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  1. Article ; Online: Target Parameter Estimation Algorithm Based on Real-Valued HOSVD for Bistatic FDA-MIMO Radar

    Yuehao Guo / Xianpeng Wang / Jinmei Shi / Lu Sun / Xiang Lan

    Remote Sensing, Vol 15, Iss 1192, p

    2023  Volume 1192

    Abstract: Since there is a frequency offset between each adjacent antenna of FDA radar, there exists angle-range two-dimensional dependence in the transmitter. For bistatic FDA-multiple input multiple output (MIMO) radar, range-direction of departure (DOD)- ... ...

    Abstract Since there is a frequency offset between each adjacent antenna of FDA radar, there exists angle-range two-dimensional dependence in the transmitter. For bistatic FDA-multiple input multiple output (MIMO) radar, range-direction of departure (DOD)-direction of arrival (DOA) information is coupled in transmitting the steering vector. How to decouple the three information has become the focus of research. Aiming at the issue of target parameter estimation of bistatic FDA-MIMO radar, a real-valued parameter estimation algorithm based on high-order-singular value decomposition (HOSVD) is developed. Firstly, for decoupling DOD and range in transmitter, it is necessary to divide the transmitter into subarrays. Then, the forward–backward averaging and unitary transformation techniques are utilized to convert complex-valued data into real-valued data. The signal subspace is obtained by HOSVD, and the two-dimensional spatial spectral function is constructed. Secondly, the dimension of spatial spectrum is reduced by the Lagrange algorithm, so that it is only related to DOA, and the DOA estimation is obtained. Then the frequency increment between subarrays is used to decouple the DOD and range information, and eliminate the phase ambiguity at the same time. Finally, the DOD and range estimation automatically matched with DOA estimation are obtained. The proposed algorithm uses the multidimensional structure of high-dimensional data to promote performance. Meanwhile, the proposed real-valued tensor-based method can effectively cut down the computing time. Simulation results verify the high efficiency of the developed method.
    Keywords bistatic FDA-MIMO radar ; unitary transformation technique ; HOSVD ; DOA-DOD-range estimation ; Science ; Q
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: CTNNAL1 promotes the structural integrity of bronchial epithelial cells through the RhoA/ROCK1 pathway.

    Liu, Caixia / Wang, Jinmei / Tan, Yurong / Liu, Chi / Qu, Xiangping / Liu, Huijun / Tan, Meiling / Deng, Changqing / Qin, Xiaoqun / Xiang, Yang

    Acta biochimica et biophysica Sinica

    2024  

    Abstract: Adhesion molecules play critical roles in maintaining the structural integrity of the airway epithelium in airways under stress. Previously, we reported that catenin alpha-like 1 (CTNNAL1) is downregulated in an asthma animal model and upregulated at the ...

    Abstract Adhesion molecules play critical roles in maintaining the structural integrity of the airway epithelium in airways under stress. Previously, we reported that catenin alpha-like 1 (CTNNAL1) is downregulated in an asthma animal model and upregulated at the edge of human bronchial epithelial cells (HBECs) after ozone stress. In this work, we explore the potential role of CTNNAL1 in the structural adhesion of HBECs and its possible mechanism. We construct a CTNNAL1
    Language English
    Publishing date 2024-04-11
    Publishing country China
    Document type Journal Article
    ZDB-ID 2175256-4
    ISSN 1745-7270 ; 0582-9879 ; 1672-9145
    ISSN (online) 1745-7270
    ISSN 0582-9879 ; 1672-9145
    DOI 10.3724/abbs.2024026
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: A Fast PARAFAC Algorithm for Parameter Estimation in Monostatic FDA-MIMO Radar

    Wenshuai Wang / Xiang Lan / Jinmei Shi / Xianpeng Wang

    Remote Sensing, Vol 14, Iss 13, p

    2022  Volume 3093

    Abstract: This paper studies the joint range and angle estimation of monostatic frequency diverse array multiple-input multiple-output (FDA-MIMO) radar and proposes a joint estimation algorithm. First, the transmit direction matrix is converted into real values by ...

