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  1. Article ; Online: Editorial: The relationship of oral and other body sites microbiome in human diseases.

    Xu, Tiansong / Chen, Ning / He, Xuesong / Chen, Feng

    Frontiers in cellular and infection microbiology

    2023  Volume 13, Page(s) 1276473

    Language English
    Publishing date 2023-08-23
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2619676-1
    ISSN 2235-2988 ; 2235-2988
    ISSN (online) 2235-2988
    ISSN 2235-2988
    DOI 10.3389/fcimb.2023.1276473
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Solidification/Stabilization of Chromium-Contaminated Soils by Polyurethane during Freeze-Thaw Cycles: Mechanical, Leaching and Microstructure Characterization.

    Ma, Qiang / Zheng, Pangkun / Chen, Junjie / Lu, Xuesong

    Materials (Basel, Switzerland)

    2024  Volume 17, Issue 6

    Abstract: The treatment of chromium-contaminated soil in seasonal frozen soil areas has been the subject of recent interest. Polyurethane (PU), as a polymer material with excellent freeze-thaw resistance and abrasion resistance, has the potential to solidify ... ...

    Abstract The treatment of chromium-contaminated soil in seasonal frozen soil areas has been the subject of recent interest. Polyurethane (PU), as a polymer material with excellent freeze-thaw resistance and abrasion resistance, has the potential to solidify Chromium-Contaminated soil in seasonal frozen soil areas. However, there is a lack of research on the mechanism of PU involved in solidifying/stabilizing chromium-contaminated soil in seasonal frozen regions from the perspective of pore structure and functional group coordination bonds. In this study, the leaching behavior of PU with different contents under different freeze-thaw cycles was analyzed, and the mechanism of PU in seasonal frozen regions was explored from the perspective of pores and functional groups by combining various microscopic characterization methods. The results show that PU can effectively resist the deterioration of chromium-contaminated soil after freeze-thaw cycles and can better prevent the harm of secondary leaching. The leaching concentration of chromium ion is only 1.09 mg/L, which is below China's regulatory limits. PU is beneficial for inhibiting the expansion of ice crystals in chromium-contaminated soil in seasonal frozen soil areas. PU solidifies chromium by physical encapsulation and complexation reactions. The amide functional groups, methyl-CH
    Language English
    Publishing date 2024-03-15
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2487261-1
    ISSN 1996-1944
    ISSN 1996-1944
    DOI 10.3390/ma17061347
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: SSCFormer: Revisiting ConvNet-Transformer Hybrid Framework from Scale-Wise and Spatial-Channel-Aware Perspectives for Volumetric Medical Image Segmentation.

    Xie, Qinlan / Chen, Yong / Liu, Shenglin / Lu, Xuesong

    IEEE journal of biomedical and health informatics

    2024  Volume PP

    Abstract: Accurate and robust medical image segmentation is crucial for assisting disease diagnosis, making treatment plan, and monitoring disease progression. Adaptive to different scale variations and regions of interest is essential for high accuracy in ... ...

    Abstract Accurate and robust medical image segmentation is crucial for assisting disease diagnosis, making treatment plan, and monitoring disease progression. Adaptive to different scale variations and regions of interest is essential for high accuracy in automatic segmentation methods. Existing methods based on the U-shaped architecture respectively tackling intra- and inter-scale problem with a hierarchical encoder, however, are restricted by the scope of multi-scale modeling. In addition, global attention and scaling attention in regions of interest have not been appropriately adopted, especially for the salient features. To address these two issues, we propose a ConvNet-Transformer hybrid framework named SSCFormer for accurate and versatile medical image segmentation. The intra-scale ResInception and inter-scale transformer bridge are designed to collaboratively capture the intra- and inter-scale features, facilitating the interaction of small-scale disparity information at a single stage with large-scale from multiple stages. Global attention and scaling attention are cleverly integrated from a spatial-channel-aware perspective. The proposed SSCFormer is tested on four different medical image segmentation tasks. Comprehensive experimental results show that SSCFormer outperforms the current state-of-the-art methods.
    Language English
    Publishing date 2024-04-22
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2695320-1
    ISSN 2168-2208 ; 2168-2194
    ISSN (online) 2168-2208
    ISSN 2168-2194
    DOI 10.1109/JBHI.2024.3392488
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5483: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  4. Article ; Online: Identification and classification of surface defects for digital twin models of the workpiece.

    Qu, Ligang / Huang, Xuesong / Zhang, Danya / Chen, Zeng

    PloS one

    2024  Volume 19, Issue 4, Page(s) e0302419

    Abstract: Workpiece surface defect detection is an indispensable part of intelligent production. The surface information obtained by traditional 2D image detection has some limitations due to the influence of environmental light factors and part complexity. ... ...

