Computers Math

Using DNA structures as scaffolds, Tim Liedl, a scientist of Ludwig-Maximilians-Universitaet (LMU) in Munich, has shown that precisely positioned gold nanoparticles can serve as efficient energy transmitters.
Since the inception of the field in 2006, laboratories around the world have been exploring the use of ‘DNA origami’ for the assembly of complex nanostructures. The method is based on DNA strands with defined sequences that interact via localized base pairing. “With the aid of short strands with appropriate sequences, we can connect specific regions of long DNA molecules together, rather like forming three-dimensional structures by folding a flat sheet of paper in certain ways,” as Professor Tim Liedl of the Faculty of Physics at LMU explains.
Image and mirror image
Liedl has now used DNA origami to construct chiral objects, i.e. structures that cannot be superimposed by any combination of rotation and translation. Instead they possess ‘handedness’, and are mirror images of one another. Such pairs often differ in their physical properties, for example, in the degree to which they absorb polarized light. This effect can be exploited in many ways. For example, it is the basis for CD spectroscopy (the ‘CD’ here stands for ‘circular dichroism’), a technique that is used to elucidate the overall spatial configuration of chemical compounds, and even whole proteins.
With a view to assembling chiral metal structures, Liedl and his group synthesized complex DNA-origami structures that provide precisely positioned binding sites for the attachment of spherical and rod-shaped gold nanoparticles. The scaffold therefore serves as a template or mold for the placement of nanoparticles at predetermined positions and in a defined spatial orientation. “One can assemble a chiral object based solely on the arrangement of the gold nanoparticles,” says Liedl
Gold is not only chemically robust, as a noble metal it exhibits what are known as surface plasmon resonances. Plasmons are coherent electron oscillations that are generated when light interacts with the surface of a metal structure. “One can picture these oscillations as being like the waves that are excited when a bottle of water is shaken either parallel or at right angles to its long axis,” says Liedl.
Gold nanoparticles as energy transmitters
Oscillations excited in spatially contiguous gold particles can couple to one another, and the plasmons in Liedl’s experiments behave as image and mirror image, thanks to their chiral disposition on the origami scaffold. “This is confirmed by our CD spectroscopic measurements,” says Liedl. In the experiments, the chiral structures are irradiated with circularly polarized light and the level of absorption is measured as a percentage of the input. This enables right- and left-handed arrangements to be distinguished from one another.
In principle, two gold nanorods should be sufficient for the construction of chiral object, as they can be arranged either in the form of an L or an inverted L. However, the rods used in the experiments were relatively far apart (on the nanoscale) and the plasmons excited in one had little effect on those generated in the other, i.e. the two hardly coupled to each other at all. But Liedl and his colleagues had a trick up their sleeves. By appropriate redesign of the origami structure, they were able to position a gold nanosphere between the pair of L-formed rods, which effectively amplified the coupling. CD spectroscopy revealed the presence of energy transitions, thus confirming the hypothesis which the team had derived from simulations.
Liedl envisages two potential settings in which these nanostructures could find practical application. They could be used to detect viruses, since the binding of viral nucleic acids to a gold particle will amplify the CD signal. In addition, chiral plasmonic transmitters could serve as model switching devices in optical computers, in which optical elements replace the transistors that are the workhorses of electronic computers.
Story Source:
Materials provided by Ludwig-Maximilians-Universität München. Note: Content may be edited for style and length. More

