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Scientists have developed a novel computational approach that incorporates individual patients’ brain activity to calculate optimal, personalized brain stimulation treatment for Alzheimer’s disease. Lazaro Sanchez-Rodriguez of the University of Calgary, Canada, and colleagues present their new framework in PLOS Computational Biology.

Electrical stimulation of certain parts of the could help promote healthy activity in neural circuits impaired by Alzheimer’s disease, a neurodegenerative condition. This experimental treatment has shown some promise in . However, all patients currently receive identical treatment protocols, potentially leading to different outcomes according to individual variations in brain signaling.

To investigate the possibility of personalized brain stimulation, Sanchez-Rodriguez and colleagues took a theoretical approach. They built a computational tool that incorporates patients’ MRI scans and physiological brain signaling measurements to calculate optimal brain stimulation signals, with the goal of delivering efficient, effective personalized treatment.

Superconductors—metals in which electricity flows without resistance—hold promise as the defining material of the near future, according to physicist Brad Ramshaw, and are already used in medical imaging machines, drug discovery research and quantum computers being built by Google and IBM.

However, the super-low temperatures need to function—a few degrees above absolute zero—make them too expensive for wide use.

In their quest to find more useful superconductors, Ramshaw, the Dick & Dale Reis Johnson Assistant Professor of physics in the College of Arts and Sciences (A&S), and colleagues have discovered that magnetism is key to understanding the behavior of electrons in “high-temperature” superconductors. With this finding, they’ve solved a 30-year-old mystery surrounding this class of superconductors, which function at much higher temperatures, greater than 100 degrees above absolute zero. Their paper, “Fermi Surface Transformation at the Pseudogap Critical Point of a Cuprate Superconductor,” published in Nature Physics March 10.

Circa 2015


Stanford bioengineer Manu Prakash and his students have developed a synchronous computer that operates using the unique physics of moving water droplets.

Computers and water typically don’t mix, but in Manu Prakash’s lab, the two are one and the same. Prakash, an assistant professor of bioengineering at Stanford, and his students have built a synchronous computer that operates using the unique physics of moving water droplets.

The computer is nearly a decade in the making, incubated from an idea that struck Prakash when he was a graduate student. The work combines his expertise in manipulating droplet fluid dynamics with a fundamental element of computer science – an operating clock.

Want to monitor the brain of a running tiger?

First, catch the tiger.

Then attach Bio-FlatScope, the latest iteration of lensless microscopy being developed at Rice University.

That particular use is fanciful but not far-fetched, according to Jacob Robinson, an electrical and computer engineer at Rice’s George R. Brown School of Engineering who led the recent effort to test Bio-FlatScope in living creatures.

Computer engineers at Duke University have developed virtual eyes that simulate how humans look at the world accurately enough for companies to train virtual reality and augmented reality programs. Called EyeSyn for short, the program will help developers create applications for the rapidly expanding metaverse while protecting user data.

The results have been accepted and will be presented at the International Conference on Information Processing in Sensor Networks (IPSN), May 4–6, 2022, a leading annual forum on research in networked sensing and control.

“If you’re interested in detecting whether a person is reading a comic book or advanced literature by looking at their eyes alone, you can do that,” said Maria Gorlatova, the Nortel Networks Assistant Professor of Electrical and Computer Engineering at Duke.

In findings that could help advance another “viable pathway” to fusion energy, research led by Lawrence Livermore National Laboratory (LLNL) physicists has proven the existence of neutrons produced through thermonuclear reactions from a sheared-flow stabilized Z-pinch device.

The researchers used advanced computer modeling techniques and diagnostic measurement devices honed at LLNL to solve a decades-old problem of distinguishing neutrons produced by from ones produced by ion beam-driven instabilities for plasmas in the magneto-inertial fusion regime.

While the team’s previous research showed neutrons measured from sheared-flow stabilized Z-pinch devices were “consistent with thermonuclear production, we hadn’t completely proven it yet,” said LLNL physicist Drew Higginson, one of the co-authors of a paper recently published in Physics of Plasmas.