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    MCCN Case Study 1 - Evaluate impact from environmental events/pressures by Donald Hobern (21435904)

    Published 2025
    “…filters=eyJTVEFURSI6WyJBQ1QiXX0=&location=-35.437128,149.203518,11.00</a></li><li><b>caladenia_act.csv</b> - Distribution records for orchids in the genus <i>Caladenia</i> between 1990 and present from the ALA in CSV format: <a href="https://doi.org/10.26197/ala.1e501311-7077-403b-a743-59e096068fa0" target="_blank">https://doi.org/10.26197/ala.1e501311-7077-403b-a743-59e096068fa0</a></li></ul><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Group orchid species records by species</li><li>Prepare STAC metadata records for each data source (separate records for the distribution data for each orchid species)</li><li>Load data cube</li><li>Mask orchid distribution records to boundaries of ACT</li><li>Calculate the proportion of distribution records for each species occurring inside and outside protected areas</li><li>Calculate the proportion of distribution records for each species occurring in areas with each class of vegetation cover</li><li>Report the apparent affinity between each species and protected areas and between each species and different classes of vegetation cover</li></ol><h4><b>Notes</b></h4><ul><li>No attempt is made here to compensate for underlying bias in the areas where observers have spent time recording orchids. …”
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    <i>In vivo</i> identification of <i>Toxoplasma gondii</i> antigenic proteins and <i>in silico</i> study of their polymorphism. by Julie DENIS (19696753)

    Published 2024
    “…<h2>Abstract</h2><p dir="ltr">This study aims to identify novel candidates for the development of serotyping assays for <i>Toxoplasma gondii</i> (<i>T. gondii</i>). …”
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    Environmental Census: Modeling Synthetic Biology Ecological Risk with Metagenomic Enzymatic Data and High-Performance Computing by John Docter (22772100)

    Published 2025
    “…Improved predictive computational tools are necessary to assess the potential establishment risk and environmental location of these escaped engineered microorganisms, assisting their design and management. Here, we present <i>EnCen</i>, a risk assessment Python software package that predicts the environmental range of engineered microorganisms through annotated functional one-hot-encoded similarity between the engineered microorganism and resident microorganisms of a given environment. …”
  13. 73

    Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

    Published 2025
    “…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”
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    Research Data and Code on Characteristics and Drivers of Plant Diversity in Viaduct Footprint Spaces of a Mountainous, High-Density City—A Case Study of Central Chongqing by Junjie Zhang (355622)

    Published 2025
    “…<p dir="ltr">This dataset supports the research presented in the article titled "Characteristics and Drivers of Plant Diversity in Viaduct Footprint Spaces of a Mountainous, High-Density City—A Case Study of Central Chongqing."…”
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    Comparison of previous predictive models. by Saeid Rasouli (20370998)

    Published 2024
    “…<div><p>Background</p><p>Optic neuritis (ON) can be an initial clinical presentation of multiple sclerosis This study aims to provide a practical predictive model for identifying at-risk ON patients in developing MS.…”