Computers Math

A Rutgers analysis of dozens of artificial intelligence (AI) software programs used in precision, or personalized, medicine to prevent, diagnose and treat disease found that no program exists that can be used for all treatments.
“Precision medicine is one of the most trending subjects in basic and medical science today,” said Zeeshan Ahmed, an assistant professor of medicine at Rutgers Robert Wood Johnson Medical School who led the study, published in Briefings in Bioinformatics. “Major reasons include its potential to provide predictive diagnostics and personalized treatment to variable known and rare disorders. However, until now, there has been very little effort exerted in organizing and understanding the many computing approaches to this field. We want to pave the way for a new data-centric era of discovery in health care.”
Precision medicine, a technology still in its infancy, is an approach to treatment that uses information about an individual’s medical history and genetic profile and relates it to the information of many others to find patterns that can help prevent, diagnose or treat a disease. The AI-based approach rests on a high level of both computing power and machine-learning intelligence because of the enormous scope of medical and genetic information scoured and analyzed for patterns.
The comparative and systematic review, believed by the authors to be one of the first of its kind, identified 32 of the most prevalent precision medicine AI approaches used to study preventive treatments for a range of diseases, including obesity, Alzheimer’s, inflammatory bowel disease, breast cancer and major depressive disorder. The bevy of AI approaches analyzed in the study — the researchers combed through five years of high-quality medical literature — suggest the field is advancing rapidly but is suffering from disorganization, Ahmed said.
In AI, software programs simulate human intelligence processes. In machine learning, a subcategory of AI, programs are designed to “learn” as they process more and more data, becoming ever more accurate at predicting outcomes. The effort rests on algorithms, step-by-step procedures for solving a problem or performing a computation.
Researchers such as Ahmed, who conducts studies on cardiovascular genomics at the Rutgers Institute for Health, Health Care Policy and Aging Research (IFH), are racing to collect and analyze complex biological data while also developing the computational systems that undergird the endeavor.
Because the use of genetics is “arguably the most data-rich and complex component of precision medicine,” Ahmed said, the team focused especially on reviewing and comparing scientific objectives, methodologies, data sources, ethics and gaps in approaches used.
Those interested in precision medicine, he said, can look to the paper for guidance as to which AI programs may be best suited for their research.
To aid the advent of precision medicine, the study concluded that the scientific community needs to embrace several “grand challenges,” from addressing general issues such as improved data standardization and enhanced protection of personal identifying information to more technical issues such as correcting for errors in genomic and clinical data.
“AI has the potential to play a vital role to achieve significant improvements in providing better individualized and population healthcare at lower costs,” Ahmed said. “We need to strive to address possible challenges that continue to slow the advancements of this breakthrough treatment approach.”
Other Rutgers researchers involved in the study included Sreya Vadapalli and Habiba Abdelhalim, research assistants at the IFH, and Saman Zeeshan, a bioinformatics research scientist and former postdoctoral research associate at the Rutgers Cancer Institute of New Jersey.
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Materials provided by Rutgers University. Original written by Kitta MacPherson. Note: Content may be edited for style and length. More

When some materials are cooled to a certain temperature, they lose electric resistance, becoming superconductors.
In this state, an electric charge can course through the material indefinitely, making superconductors a valuable resource for transmitting high volumes of electricity and other applications. Superconductors ferry electricity between Long Island and Manhattan. They’re used in medical imaging devices such as MRI machines, in particle accelerators and in magnets such as those used in maglev trains. Even unexpected materials, such as certain ceramic materials, can become superconductors when cooled sufficiently.
But scientists previously have not understood what occurs in a material to make it a superconductor. Specifically, how high-temperature superconductivity, which occurs in some copper-oxide materials, works hasn’t been previously understood. A 1966 theory examining a different type of superconductors posited that electrons which spin in opposite directions bind together to form what’s called a Cooper pair and allow electric current to pass through the material freely.
