Resultados de investigación

[EN] This article introduces a nationwide dataset that maps how 112,814 Spanish firms communicate and implement artificial intelligence (AI) on their corporate websites in 2023 and 2025, resulting in 225,628 firm-year observations. Using a systemic pipeline based on large language models (LLMs), website text is segmented, semantically filtered, and evaluated with a structured rubric to identify explicit evidence of AI use in internal processes and in products or services. The dataset offers a detailed portrait of AI adoption across regions (NUTS 3), industries, and firm size categories. For each province–sector–size combination, it reports whether firms adopt AI, whether they apply it internally, whether it is embedded in their offerings, and how many firms have valid website content. This multi-dimensional structure enables users to explore territorial patterns, sectoral differences, and size-related disparities in the uptake of AI. By providing indicators for two benchmark years, the dataset supports the study of how AI adoption evolves across the Spanish business landscape. It offers a reproducible and scalable foundation for research on technological diffusion, regional digitalisation, and industry-level transformation, and can be readily extended to future years or adapted to other countries.

[EN] The integration of autonomous vehicles (AVs) into road transport requires robust ex-perimental tools to analyze human–machine interaction, particularly under conditions of system disengagement. This study presents the development and validation of the EVACH autonomous driving simulator, designed to reproduce SAE Level 2 and Level 3 driving modes in rural road scenarios. The simulator was customized through hardware and software developments, including a dedicated data acquisition system to ensure accurate detection of braking, steering, and other critical control inputs. Calibration tests demonstrated high reliability, with minor errors in brake and steering control meas-urements, consistent with values observed in production vehicles. To validate the virtual driving rural environment, comparative experiments were conducted between natu-ralistic road tests and simulator-based autonomous driving. Results showed that average speeds in simulation closely matched those recorded on real roads, with differences of less than 1 km/h and significantly lower variability. These findings confirm that the EVACH simulator provides a stable and faithful reproduction of autonomous driving conditions. The platform represents a validated and versatile tool for evaluating driver workload, takeover performance, and human–machine interaction, offering valuable support for current and future research on the safe deployment of automated vehicles.

Datos de la publicación: 10.1007/s10533-020-00657-8 Incluye los datos de análisis químico de suelo, análisis químico de las hojas de la planta y el fraccionamiento de fósforo en el suelo