    Abstract This paper studies the joint range and angle estimation of monostatic frequency diverse array multiple-input multiple-output (FDA-MIMO) radar and proposes a joint estimation algorithm. First, the transmit direction matrix is converted into real values by unitary transformation, and the Vandermonde-like matrix structure is used to construct an augmented output that doubles the aperture of the receive array. Then the augmented output is combined into a third-order tensor. Next, the factor matrices are initially estimated. Finally, the direction matrices are estimated utilizing parallel factor (PARAFAC) decomposition, and the range and angle are calculated by employing least square fitting. As contrasted with the classic PARAFAC method, the proposed method can estimate more targets and provide better estimation performance, and requires less computational complexity. The availability and excellence of the proposed method are reflected by numerical simulations and complexity analysis.
    Keywords monostatic FDA-MIMO radar ; augmented output ; parameter estimation ; PARAFAC decomposition ; Science ; Q
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Joint Angle and Range Estimation in Monostatic FDA-MIMO Radar via Compressed Unitary PARAFAC

    Wenshuai Wang / Xianpeng Wang / Jinmei Shi / Xiang Lan

    Remote Sensing, Vol 14, Iss 1398, p

    2022  Volume 1398

    Abstract: In this paper, we study the joint range and angle estimation problem based in monostatic frequency diverse-array multiple-input multiple-output (FDA-MIMO) radar, and propose a method for range and angle estimation base on compressed unitary parallel ... ...

    Abstract In this paper, we study the joint range and angle estimation problem based in monostatic frequency diverse-array multiple-input multiple-output (FDA-MIMO) radar, and propose a method for range and angle estimation base on compressed unitary parallel factor (PARAFAC). First, the received complex signal matrix is stacked into a third-order complex signal tensor. Then, we can transform the obtained third-order complex signal tensor into a third-order real-valued signal tensor by employing forward–backward and unitary transformation techniques. Next, a smaller third-order real-valued signal tensor is composed by using compressing the third-order real-valued signal tensor. After that, PARAFAC decomposition is applied to obtain the direction matrix. Lastly, the angle and range are estimated by employing the least square (LS) fitting. The estimation error of the proposed method is about <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>10</mn><mo>%</mo></mrow></semantics></math> lower than that of the traditional PARAFAC method under the low number of snapshots. When the number of snapshots is high, the performance of the two methods is close. Moreover, the computational complexity of the proposed method is nearly <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>96</mn><mo>%</mo></mrow></semantics></math> less than those of the traditional PARAFAC methods in the case of low snapshots, while the gap is larger in the case of high snapshots. The superiority and effectiveness of the method are proved by complexity analysis and simulation experiments.
    Keywords real-valued tensor ; tensor compression ; unitary transformation ; FDA-MIMO radar ; PARAFAC decomposition ; angle estimation ; Science ; Q
    Subject code 511
    Language English
    Publishing date 2022-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: Risk Factors and Prognosis in Patients With Anti-N-Methyl-D-Aspartate Receptor Encephalitis Requiring Prolonged Mechanical Ventilation.

    Lin, Jingfang / Xiang, Qu / Liu, Xu / Li, Jinmei

    Frontiers in neurology

    2022  Volume 13, Page(s) 814673

    Abstract: Background: Mechanical ventilation (MV) is commonly used in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients with serious conditions. However, little is known about the potential risk factors and long-term outcomes of anti-NMDAR ... ...

    Abstract Background: Mechanical ventilation (MV) is commonly used in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients with serious conditions. However, little is known about the potential risk factors and long-term outcomes of anti-NMDAR encephalitis requiring MV, especially prolonged MV.
    Methods: The data collected prospectively from 305 patients with anti-NMDAR encephalitis were retrospectively reviewed. The functional outcome was assessed using a modified Rankin scale (mRS) every 3 months.
    Results: We identified 62 (20.3%) patients who required MV. The most common reasons for MV were decreased consciousness and/or status epilepticus (SE). Among 60 patients analyzed, 27 patients required prolonged MV (>15 days). Prolonged MV primarily was based on the younger age, coma, tumor, and severe pneumonia. During the follow-up (median: 28 months, range: 3-87 months), 77% of patients required MV that exhibited a good outcome. In univariate analysis, prolonged MV, higher levels of C-reactive protein (CRP), and neutrophil-to-lymphocyte ratio (NLR) were found to be associated with poor neurological outcome at 6 months. Although the prolonged MV group exhibited a longer time to achieve a good outcome as compared to the short MV group (median duration 6 months vs. 3 months,
    Conclusion: It is important to recognize that most anti-NMDAR encephalitis patients who required MV will achieve a favorable long-term outcomes, despite the longer duration of MV. Our results may help clinicians in the ventilator management of severe anti-NMDAR encephalitis patients.
    Language English
    Publishing date 2022-02-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2564214-5
    ISSN 1664-2295
    ISSN 1664-2295
    DOI 10.3389/fneur.2022.814673
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: A Fast PARAFAC Algorithm for Parameter Estimation in Monostatic FDA-MIMO Radar

