While most states mandate screenings to guide early interventions for children struggling with reading, many teachers feel underprepared to administer and interpret them.
New research shows attention lapses due to sleep deprivation coincide with a flushing of fluid from the brain — a process that normally occurs during sleep.
Selective crystallization can greatly improve the purity, selectivity, and active yield of viral vector-based gene therapy drugs, MIT study finds.
Adding amino acids to certain protein-based medications can improve stability and effectiveness. New MIT research demonstrates how it works.
The discovery will help researchers understand how chemicals form and change before stars and planets are born.
PhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.
An alternative to massive particle colliders, the approach could reveal insights into the universe’s starting ingredients.
The DIGIT imaging tool could enable the design of quantum devices and shed light on atomic-scale processes in cells and tissues.
Researchers find that design elements of data visualizations influence viewers’ assumptions about the source of the information and its trustworthiness.
Scientists identified how circuit connections in fruit flies tune to the right size and degree of signal transmission capability. Understanding this could lead to a way to tweak abnormal signal transmission in certain disorders.
How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.
Launched in 2008, the program has expanded exponentially and spent $30 million on high-impact research.
To reduce waste, the Refashion program helps users create outlines for adaptable clothing, such as pants that can be reconfigured into a dress. Each component of these pieces can be replaced, rearranged, or restyled.
Enabled by a new high-resolution mapping technique, the findings overturn a long-held belief that the genome loses its 3D structure when cells divide.
After being trained with this technique, vision-language models can better identify a unique item in a new scene.