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  1. Article ; Online: A sudden-melting event during water freezing inside a copper well.

    Xu, WenQiang

    RSC advances

    2018  Volume 8, Issue 61, Page(s) 35257–35262

    Abstract: We studied the freezing of super-cooled water inside a millimeter-sized copper well by confocal microscopy. During freezing, we surprisingly observed a novel melting scenario, which we call a 'sudden-melting event': the ice directly above the bottom ... ...

    Abstract We studied the freezing of super-cooled water inside a millimeter-sized copper well by confocal microscopy. During freezing, we surprisingly observed a novel melting scenario, which we call a 'sudden-melting event': the ice directly above the bottom substrate suddenly melts in the late stage of the freezing process, while the system is continuously being cooled. After this event, an empty gap around 10 μm to 20 μm between the substrate and the bulk ice is formed. Because this gap occupies the majority of the area of the bottom substrate, the adhesion between the bulk ice and the substrate is greatly reduced: the adhesion force decreases by more than 50% compared with the flat-substrate situation. We further discovered that air dissolved in water plays a crucial role in this melting event: the air excluded by water freezing produces inter-connecting channels in the bulk ice, which transport the warm water produced by latent heat to the substrate which causes the sudden melting event. Because this event makes the contact between ice and substrate very poor, and greatly reduces ice adhesion, our observation may lead to a promising anti-icing method on solid substrates. Compared to the prevalent super-hydrophobic surface technique, our approach only requires millimeter-sized wells instead of complex microscopic textures. Therefore, it is much easier and cheaper to produce, as well as much more robust for large-scale practical applications.
    Language English
    Publishing date 2018-10-15
    Publishing country England
    Document type Journal Article
    ISSN 2046-2069
    ISSN (online) 2046-2069
    DOI 10.1039/c8ra06601a
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Directional Polarization of a Ferroelectric Intermediate Layer Inspires a Built-In Field in Si Anodes to Regulate Li

    Liu, Ming / Xu, Wenqiang / Liu, Shigang / Liu, Bowen / Gao, Yang / Wang, Bin

    Advanced science (Weinheim, Baden-Wurttemberg, Germany)

    2024  , Page(s) e2402915

    Abstract: The silicon (Si) anode is prone to forming a high electric field gradient and concentration gradient on the electrode surface under high-rate conditions, which may destroy the surface structure and decrease cycling stability. In this study, a ... ...

    Abstract The silicon (Si) anode is prone to forming a high electric field gradient and concentration gradient on the electrode surface under high-rate conditions, which may destroy the surface structure and decrease cycling stability. In this study, a ferroelectric (BaTiO
    Language English
    Publishing date 2024-04-19
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2808093-2
    ISSN 2198-3844 ; 2198-3844
    ISSN (online) 2198-3844
    ISSN 2198-3844
    DOI 10.1002/advs.202402915
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Learning a Contact Potential Field for Modeling the Hand-Object Interaction.

    Yang, Lixin / Zhan, Xinyu / Li, Kailin / Xu, Wenqiang / Zhang, Junming / Li, Jiefeng / Lu, Cewu

    IEEE transactions on pattern analysis and machine intelligence

    2024  Volume PP

    Abstract: Estimating and synthesizing the hand's manipulation of objects is central to understanding human behaviour. To accurately model the interaction between the hand and object (referred to as the "hand-object"), we must not only focus on the pose of the hand ...

    Abstract Estimating and synthesizing the hand's manipulation of objects is central to understanding human behaviour. To accurately model the interaction between the hand and object (referred to as the "hand-object"), we must not only focus on the pose of the hand and object, but also consider the contact between them. This contact provides valuable information for generating semantically and physically plausible grasps. In this paper, we propose an explicit contact representation called Contact Potential Field (CPF). In CPF, we model the contact between a pair of hand-object vertices as a spring-mass system. This system encodes the distance of the pair, as well as a likelihood of that contact being stable. Therefore, the system of multiple extended and compressed springs forms an elastic potential field with minimal energy at the optimal grasp position. We apply CPF to two relevant tasks, namely, hand-object pose estimation and grasping pose generation. Extensive experiments on the two challenging tasks and three commonly used datasets have demonstrated that our method can achieve state-of-the-art in several reconstruction metrics, allowing us to produce more physically plausible hand-object poses even when the ground-truth exhibits severe interpenetration or disjointedness. Our model and source codes are made publicly available at https://github.com/lixiny/CPF.
    Language English
    Publishing date 2024-03-22
    Publishing country United States
    Document type Journal Article
    ISSN 1939-3539
    ISSN (online) 1939-3539
    DOI 10.1109/TPAMI.2024.3372102
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Auto Diagnosis of Parkinson's Disease Via a Deep Learning Model Based on Mixed Emotional Facial Expressions.