    Wang, Wenshuai / Lan, Xiang / Shi, Jinmei / Wang, Xianpeng

    Remote Sensing. 2022 June 27, v. 14, no. 13

    2022  

    Abstract: This paper studies the joint range and angle estimation of monostatic frequency diverse array multiple-input multiple-output (FDA-MIMO) radar and proposes a joint estimation algorithm. First, the transmit direction matrix is converted into real values by ...

    Abstract This paper studies the joint range and angle estimation of monostatic frequency diverse array multiple-input multiple-output (FDA-MIMO) radar and proposes a joint estimation algorithm. First, the transmit direction matrix is converted into real values by unitary transformation, and the Vandermonde-like matrix structure is used to construct an augmented output that doubles the aperture of the receive array. Then the augmented output is combined into a third-order tensor. Next, the factor matrices are initially estimated. Finally, the direction matrices are estimated utilizing parallel factor (PARAFAC) decomposition, and the range and angle are calculated by employing least square fitting. As contrasted with the classic PARAFAC method, the proposed method can estimate more targets and provide better estimation performance, and requires less computational complexity. The availability and excellence of the proposed method are reflected by numerical simulations and complexity analysis.
    Keywords algorithms ; least squares ; methodology ; radar ; remote sensing ; simulation models
    Language English
    Dates of publication 2022-0627
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs14133093
    Database NAL-Catalogue (AGRICOLA)

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  7. Article: Joint Angle and Range Estimation in Monostatic FDA-MIMO Radar via Compressed Unitary PARAFAC

    Wang, Wenshuai / Wang, Xianpeng / Shi, Jinmei / Lan, Xiang

    Remote Sensing. 2022 Mar. 14, v. 14, no. 6

    2022  

    Abstract: In this paper, we study the joint range and angle estimation problem based in monostatic frequency diverse-array multiple-input multiple-output (FDA-MIMO) radar, and propose a method for range and angle estimation base on compressed unitary parallel ... ...

    Abstract In this paper, we study the joint range and angle estimation problem based in monostatic frequency diverse-array multiple-input multiple-output (FDA-MIMO) radar, and propose a method for range and angle estimation base on compressed unitary parallel factor (PARAFAC). First, the received complex signal matrix is stacked into a third-order complex signal tensor. Then, we can transform the obtained third-order complex signal tensor into a third-order real-valued signal tensor by employing forward–backward and unitary transformation techniques. Next, a smaller third-order real-valued signal tensor is composed by using compressing the third-order real-valued signal tensor. After that, PARAFAC decomposition is applied to obtain the direction matrix. Lastly, the angle and range are estimated by employing the least square (LS) fitting. The estimation error of the proposed method is about 10% lower than that of the traditional PARAFAC method under the low number of snapshots. When the number of snapshots is high, the performance of the two methods is close. Moreover, the computational complexity of the proposed method is nearly 96% less than those of the traditional PARAFAC methods in the case of low snapshots, while the gap is larger in the case of high snapshots. The superiority and effectiveness of the method are proved by complexity analysis and simulation experiments.
    Keywords least squares ; methodology ; radar ; remote sensing ; simulation models
    Language English
    Dates of publication 2022-0314
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs14061398
    Database NAL-Catalogue (AGRICOLA)

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  8. Article: A preliminary study of the chemical composition and bioactivity of

    Yin, Kehong / Yang, Jinmei / Wang, Fang / Wang, Zhenxing / Xiang, Ping / Xie, Xing / Sun, Jian / He, Xuemei / Zhang, Xuechun

    Frontiers in nutrition

    2022  Volume 9, Page(s) 1018733

    Abstract: This study aimed to preliminary investigate the phytochemistry, bioactivity, hypoglycemic potential, and mechanism of action ... ...

