Computers Math

Nearly everything author Malcolm Gladwell said about how information spreads in his 2000 bestseller “The Tipping Point” is wrong, according to a recent study led by UCLA professor of sociology Gabriel Rossman.
“The main point of ‘The Tipping Point’ is if you want your idea to spread, you find the most popular person in the center of any given network and you sell them on your idea, and then they’ll sell the rest of the world on it,” Rossman said.
But Rossman’s latest study, recently published in Proceedings of the National Academy of Sciences, pokes holes in that widely accepted notion by showing how the presence of even just a bit of advertising or other mass communication — “top-down” information that comes from outside the network — effectively equalizes the influence of everyone across the network.
Rossman, together with co-author Jacob Fisher of Duke University and the University of Michigan, used a statistical programming language called R to build out network maps based on several different datasets. One set harnessed Twitter posts, along with retweets and mentions, over two weeks in 2011. Another used the Democratic National Committee email network from WikiLeaks’ 2016 data dump. Another used the emails of Enron executives subpoenaed in 2002. Six others were randomly generated.
These provided a network structure — a web of dots and lines showing how users in each network were connected to one another. Once those maps existed, Rossman and Fisher were able to see how quickly an idea might spread throughout the network if it started from the network’s single most important person or if it started from someone chosen at random.
They looked at that information spread in several ways, comparing via computer simulation how information moved throughout the networks when it came solely through word-of-mouth within a network (“bottom up”), when it came solely through external advertising or public information (“top down”) and when it came through varying bottom-up and top-down combinations.
What they discovered refutes Gladwell’s concept that network position is always paramount. They found that in instances where there is even a small amount of advertising — even when it is just a quarter of a percent as strong as word-of-mouth — there’s virtually no difference between the influence of the person at the center of a network and those further out on the string.
“It’s not that word-of-mouth doesn’t matter — it’s that nobody is particularly important for the word-of-mouth process,” Rossman said. “What we saw is that when advertising doesn’t exist, when advertising is exactly zero, it looks like whoever is Mr. Popular, whoever has the most central connections, really matters. And in that scenario, if you start with that person at the center of the network, like the leader of an organization or company, rather than the intern, then whatever you’re selling gets an uptick.”
But it takes only an incredibly weak amount of advertising to effectively neutralize the dominance of Mr. Popular, Rossman said. “Just a small amount changes the dynamic so that it practically doesn’t matter whether you start with Mr. Popular or the intern.”
Rossman is an expert on information spread in culture and mass media and is the author of “Climbing the Charts: What Radio Airplay Tells Us About the Diffusion of Innovation.”
The findings of his latest study, he notes, have wide-ranging implications, from selling products to a specific audience to understanding how to share information on vaccines with vulnerable communities.
“There’s a reasonably big body of literature that says you should find someone who appears to be structurally important to the network you’re trying to connect with,” he said. “We’re arguing that, if advertising exists, you can just pick somebody at random in the network and you’ll get just as good results as if you found the absolutely ideal person to start with.”

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Materials provided by University of California – Los Angeles. Original written by Jessica Wolf. Note: Content may be edited for style and length. More

