Complete text output printed to the terminal by the CLT (shown in Fig 2A) of the main text. by Guillermo Pérez-Hernández (21156182)

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Example Jupyter notebook illustrating how mdciao can be used in API mode. by Guillermo Pérez-Hernández (21156182)

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Table 1 - mdciao: Accessible Analysis and Visualization of Molecular Dynamics Simulation Data by Guillermo Pérez-Hernández (21156182)

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Longer-range peaks of S2 Fig (using arrows and the *, ⁑, †, ‡, and ⸸ symbols) not corresponding to short-range contacts, but rather secondary structure elements like beta-sheets or... by Guillermo Pérez-Hernández (21156182)

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Example Jupyter notebook illustrating how mdciao is used in API mode. by Guillermo Pérez-Hernández (21156182)

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Overview of one by Guillermo Pérez-Hernández (21156182)

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PyGMT – Accessing and Integrating GMT with Python and the Scientific Python Ecosystem (AGU24, U12B-05) by Yvonne Fröhlich (20442683)

“…</p><p dir="ltr">PyGMT (<a href="https://www.pygmt.org/" target="_blank">https://www.pygmt.org/</a>) wraps around the very fast GMT C code to make it accessible through the Python programming language. …”

Evaluation and Statistical Analysis Code for "Multi-Task Learning for Joint Fisheye Compression and Perception for Autonomous Driving" by Basem Ahmed (18127861)

“…</li></ul><p dir="ltr">These scripts are implemented in Python using the PyTorch framework and are provided to ensure the reproducibility of the experimental results presented in the manuscript.…”

Multifunctional Lead-Free Halide Perovskite-Based Nanogenerator for Enhanced Energy Harvesting and Information-Encrypted Transmission by Monika Salesh (15306281)

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Multifunctional Lead-Free Halide Perovskite-Based Nanogenerator for Enhanced Energy Harvesting and Information-Encrypted Transmission by Monika Salesh (15306281)

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Multifunctional Lead-Free Halide Perovskite-Based Nanogenerator for Enhanced Energy Harvesting and Information-Encrypted Transmission by Monika Salesh (15306281)

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Multifunctional Lead-Free Halide Perovskite-Based Nanogenerator for Enhanced Energy Harvesting and Information-Encrypted Transmission by Monika Salesh (15306281)

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The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

Datasets To EVAL. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”

Statistical significance test results. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”

How RAG work. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”

OpenBookQA experimental results. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”

AI2_ARC experimental results. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”

TQA experimental results. by Jin Lu (428513)

“…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …”