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Uploaded raw data calibrated by QI software, derived from untargeted metabolomics profiling of plasma metabolites in patients with unexplained infertility and healthy volunteers.

This file has the answers of the participants in the usability test of RADIANCE+. The data includes the answers to the questions in the System Sustainability Score as well as additional questions relevant to RADIANCE+.

Los datos empleados en la investigación permitieron dar respuesta a la siguiente pregunta de investigación: ¿Cómo el eco marketing influye en la decisión de compra de los consumidores de empresas eco amigables de Lima Metropolitana?, de la que se derivaron 5 hipótesis de investigación: Hipótesis 1: El eco marketing influye en la decisión de compra, Hipótesis 2: El etiquetado ecológico influye en la decisión de compra, Hipótesis 3: El empaque ecológico influye en la decisión de compra, Hipótesis 4: Los productos ecológicos influyen en la decisión de compra, Hipótesis 5: El precio ecológico influye en la decisión de compra.

This dataset contains industrial PLC program backups corresponding to the edge and cloud layers of the CRISP (Control and Resource Integration as a Service Provisioning) architecture. The edge-side control logic is implemented using SIMATIC Manager (STEP 7), representing a legacy PLC environment, while the cloud-side control logic is implemented using Siemens TIA Portal v16, representing a modern industrial automation platform. The dataset is provided as two compressed archives—one for the edge layer and one for the cloud layer—to preserve the original project structure and configuration files. Communication between the edge and cloud layers is realized using the MQTT protocol with Quality of Service (QoS) level 2, ensuring exactly-once message delivery over the public internet. These PLC programs demonstrate practical edge–cloud integration, secure telemetry exchange, and control coordination in an Industrial IoT setting. The dataset is intended to support reproducibility, validation, and further research on industrial edge–cloud architectures, legacy system migration, and Industry 4.0–compliant control frameworks.

Table S1.qRT-PCR Primer Sequence List

The full corpus is curated across multiple STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset. Dataset composition (full corpus): Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada) Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages) Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC. Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel) Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports. This repository includes: A small preview subset of the STEM English Q&A data Flat, viewer-friendly schema for inspection Parquet files suitable for benchmarking and evaluation Purpose of this dataset: Dataset preview and validation Model evaluation and experimentation Schema and format inspection before full-scale access ⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset. For full details, Please contact [Em: vipul.mishra@infobay.ai]

Raw data.

The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset. Dataset composition (full corpus): Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ textbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada) Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages) Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC. Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel) Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports. This repository includes: A small preview subset of the STEM English Q&A data Flat, viewer-friendly schema for inspection Parquet files suitable for benchmarking and evaluation Purpose of this dataset: Dataset preview and validation Model evaluation and experimentation Schema and format inspection before full-scale access ⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset. For further details contact vipul.mishra@infobay.ai

Raw data and Analysis.

The dataset contains information on microbial necromass carbon, sampling depth, sampling sites and other related variables for planted and natural forest ecosystems.