A novel computer algorithm that could create a broadly reactive influenza vaccine for swine flu also offers a path toward a pan-influenza vaccine and possibly a pan-coronavirus vaccine as well, according to a new paper published in Nature Communications.
“This work takes us a step closer to a pan-swine flu virus vaccine,” said Bette Korber, a computational biologist at Los Alamos National Laboratory and a co-author on the paper. “The hope is to eventually be prepared with an effective and rapid response if another swine flu epidemic begins to spread in humans, but this swine flu vaccine could also be useful in a veterinary setting.” The immune responses to the vaccine showed very promising breadth against diverse viral variants. “The same basic principles may be applicable to developing a pan-coronavirus vaccine to enable a rapid vaccine response to future coronavirus cross-species jumps,” said Korber.
The algorithm, Epigraph, has already been used to predict therapeutic HIV vaccine candidates, and it has also shown promising potential as a pan-filovirus vaccine against highly diverse Ebola and Marburg viruses, protecting against disease when tested in an animal model.
Vaccination with the Epigraph-designed product led to the development of a strong cross-reactive antibody response in mice, the study showed. In swine, it induced strong cross-reactive antibody and T-cell responses. The research was conducted in close collaboration with researchers from the Nebraska Center for Virology at the University of Nebraska, St. Jude Children’s Research Hospital, and Los Alamos National Laboratory.
“We developed the Epigraph strategy for this kind of problem, and it can, in theory, be applied to many diverse pathogens,” said Korber, who created it in partnership with her husband, James Theiler, a Los Alamos Fellow. “The tool creates a cocktail of vaccine antigens designed to maximize efficacy across a highly diverse population.”
Since 2010, more than 460 swine-flu variant infections have been reported in humans in the United States. Pigs are susceptible to swine, avian, and human influenza viruses, making them the perfect “mixing vessel” for novel reassorted influenza viruses, the authors note. These novel reassorted viruses have significant pandemic potential if zoonosis (transfer from pigs to humans) occurs, as seen with 2009 H1N1 swine flu pandemic.

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Materials provided by DOE/Los Alamos National Laboratory. Note: Content may be edited for style and length. More

The era of widespread remote learning brought about by the COVID-19 pandemic requires online testing methods that effectively prevent cheating, especially in the form of collusion among students. With concerns about cheating on the rise across the country, a solution that also maintains student privacy is particularly valuable.
In research published today in npj Science of Learning, engineers from Rensselaer Polytechnic Institute demonstrate how a testing strategy they call “distanced online testing” can effectively reduce students’ ability to receive help from one another in order to score higher on a test taken at individual homes during social distancing.
“Often in remote online exams, students can talk over the phone or internet to discuss answers,” said Ge Wang, an endowed chair professor of biomedical engineering at Rensselaer and the corresponding author on this paper. “The key idea of our method is to minimize this chance via discrete optimization aided by knowledge of a student’s competencies.”
When a distanced online test is performed, students receive the same questions, but at varying times depending on their skill level. For instance, students of highest mastery levels receive each question after other groups of students have already answered those questions. This approach, Wang said, reduces the incentive for students to receive help from those who have more mastery of the material. In order to determine the order of each student’s questions, their competence levels are estimated using their grade point averages, SAT scores, or midterm scores, depending on what is available at a specific point in the semester.
According to statistical tests and post-exam surveys, this method reduced the points gained through collusion by orders of magnitude when compared to conventional exam methods. As an added benefit, Wang said, when students knew collusion would not be possible, they were more motivated to study class material. Wang and his collaborators hope to share this pedagogical innovation beyond the Rensselaer campus.
“We plan to develop a good platform so that others can easily use this method,” said Wang, a member of the Center for Biotechnology and Interdisciplinary Studies at Rensselaer.

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Materials provided by Rensselaer Polytechnic Institute. Note: Content may be edited for style and length. More

A joint research team co-led by City University of Hong Kong (CityU) has developed a new soft tactile sensor with skin-comparable characteristics. A robotic gripper with the sensor mounted at the fingertip could accomplish challenging tasks such as stably grasping fragile objects and threading a needle. Their research provided new insight into tactile sensor design and could contribute to various applications in the robotics field, such as smart prosthetics and human-robot interaction.
Dr Shen Yajing, Associate Professor at CityU’s Department of Biomedical Engineering (BME) was one of the co-leaders of the study. The findings have been recently published in the scientific journal Science Robotics, titled “Soft magnetic skin for super-resolution tactile sensing with force self-decoupling.”
Mimicking human skin characteristics
A main characteristic of human skin is its ability to sense the shear force, meaning the force that makes two objects slip or slide over each other when coming into contact. By sensing the magnitude, direction and the subtle change of shear force, our skin can act as feedback and allow us to adjust how we should hold an object stably with our hands and fingers or how tight we should grasp it.
To mimick this important feature of human skin, Dr Shen and Dr Pan Jia, a collaborator from the University of Hong Kong (HKU), have developed a novel, soft tactile sensor. The sensor is in a multi-layered structure like human skin and includes a flexible and specially magnetised film of about 0.5mm thin as the top layer. When an external force is exerted on it, it can detect the change of the magnetic field due to the film’s deformation. More importantly, it can “decouple,” or decompose, the external force automatically into two components — normal force (the force applied perpendicularly to the object) and shear force, providing the accurate measurement of these two forces respectively.
“It is important to decouple the external force because each force component has its own influence on the object. And it is necessary to know the accurate value of each force component to analyse or control the stationary or moving state of the object,” explained Yan Youcan, PhD student at BME and the first author of the paper.