    Abstract Workpiece surface defect detection is an indispensable part of intelligent production. The surface information obtained by traditional 2D image detection has some limitations due to the influence of environmental light factors and part complexity. However, the digital twin model has the characteristics of high fidelity and scalability, and the digital twin surface can be obtained by a device with a scanning accuracy of 0.02mm to achieve the representation of the real surface of the workpiece. The surface defect detection system for digital twin models is proposed based on the improved YOLOv5 model in this paper. Firstly, the digital twin model of the workpiece is reconstructed by the point cloud data obtained by the scanning device, and the surface features with defects are captured. Subsequently, the training dataset is calibrated based on the defect surface, where the defect types include Inclusion, Perforation, pitting surface and Rolled-in scale. Finally, the improved YOLOv5 model with CBAM mechanism and BiFPN module was used to identify the surface defects of the digital twin model and compare it with the original YOLOv5 model and other common models. The results show that the improved YOLOv5 model can realize the identification and classification of surface defects. Compared with the original YOLOv5 model, the mAP value of the improved YOLOv5 model has increased by 0.2%, and the model has high precision. On the basis of the same data set, the improved YOLOv5 model has higher recognition accuracy than other models, improving 11.7%, 3.4%, 6.2%, 33.5%, respectively. As a result, this study provides a practical and systematic detection method for digital twin model surface during the intelligent production process, and realizes the rapid screening of the workpiece with defects.
    MeSH term(s) Surface Properties ; Image Processing, Computer-Assisted/methods ; Humans ; Models, Theoretical ; Algorithms
    Language English
    Publishing date 2024-04-30
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0302419
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Diversity and Abundance of Bacterial and Fungal Communities Inhabiting

    Qu, Hao / Long, Yaqin / Wang, Xuesong / Wang, Kaibo / Chen, Long / Yang, Yunqiu / Chen, Linbo

    Microorganisms

    2023  Volume 11, Issue 9

    Abstract: Agriophara ... ...

    Abstract Agriophara rhombata
    Language English
    Publishing date 2023-08-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2720891-6
    ISSN 2076-2607
    ISSN 2076-2607
    DOI 10.3390/microorganisms11092188
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Correction: Caffeine blocks disruption of blood brain barrier in a rabbit model of Alzheimer's disease.

    Chen, Xuesong / Gawryluk, Jeremy W / Wagener, John F / Ghribi, Othman / Geiger, Jonathan D

    Journal of neuroinflammation

    2023  Volume 20, Issue 1, Page(s) 40

    Language English
    Publishing date 2023-02-18
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2156455-3
    ISSN 1742-2094 ; 1742-2094
    ISSN (online) 1742-2094
    ISSN 1742-2094
    DOI 10.1186/s12974-023-02725-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: [Investigation on the addition of dietary fiber in infant and follow-up formula in China from 2017 to 2022].

    Yang, Jingming / Wang, Xin / Chen, Huihui / Wang, Guodong / Zhang, Xuesong / Xiang, Xuesong

    Wei sheng yan jiu = Journal of hygiene research

    2023  Volume 52, Issue 3, Page(s) 407–411

    Abstract: Objective: To investigate the addition of dietary fiber in infant formula approved in recent 5 years.: Methods: A total of 1438 infant formula milk powder approved in China from January 2017 to June 2022 were collected and the addition rate, content ... ...

    Abstract Objective: To investigate the addition of dietary fiber in infant formula approved in recent 5 years.
    Methods: A total of 1438 infant formula milk powder approved in China from January 2017 to June 2022 were collected and the addition rate, content and mixture of dietary fiber components such as galactooligosaccharide(FOS), fructooligosaccharide(GOS), polyfructose, polyglucose, raffinose and yeast β-dextran were statistically analyzed.
    Results: Among the 1438 infant formulas, 84.07%(1209) were added with dietary fiber, and the addition rate increased yearly. Among them, the addition rate of GOS(79.82%) and FOS(79.74%) was the highest, and the median amount of dietary fiber components was 3.00 g/100 g. Among the products added with various dietary fiber components, there were 762 products added with GOS and FOS, The addition ratios of GOS and FOS were mainly concentrated at 1∶1.
    Conclusion: The addition rate of dietary fiber in infant formula milk powder in China is constantly increasing, however there are large differences in the addition amount, dietary fiber combination and proportion of different products.
    MeSH term(s) Humans ; Infant ; Powders ; Follow-Up Studies ; Infant Formula ; Dietary Fiber ; China
    Chemical Substances Powders ; Dietary Fiber
    Language Chinese
    Publishing date 2023-07-27
    Publishing country China
    Document type English Abstract ; Journal Article
    ZDB-ID 1050909-4
    ISSN 1000-8020
    ISSN 1000-8020
    DOI 10.19813/j.cnki.weishengyanjiu.2023.03.012
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4878: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Dual Parallel Policy Iteration With Coupled Policy Improvement.

