4, respectively. The outstanding photocatalytic performance is attributed to the improved charge separation efficiency and visible-light harvest ability. The density functional theory (DFT) investigations reveal the incorporation of Co/V into g-C3N4 can induce the bimetallic synergetic regulating effect on electronic structure, which results in improving the physical, optical and photoelectrochemical properties. Moreover, the significant degradation intermediates, pathway and mechanism of TC−HCl, and charge transfer behaviors are also discussed in depth. This work provides a meritorious instance to design and synthesize new bimetallic co-doped g-C3N4 materials in the photocatalytic application field.

Advanced Electrocatalysis for Energy and Environmental Sustainability via Water and Nitrogen Reactions

Abstract: Clean and efficient energy storage and conversion via sustainable water and nitrogen reactions have attracted substantial attention to address the energy and environmental issues due to the overwhelming use of fossil fuels. These electrochemical reactions are crucial for desirable clean energy technologies, including advanced water electrolyzers, hydrogen fuel cells, and ammonia electrosynthesis and utilization. Their sluggish reaction kinetics lead to inefficient energy conversion. Innovative electrocatalysis, i.e., catalysis at the interface between the electrode and electrolyte to facilitate charge transfer and mass transport, plays a vital role in boosting energy conversion efficiency and providing sufficient performance and durability for these energy technologies. Herein, a comprehensive review on recent progress, achievements, and remaining challenges for these electrocatalysis processes related to water (i.e., oxygen evolution reaction, OER, and oxygen reduction reaction, ORR) and nitrogen (i.e., nitrogen reduction reaction, NRR, for ammonia synthesis and ammonia oxidation reaction, AOR, for energy utilization) is provided. Catalysts, electrolytes, and interfaces between the two within electrodes for these electrocatalysis processes are discussed. The primary emphasis is device performance of OER-related proton exchange membrane (PEM) electrolyzers, ORR-related PEM fuel cells, NRR-driven ammonia electrosynthesis from water and nitrogen, and AOR-related direct ammonia fuel cells.

Event-Triggered Robust Fuzzy Adaptive Finite-Time Control of Nonlinear Systems With Prescribed Performance

Abstract: In this article, an event-triggered robust fuzzy adaptive prescribed performance finite-time control strategy is presented for a class of strict-feedback nonlinear systems with external disturbances. The relative-threshold-based event-triggered signal is introduced to reduce communication burden, and the dynamic surface control technique is applied to address the computational complexity problem. A disturbance observer is designed to estimate the compounded disturbances, which are composed of external disturbances and fuzzy approximation errors. The proposed control strategy can guarantee that the closed-loop system is semiglobally practically finite-time stable, and the tracking error converges to a small residual set by incorporating the prescribed performance bound in finite-time. Finally, simulation results are provided to verify the effectiveness of the proposed robust fuzzy control strategy.

Interface Issues and Challenges in All-Solid-State Batteries: Lithium, Sodium, and Beyond.

Abstract: Owing to the promise of high safety and energy density, all-solid-state batteries are attracting incremental interest as one of the most promising next-generation energy storage systems. However, their widespread applications are inhibited by many technical challenges, including low-conductivity electrolytes, dendrite growth, and poor cycle/rate properties. Particularly, the interfacial dynamics between the solid electrolyte and the electrode is considered as a crucial factor in determining solid-state battery performance. In recent years, intensive research efforts have been devoted to understanding the interfacial behavior and strategies to overcome these challenges for all-solid-state batteries. Here, the interfacial principle and engineering in a variety of solid-state batteries, including solid-state lithium/sodium batteries and emerging batteries (lithium-sulfur, lithium-air, etc.), are discussed. Specific attention is paid to interface physics (contact and wettability) and interface chemistry (passivation layer, ionic transport, dendrite growth), as well as the strategies to address the above concerns. The purpose here is to outline the current interface issues and challenges, allowing for target-oriented research for solid-state electrochemical energy storage. Current trends and future perspectives in interfacial engineering are also presented.

