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The authors access a panel of leaf traits across ten deciduous tree species to explore adaptive strategies between large and small trees.

The authors investigated the impact of light pollution on astrophotography.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

The study explored converting Gracilaria seaweed waste—known for releasing toxic hydrogen sulfide when decomposed—into biochar as a sustainable solution for waste management and soil improvement.

The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.

The authors studied the response of various construction materials to UV solar radiation and heat.

The authors looked at how soil temperature changes with fire to develop a sensor system that could aid in earlier detection of fires.

The authors looked at the impact of vitamin A (retinol) on growth of S. epidermidis (most abundant bacterium on the skin) and E. coli (found in the gut microbiome, but not on the skin).

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.