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  1. Article ; Online: Chinese technical terminology extraction based on DC-value and information entropy.

    Liwei, Zhang

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 20044

    Abstract: China's technology is developing rapidly, and the number of patent applications has surged. Therefore, there is an urgent need for technical managers and researchers that how to apply computer technology to conduct in-depth mining and analysis of lots of ...

    Abstract China's technology is developing rapidly, and the number of patent applications has surged. Therefore, there is an urgent need for technical managers and researchers that how to apply computer technology to conduct in-depth mining and analysis of lots of Chinese patent documents to efficiently use patent information, perform technological innovation and avoid R&D risks. Automatic term extraction is the basis of patent mining and analysis, but many existing approaches focus on extracting domain terms in English, which are difficult to extend to Chinese due to the distinctions between Chinese and English languages. At the same time, some common Chinese technical terminology extraction methods focus on the high-frequency characteristics, while technical domain correlation characteristic and the unithood feature of terminology are given less attention. Aiming at these problems, this paper proposes a Chinese technical terminology method based on DC-value and information entropy to achieve automatic extraction of technical terminology in Chinese patents. The empirical results show that the presented algorithm can effectively extract the technical terminology in Chinese patent literatures and has a better performance than the C-value method, the log-likelihood ratio method and the mutual information method, which has theoretical significance and practical application value.
    MeSH term(s) Entropy ; Language ; Technology ; Inventions ; China
    Language English
    Publishing date 2022-11-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-23209-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Chinese technical terminology extraction based on DC-value and information entropy

    Zhang Liwei

    Scientific Reports, Vol 12, Iss 1, Pp 1-

    2022  Volume 12

    Abstract: Abstract China's technology is developing rapidly, and the number of patent applications has surged. Therefore, there is an urgent need for technical managers and researchers that how to apply computer technology to conduct in-depth mining and analysis ... ...

    Abstract Abstract China's technology is developing rapidly, and the number of patent applications has surged. Therefore, there is an urgent need for technical managers and researchers that how to apply computer technology to conduct in-depth mining and analysis of lots of Chinese patent documents to efficiently use patent information, perform technological innovation and avoid R&D risks. Automatic term extraction is the basis of patent mining and analysis, but many existing approaches focus on extracting domain terms in English, which are difficult to extend to Chinese due to the distinctions between Chinese and English languages. At the same time, some common Chinese technical terminology extraction methods focus on the high-frequency characteristics, while technical domain correlation characteristic and the unithood feature of terminology are given less attention. Aiming at these problems, this paper proposes a Chinese technical terminology method based on DC-value and information entropy to achieve automatic extraction of technical terminology in Chinese patents. The empirical results show that the presented algorithm can effectively extract the technical terminology in Chinese patent literatures and has a better performance than the C-value method, the log-likelihood ratio method and the mutual information method, which has theoretical significance and practical application value.
    Keywords Medicine ; R ; Science ; Q
    Subject code 020
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Combination of tenuigenin-based

    Liang, Guocui / Gao, Chengxia / Zhang, Liwei / Du, Huizhi

    Natural product research

    2024  , Page(s) 1–5

    Abstract: Tenuigenin is a kind of the main active ingredients in roots ... ...

    Abstract Tenuigenin is a kind of the main active ingredients in roots of
    Language English
    Publishing date 2024-03-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2185747-7
    ISSN 1478-6427 ; 1478-6419
    ISSN (online) 1478-6427
    ISSN 1478-6419
    DOI 10.1080/14786419.2024.2332945
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A commentary on 'Salvage surgeries for splanchnic artery aneurysms after failed endovascular therapy: case series'.

    Yu, Long / Xia, Qian / Su, Feng / Song, Bin / Zhang, Liwei

    International journal of surgery (London, England)

    2024  

    Language English
    Publishing date 2024-03-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2212038-5
    ISSN 1743-9159 ; 1743-9191
    ISSN (online) 1743-9159
    ISSN 1743-9191
    DOI 10.1097/JS9.0000000000001206
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6502: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: A commentary on "High ligation of the anal fistula tract by lateral approach: A prospective cohort study on a modification of the ligation of the intersphincteric fistula tract technique".