    Huang, Wei / Xu, Wenqiang / Wan, Renjie / Zhang, Peng / Zha, Yufei / Pang, Meng

    IEEE journal of biomedical and health informatics

    2024  Volume 28, Issue 5, Page(s) 2547–2557

    Abstract: Parkinson's disease (PD) is a common degenerative disease of the nervous system in the elderly. The early diagnosis of PD is very important for potential patients to receive prompt treatment and avoid the aggravation of the disease. Recent studies have ... ...

    Abstract Parkinson's disease (PD) is a common degenerative disease of the nervous system in the elderly. The early diagnosis of PD is very important for potential patients to receive prompt treatment and avoid the aggravation of the disease. Recent studies have found that PD patients always suffer from emotional expression disorder, thus forming the characteristics of "masked faces". Based on this, we thus propose an auto PD diagnosis method based on mixed emotional facial expressions in the paper. Specifically, the proposed method is cast into four steps: Firstly, we synthesize virtual face images containing six basic expressions (i.e., anger, disgust, fear, happiness, sadness, and surprise) via generative adversarial learning, in order to approximate the premorbid expressions of PD patients; Secondly, we design an effective screening scheme to assess the quality of the above synthesized facial expression images and then shortlist the high-quality ones; Thirdly, we train a deep feature extractor accompanied with a facial expression classifier based on the mixture of the original facial expression images of the PD patients, the high-quality synthesized facial expression images of PD patients, and the normal facial expression images from other public face datasets; Finally, with the well-trained deep feature extractor, we thus adopt it to extract the latent expression features for six facial expression images of a potential PD patient to conduct PD/non-PD prediction. To show real-world impacts, we also collected a new facial expression dataset of PD patients in collaboration with a hospital. Extensive experiments are conducted to validate the effectiveness of the proposed method for PD diagnosis and facial expression recognition.
    MeSH term(s) Humans ; Parkinson Disease/diagnosis ; Deep Learning ; Facial Expression ; Emotions/physiology ; Image Interpretation, Computer-Assisted/methods ; Male ; Female ; Databases, Factual ; Aged
    Language English
    Publishing date 2024-05-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2695320-1
    ISSN 2168-2208 ; 2168-2194
    ISSN (online) 2168-2208
    ISSN 2168-2194
    DOI 10.1109/JBHI.2023.3239780
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Contribution of Climate Change and Grazing on Carbon Dynamics in Central Asian Pasturelands

    Li, Chaofan / Han, Qifei / Xu, Wenqiang

    Remote Sensing. 2022 Mar. 01, v. 14, no. 5

    2022  

    Abstract: Reducing the uncertainties in carbon balance assessment is essential for better pastureland management in arid areas. Climate forcing data are some of the major uncertainty sources. In this study, a modified Biome-BGC grazing model was driven by an ... ...

    Abstract Reducing the uncertainties in carbon balance assessment is essential for better pastureland management in arid areas. Climate forcing data are some of the major uncertainty sources. In this study, a modified Biome-BGC grazing model was driven by an ensemble of reanalysis data of the Climate Forecast System Reanalysis data (CFSR), the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and the Modern-Era Retrospective Analysis for Research and Applications (MERRA), to study the effect of climate change and grazing on the net ecosystem exchange (NEE) of the pasturelands in Central Asia. Afterwards, we evaluated the performance of corresponding climate datasets over four major pastureland types, and quantified the modeling uncertainty induced by climate forcing data. Our results suggest that (1) a significant positive trend in temperature and a negative trend in precipitation were obtained from the three climate datasets. The average precipitation is apparently higher in the CFSR and MERRA data, showing the highest temperature value among the data sets; (2) pasturelands in Central Asia released 2.10 ± 1.60 Pg C in the past 36 years. The highest values were obtained with the CFSR (−1.53 Pg C) and the lowest with the MERRA (−2.35 Pg C) data set; (3) without grazing effects, pasturelands in Central Asia assimilated 0.13 ± 0.06 Pg C from 1981–2014. Grazing activities dominated carbon release (100%), whereas climate changes dominated carbon assimilation (offset 6.22% of all the carbon release). This study offered possible implications to the policy makers and local herdsmen of sustainable management of pastureland and the adaptation of climate change in Central Asia.
    Keywords carbon ; carbon dioxide fixation ; climate ; climate change ; data collection ; issues and policy ; models ; net ecosystem exchange ; pastures ; retrospective studies ; temperature ; uncertainty ; Central Asia
    Language English
    Dates of publication 2022-0301
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs14051210
    Database NAL-Catalogue (AGRICOLA)