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Deep learning enhanced accuracy
Moreover, the senor possesses another human skin-like characteristic — the tactile “super-resolution” that allows it to locate the stimuli’s position as accurate as possible. “We have developed an efficient tactile super-resolution algorithm using deep learning and achieved a 60-fold improvement of the localisation accuracy for contact position, which is the best among super-resolution methods reported so far,” said Dr Shen. Such an efficient tactile super-resolution algorithm can help improve the physical resolution of a tactile sensor array with the least number of sensing units, thus reducing the number of wirings and the time required for signal transmitting.
“To the best of our knowledge, this is the first tactile sensor that achieved self-decoupling and super-resolution abilities simultaneously,” he added.
Robotic hand with the new sensor completes challenging tasks
By mounting the sensor at the fingertip of a robotic gripper, the team showed that robots can accomplish challenging tasks. For example, the robotic gripper stably grasped fragile objects like an egg while an external force trying to drag it away, or threaded a needle via teleoperation. “The super-resolution of our sensor helps the robotic hand to adjust the contact position when it grasps an object. And the robotic arm can adjust force magnitude based on the force decoupling ability of the tactile sensor,” explained Dr Shen.
He added that the sensor can be easily extended to the form of sensor arrays or even continuous electronic skin that covers the whole body of the robot in the future. The sensitivity and measurement range of the sensor can be adjusted by changing the magnetisation direction of the top layer (magnetic film) of the sensor without changing the sensor’s thickness. This enabled the e-skin to have different sensitivity and measurement range in different parts, just like human skin.
Also, the sensor has a much shorter fabrication and calibration processes compared with other tactile sensors, facilitating the actual applications.
“This proposed sensor could be beneficial to various applications in the robotics field, such as adaptive grasping, dextrous manipulation, texture recognition, smart prosthetics and human-robot interaction. The advancement of soft artificial tactile sensors with skin-comparable characteristics can make domestic robots become part of our daily life,” concluded Dr Shen. More

During World War II, British intelligence agents planted false documents on a corpse to fool Nazi Germany into preparing for an assault on Greece. “Operation Mincemeat” was a success, and covered the actual Allied invasion of Sicily.
The “canary trap” technique in espionage spreads multiple versions of false documents to conceal a secret. Canary traps can be used to sniff out information leaks, or as in WWII, to create distractions that hide valuable information.
WE-FORGE, a new data protection system designed at Dartmouth’s Department of Computer Science, uses artificial intelligence to build on the canary trap concept. The system automatically creates false documents to protect intellectual property such as drug design and military technology.
“The system produces documents that are sufficiently similar to the original to be plausible, but sufficiently different to be incorrect,” said V.S. Subrahmanian, the Distinguished Professor in Cybersecurity, Technology, and Society, and director of the Institute for Security, Technology, and Society.
Cybersecurity experts already use canary traps, “honey files,” and foreign language translators to create decoys that deceive would-be attackers. WE-FORGE improves on these techniques by using natural language processing to automatically generate multiple fake files that are both believable and incorrect. The system also inserts an element of randomness to keep adversaries from easily identifying the real document.
WE-FORGE can be used to create numerous fake versions of any technical design document. When adversaries hack a system, they are faced with the daunting task of figuring out which of the many similar documents is real.