It may be possible in the future to use information technology where electron spin is used to store, process and transfer information in quantum computers. It has long been the goal of scientists to be able to use spin-based quantum information technology at room temperature. A team of researchers from Sweden, Finland and Japan have now constructed a semiconductor component in which information can be efficiently exchanged between electron spin and light at room temperature and above. The new method is described in an article published in Nature Photonics.
It is well known that electrons have a negative charge, and they also have another property, namely spin. The latter may prove instrumental in the advance of information technology. To put it simply, we can imagine the electron rotating around its own axis, similar to the way in which the Earth rotates around its own axis. Spintronics — a promising candidate for future information technology — uses this quantum property of electrons to store, process and transfer information. This brings important benefits, such as higher speed and lower energy consumption than traditional electronics.
Developments in spintronics in recent decades have been based on the use of metals, and these have been highly significant for the possibility of storing large amounts of data. There would, however, be several advantages in using spintronics based on semiconductors, in the same way that semiconductors form the backbone of today’s electronics and photonics.
“One important advantage of spintronics based on semiconductors is the possibility to convert the information that is represented by the spin state and transfer it to light, and vice versa. The technology is known as opto-spintronics. It would make it possible to integrate information processing and storage based on spin with information transfer through light,” says Weimin Chen, professor at Linköping University, Sweden, who led the project.
As electronics used today operates at room temperature and above, a serious problem in the development of spintronics has been that electrons tend to switch and randomise their direction of spin when the temperature rises. This means that the information coded by the electron spin states is lost or becomes ambiguous. It is thus a necessary condition for the development of semiconductor-based spintronics that we can orient essentially all electrons to the same spin state and maintain it, in other words that they are spin polarised, at room temperature and higher temperatures. Previous research has achieved a highest electron spin polarisation of around 60% at room temperature, untenable for large-scale practical applications.
Researchers at Linköping University, Tampere University and Hokkaido University have now achieved an electron spin polarisation at room temperature greater than 90%. The spin polarisation remains at a high level even up to 110 °C. This technological advance, which is described in Nature Photonics, is based on an opto-spintronic nanostructure that the researchers have constructed from layers of different semiconductor materials. It contains nanoscale regions called quantum dots. Each quantum dot is around 10,000 times smaller than the thickness of a human hair. When a spin polarised electron impinges on a quantum dot, it emits light — to be more precise, it emits a single photon with a state (angular momentum) determined by the electron spin. Thus, quantum dots are considered to have a great potential as an interface to transfer information between electron spin and light, as will be necessary in spintronics, photonics and quantum computing. In the newly published study, the scientists show that it is possible to use an adjacent spin filter to control the electron spin of the quantum dots remotely, and at room temperature.
The quantum dots are made from indium arsenide (InAs), and a layer of gallium nitrogen arsenide (GaNAs) functions as a filter of spin. A layer of gallium arsenide (GaAs) is sandwiched between them. Similar structures are already being used in optoelectronic technology based on gallium arsenide, and the researchers believe that this can make it easier to integrate spintronics with existing electronic and photonic components.
“We are very happy that our long-term efforts to increase the expertise required to fabricate highly-controlled N-containing semiconductors is defining a new frontier in spintronics. So far, we have had a good level of success when using such materials for optoelectronics devices, most recently in high-efficiency solar-cells and laser diodes. Now we are looking forward to continuing this work and to unite photonics and spintronics, using a common platform for light-based and spin-based quantum technology,” says Professor Mircea Guina, head of the research team at Tampere University in Finland.
Story Source:
Materials provided by Linköping University. Original written by Karin Söderlund Leifler. Note: Content may be edited for style and length. More

A decade ago, the discovery of quasiparticles called magnetic skyrmions provided important new clues into how microscopic spin textures will enable spintronics, a new class of electronics that use the orientation of an electron’s spin rather than its charge to encode data.
But although scientists have made big advances in this very young field, they still don’t fully understand how to design spintronics materials that would allow for ultrasmall, ultrafast, low-power devices. Skyrmions may seem promising, but scientists have long treated skyrmions as merely 2D objects. Recent studies, however, have suggested that 2D skyrmions could actually be the genesis of a 3D spin pattern called hopfions. But no one had been able to experimentally prove that magnetic hopfions exist on the nanoscale.
Now, a team of researchers co-led by Berkeley Lab has reported in Nature Communications the first demonstration and observation of 3D hopfions emerging from skyrmions at the nanoscale (billionths of a meter) in a magnetic system. The researchers say that their discovery heralds a major step forward in realizing high-density, high-speed, low-power, yet ultrastable magnetic memory devices that exploit the intrinsic power of electron spin.
“We not only proved that complex spin textures like 3D hopfions exist — We also demonstrated how to study and therefore harness them,” said co-senior author Peter Fischer, a senior scientist in Berkeley Lab’s Materials Sciences Division who is also an adjunct professor in physics at UC Santa Cruz. “To understand how hopfions really work, we have to know how to make them and study them. This work was possible only because we have these amazing tools at Berkeley Lab and our collaborative partnerships with scientists around the world,” he said.
According to previous studies, hopfions, unlike skyrmions, don’t drift when they move along a device and are therefore excellent candidates for data technologies. Furthermore, theory collaborators in the United Kingdom had predicted that hopfions could emerge from a multilayered 2D magnetic system.
The current study is the first to put those theories to test, Fischer said. More

