System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool by Pavel Izosimov (20096259)

“…System Hardware ID Generator Script: Unique Device Identification for Enhanced Security and Licensing<p dir="ltr">The <b>System Hardware ID Generator Script</b> is a powerful Python tool developed to generate a unique Hardware ID (HWID) for the device it runs on. …”

SparcleQC: Automated Input File Creation for QM/MM Studies of Protein:Ligand Complexes by Caroline S. Glick (21561990)

“…The resulting input files include quantum mechanical representations of the ligand and a small section of the protein, surrounded by point charges that represent the rest of the protein. …”

Data for "A hollow fiber membrane permeance evaluation device demonstrating outside-in and inside-out performance differences" by Timothy Warner (20222838)

“…</li></ul><h4>Device_validation > Plot_data > results:</h4><ul><li>Contains a .jpg and .svg file of Figure 2 without the inserts, generated by the python script.…”

Results derived from <i>D</i>-SPR analysis at 25°C: <i>D</i>-SPR values refer to the <i>D</i> calculated with the Python script; <i>error</i> column reports the standard deviation values and represents the variability within the mean of four experimental replicates. by Gabriele Antonio Zingale (12463357)

“…<p>Results derived from <i>D</i>-SPR analysis at 25°C: <i>D</i>-SPR values refer to the <i>D</i> calculated with the Python script; <i>error</i> column reports the standard deviation values and represents the variability within the mean of four experimental replicates.…”

Results derived from <i>D</i>-SPR analysis of the lysozyme (349μM) at 25°C: <i>D</i>-SPR values refer to the <i>D</i> calculated with the Python script described previously; the <i>error</i> column reports the standard deviation values and represents the variability within the mean of four experimental replicates; values are consistent with the ones reported in the existing literature [13]. by Gabriele Antonio Zingale (12463357)

“…<p>Results derived from <i>D</i>-SPR analysis of the lysozyme (349μM) at 25°C: <i>D</i>-SPR values refer to the <i>D</i> calculated with the Python script described previously; the <i>error</i> column reports the standard deviation values and represents the variability within the mean of four experimental replicates; values are consistent with the ones reported in the existing literature [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0312594#pone.0312594.ref013" target="_blank">13</a>].…”

Overview of one by Guillermo Pérez-Hernández (21156182)

Correlation (a) and Mean-Absolute-Error (b) between frequencies at a reference cutoff, δ₀, and different frequencies, , at different cutoff-values, δ_scan ∊ [3... by Guillermo Pérez-Hernández (21156182)

Multi-Version PYZ Builder Script: A Universal Python Module Creation Tool by Pavel Izosimov (20096259)

“…</li><li><b>Python App Bundle Shield</b>: Enables the creation of standalone protected applications and executable files from Python scripts. …”

Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10,... by Enock Niyonkuru (21246879)

Comparison of tools with features similar to <i>bmdrc,</i> and a descriptions of the modules within the <i>bmdrc</i> package.  by David J. Degnan (13886280)

Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

“…</p><p dir="ltr"><br></p><p dir="ltr">## Files in the Project</p><p dir="ltr"><br></p><p dir="ltr">### Python Scripts</p><p dir="ltr">- **Wildfire_on_m_n-CAk.py**: This file contains the main code for the fire cellular automaton. …”

Resolving Harvesting Errors in Institutional Repository Migration : Using Python Scripts with VS Code and LLM Integration. by satoshi hashimoto(橋本 郷史) (18851272)

“…</li><li>Initially, the error report files were loaded into VS Code.</li><li>Next, we provided GitHub Copilot with contextual information, file details, and analysis objectives as initial instructions to generate the Python code.…”

City-level GDP estimates for China under alternative pathways from 2020 to 2100-python code by Jinjie Sun (11791715)

“…The tabular component includes annual GDP projections (in million yuan at 2020 constant prices) and total factor productivity (TFP) estimates stored in standardized CSV files, while the geospatial data comprises city-level GDP distributions under representative pathways in shapefile format using WGS84 coordinate system (EPSG:4326). …”

Deakin IoT Traffic Dataset by Aleksandar Pasquini (13092765)

“…This mapping simplifies the identification and filtering of packets belonging to each device within the pcap files. 3 extra CSV (<b>CSVs</b>) files provide metadate about the states that the devices were in at different times. …”

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... by Ziyan Jin (21021976)

PTPC-UHT bounce by David Parry (22169299)

“…</p><p dir="ltr">Included files:</p><ul><li>Python source code (<code>PTPC_UHT_bounce.py</code>)</li><li>Parameter sets for representative runs (α,β,Tcrit,V(T)\alpha, \beta, T_{\mathrm{crit}}, V(T)α,β,Tcrit​,V(T))</li><li>Output arrays of trajectories across multiple bounces</li><li>Multi-panel plots (PNG/PDF) for a(t)a(t)a(t), H(t)H(t)H(t), T(t)T(t)T(t), S(t)S(t)S(t), R(t)R(t)R(t), and ρT\rho_TρT​</li></ul><p dir="ltr">This dataset ensures full reproducibility of the PTPC simulations and provides a starting point for independent verification, parameter exploration, and future model extensions.…”

Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research by Temitope Omogbene (18615415)

“…</li></ul><p dir="ltr">Importantly, the <b>file names of each dataset</b> presented here were <b>renamed from their original Google Drive file paths</b> (referenced in the Python Google Colab scripts) to ensure <b>sequential, descriptive, and logically ordered naming</b>. …”

LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery by M RN (9866504)

Segmentation module training details. by Khelina Fedorchuk (19130089)

Experimental results of data retrieval from two Atlas DataLab setups: next-to-data deployment in the CSIC-DDC Hub (bottom) and remote data access from a user’s workstation (top). by Ezequiel Cimadevilla (8412531)