Supporting Data for “All-temperature barocaloric effects at pressure-induced phase transitions” by Zhao Xueting (21796316)

“…The structure search for the low-temperature phase was conducted using the generic evolutionary algorithm implemented in the USPEX code^42–44. …”

Table 5_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 3_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 6_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 2_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 4_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 7_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 1_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Table 8_MMPred: a tool to predict peptide mimicry events in MHC class II recognition.xlsx by Filippo Guerri (17017524)

“…<p>We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. …”

Order-flow and long-memory in a simulated financial market by Shane Silverman (22497770)

“…This data does not contain Trader IDs (a way of knowing which trade is associated with which trader) and thus one needs to apply a method for generating synthetic trader IDs for these trades. We used the <a href="https://arxiv.org/abs/2503.18199" rel="noreferrer" target="_blank">Maitrier-Loeper-Bouchaud (MLB)</a> algorithm once we had processed this raw data. …”

ImproBR Replication Package by Anonymus (18533633)

“…**Improve**: Enhance using knowledge retrieval and LLM generation<br><br>## RQ2 Evaluation Pipeline<br>To run the RQ2 evaluation pipeline that compares ImproBR-improved, ChatBR-improved, and raw bug reports against ground truth using similarity analysis on 37 duplicate pairs:<br>```bash<br>cd Modified_ChatBR_Similarity_Codes/RQ2/<br>```<br>Then follow the steps in: [`Modified_ChatBR_Similarity_Codes/RQ2/README.md`](<u>Modified_ChatBR_Similarity_Codes/RQ2/README.md</u>)<br><br><br>## Troubleshooting<br><br>### API Configuration Issues<br><br>**LLM Connection Errors:**<br>- Ensure `AZURE_API_KEY` is valid and not expired<br>- Verify `AZURE_RESOURCE_NAME` matches your Azure OpenAI resource<br>- Check that your deployment name is exactly "gpt-4o-mini"<br>- Confirm you have sufficient quota/credits in your Azure account<br><br>**Knowledge Base Missing:**<br>If you see "Vector store not found" error:<br>```bash<br>python data/build_full_knowledge_base.py<br>```<br><br>### Common Installation Issues<br><br>**ChromaDB Installation Problems:**<br>If ChromaDB fails to install, try:<br>```bash<br>pip install --upgrade pip<br>pip install chromadb==0.4.15 --no-cache-dir<br>```<br><br>Alternative: Install without ChromaDB and use local embeddings<br>```bash<br>pip install -r requirements.txt --exclude chromadb<br>```<br><br>**Requirements Installation Failures:**<br>If requirements.txt fails, install core dependencies first:<br>```bash<br>pip install torch==2.8.0 transformers==4.30.2 sentence-transformers==2.2.2<br>pip install azure-ai-inference==1.0.0b1 openai==1.107.0<br>pip install requests==2.32.5 tqdm==4.67.1 colorama==0.4.6<br>```<br><br>Then install remaining packages:<br>```bash<br>pip install -r requirements.txt<br>```<br><br>**Python Version Compatibility:**<br>- **Minimum**: Python 3.8<br>- **Maximum**: Python 3.11.x<br>- **Recommended**: Python 3.9-3.11<br>- **Known Issues**: Python 3.12+ not supported due to package conflicts<br><br>### Configuration Issues<br><br>**Missing config.py:**<br>Copy template and edit with your API keys:<br>```bash<br>cp config.py.template config.py<br>```<br>Edit config.py with your Azure OpenAI credentials.…”

Raw and derived data: The quantification of downhole fractionation for laser ablation mass spectrometry by Jarred Lloyd (4825671)

“…</p><p dir="ltr">The zip file "DerivedData" contains two CSV files generated by the accompanying Julia code that processes data in preparation for fitting orthogonal polynomials that quantify the dowhnhole fractionation of these analyses and generates the figures for the publication.…”

Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014 by Karin L. Riley (19657882)

“…While such observations do exist at selected spots such as established forest plots, most forests have not been mapped with this level of specificity. …”

Overcoming limitations to customize DeepVariant for domesticated animals with TrioTrain by Robert Schnabel (236298)

“…However, the growing appeal of a “universal” algorithm has magnified the unknown impacts when used with non-human species. …”

Overview of mouse ovary analysis using Vizgen MERFISH data. by Ian K. Gingerich (22822222)

“…<b>C: Clustering Accuracy (ARI) Across Methods</b> — Adjusted Rand Index values for all methods, color-coded by clustering algorithm; shows full ARI range at default RASP parameters (kNN = 2–20, ) and the default parameter single-point performance (kNN=10, ). …”

Data Sheet 1_ARGContextProfiler: extracting and scoring the genomic contexts of antibiotic resistance genes using assembly graphs.pdf by Nazifa Ahmed Moumi (7434359)

“…Several tools, databases, and algorithms are now available to facilitate the identification of ARGs in metagenomic sequencing data; however, direct annotation of short-read data provides limited contextual information. …”

Biomass data and prediction model of rice heading stage in Haitang district, Sanya City, Hainan Province. by Wanyi He (14164810)

“…"Model" folder: The MATLAB R2024a rice heading stage modeling code and prediction code are stored, providing practical research tools for researchers in related fields.…”

Table 1_An interpretable machine learning model for early prediction of Escherichia coli infection in ICU patients.docx by Shu Yang (381226)

“…E. coli infection was identified based on microbiological results and diagnostic codes. Missing data were imputed using the missForest algorithm. …”

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

“…Version 3.0 has been deprecated due to the discovery of a data inconsistency in the calculation of net longwave radiation in the source code used to generate the dataset. As a result, there is a general positive bias in potential evapotranspiration (ET₀) and a consequent lower (drier) bias in the Aridity Index (AI) in affected outputs. …”

Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma by Zhaochen Wang (12176245)

“…Differential gene expression analysis, univariate and multivariate Cox regression analyses and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to identify prognostic ferroptosis-related genes and establish a nomogram model of risk score. …”