Tyler O'Neal, Staff Editor ACADEMIA

UVA scientists use machine learning to improve gut disease diagnosis

A study published in the open access journal JAMA Open Network June 14 by scientists at the University of Virginia schools of Engineering and Medicine and the Data Science Institute says machine learning algorithms applied to biopsy images can shorten the time for diagnosing and treating a gut disease that often causes permanent physical and cognitive damage in children from impoverished areas.

In places where sanitation, potable water and food are scarce, there are high rates of children suffering from environmental enteric dysfunction, a disease that limits the gut's ability to absorb essential nutrients and can lead to stunted growth, impaired brain development and even death.

The disease affects 20 percent of children under the age of 5 in low- and middle-income countries, such as Bangladesh, Zambia and Pakistan, but it also affects some children in rural Virginia. {module In-article} 

For Dr. Sana Syed, an assistant professor of pediatrics in the UVA School of Medicine, this project is an example of why she got into medicine. "You're talking about a disease that affects hundreds of thousands of children, and that is entirely preventable," she said.

Syed is working with Donald Brown, founding director of the UVA Data Science Institute and W.S. Calcott Professor in the Department of Engineering Systems and Environment, to incorporate machine learning into the diagnostic process for health officials combating this disease. Syed and Brown are using a deep learning approach called "convolutional neural networks" to train computers to read thousands of images of biopsies. Pathologists can then learn from the algorithms how to more effectively screen patients based on where the neural network is looking for differences and where it is focusing its analysis to get results.

"These are the same types of algorithms Google is using in facial recognition, but we're using them to aid in the diagnosis of disease through biopsy images," said Brown.

The machine learning algorithm can provide insights that have evaded human eyes, validate pathologists' diagnoses and shorten the time between imaging and diagnosis, and from a technical engineering perspective, might be able to offer a look into data science's "black boxes" by giving clues into the thinking mechanism of the machine.

But for Syed, it is still about saving lives.

"There is so much poverty and such an unfair set of consequences," she said. "If we can use these cutting-edge technologies and ways of looking at data through data science, we can get answers faster and help these children sooner."

German theoretical physicists discover immortal quantum particles

Tyler O'Neal, Staff Editor ACADEMIA

Oscillating quasiparticles: the cycle of decay and rebirth

As the saying goes, nothing lasts forever. The laws of physics confirm this: on our planet, all processes increase entropy, thus molecular disorder. For example, a broken glass would never put itself back together again.

Theoretical physicists at the Technical University of Munich (TUM) and the Max Planck Institute for the Physics of Complex Systems have discovered that things which seem inconceivable in the everyday world are possible on a microscopic level.

"Until now, the assumption was that quasiparticles in interacting quantum systems decay after a certain time. We now know that the opposite is the case: strong interactions can even stop decay entirely," explains Frank Pollmann, Professor for Theoretical Solid-State Physics at the TUM. Collective lattice vibrations in crystals, so-called phonons, are one example of such quasiparticles. CAPTION Strong quantum interactions prevent quasiparticles from decay. CREDIT K. Verresen / TUM{module In-article}

The concept of quasiparticles was coined by the physicist and Nobel prize winner Lev Davidovich Landau. He used it to describe collective states of lots of particles or rather their interactions due to electrical or magnetic forces. Due to this interaction, several particles act like one single one.

Numeric methods open up new perspectives

Up until now, it wasn't known in detail which processes influence the fate of these quasiparticles in interacting systems," says Pollmann. "It is only now that we possess numerical methods with which we can calculate complex interactions as well as computers with a performance which is high enough to solve these equations."

"The result of the elaborate simulation: admittedly, quasiparticles do decay, however new, identical particle entities emerge from the debris," says the lead author, Ruben Verresen. "If this decay proceeds very quickly, an inverse reaction will occur after a certain time and the debris will converge again. This process can recur endlessly and a sustained oscillation between decay and rebirth emerges."

From a physical point of view, this oscillation is a wave which is transformed into matter, which, according to quantum mechanical wave-particle duality, is possible. Therefore, the immortal quasiparticles do not transgress the second law of thermodynamics. Their entropy remains constant, decay has been stopped.

The reality check

The discovery also explains phenomena which were baffling until now. Experimental physicists had measured that the magnetic compound Ba3CoSB2O9 is astonishingly stable. Magnetic quasiparticles, magnons, are responsible for it. Other quasiparticles, rotons, ensure that helium which is a gas on the earth's surface becomes a liquid at absolute zero which can flow unrestricted.

"Our work is purely basic research," emphasizes Pollmann. However, it is perfectly possible that one day the results will even allow for applications, for example the construction of durable data memories for future quantum supercomputers.

Small currents for big gains in spintronics

Tyler O'Neal, Staff Editor ACADEMIA

A new low-power magnetic switching component could aid spintronic devices

University of Tokyo researchers have created an electronic component that demonstrates functions and abilities important to future generations of computational logic and memory devices. It is between one and two orders of magnitude more power efficient than previous attempts to create a component with the same kind of behavior. This fact could help it realize developments in spintronics.

If you're a keen technophile and like to keep up to date with current and future developments in the field of supercomputing, you might have come across the emerging field of spintronic devices. In a nutshell, spintronics explores the possibility of high-performance, low-power components for logic and memory. It's based around the idea of encoding information into the spin -- a property related to angular momentum -- of an electron, rather than by using packets of electrons to represent logical bits, 1s, and 0s. This diagram shows how magnetization reverses in a GaMnAs crystal.{module In-article}

One of the keys to unlock the potential of spintronics lies in the ability to quickly and efficiently magnetize materials. University of Tokyo Professor Masaaki Tanaka and colleagues have made an important breakthrough in this area. The team has created a component -- a thin film of ferromagnetic material -- the magnetization of which can be fully reversed with the application of very small current densities. These are between one and two orders of magnitude smaller than the current densities required by previous techniques, so this device is far more efficient.

"We are trying to solve the problem of the large power consumption required for magnetization reversal in magnetic memory devices," said Tanaka. "Our ferromagnetic semiconductor material -- gallium manganese arsenide (GaMnAs) -- is ideal for this task as it is a high-quality single crystal. Less ordered films have an undesirable tendency to flip electron spins. This is akin to resistance in electronic materials and it's the kind of inefficiency we try to reduce."

The GaMnAs film the team used for their experiment is special in another way too. It is especially thin thanks to a fabrication process known as molecular beam epitaxy. With this method, devices can be constructed more simply than other analogous experiments which try and use multiple layers rather than single-layer thin films.

"We did not expect that the magnetization can be reversed in this material with such a low current density; we were very surprised when we found this phenomenon," concludes Tanaka. "Our study will promote research of material development for more efficient magnetization reversal. And this in turn will help researchers realize promising developments in spintronics."