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“Using this technique, we force an adversary to waste time and effort in identifying the correct document. Even if they do, they may not have confidence that they got it right,” said Subrahmanian.
Creating the false technical documents is no less daunting. According to the research team, a single patent can include over 1,000 concepts with up to 20 possible replacements. WE-FORGE can end up considering millions of possibilities for all of the concepts that might need to be replaced in a single technical document.
“Malicious actors are stealing intellectual property right now and getting away with it for free,” said Subrahmanian. “This system raises the cost that thieves incur when stealing government or industry secrets.”
The WE-FORGE algorithm works by computing similarities between concepts in a document and then analyzing how relevant each word is to the document. The system then sorts concepts into “bins” and computes the feasible candidate for each group.
“WE-FORGE can also take input from the author of the original document,” said Dongkai Chen, a graduate student at Dartmouth who worked on the project. “The combination of human and machine ingenuity can increase costs on intellectual-property thieves even more.”
As part of the research, the team falsified a series of computer science and chemistry patents and asked a panel of knowledgeable subjects to decide which of the documents were real.

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According to the research, published in ACM Transactions on Management Information Systems, the WE-FORGE system was able to “consistently generate highly believable fake documents for each task.”
Unlike other tools, WE-FORGE specializes in falsifying technical information rather than just concealing simple information, such as passwords.
WE-FORGE improves on an earlier version of the system — known as FORGE — by removing the time-consuming need to create guides of concepts associated with specific technologies. WE-FORGE also ensures that there is greater diversity among fakes, and follows an improved technique for selecting concepts to replace and their replacements.
Almas Abdibayev, Deepti Poluru Guarini and Haipeng Chen all contributed to this research while with Dartmouth’s Department of Computer Science.

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Materials provided by Dartmouth College. Original written by David Hirsch. Note: Content may be edited for style and length. More

Robots that could take on basic healthcare tasks to support the work of doctors and nurses may be the way of the future. Who knows, maybe a medical robot can prescribe your medicine someday? That’s the idea behind 3D structural-sensing robots being developed and tested at Simon Fraser University by Woo Soo Kim, associate professor in the School of Mechatronic Systems Engineering.
“The recent pandemic demonstrates the need to minimize human-to-human interaction between healthcare workers and patients,” says Kim, who authored two recent papers on the subject — a perspective on the technology and a demonstration of a robots’ usefulness in healthcare. “There’s an opportunity for sensing robots to measure essential healthcare information on behalf of care providers in the future.”
Kim’s research team programmed two robots, a humanoid figure and a robotic arm, to measure human physiological signals, working from Kim’s Additive Manufacturing Lab located in SFU Surrey’s new engineering building. The robotic arm, created using Kim’s 3D printed origami structures, contains biomedical electrodes on the tip of each finger. When the hand touches a person, it detects physiological signals, including those from an electrocardiogram (which monitors heartbeat), respiration rate, electromyogram (monitoring electrical signals from muscle movements) and temperature.
The humanoid robot can also monitor oxygen levels, which could be used to monitor the condition of those who develop severe COVID-19. The data can be viewed in real-time on the robot’s monitor or sent directly to the healthcare provider.
Kim plans further development and testing of the robot together with healthcare collaborators. At this stage, the robots are capable of passively gathering patient information. But within the next decade, he says it’s conceivable that healthcare robots fitted with artificial intelligence could take a more active role, interacting with the patient, processing the data they have collected and even prescribing medication.
Further study will also need to involve determining acceptance levels for this type of technology among various age groups, from youth to seniors, in a hospital setting.

