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Showing papers by "Xi'an Jiaotong University published in 2022"


Journal ArticleDOI
TL;DR: Results indicate that these multifunctional antibacterial adhesive hemostatic hydrogels have better healing effects than commercially available Tegaderm™ Film, revealing that they have become promising alternative in the healing of infected wounds.

216 citations


Journal ArticleDOI
TL;DR: Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can not only leverage the advantages of Deep Learning (DL) in feature representation, but also benefit from the superiority of transfer learning (TL) in knowledge transfer.

161 citations


Journal ArticleDOI
TL;DR: In this paper, a review of the research results on intelligent fault diagnosis with small and imbalanced data (S&I-IFD) is presented, which refers to build intelligent diagnosis models using limited machine faulty samples to achieve accurate fault identification.
Abstract: The research on intelligent fault diagnosis has yielded remarkable achievements based on artificial intelligence-related technologies. In engineering scenarios, machines usually work in a normal condition, which means limited fault data can be collected. Intelligent fault diagnosis with small & imbalanced data (S&I-IFD), which refers to build intelligent diagnosis models using limited machine faulty samples to achieve accurate fault identification, has been attracting the attention of researchers. Nowadays, the research on S&I-IFD has achieved fruitful results, but a review of the latest achievements is still lacking, and the future research directions are not clear enough. To address this, we review the research results on S&I-IFD and provides some future perspectives in this paper. The existing research results are divided into three categories: the data augmentation-based, the feature learning-based, and the classifier design-based. Data augmentation-based strategy improves the performance of diagnosis models by augmenting training data. Feature learning-based strategy identifies faults accurately by extracting features from small & imbalanced data. Classifier design-based strategy achieves high diagnosis accuracy by constructing classifiers suitable for small & imbalanced data. Finally, this paper points out the research challenges faced by S&I-IFD and provides some directions that may bring breakthroughs, including meta-learning and zero-shot learning.

118 citations


Journal ArticleDOI
01 Jan 2022
TL;DR: In this paper , a review of the research results on intelligent fault diagnosis with small and imbalanced data (S&I-IFD) is presented, which refers to build intelligent diagnosis models using limited machine faulty samples to achieve accurate fault identification.
Abstract: The research on intelligent fault diagnosis has yielded remarkable achievements based on artificial intelligence-related technologies. In engineering scenarios, machines usually work in a normal condition, which means limited fault data can be collected. Intelligent fault diagnosis with small & imbalanced data (S&I-IFD), which refers to build intelligent diagnosis models using limited machine faulty samples to achieve accurate fault identification, has been attracting the attention of researchers. Nowadays, the research on S&I-IFD has achieved fruitful results, but a review of the latest achievements is still lacking, and the future research directions are not clear enough. To address this, we review the research results on S&I-IFD and provides some future perspectives in this paper. The existing research results are divided into three categories: the data augmentation-based, the feature learning-based, and the classifier design-based. Data augmentation-based strategy improves the performance of diagnosis models by augmenting training data. Feature learning-based strategy identifies faults accurately by extracting features from small & imbalanced data. Classifier design-based strategy achieves high diagnosis accuracy by constructing classifiers suitable for small & imbalanced data. Finally, this paper points out the research challenges faced by S&I-IFD and provides some directions that may bring breakthroughs, including meta-learning and zero-shot learning.

113 citations


Journal ArticleDOI
TL;DR: An adaptive maximum cyclostationarity blind deconvolution (ACYCBD) is proposed, aiming at the determination of cyclic frequency set estimation method based on autocorrelation function of morphological envelope and the validity of the method is verified.

107 citations


Journal ArticleDOI
TL;DR: In this paper, the causal relationship among technological innovation, environment pollution, energy consumption, and sustainable economic growth from selected South Asian economies was examined using the premises of the EKC framework in order to identify the causal association between energy growth and nexus of CO2 emissions, and found bidirectional causality between economic growth and energy use.

100 citations


Journal ArticleDOI
TL;DR: In this article , the causal relationship among technological innovation, environment pollution, energy consumption, and sustainable economic growth from selected South Asian economies was examined using the premises of the EKC framework in order to identify the causal association between energy growth and nexus of CO2 emissions, and found bidirectional causality between economic growth and energy use.

