Showing 1,281 - 1,300 results of 8,651 for search '((pina OR (find OR (spine OR (shinae OR (shin OR chin))))) OR (ming OR (long OR min)))', query time: 0.22s Refine Results
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    Balancing degradability and mechanical strength in keto modified polyethylene through hydrogen bonds by Li, Ke, Chen, Xi, Pan, Yuqing, Min, Benzhi, Ye, Enyi, Li, Shuzhou, Li, Zibiao, Loh, Xian Jun

    Published 2024
    “…Adding keto groups to the PE chain decreases its photostability, our findings reveal that increase in keto group concentration further amplifies degradation, albeit with minimal impact on photostability. …”
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    Journal Article
  14. 1294

    Hear together by Lim, Gladys Cheng Hui, Yeo, Justin Wei Min, Soh, Juliana Li Jing, Koh, Faith Joyce Wyue Enn

    Published 2020
    “…Based on our research findings, social influence is a factor that affects elderly intention to screen. …”
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    Final Year Project (FYP)
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    Metabolomic fingerprints: seasonal and farm-specific differences in Heterotrigona itama bee bread by Shin, Siong Ng, Nurkhalida Kamal, Wan, Kiew-Lian, Izfa Riza Hazmi, Nurul Yuziana Mohd Yusof, Mohd Faizal Abu Bakar, Mohd Fahimee Jaapar, Norela Sulaiman, Fareed Sairi

    Published 2024
    “…Thus, tandem mass spectrometry (LCMS/MS) based metabolomics analysis was used to achieve the said goal, focusing on H. itama bee bread samples, followed by multivariate analysis using the MetaboAnalyst platform. Our findings revealed significant metabolites that set bee bread samples apart. …”
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    Article
  20. 1300

    Mine yOur owN Anatomy: revisiting medical image segmentation with extremely limited labels by You, C, Dai, W, Liu, F, Min, Y, Dvornek, NC, Li, X, Clifton, DA, Staib, L, Duncan, JS

    Published 2024
    “…However, they face three common pitfalls: (1) tailness: medical image data usually follows an implicit long-tail class distribution. Blindly leveraging all pixels in training hence can lead to the data imbalance issues, and cause deteriorated performance; (2) consistency: it remains unclear whether a segmentation model has learned meaningful and yet consistent anatomical features due to the intra-class variations between different anatomical features; and (3) diversity: the intra-slice correlations within the entire dataset have received significantly less attention. …”
    Journal article