    Abstract This study aimed to preliminary investigate the phytochemistry, bioactivity, hypoglycemic potential, and mechanism of action of
    Language English
    Publishing date 2022-10-13
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2776676-7
    ISSN 2296-861X
    ISSN 2296-861X
    DOI 10.3389/fnut.2022.1018733
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Multi-Target Parameter Estimation of the FMCW-MIMO Radar Based on the Pseudo-Noise Resampling Method.

    Jiang, Yao / Lan, Xiang / Shi, Jinmei / Han, Zhiguang / Wang, Xianpeng

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 24

    Abstract: Subspace methods are widely used in FMCW-MIMO radars for target parameter estimations. However, the performances of the existing algorithms degrade rapidly in non-ideal situations. For example, a small number of snapshots may result in the distortion of ... ...

    Abstract Subspace methods are widely used in FMCW-MIMO radars for target parameter estimations. However, the performances of the existing algorithms degrade rapidly in non-ideal situations. For example, a small number of snapshots may result in the distortion of the covariance matrix estimation and a low signal-to-noise ratio (SNR) can lead to subspace leakage problems, which affects the parameter estimation accuracy. In this paper, a joint DOA-range estimation algorithm is proposed to solve the above issues. Firstly, the improved unitary root-MUSIC algorithm is applied to reduce the influence of non-ideal terms in building the covariance matrix. Subsequently, the least squares method is employed to process the data and obtain paired range estimation. However, in a small number of snapshots and low SNR scenarios, even if the impact of non-ideal terms is reduced, there will still be cases where the estimators sometimes deviate from the true target. The estimators that deviate greatly from targets are regarded as outliers. Therefore, threshold detection is applied to determine whether outliers exist. After that, a pseudo-noise resampling (PR) technology is proposed to form a new data observation matrix, which further alleviates the error of the estimators. The proposed method overcomes performance degradation in a small number of snapshots or low SNRs simultaneously. Theoretical analyses and simulation results demonstrate the effectiveness and superiority.
    Language English
    Publishing date 2022-12-11
    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/s22249706
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Comprehensive Analysis of the Relationships Between the Gut Microbiota and Fecal Metabolome in Individuals With Primary Sjogren's Syndrome by 16S rRNA Sequencing and LC-MS-Based Metabolomics.

    Yang, Li / Xiang, Zhao / Zou, Jinmei / Zhang, Yu / Ni, Yuanpiao / Yang, Jing

    Frontiers in immunology

    2022  Volume 13, Page(s) 874021

    Abstract: The gut microbiota has been associated with primary Sjogren's syndrome (pSS), yet the biological implications of these associations are often elusive. We analyzed the fecal microbiota through 16S rRNA gene amplification and sequencing in 30 patients with ...

    Abstract The gut microbiota has been associated with primary Sjogren's syndrome (pSS), yet the biological implications of these associations are often elusive. We analyzed the fecal microbiota through 16S rRNA gene amplification and sequencing in 30 patients with pSS and 20 healthy controls (HCs); At the same time, the fecal metabolome was characterized by ultrahigh-performance liquid chromatography-mass spectrometry. In addition, correlation analyses of microbiota and metabolome data were performed to identify meaningful associations. We found that the microbiota composition of pSS patients was significantly different from that of HCs. The pSS gut microbiota is characterized by increased abundances of proinflammatory microbes, especially
    MeSH term(s) Amino Acids ; Chromatography, Liquid ; Gastrointestinal Microbiome/genetics ; Humans ; Metabolome ; Metabolomics/methods ; RNA, Ribosomal, 16S/genetics ; Sjogren's Syndrome ; Tandem Mass Spectrometry
    Chemical Substances Amino Acids ; RNA, Ribosomal, 16S
    Language English
    Publishing date 2022-05-11
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2606827-8
    ISSN 1664-3224 ; 1664-3224
    ISSN (online) 1664-3224
    ISSN 1664-3224
    DOI 10.3389/fimmu.2022.874021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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