100 citations


Journal ArticleDOI
Pierre Friedlingstein1, Sönke Zaehle2, Corinne Le Quéré3, Christian Rödenbeck2, Bronte Tilbrook, Henry C. Bittig4, Denis Pierrot5, Louise Chini6, Jan Ivar Korsbakken7, Nicolas Bellouin8, Toste Tanhua9, Benjamin Poulter10, Peter Landschützer11, Francesco N. Tubiello12, Judith Hauck13, Are Olsen14, Vivek K. Arora15, Colm Sweeney16, Almut Arneth17, Marion Gehlen18, Hiroyuki Tsujino19, Daniel P. Kennedy20, Yosuke Iida19, Luke Gregor21, Jiye Zeng22, George C. Hurtt6, Nicolas Mayot23, Giacomo Grassi24, Shin-Ichiro Nakaoka22, Frédéric Chevallier18, Clemens Schwingshackl7, Wiley Evans25, Meike Becker26, Thomas Gasser27, Xu Yue28, Katie Pocock25, Stephanie Falk29, Thanos Gkritzalis11, Naiqing Pan30, Ingrid T. van der Laan-Luijkx31, Fraser Holding32, Carlos Gustavo Halaburda, Guanghong Zhou33, Peter Angele34, Jianling Chen1, e6gehqc68135, Carlos Muñoz Pérez23, Hiroshi Niinami36, Zongwe Binesikwe Crystal Hardy, Samuel Bourne37, Ralf Wüsthofen38, Paulo Brito, Christian Liguori39, Juan A. Martin-Ramos, Rattan Lal, kensetyrdhhtml2mdcom40, Staffan Furusten, Luca Miceli41, Eric Horster16, V. Miranda Chase, Field Palaeobiology Lab30, Living Tree Cbd Gummies, Lifeng Qin34, Yong Tang42, Annie Phillips43, Nathalie Fenouil26, mark, Karina Querne de Carvalho44, Satya Wydya Yenny, Maja Bak Herrie, Silvia Ravelli45, Andreas Gerster46, Denise Hottmann47, Wui-Lee Chang, Andreas Lutz48, Olga D. Vorob'eva49, Pallavi Banerjee1, Verónica Undurraga50, Jovan Babić, Michele D. Wallace9, Mònica Ginés-Blasi, 에볼루션카지노51, James Kelvin29, Christos Kontzinos1, Охунова Дилафруз Муминовна, Isabell Diekmann, Emily Burgoyne16, Vilemina Čenić52, Naomi Gikonyo26, CHAO LUAN21, Benjamin Pfluger53, Benjamin Pfluger54, A. J. Shields, Kobzos, Laszlo55, Adrian Langer56, Stuart L. Weinstein55, Abdullah ÖZÇELİK57, Yi Chen58, Anzhelika Solodka59, Valery Vasil'evich Kozlov60, Н.С. Рыжук, Roshan Vasant Shinde, Dr Sandeep Haribhau Wankhade, Dr Nitin Gajanan Shekapure, Mr Sachin Shrikant …61, Mylene Charon7, David Seibt62, Kobi Peled, None Rahmi52 
University of Exeter1, Max Planck Institute for Biogeochemistry2, Tyndall Centre3, Leibniz Institute for Baltic Sea Research4, Atlantic Oceanographic and Meteorological Laboratory5, University of Maryland, College Park6, CICERO Center for International Climate Research7, University of Reading8, Leibniz Institute of Marine Sciences9, Goddard Space Flight Center10, Flanders Marine Institute11, Food and Agriculture Organization12, Alfred Wegener Institute for Polar and Marine Research13, Geophysical Institute14, University of Victoria15, National Oceanic and Atmospheric Administration16, Karlsruhe Institute of Technology17, Laboratoire des Sciences du Climat et de l'Environnement18, Japan Meteorological Agency19, Indiana University20, ETH Zurich21, National Institute for Environmental Studies22, University of East Anglia23, European Commission24, Tula Foundation25, Bjerknes Centre for Climate Research26, Hertie Institute for Clinical Brain Research27, Nanjing University of Information Science and Technology28, Ludwig Maximilian University of Munich29, Auburn University30, Wageningen University and Research Centre31, University of Western Sydney32, Cooperative Institute for Research in Environmental Sciences33, Tsinghua University34, University of Florida35, Center for Neuroscience and Regenerative Medicine36, Woods Hole Research Center37, University of Alaska Fairbanks38, Princeton University39, Michigan State University40, University of Washington41, Appalachian State University42, Sun Yat-sen University43, Imperial College London44, University of Groningen45, University of Tennessee46, Washington University in St. Louis47, Jilin Medical University48, Tohoku University49, Rutgers University50, Centre for Research on Ecology and Forestry Applications51, Institut Pierre-Simon Laplace52, North West Agriculture and Forestry University53, Northwest A&F University54, Pacific Marine Environmental Laboratory55, Xi'an Jiaotong University56, Stanford University57, National Center for Atmospheric Research58, University of Edinburgh59, Max Planck Institute for Meteorology60, Utrecht University61, Oak Ridge National Laboratory62
TL;DR: Friedlingstein et al. as mentioned in this paper presented and synthesized data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties, including fossil CO2 emissions, land use and land-use change data and bookkeeping models.
Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

