Scope of our collection of pathogen models of metabolism. by Emma M. Glass (13102872)

“…This cladogram was created using the GraPhlAn python tool. (b) Our collection of GENREs represents 9 phyla, 17 classes, 36 orders, 94 genera, and 345 species of pathogens. …”

<b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints</b> by Nariman Mani (21380459)

“…<ul><li>A <b>Python repo</b> with minimal implementations of all five layers<br>(<b>COL</b>, <b>SCL</b>, <b>CDM</b>, <b>RPE</b>, <b>RAS</b>) plus an <b>orchestrator</b> and utilities.…”

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

“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

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

“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

Online Resource: Reservoir Computing as a Promising Approach for False Data Injection Attack Detection in Smart Grids by Carl-Hendrik Peters (21530624)

“…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…”

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

“…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …”

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

“…<p dir="ltr">Spatially Offset Raman Spectroscopy (SORS) has emerged as a potential tool for non-invasive biomedical diagnostics, enabling molecularly specific probing of subsurface tissues. …”

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

“…Its efficiency and scalability make it well-suited for early-stage antibody discovery, repertoire profiling, and therapeutic design, particularly in the absence of structural data. The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

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

“…</li><li><b>Requirements File:</b> A <code>requirements.txt</code> file listing the necessary Python libraries to run the script seamlessly.</li></ol><p dir="ltr">This dataset and accompanying tools aim to support researchers, policymakers, and journalists in analyzing and addressing the issue of missing persons in Mexico.…”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

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. …”

face recognation with Flask by Muammar, SST, M.Kom (21435692)

“…Built using the <b>Flask</b> web framework (Python), this system provides a lightweight and scalable solution for implementing facial recognition capabilities in real-time or on-demand through a browser interface.…”

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>…”

IGD-cyberbullying-detection-AI by Bryan James (19921044)

“…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…”

Overview of generalized weighted averages. by Nobuhito Manome (8882084)

“…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”

Automatic data reduction for the typical astronomer by Bradford Holden (21789524)

“…PypeIt has been developed by a small team of astronomers with two leading philosophies: (1) build instrument-agnostic code to serve nearly any spectrograph; (2) implement algorithms that achieve Poisson-level sky-subtraction with minimal systematics to yield precisely calibrated spectra with a meaningful noise model. …”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”