Extreme delta - pydeltaRCM models by Octria Adi Prasojo (10507373)

“…<p dir="ltr">The folder contains the Python codes (.ipynb) to run the pyDeltaRCM models of extreme events impact on delta morphodynamics across five climate regions, along with the modelling results (.nc) presented by the same authors in the manuscript.…”

Examples of beekeeper associations resulting from using pollen images. by Juan D. Leal Campuzano (22470316)

Flowchart of the geographic origin classification process. by Juan D. Leal Campuzano (22470316)

Data and analysis code for manuscript "Preparations for ultra-high dose rate 25-90 MeV electron irradiation experiments with a compact, high-peak-current, X-band linear accelerator... by Haytham Effarah (11979509)

“…</p><p dir="ltr">The environment.yml file can create a conda virtual environment named "prep4vhee" with the required Python version and dependencies using the following conda command:</p><pre>conda env create -f environment.yml<br></pre><p dir="ltr">TOPAS input decks are also included in some folders with seeds set to reproduce Monte Carlo simulation results presented in the manuscript. …”

Dataset for the Modeling and Bibliometric Analysis of Business plan for Entrepreneurship by Shofie Galuh Amanda (22121604)

“…The analysis and visualization were carried out using R Biblioshiny for thematic mapping and trend topics, and Microsoft Excel for main information and annual publication production. For modeling, Python was applied to generate projection analyses of annual scientific production using polynomial regression. …”

Leveraging Large Language Models as Requirements Elicitation Interview Bots-all data by Samuel Gorsch (19947618)

“…<p dir="ltr"><b>Title:</b> Code and Supplementary Files for "Leveraging Large Language Models as Requirements Elicitation Interview Bots"</p><p dir="ltr"><b>Description:</b><br>This repository contains all code, supplementary plots, and select data files used in the master’s thesis, "Leveraging Large Language Models (LLMs) as Requirements Elicitation Interview Bots." …”

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

“…<p>Latent Gaussian process (GP) models are flexible probabilistic nonparametric function models. …”

Horuss Research: methodology for validating unstructured data using large language models by Fabiano Castello (6803171)

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

<b>Beyond absolute space: Modeling disease dispersion and reactive actions from a multi-spatialization perspective</b> by Shiran Zhong (14518376)

“…</p><h3>Running the Code</h3><p dir="ltr">· To run the Python code (preferably in Jupyter Notebook), ensure that all dependencies are installed by running: <i>pip install pandas pgmpy</i>. …”

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

“…However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.</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)

“…However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

Table 1_Net2Brain: a toolbox to compare artificial vision models with human brain responses.pdf by Domenic Bersch (21248975)

“…To address these challenges, we present Net2Brain, a Python-based toolbox that provides an end-to-end pipeline for incorporating DNNs into neuroscience research, encompassing dataset download, a large selection of models, feature extraction, evaluation, and visualization. …”

Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management by Ning Li (18882138)

“…This repository contains data and code for a research project replicating human psychological experiments using Large Language Models (LLMs). …”

ML model for prediction of postpartum rehospitalization in pregnant women/new mothers using readily obtainable pre-pregnancy or early pregnancy sociodemographic and health determin... by Martin Frasch (5754731)

“…</li><li>Here, we present an open-access Python code including the ML model for inference to facilitate prospective utilization of the developed model and further study of the nuMoM2b and similar datasets with machine learning approaches.…”

Data Sheet 1_Research on propagation dynamics of emotional contagion using S3EIR model based on multiple social media platforms.pdf by Hejie Chen (3947525)

“…In order to verify the validity and applicability of the S3EIR model, this paper constructs a dynamical model.</p>Methods<p>It uses Python to crawl the comments of the family-seeking event on the four social platforms and uses simulation to simulate and verify the dynamic process of emotional contagion and information dissemination.…”

Workflow of T cell activation analysis. by Yitong Ma (8144697)

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.…”

Dataset of experimental and computational characterization of tissue spheroid fusion by Steven Ongenae (19646189)

“…Various csv and xlsx files are attached, which can be readily imported using pandas in Python, relating to: - processed experimental fusion data (100 cells, 500 cells, and new JASP experiments) - measures of granularity / contact angles using GSI - MSRD data from two-photon microscopy experiments - Combined data of all parameter studies and their extracted metrics from the computational model. …”

Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning by Joan Alexander (17047170)

“…Establishing a framework for implementing and testing ML-based parameterizations in atmospheric models. Focusing first on idealized atmospheric modeling systems, we will tackle challenges associated with coupling interactively an ML-based data-driven scheme and a climate model (e.g., numerical instabilities, linking Python and Fortran). …”