A pair of University of Michigan-led studies examined how superconductivity works, and found, in the first paper, that about 50% of superconductivity can be attributed to the 1966 theory — but the reality, examined in the second paper, is a bit more complicated. The studies, led by recent U-M doctoral graduate Xinyang Dong and U-M physicist Emanuel Gull, are published in Nature Physics and the Proceedings of the National Academy of Science.
Electrons floating in a crystal need something to bind them together, Gull said. Once you have two electrons bound together, they build a superconducting state. But what ties these electrons together? Electrons typically repel each other, but the 1966 theory suggested that in a crystal with strong quantum effects, the electron-electron repulsion is being screened, or absorbed, by the crystals.
While the electron repulsion is absorbed by the crystal, an opposite attraction emerges from the spinning properties of the electrons — and causes the electrons to bind in Cooper pairs. This underlies the lack of electronic resistivity. However, the theory doesn’t account for complex quantum effects in these crystals. More

An advance in the use of antiferromagnetic materials in memory storage devices has been made by an international team of physicists.
Antiferromagnets are materials that have an internal magnetism caused by the spin of electrons, but almost no external magnetic field. They are of interest because of their potential for data storage since absence of this external (or ‘long range’) magnetic field means the data units — bits — can be packed in more densely within the material.
This is in contrast to ferromagnets, used in standard magnetic memory devices. The bits in these devices do generate long-range magnetic fields, which prevent them being packed too closely, because otherwise they would interact.
The property that is measured to read out an antiferromagnetic bit is called the Hall effect, which is a voltage that appears perpendicular to the applied current direction. If the spins in the antiferromagnet are all flipped, the Hall voltage changes sign. So one sign of the Hall voltage corresponds to a ‘1’, and the other sign to a ‘0’ — the basis of binary code used in all computing systems.
Although scientists have known about the Hall effect in ferromagnetic materials for a long time, the effect in antiferromagnets has only been recognised in the past decade or so and is still poorly understood.
A team of researchers at the University of Tokyo, in Japan, Cornell and Johns Hopkins Universities in the USA and the University of Birmingham in the UK have suggested an explanation for the ‘Hall effect’ in a Weyl antiferromagnet (Mn3Sn), a material which has a particularly strong spontaneous Hall effect.
Their results, published in Nature Physics, have implications for both ferromagnets and antiferromagnets — and therefore for next generation memory storage devices overall.
The researchers were interested in Mn3Sn because it is not a perfect antiferromagnet, but does have a weak external magnetic field. The team wanted to find out if this weak magnetic field was responsible for the Hall effect.
In their experiment, the team used a device invented by Doctor Clifford Hicks, at the University of Birmingham, who is also a co-author on the paper. The device can be used to apply a tunable stress to the material being tested. By applying this stress to this Weyl antiferromagnet, the researchers observed that the residual external magnetic field increased.
If the magnetic field were driving the Hall effect, there would be a corresponding effect on the voltage across the material. The researchers showed that, in fact, the voltage does not change substantially, proving that the magnetic field is not important. Instead, they concluded, the arrangement of spinning electrons within the material is responsible for the Hall effect.
Clifford Hicks, co-author on the paper at the University of Birmingham, said: “These experiments prove that the Hall effect is caused by the quantum interactions between conduction electrons and their spins. The findings are important for understanding — and improving — magnetic memory technology.”
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Topological insulators, or TIs, have two faces: Electrons flow freely along their surface edges, like cars on a superhighway, but can’t flow through the interior of the material at all. It takes a special set of conditions to create this unique quantum state — part electrical conductor, part insulator — which researchers hope to someday exploit for things like spintronics, quantum computing and quantum sensing. For now, they’re just trying to understand what makes TIs tick.
In the latest advance along those lines, researchers at the Department of Energy’s SLAC National Accelerator Laboratory and Stanford University systematically probed the “phase transition” in which a TI loses its quantum properties and becomes just another ordinary insulator.
They did this by using spiraling beams of laser light to generate harmonics — much like the vibrations of a plucked guitar string — from the material they were examining. Those harmonics make it easy to distinguish what’s happening in the superhighway layer from what’s happening in the interior and see how one state gives way to the other, they reported in Nature Photonics today.
“The harmonics generated by the material amplify the effects we want to measure, making this a very sensitive way to see what’s going on in a TI,” said Christian Heide, a postdoctoral researcher with the Stanford PULSE Institute at SLAC, who led the experiments.
“And since this light-based approach can be done in a lab with tabletop equipment, it makes exploring these materials easier and more accessible than some previous methods.”
These results are exciting, added PULSE principal investigator Shambhu Ghimire, because they show the new method has potential for watching TIs flip back and forth between superhighway and insulating states as it happens and in fine detail — much like a using camera with a very fast shutter speed. More

Swarms of microrobots injected into the human body could unblock internal medical devices and avoid the need for further surgery, according to new research from the University of Essex.
The study is the first-time scientists have developed magnetic microrobotics to remove deposits in shunts — common internal medical devices used to treat a variety of conditions by draining excess fluid from organs.
Shunts are prone to malfunctioning, often caused by blockages due to a build-up of sediment. The sediment not only narrows and obstructs liquid passing through the shunt, but it also affects the shunt’s flexibility. This leads to patients needing repeated, invasive surgeries throughout their lives either to replace the shunt or use a catheter to remove the blockage.
However, this new research, led by microrobotics expert Dr Ali Hoshiar, from Essex’s School of Computer Science and Electronic Engineering, has shown there could be a wireless, non-invasive alternative to clearing the blockage in a shunt.
Published in the IEEE Transaction on Biomedical Engineering journal, Dr Hoshiar and his team have shown that a swarm of hundreds of microrobots — made of nano size magnetic nanoparticles — injected into the shunt could remove the sediment instead.
“Once the magnetic microrobots are injected into the shunt they can be moved along the tube to the affected area using a magnetic field, generated by a powerful magnet on the body’s surface,” explained Dr Hoshiar. “The swarm of microrobots can then be moved so they scrape away the sediment, clearing the tube.
“The non-invasive nature of this method is a considerable advantage to existing methods as it will potentially eliminate the risk of surgery and a surgery-related infection, thereby decreasing recovery time.”
With each microrobot smaller than the width of a human hair, once the swarm has done its job, it can either be guided to the stomach via a magnetic field or bodily fluid, so they leave the body naturally. Because the microrobots have very high biocompatibility they will not cause toxicity.
The research also found a direct relation between the strength of the magnetic field and the success of scraping away the sediment in the shunt.
This is the first proof-of-concept experiment using microswarms for opening a blockage in a shunt. The next stage of this research is to work with clinicians to carry out trials. The researchers are also looking at how the concept can be used to other applications.
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Researchers report an experimental demonstration of a space-to-ground quantum key distribution (QKD) network using a compact QKD terminal aboard the Chinese Space Lab Tiangong-2 and four ground stations. The new QKD system is less than half the weight of the system the researchers developed for the Micius satellite, which was used to perform the world’s first quantum-encrypted virtual teleconference.
The demonstration represents an important step toward practical QKD based on constellations of small satellites, a setup considered one of the most promising routes to creating a global quantum communication network.
“QKD offers unconditional security by using single photons to encode information between two distant terminals,” said research team member Cheng-Zhi Peng from the University of Science and Technology of China. “The compact system we developed can reduce the cost of implementing QKD by making it possible to use small satellites.”
Peng and researchers from other institutions in China describe their new system and experimental results in Optica, Optica Publishing Group’s journal for high-impact research. They also found that QKD performance can be boosted by building a network of satellites orbiting at different angles, or inclinations, in relation to the equator.
“Our new work demonstrates the feasibility of a space-ground QKD network based on a compact satellite payload combined with constellations of satellites with different orbit types,” said Peng. “In the near future, this type of QKD system could be used in applications that require high security such as government affairs, diplomacy and finance.”
Shrinking the QKD system
QKD uses the quantum properties of light to generate secure random keys for encrypting and decrypting data. In previous work, the research group demonstrated satellite-to-ground QKD and satellite-relayed intercontinental quantum networks using the Micius satellite. However, the QKD system used aboard that satellite was bulky and expensive. About the size of a large refrigerator, the system weighed around 130 kg and required 130 W of power. More

An international team of researchers has designed and built a chip that runs computations directly in memory and can run a wide variety of AI applications-all at a fraction of the energy consumed by computing platforms for general-purpose AI computing.
