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effective implementation » effective prevention (توسيع البحث)
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يعرض 101 - 120 نتائج من 341 نتيجة بحث عن '(( python plot representing ) OR ( python effective implementation ))', وقت الاستعلام: 0.47s تنقيح النتائج
  1. 101
    Data_Sheet_1_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.pdf

    Data_Sheet_1_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.pdf حسب Stefano Casali (6703274)

    منشور في 2019
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  2. 102
    System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool

    System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool حسب Pavel Izosimov (20096259)

    منشور في 2024
    "…This tool provides <a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank">code obfuscation in Python</a> and <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank">Python code encryption</a>, enabling developers to <a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank">protect Python code</a> effectively.…"
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  3. 103
    Dialogue Propositional Content Replacement (DPCR) code

    Dialogue Propositional Content Replacement (DPCR) code حسب Jacopo Amidei (10511297)

    منشور في 2025
    "…<p dir="ltr">This resource consists of a Python notebook with code that was implemented for a research project that developed a novel method for testing the components of theories of (dialogue) coherence through utterance substitution. …"
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  4. 104
    Bursty model and Refractory model simulation results. (A) Bursty model simulation results ( samples). The production of nascent mRNA occurs in bursts and degrade after delay time <i>τ</i>. The burst frequency , the mean burst size and . (B) Refractory model simulation results ( samples). The gene has three states, , and , and can switch from one state to another. Moreover, nascent mRNA is produced only when the gene is in state . The parameters are , , , and <i>τ</i> = 1.

    Bursty model and Refractory model simulation results. (A) Bursty model simulation results ( samples). The production of nascent mRNA occurs in bursts and degrade after delay time <... حسب Ziyan Jin (21021976)

    منشور في 2025
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  5. 105
    RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production and degradation) and a down-regulation phase (degradation-only). In the first phase, <i>%</i>, <i>%</i> and <i>%</i> for the reaction time . In the second phase,  ∕ 1, <i>X</i> ∼ NB ( <i>r</i> , <i>μ</i> )  and <i>μ</i>. (B) Simulation results for RNA Velocity model with delay in degradation ( samples). RNA degradation is specified as a delayed reaction. In the first (up-regulation) phase: <i>Y</i> ≡ <i>n</i>, <i>t</i> = 0 and <i>%</i>. In the second (down-regulation) phase: <i>%</i>, <i>%</i> and <i>%.</i>

    RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production... حسب Ziyan Jin (21021976)

    منشور في 2025
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  6. 106
    Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , with different . The control parameter is . (B) The potential landscape is approximated by simulating a large number of molecules corresponding to concentrations ( samples) with parameter values , , and , respectively representing the adenocarcinoma state, the intermediate state, and the squamous carcinoma state. FOXA2 and SOX2 amounts are chosen to visualize the landscape. (C) Principle of SOX2-targeted degradation by the PROTAC technique. The PROTAC molecule here is designed to recognize SOX2 proteins and to recruit E3 ligases to induce an addition of ubiquitin (Ub) proteins onto SOX2, which causes degradation of SOX2 subsequently. (D) Application of a SOX2 degrader to the squamous carcinoma state () reprogram the AST network back to the adenocarcinoma state. Here the treatment effect of the SOX2 degrad

    Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... حسب Ziyan Jin (21021976)

    منشور في 2025
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  7. 107
    Batch correction using the Harmony algorithm.

    Batch correction using the Harmony algorithm. حسب Ross J. Burton (10941910)

    منشور في 2021
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  8. 108
    Fig 6 -

    Fig 6 - حسب Ross J. Burton (10941910)

    منشور في 2021
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  9. 109
    Data_Sheet_1_oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.pdf

    Data_Sheet_1_oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.pdf حسب Tung Dang (15229042)

    منشور في 2023
    "…This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy.…"
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  10. 110
    Creation of adjacency plots.

    Creation of adjacency plots. حسب Laura Muñoz-Baena (9911640)

    منشور في 2022
    "…Finally, we used a Python script to generate dot files using Graphviz. …"
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  11. 111
    Comparison of Monod model fit with linear error model.

    Comparison of Monod model fit with linear error model. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  12. 112
    Relationship of independent and dependent variable.

    Relationship of independent and dependent variable. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  13. 113
    Calibration model of biomass-dependent backscatter measurement.

    Calibration model of biomass-dependent backscatter measurement. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  14. 114
    Data structures and computation graph of murefi models.

    Data structures and computation graph of murefi models. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  15. 115
    Uncertainty about the independent variable.

    Uncertainty about the independent variable. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  16. 116
    Tabular representation of a parameter mapping.

    Tabular representation of a parameter mapping. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  17. 117
    Linear (top) and logistic (bottom) calibration model of glucose assay.

    Linear (top) and logistic (bottom) calibration model of glucose assay. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  18. 118
    Independent variable PDFs in various observation scenarios.

    Independent variable PDFs in various observation scenarios. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  19. 119
    Comparison with related software packages.

    Comparison with related software packages. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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  20. 120
    Posterior group mean and well-specific initial biomass concentrations <i>X</i><sub>0</sub>.

    Posterior group mean and well-specific initial biomass concentrations <i>X</i><sub>0</sub>. حسب Laura Marie Helleckes (12206910)

    منشور في 2022
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