The Organization for Women in Science for the Developing World and the Elsevier Foundation celebrated the 2023 OWSD-EF Awards for Women Scientists, with researchers from Benin, Bolivia, Guatemala, Palestine, Mongolia, South Africa and Sri Lanka. Awarding women scientists means not only recognizing their impressive work but empowering them to be role models. Read more about these incredible women! This article relates to SDG 5, Gender Equality.
Elsevier,
Geography and Sustainability, Volume 4, Issue 2, June 2023, Pages 112-126
This article supports SDG 2, SDG 3 and SDG 13 by demonstrating the importance of enhancing farmers’ perceptions of of Climate-Smart Agriculture potential to promote environmental stewardship with motivations by demographic, socioeconomic and ecological factors.
Progress in Oceanography, Volume 211, February 2023
This study shows downscaled climate projections that, without strong curbing of emissions, the California Current System (CCS) will undergo significant change this century, including 2–4 °C warming of sea surface temperature and an almost ubiquitous shift to novel conditions
Elsevier,
Ocean Modelling, Volume 181, February 2023
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.
Elsevier,
Ocean Modelling, Volume 181, February 2023
This paper based on three implemented Regional Climate Models (RCMs), namely CMCC-CCLM, CNRM-ALADIN52, and GUF-CCLM-NEMO, for RCP4.5 and RCP8.5 scenarios of the 21st century. Atmospheric modelling datasets cover the Reference (1971–2000) and Future (2071–2100) Periods of climate projections. The results produced within this study can be used for investigations in specific locations of the Mediterranean basin within integrated hydrologic/hydrodynamic modelling under projected climate change conditions during the 21st century.
Elsevier,
Engineering Applications of Artificial Intelligence, Volume 117, Part A, 2023, 105617
An examination of the challenges involved in water demand forecasting, with a particular focus on the impact of COVID-19 on the performance of various machine learning models designed for this purpose.