Self-Supervised Deep Correlation Tracking

Abstract: The training of a feature extraction network typically requires abundant manually annotated training samples, making this a time-consuming and costly process. Accordingly, we propose an effective self-supervised learning-based tracker in a deep correlation framework (named: self-SDCT). Motivated by the forward-backward tracking consistency of a robust tracker, we propose a multi-cycle consistency loss as self-supervised information for learning feature extraction network from adjacent video frames. At the training stage, we generate pseudo-labels of consecutive video frames by forward-backward prediction under a Siamese correlation tracking framework and utilize the proposed multi-cycle consistency loss to learn a feature extraction network. Furthermore, we propose a similarity dropout strategy to enable some low-quality training sample pairs to be dropped and also adopt a cycle trajectory consistency loss in each sample pair to improve the training loss function. At the tracking stage, we employ the pre-trained feature extraction network to extract features and utilize a Siamese correlation tracking framework to locate the target using forward tracking alone. Extensive experimental results indicate that the proposed self-supervised deep correlation tracker (self-SDCT) achieves competitive tracking performance contrasted to state-of-the-art supervised and unsupervised tracking methods on standard evaluation benchmarks.

High-efficient charge separation driven directionally by pyridine rings grafted on carbon nitride edge for boosting photocatalytic hydrogen evolution

Abstract: Intramolecular doping of conjugated nitrogen heterocycles in carbon nitride (CN) has been used to promote charge separation, but it also causes recombination of photogenerated electrons and holes due to their in-plane non-directional transfer. Herein, it achieves the dual regulation of adjusting electron hybridization structure and electron directional transfer from centre to edge of CN by grafting pyridine rings on the edge of CN framework, which effectively drives separation and avoids recombination of photogenerated carriers in plane. The photocatalytic HER rate of up to 6317.5 μmol g−1 h−1 is obtained over the optimum 2AP-CN-15 sample, which has 3.9-fold increase over primal CN. Moreover, the apparent quantum efficiency of HER reaches up to 20.1 % at 420 nm. This work performs an essential insight into edge decoration effect of pyridine rings on CN, which affords a new guidance for the modification of CN-like materials with conjugated nitrogen heterocycles for high-efficiency photocatalytic application.

Recent Progress in Graphene/Polymer Nanocomposites.

Abstract: Nanocomposites, multiphase solid materials with at least one nanoscaled component, have been attracting ever-increasing attention because of their unique properties. Graphene is an ideal filler for high-performance multifunctional nanocomposites in light of its superior mechanical, electrical, thermal, and optical properties. However, the 2D nature of graphene usually gives rise to highly anisotropic features, which brings new opportunities to tailor nanocomposites by making full use of its excellent in-plane properties. Here, recent progress on graphene/polymer nanocomposites is summarized with emphasis on strengthening/toughening, electrical conduction, thermal transportation, and photothermal energy conversion. The influence of the graphene configuration, including layer number, defects, and lateral size, on its intrinsic properties and the properties of graphene/polymer nanocomposites is systematically analyzed. Meanwhile, the role of the interfacial interaction between graphene and polymer in affecting the properties of nanocomposites is also explored. The correlation between the graphene distribution in the matrix and the properties of the nanocomposite is discussed in detail. The key challenges and possible solutions are also addressed. This review may provide a constructive guidance for preparing high-performance graphene/polymer nanocomposite in the future.

Modifying redox properties and local bonding of Co3O4 by CeO2 enhances oxygen evolution catalysis in acid

Abstract: Developing efficient and stable earth-abundant electrocatalysts for acidic oxygen evolution reaction is the bottleneck for water splitting using proton exchange membrane electrolyzers. Here, we show that nanocrystalline CeO2 in a Co3O4/CeO2 nanocomposite can modify the redox properties of Co3O4 and enhances its intrinsic oxygen evolution reaction activity, and combine electrochemical and structural characterizations including kinetic isotope effect, pH- and temperature-dependence, in situ Raman and ex situ X-ray absorption spectroscopy analyses to understand the origin. The local bonding environment of Co3O4 can be modified after the introduction of nanocrystalline CeO2, which allows the CoIII species to be easily oxidized into catalytically active CoIV species, bypassing the potential-determining surface reconstruction process. Co3O4/CeO2 displays a comparable stability to Co3O4 thus breaks the activity/stability tradeoff. This work not only establishes an efficient earth-abundant catalysts for acidic oxygen evolution reaction, but also provides strategies for designing more active catalysts for other reactions.