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  6. Article ; Online: Systematic analysis of glutamine metabolism family genes and exploration of the biological role of GPT in colorectal cancer.

    Dai, Weiqi / Mo, Wenhui / Xu, Wenqiang / Han, Dengyu / Xu, Xuanfu

    Aging

    2023  Volume 15, Issue 21, Page(s) 11811–11830

    Abstract: Background: Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and ... ...

    Abstract Background: Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and development of CRC. However, no research has systematically analyzed the biological role of glutamine metabolism-related genes (GMRGs) in CRC.
    Methods: We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.
    Results: A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.
    Conclusions: GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.
    MeSH term(s) Humans ; Glutamine ; Oncogenes ; Databases, Factual ; Epithelial Cells ; Colorectal Neoplasms/genetics ; Prognosis ; Tumor Microenvironment
    Chemical Substances Glutamine (0RH81L854J)
    Language English
    Publishing date 2023-10-17
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1945-4589
    ISSN (online) 1945-4589
    DOI 10.18632/aging.205079
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Cobalt-Catalyzed Enantioselective Cross-Electrophile Couplings: Stereoselective Syntheses of 5-7-Membered Azacycles.

    Ma, Zhaoming / Xu, Wenqiang / Wu, Yun-Dong / Zhou, Jianrong Steve

    Journal of the American Chemical Society

    2023  Volume 145, Issue 30, Page(s) 16464–16473

    Abstract: Cobalt complexes of chiral pyrox ligands catalyzed enantioselective reductive couplings of nonconjugated iododienes with aryl iodides or alkenyl bromides. The reaction enabled stereoselective syntheses of 5-7-membered azacycles carrying quaternary ... ...

    Abstract Cobalt complexes of chiral pyrox ligands catalyzed enantioselective reductive couplings of nonconjugated iododienes with aryl iodides or alkenyl bromides. The reaction enabled stereoselective syntheses of 5-7-membered azacycles carrying quaternary stereocenters. Mechanistically, cross-electrophile selectivity originated from selective coupling of alkylcobalt(I) complexes generated after cyclization with aryl iodides.
    Language English
    Publishing date 2023-07-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.3c02829
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Micro-Doppler Signature Detection and Recognition of UAVs Based on OMP Algorithm.

    Fan, Shiqi / Wu, Ziyan / Xu, Wenqiang / Zhu, Jiabao / Tu, Gangyi

    Sensors (Basel, Switzerland)

    2023  Volume 23, Issue 18

    Abstract: With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler characteristics of a UAV can reflect its structure and motion ...

    Abstract With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler characteristics of a UAV can reflect its structure and motion information, which provides an important reference for UAV recognition. The low flight altitude and small radar cross-section (RCS) of UAVs make the cancellation of strong ground clutter become a key problem in extracting the weak micro-Doppler signals. In this paper, a clutter suppression method based on an orthogonal matching pursuit (OMP) algorithm is proposed, which is used to process echo signals obtained by a linear frequency modulated continuous wave (LFMCW) radar. The focus of this method is on the idea of sparse representation, which establishes a complete set of environmental clutter dictionaries to effectively suppress clutter in the received echo signals of a hovering UAV. The processed signals are analyzed in the time-frequency domain. According to the flicker phenomenon of UAV rotor blades and related micro-Doppler characteristics, the feature parameters of unknown UAVs can be estimated. Compared with traditional signal processing methods, the method based on OMP algorithm shows advantages in having a low signal-to-noise ratio (-10 dB). Field experiments indicate that this approach can effectively reduce clutter power (-15 dB) and successfully extract micro-Doppler signals for identifying different UAVs.
    Language English
    Publishing date 2023-09-15
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s23187922
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Bidirectional visual-tactile cross-modal generation using latent feature space flow model.