Working safely is not only about processes, but context — understanding the work environment and circumstances, and being able to predict what other people will do next. A new system empowers robots with this level of context awareness, so they can work side-by-side with humans on assembly lines more efficiently and without unnecessary interruptions.
Instead of being able to only judge distance between itself and its human co-workers, the human-robot collaboration system can identify each worker it works with, as well as the person’s skeleton model, which is an abstract of body volume, says Hongyi Liu, a researcher at KTH Royal Institute of Technology. Using this information, the context-aware robot system can recognize the worker’s pose and even predict the next pose. These abilities provide the robot with a context to be aware of while interacting.
Liu says that the system operates with artificial intelligence that requires less computational power and smaller datasets than traditional machine learning methods. It relies instead on a form of machine learning called transfer learning — which reuses knowledge developed through training before being adapted into an operational model.
The research was published in the recent issue of Robotics and Computer-Integrated Manufacturing, and was co-authored by KTH Professor Lihui Wang.
Liu says that the technology is out ahead of today’s International Organization for Standards (ISO) requirements for collaborative robot safety, so implementation of the technology would require industrial action. But the context awareness offers better efficiency than the one-dimensional interaction workers now experience with robots, he says.
“Under the ISO standard and technical specification, when a human approaches a robot it slows down, and if he or she comes close enough it will stop. If the person moves away it resumes. That’s a pretty low level of context awareness,” he says.
“It jeopardizes efficiency. Production is slowed and humans cannot work closely to robots.”
Liu compares the context-aware robot system to a self-driving car that recognizes how long a stoplight has been red and anticipates moving again. Instead of braking or downshifting, it begins to adjust its speed by cruising toward the intersection, thereby sparing the brakes and transmission further wear.
Experiments with the system showed that with context, a robot can operate more safely and efficiently without slowing down production.
In one test performed with the system, a robot arm’s path was blocked unexpectedly by someone’s hand. But rather than stop, the robot adjusted — it predicted the future trajectory of the hand and the arm moved around the hand.
“This is safety not just from the technical point of view in avoiding collisions, but being able to recognize the context of the assembly line,” he says. “This gives an additional layer of safety.”
The research was an extension of the Symbiotic Human Robot Collaborative Assembly project, which was completed in 2019.
Story Source:
Materials provided by KTH, Royal Institute of Technology. Note: Content may be edited for style and length. More

School-based interventions that target students with, or at risk of, academic difficulties in kindergarten to grade 6 have positive effects on reading and mathematics, according to an article published in Campbell Systematic Reviews.
The review analyzed evidence from 205 studies, 186 of which were randomized controlled trials, to examine the effects of targeted school-based interventions on students’ performance on standardized tests in reading and math.
Peer-assisted instruction and small-group instruction by adults were among the most effective interventions. The authors noted that these have substantial potential to boost skills in students experiencing academic difficulties.
“It is exciting to see that there are many interventions with substantial impacts on math and reading skills, especially in these times when many students have not been able to attend school and the number of students who need extra help may be even larger than usual,” said lead author Jens Dietrichson, PhD, of VIVE, the Danish Center for Social Science Research. “It is also interesting that there is large variation: far from all interventions have positive effects, and there are substantial and robust differences between the types of interventions. Thus, schools can boost the skills of students with difficulties by implementing targeted interventions, but it matters greatly how they do it.”
Story Source:
Materials provided by Wiley. Note: Content may be edited for style and length. More