    Yang, Shiwei / Yan, Liwei / Jia, Keliang / Gu, Chao / Zhang, Guang

    International journal of surgery (London, England)

    2024  

    Language English
    Publishing date 2024-03-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2212038-5
    ISSN 1743-9159 ; 1743-9191
    ISSN (online) 1743-9159
    ISSN 1743-9191
    DOI 10.1097/JS9.0000000000001270
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6502: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  6. Article: Is open science a double-edged sword?: data sharing and the changing citation pattern of Chinese economics articles.

    Zhang, Liwei / Ma, Liang

    Scientometrics

    2023  Volume 128, Issue 5, Page(s) 2803–2818

    Abstract: Data sharing is an important part of open science (OS), and more and more institutions and journals have been enforcing open data (OD) policies. OD is advocated to help increase academic influences and promote scientific discovery and development, but ... ...

    Abstract Data sharing is an important part of open science (OS), and more and more institutions and journals have been enforcing open data (OD) policies. OD is advocated to help increase academic influences and promote scientific discovery and development, but such a proposition has not been elaborated on well. This study explores the nuanced effects of the OD policies on the citation pattern of articles by using the case of Chinese economics journals.
    Supplementary information: The online version contains supplementary material available at 10.1007/s11192-023-04684-8.
    Language English
    Publishing date 2023-03-21
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 435652-4
    ISSN 0138-9130
    ISSN 0138-9130
    DOI 10.1007/s11192-023-04684-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 82/706: Show issues

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  7. Article: Identifying the tumor-associated macrophage of lung adenocarcinoma reveals immune landscape through omics data integration.

    Zhang, Xu / Wu, Liwei / Zhang, Xiaotian / Xu, Yanlong

    Heliyon

    2024  Volume 10, Issue 6, Page(s) e27586

    Abstract: The tumor-associated macrophages (TAM) play a crucial role in lung adenocarcinoma (LUAD), which can cause the proliferation, migration and invasion of tumor cells. In particular, TAMs mainly regulate changes in the tumor microenvironment thereby ... ...

    Abstract The tumor-associated macrophages (TAM) play a crucial role in lung adenocarcinoma (LUAD), which can cause the proliferation, migration and invasion of tumor cells. In particular, TAMs mainly regulate changes in the tumor microenvironment thereby contributing to tumorigenesis and progression. Recently, an increasing number of studies are using single-cell RNA (Sc-RNA) sequencing to investigate changes in the composition and transcriptomics of the tumor microenvironment. We obtained Sc-RNA sequencing data of LUAD from GEO database and transcriptome data with clinical information of LUAD patients from TCGA database. A group of important genes in the state transition of TAMs was identified by analyzing TAMs at the single-cell level, while 5 TAM-related prognostic genes were obtained by omics data integration, and a prognostic model was constructed. GOBP analysis revealed that TAM-related genes were mainly enriched in tumor-promoting and immunosuppression-related pathways. After ROC analysis, it was found that the AUC of the prognosis model reached 0.751, with well predictive effectiveness. The 5 unique genes, HLA-DMB, HMGN3, ID3, PEBP1, and TUBA1B, was finally identified through synthesized analysis. The transcriptional characteristics of 5 genes were determined through GEPIA2 database and RT-qPCR. The increased expression of TUBA1B in advanced LUAD may serve as a prognostic indicator, while low expression of PEBP1 in LUAD may have the potential to become a therapeutic target.
    Language English
    Publishing date 2024-03-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e27586
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Construction of a predictive model for bone metastasis from first primary lung adenocarcinoma within 3 cm based on machine learning algorithm: a retrospective study.

    Zhang, Yu / Xiao, Lixia / LYu, Lan / Zhang, Liwei

    PeerJ

    2024  Volume 12, Page(s) e17098

    Abstract: Background: Adenocarcinoma, the most prevalent histological subtype of non-small cell lung cancer, is associated with a significantly higher likelihood of bone metastasis compared to other subtypes. The presence of bone metastasis has a profound adverse ...

