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Showing 1 - 20 results of 248 for search '(( python effective intervention ) OR ( python model implementation ))', query time: 0.45s Refine Results
  1. 1
    SCADET algorithm parameter configuration (Python implementation).

    SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

    Published 2025
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  2. 2
    Python Implementation of HSGAdviser Chatbot: AI model for Sustainable Education

    Python Implementation of HSGAdviser Chatbot: AI model for Sustainable Education by Suha Assayed (22454038)

    Published 2025
    “…<p dir="ltr">This repository contains the Python source code and model implementation for HSGAdviser, an AI speech assistant designed to provide personalized college and career guidance for high school students through conversational AI. …”
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  3. 3
    Python code for estimating parameters of an ALAAM model.

    Python code for estimating parameters of an ALAAM model. by Alex Stivala (8356257)

    Published 2024
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  4. 4
    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, the temporal molecular states <i>n</i> at specific time <i>t</i> will be generated for further visualization.

    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

    Published 2025
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  5. 5
    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 <... by Ziyan Jin (21021976)

    Published 2025
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  6. 6
    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... by Ziyan Jin (21021976)

    Published 2025
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  7. 7
    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... by Ziyan Jin (21021976)

    Published 2025
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  8. 8
    Reproducible implementation for article: Reproducibility study of the modular and reusable model of epithelial transport in the proximal convoluted tubule

    Reproducible implementation for article: Reproducibility study of the modular and reusable model of epithelial transport in the proximal convoluted tubule by Leyla Noroozbabaee (14301173)

    Published 2025
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  9. 9
    Source Code for the Hierarchical Key Assignment Scheme (HKAS)

    Source Code for the Hierarchical Key Assignment Scheme (HKAS) by Baris Celiktas (22804778)

    Published 2025
    Subjects: “…Hierarchical Key Assignment, Cryptography, Key Management, HKAS, Security Model, Python Implementation…”
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  10. 10
    Comparison of performance between our next reaction implementation and the Python library from Ref. [3].

    Comparison of performance between our next reaction implementation and the Python library from Ref. [3]. by Samuel Cure (22250922)

    Published 2025
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  11. 11
    Python implementation for image-based ERT inversion using ViT, CNN, UNet, and LDM models, and related data conversion and visualization

    Python implementation for image-based ERT inversion using ViT, CNN, UNet, and LDM models, and related data conversion and visualization by Huichao Yin (14589020)

    Published 2025
    “…<p dir="ltr">Python implementation for image-based ERT inversion using ViT, CNN, UNet, and LDM models, and related data conversion and visualization.…”
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  12. 12
    PYTHON

    PYTHON by Kan Jia (21666161)

    Published 2025
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  13. 13
    Left schematic of the XOR gate implementation [11].

    Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

    Published 2025
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  14. 14
    Example change statistic implementations.

    Example change statistic implementations. by Alex Stivala (8356257)

    Published 2024
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  15. 15
    Overview of the implemented simulation tool and training framework in Diffrax.

    Overview of the implemented simulation tool and training framework in Diffrax. by Paul van Lent (16876977)

    Published 2025
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  16. 16
    Python implementation of a wildfire propagation example using m:n-CAk over Z and R.

    Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

    Published 2025
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  17. 17
    Python script for binary classification with RoBERTa

    Python script for binary classification with RoBERTa by Maija Ozola-Schade (20938460)

    Published 2025
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  18. 18
    Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management

    Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management by Pavel Izosimov (20096259)

    Published 2024
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  19. 19
    Dataset and Python/R scripts used in "Effect Of Health Literacy Class on the Exercise Behavior Stage Change: An Attempt of The Self-Determination Theory-Informed Intervention with Japanese University Students."

    Dataset and Python/R scripts used in "Effect Of Health Literacy Class on the Exercise Behavior Stage Change: An Attempt of The Self-Determination Theory-Informed Intervention with Japanese University Students." by Issei Ogasawara (22506893)

    Published 2025
    “…<p dir="ltr">This dataset contains the raw data used in the paper “Effect of Health Literacy Class on Exercise Behaviour Stage Change: Attempting Self-Determination Theory-Informed Intervention among Japanese University Students, doi:(later)” along with the Python and R scripts used for analysis and visualization. …”
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  20. 20
    Python sript.

    Python sript. by Kan Jia (6438599)

    Published 2025
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