    Cheng, Yuhu / Huang, Longyang / Chen, C L Philip / Wang, Xuesong

    IEEE transactions on neural networks and learning systems

    2024  Volume 35, Issue 3, Page(s) 4286–4298

    Abstract: In this article, a novel coupled policy improvement mechanism is developed for improving policy iteration (PI) algorithms. In contrast to the common PI, the developed dual parallel policy iteration (DPPI) with coupled policy improvement mechanism ... ...

    Abstract In this article, a novel coupled policy improvement mechanism is developed for improving policy iteration (PI) algorithms. In contrast to the common PI, the developed dual parallel policy iteration (DPPI) with coupled policy improvement mechanism consists of two parallel PIs. At each PI step, the performances of the two parallel policies are evaluated and the better one is defined as the dominant policy. Then, the dominant policy is used to guide the parallel policy improvement in a soft manner by constraining the Kullback-Liebler (KL) divergence between the dominant policy and the policy to be updated. It is proven that the convergence of DPPI can be guaranteed under the designed coupled policy improvement mechanism. Moreover, it is clearly shown that under certain conditions, the Q -functions of the two new policies obtained in each parallel policy improvement are larger than those of all the previous dominant policies, which is conductive to accelerate the PI process and improve the policy learning efficiency to some extent. Furthermore, by combining DPPI with the twin delay deep deterministic (TD3) policy gradient, we propose a reinforcement learning (RL) algorithm: parallel TD3 (PTD3). Experimental results on continuous-action control tasks in the MuJoCo and OpenAI Gym platforms show that the proposed PTD3 outperforms the state-of-the-art RL algorithms.
    Language English
    Publishing date 2024-02-29
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2022.3202192
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Artificial intelligence for drug discovery: Resources, methods, and applications.

    Chen, Wei / Liu, Xuesong / Zhang, Sanyin / Chen, Shilin

    Molecular therapy. Nucleic acids

    2023  Volume 31, Page(s) 691–702

    Abstract: Conventional wet laboratory testing, validations, and synthetic procedures are costly and time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques have revolutionized their applications to drug discovery. Combined with ... ...

    Abstract Conventional wet laboratory testing, validations, and synthetic procedures are costly and time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques have revolutionized their applications to drug discovery. Combined with accessible data resources, AI techniques are changing the landscape of drug discovery. In the past decades, a series of AI-based models have been developed for various steps of drug discovery. These models have been used as complements of conventional experiments and have accelerated the drug discovery process. In this review, we first introduced the widely used data resources in drug discovery, such as ChEMBL and DrugBank, followed by the molecular representation schemes that convert data into computer-readable formats. Meanwhile, we summarized the algorithms used to develop AI-based models for drug discovery. Subsequently, we discussed the applications of AI techniques in pharmaceutical analysis including predicting drug toxicity, drug bioactivity, and drug physicochemical property. Furthermore, we introduced the AI-based models for de novo drug design, drug-target structure prediction, drug-target interaction, and binding affinity prediction. Moreover, we also highlighted the advanced applications of AI in drug synergism/antagonism prediction and nanomedicine design. Finally, we discussed the challenges and future perspectives on the applications of AI to drug discovery.
    Language English
    Publishing date 2023-02-18
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2662631-7
    ISSN 2162-2531
    ISSN 2162-2531
    DOI 10.1016/j.omtn.2023.02.019
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Fitting of Growth Curves and Estimation of Genetic Relationship between Growth Parameters of Qianhua Mutton Merino.

    Li, Jiarong / Shan, Xuesong / Chen, Yang / Xu, Chongshun / Tang, Lin / Jiang, Huaizhi

    Genes

    2024  Volume 15, Issue 3

    Abstract: Qianhua Mutton Merino is a dual-purpose (meat and wool) breed of sheep that has been newly developed in China. In this study, we assessed the growth and development of the Qianhua Mutton Merino sheep breed under house feeding conditions by measuring the ... ...

    Abstract Qianhua Mutton Merino is a dual-purpose (meat and wool) breed of sheep that has been newly developed in China. In this study, we assessed the growth and development of the Qianhua Mutton Merino sheep breed under house feeding conditions by measuring the body weight and chest circumference of 2300 rams and ewes of this breed aged 0-24 months. Based on the fitting results of three nonlinear growth models, namely Logistic, Gompertz, and von Bertalanffy, in Qianhua Mutton Merino, we selected the von Bertalanffy model because of its highest fitting degree among all models (R
    MeSH term(s) Sheep/genetics ; Animals ; Male ; Female ; Sheep, Domestic ; Red Meat ; Body Weight/genetics ; Phenotype ; Meat
    Language English
    Publishing date 2024-03-21
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527218-4
    ISSN 2073-4425 ; 2073-4425
    ISSN (online) 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes15030390
    Database MEDical Literature Analysis and Retrieval System OnLINE

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