Friday, October 27, 2017

Machine learning used to predict earthquakes in a lab setting

San Andreas Fault, from PhysOrg.

A group of researchers from the UK and the US have used machine learning techniques to successfully predict earthquakes. Although their work was performed in a laboratory setting, the experiment closely mimics real-life conditions, and the results could be used to predict the timing of a real earthquake.

The team at Los Alamos, led by Paul Johnson, studies the interactions among earthquakes, precursor quakes (often very small earth movements) and faults, with the hope of developing a method to predict earthquakes. (Full Story)

Doped dots release laser light more efficiently

Quantum dot laser light, LANL image.

Los Alamos National Laboratory’s Nanotech team has found a way to dope quantum dots with additional electrons to improve their efficiency in tiny laser devices such as opthalmic surgery scalpels.

“When we properly tailor the compositional profile within the particles during their fabrication, and then inject two or more electrons in each dot, they become more able to emit laser light. Importantly, they require considerably less power to initiate the lasing action," said Victor Klimov, leader of the Nanotech team. (Full Story)

Modeling influenza virology and pharmacology

Viral kinetic models can also be combined with PK/PD models to explore how exposure to antiviral drugs reduces viral load and attenuates disease symptoms. PK/PD models have also been used to describe the mechanisms behind the emergence and spread of drug resistance. For example, a research team based out of Los Alamos National Laboratory developed a model that included oseltamivir PK, symptom dynamics, and patient physiological variability. The findings from this model suggested that the timing of initiating prophylactic oseltamivir treatment was a primary factor in the emergence of drug resistance. (Full Story)

Lab awards 2017 Fellows Prizes

From top left: Light, Sinitsyn and Mukundan. Bottom, from left: Flynn and Albright. LANL photo.

Five Los Alamos National Laboratory scientists have been awarded the laboratory’s prestigious Fellows Prize in the areas of science or engineering research and leadership.

Among those awarded are Eric Flynn, Harshini Mukundan and Nikolai Sinitsyn were awarded the Fellows’ Prize for Outstanding Research, and Brian Albright and Tess Light were awarded the Fellows Prize for Outstanding Leadership.

“These scientists demonstrate the breadth of scientific research and leadership supporting the Laboratory’s national security mission and benefiting society,” said Alan Bishop, principal associate director for Science, Technology and Engineering. “Their innovative scientific discoveries and leadership represent the highest level of excellence. I congratulate all of them on their achievements.” (Full Story)

Seven Los Alamos scientists honored as APS Fellows

Clockwise from upper right: Zapf, Trugman, Smilowitz, Lewellen, Fontes, Htoon and Kawano. LANL photo.

Seven scientists at Los Alamos National Laboratory were tapped this year as new Fellows of the American Physical Society (APS), a significant honor for the Laboratory and its people. The honorees are Christopher J. Fontes, Han Htoon, Toshihiko Kawano, John W. Lewellen, Laura Beth Smilowitz, Stuart A. Trugman and Vivien Zapf.

"Selection as American Physical Society fellows reflects the vibrant engagement that Los Alamos scientists have with the larger scientific community," said Laboratory Director Charlie McMillan. This year, as Los Alamos saw the admission of seven scientists into APS, Director McMillan noted. (Full Story)

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