    Fang, Yu / Zhang, Xuehe / Xu, Wenqiang / Liu, Gangfeng / Zhao, Jie

    Neural networks : the official journal of the International Neural Network Society

    2023  Volume 172, Page(s) 106088

    Abstract: Inspired by visual-tactile cross-modal bidirectional mapping of the human brain, this paper introduces a novel approach to bidirectional mapping between visual and tactile data, an area not fully explored in the predominantly unidirectional existing ... ...

    Abstract Inspired by visual-tactile cross-modal bidirectional mapping of the human brain, this paper introduces a novel approach to bidirectional mapping between visual and tactile data, an area not fully explored in the predominantly unidirectional existing studies. First, we adopt separate Variational AutoEncoder (VAE) models for visual and tactile data. Furthermore, we introduce a conditional flow model built on the VAE latent feature space, enabling cross-modal bidirectional mapping between visual and tactile data using one model. The experimental results show that our method achieves excellent performance in terms of the similarity between the generated data and the original data (Structural Similarity Index (SSIM) of visual data: 0.58, SSIM of tactile data: 0.80), the classification accuracy on generated data (visual data: 91.60%, tactile data: 88.05%), and the zero-shot classification accuracy between generated data and language (visual data: 44.49%, tactile data: 45.03%). To the best of our knowledge, the method proposed in this paper is the first one to utilize a single model to achieve bidirectional mapping between visual and tactile data. Our model and code will be made public after the acceptance of the paper.
    MeSH term(s) Humans ; Touch ; Brain ; Brain Mapping/methods
    Language English
    Publishing date 2023-12-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 740542-x
    ISSN 1879-2782 ; 0893-6080
    ISSN (online) 1879-2782
    ISSN 0893-6080
    DOI 10.1016/j.neunet.2023.12.042
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Inhibition Effect and Mechanism Explanation of Perilla Seed Extract as a Green Corrosion Inhibitor on Q235 Carbon Steel.

    Li, Yu / Xu, Wenqiang / Lai, Jiayu / Qiang, Sheng

    Materials (Basel, Switzerland)

    2022  Volume 15, Issue 15

    Abstract: The development of environmentally friendly corrosion inhibitors has become a research hotspot. Aiming at the potential corrosion inhibition effect of perilla seed extract on Q235 carbon steel, the corrosion inhibition effect was quantitatively evaluated ...

    Abstract The development of environmentally friendly corrosion inhibitors has become a research hotspot. Aiming at the potential corrosion inhibition effect of perilla seed extract on Q235 carbon steel, the corrosion inhibition effect was quantitatively evaluated by various research methods, and the effective corrosion inhibition composition and mechanism were discussed. The research methods include potentiodynamic polarization curve method, HPLC-MS, FT-IR, XPS and chemical calculation. The experimental results show that the inhibitor prepared from perilla seed extract is a mixed inhibitor, and its adsorption behavior accords with Langmuir adsorption theory and its adsorption free energy is -22.70 kJ/mol. Combined with the experimental results and theoretical calculation, the effective corrosion inhibiting components are luteolin and apigenin. Theoretical calculation shows that both of them are adsorbed parallel to the surface of carbon steel to form thin films. The adsorption mechanism is that carbonyl O atoms in luteolin and apigenin hybridize with the 3 d empty orbit of Fe. From the point of view of quantum chemistry, the smaller the HOMO value and the energy gap value, the better the adsorption of corrosion inhibitor on the surface of carbon steel. From the point of view of molecular dynamics simulation, the greater the absolute value of adsorption energy, the better the adsorption of corrosion inhibitor on carbon steel surface.
    Language English
    Publishing date 2022-08-05
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2487261-1
    ISSN 1996-1944
    ISSN 1996-1944
    DOI 10.3390/ma15155394
    Database MEDical Literature Analysis and Retrieval System OnLINE

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