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Materials provided by Simon Fraser University. Note: Content may be edited for style and length. More

In a twist befitting the strange nature of quantum mechanics, physicists have discovered the Hall effect — a characteristic change in the way electricity is conducted in the presence of a magnetic field — in a nonmagnetic quantum material to which no magnetic field was applied.
The discovery by researchers from Rice University, Austria’s Vienna University of Technology (TU Wien), Switzerland’s Paul Scherrer Institute and Canada’s McMaster University is detailed in a paper in the Proceedings of the National Academy of Sciences. Of interest are both the origins of the effect, which is typically associated with magnetism, and its gigantic magnitude — more than 1,000 times larger than one might observe in simple semiconductors.
Rice study co-author Qimiao Si, a theoretical physicist who has investigated quantum materials for nearly three decades, said, “It’s really topology at work,” referring to the patterns of quantum entanglement that give rise the unorthodox state.
The material, an exotic semimetal of cerium, bismuth and palladium, was created and measured at TU Wien by Silke Bühler-Paschen, a longtime collaborator of Si’s. In late 2017, Si, Bühler-Paschen and colleagues discovered a new type of quantum material they dubbed a “Weyl-Kondo semimetal.” The research laid the groundwork for empirical investigations, but Si said the experiments were challenging, in part because it wasn’t clear “which physical quantity would pick up the effect.”
In April 2018, Bühler-Paschen and TU Wien graduate student Sami Dzsaber, the study’s first author, dropped by Si’s office while attending a workshop at the Rice Center for Quantum Materials (RCQM). When Si saw Dzsaber’s data, he was dubious.
“Upon seeing this, everybody’s first reaction is that it is not possible,” he said.

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To appreciate why, it helps to understand both the nature and the 1879 discovery of Edwin Hall, a doctoral student who found that applying a magnetic field at a 90-degree angle to conducting wire produced a voltage difference across the wire, in the direction perpendicular to both the current and the magnetic field. Physicists eventually discovered the source of the Hall effect: The magnetic field deflects the motion of passing electrons, pulling them toward one side of the wire. The Hall effect is a standard tool in physics labs, and devices that make use of it are found in products as diverse as rocket engines and paintball guns. Studies related to the quantum nature of the Hall effect captured Nobel Prizes in 1985 and 1998.
Dzsaber’s experimental data clearly showed a characteristic Hall signal, even though no magnetic field was applied.
“If you don’t apply a magnetic field, the electron is not supposed to bend,” Si said. “So, how could you ever get a voltage drop along the perpendicular direction? That’s why everyone didn’t believe this at first.”
Experiments at the Paul Scherrer Institute ruled out the presence of a tiny magnetic field that could only be detected on a microscopic scale. So the question remained: What caused the effect?
“In the end, all of us had to accept that this was connected to topology,” Si said.

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In topological materials, patterns of quantum entanglement produce “protected” states, universal features that cannot be erased. The immutable nature of topological states is of increasing interest for quantum computing. Weyl semimetals, which manifest a quasiparticle known as the Weyl fermion, are topological materials.
So are the Weyl-Kondo semimetals Si, Bühler-Paschen and colleagues discovered in 2018. Those feature both Weyl fermions and the Kondo effect, an interaction between the magnetic moments of electrons attached to atoms inside the metal and the spins of passing conduction electrons.
“The Kondo effect is the quintessential form of strong correlations in quantum materials,” Si said in reference to the correlated, collective behavior of billions upon billions of quantum entangled particles. “It qualifies the Weyl-Kondo semimetal as one of the rare examples of a topological state that’s driven by strong correlations.
“Topology is a defining characteristic of the Weyl-Kondo semimetal, and the discovery of this spontaneous giant Hall effect is really the first detection of topology that’s associated with this kind of Weyl fermion,” Si said.
Experiments showed that the effect arose at the characteristic temperature associated with the Kondo effect, indicating the two are likely connected, Si said.
“This kind of spontaneous Hall effect was also observed in contemporaneous experiments in some layered semiconductors, but our effect is more than 1,000 times larger,” he said. “We were able to show that the observed giant effect is, in fact, natural when the topological state develops out of strong correlations.”
Si said the new observation is likely “a tip of the iceberg” of extreme responses that result from the interplay between strong correlations and topology.
He said the size of the topologically generated Hall effect is also likely to spur investigations into potential uses of the technology for quantum computation.
“This large magnitude, and its robust, bulk nature presents intriguing possibilities for exploitation in topological quantum devices,” Si said.
Si is the Harry C. and Olga K. Wiess Professor in Rice’s Department of Physics and Astronomy and director of RCQM. Bühler-Paschen is a professor at TU Wien’s Institute for Solid State Physics. More

