Showing 81 - 97 results of 97 for search 'python code represent', query time: 0.19s Refine Results
  1. 81

    (A) Sampling locations and ranges of <i>I. feisthamelii</i> (purple) and <i>I. podalirius</i> (teal) butterflies. by Sam Ebdon (21072525)

    Published 2025
    “…(B) Sampling locations of butterflies from the <i>Iphiclides</i> HZ. The dashed line represents the approximate HZ center, based on samples collected by Lafranchis et al. …”
  2. 82

    Oka et al., Supplementary Data for "Development of a battery emulator using deep learning model to predict the charge–discharge voltage profile of lithium-ion batteries" by Kanato Oka (20132185)

    Published 2024
    “…(<b>DOI:</b> 10.1038/s41598-024-80371-9 )<br><br>A zip file contains following data and codes.</p><p dir="ltr"><br></p><p dir="ltr">01_lstm_model_making.py</p><p dir="ltr">This file is a Python script for reading battery charge-discharge data and training an LSTM model. …”
  3. 83

    Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

    Published 2025
    “…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”
  4. 84

    Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution by Giorgio Boccarella (22810952)

    Published 2025
    “…This file can be used together with the analysis code (link to be added upon publication) to generate all figures.…”
  5. 85

    <b>Engineered Muscle-Derived Extracellular Vesicles Boost Insulin Sensitivity and Glucose Regulation</b> by Hagit Shoyhet (21090650)

    Published 2025
    “…</p><p dir="ltr"><b>miR_path_target_enrichment.csv</b></p><p dir="ltr"><b>Description:</b> KEGG pathway enrichment analysis results of shared mRNA targets of miRNAs miR-16-5p, miR-122-5p and miR-486-5p ranked by their interaction score defined in our paper. this includes the pathway name, the enrichment p-value, number of genes found in the term and number of miRNAs targeting these genes</p><p dir="ltr"><b>Code/software</b></p><p dir="ltr">Data were analyzed using R-V4.0.4, Python-V3.9.2 and GraphPad software. miRNA analyses were run in R-V4.0.4 Differential expression analysis was conducted using the “DEseq2” package and corrected for multiple hypotheses by FDR. …”
  6. 86

    Tracking when the number of individuals in the video frame changes. by Hirotsugu Azechi (20700528)

    Published 2025
    “…The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). …”
  7. 87

    MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

    Published 2025
    “…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><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>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”
  8. 88

    Data Sheet 1_Nationwide epidemiological study of subarachnoid hemorrhage: trends in admissions, mortality, seasonality, costs, clipping, embolization, and the impact of COVID-19.pd... by Thiago Oscar Goulart (22485604)

    Published 2025
    “…</p>Methods<p>This retrospective study analyzed secondary data from the Brazilian public health system (DataSUS) using ICD-10 code I60 for aSAH. Key metrics included the evaluation of admissions with time-series in Python, and mortality rates, procedures, and costs.…”
  9. 89

    2024 HUD Point in Time Count Data by State and CoC with Serious Mental Illness and Chronic Substance Use Counts by Benjamin Gorman (21648794)

    Published 2025
    “…</p><p dir="ltr">HUD PIT Count reports for states, Washington, DC, and the 384 CoCs were systematically downloaded from the HUD Exchange website using a Python script developed using Cursor software. Cursor uses large language models, especially Claude Sonnet 4 (Anthropic), to generate code. …”
  10. 90

    Electrical Tactile Dataset (Piezoelectric and Accelerometer) for textures by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, sensor index)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  11. 91

    Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

    Published 2025
    “…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”
  12. 92

    Phylogenomics of aquatic bacteria by Krzysztof Jurdzinski (12519700)

    Published 2025
    “…</p> <p><br></p> <p>all_MSG_ids.txt - a text file with names of all the representative MAGs within all the MSG pairs.</p> <p><br></p> <p>filter_MSGs.py - a Python script to extract the MAGs from within the MSGs (given all_MSG_ids.txt) from a folder containing a larger set of sequences.…”
  13. 93

    Optical Tactile (TacTip) Dataset for texture classification by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, h, w)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr"><br></p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  14. 94

    Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

    Published 2025
    “…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…”
  15. 95

    <b>Challenges and Strategies for the Management of Quality-Oriented Education Bases in Universities under Informatization Background</b> by Yang Yanxi (21571568)

    Published 2025
    “…Final codes, together with basic demographic attributes supplied by the institutions’ HR offices, were exported to Excel and cleaned in Python 3.10 using pandas 2.2.1 and numpy 1.26. …”
  16. 96

    Chromosomal rearrangements among clade A pathogenic <i>Cryptococcus</i> species. by Marco A. Coelho (7353659)

    Published 2025
    “…<p>(A) Synteny comparisons between <i>C. neoformans</i> strain 125.91 (reference) and representative strains from 7 other clade A species (8 species total). …”
  17. 97

    PepENS by Abel Chandra (16854753)

    Published 2025
    “…<br><br>Download and Use</p><p dir="ltr">The codes for Datasets 1 and 2 are found in the respective folders of this repository.…”