Testing Code for JcvPCA and JsvCRP. by Océane Dubois (21989812)

“…<p>This file contains the code that implements both metrics in python and apply them on a simulated dataset.…”

Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

“…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …”

Code and data for reproducing the results in the original paper of DML-Geo by Pengfei CHEN (8059976)

“…<p dir="ltr">This asset provides all the code and data for reproducing the results (figures and statistics) in the original paper of DML-Geo</p><h2>Main Files:</h2><p dir="ltr"><b>main.ipynb</b>: the main notebook to generate all the figures and data presented in the paper</p><p dir="ltr"><b>data_generator.py</b>: used for generating synthetic datasets to validate the performance of different models</p><p dir="ltr"><b>dml_models.py</b>: Contains implementations of different Double Machine Learning variants used in this study.…”

Data sets and coding scripts for research on sensory processing in ADHD and ASD by Vesko Varbanov (9687029)

“…</p><h4>Contents</h4><p dir="ltr">The repository includes:</p><ul><li>Questionnaire data (ASRS, BAPQ)</li><li>Visual orientation discrimination thresholds (vertical and oblique)</li><li>Demographic variables (age, gender)</li><li>Clinical vs. non-clinical group labels</li><li>Propensity score matching files and reproducible Python code</li><li>JASP analysis files and outputs</li><li>Study documentation and methodological details</li></ul><p dir="ltr">These data support the study’s finding that ADHD and ASD show distinct sensory signatures: clinical ADHD was associated with reduced oblique sensitivity, while clinical ASD showed enhanced vertical discrimination relative to matched non-clinical controls. …”

Data files accompanying our PLoS One publication by Peter Hinow (21810605)

Code for High-quality Human Activity Intensity Maps in China from 2000-2020 by Wenqi Xie (18273238)

“…<p dir="ltr">Code and remote sensing images and interpretation results of the samples for uncertainty analysis for "High-quality Human Activity Intensity Maps in China from 2000-2020"</p><p dir="ltr">“Mapping_HAI.py”：We generated the HAI maps using ArcGIS 10.8, and the geoprocessing tasks were implemented using Python 2.7 with the ArcPy library (ArcGIS 10.8 + Python 2.7 environment). …”

Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) by Winston Yap (13771969)

“…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …”

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

“…Each lane includes 'geometry' and 'inter_id' attributes.</li></ul><h2>Codes</h2><p dir="ltr">This repository contains the following Python codes：</p><ul><li>`data_processing.py`: Contains the implementation of data processing and feature extraction. …”

<b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b> by Pajtim Zariqi (22155799)

“…</li><li>Python/Kaggle notebooks (<code>.ipynb</code>): reproducibility pipeline for accuracy metrics and statistical analysis.…”

<b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> by Marly G F Costa (19812192)

“…<p dir="ltr"><b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b></p><p dir="ltr">The code was developed in the Google Collaboratory environment, using Python version 3.7.13, with TensorFlow 2.8.2. …”

Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> by Zhou (20184816)

“…Create a directory named "28pd" to place the .csv format data files to be labeled or predicted.</p>…”

Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files) by Wubin Ding (11823941)

“…</p><p dir="ltr">PMID: 37824674</p><p><br></p><h2>How to download</h2><p dir="ltr">To quickly download the whole folder, Python package <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">pyfigshare</a> can be implemented. please refer to pyfigshare documentation: <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">https://github.com/DingWB/pyfigshare</a></p><p dir="ltr">for example: <code>figshare download 28424780 -o downlnoaded_data</code></p>…”

High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch by Andrey Samokhin (20282728)

“…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …”

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

<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b> by Richard McDowell (7311011)

“…<p dir="ltr">Contains</p><p dir="ltr">Final Analysis Output.xlsx: Current and reference concentrations of DRP, TP, NO3-N and TN along with pivot table analysis</p><p dir="ltr">Code: Python code used to implement the model in ArcGIS Pro.…”

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”

HCC Evaluation Dataset and Results by Jens-Rene Giesen (18461928)

“…</p><h3>Report Script</h3><p dir="ltr">On the top-level directory you find a <code>report.py</code> file, which is an executable Python script. …”

Data and software for "Social networks affect redistribution decisions and polarization" by Milena Tsvetkova (11217969)

“…</p><p dir="ltr">The repository contains data in .csv and .xlsx format, model code in .nlogox Netlogo format, analysis code in .ipynb Jupyter notebooks, and helping code in .py Python files.…”

Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Raw and Processed Data</p> <p><br></p> <p>EEG brainwave recordings (raw and preprocessed signals)</p> <p><br></p> <p>Neurofeedback score datasets ( Neuron-Spectrum.NET )</p> <p><br></p> <p>Statistical analysis data (e.g., SPSS, MATLAB, or Python files)</p> <p><br></p> <p>Cognitive achievement test scores and student performance data</p> <p><br></p> <p><br></p> <p><br></p> <p>2. …”

Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Raw and Processed Data</p> <p><br></p> <p>EEG brainwave recordings (raw and preprocessed signals)</p> <p><br></p> <p>Neurofeedback score datasets ( Neuron-Spectrum.NET )</p> <p><br></p> <p>Statistical analysis data (e.g., SPSS, MATLAB, or Python files)</p> <p><br></p> <p>Cognitive achievement test scores and student performance data</p> <p><br></p> <p><br></p> <p><br></p> <p>2. …”