The NeuRRAM neuromorphic chip brings AI a step closer to running on a broad range of edge devices, disconnected from the cloud, where they can perform sophisticated cognitive tasks anywhere and anytime without relying on a network connection to a centralized server. Applications abound in every corner of the world and every facet of our lives, and range from smart watches, to VR headsets, smart earbuds, smart sensors in factories and rovers for space exploration.
The NeuRRAM chip is not only twice as energy efficient as the state-of-the-art “compute-in-memory” chips, an innovative class of hybrid chips that runs computations in memory, it also delivers results that are just as accurate as conventional digital chips. Conventional AI platforms are a lot bulkier and typically are constrained to using large data servers operating in the cloud.
In addition, the NeuRRAM chip is highly versatile and supports many different neural network models and architectures. As a result, the chip can be used for many different applications, including image recognition and reconstruction as well as voice recognition.
“The conventional wisdom is that the higher efficiency of compute-in-memory is at the cost of versatility, but our NeuRRAM chip obtains efficiency while not sacrificing versatility,” said Weier Wan, the paper’s first corresponding author and a recent Ph.D. graduate of Stanford University who worked on the chip while at UC San Diego, where he was co-advised by Gert Cauwenberghs in the Department of Bioengineering.
The research team, co-led by bioengineers at the University of California San Diego, presents their results in the Aug. 17 issue of Nature. More

Researchers from Göttingen (Germany) and Lausanne (Switzerland) have successfully created electron-photon pairs in a controlled way in an electron microscope for the first time. Using a new method, they could precisely detect the involved particles. The findings of the study expand the toolbox of quantum technology.
Faster computers, tap-proof communication, better car sensors — quantum technologies have the potential to revolutionize our lives just as once the invention of computers or the internet. Experts worldwide are trying to implement findings from basic research into quantum technologies. To this end, they often require individual particles, such as photons — the elementary particles of light — with tailored properties. However, obtaining individual particles is complicated and requires intricate methods. In a study recently published in the journal Science, researchers now present a new method that simultaneously generates two individual particles in form of a pair.
The international team from the Göttingen Max Planck Institute (MPI) for Multidisciplinary Sciences, the University of Göttingen, and the Swiss Federal Institute of Technology in Lausanne (EPFL) succeeded in coupling single free electrons and photons in an electron microscope. In the Göttingen experiment, the beam from an electron microscope passes through an integrated optical chip, fabricated by the Swiss team. The chip consists of a fiber-optic coupling and a ring-shaped resonator that stores light by keeping moving photons on a circular path. “When an electron scatters at the initially empty resonator, a photon is generated,” explains Armin Feist, scientist at the MPI and one of the study’s first authors. “In the process, the electron loses exactly the amount of energy that the photon requires to be created virtually from nothing in the resonator. As a result, the two particles are coupled through their interaction and form a pair.” With an improved measurement method, the physicists could precisely detect the individual particles involved and their simultaneous manifestation.
Future quantum technology with free electrons
“With the electron-photon pair, we only need to measure one particle to obtain information about the energy content and temporal appearance of the second one,” emphasizes Germaine Arend, a PhD candidate at the MPI and also first author of the study. This allows researchers to use one quantum particle in an experiment while, at the same time, confirming its presence by detecting the other particle, in a so-called heralding scheme. Such a feature is necessary for many applications in quantum technology.
Max Planck Director Claus Ropers sees electron-photon pairs as a new opportunity for quantum research: “The method opens up fascinating new possibilities in electron microscopy. In the field of quantum optics, entangled photon pairs already improve imaging. With our work, such concepts can now be explored with electrons.” Tobias Kippenberg, professor at EPFL adds, “For the first time, we bring free electrons into the toolbox of quantum information science. More broadly, coupling free electrons and light using integrated photonics could open the way to a new class of hybrid quantum technologies.”
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