Showing 941 - 960 results of 1,453 for search '(( algorithm within function ) OR ((( algorithm python function ) OR ( algorithm both function ))))', query time: 0.39s Refine Results
  1. 941

    A Subsampling Strategy for AIC-based Model Averaging with Generalized Linear Models by Jun Yu (5904)

    Published 2024
    “…A practically implementable algorithm is developed, and its performance is evaluated through numerical experiments on both real and simulated datasets.…”
  2. 942

    Model-Free UAV Navigation in Unknown Complex Environments Using Vision-Based Reinforcement Learning by Satoshi Suzuki (20437556)

    Published 2025
    “…However, most existing approaches rely heavily on precise modeling of both the UAV and its operating environment, which tends to be unrealistic under real-world conditions. …”
  3. 943

    Table 12_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  4. 944

    Table 9_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  5. 945

    Table 8_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  6. 946

    Table 1_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  7. 947

    Table 2_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  8. 948

    Table 3_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  9. 949

    Table 5_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  10. 950

    Table 13_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  11. 951

    Table 6_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  12. 952

    Table 11_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  13. 953

    Table 7_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  14. 954

    Table 10_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  15. 955

    Table 4_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

    Published 2025
    “…RT-qPCR confirmed a significant upregulation of SMARCD3 and TCN1 in ARDS samples, aligning with dataset expression analysis results. Both in vitro and in vivo experiments demonstrated that modulation of SMARCD3 and TCN1 (but not RPL14) significantly affected mitochondrial function, oxidative stress, apoptosis, glucose metabolism and inflammatory cytokine expression.…”
  16. 956

    Tree-Enhanced Latent Space Models for Two-Mode Networks by Dan Pu (3714616)

    Published 2025
    “…In this framework, each node is characterized by a latent embedding vector, reparameterized as the aggregate of intermediate vectors corresponding to nodes within the tree structure. By optimizing the log-likelihood function augmented with a tree-based regularization term, the proposed model facilitates the simultaneous estimation of embedding vectors and the derivation of interpretable community structures. …”
  17. 957

    Data Sheet 1_PAQR6 as a prognostic biomarker and potential therapeutic target in kidney renal clear cell carcinoma.zip by Tao Zou (662198)

    Published 2024
    “…However, its biological function in kidney renal clear cell carcinoma (KIRC) and its potential as a therapeutic target remain underexplored.…”
  18. 958

    Table1_Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.pdf by Lijuan Liang (4277053)

    Published 2024
    “…We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. …”
  19. 959

    Wasserstein-Kaplan-Meier Survival Regression by Yidong Zhou (580573)

    Published 2024
    “…The proposed model is supported with a solid theoretical foundation including pointwise and uniform convergence rates, along with an efficient algorithm for model fitting. The proposed model effectively accommodates random variation that may exist in the probability measures across different subgroups, demonstrating superior performance in both simulations and two case studies compared to the Cox proportional hazards model and other alternative models. …”
  20. 960

    Pipeline for mean shape based post-processing method. by Zhicheng Lin (218641)

    Published 2024
    “…To reduce substantial spatial disparities between the original prediction and the mean shape, a rigid registration based on an iterative closest point algorithm (ICP) was performed in MATLAB (fixed shape: original prediction; moving shape: mean shape; function: pcregistericp (moving, fixed)) (b-1). …”