<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> حسب Shubham Pawar (22471285)

"…</p><h2>Project Structure</h2><pre><pre>Perception_based_neighbourhoods/<br>├── raw_data/<br>│ ├── ET_cells_glasgow/ # Glasgow grid cells for analysis<br>│ └── glasgow_open_built/ # Built area boundaries<br>├── svi_module/ # Street View Image processing<br>│ ├── svi_data/<br>│ │ ├── svi_info.csv # Image metadata (output)<br>│ │ └── images/ # Downloaded images (output)<br>│ ├── get_svi_data.py # Download street view images<br>│ └── trueskill_score.py # Generate TrueSkill scores<br>├── perception_module/ # Perception prediction<br>│ ├── output_data/<br>│ │ └── glasgow_perception.nc # Perception scores (demo data)<br>│ ├── trained_models/ # Pre-trained models<br>│ ├── pred.py # Predict perceptions from images<br>│ └── readme.md # Training instructions<br>└── cluster_module/ # Neighbourhood clustering<br> ├── output_data/<br> │ └── clusters.shp # Final neighbourhood boundaries<br> └── cluster_perceptions.py # Clustering algorithm<br></pre></pre><h2>Prerequisites</h2><ul><li>Python 3.8 or higher</li><li>GDAL/OGR libraries (for geospatial processing)</li></ul><h2>Installation</h2><ol><li>Clone this repository:</li></ol><p dir="ltr">Download the zip file</p><pre><pre>cd perception_based_neighbourhoods<br></pre></pre><ol><li>Install required dependencies:</li></ol><pre><pre>pip install -r requirements.txt<br></pre></pre><p dir="ltr">Required libraries include:</p><ul><li>geopandas</li><li>pandas</li><li>numpy</li><li>xarray</li><li>scikit-learn</li><li>matplotlib</li><li>torch (PyTorch)</li><li>efficientnet-pytorch</li></ul><h2>Usage Guide</h2><h3>Step 1: Download Street View Images</h3><p dir="ltr">Download street view images based on the Glasgow grid sampling locations.…"

Code and parameter package for long-term mapping and object-based typing of freeze–thaw colluvial deposits (1990–2024) along the Yunnan–Tibet corridor حسب Hui Ye (22308559)

"…Tested with Python 3.x/ArcGIS Pro (ArcPy) and the GEE Code Editor. …"

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

"…On an independent blind test set, ParaDeep attained F1 = 0.723 and MCC = 0.685 for H chains, and F1 = 0.607 and MCC = 0.587 for L chains, representing a 27% MCC improvement over the sequence-based baseline Parapred. …"

Overview of deep learning terminology. حسب Aaron E. Maxwell (8840882)

"…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …"

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

"…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"

S1 Data - حسب Nicole Fouda Mbarga (10789287)

"…Data was analyzed using python software version 21 for the quantitative arm and content analysis was performed for qualitative data. …"

Missing and Unaccounted-for People in Mexico (1960s–2025) حسب Montserrat Mora (20430644)

"…</li></ul><p dir="ltr"><b>Additional Materials:</b></p><ol><li><b>Python Script:</b> A Python script to generate customizable visualizations based on the dataset. …"

Data and Code repository for the paper: <b>Visual loom caused by self- or object-movement elicits distinct responses in mouse superior colliculus</b> حسب Stefano Zucca (21686006)

"…In particular, shared MATLAB functions have been provided to generate results in figures 1-3 and divided into different folders based on figure number. For data reported in figure 4, python scripts have been collected in a separate folders, together with all the functions used to perform data analysis reported in figure 4. …"

The global dryland lake storage (GDLS) dataset حسب Gang Zhao (18368925)

"…</b><b>5_Dryland_lakeUncertainty.csv</b><br>The uncertainty for DEM-based hypsometric relationship. Column "source" represents the DEM source. …"

Smart contract and interface code for Nature Energy "A general form of smart contract for decentralised energy systems management" حسب Lee Thomas (19655773)

"…This provides the modelled electricity network cost data, the smart contract code, and the Python interface scripts described in the Nature Energy Paper  "A general form of smart contract for decentralised energy systems management." …"

Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024) حسب Lucky Ario (22115884)

"…Analytical outputs are organized into multiple formats: CSV files for raw bibliometric data; PNG images for thematic maps, trend topic visualizations, and research flowcharts; and CSV and PNG outputs for annual publication trajectories and polynomial regression-based modeling projections. Visualization and analysis were conducted using Microsoft Excel for summary statistics, R Biblioshiny for thematic and trend mapping, and Python for projection modeling.…"

Table 1_MitoLandscape, a semi-automated pipeline for subcellular localization and quantification of mitochondria.xlsx حسب Enrico Negri (22579151)

"…MitoLandscape integrates Airyscan super-resolution microscopy, semi-automated segmentation (leveraging ImageJ and 3DSlicer), machine-learning-driven pixel classification (ilastik), and a modular custom Python script for robust and versatile analysis. Using graph-based representations derived from manual annotations and binary mitochondrial images, MitoLandscape efficiently extracts detailed morphological parameters from distinct subcellular compartments, applicable from cells with simple morphologies to complex neuronal architectures. …"

Data Sheet 1_MitoLandscape, a semi-automated pipeline for subcellular localization and quantification of mitochondria.pdf حسب Enrico Negri (22579151)

"…MitoLandscape integrates Airyscan super-resolution microscopy, semi-automated segmentation (leveraging ImageJ and 3DSlicer), machine-learning-driven pixel classification (ilastik), and a modular custom Python script for robust and versatile analysis. Using graph-based representations derived from manual annotations and binary mitochondrial images, MitoLandscape efficiently extracts detailed morphological parameters from distinct subcellular compartments, applicable from cells with simple morphologies to complex neuronal architectures. …"

Table 2_MitoLandscape, a semi-automated pipeline for subcellular localization and quantification of mitochondria.xlsx حسب Enrico Negri (22579151)

"…MitoLandscape integrates Airyscan super-resolution microscopy, semi-automated segmentation (leveraging ImageJ and 3DSlicer), machine-learning-driven pixel classification (ilastik), and a modular custom Python script for robust and versatile analysis. Using graph-based representations derived from manual annotations and binary mitochondrial images, MitoLandscape efficiently extracts detailed morphological parameters from distinct subcellular compartments, applicable from cells with simple morphologies to complex neuronal architectures. …"

<b>Data and Code from 'The Perfect and Legitimate Bribe': A Transparent Record of Human-AI Collaboration in Legal Scholarship</b> حسب Joshua Stern (21748181)

"…</p><p dir="ltr">For optimal viewing of `collated-anonymized.txt`, a text editor that can handle long lines without word wrapping is recommended to preserve the indentation that represents the conversational branching structure.</p><p><br></p><p dir="ltr">### **Running Code/Software**</p><p dir="ltr">The provided scripts (`collator-ipynb.txt` and `sentence-ancestry-ipynb.txt`) are Jupyter Notebooks and require a Python 3 environment to run. …"

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

"…(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. …"

MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health. حسب Melissa Y. Chen (11301882)

"…Plants are scanned after 1 week of incubation with bacteria and images are processed using a custom Python script to extract pixel data. Plants are assigned “health scores” based on their colour and size (Hue*saturation*log₁₀(Plant pixels + 1)*100). …"

CompuCrawl: Full database and code حسب Richard Haans (6324669)

"…</li><li><i>05 Clean and select.py</i>: Python script applying data selection and cleaning (including selection based on page category), with setting and decisions described at the top of the script. …"

CpG Signature Profiling and Heatmap Visualization of SARS-CoV Genomes: Tracing the Genomic Divergence From SARS-CoV (2003) to SARS-CoV-2 (2019) حسب Tahir Bhatti (20961974)

"…</p><p dir="ltr">The Python script can be adapted to analyze other viral genomes or datasets.…"

GameOfLife Prediction Dataset حسب David Towers (12857447)

"…<p dir="ltr">The GameOfLife dataset is an algorithmically generated dataset based off John Horton Conway's Game of Life. Conway's Game of Life follows a strict set off rules at each "generation" (simulation step) where cells alternate between a dead and alive state based on number of surrounding alive cells. …"