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  1. Article ; Online: Challenges and countermeasures for China's centralised volume-based procurement policy in healthcare.

    Chang, Qi / Tian, Yihui / Gao, Lingyun / Xia, Nan

    The International journal of health planning and management

    2024  

    Abstract: To reduce the cost of healthcare expenditures in China, the government has developed a centralised volume-based procurement (CVBP) policy for medicines and medical consumables. Based on tracking the development history of centralised procurement in China, ...

    Abstract To reduce the cost of healthcare expenditures in China, the government has developed a centralised volume-based procurement (CVBP) policy for medicines and medical consumables. Based on tracking the development history of centralised procurement in China, this study explores China's CVBP model. By comparing the centralised procurement models and healthcare expenditure data among China, the United States (U.S), the United Kingdom (UK), and Singapore, we find that China still faces many challenges in implementing the CVBP policy. The main challenges are as follows. First, the policy cannot be guaranteed the effectiveness of implementation without a well-coordinated regulatory mechanism. Second, the CVBP rules and quality evaluation standards are imperfect. Third, the interests of healthcare companies cannot be guaranteed. Fourth, the policy affects the benefits of medical institutions, and the government has not built a compensation mechanism for medical institutions. Fifth, it poses a challenge to the operational capacity and innovation level of Chinese companies. Therefore, this paper posits a three-stage strategy and nine measures that could benefit China's progress in implementing the CVBP policy.
    Language English
    Publishing date 2024-04-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 632786-2
    ISSN 1099-1751 ; 0749-6753
    ISSN (online) 1099-1751
    ISSN 0749-6753
    DOI 10.1002/hpm.3803
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 2897: 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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  2. Article ; Online: Predicting Cancer Lymph-Node Metastasis From LncRNA Expression Profiles Using Local Linear Reconstruction Guided Distance Metric Learning.

    Li, Bo / Tian, Yihui / Tian, Yang / Zhang, Shihua / Zhang, Xiaolong

    IEEE/ACM transactions on computational biology and bioinformatics

    2022  Volume 19, Issue 6, Page(s) 3179–3189

    Abstract: Lymph-node metastasis is the most perilous cancer progressive state, where long non-coding RNA (lncRNA) has been confirmed to be an important genetic indicator in cancer prediction. However, lncRNA expression profile is often characterized of large ... ...

    Abstract Lymph-node metastasis is the most perilous cancer progressive state, where long non-coding RNA (lncRNA) has been confirmed to be an important genetic indicator in cancer prediction. However, lncRNA expression profile is often characterized of large features and small samples, it is urgent to establish an efficient judgment to deal with such high dimensional lncRNA data, which will aid in clinical targeted treatment. Thus, in this study, a local linear reconstruction guided distance metric learning is put forward to handle lncRNA data for determination of cancer lymph-node metastasis. In the original locally linear embedding (LLE) approach, any point can be approximately linearly reconstructed using its nearest neighborhood points, from which a novel distance metric can be learned by satisfying both nonnegative and sum-to-one constraints on the reconstruction weights. Taking the defined distance metric and lncRNA data supervised information into account, a local margin model will be deduced to find a low dimensional subspace for lncRNA signature extraction. At last, a classifier is constructed to predict cancer lymph-node metastasis, where the learned distance metric is also adopted. Several experiments on lncRNA data sets have been carried out, and experimental results show the performance of the proposed method by making comparisons with some other related dimensionality reduction methods and the classical classifier models.
    MeSH term(s) Humans ; RNA, Long Noncoding/genetics ; Lymphatic Metastasis/genetics ; Gene Expression Regulation, Neoplastic/genetics
    Chemical Substances RNA, Long Noncoding
    Language English
    Publishing date 2022-12-08
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1557-9964
    ISSN (online) 1557-9964
    DOI 10.1109/TCBB.2022.3149791
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Distinct and diverse anaerobic respiration of methanogenic community in response to MnO

    Tian, Tian / Qiao, Sen / Yu, Cong / Tian, Yihui / Yang, Yue / Zhou, Jiti

    Water research

    2017  Volume 123, Page(s) 206–215

    Abstract: Recently, the influence of metal oxide nanoparticles (NPs) on methanogenesis in anaerobic digestion has drawn much attention, however, the changes in NPs and functioning consortia within the methanogenic community are usually not investigated. Therefore, ...

    Abstract Recently, the influence of metal oxide nanoparticles (NPs) on methanogenesis in anaerobic digestion has drawn much attention, however, the changes in NPs and functioning consortia within the methanogenic community are usually not investigated. Therefore, the methanogenesis performance, NPs transformation and methanogenic community development in anaerobic digester sludge under MnO
    MeSH term(s) Metal Nanoparticles ; Methane ; Methanobacterium ; Methanosarcina ; Sewage
    Chemical Substances Sewage ; Methane (OP0UW79H66)
    Language English
    Publishing date 2017-10-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 202613-2
    ISSN 1879-2448 ; 0043-1354
    ISSN (online) 1879-2448
    ISSN 0043-1354
    DOI 10.1016/j.watres.2017.06.066
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 78/260: Show issues
    Z 3381: Show issues

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  4. Article: analysis of energy-related greenhouse gas emissions in the Chinese iron and steel industry

    Tian, Yihui / Zhu, Qinghua / Geng, Yong

    Energy policy

    Volume v. 56

    Abstract: With China's increasing pressures on reducing greenhouse gas (GHG) emission, Chinese iron and steel industry (ISI) is facing a great challenge. In this paper, we address the energy-related GHG emission trajectories, features, and driving forces in ... ...

    Abstract With China's increasing pressures on reducing greenhouse gas (GHG) emission, Chinese iron and steel industry (ISI) is facing a great challenge. In this paper, we address the energy-related GHG emission trajectories, features, and driving forces in Chinese ISI for 2001–2010. First, energy related GHG inventory for ISI is made for both scope 1 (direct emissions) and scope 2 (including imported electricity emission). Then, the driving forces for such emission changes are explored by utilizing the method of logarithmic mean Divisa index (LMDI) decomposition analysis. Results indicate that Chinese ISI experienced a rapid growth of energy related GHG emission at average annual growth rate of 70milliontons CO₂e. Production scale effect is the main driving factor for energy related GHG emission increase in Chinese ISI, while energy intensity effect and emission factor change effect offset the total increase and energy structure has marginal effect. Construction, manufacture of general purpose and special purpose machinery and manufacture of transport equipment sectors are main sectors for embodied emissions, amounting for more than 75% of the total embodied emissions from Chinese ISI. Such research findings propose that a detailed consideration can help make appropriate polices for mitigating ISI's energy-related GHG emission.
    Keywords manufacturing ; emissions factor ; greenhouse gas emissions ; equipment ; electricity ; greenhouse gases ; steel ; iron ; energy
    Language English
    Document type Article
    ISSN 0301-4215
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

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