98 citations


Journal ArticleDOI
Meng Li1, Yongping Liang1, Yuqing Liang1, Guoying Pan1, Baolin Guo1 
TL;DR: In in vivo normal and infected full-thickness skin defect motion wound models, the hydrogel dressings significantly prevented wound infections and promoted wound healing with milder inflammation, higher granulation tissue thickness and collagen disposition, indicating their great potential in motion wound treatment in clinics.

93 citations


Journal ArticleDOI
01 Jan 2022-Fuel
TL;DR: In this article, a review of the factors that induce backfire in hydrogen-injected internal combustion engines is presented, including improper intake valve timing and fuel injection timing, high fuel-air equivalence ratios, and improper hydrogen distribution around intake valve seats.

89 citations


Journal ArticleDOI
TL;DR: Sarcopenia was associated with an increased risk of mortality in patients with cirrhosis (adjusted hazard ratio [aHR] 2.30, 95% CI 2.01-2.63) as mentioned in this paper .

Journal ArticleDOI
TL;DR: In this paper, a novel design on angled fins was proposed to improve the thermal transport for phase change materials (PCMs) in a shell-and-tube thermal storage unit, and a numerical model was built and verified by comparing with experimental observations on the melting front evolution and temperature history.

Journal ArticleDOI
TL;DR: In this paper, a tri-arm CdS/ZnS core-shell nanorod was designed for the first time, where tri-armed CcS nanorods were decorated by dodecylamine (DDA) molecules and then wrapped in an intermittent ZnS shell.

Journal ArticleDOI
TL;DR: Different perovskite structure-related compounds are discussed in this paper, which could be possible electrode materials in Solid Oxide Fuel Cells (SOFCs) and provide some useful recommendations and prospective directions for designing future electrode materials of SOFCs.

Journal ArticleDOI
TL;DR: In this paper, a comprehensive analysis of reaction mechanism, reactor characteristics, influencing factors, technoeconomic aspects, challenges, and prospects for liquid hot water-based biomass pretreatment is provided.

Journal ArticleDOI
TL;DR: Pore-scale modeling is an efficient tool for the simulation of porescale transport and reactions in porous media because of its ability to accurately characterize these processes and to provide the distribution details of important variables which are challenging for current experimental techniques to provide either due to lack of in-situ measurement capability or due to limited spatial and temporal resolution as discussed by the authors.

Journal ArticleDOI
TL;DR: In this article, a design strategy is proposed to optimize the energy storage characteristics and transparency of ceramics by introducing nanodomains, increasing the band gap energy and reducing the grain size.

Journal ArticleDOI
TL;DR: This paper provides a comprehensive review of blind deconvolution methods from history to state-of-the-art methods and finally to research prospects, as well as provides a survey and summarize the current progress of BDMs applied in machinery fault diagnosis.

