The Conditions of Recurrence Dataset (CoR-D)

Conditions of Recurrence Dataset, Conditions of Recurrence Dataset Codebook and Supplementary Online Appendix for the book "How to prevent civil war recurrence: Learning from Failure

Simulation and analysis of an AmBe source

Code for AmBe simulation Americium-Beryllium (AmBe) sources are commonly used in industry and research applications. Existing simulations fail to match all the expected features of the AmBe neutron spectrum from reliable underlying data, and also lack the generation of carbon ions and fission fragments that appearexperimentally. This article details a comprehensive Geant4 simulation based on an analytical approach to the PrimaryGenerator class. Rather than simulating the interaction of 241 Am α decay with 9 Be through the in-built Geant4 physics list, this simulation uses the differential cross sections of the 9Be(α, n)12 C reaction to directly produce neutrons and 12 C ions while simultaneously increasing computational efficiency. Each stage of the simulation has been verified against commonly accepted results, including the mass distribution of the 241 Am fission fragments. The features of the emerging neutron spectrum have been compared to commonly accepted data, confirming the validity of the simulation. The source term and the simulation template are made publicly available in conjunction with this article. Although not extensively verified, the 239 PuBe neutron source has also been implemented, making it a straightforward framework for implementing further sources

Research software supporting the publication “Leveraging Large Language Models to Classify and Inspect Defects in Reinforced Autoclaved Aerated Concrete (RAAC)”

This deposit contains the full Python code for the LLM-based approach described in “Leveraging Large Language Models to Classify and Inspect Defects in Reinforced Autoclaved Aerated Concrete (RAAC).” It includes six scripts: two parallel prompt modules for RAAC mention detection and definition extraction; a seven-question defect-extraction script; and a data-aggregation script that produces a unified defect database. All scripts are versioned for reproducibility and require Python 3.11+, the Anthropic Claude 3 Opus API, and standard data-analysis libraries. A comprehensive README.md is included, detailing environment setup, dependency installation, API key configuration, and step-by-step execution instructions. The code is mirrored on GitHub for ongoing collaboration and version tracking. An interactive project overview and navigation interface is also provided via index.html on the project’s GitHub Pages site

Research data supporting the publication "Synthesis of δ-bismuth oxide stable at room temperature"

data set for experiments conducted on bismuth oxid

Research software supporting the publication “Leveraging Large Language Models to Classify and Inspect Defects in Reinforced Autoclaved Aerated Concrete (RAAC)”

This dataset contains a Python-based tool to automate the download of open access full-text PDFs using the Unpaywall API. It accepts a CSV of DOIs and retrieves available PDFs into a structured directory. The project includes source code, a requirements file, and documentation. It was developed to support open science workflows by simplifying access to freely available scholarly publications

Research data supporting the publication "Air Pollution Emissions from Vehicles as a Function of Their Current Real- World Market Price"

This dataset, provided in CSV format, supports the findings of the associated research paper. It contains anonymised vehicle-level data with technical attributes and corresponding real-world emission factors (EFs), calculated to three significant figures. Key variables include vehicle characteristics (e.g., Euro standard, registration year), test conditions (vehicle-specific power, repeats), and both distance-based (g/km) and fuel-based (g/kg fuel) emission factors for NOx, NO₂, NO, CO, and PM

Fermi acceleration with cold atoms

The dataset contains all the data needed to replicate Fig. 1,2, 3 and 4 of the manuscript, the code used to generate parts of Fig. 1 and 2 of the manuscript, and a file containing instructions

Research data supporting “Traffic-emitted amines promote new particle formation at roadsides”

Files describing concentrations of atmospheric species during measurement campaigns in Leipzig, German

Raw data from observations of SSRI-suspected ADRs from the Yellow Card System-March 2025

Each sheet contains an increasingly cleaned format of the overall SSRI dataset, this is to display continuity and progression of data cleaning. Datasets after the 'No SEX and AGE missing or unknown' worksheet are the final cleaned formats of the original 'uncleaned SSRI dataset'. Final cleaned sheets are named as follows: 'No DPX', 'Male only', 'Female only', 'Paediatric', 'Adolescent', 'Adult', and 'Elderly'

Data corresponding to thesis chapter entitled 'Assessing the potential of three organic biomarkers in providing insights into the diet and ecology of two lemur species'

Tabular data corresponding to thesis chapter no 6