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Gizmorama - April 19, 2017

Good Morning,

Learn about the creation of fluid with 'negative mass.' It's quite amazing that there is liquid that ignores physics.

Learn about this and more interesting stories from the scientific community in today's issue.

Until Next Time,

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*-- Physicists create fluid with 'negative mass' --*

A team of physicists at Washington State University have created a fluid that ignores Isaac Newton's Second Law of Motion. The fluid has "negative mass." When it's pushed it accelerates backwards.

Almost all matter in the universe obey's Newton's second law -- matter accelerates in the direction of the force applied to it. The new fluid does the opposite.

"With negative mass, if you push something, it accelerates toward you," Michael Forbes, an assistant professor of physics and astronomy at Washington State, said in a news release.

The liquid consists of rubidium atoms cooled to a temperature barely greater than absolute zero. The cooled atoms formed a Bose-Einstein condensate, a phase of matter characterized by slow-moving particles that behave like waves. The matter behaves like a superfluid, meaning its particles move in unison without sacrificing energy.

Researchers used lasers to cool the liquid in a tiny bowl. When scientists broke the bowl, the rubidium atoms rushed outwards. Scientists applied a second set of lasers to alter the spin of the out-rushing atoms. As a result, the atoms took on negative mass.

"Once you push, it accelerates backwards," said Forbes. "It looks like the rubidium hits an invisible wall."

Researchers say their latest experiments -- detailed in the journal Physical Review Letters -- were simpler and offered greater control over negative mass than previous attempts.

"What's a first here is the exquisite control we have over the nature of this negative mass, without any other complications," said Forbes.

The success may allow for exploration of strange phenomena like black holes and neutron stars.

*-- Camera system could replace sensors to monitor premature infants --*

New cameras capable of medically monitoring premature babies in incubators has been developed as part of the Swiss research program Nano-Tera.

The system is about to be tested at University Hospital Zurich, or USZ-CH, and was developed by EPFL, CSEM and USZ to potentially replace skin sensors on premature infants in neonatal incubators in neonatal intensive care units.

The camera system was created to improve the way infants' heart rates and breathing are monitored.

"Skin sensors placed on the babies' chests are so sensitive that they generate false alarms up to 90 percent of the time, mainly caused by the babies moving around," Dr. Jean-Claude Fauchere, a doctor at USZ's neonatal clinic, said in a press release. "This is a source of discomfort for the babies, because we have to check on them every time. It's also a significant stress factor for nurses and a poor use of their time -- it distracts them from managing real emergencies and can affect quality of care."

The cameras are able to detect a baby's pulse by analyzing skin color, which changes slightly every time the heart beats. Breathing is monitored by measuring movements of the thorax and shoulders. Infrared cameras take over at night to continue the monitoring without stopping.

The camera's optical system is sensitive enough to detect minute changes in skin color and uses algorithms to process data in real time.

"We ran an initial study on a group of adults, where we looked at a defined patch of skin on their foreheads," said Sibylle Fallet, a doctoral student at EPFL. "With our algorithms we can track this area when the person moves, isolate the skin pixels and use minor changes in their color to determine the pulse. The tests showed that the cameras produced practically the same results as conventional sensors."

The cameras will be tested on premature babies at the University Hospital Zurich.

*-- Honey bees inspire crime-fighting algorithm --*

Scientists at the University of Granada, in Spain, have created a new algorithm to help law enforcement dismantle problematic social networks, including criminal and terror networks. The researchers inspiration: honey bees.

The bio-inspired algorithm can be used to analyze the connections and relationships among a social network and identify the most dangerous nodes or individuals. Analysis provided by the algorithm could help law enforcement dismantle crime networks or terror cells more effectively and efficiently.

Bee colonies feature highly efficient social structures. They are composed of an organized workforce with well-defined tasks, and their organization and efficiency is reliant upon effective communication.

"Bees form fairly well organized societies, in which each member has a specific role," Manuel Lozano Márquez, a computer scientist at Granada, said in a news release. "There are three main types: scout bees, which are looking for food sources; worker bees, who collect food; and supervisor bees, who wait in the colony."

Scientists at Granada decided to study bee colony organization and behavior -- and the flow of information among different types of bees -- as a model for understanding harmful social networks.

Their analysis showed the traditional method for combating pernicious social networks can be improved upon. Traditionally, law enforcement officials attack crime networks by targeting the most active or dangerous individuals. But removing most important players doesn't ensure the cell or network falls apart.

"In order to find the most effective way of dismantling a network, it is necessary to develop and put into action an optimization process that analyzes a multitude of situations and selects the best option in the shortest time possible," said Humberto Trujillo Mendoza, a behavioral scientist at Granada. "It's similar to what a chess program does when identifying, predicting and checking the possible steps or paths that may occur in a game of chess from a given moment and movement."

The latest research -- detailed in the journal Information Sciences -- can help officials identify not just the most active or dangerous links within a harmful network, but the nodes or actors most important to the network's functionality and efficiency.


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