Journal ArticleDOI
TL;DR: In this article, the progress and challenges on thermal management of different electrochemical energy devices including fuel cells, electrolysers and supercapacitors are discussed in-depth and some directions for future studies are provided.

Journal ArticleDOI
TL;DR: In this article, a high-performance NH4V4O10 cathode with oxygen vacancy and reduced graphene oxide surface modification is presented, which leads to high electronic conductivity, weak electrostatic interaction and low Zn2+ diffusion barrier.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper explored the influence of different public participation constraints on green technological innovation, and examined the moderating role of environmental regulatory enforcement in Chinese provincial data from 2009 to 2018.

Journal ArticleDOI
TL;DR: An open set fault diagnosis method is proposed to address the fault diagnosis problem in a more practical scenario where the test label set consists of a portion of the training label set and some unknown classes.
Abstract: Existing data-driven fault diagnosis methods assume that the label sets of the training data and test data are consistent, which is usually not applicable for real applications since the fault modes that occur in the test phase are unpredictable. To address this problem, open set fault diagnosis (OSFD), where the test label set consists of a portion of the training label set and some unknown classes, is studied in this article. Considering the changeable operating conditions of machinery, OSFD tasks are further divided into shared-domain open set fault diagnosis (SOSFD) and cross-domain open set fault diagnosis (COSFD) in this article. For SOSFD, 1-D convolutional neural networks are trained for learning discriminative features and recognizing fault modes. For COSFD, due to the distribution discrepancy between the source and target domains, the deep model needs to learn domain-invariant features of shared classes and separate features of outlier classes. Thus, by utilizing the output of an additional domain classifier, a model named bilateral weighted adversarial networks is proposed to assign large weights to shared classes and small weights to outlier classes during the feature alignment. In the test phase, samples are classified according to the outputs of the deep model and unknown-class samples are rejected by the extreme value theory model. Experimental results on two bearing datasets demonstrate the effectiveness and superiority of the proposed method.

Journal ArticleDOI
TL;DR: A framework to aggregate and transfer diagnostic knowledge from multiple source machines by combining multiple partial distribution adaptation sub-networks (PDA-Subnets) and a multi-source diagnostic knowledge fusion module is proposed.

Journal ArticleDOI
TL;DR: In this paper , a design strategy is proposed to optimize the energy storage characteristics and transparency of ceramics by introducing nanodomains, increasing the band gap energy and reducing the grain size.

Journal ArticleDOI
TL;DR: Li et al. as mentioned in this paper proposed a zinc-ion hybrid micro-supercapacitor (ZIHMSC) by designing a Ti3C2Tx MXene based electrode as capacitor-type anode and vanadium pentoxide (V2O5)-based electrode as battery-type cathode.

Journal ArticleDOI
TL;DR: In this article, the degradation of polystyrene (PS) in supercritical water with CO2 was studied in the temperature range of 400°C−700°C and time range of 0-30min.

Journal ArticleDOI
01 Jan 2022-Energy
TL;DR: An improved electricity price forecasting model is developed that offers the advantages of adaptive data preprocessing, advanced optimization method and kernel-based model, and optimal model selection strategy, and a newly proposed optimal models selection strategy is applied to determine the developed model that provides the most desirable forecasting result.

Journal ArticleDOI
TL;DR: In this article, the oxidation, diffusion, and mechanical properties of Cr-coated Zr alloys in normal operation conditions and accident conditions of nuclear reactors are reviewed, and the factors that cause the failure of the coating are analyzed, and some questions that need to be clarified and further studied are proposed.

Journal ArticleDOI
TL;DR: In this article , a high-performance NH4V4O10 cathode with oxygen vacancy and reduced graphene oxide surface modification is presented, which leads to high electronic conductivity, weak electrostatic interaction and low Zn2+ diffusion barrier.

Journal ArticleDOI
TL;DR: In this paper , the authors reported a high-quality and almost complete Col-0 genome assembly with two gaps (named Col-XJTU) by combining the Oxford Nanopore Technologies ultra-long reads, Pacific Biosciences high-fidelity long reads, and Hi-C data.