A Mason Engineering researcher has discovered that artificial microswimmers accumulate where their speed is minimized, an idea that could have implications for improving the efficacy of targeted cancer therapy.
Jeff Moran, an assistant professor of mechanical engineering in the Volgenau School of Engineering, and colleagues from the University of Washington in Seattle studied self-propelled half-platinum/half-gold rods that “swim” in water using hydrogen peroxide as a fuel. The more peroxide there is, the faster the swimming; without peroxide in pure water, the rods don’t swim.
In this work, they set out to understand what happens when these artificial microswimmers are placed in a fluid reservoir containing a gradient of hydrogen peroxide–lots of peroxide on one side, not much on the other side.
They found that, predictably, the microswimmers swam faster in regions with high peroxide concentration, says Moran, whose research was published in the new issue of Scientific Reports.
As others had observed, the direction of swimming varied randomly in time as the swimmers explored their surroundings. In contrast, in the low-concentration regions, the rods slowed down and accumulated in these regions over the course of a few minutes.
The results suggest a simple strategy to make microswimmers passively accumulate in specific regions, an idea that might have useful, practical applications, he says.

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Swimming at the microscopic scale is a ubiquitous phenomenon in biology, Moran says. “Lots of cells and microorganisms, such as bacteria, can autonomously swim toward higher or lower concentrations of chemicals that benefit or harm the cell, respectively.”
This behavior is called chemotaxis, and it’s both common and important, he says. “For example, your immune cells use chemotaxis to detect and swim toward sites of injury, so they can initiate tissue repair.”
Moran and colleagues, like others in the field, have long been curious whether artificial microswimmers can mimic cells by performing chemotaxis, continuously swimming toward higher chemical concentrations. Some had claimed that the platinum/gold rods, in particular, could swim autonomously toward peroxide-rich regions.
“We were skeptical of these claims since the rods aren’t alive, and therefore they don’t have the sensing and response capabilities that are necessary for cells to execute this behavior,” he says.
“Instead, we found the opposite: the rods built up in the lower concentration regions. This is the opposite of what one would expect from chemotaxis,” Moran says.

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The researchers conducted computer simulations that predicted this and validated them with experiments, he says.
“We propose a simple explanation for this behavior: Wherever they are, the rods move in randomly varying directions, exploring their surroundings. When they get to a low-fuel region, they can’t explore as vigorously. In a sense, they get trapped in their comfort zones,” Moran says.
“Conversely, in the high-peroxide regions, they move at higher speeds and, because their direction is constantly changing, escape from these regions more often. Over time, the net result is that rods accumulate in low-concentration regions,” he says. “They don’t have any intelligence. They end up where their mobility is the lowest.”
Moran says this research is promising from a technical standpoint because it suggests a new strategy to make chemicals accumulate in a highly acidic area.
“Due to their abnormal metabolic processes, cancer cells cause their immediate surroundings to become acidic. These are the cells that need the most drugs because the acidic environment is known to promote metastasis and confer resistance to drugs. Thus, the cells in these regions are a major target of many cancer therapies.”
Moran and colleagues are now designing microswimmers that move slowly in acidic regions and fast in neutral or basic regions. Through the mechanism they discovered here, they hypothesize that acid-dependent swimmers will accumulate and release their cargo preferentially where their speeds are minimized, namely the most acidic and hypoxic regions of the tumor, where the most problematic cells reside.
There is much more research to be conducted, but “these rods may have the ability to deliver chemotherapy drugs to the cancer cells that need them the most,” Moran says.
“To be clear, our study doesn’t prove that chemotaxis is impossible in artificial microswimmers, period; just that these particular microswimmers don’t undergo chemotaxis.
“Instead, we’ve identified an elegantly simple method of causing unguided microswimmers to accumulate and deliver drugs to the most problematic cancer cells, which could have implications for the treatment of many cancers, as well as other diseases like fibrosis. We’re excited to see where this goes.”
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