Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by 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. …”

Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

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

Linking Thermal Conductivity to Equations of State Using the Residual Entropy Scaling Theory by Zhuo Li (165589)

“…Besides, a detailed examination of the impact of the critical enhancement term on mixture calculations was conducted. To use our model easily, a software package written in Python is provided in the Supporting Information.…”

The format of the electrode csv file by Joseph James Tharayil (21416715)

“…We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”

The format of the simulation reports by Joseph James Tharayil (21416715)

“…We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”

Comparison of BlueRecording with existing tools by Joseph James Tharayil (21416715)

“…We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”

The format of the weights file by Joseph James Tharayil (21416715)

“…We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”

Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations by Sascha Mausenberger (22225772)

“…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …”

Overview of deep learning terminology. by 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. …”

Map of cumulative daily root-mean-square errors for each province in China in the test set. by Xiaoyi Wang (90589)

Compiled Global Dataset on Digital Business Model Research by Dimas Fauzan Aryadefa (22123186)

“…</p><p dir="ltr">For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. …”

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models by Pascal Kündig (19824557)

“…In particular, we obtain a speed-up of an order of magnitude compared to Cholesky-based calculations and a 3-fold increase in prediction accuracy in terms of the continuous ranked probability score compared to a state-of-the-art method on a large satellite dataset. All methods are implemented in a free C++ software library with high-level Python and R packages. …”

Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model by Marina Diachenko (19739092)

“…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”

<b>Code: Inferred movements of SARS-CoV-2 infections between the 25 administrative regions of Peru (Figure 3) + </b><b>International spread of four SARS-CoV-2 sub-lineages of Peruv... by Pablo Tsukayama (22614461)

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

“…<p dir="ltr">This deposit provides the Python notebook and the input dataset used in the study “Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil).” …”

Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems by Lakshit Mathur (20894549)

“…The work advances national AI autonomy, real-time cognitive context modeling, and ethical human-AI integration.</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

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.…”

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

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