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A new automated system of monitoring and classifying persistent vibrations at active volcanoes can eliminate the hours of manual effort needed to document them.

Graduate student researcher Darren Tan at the University of Alaska Fairbanks Geophysical Institute led development of the system, which is based on machine learning. Machine learning is a branch of artificial intelligence focused on building systems that learn from data, identify patterns and make decisions with minimal human intervention.

Details about Tan’s automated system were published June 11 in the journal JGR Solid Earth.

His system documents volcanic tremor, a continuous, rhythmic seismic signal that emanates from a volcano. It often indicates underground movement of magma or gas and occurs regularly at active volcanoes.

Read more at: University of Alaska Fairbanks

Photo Credit: Ben David Jacob

Researchers used more than 120 years of data to decipher how melting ice, dwindling groundwater, and rising seas are nudging the planet’s spin axis and lengthening days.

Researchers at the University of Cambridge demonstrate that the plant hormone gibberellin (GA) is essential for the formation and maturation of nitrogen-fixing root nodules in legumes and can also increase nodule size.

In a large Singapore cohort study involving over 13,000 participants spanning close to 20 years, higher consumption of fruits during midlife was found to be associated with lower odds of depressive symptoms at late-life.

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