A roadmap for health care leaders to execute intrinsic agency toward equity, supporting SDGs 3 and 10.

Digital health programs are urgently needed to accelerate the adoption of Artificial Intelligence and Clinical Decision Support Systems (AI-CDSS) in clinical settings. However, such programs are still lacking for undergraduate medical students, and new approaches are required to prepare them for the arrival of new and unknown technologies.

The study discusses the fundamental concepts of blockchain technology, including cryptography, hash functions, digital signatures, and Merkle trees. Providing an in-depth presentation of the mechanism for reaching consensus.

This study supports SDG's 9 and 13 through its discussion of the effects of optimizing Municipal Solid Waste management systems by increasing waste collection coverage and implementing diverse streams of waste valorization, causing a decrease of atmospheric pollution.

Studies on the distribution of microplastics in aquatic environments are summarized and environmental and anthropogenic factors affecting microplastic toxicity are reviewed

This paper sought to explore similarities, variations and determinants of sustainable plastics consumption behavior within a sample of approximately 7600 respondents from eight European countries. We find that most consumers engage in sustainable plastics behavior during the usage phase, by reusing plastic containers and refilling water bottles. The regression analysis suggests that personal responsibility, having high values for nature, being a member of a nature organization and feeling knowledgeable about plastic pollution are important predictors of sustainable plastics consumption.

The research aims to assess the environmental sustainability of measurements, and the investigation is conducted through two case studies within the information and communication technology sector. The authors put forward recommendations for increasing a measurement's environmental sustainability.

This article supports SDG 13 and 9 by providing exploring the estimation of the role of the studied species as sinks of atmospheric carbon.

This paper show the mathematical and theoretical background of the machine learning algorithm used in this work, the LSTM. The data used are described and the methodology of framework is presented. It shows the predictions results based on LSTM and comparisons with ERA5 and buoy observations.

This Study explores the racial disparities that exist in the emergency departments of 4 hospitals, when they are most prevalent, and how patients' sociodemographic characteristics impact image acquisition time, raising awareness for SDGs 3, 9 and 10.