CERENA researchers participate in DEQ Open Laboratories

In the end of April, Amélia Lemos, Francisco Lemos, and Rosana Pinto participated in the Department of Chemical Engineering (DEQ) of Instituto Superior Técnico Open Laboratories. Amélia and Francisco Lemos gave a talk about how engineering could be used to serve humanity, while Rosana focused on how metallic organic frameworks can be used as magical sponges of the future.

RESTAURA - Revitalizar a Terra: Avaliação da saúde do solo, análise de risco e reabilitação de antigas áreas mineiras

Waste resulting from coal and mineral mining, such as Au-As, Sb-Au, and W, deposited in tailings ponds, represents a source of pollutants. Particles released into the atmosphere by wind, as well as the mobilization and leaching of potentially hazardous, phytotoxic, and zootoxic elements, affect the quality of air, soil, surface water, and groundwater, causing environmental pollution and impacts on biodiversity and human health.

DAEDALUS - The Labyrinth of Warm-Bloodedness: a journey into the origins of dinosaur-bird endothermy via semicircular canal biomechanics

The DAEDALUS project aims to uncover how warm-bloodedness (endothermy) developed in birds and their dinosaur ancestors by studying the semicircular canal system in the inner ear (or labyrinth), vital for balance and orientation. The principle: as fluid warms, it becomes less viscous. Thus, as early endotherms evolved endothermy, their ear canal fluid's viscosity decreased, leading to necessary adaptations in canal morphology and/or physicochemical properties for survival.

Spatial Data Sciences

Have you ever wondered why a phenomenon occurs in a specific location? What tools do we have to model and predict phenomena with a significant spatial component? Spatial Data Science offers insights into these questions.

Spatial Data Science is an interdisciplinary field that integrates traditional data science methods-such as Machine Learning and Artificial Intelligence-with spatial analysis methodologies, including Geographic Information Systems, Geostatistics, and Remote Sensing. This combination enables us to understand, characterize, and manage big spatial data.