Imagine there are arrows that are lethal when fired on your enemies yet harmless if they fall on your friends. It’s easy to see how these would be an amazing advantage in warfare, if they were real. However, something just like these arrows does indeed exist, and they are used in warfare … just on a different scale.
These weapons are called tailocins, and the reality is almost stranger than fiction.
“Tailocins are extremely strong protein nanomachines made by bacteria,” explained Vivek Mutalik, a research scientist at Lawrence Berkeley National Laboratory (Berkeley Lab) who studies tailocins and phages, the bacteria-infecting viruses that tailocins appear to be remnants of. “They look like phages but they don’t have the capsid, which is the ‘head’ of the phage that contains the viral DNA and replication machinery. So, they’re like a spring-powered needle that goes and sits on the target cell, then appears to poke all the way through the cell membrane making a hole to the cytoplasm, so the cell loses its ions and contents and collapses.”
A wide variety of bacteria are capable of producing tailocins, and seem to do so under stress conditions. Because the tailocins are only lethal to specific strains — so specific, in fact, that they have earned the nickname “bacterial homing missiles” — tailocins appear to be a tool used by bacteria to compete with their rivals. Due to their similarity with phages, scientists believe that the tailocins are produced by DNA that was originally inserted into bacterial genomes during viral infections (viruses give their hosts instructions to make more of themselves), and over evolutionary time, the bacteria discarded the parts of the phage DNA that weren’t beneficial but kept the parts that could be co-opted for their own benefit.
But, unlike most abilities that are selected through evolution, tailocins do not save the individual. According to Mutalik, bacteria are killed if they produce tailocins, just as they would be if they were infected by true phage virus, because the pointed nanomachines erupt through the membrane to exit the producing cell much like replicated viral particles. But once released, the tailocins only target certain strains, sparing the other cells of the host lineage.
“They benefit kin but the individual is sacrificed, which is a type of altruistic behavior. But we don’t yet understand how this phenomenon happens in nature,” said Mutalik. Scientists also don’t know precisely how the stabbing needle plunger of the tailocin functions. More

Researchers have found a way to use chaos to help develop digital fingerprints for electronic devices that may be unique enough to foil even the most sophisticated hackers.
Just how unique are these fingerprints? The researchers believe it would take longer than the lifetime of the universe to test for every possible combination available.
“In our system, chaos is very, very good,” said Daniel Gauthier, senior author of the study and professor of physics at The Ohio State University.
The study was recently published online in the journal IEEE Access.
The researchers created a new version of an emerging technology called physically unclonable functions, or PUFs, that are built into computer chips.
Gauthier said these new PUFs could potentially be used to create secure ID cards, to track goods in supply chains and as part of authentication applications, where it is vital to know that you’re not communicating with an impostor. More

The founding chair of the Biomedical Engineering Department at the University of Houston is reporting a new deep neural network architecture that provides early diagnosis of systemic sclerosis (SSc), a rare autoimmune disease marked by hardened or fibrous skin and internal organs. The proposed network, implemented using a standard laptop computer (2.5 GHz Intel Core i7), can immediately differentiate between images of healthy skin and skin with systemic sclerosis.
“Our preliminary study, intended to show the efficacy of the proposed network architecture, holds promise in the characterization of SSc,” reports Metin Akay, John S. Dunn Endowed Chair Professor of biomedical engineering. The work is published in the IEEE Open Journal of Engineering in Medicine and Biology.
“We believe that the proposed network architecture could easily be implemented in a clinical setting, providing a simple, inexpensive and accurate screening tool for SSc.”
For patients with SSc, early diagnosis is critical, but often elusive. Several studies have shown that organ involvement could occur far earlier than expected in the early phase of the disease, but early diagnosis and determining the extent of disease progression pose significant challenge for physicians, even at expert centers, resulting in delays in therapy and management.
In artificial intelligence, deep learning organizes algorithms into layers (the artificial neural network) that can make its own intelligent decisions. To speed up the learning process, the new network was trained using the parameters of MobileNetV2, a mobile vision application, pre-trained on the ImageNet dataset with 1.4M images.
“By scanning the images, the network learns from the existing images and decides which new image is normal or in an early or late stage of disease,” said Akay.
Among several deep learning networks, Convolutional Neural Networks (CNNs) are most commonly used in engineering, medicine and biology, but their success in biomedical applications has been limited due to the size of the available training sets and networks.
To overcome these difficulties, Akay and partner Yasemin Akay combined the UNet, a modified CNN architecture, with added layers, and they developed a mobile training module. The results showed that the proposed deep learning architecture is superior and better than CNNs for classification of SSc images.
“After fine tuning, our results showed the proposed network reached 100% accuracy on the training image set, 96.8% accuracy on the validation image set, and 95.2% on the testing image set,” said Yasmin Akay, UH instructional associate professor of biomedical engineering.
The training time was less than five hours.
Joining Metin Akay and Yasemin Akay, the paper was co-authored by Yong Du, Cheryl Shersen, Ting Chen and Chandra Mohan, all of University of Houston; and Minghua Wu and Shervin Assassi of the University of Texas Health Science Center (UT Health).
Story Source:
Materials provided by University of Houston. Original written by Laurie Fickman. Note: Content may be edited for style and length. More