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Showing 1,001 - 1,020 results of 1,800 for search '(( algorithms within function ) OR ((( algorithm python function ) OR ( algorithm b function ))))', query time: 0.46s Refine Results
  1. 1001
    Adult eclosion rhythm is disrupted in <i>Clk</i><sup><i>Δ29</i></sup> under DD conditions.

    Adult eclosion rhythm is disrupted in <i>Clk</i><sup><i>Δ29</i></sup> under DD conditions. by Daniel J. Brady (20622465)

    Published 2025
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  2. 1002
    Rhythmic egg hatching is disrupted in <i>Clk</i><sup><i>Δ29</i></sup> under DD conditions.

    Rhythmic egg hatching is disrupted in <i>Clk</i><sup><i>Δ29</i></sup> under DD conditions. by Daniel J. Brady (20622465)

    Published 2025
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  3. 1003
    Table 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.xlsx

    Table 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.xlsx by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  4. 1004
    Image 3_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 3_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  5. 1005
    Image 1_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 1_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  6. 1006
    Image 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  7. 1007
    Image 7_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 7_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  8. 1008
    Image 6_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 6_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  9. 1009
    Image 5_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 5_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  10. 1010
    Image 4_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif

    Image 4_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

    Published 2025
    “…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”
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  11. 1011
    Monthly averages of ED2 model simulations initialised with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

    Monthly averages of ED2 model simulations initialised with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon by Marcos Longo (1928929)

    Published 2025
    “…B. Görgens, E. J. L. Larson, J. F. Needham, E. …”
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  12. 1012
    Data repository for paper: "Variational approach to open quantum systems with long-range competing interactions"

    Data repository for paper: "Variational approach to open quantum systems with long-range competing interactions" by Dawid Hryniuk (11488600)

    Published 2025
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  13. 1013
    An HSR corridor with m stations and n trains.

    An HSR corridor with m stations and n trains. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  14. 1014
    Structure of bi-level programming model.

    Structure of bi-level programming model. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  15. 1015
    Lanzhou-Xi’an HSR corridor.

    Lanzhou-Xi’an HSR corridor. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  16. 1016
    Comparison of related studies with our work.

    Comparison of related studies with our work. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  17. 1017
    Unit impedance of each OD pair.

    Unit impedance of each OD pair. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  18. 1018
    Subscripts and parameters used in TSSN.

    Subscripts and parameters used in TSSN. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  19. 1019
    Occupying rate of v-class seat in each train.

    Occupying rate of v-class seat in each train. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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  20. 1020
    Schematic diagram of mutation operation.

    Schematic diagram of mutation operation. by Zhipeng Huang (1759759)

    Published 2025
    “…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”
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