    Abstract Background: Adenocarcinoma, the most prevalent histological subtype of non-small cell lung cancer, is associated with a significantly higher likelihood of bone metastasis compared to other subtypes. The presence of bone metastasis has a profound adverse impact on patient prognosis. However, to date, there is a lack of accurate bone metastasis prediction models. As a result, this study aims to employ machine learning algorithms for predicting the risk of bone metastasis in patients.
    Method: We collected a dataset comprising 19,454 cases of solitary, primary lung adenocarcinoma with pulmonary nodules measuring less than 3 cm. These cases were diagnosed between 2010 and 2015 and were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Utilizing clinical feature indicators, we developed predictive models using seven machine learning algorithms, namely extreme gradient boosting (XGBoost), logistic regression (LR), light gradient boosting machine (LightGBM), Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GNB), multilayer perceptron (MLP) and support vector machine (SVM).
    Results: The results demonstrated that XGBoost exhibited superior performance among the four algorithms (training set: AUC: 0.913; test set: AUC: 0.853). Furthermore, for convenient application, we created an online scoring system accessible at the following URL: https://www.xsmartanalysis.com/model/predict/?mid=731symbol=7Fr16wX56AR9Mk233917, which is based on the highest performing model.
    Conclusion: XGBoost proves to be an effective algorithm for predicting the occurrence of bone metastasis in patients with solitary, primary lung adenocarcinoma featuring pulmonary nodules below 3 cm in size. Moreover, its robust clinical applicability enhances its potential utility.
    MeSH term(s) Humans ; Retrospective Studies ; Carcinoma, Non-Small-Cell Lung ; Bayes Theorem ; Lung Neoplasms ; Adenocarcinoma of Lung ; Adenocarcinoma ; Algorithms ; Bone Neoplasms ; Machine Learning
    Language English
    Publishing date 2024-03-14
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2703241-3
    ISSN 2167-8359 ; 2167-8359
    ISSN (online) 2167-8359
    ISSN 2167-8359
    DOI 10.7717/peerj.17098
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Corrigendum to "Phosphorylation modification of bovine bone collagen peptide enhanced its effect on mineralization of MC3T3-E1 cells via improving calcium-binding capacity" [Food Chem. 433 (2024) 137365].

    Qi, Liwei / Wang, Kangyu / Zhou, Jiaojiao / Zhang, Hongru / Guo, Yujie / Zhang, Chunhui

    Food chemistry

    2024  Volume 442, Page(s) 138638

    Language English
    Publishing date 2024-02-07
    Publishing country England
    Document type Published Erratum
    ZDB-ID 243123-3
    ISSN 1873-7072 ; 0308-8146
    ISSN (online) 1873-7072
    ISSN 0308-8146
    DOI 10.1016/j.foodchem.2024.138638
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 3634: Show issues

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  10. Article ; Online: The Impact of Smart City Pilots on Haze Pollution in China—An Empirical Test Based on Panel Data of 283 Prefecture-Level Cities

    Liwei Zhang / Chuanqing Wu

    Sustainability, Vol 15, Iss 9653, p

    2023  Volume 9653

    Abstract: The rapid pace of urbanization in China has led to a significant increase in haze pollution in its cities. However, there has been limited research on the dynamic impact and mechanisms of smart city pilots, which offer an innovative approach to ... ...

    Abstract The rapid pace of urbanization in China has led to a significant increase in haze pollution in its cities. However, there has been limited research on the dynamic impact and mechanisms of smart city pilots, which offer an innovative approach to urbanization, on haze pollution. This study selects panel data from 283 prefecture-level cities in China from 2007 to 2017 and uses a quasi-experimental approach based on the three batches of pilot construction of smart cities since 2012 to examine the impact of smart city pilots on haze pollution. The multi-phase difference-in-differences (DID) model is used for the analysis. The findings reveal: (1) Smart city pilots have a significant positive effect on reducing urban haze pollution. (2) Smart city pilots contribute to changes in the urban development model, where technological innovation, industrial structure adjustment, and resource allocation optimization under innovation-driven development significantly mitigate haze pollution. (3) Heterogeneity analysis shows regional differences in the effectiveness of smart city pilot policies in reducing haze pollution in China, with a decreasing trend from the eastern to the western regions. The haze-reducing effect of smart city pilots in the central region has yet to be observed. This research provides valuable theoretical and policy insights for improving urban ecological environments and promoting green transformations of production and lifestyle.
    Keywords smart city pilot ; multi-phase DID ; haze pollution ; innovation-driven development ; green development ; regional difference ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 720
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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